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How can model comparison help improving species distribution models?

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Emmanuel Stephan Gritti

Full Text Available Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs. However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagussylvatica L., Quercusrobur L. and Pinussylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.
Improvement for Amelioration Inventory Model with Weibull Distribution

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Han-Wen Tuan

2017-01-01

Full Text Available Most inventory models dealt with deteriorated items. On the contrary, just a few papers considered inventory systems under amelioration environment. We study an amelioration inventory model with Weibull distribution. However, there are some questionable results in the amelioration paper. We will first point out those questionable results in the previous paper that did not derive the optimal solution and then provide some improvements. We will provide a rigorous analytical work for different cases dependent on the size of the shape parameter. We present a detailed numerical example for different ranges of the sharp parameter to illustrate that our solution method attains the optimal solution. We developed a new amelioration model and then provided a detailed analyzed procedure to find the optimal solution. Our findings will help researchers develop their new inventory models.
Improving permafrost distribution modelling using feature selection algorithms

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Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

2016-04-01

The availability of an increasing number of spatial data on the occurrence of mountain permafrost allows the employment of machine learning (ML) classification algorithms for modelling the distribution of the phenomenon. One of the major problems when dealing with high-dimensional dataset is the number of input features (variables) involved. Application of ML classification algorithms to this large number of variables leads to the risk of overfitting, with the consequence of a poor generalization/prediction. For this reason, applying feature selection (FS) techniques helps simplifying the amount of factors required and improves the knowledge on adopted features and their relation with the studied phenomenon. Moreover, taking away irrelevant or redundant variables from the dataset effectively improves the quality of the ML prediction. This research deals with a comparative analysis of permafrost distribution models supported by FS variable importance assessment. The input dataset (dimension = 20-25, 10 m spatial resolution) was constructed using landcover maps, climate data and DEM derived variables (altitude, aspect, slope, terrain curvature, solar radiation, etc.). It was completed with permafrost evidences (geophysical and thermal data and rock glacier inventories) that serve as training permafrost data. Used FS algorithms informed about variables that appeared less statistically important for permafrost presence/absence. Three different algorithms were compared: Information Gain (IG), Correlation-based Feature Selection (CFS) and Random Forest (RF). IG is a filter technique that evaluates the worth of a predictor by measuring the information gain with respect to the permafrost presence/absence. Conversely, CFS is a wrapper technique that evaluates the worth of a subset of predictors by considering the individual predictive ability of each variable along with the degree of redundancy between them. Finally, RF is a ML algorithm that performs FS as part of its
Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

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Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

2015-12-01

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium
Landscape and flow metrics affecting the distribution of a federally-threatened fish: Improving management, model fit, and model transferability

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Worthington, Thomas A.; Zhang, T.; Logue, Daniel R.; Mittelstet, Aaron R.; Brewer, Shannon K.

2016-01-01

Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi, constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the
A GIS Tool for evaluating and improving NEXRAD and its application in distributed hydrologic modeling

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Zhang, X.; Srinivasan, R.

2008-12-01

In this study, a user friendly GIS tool was developed for evaluating and improving NEXRAD using raingauge data. This GIS tool can automatically read in raingauge and NEXRAD data, evaluate the accuracy of NEXRAD for each time unit, implement several geostatistical methods to improve the accuracy of NEXRAD through raingauge data, and output spatial precipitation map for distributed hydrologic model. The geostatistical methods incorporated in this tool include Simple Kriging with varying local means, Kriging with External Drift, Regression Kriging, Co-Kriging, and a new geostatistical method that was newly developed by Li et al. (2008). This tool was applied in two test watersheds at hourly and daily temporal scale. The preliminary cross-validation results show that incorporating raingauge data to calibrate NEXRAD can pronouncedly change the spatial pattern of NEXRAD and improve its accuracy. Using different geostatistical methods, the GIS tool was applied to produce long term precipitation input for a distributed hydrologic model - Soil and Water Assessment Tool (SWAT). Animated video was generated to vividly illustrate the effect of using different precipitation input data on distributed hydrologic modeling. Currently, this GIS tool is developed as an extension of SWAT, which is used as water quantity and quality modeling tool by USDA and EPA. The flexible module based design of this tool also makes it easy to be adapted for other hydrologic models for hydrological modeling and water resources management.
Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

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Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

2016-01-01

Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of
Improved CFD Model to Predict Flow and Temperature Distributions in a Blast Furnace Hearth

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Komiyama, Keisuke M.; Guo, Bao-Yu; Zughbi, Habib; Zulli, Paul; Yu, Ai-Bing

2014-10-01

The campaign life of a blast furnace is limited by the erosion of hearth refractories. Flow and temperature distributions of the liquid iron have a significant influence on the erosion mechanism. In this work, an improved three-dimensional computational fluid dynamics model is developed to simulate the flow and heat transfer phenomena in the hearth of BlueScope's Port Kembla No. 5 Blast Furnace. Model improvements feature more justified input parameters in turbulence modeling, buoyancy modeling, wall boundary conditions, material properties, and modeling of the solidification of iron. The model is validated by comparing the calculated temperatures with the thermocouple data available, where agreements are established within ±3 pct. The flow distribution in the hearth is discussed for intact and eroded hearth profiles, for sitting and floating coke bed states. It is shown that natural convection affects the flow in several ways: for example, the formation of (a) stagnant zones preventing hearth bottom from eroding or (b) the downward jetting of molten liquid promoting side wall erosion, or (c) at times, a vortex-like peripheral flow, promoting the "elephant foot" type erosion. A significant influence of coke bed permeability on the macroscopic flow pattern and the refractory temperature is observed.
Using Environmental DNA to Improve Species Distribution Models for Freshwater Invaders

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Teja P. Muha

2017-12-01

Full Text Available Species Distribution Models (SDMs have been reported as a useful tool for the risk assessment and modeling of the pathways of dispersal of freshwater invasive alien species (IAS. Environmental DNA (eDNA is a novel tool that can help detect IAS at their early stage of introduction and additionally improve the data available for a more efficient management. SDMs rely on presence and absence of the species in the study area to infer the predictors affecting species distributions. Presence is verified once a species is detected, but confirmation of absence can be problematic because this depends both on the detectability of the species and the sampling strategy. eDNA is a technique that presents higher detectability and accuracy in comparison to conventional sampling techniques, and can effectively differentiate between presence or absence of specific species or entire communities by using a barcoding or metabarcoding approach. However, a number of potential bias can be introduced during (i sampling, (ii amplification, (iii sequencing, or (iv through the usage of bioinformatics pipelines. Therefore, it is important to report and conduct the field and laboratory procedures in a consistent way, by (i introducing eDNA independent observations, (ii amplifying and sequencing control samples, (iii achieving quality sequence reads by appropriate clean-up steps, (iv controlling primer amplification preferences, (v introducing PCR-free sequence capturing, (vi estimating primer detection capabilities through controlled experiments and/or (vii post-hoc introduction of “site occupancy-detection models.” With eDNA methodology becoming increasingly routine, its use is strongly recommended to retrieve species distributional data for SDMs.
Regional climate model downscaling may improve the prediction of alien plant species distributions

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Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

2014-12-01

Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.
Improved Mathematical Models for Particle-Size Distribution Data

African Journals Online (AJOL)

BirukEdimon

School of Civil & Environmental Engineering, Addis Ababa Institute of Technology,. 3. Murray Rix ... two improved mathematical models to describe ... demand further improvement to handle the PSD ... statistics and the range of the optimized.
Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

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Christian Vögeli

2016-12-01

Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.
Distributed Generation Market Demand Model (dGen): Documentation

Energy Technology Data Exchange (ETDEWEB)

Sigrin, Benjamin [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Preus, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States); Baring-Gould, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Margolis, Robert [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-02-01

The Distributed Generation Market Demand model (dGen) is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States. The new model builds off, extends, and replaces NREL's SolarDS model (Denholm et al. 2009a), which simulates the market penetration of distributed PV only. Unlike the SolarDS model, dGen can model various DER technologies under one platform--it currently can simulate the adoption of distributed solar (the dSolar module) and distributed wind (the dWind module) and link with the ReEDS capacity expansion model (Appendix C). The underlying algorithms and datasets in dGen, which improve the representation of customer decision making as well as the spatial resolution of analyses (Figure ES-1), also are improvements over SolarDS.
A distribution benefits model for improved information on worldwide crop production. Volume 1: Model structure and application to wheat

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Andrews, J.

1976-01-01

The improved model is suitable for the study of benefits of worldwide information on a variety of crops. Application to the previously studied case of worldwide wheat production shows that about $108 million per year of distribution benefits to the United States would be achieved by a satellite-based wheat information system meeting the goals of LACIE. The model also indicates that improved information alone will not change world stock levels unless production itself is stabilized. The United States benefits mentioned above are associated with the reduction of price fluctuations within the year and the more effective use of international trade to balance supply and demand. Price fluctuations from year to year would be reduced only if production variability were itself reduced.
Improvement, calibration and validation of a distributed hydrological model over France

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P. Quintana Seguí

2009-02-01

Full Text Available The hydrometeorological model SAFRAN-ISBA-MODCOU (SIM computes water and energy budgets on the land surface and riverflows and the level of several aquifers at the scale of France. SIM is composed of a meteorological analysis system (SAFRAN, a land surface model (ISBA, and a hydrogeological model (MODCOU. In this study, an exponential profile of hydraulic conductivity at saturation is introduced to the model and its impact analysed. It is also studied how calibration modifies the performance of the model. A very simple method of calibration is implemented and applied to the parameters of hydraulic conductivity and subgrid runoff. The study shows that a better description of the hydraulic conductivity of the soil is important to simulate more realistic discharges. It also shows that the calibrated model is more robust than the original SIM. In fact, the calibration mainly affects the processes related to the dynamics of the flow (drainage and runoff, and the rest of relevant processes (like evaporation remain stable. It is also proven that it is only worth introducing the new empirical parameterization of hydraulic conductivity if it is accompanied by a calibration of its parameters, otherwise the simulations can be degraded. In conclusion, it is shown that the new parameterization is necessary to obtain good simulations. Calibration is a tool that must be used to improve the performance of distributed models like SIM that have some empirical parameters.
Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

International Nuclear Information System (INIS)

Han, Jing-Cheng; Huang, Guohe; Huang, Yuefei; Zhang, Hua; Li, Zhong; Chen, Qiuwen

2015-01-01

Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A
Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

Energy Technology Data Exchange (ETDEWEB)

Han, Jing-Cheng [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Huang, Guohe, E-mail: huang@iseis.org [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, Yuefei [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Zhang, Hua [College of Science and Engineering, Texas A& M University — Corpus Christi, Corpus Christi, TX 78412-5797 (United States); Li, Zhong [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Chen, Qiuwen [Center for Eco-Environmental Research, Nanjing Hydraulics Research Institute, Nanjing 210029 (China)

2015-08-15

Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A
A supply chain model to improve the beef quality distribution using investment analysis: A case study

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Lupita, Alessandra; Rangkuti, Sabrina Heriza; Sutopo, Wahyudi; Hisjam, Muh.

2017-11-01

There are significant differences related to the quality and price of the beef commodity in traditional market and modern market in Indonesia. Those are caused by very different treatments of the commodity. The different treatments are in the slaughter lines, the transportation from the abattoir to the outlet, the display system, and the control system. If the problem is not solved by the Government, the gap will result a great loss of the consumer regarding to the quality and sustainability of traditional traders business because of the declining interest in purchasing beef in the traditional markets. This article aims to improve the quality of beef in traditional markets. This study proposed A Supply Chain Model that involves the schemes of investment and government incentive for improving the distribution system. The supply chain model is can be formulated using the Mix Integer Linear Programming (MILP) and solved using the IBM®ILOG®CPLEX software. The results show that the proposed model can be used to determine the priority of programs for improving the quality and sustainability business of traditional beef merchants. By using the models, The Government can make a decision to consider incentives for improving the condition.
Improved Testing of Distributed Lag Model in Presence of ...

African Journals Online (AJOL)

The finite distributed lag models (DLM) are often used in econometrics and statistics. Application of the ordinary least square (OLS) directly on the DLM for estimation may have serious problems. To overcome these problems, some alternative estimation procedures are available in the literature. One popular method to ...
Improved high-frequency equivalent circuit model based on distributed effects for SiGe HBTs with CBE layout

International Nuclear Information System (INIS)

Sun Ya-Bin; Li Xiao-Jin; Zhang Jin-Zhong; Shi Yan-Ling

2017-01-01

In this paper, we present an improved high-frequency equivalent circuit for SiGe heterojunction bipolar transistors (HBTs) with a CBE layout, where we consider the distributed effects along the base region. The actual device structure is divided into three parts: a link base region under a spacer oxide, an intrinsic transistor region under the emitter window, and an extrinsic base region. Each region is considered as a two-port network, and is composed of a distributed resistance and capacitance. We solve the admittance parameters by solving the transmission-line equation. Then, we obtain the small-signal equivalent circuit depending on the reasonable approximations. Unlike previous compact models, in our proposed model, we introduce an additional internal base node, and the intrinsic base resistance is shifted into this internal base node, which can theoretically explain the anomalous change in the intrinsic bias-dependent collector resistance in the conventional compact model. (paper)

Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling.

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El-Gabbas, Ahmed; Dormann, Carsten F

2018-02-01

Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data
Improving flow distribution in influent channels using computational fluid dynamics.

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Park, No-Suk; Yoon, Sukmin; Jeong, Woochang; Lee, Seungjae

2016-10-01

Although the flow distribution in an influent channel where the inflow is split into each treatment process in a wastewater treatment plant greatly affects the efficiency of the process, and a weir is the typical structure for the flow distribution, to the authors' knowledge, there is a paucity of research on the flow distribution in an open channel with a weir. In this study, the influent channel of a real-scale wastewater treatment plant was used, installing a suppressed rectangular weir that has a horizontal crest to cross the full channel width. The flow distribution in the influent channel was analyzed using a validated computational fluid dynamics model to investigate (1) the comparison of single-phase and two-phase simulation, (2) the improved procedure of the prototype channel, and (3) the effect of the inflow rate on flow distribution. The results show that two-phase simulation is more reliable due to the description of the free-surface fluctuations. It should first be considered for improving flow distribution to prevent a short-circuit flow, and the difference in the kinetic energy with the inflow rate makes flow distribution trends different. The authors believe that this case study is helpful for improving flow distribution in an influent channel.
Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

Science.gov (United States)

Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

2018-02-01

Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.
A phenomenological retention tank model using settling velocity distributions.

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Maruejouls, T; Vanrolleghem, P A; Pelletier, G; Lessard, P

2012-12-15

Many authors have observed the influence of the settling velocity distribution on the sedimentation process in retention tanks. However, the pollutants' behaviour in such tanks is not well characterized, especially with respect to their settling velocity distribution. This paper presents a phenomenological modelling study dealing with the way by which the settling velocity distribution of particles in combined sewage changes between entering and leaving an off-line retention tank. The work starts from a previously published model (Lessard and Beck, 1991) which is first implemented in a wastewater management modelling software, to be then tested with full-scale field data for the first time. Next, its performance is improved by integrating the particle settling velocity distribution and adding a description of the resuspension due to pumping for emptying the tank. Finally, the potential of the improved model is demonstrated by comparing the results for one more rain event. Copyright © 2011 Elsevier Ltd. All rights reserved.
Incorporating uncertainty in predictive species distribution modelling.

Science.gov (United States)

Beale, Colin M; Lennon, Jack J

2012-01-19

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.
Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

Science.gov (United States)

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946
Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

Science.gov (United States)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

2018-02-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex
Model improvements to simulate charging in SEM

Science.gov (United States)

Arat, K. T.; Klimpel, T.; Hagen, C. W.

2018-03-01

Charging of insulators is a complex phenomenon to simulate since the accuracy of the simulations is very sensitive to the interaction of electrons with matter and electric fields. In this study, we report model improvements for a previously developed Monte-Carlo simulator to more accurately simulate samples that charge. The improvements include both modelling of low energy electron scattering and charging of insulators. The new first-principle scattering models provide a more realistic charge distribution cloud in the material, and a better match between non-charging simulations and experimental results. Improvements on charging models mainly focus on redistribution of the charge carriers in the material with an induced conductivity (EBIC) and a breakdown model, leading to a smoother distribution of the charges. Combined with a more accurate tracing of low energy electrons in the electric field, we managed to reproduce the dynamically changing charging contrast due to an induced positive surface potential.
Improving the modelling of redshift-space distortions - I. A bivariate Gaussian description for the galaxy pairwise velocity distributions

Science.gov (United States)

Bianchi, Davide; Chiesa, Matteo; Guzzo, Luigi

2015-01-01

As a step towards a more accurate modelling of redshift-space distortions (RSD) in galaxy surveys, we develop a general description of the probability distribution function of galaxy pairwise velocities within the framework of the so-called streaming model. For a given galaxy separation r, such function can be described as a superposition of virtually infinite local distributions. We characterize these in terms of their moments and then consider the specific case in which they are Gaussian functions, each with its own mean μ and dispersion σ. Based on physical considerations, we make the further crucial assumption that these two parameters are in turn distributed according to a bivariate Gaussian, with its own mean and covariance matrix. Tests using numerical simulations explicitly show that with this compact description one can correctly model redshift-space distortions on all scales, fully capturing the overall linear and non-linear dynamics of the galaxy flow at different separations. In particular, we naturally obtain Gaussian/exponential, skewed/unskewed distribution functions, depending on separation as observed in simulations and data. Also, the recently proposed single-Gaussian description of RSD is included in this model as a limiting case, when the bivariate Gaussian is collapsed to a two-dimensional Dirac delta function. We also show how this description naturally allows for the Taylor expansion of 1 + ξS(s) around 1 + ξR(r), which leads to the Kaiser linear formula when truncated to second order, explicating its connection with the moments of the velocity distribution functions. More work is needed, but these results indicate a very promising path to make definitive progress in our programme to improve RSD estimators.
Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

Science.gov (United States)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.
Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

Science.gov (United States)

Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...
Consideration of time-evolving capacity distributions and improved degradation models for seismic fragility assessment of aging highway bridges

International Nuclear Information System (INIS)

Ghosh, Jayadipta; Sood, Piyush

2016-01-01

This paper presents a methodology to develop seismic fragility curves for deteriorating highway bridges by uniquely accounting for realistic pitting corrosion deterioration and time-dependent capacity distributions for reinforced concrete columns under chloride attacks. The proposed framework offers distinct improvements over state-of-the-art procedures for fragility assessment of degrading bridges which typically assume simplified uniform corrosion deterioration model and pristine limit state capacities. Depending on the time in service life and deterioration mechanism, this study finds that capacity limit states for deteriorating bridge columns follow either lognormal distribution or generalized extreme value distributions (particularly for pitting corrosion). Impact of column degradation mechanism on seismic response and fragility of bridge components and system is assessed using nonlinear time history analysis of three-dimensional finite element bridge models reflecting the uncertainties across structural modeling parameters, deterioration parameters and ground motion. Comparisons are drawn between the proposed methodology and traditional approaches to develop aging bridge fragility curves. Results indicate considerable underestimations of system level fragility across different damage states using the traditional approach compared to the proposed realistic pitting model for chloride induced corrosion. Time-dependent predictive functions are provided to interpolate logistic regression coefficients for continuous seismic reliability evaluation along the service life with reasonable accuracy. - Highlights: • Realistic modeling of chloride induced corrosion deterioration in the form of pitting. • Time-evolving capacity distribution for aging bridge columns under chloride attacks. • Time-dependent seismic fragility estimation of highway bridges at component and system level. • Mathematical functions for continuous tracking of seismic fragility along service
Estimating Predictive Variance for Statistical Gas Distribution Modelling

International Nuclear Information System (INIS)

Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

2009-01-01

Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.
Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

Directory of Open Access Journals (Sweden)

M. C. Demirel

2018-02-01

Full Text Available Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the
Spatial distribution of emissions to air - the SPREAD model

Energy Technology Data Exchange (ETDEWEB)

Plejdrup, M S; Gyldenkaerne, S

2011-04-15

The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Elasto-dynamic analysis of a gear pump-Part IV: Improvement in the pressure distribution modelling

Science.gov (United States)

Mucchi, E.; Dalpiaz, G.; Fernàndez del Rincòn, A.

2015-01-01

This work concerns external gear pumps for automotive applications, which operate at high speed and low pressure. In previous works of the authors (Part I and II, [1,2]), a non-linear lumped-parameter kineto-elastodynamic model for the prediction of the dynamic behaviour of external gear pumps was presented. It takes into account the most important phenomena involved in the operation of this kind of machine. The two main sources of noise and vibration are considered: pressure pulsation and gear meshing. The model has been used in order to foresee the influence of working conditions and design modifications on vibration generation. The model experimental validation is a difficult task. Thus, Part III proposes a novel methodology for the validation carried out by the comparison of simulations and experimental results concerning forces and moments: it deals with the external and inertial components acting on the gears, estimated by the model, and the reactions and inertial components on the pump casing and the test plate, obtained by measurements. The validation is carried out by comparing the level of the time synchronous average in the time domain and the waterfall maps in the frequency domain, with particular attention to identify system resonances. The validation results are satisfactory global, but discrepancies are still present. Moreover, the assessed model has been properly modified for the application to a new virtual pump prototype with helical gears in order to foresee gear accelerations and dynamic forces. Part IV is focused on improvements in the modelling and analysis of the phenomena bound to the pressure distribution around the gears in order to achieve results closer to the measured values. As a matter of fact, the simulation results have shown that a variable meshing stiffness has a notable contribution on the dynamic behaviour of the pump but this is not as important as the pressure phenomena. As a consequence, the original model was modified with
Modeling soil water content for vegetation modeling improvement

Science.gov (United States)

Cianfrani, Carmen; Buri, Aline; Zingg, Barbara; Vittoz, Pascal; Verrecchia, Eric; Guisan, Antoine

2016-04-01

Soil water content (SWC) is known to be important for plants as it affects the physiological processes regulating plant growth. Therefore, SWC controls plant distribution over the Earth surface, ranging from deserts and grassland to rain forests. Unfortunately, only a few data on SWC are available as its measurement is very time consuming and costly and needs specific laboratory tools. The scarcity of SWC measurements in geographic space makes it difficult to model and spatially project SWC over larger areas. In particular, it prevents its inclusion in plant species distribution model (SDMs) as predictor. The aims of this study were, first, to test a new methodology allowing problems of the scarcity of SWC measurements to be overpassed and second, to model and spatially project SWC in order to improve plant SDMs with the inclusion of SWC parameter. The study was developed in four steps. First, SWC was modeled by measuring it at 10 different pressures (expressed in pF and ranging from pF=0 to pF=4.2). The different pF represent different degrees of soil water availability for plants. An ensemble of bivariate models was built to overpass the problem of having only a few SWC measurements (n = 24) but several predictors to include in the model. Soil texture (clay, silt, sand), organic matter (OM), topographic variables (elevation, aspect, convexity), climatic variables (precipitation) and hydrological variables (river distance, NDWI) were used as predictors. Weighted ensemble models were built using only bivariate models with adjusted-R2 > 0.5 for each SWC at different pF. The second step consisted in running plant SDMs including modeled SWC jointly with the conventional topo-climatic variable used for plant SDMs. Third, SDMs were only run using the conventional topo-climatic variables. Finally, comparing the models obtained in the second and third steps allowed assessing the additional predictive power of SWC in plant SDMs. SWC ensemble models remained very good, with
An Improved Harmony Search Algorithm for Power Distribution Network Planning

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Distribution network planning because of involving many variables and constraints is a multiobjective, discrete, nonlinear, and large-scale optimization problem. Harmony search (HS algorithm is a metaheuristic algorithm inspired by the improvisation process of music players. HS algorithm has several impressive advantages, such as easy implementation, less adjustable parameters, and quick convergence. But HS algorithm still has some defects such as premature convergence and slow convergence speed. According to the defects of the standard algorithm and characteristics of distribution network planning, an improved harmony search (IHS algorithm is proposed in this paper. We set up a mathematical model of distribution network structure planning, whose optimal objective function is to get the minimum annual cost and constraint conditions are overload and radial network. IHS algorithm is applied to solve the complex optimization mathematical model. The empirical results strongly indicate that IHS algorithm can effectively provide better results for solving the distribution network planning problem compared to other optimization algorithms.
Spatial distribution of emissions to air - the SPREAD model

Energy Technology Data Exchange (ETDEWEB)

Plejdrup, M.S.; Gyldenkaerne, S.

2011-04-15

The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)
Automatic generation of 3D statistical shape models with optimal landmark distributions.

Science.gov (United States)

Heimann, T; Wolf, I; Meinzer, H-P

2007-01-01

To point out the problem of non-uniform landmark placement in statistical shape modeling, to present an improved method for generating landmarks in the 3D case and to propose an unbiased evaluation metric to determine model quality. Our approach minimizes a cost function based on the minimum description length (MDL) of the shape model to optimize landmark correspondences over the training set. In addition to the standard technique, we employ an extended remeshing method to change the landmark distribution without losing correspondences, thus ensuring a uniform distribution over all training samples. To break the dependency of the established evaluation measures generalization and specificity from the landmark distribution, we change the internal metric from landmark distance to volumetric overlap. Redistributing landmarks to an equally spaced distribution during the model construction phase improves the quality of the resulting models significantly if the shapes feature prominent bulges or other complex geometry. The distribution of landmarks on the training shapes is -- beyond the correspondence issue -- a crucial point in model construction.

Hierarchical species distribution models

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.
Improved dust representation in the Community Atmosphere Model

Science.gov (United States)

Albani, S.; Mahowald, N. M.; Perry, A. T.; Scanza, R. A.; Zender, C. S.; Heavens, N. G.; Maggi, V.; Kok, J. F.; Otto-Bliesner, B. L.

2014-09-01

Aerosol-climate interactions constitute one of the major sources of uncertainty in assessing changes in aerosol forcing in the anthropocene as well as understanding glacial-interglacial cycles. Here we focus on improving the representation of mineral dust in the Community Atmosphere Model and assessing the impacts of the improvements in terms of direct effects on the radiative balance of the atmosphere. We simulated the dust cycle using different parameterization sets for dust emission, size distribution, and optical properties. Comparing the results of these simulations with observations of concentration, deposition, and aerosol optical depth allows us to refine the representation of the dust cycle and its climate impacts. We propose a tuning method for dust parameterizations to allow the dust module to work across the wide variety of parameter settings which can be used within the Community Atmosphere Model. Our results include a better representation of the dust cycle, most notably for the improved size distribution. The estimated net top of atmosphere direct dust radiative forcing is -0.23 ± 0.14 W/m2 for present day and -0.32 ± 0.20 W/m2 at the Last Glacial Maximum. From our study and sensitivity tests, we also derive some general relevant findings, supporting the concept that the magnitude of the modeled dust cycle is sensitive to the observational data sets and size distribution chosen to constrain the model as well as the meteorological forcing data, even within the same modeling framework, and that the direct radiative forcing of dust is strongly sensitive to the optical properties and size distribution used.
Photovoltaic subsystem marketing and distribution model: programming manual. Final report

Energy Technology Data Exchange (ETDEWEB)

1982-07-01

Complete documentation of the marketing and distribution (M and D) computer model is provided. The purpose is to estimate the costs of selling and transporting photovoltaic solar energy products from the manufacturer to the final customer. The model adjusts for the inflation and regional differences in marketing and distribution costs. The model consists of three major components: the marketing submodel, the distribution submodel, and the financial submodel. The computer program is explained including the input requirements, output reports, subprograms and operating environment. The program specifications discuss maintaining the validity of the data and potential improvements. An example for a photovoltaic concentrator collector demonstrates the application of the model.
Improving Modeling of Extreme Events using Generalized Extreme Value Distribution or Generalized Pareto Distribution with Mixing Unconditional Disturbances

OpenAIRE

Suarez, R

2001-01-01

In this paper an alternative non-parametric historical simulation approach, the Mixing Unconditional Disturbances model with constant volatility, where price paths are generated by reshuffling disturbances for S&P 500 Index returns over the period 1950 - 1998, is used to estimate a Generalized Extreme Value Distribution and a Generalized Pareto Distribution. An ordinary back-testing for period 1999 - 2008 was made to verify this technique, providing higher accuracy returns level under upper ...
An Equivalent cross-section Framework for improving computational efficiency in Distributed Hydrologic Modelling

Science.gov (United States)

Khan, Urooj; Tuteja, Narendra; Ajami, Hoori; Sharma, Ashish

2014-05-01

While the potential uses and benefits of distributed catchment simulation models is undeniable, their practical usage is often hindered by the computational resources they demand. To reduce the computational time/effort in distributed hydrological modelling, a new approach of modelling over an equivalent cross-section is investigated where topographical and physiographic properties of first-order sub-basins are aggregated to constitute modelling elements. To formulate an equivalent cross-section, a homogenization test is conducted to assess the loss in accuracy when averaging topographic and physiographic variables, i.e. length, slope, soil depth and soil type. The homogenization test indicates that the accuracy lost in weighting the soil type is greatest, therefore it needs to be weighted in a systematic manner to formulate equivalent cross-sections. If the soil type remains the same within the sub-basin, a single equivalent cross-section is formulated for the entire sub-basin. If the soil type follows a specific pattern, i.e. different soil types near the centre of the river, middle of hillslope and ridge line, three equivalent cross-sections (left bank, right bank and head water) are required. If the soil types are complex and do not follow any specific pattern, multiple equivalent cross-sections are required based on the number of soil types. The equivalent cross-sections are formulated for a series of first order sub-basins by implementing different weighting methods of topographic and physiographic variables of landforms within the entire or part of a hillslope. The formulated equivalent cross-sections are then simulated using a 2-dimensional, Richards' equation based distributed hydrological model. The simulated fluxes are multiplied by the weighted area of each equivalent cross-section to calculate the total fluxes from the sub-basins. The simulated fluxes include horizontal flow, transpiration, soil evaporation, deep drainage and soil moisture. To assess
Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

Science.gov (United States)

Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

2018-02-01

A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method
Real-time modeling and simulation of distribution feeder and distributed resources

Science.gov (United States)

Singh, Pawan

The analysis of the electrical system dates back to the days when analog network analyzers were used. With the advent of digital computers, many programs were written for power-flow and short circuit analysis for the improvement of the electrical system. Real-time computer simulations can answer many what-if scenarios in the existing or the proposed power system. In this thesis, the standard IEEE 13-Node distribution feeder is developed and validated on a real-time platform OPAL-RT. The concept and the challenges of the real-time simulation are studied and addressed. Distributed energy resources include some of the commonly used distributed generation and storage devices like diesel engine, solar photovoltaic array, and battery storage system are modeled and simulated on a real-time platform. A microgrid encompasses a portion of an electric power distribution which is located downstream of the distribution substation. Normally, the microgrid operates in paralleled mode with the grid; however, scheduled or forced isolation can take place. In such conditions, the microgrid must have the ability to operate stably and autonomously. The microgrid can operate in grid connected and islanded mode, both the operating modes are studied in the last chapter. Towards the end, a simple microgrid controller modeled and simulated on the real-time platform is developed for energy management and protection for the microgrid.
Improvement of Reynolds-Stress and Triple-Product Lag Models

Science.gov (United States)

Olsen, Michael E.; Lillard, Randolph P.

2017-01-01

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was denied by a 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of r(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+)= [4/(9/2)*.3] approximately 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to make the model better match experiment, but there is significant improvement in many of the details of the log layer behavior.
Model for the angular distribution of sky radiance

Energy Technology Data Exchange (ETDEWEB)

Hooper, F C; Brunger, A P

1979-08-01

A flexible mathematical model is introduced which describes the radiance of the dome of the sky under various conditions. This three-component continuous distribution (TCCD) model is compounded by the superposition of three separate terms, the isotropic, circumsolar and horizon brightening terms, each representing the contribution of a particular sky characteristic. In use a particular sky condition is characterized by the values of the coefficients of each of these three terms, defining the distribution of the total diffuse component. The TCCD model has been demonstrated to fit both the normalized clear sky data and the normalized overcast sky data with an RMS error of about ten percent of the man overall sky radiance. By extension the model could describe variable or partly clouded sky conditions. The model can aid in improving the prediction of solar collector performance.
Improved quasi parton distribution through Wilson line renormalization

Energy Technology Data Exchange (ETDEWEB)

Chen, Jiunn-Wei [Department of Physics, Center for Theoretical Sciences, and Leung Center for Cosmology and Particle Astrophysics, National Taiwan University, Taipei, 106, Taiwan (China); Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Ji, Xiangdong [INPAC, Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, 200240 (China); Maryland Center for Fundamental Physics, Department of Physics, University of Maryland, College Park, MD 20742 (United States); Zhang, Jian-Hui, E-mail: jianhui.zhang@physik.uni-regensburg.de [Institut für Theoretische Physik, Universität Regensburg, D-93040 Regensburg (Germany)

2017-02-15

Recent developments showed that hadron light-cone parton distributions could be directly extracted from spacelike correlators, known as quasi parton distributions, in the large hadron momentum limit. Unlike the normal light-cone parton distribution, a quasi parton distribution contains ultraviolet (UV) power divergence associated with the Wilson line self energy. We show that to all orders in the coupling expansion, the power divergence can be removed by a “mass” counterterm in the auxiliary z-field formalism, in the same way as the renormalization of power divergence for an open Wilson line. After adding this counterterm, the quasi quark distribution is improved such that it contains at most logarithmic divergences. Based on a simple version of discretized gauge action, we present the one-loop matching kernel between the improved non-singlet quasi quark distribution with a lattice regulator and the corresponding quark distribution in dimensional regularization.
Improved quasi parton distribution through Wilson line renormalization

Directory of Open Access Journals (Sweden)

Jiunn-Wei Chen

2017-02-01

Full Text Available Recent developments showed that hadron light-cone parton distributions could be directly extracted from spacelike correlators, known as quasi parton distributions, in the large hadron momentum limit. Unlike the normal light-cone parton distribution, a quasi parton distribution contains ultraviolet (UV power divergence associated with the Wilson line self energy. We show that to all orders in the coupling expansion, the power divergence can be removed by a “mass” counterterm in the auxiliary z-field formalism, in the same way as the renormalization of power divergence for an open Wilson line. After adding this counterterm, the quasi quark distribution is improved such that it contains at most logarithmic divergences. Based on a simple version of discretized gauge action, we present the one-loop matching kernel between the improved non-singlet quasi quark distribution with a lattice regulator and the corresponding quark distribution in dimensional regularization.
Productivity improvements in gas distribution

International Nuclear Information System (INIS)

Young, M.R.

1997-01-01

In 1993, the Hilmer Report resulted in the introduction of the National Competition Policy which, in the case of the gas industry, aims to promote gas-on-gas competition where to date it has been excluded. In response, and to prepare for wide gas industry reform, Gas and Fuel formed three fundamentally different core businesses on 1 July 1996 - Energy Retail, Network, and Contestable Services. In one productivity improvement initiative which is believed to be unique, Gas and Fuel appointed three companies as strategic alliance partners for distribution system maintenance. Gas and Fuel can now concentrate on its core role as asset manager which owns and operates the distribution system while procuring all services from what will become non-regulated businesses. This Paper details this initiative and the benefits which have resulted from overall changes and improvements, and outlines the challenges facing Gas and Fuel in the future. (au)
Distributed modelling of shallow landslides triggered by intense rainfall

Directory of Open Access Journals (Sweden)

G. B. Crosta

2003-01-01

Full Text Available Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use. For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997 that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy. In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.
ATLAS Distributed Computing Operations: Experience and improvements after 2 full years of data-taking

International Nuclear Information System (INIS)

Jézéquel, S; Stewart, G

2012-01-01

This paper summarizes operational experience and improvements in ATLAS computing infrastructure in 2010 and 2011. ATLAS has had 2 periods of data taking, with many more events recorded in 2011 than in 2010. It ran 3 major reprocessing campaigns. The activity in 2011 was similar to 2010, but scalability issues had to be addressed due to the increase in luminosity and trigger rate. Based on improved monitoring of ATLAS Grid computing, the evolution of computing activities (data/group production, their distribution and grid analysis) over time is presented. The main changes in the implementation of the computing model that will be shown are: the optimization of data distribution over the Grid, according to effective transfer rate and site readiness for analysis; the progressive dismantling of the cloud model, for data distribution and data processing; software installation migration to cvmfs; changing database access to a Frontier/squid infrastructure.
Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and Favourability Function models

Energy Technology Data Exchange (ETDEWEB)

Olivero, J.; Toxopeus, A.G.; Skidmore, A.K.; Real, R.

2016-07-01

Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt) and the Favourability Function (FF). We used atlas data (10 x 10 km) of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model. (Author)
Vaginal drug distribution modeling.

Science.gov (United States)

Katz, David F; Yuan, Andrew; Gao, Yajing

2015-09-15

This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.
A strategy for improved computational efficiency of the method of anchored distributions

Science.gov (United States)

Over, Matthew William; Yang, Yarong; Chen, Xingyuan; Rubin, Yoram

2013-06-01

This paper proposes a strategy for improving the computational efficiency of model inversion using the method of anchored distributions (MAD) by "bundling" similar model parametrizations in the likelihood function. Inferring the likelihood function typically requires a large number of forward model (FM) simulations for each possible model parametrization; as a result, the process is quite expensive. To ease this prohibitive cost, we present an approximation for the likelihood function called bundling that relaxes the requirement for high quantities of FM simulations. This approximation redefines the conditional statement of the likelihood function as the probability of a set of similar model parametrizations "bundle" replicating field measurements, which we show is neither a model reduction nor a sampling approach to improving the computational efficiency of model inversion. To evaluate the effectiveness of these modifications, we compare the quality of predictions and computational cost of bundling relative to a baseline MAD inversion of 3-D flow and transport model parameters. Additionally, to aid understanding of the implementation we provide a tutorial for bundling in the form of a sample data set and script for the R statistical computing language. For our synthetic experiment, bundling achieved a 35% reduction in overall computational cost and had a limited negative impact on predicted probability distributions of the model parameters. Strategies for minimizing error in the bundling approximation, for enforcing similarity among the sets of model parametrizations, and for identifying convergence of the likelihood function are also presented.
A Stochastic After-Taxes Optimisation Model to Support Distribution Network Strategies

DEFF Research Database (Denmark)

Fernandes, Rui; Hvolby, Hans-Henrik; Gouveia, Borges

2012-01-01

The paper proposes a stochastic model to integrate tax issues into strategic distribution network decisions. Specifically, this study will explore the role of distribution models in business profitability, and how to use the network design to deliver additional bottom-line results, using...... distribution centres located in different countries. The challenge is also to reveal how financial and tax knowledge can help logistic leaders improving the value to their companies under global solutions and sources of business net profitability in a dynamic environment. In particular, based on inventory...
Modeling complexity in engineered infrastructure system: Water distribution network as an example

Science.gov (United States)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.
Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and Favourability Function models

Directory of Open Access Journals (Sweden)

Olivero, J.

2016-03-01

Full Text Available Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt and the Favourability Function (FF. We used atlas data (10 x 10 km of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model.

Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

Science.gov (United States)

Beauregard, Frieda; de Blois, Sylvie

2014-01-01

Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential
Modeling and Simulation of Power Distribution System in More Electric Aircraft

Directory of Open Access Journals (Sweden)

Zhangang Yang

2015-01-01

Full Text Available The More Electric Aircraft concept is a fast-developing trend in modern aircraft industry. With this new concept, the performance of the aircraft can be further optimized and meanwhile the operating and maintenance cost will be decreased effectively. In order to optimize the power system integrity and have the ability to investigate the performance of the overall system in any possible situations, one accurate simulation model of the aircraft power system will be very helpful and necessary. This paper mainly introduces a method to build a simulation model for the power distribution system, which is based on detailed component models. The power distribution system model consists of power generation unit, transformer rectifier unit, DC-DC converter unit, and DC-AC inverter unit. In order to optimize the performance of the power distribution system and improve the quality of the distributed power, a feedback control network is designed based on the characteristics of the power distribution system. The simulation result indicates that this new simulation model is well designed and it works accurately. Moreover, steady state performance and transient state performance of the model can fulfill the requirements of aircraft power distribution system in the realistic application.
A New Distribution-Random Limit Normal Distribution

OpenAIRE

Gong, Xiaolin; Yang, Shuzhen

2013-01-01

This paper introduces a new distribution to improve tail risk modeling. Based on the classical normal distribution, we define a new distribution by a series of heat equations. Then, we use market data to verify our model.
A national-scale model of linear features improves predictions of farmland biodiversity.

Science.gov (United States)

Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

2017-12-01

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.
Renewable Distributed Generation Models in Three-Phase Load Flow Analysis for Smart Grid

Directory of Open Access Journals (Sweden)

K. M. Nor

2013-11-01

Full Text Available The paper presents renewable distributed generationÂ (RDG models as three-phase resource in load flow computation and analyzes their effect when they are connected in composite networks. The RDG models that have been considered comprise of photovoltaic (PV and wind turbine generation (WTG. The voltage-controlled node and complex power injection node are used in the models. These improvement models are suitable for smart grid power system analysis. The combination of IEEE transmission and distribution data used to test and analyze the algorithm in solving balanced/unbalanced active systems. The combination of IEEE transmission data and IEEE test feeder are used to test the the algorithm for balanced and unbalanced multi-phase distribution system problem. The simulation results show that by increased number and size of RDG units have improved voltage profile and reduced system losses.
Assimilation of ground and satellite snow observations in a distributed hydrologic model to improve water supply forecasts in the Upper Colorado River Basin

Science.gov (United States)

Micheletty, P. D.; Day, G. N.; Quebbeman, J.; Carney, S.; Park, G. H.

2016-12-01

The Upper Colorado River Basin above Lake Powell is a major source of water supply for 25 million people and provides irrigation water for 3.5 million acres. Approximately 85% of the annual runoff is produced from snowmelt. Water supply forecasts of the April-July runoff produced by the National Weather Service (NWS) Colorado Basin River Forecast Center (CBRFC), are critical to basin water management. This project leverages advanced distributed models, datasets, and snow data assimilation techniques to improve operational water supply forecasts made by CBRFC in the Upper Colorado River Basin. The current work will specifically focus on improving water supply forecasts through the implementation of a snow data assimilation process coupled with the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM). Three types of observations will be used in the snow data assimilation system: satellite Snow Covered Area (MODSCAG), satellite Dust Radiative Forcing in Snow (MODDRFS), and SNOTEL Snow Water Equivalent (SWE). SNOTEL SWE provides the main source of high elevation snowpack information during the snow season, however, these point measurement sites are carefully selected to provide consistent indices of snowpack, and may not be representative of the surrounding watershed. We address this problem by transforming the SWE observations to standardized deviates and interpolating the standardized deviates using a spatial regression model. The interpolation process will also take advantage of the MODIS Snow Covered Area and Grainsize (MODSCAG) product to inform the model on the spatial distribution of snow. The interpolated standardized deviates are back-transformed and used in an Ensemble Kalman Filter (EnKF) to update the model simulated SWE. The MODIS Dust Radiative Forcing in Snow (MODDRFS) product will be used more directly through temporary adjustments to model snowmelt parameters, which should improve melt estimates in areas affected by dust on snow. In
DESIGN IMPROVEMENTS IN MODERN DISTRIBUTION TRANSFORMERS

OpenAIRE

Ćućić, Branimir; Meško, Nina; Mikulić, Martina; Trstoglavec, Dominik

2017-01-01

In the paper design improvements of distribution transformers related to improved energy efficiency and environmental awareness are discussed. Eco design of transformers, amorphous transformers, voltage regulated transformers and transformers filled with ester liquids are analyzed. As a consequence of growing energy efficiency importance, European Commission has adopted new regulation which defines maximum permissible levels of load and no-load losses of transformers with rated...
Modeling the distribution of colonial species to improve estimation of plankton concentration in ballast water

Science.gov (United States)

Rajakaruna, Harshana; VandenByllaardt, Julie; Kydd, Jocelyn; Bailey, Sarah

2018-03-01

The International Maritime Organization (IMO) has set limits on allowable plankton concentrations in ballast water discharge to minimize aquatic invasions globally. Previous guidance on ballast water sampling and compliance decision thresholds was based on the assumption that probability distributions of plankton are Poisson when spatially homogenous, or negative binomial when heterogeneous. We propose a hierarchical probability model, which incorporates distributions at the level of particles (i.e., discrete individuals plus colonies per unit volume) and also within particles (i.e., individuals per particle) to estimate the average plankton concentration in ballast water. We examined the performance of the models using data for plankton in the size class ≥ 10 μm and test ballast water compliance using the above models.
Effects of varying the step particle distribution on a probabilistic transport model

International Nuclear Information System (INIS)

Bouzat, S.; Farengo, R.

2005-01-01

The consequences of varying the step particle distribution on a probabilistic transport model, which captures the basic features of transport in plasmas and was recently introduced in Ref. 1 [B. Ph. van Milligen et al., Phys. Plasmas 11, 2272 (2004)], are studied. Different superdiffusive transport mechanisms generated by a family of distributions with algebraic decays (Tsallis distributions) are considered. It is observed that the possibility of changing the superdiffusive transport mechanism improves the flexibility of the model for describing different situations. The use of the model to describe the low (L) and high (H) confinement modes is also analyzed
Improvements on Semi-Classical Distorted-Wave model

Energy Technology Data Exchange (ETDEWEB)

Sun Weili; Watanabe, Y.; Kuwata, R. [Kyushu Univ., Fukuoka (Japan); Kohno, M.; Ogata, K.; Kawai, M.

1998-03-01

A method of improving the Semi-Classical Distorted Wave (SCDW) model in terms of the Wigner transform of the one-body density matrix is presented. Finite size effect of atomic nuclei can be taken into account by using the single particle wave functions for harmonic oscillator or Wood-Saxon potential, instead of those based on the local Fermi-gas model which were incorporated into previous SCDW model. We carried out a preliminary SCDW calculation of 160 MeV (p,p`x) reaction on {sup 90}Zr with the Wigner transform of harmonic oscillator wave functions. It is shown that the present calculation of angular distributions increase remarkably at backward angles than the previous ones and the agreement with the experimental data is improved. (author)
Real-time modeling of heat distributions

Science.gov (United States)

Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas

2018-01-02

Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.
Distributed parallel computing in stochastic modeling of groundwater systems.

Science.gov (United States)

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.
Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

Directory of Open Access Journals (Sweden)

Frieda Beauregard

Full Text Available Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839 covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study
Distributed Wind Competitiveness Improvement Project

Energy Technology Data Exchange (ETDEWEB)

2018-02-27

The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy and its National Renewable Energy Laboratory. The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy and its National Renewable Energy Laboratory. Manufacturers of small and medium wind turbines are awarded cost-shared grants via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine designs certified to national testing standards. This fact sheet describes the CIP and funding awarded as part of the project.ufacturers of small and medium wind turbines are awarded cost-shared grants via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine designs certified to national testing standards. This fact sheet describes the CIP and funding awarded as part of the project.
An Improved Inventory Control Model for the Brazilian Navy Supply System

Science.gov (United States)

2001-12-01

Portuguese Centro de Controle de Inventario da Marinha, the Brazilian Navy Inventory Control Point (ICP) developed an empirical model called SPAADA...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS Approved for public release; distribution is unlimited AN IMPROVED INVENTORY CONTROL ...AN IMPROVED INVENTORY CONTROL MODEL FOR THE BRAZILIAN NAVY SUPPLY SYSTEM Contract Number Grant Number Program Element Number Author(s) Moreira
Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

Science.gov (United States)

Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

2015-01-01

Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.
Can model weighting improve probabilistic projections of climate change?

Energy Technology Data Exchange (ETDEWEB)

Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)

2012-10-15

Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)
A Predictive Distribution Model for Cooperative Braking System of an Electric Vehicle

Directory of Open Access Journals (Sweden)

Hongqiang Guo

2014-01-01

Full Text Available A predictive distribution model for a series cooperative braking system of an electric vehicle is proposed, which can solve the real-time problem of the optimum braking force distribution. To get the predictive distribution model, firstly three disciplines of the maximum regenerative energy recovery capability, the maximum generating efficiency and the optimum braking stability are considered, then an off-line process optimization stream is designed, particularly the optimal Latin hypercube design (Opt LHD method and radial basis function neural network (RBFNN are utilized. In order to decouple the variables between different disciplines, a concurrent subspace design (CSD algorithm is suggested. The established predictive distribution model is verified in a dynamic simulation. The off-line optimization results show that the proposed process optimization stream can improve the regenerative energy recovery efficiency, and optimize the braking stability simultaneously. Further simulation tests demonstrate that the predictive distribution model can achieve high prediction accuracy and is very beneficial for the cooperative braking system.
From Logical to Distributional Models

Directory of Open Access Journals (Sweden)

Anne Preller

2014-12-01

Full Text Available The paper relates two variants of semantic models for natural language, logical functional models and compositional distributional vector space models, by transferring the logic and reasoning from the logical to the distributional models. The geometrical operations of quantum logic are reformulated as algebraic operations on vectors. A map from functional models to vector space models makes it possible to compare the meaning of sentences word by word.
The low cost of quality improvements in the electricity distribution sector of Brazil

International Nuclear Information System (INIS)

Corton, Maria Luisa; Zimmermann, Aneliese; Phillips, Michelle Andrea

2016-01-01

We analyze the impact of introducing output-based incentives in the price-cap regulatory regime of the Brazilian electricity distribution sector. We focus on the trade-off between operating costs and quality improvement, hypothesizing a positive relationship. Operating costs include maintenance and repair expenses. The regulator sets limits for service continuity and non-technical energy losses in each regulatory period. Service continuity refers to the average length of interruptions in electricity distribution. Non-technical losses refer to losses due to factors specific to the distribution segment. Quality incentives include peer-pressure and penalties/rewards for compliance with minimum quality standards. We model operating costs using a GMM framework to acknowledge endogeneity of variables. The model is dynamic given the inclusion of regulatory lags to recognize past cost behavior. Findings reveal a small trade-off between costs and quality. We conclude that quality improvements are not costly relative to the potential savings from complying with quality standards. We also find that the impact on operating costs is larger when energy losses increase compared to the cost effect due to increases in duration of outages. These findings suggest areas of attention in managerial decision making, and serve as valuable information to the regulator in tailoring quality incentives for this sector. - Highlights: • The article focuses on the impact of quality improvements on operating costs. • We find a very small tradeoff between quality improvements and operating costs. • We find the impact of a large share of electricity losses on costs larger compared to the impact of longer outages. • The results serve the regulator to adjust incentives for quality improvement. • The results serve the regulator in tailoring regulatory values for electricity losses and outages.

Combining kernel matrix optimization and regularization to improve particle size distribution retrieval

Science.gov (United States)

Ma, Qian; Xia, Houping; Xu, Qiang; Zhao, Lei

2018-05-01

A new method combining Tikhonov regularization and kernel matrix optimization by multi-wavelength incidence is proposed for retrieving particle size distribution (PSD) in an independent model with improved accuracy and stability. In comparison to individual regularization or multi-wavelength least squares, the proposed method exhibited better anti-noise capability, higher accuracy and stability. While standard regularization typically makes use of the unit matrix, it is not universal for different PSDs, particularly for Junge distributions. Thus, a suitable regularization matrix was chosen by numerical simulation, with the second-order differential matrix found to be appropriate for most PSD types.
Evaluation for the models of neutron diffusion theory in terms of power density distributions of the HTTR

International Nuclear Information System (INIS)

Takamatsu, Kuniyoshi; Shimakawa, Satoshi; Nojiri, Naoki; Fujimoto, Nozomu

2003-10-01

In the case of evaluations for the highest temperature of the fuels in the HTTR, it is very important to expect the power density distributions accurately; therefore, it is necessary to improve the analytical model with the neutron diffusion and the burn-up theory. The power density distributions are analyzed in terms of two models, the one mixing the fuels and the burnable poisons homogeneously and the other modeling them heterogeneously. Moreover these analytical power density distributions are compared with the ones derived from the gross gamma-ray measurements and the Monte Carlo calculational code with continuous energy. As a result the homogeneous mixed model isn't enough to expect the power density distributions of the core in the axial direction; on the other hand, the heterogeneous model improves the accuracy. (author)
Distributed generation system with PEM fuel cell for electrical power quality improvement

Energy Technology Data Exchange (ETDEWEB)

Ramirez, D.; Beites, L.F.; Blazquez, F. [Department of Electrical Engineering, ETSII, Escuela de Ingenieros Industriales, Universidad Politecnica de Madrid, C/ Jose Gutierrez Abascal 2, 28006 Madrid (Spain); Ballesteros, J.C. [Endesa Generacion, S.A. c/ Ribera de Loira 60, 28042 Madrid (Spain)

2008-08-15

In this paper, a physical model for a distributed generation (DG) system with power quality improvement capability is presented. The generating system consists of a 5 kW PEM fuel cell, a natural gas reformer, hydrogen storage bottles and a bank of ultra-capacitors. Additional power quality functions are implemented with a vector-controlled electronic converter for regulating the injected power. The capabilities of the system were experimentally tested on a scaled electrical network. It is composed of different lines, built with linear inductances and resistances, and taking into account both linear and non-linear loads. The ability to improve power quality was tested by means of different voltage and frequency perturbations produced on the physical model electrical network. (author)
Study on isotopic distribution produced by nucleus-nucleus collisions with modified SAA model

International Nuclear Information System (INIS)

Zhong Chen; Fang Deqing; Cai Xiangzhou; Shen Wenqing; Zhang Huyong; Wei Yibin; Ma Yugang

2003-01-01

Base on Brohm's Statistic-Ablation-Abrasion (SAA) model, the modified SAA model was developed via introducing the isospin dependence of nucleon distribution in nucleus and parameterized formulas for nucleon-nucleon cross section in nuclear matter. It can simulate well the isotopic distribution at both high and intermediate energies. By the improvement of computational method, the range of calculation of isotopic distribution can be increased from three order magnitude to eight order magnitude (even higher). It can reproduce experimental data and predict the isotopic distribution for very far from stability line which is very important from experimental viewpoint
Distribution system modeling and analysis

CERN Document Server

Kersting, William H

2001-01-01

For decades, distribution engineers did not have the sophisticated tools developed for analyzing transmission systems-often they had only their instincts. Things have changed, and we now have computer programs that allow engineers to simulate, analyze, and optimize distribution systems. Powerful as these programs are, however, without a real understanding of the operating characteristics of a distribution system, engineers using the programs can easily make serious errors in their designs and operating procedures. Distribution System Modeling and Analysis helps prevent those errors. It gives readers a basic understanding of the modeling and operating characteristics of the major components of a distribution system. One by one, the author develops and analyzes each component as a stand-alone element, then puts them all together to analyze a distribution system comprising the various shunt and series devices for power-flow and short-circuit studies. He includes the derivation of all models and includes many num...
Improvement of the design model for SMART fuel assembly

International Nuclear Information System (INIS)

Zee, Sung Kyun; Yim, Jeong Sik

2001-04-01

A Study on the design improvement of the TEP, BEP and Hoddown spring of a fuel assembly for SMART was performed. Cut boundary Interpolation Method was applied to get more accurate results of stress and strain distribution from the results of the coarse model calculation. The improved results were compared with that of a coarse one. The finer model predicted slightly higher stress and strain distribution than the coarse model, which meant the results of the coarse model was not converged. Considering that the test results always showed much less stress than the FEM and the location of the peak stress of the refined model, the pressure stress on the loading point seemed to contribute significantly to the stresses. Judging from the fact that the peak stress appeared only at the local area, the results of the refined model were considered enough to be a conservative prediction of the stress levels. The slot of the guide thimble screw was ignored to get how much thickness of the flow plate can be reduced in case of optimization of the thickness and also cut off the screw dent hole was included for the actual geometry. For the BEP, the leg and web were also included in the model and the results with and without the leg alignment support were compared. Finally, the holddown spring which is important during the in-reactor behavior of the FA was modeled more realistic and improved to include the effects of the friction between the leaves and the loading surface. Using this improved model, it was possible that the spring characteristics were predicted more accurate to the test results. From the analysis of the spring characteristics, the local plastic area controled the characteristics of the spring dominantly which implied that it was necessary for the design of the leaf to be optimized for the improvement of the plastic behavior of the leaf spring
Improved virtual channel noise model for transform domain Wyner-Ziv video coding

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2009-01-01

Distributed video coding (DVC) has been proposed as a new video coding paradigm to deal with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. A virtual channel noise model is utilized at the decoder to estimate...... the noise distribution between the side information frame and the original frame. This is one of the most important aspects influencing the coding performance of DVC. Noise models with different granularity have been proposed. In this paper, an improved noise model for transform domain Wyner-Ziv video...... coding is proposed, which utilizes cross-band correlation to estimate the Laplacian parameters more accurately. Experimental results show that the proposed noise model can improve the rate-distortion (RD) performance....
Distributed hydrological modelling of total dissolved phosphorus transport in an agricultural landscape, part I: distributed runoff generation

Directory of Open Access Journals (Sweden)

P. Gérard-Marchant

2006-01-01

Full Text Available Successful implementation of best management practices for reducing non-point source (NPS pollution requires knowledge of the location of saturated areas that produce runoff. A physically-based, fully-distributed, GIS-integrated model, the Soil Moisture Distribution and Routing (SMDR model was developed to simulate the hydrologic behavior of small rural upland watersheds with shallow soils and steep to moderate slopes. The model assumes that gravity is the only driving force of water and that most overland flow occurs as saturation excess. The model uses available soil and climatic data, and requires little calibration. The SMDR model was used to simulate runoff production on a 164-ha farm watershed in Delaware County, New York, in the headwaters of New York City water supply. Apart from land use, distributed input parameters were derived from readily available data. Simulated hydrographs compared reasonably with observed flows at the watershed outlet over a eight year simulation period, and peak timing and intensities were well reproduced. Using off-site weather input data produced occasional missed event peaks. Simulated soil moisture distribution agreed well with observed hydrological features and followed the same spatial trend as observed soil moisture contents sampled on four transects. Model accuracy improved when input variables were calibrated within the range of SSURGO-available parameters. The model will be a useful planning tool for reducing NPS pollution from farms in landscapes similar to the Northeastern US.
An improved AVC strategy applied in distributed wind power system

Science.gov (United States)

Zhao, Y. N.; Liu, Q. H.; Song, S. Y.; Mao, W.

2016-08-01

Traditional AVC strategy is mainly used in wind farm and only concerns about grid connection point, which is not suitable for distributed wind power system. Therefore, this paper comes up with an improved AVC strategy applied in distributed wind power system. The strategy takes all nodes of distribution network into consideration and chooses the node having the most serious voltage deviation as control point to calculate the reactive power reference. In addition, distribution principles can be divided into two conditions: when wind generators access to network on single node, the reactive power reference is distributed according to reactive power capacity; when wind generators access to network on multi-node, the reference is distributed according to sensitivity. Simulation results show the correctness and reliability of the strategy. Compared with traditional control strategy, the strategy described in this paper can make full use of generators reactive power output ability according to the distribution network voltage condition and improve the distribution network voltage level effectively.
Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

DEFF Research Database (Denmark)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren Gonzalez, Gorka

2018-01-01

selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient...
Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Directory of Open Access Journals (Sweden)

Qingwu Gong

2017-03-01

Full Text Available The intermittency and variability of permeated distributed generators (DGs could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices—EENS (expected energy not supplied, PLC (probability of load curtailment, EFLC (expected frequency of load curtailment, and SI (severity index—were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs’ output power, an improved PEM (point estimate method-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.
A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

Science.gov (United States)

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this
BAYESIAN MODELS FOR SPECIES DISTRIBUTION MODELLING WITH ONLY-PRESENCE RECORDS

Directory of Open Access Journals (Sweden)

Bartolo de JesÃºs Villar-HernÃ¡ndez

2015-08-01

Full Text Available One of the central issues in ecology is the study of geographical distribution of species of flora and fauna through Species Distribution Models (SDM. Recently, scientific interest has focused on presence-only records. Two recent approaches have been proposed for this problem: a model based on maximum likelihood method (Maxlike and an inhomogeneous poisson process model (IPP. In this paper we discussed two bayesian approaches called MaxBayes and IPPBayes based on Maxlike and IPP model, respectively. To illustrate these proposals, we implemented two study examples: (1 both models were implemented on a simulated dataset, and (2 we modeled the potencial distribution of genus Dalea in the Tehuacan-CuicatlÃ¡n biosphere reserve with both models, the results was compared with that of Maxent. The results show that both models, MaxBayes and IPPBayes, are viable alternatives when species distribution are modeled with only-presence records. For simulated dataset, MaxBayes achieved prevalence estimation, even when the number of records was small. In the real dataset example, both models predict similar potential distributions like Maxent does. Â
Improving the cooling performance of electrical distribution transformer using transformer oil – Based MEPCM suspension

OpenAIRE

Mushtaq Ismael Hasan

2017-01-01

In this paper the electrical distribution transformer has been studied numerically and the effect of outside temperature on its cooling performance has been investigated. The temperature range studied covers the hot climate regions. 250 KVA distribution transformer is chosen as a study model. A novel cooling fluid is proposed to improve the cooling performance of this transformer, transformer oil-based microencapsulated phase change materials suspension is used with volume concentration (5–25...
A Meteorological Distribution System for High Resolution Terrestrial Modeling (MicroMet)

Science.gov (United States)

Liston, G. E.; Elder, K.

2004-12-01

Spatially distributed terrestrial models generally require atmospheric forcing data on horizontal grids that are of higher resolution than available meteorological data. Furthermore, the meteorological data collected may not necessarily represent the area of interest's meteorological variability. To address these deficiencies, computationally efficient and physically realistic methods must be developed to take available meteorological data sets (e.g., meteorological tower observations) and generate high-resolution atmospheric-forcing distributions. This poster describes MicroMet, a quasi-physically-based, but simple meteorological distribution model designed to produce high-resolution (e.g., 5-m to 1-km horizontal grid increments) meteorological data distributions required to run spatially distributed terrestrial models over a wide variety of landscapes. The model produces distributions of the seven fundamental atmospheric forcing variables required to run most terrestrial models: air temperature, relative humidity, wind speed, wind direction, incoming solar radiation, incoming longwave radiation, and precipitation. MicroMet includes a preprocessor that analyzes meteorological station data and identifies and repairs potential data deficiencies. The model uses known relationships between meteorological variables and the surrounding area (primarily topography) to distribute those variables over any given landscape. MicroMet performs two kinds of adjustments to available meteorological data: 1) when there are data at more than one location, at a given time, the data are spatially interpolated over the domain using a Barnes objective analysis scheme, and 2) physical sub-models are applied to each MicroMet variable to improve its realism at a given point in space and time with respect to the terrain. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) will be used as example Micro
Bounding species distribution models

Directory of Open Access Journals (Sweden)

Thomas J. STOHLGREN, Catherine S. JARNEVICH, Wayne E. ESAIAS,Jeffrey T. MORISETTE

2011-10-01

Full Text Available Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART and maximum entropy (Maxent models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5: 642–647, 2011].
Bounding Species Distribution Models

Science.gov (United States)

Stohlgren, Thomas J.; Jarnevich, Cahterine S.; Morisette, Jeffrey T.; Esaias, Wayne E.

2011-01-01

Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].
Improved margin utilization through the use of beacon power distribution surveillance

International Nuclear Information System (INIS)

Miller, R. Wade; Boyd, William A.

2002-01-01

Core Operations, including fuel cycle costs, can be significantly improved when state of the art surveillance techniques are employed for core power distribution monitoring. Core power distribution monitoring and Technical Specification surveillance are major operational issues at PWR's, particularly in plants with movable in core detectors. Even plants with fixed in core detectors do not always make use of the continuous data that is available. The BEACON TM system (Best Estimate Analysis of Core Operations - Nuclear) is a core monitoring and operational support package developed by Westinghouse for use in PWR plants with fixed or movable in core detectors. BEACON is a real time core monitoring system, which uses existing core instrumentation data and an on-line neutronics model to provide continuous monitored of the core power distribution information. With this information available the BEACON system can be used to continuously monitor core power margin for the plant Tech Spec surveillance requirements and for plant operational guidance
Some important results from the air pollution distribution model STACKS (1988-1992)

International Nuclear Information System (INIS)

Erbrink, J.J.

1993-01-01

Attention is paid to the results of the study on the distribution of air pollutants by high chimney-stacks of electric power plants. An important product of the study is the integrated distribution model STACKS (Short Term Air-pollutant Concentrations Kema modelling System). The improvements and the extensions of STACKS are described in relation to the National Model, which has been used to estimate the environmental effects of individual chimney-stacks. The National Model shows unacceptable variations for high pollutant sources. Based on the results of STACKS revision of the National model has been taken into consideration. By means of the revised National Model a more realistic estimation of the environmental effects of electric power plants can be carried out
Validation of model predictions of pore-scale fluid distributions during two-phase flow

Science.gov (United States)

Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

2018-05-01

Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

A distribution-free newsvendor model with balking penalty and random yield

Directory of Open Access Journals (Sweden)

Chongfeng Lan

2015-05-01

Full Text Available Purpose: The purpose of this paper is to extend the analysis of the distribution-free newsvendor problem in an environment of customer balking, which occurs when customers are reluctant to buy a product if its available inventory falls below a threshold level. Design/methodology/approach: We provide a new tradeoff tool as a replacement of the traditional one to weigh the holding cost and the goodwill costs segment: in addition to the shortage penalty, we also introduce the balking penalty. Furthermore, we extend our model to the case of random yield. Findings: A model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand. We also study the effects of shortage penalty and the balking penalty on the optimal order quantity, which have been largely bypassed in the existing distribution free single period models with balking. Numerical examples are presented to illustrate the result. Originality/value: The incorporation of balking penalty and random yield represents an important improvement in inventory policy performance for distribution-free newsvendor problem when customer balking occurs and the distributional form of demand is unknown.
Distributions with given marginals and statistical modelling

CERN Document Server

Fortiana, Josep; Rodriguez-Lallena, José

2002-01-01

This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.
Modeling the economics and market adoption of distributed power generation

International Nuclear Information System (INIS)

Maribu, Karl Magnus

2006-01-01

After decades of power generating units increasing in size, there is currently a growing focus on distributed generation, power generation close to energy loads. Investments in large-scale units have been driven by economy of scale, but recent technological improvements on small generating plants have made it possible to exploit the benefits of local power generation to a larger extent than previously. Distributed generation can improve power system efficiency because heat can be recovered from thermal units to supply heat and thermally activated cooling, and because small-scale renewables have a promising end-user market. Further benefits of distributed generation include improved reliability, deferral of often controversial and costly grid investments and reduction of grid losses. The new appeal of small-scale power generation means that there is a need for new tools to analyze distributed generation, both from a system perspective and from the perspective of potential developers. In this thesis, the focus is on the value of power generation for end-users. The thesis identifies how an end-user can find optimal distributed generation systems and investment strategies under a variety of economic and regulatory scenarios. The final part of the thesis extends the analysis with a bottom up model of how the economics of distributed generation for a representative set of building types can transfer to technology diffusion in a market. Four separate research papers make up the thesis. In the first paper, Optimal Investment Strategies in Decentralized Renewable Power Generation under Uncertainty, a method for evaluation of investments in renewable power units under price uncertainty is presented. It is assumed the developer has a building with an electricity load and a renewable power resource. The case study compares a set of wind power systems with different capacity and finds that capacity depends on the electricity price and that there under uncertain prices can be a
A Distributed Hydrological model Forced by DIMP2 Data and the WRF Mesoscale model

Science.gov (United States)

Wayand, N. E.

2010-12-01

Forecasted warming over the next century will drastically reduce seasonal snowpack that provides 40% of the world’s drinking water. With increased climate warming, droughts may occur more frequently, which will increase society’s reliance on this same summer snowpack as a water supply. This study aims to reduce driving data errors that lead to poor simulations of snow ablation and accumulation, and streamflow. Results from the Distributed Hydrological Model Intercomparison Project Phase 2 (DMIP2) project using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted the critical need for accurate driving data that distributed models require. Currently, the meteorological driving data for distributed hydrological models commonly rely on interpolation techniques between a network of observational stations, as well as historical monthly means. This method is limited by two significant issues: snowpack is stored at high elevations, where interpolation techniques perform poorly due to sparse observations, and historic climatological means may be unsuitable in a changing climate. Mesoscale models may provide a physically-based approach to supplement surface observations over high-elevation terrain. Initial results have shown that while temperature lapse rates are well represented by multiple mesoscale models, significant precipitation biases are dependent on the particular model microphysics. We evaluate multiple methods of downscaling surface variables from the Weather and Research Forecasting (WRF) model that are then used to drive DHSVM over the North Fork American River basin in California. A comparison between each downscaled driving data set and paired DHSVM results to observations will determine how much improvement in simulated streamflow and snowpack are gained at the expense of each additional degree of downscaling. Our results from DMIP2 will be used as a benchmark for the best available DHSVM run using all available observational data. The
Improving the spectral measurement accuracy based on temperature distribution and spectra-temperature relationship

Science.gov (United States)

Li, Zhe; Feng, Jinchao; Liu, Pengyu; Sun, Zhonghua; Li, Gang; Jia, Kebin

2018-05-01

Temperature is usually considered as a fluctuation in near-infrared spectral measurement. Chemometric methods were extensively studied to correct the effect of temperature variations. However, temperature can be considered as a constructive parameter that provides detailed chemical information when systematically changed during the measurement. Our group has researched the relationship between temperature-induced spectral variation (TSVC) and normalized squared temperature. In this study, we focused on the influence of temperature distribution in calibration set. Multi-temperature calibration set selection (MTCS) method was proposed to improve the prediction accuracy by considering the temperature distribution of calibration samples. Furthermore, double-temperature calibration set selection (DTCS) method was proposed based on MTCS method and the relationship between TSVC and normalized squared temperature. We compare the prediction performance of PLS models based on random sampling method and proposed methods. The results from experimental studies showed that the prediction performance was improved by using proposed methods. Therefore, MTCS method and DTCS method will be the alternative methods to improve prediction accuracy in near-infrared spectral measurement.
Supply chain solutions to improve the distribution of antiretroviral ...

African Journals Online (AJOL)

Recommendations to address the problems include: Implementing a supply chain planning and design process; improving inventory management and warehousing practices; implementing more effective and reliable distribution and transportation processes; as well as improving supply chain coordination and overall ...
The value of oxygen-isotope data and multiple discharge records in calibrating a fully-distributed, physically-based rainfall-runoff model (CRUM3) to improve predictive capability

Science.gov (United States)

Neill, Aaron; Reaney, Sim

2015-04-01

Fully-distributed, physically-based rainfall-runoff models attempt to capture some of the complexity of the runoff processes that operate within a catchment, and have been used to address a variety of issues including water quality and the effect of climate change on flood frequency. Two key issues are prevalent, however, which call into question the predictive capability of such models. The first is the issue of parameter equifinality which can be responsible for large amounts of uncertainty. The second is whether such models make the right predictions for the right reasons - are the processes operating within a catchment correctly represented, or do the predictive abilities of these models result only from the calibration process? The use of additional data sources, such as environmental tracers, has been shown to help address both of these issues, by allowing for multi-criteria model calibration to be undertaken, and by permitting a greater understanding of the processes operating in a catchment and hence a more thorough evaluation of how well catchment processes are represented in a model. Using discharge and oxygen-18 data sets, the ability of the fully-distributed, physically-based CRUM3 model to represent the runoff processes in three sub-catchments in Cumbria, NW England has been evaluated. These catchments (Morland, Dacre and Pow) are part of the of the River Eden demonstration test catchment project. The oxygen-18 data set was firstly used to derive transit-time distributions and mean residence times of water for each of the catchments to gain an integrated overview of the types of processes that were operating. A generalised likelihood uncertainty estimation procedure was then used to calibrate the CRUM3 model for each catchment based on a single discharge data set from each catchment. Transit-time distributions and mean residence times of water obtained from the model using the top 100 behavioural parameter sets for each catchment were then compared to
Dynamic models for distributed generation resources

Energy Technology Data Exchange (ETDEWEB)

Morched, A.S. [BPR Energie, Sherbrooke, PQ (Canada)

2010-07-01

Distributed resources can impact the performance of host power systems during both normal and abnormal system conditions. This PowerPoint presentation discussed the use of dynamic models for identifying potential interaction problems between interconnected systems. The models were designed to simulate steady state behaviour as well as transient responses to system disturbances. The distributed generators included directly coupled and electronically coupled generators. The directly coupled generator was driven by wind turbines. Simplified models of grid-side inverters, electronically coupled wind generators and doubly-fed induction generators (DFIGs) were presented. The responses of DFIGs to wind variations were evaluated. Synchronous machine and electronically coupled generator responses were compared. The system model components included load models, generators, protection systems, and system equivalents. Frequency responses to islanding events were reviewed. The study demonstrated that accurate simulations are needed to predict the impact of distributed generation resources on the performance of host systems. Advances in distributed generation technology have outpaced the development of models needed for integration studies. tabs., figs.
Dynamic modeling method of the bolted joint with uneven distribution of joint surface pressure

Science.gov (United States)

Li, Shichao; Gao, Hongli; Liu, Qi; Liu, Bokai

2018-03-01

The dynamic characteristics of the bolted joints have a significant influence on the dynamic characteristics of the machine tool. Therefore, establishing a reasonable bolted joint dynamics model is helpful to improve the accuracy of machine tool dynamics model. Because the pressure distribution on the joint surface is uneven under the concentrated force of bolts, a dynamic modeling method based on the uneven pressure distribution of the joint surface is presented in this paper to improve the dynamic modeling accuracy of the machine tool. The analytic formulas between the normal, tangential stiffness per unit area and the surface pressure on the joint surface can be deduced based on the Hertz contact theory, and the pressure distribution on the joint surface can be obtained by the finite element software. Futhermore, the normal and tangential stiffness distribution on the joint surface can be obtained by the analytic formula and the pressure distribution on the joint surface, and assigning it into the finite element model of the joint. Qualitatively compared the theoretical mode shapes and the experimental mode shapes, as well as quantitatively compared the theoretical modal frequencies and the experimental modal frequencies. The comparison results show that the relative error between the first four-order theoretical modal frequencies and the first four-order experimental modal frequencies is 0.2% to 4.2%. Besides, the first four-order theoretical mode shapes and the first four-order experimental mode shapes are similar and one-to-one correspondence. Therefore, the validity of the theoretical model is verified. The dynamic modeling method proposed in this paper can provide a theoretical basis for the accurate dynamic modeling of the bolted joint in machine tools.
Smart Demand for Improving Short-term Voltage Control on Distribution Networks

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Xu, Zhao

2009-01-01

customer integration to aid power system performance is almost inevitable. This study introduces a new type of smart demand side technology, denoted demand as voltage controlled reserve (DVR), to improve short-term voltage control, where customers are expected to play a more dynamic role to improve voltage...... control. The technology can be provided by thermostatically controlled loads as well as other types of load. This technology is proven to be effective in case of distribution systems with a large composition of induction motors, where the voltage presents a slow recovery characteristic due to deceleration...... of the motors during faults. This study presents detailed models, discussion and simulation tests to demonstrate the technical viability and effectiveness of the DVR technology for short-term voltage control....
A proposed centralised distribution model for the South African automotive component industry

Directory of Open Access Journals (Sweden)

Micheline J. Naude

2009-12-01

Full Text Available Purpose: This article explores the possibility of developing a distribution model, similar to the model developed and implemented by the South African pharmaceutical industry, which could be implemented by automotive component manufacturers for supply to independent retailers. Problem Investigated: The South African automotive components distribution chain is extensive with a number of players of varying sizes, from the larger spares distribution groups to a number of independent retailers. Distributing to the smaller independent retailers is costly for the automotive component manufacturers. Methodology: This study is based on a preliminary study of an explorative nature. Interviews were conducted with a senior staff member from a leading automotive component manufacturer in KwaZulu Natal and nine participants at a senior management level at five of their main customers (aftermarket retailers. Findings: The findings from the empirical study suggest that the aftermarket component industry is mature with the role players well established. The distribution chain to the independent retailer is expensive in terms of transaction and distribution costs for the automotive component manufacturer. A proposed centralised distribution model for supply to independent retailers has been developed which should reduce distribution costs for the automotive component manufacturer in terms of (1 the lowest possible freight rate; (2 timely and controlled delivery; and (3 reduced congestion at the customer's receiving dock. Originality: This research is original in that it explores the possibility of implementing a centralised distribution model for independent retailers in the automotive component industry. Furthermore, there is a dearth of published research on the South African automotive component industry particularly addressing distribution issues. Conclusion: The distribution model as suggested is a practical one and should deliver added value to automotive
Species distribution modeling based on the automated identification of citizen observations.

Science.gov (United States)

Botella, Christophe; Joly, Alexis; Bonnet, Pierre; Monestiez, Pascal; Munoz, François

2018-02-01

A species distribution model computed with automatically identified plant observations was developed and evaluated to contribute to future ecological studies. We used deep learning techniques to automatically identify opportunistic plant observations made by citizens through a popular mobile application. We compared species distribution modeling of invasive alien plants based on these data to inventories made by experts. The trained models have a reasonable predictive effectiveness for some species, but they are biased by the massive presence of cultivated specimens. The method proposed here allows for fine-grained and regular monitoring of some species of interest based on opportunistic observations. More in-depth investigation of the typology of the observations and the sampling bias should help improve the approach in the future.
Evaluating the impact of improvements to the FLAMBE smoke source model on forecasts of aerosol distribution from NAAPS

Science.gov (United States)

Hyer, E. J.; Reid, J. S.

2006-12-01

As more forecast models aim to include aerosol and chemical species, there is a need for source functions for biomass burning emissions that are accurate, robust, and operable in real-time. NAAPS is a global aerosol forecast model running every six hours and forecasting distributions of biomass burning, industrial sulfate, dust, and sea salt aerosols. This model is run operationally by the U.S. Navy as an aid to planning. The smoke emissions used as input to the model are calculated from the data collected by the FLAMBE system, driven by near-real-time active fire data from GOES WF_ABBA and MODIS Rapid Response. The smoke source function uses land cover data to predict properties of detected fires based on literature data from experimental burns. This scheme is very sensitive to the choice of land cover data sets. In areas of rapid land cover change, the use of static land cover data can produce artifactual changes in emissions unrelated to real changes in fire patterns. In South America, this change may be as large as 40% over five years. We demonstrate the impact of a modified land cover scheme on FLAMBE emissions and NAAPS forecasts, including a fire size algorithm developed using MODIS burned area data. We also describe the effects of corrections to emissions estimates for cloud and satellite coverage. We outline areas where existing data sources are incomplete and improvements are required to achieve accurate modeling of biomass burning emissions in real time.
Distributed collaborative team effectiveness: measurement and process improvement

Science.gov (United States)

Wheeler, R.; Hihn, J.; Wilkinson, B.

2002-01-01

This paper describes a measurement methodology developed for assessing the readiness, and identifying opportunities for improving the effectiveness, of distributed collaborative design teams preparing to conduct a coccurent design session.
Testing species distribution models across space and time: high latitude butterflies and recent warming

DEFF Research Database (Denmark)

Eskildsen, Anne; LeRoux, Peter C.; Heikkinen, Risto K.

2013-01-01

changes at expanding range margins can be predicted accurately. Location. Finland. Methods. Using 10-km resolution butterfly atlas data from two periods, 1992–1999 (t1) and 2002–2009 (t2), with a significant between-period temperature increase, we modelled the effects of climatic warming on butterfly...... butterfly distributions under climate change. Model performance was lower with independent compared to non-independent validation and improved when land cover and soil type variables were included, compared to climate-only models. SDMs performed less well for highly mobile species and for species with long......Aim. To quantify whether species distribution models (SDMs) can reliably forecast species distributions under observed climate change. In particular, to test whether the predictive ability of SDMs depends on species traits or the inclusion of land cover and soil type, and whether distributional...
Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

Science.gov (United States)

Du, Tingsong; Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.
Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

Directory of Open Access Journals (Sweden)

Tingsong Du

2015-01-01

Full Text Available An improved quantum artificial fish swarm algorithm (IQAFSA for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA, the basic artificial fish swarm algorithm (BAFSA, and the global edition artificial fish swarm algorithm (GAFSA to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.
Multi-Model Prediction for Demand Forecast in Water Distribution Networks

Directory of Open Access Journals (Sweden)

Rodrigo Lopez Farias

2018-03-01

Full Text Available This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+ for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction is forecasted and the pattern mode estimated using a Nearest Neighbor (NN classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN, the statistical Autoregressive Integrated Moving Average (ARIMA, and Double Seasonal Holt-Winters (DSHW approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy.
Probability Distribution and Deviation Information Fusion Driven Support Vector Regression Model and Its Application

Directory of Open Access Journals (Sweden)

Changhao Fan

2017-01-01

Full Text Available In modeling, only information from the deviation between the output of the support vector regression (SVR model and the training sample is considered, whereas the other prior information of the training sample, such as probability distribution information, is ignored. Probabilistic distribution information describes the overall distribution of sample data in a training sample that contains different degrees of noise and potential outliers, as well as helping develop a high-accuracy model. To mine and use the probability distribution information of a training sample, a new support vector regression model that incorporates probability distribution information weight SVR (PDISVR is proposed. In the PDISVR model, the probability distribution of each sample is considered as the weight and is then introduced into the error coefficient and slack variables of SVR. Thus, the deviation and probability distribution information of the training sample are both used in the PDISVR model to eliminate the influence of noise and outliers in the training sample and to improve predictive performance. Furthermore, examples with different degrees of noise were employed to demonstrate the performance of PDISVR, which was then compared with those of three SVR-based methods. The results showed that PDISVR performs better than the three other methods.
Modeled ground water age distributions

Science.gov (United States)

Woolfenden, Linda R.; Ginn, Timothy R.

2009-01-01

The age of ground water in any given sample is a distributed quantity representing distributed provenance (in space and time) of the water. Conventional analysis of tracers such as unstable isotopes or anthropogenic chemical species gives discrete or binary measures of the presence of water of a given age. Modeled ground water age distributions provide a continuous measure of contributions from different recharge sources to aquifers. A numerical solution of the ground water age equation of Ginn (1999) was tested both on a hypothetical simplified one-dimensional flow system and under real world conditions. Results from these simulations yield the first continuous distributions of ground water age using this model. Complete age distributions as a function of one and two space dimensions were obtained from both numerical experiments. Simulations in the test problem produced mean ages that were consistent with the expected value at the end of the model domain for all dispersivity values tested, although the mean ages for the two highest dispersivity values deviated slightly from the expected value. Mean ages in the dispersionless case also were consistent with the expected mean ages throughout the physical model domain. Simulations under real world conditions for three dispersivity values resulted in decreasing mean age with increasing dispersivity. This likely is a consequence of an edge effect. However, simulations for all three dispersivity values tested were mass balanced and stable demonstrating that the solution of the ground water age equation can provide estimates of water mass density distributions over age under real world conditions.

Model of bidirectional reflectance distribution function for metallic materials

International Nuclear Information System (INIS)

Wang Kai; Zhu Jing-Ping; Liu Hong; Hou Xun

2016-01-01

Based on the three-component assumption that the reflection is divided into specular reflection, directional diffuse reflection, and ideal diffuse reflection, a bidirectional reflectance distribution function (BRDF) model of metallic materials is presented. Compared with the two-component assumption that the reflection is composed of specular reflection and diffuse reflection, the three-component assumption divides the diffuse reflection into directional diffuse and ideal diffuse reflection. This model effectively resolves the problem that constant diffuse reflection leads to considerable error for metallic materials. Simulation and measurement results validate that this three-component BRDF model can improve the modeling accuracy significantly and describe the reflection properties in the hemisphere space precisely for the metallic materials. (paper)
Model of bidirectional reflectance distribution function for metallic materials

Science.gov (United States)

Wang, Kai; Zhu, Jing-Ping; Liu, Hong; Hou, Xun

2016-09-01

Based on the three-component assumption that the reflection is divided into specular reflection, directional diffuse reflection, and ideal diffuse reflection, a bidirectional reflectance distribution function (BRDF) model of metallic materials is presented. Compared with the two-component assumption that the reflection is composed of specular reflection and diffuse reflection, the three-component assumption divides the diffuse reflection into directional diffuse and ideal diffuse reflection. This model effectively resolves the problem that constant diffuse reflection leads to considerable error for metallic materials. Simulation and measurement results validate that this three-component BRDF model can improve the modeling accuracy significantly and describe the reflection properties in the hemisphere space precisely for the metallic materials.
New trends in species distribution modelling

Science.gov (United States)

Zimmermann, Niklaus E.; Edwards, Thomas C.; Graham, Catherine H.; Pearman, Peter B.; Svenning, Jens-Christian

2010-01-01

Species distribution modelling has its origin in the late 1970s when computing capacity was limited. Early work in the field concentrated mostly on the development of methods to model effectively the shape of a species' response to environmental gradients (Austin 1987, Austin et al. 1990). The methodology and its framework were summarized in reviews 10–15 yr ago (Franklin 1995, Guisan and Zimmermann 2000), and these syntheses are still widely used as reference landmarks in the current distribution modelling literature. However, enormous advancements have occurred over the last decade, with hundreds – if not thousands – of publications on species distribution model (SDM) methodologies and their application to a broad set of conservation, ecological and evolutionary questions. With this special issue, originating from the third of a set of specialized SDM workshops (2008 Riederalp) entitled 'The Utility of Species Distribution Models as Tools for Conservation Ecology', we reflect on current trends and the progress achieved over the last decade.
Regional drought assessment using a distributed hydrological model coupled with Standardized Runoff Index

Directory of Open Access Journals (Sweden)

H. Shen

2015-05-01

Full Text Available Drought assessment is essential for coping with frequent droughts nowadays. Owing to the large spatio-temporal variations in hydrometeorology in most regions in China, it is very necessary to use a physically-based hydrological model to produce rational spatial and temporal distributions of hydro-meteorological variables for drought assessment. In this study, the large-scale distributed hydrological model Variable Infiltration Capacity (VIC was coupled with a modified standardized runoff index (SRI for drought assessment in the Weihe River basin, northwest China. The result indicates that the coupled model is capable of reasonably reproducing the spatial distribution of drought occurrence. It reflected the spatial heterogeneity of regional drought and improved the physical mechanism of SRI. This model also has potential for drought forecasting, early warning and mitigation, given that accurate meteorological forcing data are available.
Improving Distribution Resiliency with Microgrids and State and Parameter Estimation

Energy Technology Data Exchange (ETDEWEB)

Tuffner, Francis K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Schneider, Kevin P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sun, Yannan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Chen-Ching [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Xu, Yin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gourisetti, Sri Nikhil Gup [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-09-30

Modern society relies on low-cost reliable electrical power, both to maintain industry, as well as provide basic social services to the populace. When major disturbances occur, such as Hurricane Katrina or Hurricane Sandy, the nation’s electrical infrastructure can experience significant outages. To help prevent the spread of these outages, as well as facilitating faster restoration after an outage, various aspects of improving the resiliency of the power system are needed. Two such approaches are breaking the system into smaller microgrid sections, and to have improved insight into the operations to detect failures or mis-operations before they become critical. Breaking the system into smaller sections of microgrid islands, power can be maintained in smaller areas where distribution generation and energy storage resources are still available, but bulk power generation is no longer connected. Additionally, microgrid systems can maintain service to local pockets of customers when there has been extensive damage to the local distribution system. However, microgrids are grid connected a majority of the time and implementing and operating a microgrid is much different than when islanded. This report discusses work conducted by the Pacific Northwest National Laboratory that developed improvements for simulation tools to capture the characteristics of microgrids and how they can be used to develop new operational strategies. These operational strategies reduce the cost of microgrid operation and increase the reliability and resilience of the nation’s electricity infrastructure. In addition to the ability to break the system into microgrids, improved observability into the state of the distribution grid can make the power system more resilient. State estimation on the transmission system already provides great insight into grid operations and detecting abnormal conditions by leveraging existing measurements. These transmission-level approaches are expanded to using
Modelling Reliability of Supply and Infrastructural Dependency in Energy Distribution Systems

OpenAIRE

Helseth, Arild

2008-01-01

This thesis presents methods and models for assessing reliability of supply and infrastructural dependency in energy distribution systems with multiple energy carriers. The three energy carriers of electric power, natural gas and district heating are considered. Models and methods for assessing reliability of supply in electric power systems are well documented, frequently applied in the industry and continuously being subject to research and improvement. On the contrary, there are compar...
Deterministic Properties of Serially Connected Distributed Lag Models

Directory of Open Access Journals (Sweden)

Piotr Nowak

2013-01-01

Full Text Available Distributed lag models are an important tool in modeling dynamic systems in economics. In the analysis of composite forms of such models, the component models are ordered in parallel (with the same independent variable and/or in series (where the independent variable is also the dependent variable in the preceding model. This paper presents an analysis of certain deterministic properties of composite distributed lag models composed of component distributed lag models arranged in sequence, and their asymptotic properties in particular. The models considered are in discrete form. Even though the paper focuses on deterministic properties of distributed lag models, the derivations are based on analytical tools commonly used in probability theory such as probability distributions and the central limit theorem. (original abstract
Light distributions in a port wine stain model containing multiple cylindrical and curved blood vessels

NARCIS (Netherlands)

Lucassen, G. W.; Verkruysse, W.; Keijzer, M.; van Gemert, M. J.

1996-01-01

Knowledge of the light distribution in skin tissue is important for the understanding, prediction, and improvement of the clinical results in laser treatment of port wine stains (PWS). The objective of this study is to improve modelling of PWS treated by laser using an improved and more realistic
Improvement and Validation of Weld Residual Stress Modelling Procedure

International Nuclear Information System (INIS)

Zang, Weilin; Gunnars, Jens; Dong, Pingsha; Hong, Jeong K.

2009-06-01

The objective of this work is to identify and evaluate improvements for the residual stress modelling procedure currently used in Sweden. There is a growing demand to eliminate any unnecessary conservatism involved in residual stress assumptions. The study was focused on the development and validation of an improved weld residual stress modelling procedure, by taking advantage of the recent advances in residual stress modelling and stress measurement techniques. The major changes applied in the new weld residual stress modelling procedure are: - Improved procedure for heat source calibration based on use of analytical solutions. - Use of an isotropic hardening model where mixed hardening data is not available. - Use of an annealing model for improved simulation of strain relaxation in re-heated material. The new modelling procedure is demonstrated to capture the main characteristics of the through thickness stress distributions by validation to experimental measurements. Three austenitic stainless steel butt-welds cases are analysed, covering a large range of pipe geometries. From the cases it is evident that there can be large differences between the residual stresses predicted using the new procedure, and the earlier procedure or handbook recommendations. Previously recommended profiles could give misleading fracture assessment results. The stress profiles according to the new procedure agree well with the measured data. If data is available then a mixed hardening model should be used
Improvement and Validation of Weld Residual Stress Modelling Procedure

Energy Technology Data Exchange (ETDEWEB)

Zang, Weilin; Gunnars, Jens (Inspecta Technology AB, Stockholm (Sweden)); Dong, Pingsha; Hong, Jeong K. (Center for Welded Structures Research, Battelle, Columbus, OH (United States))

2009-06-15

The objective of this work is to identify and evaluate improvements for the residual stress modelling procedure currently used in Sweden. There is a growing demand to eliminate any unnecessary conservatism involved in residual stress assumptions. The study was focused on the development and validation of an improved weld residual stress modelling procedure, by taking advantage of the recent advances in residual stress modelling and stress measurement techniques. The major changes applied in the new weld residual stress modelling procedure are: - Improved procedure for heat source calibration based on use of analytical solutions. - Use of an isotropic hardening model where mixed hardening data is not available. - Use of an annealing model for improved simulation of strain relaxation in re-heated material. The new modelling procedure is demonstrated to capture the main characteristics of the through thickness stress distributions by validation to experimental measurements. Three austenitic stainless steel butt-welds cases are analysed, covering a large range of pipe geometries. From the cases it is evident that there can be large differences between the residual stresses predicted using the new procedure, and the earlier procedure or handbook recommendations. Previously recommended profiles could give misleading fracture assessment results. The stress profiles according to the new procedure agree well with the measured data. If data is available then a mixed hardening model should be used
Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

International Nuclear Information System (INIS)

Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

2007-11-01

The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results
Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling

DEFF Research Database (Denmark)

Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan

2008-01-01

uncertainty estimation (GLUE) procedure based on Markov chain Monte Carlo sampling is applied in order to improve the performance of the methodology in estimating parameters and posterior output distributions. The description of the spatial variations of the hydrological processes is accounted for by defining......In recent years, there has been an increase in the application of distributed, physically-based and integrated hydrological models. Many questions regarding how to properly calibrate and validate distributed models and assess the uncertainty of the estimated parameters and the spatially......-site validation must complement the usual time validation. In this study, we develop, through an application, a comprehensive framework for multi-criteria calibration and uncertainty assessment of distributed physically-based, integrated hydrological models. A revised version of the generalized likelihood...
Building predictive models of soil particle-size distribution

Directory of Open Access Journals (Sweden)

Alessandro Samuel-Rosa

2013-04-01

Full Text Available Is it possible to build predictive models (PMs of soil particle-size distribution (psd in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index. The PMs explained more than half of the data variance. This performance is similar to (or even better than that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd of soils in regions of complex geology.
Distributed Dynamic Traffic Modeling and Implementation Oriented Different Levels of Induced Travelers

Directory of Open Access Journals (Sweden)

Yan Liu

2015-01-01

Full Text Available In order to respond to the variable state of traffic network in time, a distributed dynamic traffic assignment strategy is proposed which can improve the intelligent traffic management. The proposed dynamic assignment method is based on utility theory and is oriented to different levels of induced users. A distributed model based on the marginal utility is developed which combines the advantages of both decentralized paradigm and traveler preference, so as to provide efficient and robust dynamic traffic assignment solutions under uncertain network conditions. Then, the solution algorithm including subroute update and subroute calculation is proposed. To testify the effectiveness of the proposed model in optimizing traffic network operation and minimizing traveler’s cost on different induced levels, a sequence numerical experiment is conducted. In the experiment, there are two test environments: one is in different network load conditions and the other is in different deployment coverage of local agents. The numerical results show that the proposed model not only can improve the running efficiency of road network but also can significantly decrease the average travel time.
A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DEFF Research Database (Denmark)

Ding, Tao; Li, Cheng; Huang, Can

2018-01-01

–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....
Location Model for Distribution Centers for Fulfilling Electronic Orders of Fresh Foods under Uncertain Demand

Directory of Open Access Journals (Sweden)

Hao Zhang

2017-01-01

Full Text Available The problem of locating distribution centers for delivering fresh food as a part of electronic commerce is a strategic decision problem for enterprises. This paper establishes a model for locating distribution centers that considers the uncertainty of customer demands for fresh goods in terms of time-sensitiveness and freshness. Based on the methodology of robust optimization in dealing with uncertain problems, this paper optimizes the location model in discrete demand probabilistic scenarios. In this paper, an improved fruit fly optimization algorithm is proposed to solve the distribution center location problem. An example is given to show that the proposed model and algorithm are robust and can effectively handle the complications caused by uncertain demand. The model proposed in this paper proves valuable both theoretically and practically in the selection of locations of distribution centers.
Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability

Science.gov (United States)

Herman, Matthew R.; Nejadhashemi, A. Pouyan; Abouali, Mohammad; Hernandez-Suarez, Juan Sebastian; Daneshvar, Fariborz; Zhang, Zhen; Anderson, Martha C.; Sadeghi, Ali M.; Hain, Christopher R.; Sharifi, Amirreza

2018-01-01

As the global demands for the use of freshwater resources continues to rise, it has become increasingly important to insure the sustainability of this resources. This is accomplished through the use of management strategies that often utilize monitoring and the use of hydrological models. However, monitoring at large scales is not feasible and therefore model applications are becoming challenging, especially when spatially distributed datasets, such as evapotranspiration, are needed to understand the model performances. Due to these limitations, most of the hydrological models are only calibrated for data obtained from site/point observations, such as streamflow. Therefore, the main focus of this paper is to examine whether the incorporation of remotely sensed and spatially distributed datasets can improve the overall performance of the model. In this study, actual evapotranspiration (ETa) data was obtained from the two different sets of satellite based remote sensing data. One dataset estimates ETa based on the Simplified Surface Energy Balance (SSEBop) model while the other one estimates ETa based on the Atmosphere-Land Exchange Inverse (ALEXI) model. The hydrological model used in this study is the Soil and Water Assessment Tool (SWAT), which was calibrated against spatially distributed ETa and single point streamflow records for the Honeyoey Creek-Pine Creek Watershed, located in Michigan, USA. Two different techniques, multi-variable and genetic algorithm, were used to calibrate the SWAT model. Using the aforementioned datasets, the performance of the hydrological model in estimating ETa was improved using both calibration techniques by achieving Nash-Sutcliffe efficiency (NSE) values >0.5 (0.73-0.85), percent bias (PBIAS) values within ±25% (±21.73%), and root mean squared error - observations standard deviation ratio (RSR) values <0.7 (0.39-0.52). However, the genetic algorithm technique was more effective with the ETa calibration while significantly
Value-based distributed generator placements for service quality improvements

Energy Technology Data Exchange (ETDEWEB)

Teng, Jen-Hao; Chen, Chi-Fa [Department of Electrical Engineering, I-Shou University, No. 1, Section 1, Syuecheng Road, Dashu Township, Kaohsiung Country 840 (Taiwan); Liu, Yi-Hwa [Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei (Taiwan); Chen, Chia-Yen [Department of Computer Science, The University of Auckland (New Zealand)

2007-03-15

Distributed generator (DG) resources are small, self-contained electric generating plants that can provide power to homes, businesses or industrial facilities in distribution feeders. They can be used to reduce power loss and improve service reliability. However, the values of DGs are largely dependent on their types, sizes and locations as they were installed in distribution feeders. A value-based method is proposed in this paper to enhance the reliability and obtain the benefits for DG placement. The benefits of DG placement described in this paper include power cost saving, power loss reduction, and reliability enhancement. The costs of DG placement include the investment, maintenance and operating costs. The proposed value-based method tries to find the best tradeoff between the costs and benefits of DG placement and then find the optimal types of DG and their corresponding locations and sizes in distribution feeders. The derived formulations are solved by a genetic algorithm based method. Test results show that with proper types, sizes and installation site selection, DG placement can be used to improve system reliability, reduce customer interruption costs and save power cost; as well as enabling electric utilities to obtain the maximal economical benefits. (author)
Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model.

Science.gov (United States)

Yilmaz, Hatice; Yilmaz, Osman Yalçın; Akyüz, Yaşar Feyza

2017-02-01

Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium , an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of M. latifolium . Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdağı Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine-scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species' distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine-scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.
A distributed computing model for telemetry data processing

Science.gov (United States)

Barry, Matthew R.; Scott, Kevin L.; Weismuller, Steven P.

1994-05-01

We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.

A distributed computing model for telemetry data processing

Science.gov (United States)

Barry, Matthew R.; Scott, Kevin L.; Weismuller, Steven P.

1994-01-01

We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.
Comparative Distributions of Hazard Modeling Analysis

Directory of Open Access Journals (Sweden)

Rana Abdul Wajid

2006-07-01

Full Text Available In this paper we present the comparison among the distributions used in hazard analysis. Simulation technique has been used to study the behavior of hazard distribution modules. The fundamentals of Hazard issues are discussed using failure criteria. We present the flexibility of the hazard modeling distribution that approaches to different distributions.
Sample sizes and model comparison metrics for species distribution models

Science.gov (United States)

B.B. Hanberry; H.S. He; D.C. Dey

2012-01-01

Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....
Improved modelling of independent parton hadronization

International Nuclear Information System (INIS)

Biddulph, P.; Thompson, G.

1989-01-01

A modification is proposed to current versions of the Field-Feynman ansatz for the hadronization of a quark in Monte Carlo models of QCD interactions. This faster-running algorithm has no more parameters and imposes a better degree of energy conservation. It results in naturally introducing a limitation of the transverse momentum distribution, similar to the experimentally observed ''seagull'' effect. There is now a much improved conservation of quantum numbers between the original parton and resultant hadrons, and the momentum of the emitted parton is better preserved in the summed momentum vectors of the final state particles. (orig.)
Mathematical Models for Room Air Distribution

DEFF Research Database (Denmark)

Nielsen, Peter V.

1982-01-01

A number of different models on the air distribution in rooms are introduced. This includes the throw model, a model on penetration length of a cold wall jet and a model for maximum velocity in the dimensioning of an air distribution system in highly loaded rooms and shows that the amount of heat...... removed from the room at constant penetration length is proportional to the cube of the velocities in the occupied zone. It is also shown that a large number of diffusers increases the amount of heat which may be removed without affecting the thermal conditions. Control strategies for dual duct and single...... duct systems are given and the paper is concluded by mentioning a computer-based prediction method which gives the velocity and temperature distribution in the whole room....
Simultaneous allocation of distributed resources using improved teaching learning based optimization

International Nuclear Information System (INIS)

Kanwar, Neeraj; Gupta, Nikhil; Niazi, K.R.; Swarnkar, Anil

2015-01-01

Highlights: • Simultaneous allocation of distributed energy resources in distribution networks. • Annual energy loss reduction is optimized using a multi-level load profile. • A new penalty factor approach is suggested to check node voltage deviations. • An improved TLBO is proposed by suggesting several modifications in standard TLBO. • An intelligent search is proposed to enhance the performance of solution technique. - Abstract: Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results
Accelerated Electromechanical Modeling of a Distributed Internal Combustion Engine Generator Unit

Directory of Open Access Journals (Sweden)

Serhiy V. Bozhko

2012-07-01

Full Text Available Distributed generation with a combustion engine prime mover is still widely used to supply electric power in a variety of applications. These applications range from backup power supply systems and combined wind-diesel generation to providing power in places where grid connection is either technically impractical or financially uneconomic. Modelling of such systems as a whole is extremely difficult due to the long-time load profiles needed and the computational difficulty of including small time-constant electrical dynamics with large time-constant mechanical dynamics. This paper presents the development of accelerated, reduced-order models of a distributed internal combustions engine generator unit. Overall these models are shown to achieve a massive improvement in the computational time required for long-time simulations while also achieving an extremely high level of dynamic accuracy. It is demonstrated how these models are derived, used and verified against benchmark models created using established techniques. Throughout the paper the modelling set as a whole, including multi level detail, is presented, detailed and finally summarised into a crucial tool for general system investigation and multiple target optimisation.
Effects of naloxone distribution to likely bystanders: Results of an agent-based model.

Science.gov (United States)

Keane, Christopher; Egan, James E; Hawk, Mary

2018-05-01

Opioid overdose deaths in the US rose dramatically in the past 16 years, creating an urgent national health crisis with no signs of immediate relief. In 2017, the President of the US officially declared the opioid epidemic to be a national emergency and called for additional resources to respond to the crisis. Distributing naloxone to community laypersons and people at high risk for opioid overdose can prevent overdose death, but optimal distribution methods have not yet been pinpointed. We conducted a sequential exploratory mixed methods design using qualitative data to inform an agent-based model to improve understanding of effective community-based naloxone distribution to laypersons to reverse opioid overdose. The individuals in the model were endowed with cognitive and behavioral variables and accessed naloxone via community sites such as pharmacies, hospitals, and urgent-care centers. We compared overdose deaths over a simulated 6-month period while varying the number of distribution sites (0, 1, and 10) and number of kits given to individuals per visit (1 versus 10). Specifically, we ran thirty simulations for each of thirteen distribution models and report average overdose deaths for each. The baseline comparator was no naloxone distribution. Our simulations explored the effects of distribution through syringe exchange sites with and without secondary distribution, which refers to distribution of naloxone kits by laypersons within their social networks and enables ten additional laypersons to administer naloxone to reverse opioid overdose. Our baseline model with no naloxone distribution predicted there would be 167.9 deaths in a six month period. A single distribution site, even with 10 kits picked up per visit, decreased overdose deaths by only 8.3% relative to baseline. However, adding secondary distribution through social networks to a single site resulted in 42.5% fewer overdose deaths relative to baseline. That is slightly higher than the 39
Using Unified Modelling Language (UML) as a process-modelling technique for clinical-research process improvement.

Science.gov (United States)

Kumarapeli, P; De Lusignan, S; Ellis, T; Jones, B

2007-03-01

The Primary Care Data Quality programme (PCDQ) is a quality-improvement programme which processes routinely collected general practice computer data. Patient data collected from a wide range of different brands of clinical computer systems are aggregated, processed, and fed back to practices in an educational context to improve the quality of care. Process modelling is a well-established approach used to gain understanding and systematic appraisal, and identify areas of improvement of a business process. Unified modelling language (UML) is a general purpose modelling technique used for this purpose. We used UML to appraise the PCDQ process to see if the efficiency and predictability of the process could be improved. Activity analysis and thinking-aloud sessions were used to collect data to generate UML diagrams. The UML model highlighted the sequential nature of the current process as a barrier for efficiency gains. It also identified the uneven distribution of process controls, lack of symmetric communication channels, critical dependencies among processing stages, and failure to implement all the lessons learned in the piloting phase. It also suggested that improved structured reporting at each stage - especially from the pilot phase, parallel processing of data and correctly positioned process controls - should improve the efficiency and predictability of research projects. Process modelling provided a rational basis for the critical appraisal of a clinical data processing system; its potential maybe underutilized within health care.
FCT: a fully-distributed context-aware trust model for location based service recommendation

Institute of Scientific and Technical Information of China (English)

Zhiquan LIU; Jianfeng MA; Zhongyuan JIANG; Yinbin MIAO

2017-01-01

With the popularity of location based service (LBS),a vast number of trust medels for LBS recommendation (LBSR) have been proposed.These trust models are centralized in essence,and the trusted third party may collude with malicious service providers or cause the single-point failure problem.This work improves the classic certified reputation (CR) model and proposes a novel fully-distributed context-aware trust (FCT) model for LBSR.Recommendation operations are conducted by service providers directly and the trusted third party is no longer required in our FCT model.Besides,our FCT model also supports the movements of service providers due to its self-certified characteristic.Moreover,for easing the collusion attack and value imbalance attack,we comprehensively consider four kinds of factor weights,namely number,time decay,preference and context weights.Finally,a fully-distributed service recommendation scenario is deployed,and comprehensive experiments and analysis are conducted.The results indicate that our FCT model significantly outperforms the CR model in terms of the robustness against the collusion attack and value imbalance attack,as well as the service recommendation performance in improving the successful trading rates of honest service providers and reducing the risks of trading with malicious service providers.
Improved side information generation for distributed video coding

DEFF Research Database (Denmark)

Huang, Xin; Forchhammer, Søren

2008-01-01

As a new coding paradigm, distributed video coding (DVC) deals with lossy source coding using side information to exploit the statistics at the decoder to reduce computational demands at the encoder. The performance of DVC highly depends on the quality of side information. With a better side...... information generation method, fewer bits will be requested from the encoder and more reliable decoded frames will be obtained. In this paper, a side information generation method is introduced to further improve the rate-distortion (RD) performance of transform domain distributed video coding. This algorithm...
Improved Root Normal Size Distributions for Liquid Atomization

Science.gov (United States)

2015-11-01

ANSI Std. Z39.18 j CONVERSION TABLE Conversion Factors for U.S. Customary to metric (SI) units of measurement. MULTIPLY BY TO...Gray (Gy) coulomb /kilogram (C/kg) second (s) kilogram (kg) kilo pascal (kPa) 1 Improved Root Normal Size Distributions for Liquid
An Improved Distribution Policy with a Maintenance Aspect for an Urban Logistic Problem

Directory of Open Access Journals (Sweden)

Nadia Ndhaief

2017-07-01

Full Text Available In this paper, we present an improved distribution plan supporting an urban distribution center (UDC to solve the last mile problem of urban freight. This is motivated by the need of UDCs to satisfy daily demand in time under a high service level in allocated urban areas. Moreover, these demands could not be satisfied in individual cases because the delivery rate can be less than daily demand and/or affected by random failure or maintenance actions of vehicles. The scope of our work is to focus on a UDC, which needs to satisfy demands in a finite horizon. To that end, we consider a distribution policy on two sequential plans, a distribution plan correlated to a maintenance plan using a subcontracting strategy with several potential urban distribution centers (UDCs and performing preventive maintenance to ensure deliveries for their allocated urban area. The choice of subcontractor will depend on distance, environmental and availability criteria. In doing so, we define a mathematical model for searching the best distribution and maintenance plans using a subcontracting strategy. Moreover, we consider delay for the next periods with an expensive penalty. Finally, we present a numerical example illustrating the benefits of our approach.
An Improved QTM Subdivision Model with Approximate Equal-area

Directory of Open Access Journals (Sweden)

ZHAO Xuesheng

2016-01-01

Full Text Available To overcome the defect of large area deformation in the traditional QTM subdivision model, an improved subdivision model is proposed which based on the “parallel method” and the thought of the equal area subdivision with changed-longitude-latitude. By adjusting the position of the parallel, this model ensures that the grid area between two adjacent parallels combined with no variation, so as to control area variation and variation accumulation of the QTM grid. The experimental results show that this improved model not only remains some advantages of the traditional QTM model(such as the simple calculation and the clear corresponding relationship with longitude/latitude grid, etc, but also has the following advantages: ①this improved model has a better convergence than the traditional one. The ratio of area_max/min finally converges to 1.38, far less than 1.73 of the “parallel method”; ②the grid units in middle and low latitude regions have small area variations and successive distributions; meanwhile, with the increase of subdivision level, the grid units with large variations gradually concentrate to the poles; ③the area variation of grid unit will not cumulate with the increasing of subdivision level.
Improvements to the RADIOM non-LTE model

Science.gov (United States)

Busquet, M.; Colombant, D.; Klapisch, M.; Fyfe, D.; Gardner, J.

2009-12-01

In 1993, we proposed the RADIOM model [M. Busquet, Phys. Fluids 85 (1993) 4191] where an ionization temperature T z is used to derive non-LTE properties from LTE data. T z is obtained from an "extended Saha equation" where unbalanced transitions, like radiative decay, give the non-LTE behavior. Since then, major improvements have been made. T z has been shown to be more than a heuristic value, but describes the actual distribution of excited and ionized states and can be understood as an "effective temperature". Therefore we complement the extended Saha equation by introducing explicitly the auto-ionization/dielectronic capture. Also we use the SCROLL model to benchmark the computed values of T z.
Using numerical model simulations to improve the understanding of micro-plastic distribution and pathways in the marine environment

NARCIS (Netherlands)

Hardesty, Britta D.; Harari, Joseph; Isobe, Atsuhiko; Lebreton, Laurent; Maximenko, Nikolai; Potemra, Jim; van Sebille, Erik; Vethaak, A.Dick; Wilcox, Chris

2017-01-01

Numerical modeling is one of the key tools with which we can gain insight into the distribution of marine litter, especially micro-plastics. Over the past decade, a series of numerical simulations have been constructed that specifically target floating marine litter, based on ocean models of various
Evaluating Domestic Hot Water Distribution System Options With Validated Analysis Models

Energy Technology Data Exchange (ETDEWEB)

Weitzel, E.; Hoeschele, M.

2014-09-01

A developing body of work is forming that collects data on domestic hot water consumption, water use behaviors, and energy efficiency of various distribution systems. A full distribution system developed in TRNSYS has been validated using field monitoring data and then exercised in a number of climates to understand climate impact on performance. This study builds upon previous analysis modelling work to evaluate differing distribution systems and the sensitivities of water heating energy and water use efficiency to variations of climate, load, distribution type, insulation and compact plumbing practices. Overall 124 different TRNSYS models were simulated. Of the configurations evaluated, distribution losses account for 13-29% of the total water heating energy use and water use efficiency ranges from 11-22%. The base case, an uninsulated trunk and branch system sees the most improvement in energy consumption by insulating and locating the water heater central to all fixtures. Demand recirculation systems are not projected to provide significant energy savings and in some cases increase energy consumption. Water use is most efficient with demand recirculation systems, followed by the insulated trunk and branch system with a central water heater. Compact plumbing practices and insulation have the most impact on energy consumption (2-6% for insulation and 3-4% per 10 gallons of enclosed volume reduced). The results of this work are useful in informing future development of water heating best practices guides as well as more accurate (and simulation time efficient) distribution models for annual whole house simulation programs.
Modeling a Distributed Power Flow Controller with a PEM Fuel Cell for Power Quality Improvement

Directory of Open Access Journals (Sweden)

J. Chakravorty

2018-02-01

Full Text Available Electrical power demand is increasing at a relatively fast rate over the last years. Because of this increasing demand the power system is becoming very complex. Both electric utilities and end users of electric power are becoming increasingly concerned about power quality. This paper presents a new concept of distributed power flow controller (DPFC, which has been implemented with a proton exchange membrane (PEM fuel cell. In this paper, a PEM fuel cell has been simulated in Simulink/MATLAB and then has been used in the proposed DPFC model. The new proposed DPFC model has been tested on a IEEE 30 bus system.
Data-driven modeling and real-time distributed control for energy efficient manufacturing systems

International Nuclear Information System (INIS)

Zou, Jing; Chang, Qing; Arinez, Jorge; Xiao, Guoxian

2017-01-01

As manufacturers face the challenges of increasing global competition and energy saving requirements, it is imperative to seek out opportunities to reduce energy waste and overall cost. In this paper, a novel data-driven stochastic manufacturing system modeling method is proposed to identify and predict energy saving opportunities and their impact on production. A real-time distributed feedback production control policy, which integrates the current and predicted system performance, is established to improve the overall profit and energy efficiency. A case study is presented to demonstrate the effectiveness of the proposed control policy. - Highlights: • A data-driven stochastic manufacturing system model is proposed. • Real-time system performance and energy saving opportunity identification method is developed. • Prediction method for future potential system performance and energy saving opportunity is developed. • A real-time distributed feedback control policy is established to improve energy efficiency and overall system profit.
A Sustainability-Oriented Multiobjective Optimization Model for Siting and Sizing Distributed Generation Plants in Distribution Systems

Directory of Open Access Journals (Sweden)

Guang Chen

2013-01-01

Full Text Available This paper proposes a sustainability-oriented multiobjective optimization model for siting and sizing DG plants in distribution systems. Life cycle exergy (LCE is used as a unified indicator of the entire system’s environmental sustainability, and it is optimized as an objective function in the model. Other two objective functions include economic cost and expected power loss. Chance constraints are used to control the operation risks caused by the uncertain power loads and renewable energies. A semilinearized simulation method is proposed and combined with the Latin hypercube sampling (LHS method to improve the efficiency of probabilistic load flow (PLF analysis which is repeatedly performed to verify the chance constraints. A numerical study based on the modified IEEE 33-node system is performed to verify the proposed method. Numerical results show that the proposed semilinearized simulation method reduces about 93.3% of the calculation time of PLF analysis and guarantees satisfying accuracy. The results also indicate that benefits for environmental sustainability of using DG plants can be effectively reflected by the proposed model which helps the planner to make rational decision towards sustainable development of the distribution system.

Distributed Video Coding: Iterative Improvements

DEFF Research Database (Denmark)

Luong, Huynh Van

Nowadays, emerging applications such as wireless visual sensor networks and wireless video surveillance are requiring lightweight video encoding with high coding efficiency and error-resilience. Distributed Video Coding (DVC) is a new coding paradigm which exploits the source statistics...... and noise modeling and also learn from the previous decoded Wyner-Ziv (WZ) frames, side information and noise learning (SING) is proposed. The SING scheme introduces an optical flow technique to compensate the weaknesses of the block based SI generation and also utilizes clustering of DCT blocks to capture...... cross band correlation and increase local adaptivity in noise modeling. During decoding, the updated information is used to iteratively reestimate the motion and reconstruction in the proposed motion and reconstruction reestimation (MORE) scheme. The MORE scheme not only reestimates the motion vectors...
Water Distribution and Removal Model

International Nuclear Information System (INIS)

Y. Deng; N. Chipman; E.L. Hardin

2005-01-01

The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD and R) Model; (2) EBS Physical and Chemical Environment (P and CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD and R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment
Water Distribution and Removal Model

Energy Technology Data Exchange (ETDEWEB)

Y. Deng; N. Chipman; E.L. Hardin

2005-08-26

The design of the Yucca Mountain high level radioactive waste repository depends on the performance of the engineered barrier system (EBS). To support the total system performance assessment (TSPA), the Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is developed to describe the thermal, mechanical, chemical, hydrological, biological, and radionuclide transport processes within the emplacement drifts, which includes the following major analysis/model reports (AMRs): (1) EBS Water Distribution and Removal (WD&R) Model; (2) EBS Physical and Chemical Environment (P&CE) Model; (3) EBS Radionuclide Transport (EBS RNT) Model; and (4) EBS Multiscale Thermohydrologic (TH) Model. Technical information, including data, analyses, models, software, and supporting documents will be provided to defend the applicability of these models for their intended purpose of evaluating the postclosure performance of the Yucca Mountain repository system. The WD&R model ARM is important to the site recommendation. Water distribution and removal represents one component of the overall EBS. Under some conditions, liquid water will seep into emplacement drifts through fractures in the host rock and move generally downward, potentially contacting waste packages. After waste packages are breached by corrosion, some of this seepage water will contact the waste, dissolve or suspend radionuclides, and ultimately carry radionuclides through the EBS to the near-field host rock. Lateral diversion of liquid water within the drift will occur at the inner drift surface, and more significantly from the operation of engineered structures such as drip shields and the outer surface of waste packages. If most of the seepage flux can be diverted laterally and removed from the drifts before contacting the wastes, the release of radionuclides from the EBS can be controlled, resulting in a proportional reduction in dose release at the accessible environment. The purposes
An integrated logit model for contamination event detection in water distribution systems.

Science.gov (United States)

Housh, Mashor; Ostfeld, Avi

2015-05-15

The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. Copyright © 2015 Elsevier Ltd. All rights reserved.
Likelihood Inference of Nonlinear Models Based on a Class of Flexible Skewed Distributions

Directory of Open Access Journals (Sweden)

Xuedong Chen

2014-01-01

Full Text Available This paper deals with the issue of the likelihood inference for nonlinear models with a flexible skew-t-normal (FSTN distribution, which is proposed within a general framework of flexible skew-symmetric (FSS distributions by combining with skew-t-normal (STN distribution. In comparison with the common skewed distributions such as skew normal (SN, and skew-t (ST as well as scale mixtures of skew normal (SMSN, the FSTN distribution can accommodate more flexibility and robustness in the presence of skewed, heavy-tailed, especially multimodal outcomes. However, for this distribution, a usual approach of maximum likelihood estimates based on EM algorithm becomes unavailable and an alternative way is to return to the original Newton-Raphson type method. In order to improve the estimation as well as the way for confidence estimation and hypothesis test for the parameters of interest, a modified Newton-Raphson iterative algorithm is presented in this paper, based on profile likelihood for nonlinear regression models with FSTN distribution, and, then, the confidence interval and hypothesis test are also developed. Furthermore, a real example and simulation are conducted to demonstrate the usefulness and the superiority of our approach.
Parameter Identification of the 2-Chlorophenol Oxidation Model Using Improved Differential Search Algorithm

Directory of Open Access Journals (Sweden)

Guang-zhou Chen

2015-01-01

Full Text Available Parameter identification plays a crucial role for simulating and using model. This paper firstly carried out the sensitivity analysis of the 2-chlorophenol oxidation model in supercritical water using the Monte Carlo method. Then, to address the nonlinearity of the model, two improved differential search (DS algorithms were proposed to carry out the parameter identification of the model. One strategy is to adopt the Latin hypercube sampling method to replace the uniform distribution of initial population; the other is to combine DS with simplex method. The results of sensitivity analysis reveal the sensitivity and the degree of difficulty identified for every model parameter. Furthermore, the posteriori probability distribution of parameters and the collaborative relationship between any two parameters can be obtained. To verify the effectiveness of the improved algorithms, the optimization performance of improved DS in kinetic parameter estimation is studied and compared with that of the basic DS algorithm, differential evolution, artificial bee colony optimization, and quantum-behaved particle swarm optimization. And the experimental results demonstrate that the DS with the Latin hypercube sampling method does not present better performance, while the hybrid methods have the advantages of strong global search ability and local search ability and are more effective than the other algorithms.
Performance measurement, modeling, and evaluation of integrated concurrency control and recovery algorithms in distributed data base systems

Energy Technology Data Exchange (ETDEWEB)

Jenq, B.C.

1986-01-01

The performance evaluation of integrated concurrency-control and recovery mechanisms for distributed data base systems is studied using a distributed testbed system. In addition, a queueing network model was developed to analyze the two phase locking scheme in the distributed testbed system. The combination of testbed measurement and analytical modeling provides an effective tool for understanding the performance of integrated concurrency control and recovery algorithms in distributed database systems. The design and implementation of the distributed testbed system, CARAT, are presented. The concurrency control and recovery algorithms implemented in CARAT include: a two phase locking scheme with distributed deadlock detection, a distributed version of optimistic approach, before-image and after-image journaling mechanisms for transaction recovery, and a two-phase commit protocol. Many performance measurements were conducted using a variety of workloads. A queueing network model is developed to analyze the performance of the CARAT system using the two-phase locking scheme with before-image journaling. The combination of testbed measurements and analytical modeling provides significant improvements in understanding the performance impacts of the concurrency control and recovery algorithms in distributed database systems.
Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

Science.gov (United States)

Karmeshu; Gupta, Varun; Kadambari, K V

2011-06-01

A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.
A Complex Network Approach to Distributional Semantic Models.

Directory of Open Access Journals (Sweden)

Akira Utsumi

Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.
Ensemble Analysis of Variational Assimilation of Hydrologic and Hydrometeorological Data into Distributed Hydrologic Model

Science.gov (United States)

Lee, H.; Seo, D.; Koren, V.

2008-12-01

A prototype 4DVAR (four-dimensional variational) data assimilator for gridded Sacramento soil-moisture accounting and kinematic-wave routing models in the Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) has been developed. The prototype assimilates streamflow and in-situ soil moisture data and adjusts gridded precipitation and climatological potential evaporation data to reduce uncertainty in the model initial conditions for improved monitoring and prediction of streamflow and soil moisture at the outlet and interior locations within the catchment. Due to large degrees of freedom involved, data assimilation (DA) into distributed hydrologic models is complex. To understand and assess sensitivity of the performance of DA to uncertainties in the model initial conditions and in the data, two synthetic experiments have been carried out in an ensemble framework. Results from the synthetic experiments shed much light on the potential and limitations with DA into distributed models. For initial real-world assessment, the prototype DA has also been applied to the headwater basin at Eldon near the Oklahoma-Arkansas border. We present these results and describe the next steps.
Stochastic frontier model approach for measuring stock market efficiency with different distributions.

Science.gov (United States)

Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.
Stochastic frontier model approach for measuring stock market efficiency with different distributions.

Directory of Open Access Journals (Sweden)

Md Zobaer Hasan

Full Text Available The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.
Framing Feedback for School Improvement around Distributed Leadership

Science.gov (United States)

Kelley, Carolyn; Dikkers, Seann

2016-01-01

Purpose: The purpose of this article is to examine the utility of framing formative feedback to improve school leadership with a focus on task-based evaluation of distributed leadership rather than on role-based evaluation of an individual leader. Research Methods/Approach: Using data from research on the development of the Comprehensive…
Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution

Directory of Open Access Journals (Sweden)

Emmanuel Kidando

2017-01-01

Full Text Available Multistate models, that is, models with more than two distributions, are preferred over single-state probability models in modeling the distribution of travel time. Literature review indicated that the finite multistate modeling of travel time using lognormal distribution is superior to other probability functions. In this study, we extend the finite multistate lognormal model of estimating the travel time distribution to unbounded lognormal distribution. In particular, a nonparametric Dirichlet Process Mixture Model (DPMM with stick-breaking process representation was used. The strength of the DPMM is that it can choose the number of components dynamically as part of the algorithm during parameter estimation. To reduce computational complexity, the modeling process was limited to a maximum of six components. Then, the Markov Chain Monte Carlo (MCMC sampling technique was employed to estimate the parameters’ posterior distribution. Speed data from nine links of a freeway corridor, aggregated on a 5-minute basis, were used to calculate the corridor travel time. The results demonstrated that this model offers significant flexibility in modeling to account for complex mixture distributions of the travel time without specifying the number of components. The DPMM modeling further revealed that freeway travel time is characterized by multistate or single-state models depending on the inclusion of onset and offset of congestion periods.
The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

Energy Technology Data Exchange (ETDEWEB)

Chen, Y W [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Zhang, L F [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Huang, J P [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China)

2007-07-20

By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property.
The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

International Nuclear Information System (INIS)

Chen, Y W; Zhang, L F; Huang, J P

2007-01-01

By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property
Distribution load estimation (DLE)

Energy Technology Data Exchange (ETDEWEB)

Seppaelae, A; Lehtonen, M [VTT Energy, Espoo (Finland)

1998-08-01

The load research has produced customer class load models to convert the customers` annual energy consumption to hourly load values. The reliability of load models applied from a nation-wide sample is limited in any specific network because many local circumstances are different from utility to utility and time to time. Therefore there is a need to find improvements to the load models or, in general, improvements to the load estimates. In Distribution Load Estimation (DLE) the measurements from the network are utilized to improve the customer class load models. The results of DLE will be new load models that better correspond to the loading of the distribution network but are still close to the original load models obtained by load research. The principal data flow of DLE is presented
Benchmarking of Generation and Distribution Units in Nepal Using Modified DEA Models

Science.gov (United States)

Jha, Deependra Kumar; Yorino, Naoto; Zoka, Yoshifumi

This paper analyzes the performance of Nepalese Electricity Supply Industry (ESI) by investigating the relative operational efficiencies of the generating stations as well as the Distribution Centers (DCs) of the Integrated Nepal Power System (INPS). Nepal Electricity Authority (NEA), a state owned utility, owns and operates the INPS. Performance evaluation of both generation and distribution systems is carried out by formulating suitable weight restriction type Data Envelopment Analysis (DEA) models. The models include a wide range of inputs and outputs representing essence of the respective processes. Decision maker's preferences as well as available quantitative information associated with the operation of the Decision Making Units (DMUs) are judiciously incorporated in the DEA models. The proposed models are realized through execution of computer programs written in General Algebraic Modeling Systems (GAMS) and the results obtained are thus compared against those from the conventional DEA models. Sensitivity analysis is performed in order to check the robustness of the results as well as to identify the improvement directions for DMUs. Ranking of the DMUs has been presented based on their average overall efficiency scores.
Distributed SLAM Using Improved Particle Filter for Mobile Robot Localization

Directory of Open Access Journals (Sweden)

Fujun Pei

2014-01-01

Full Text Available The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle filter use in distributed SLAM was improved in two aspects. First, we improved the important function of the local filters in particle filter. The adaptive values were used to replace a set of constants in the computational process of importance function, which improved the robustness of the particle filter. Second, an information fusion method was proposed by mixing the innovation method and the number of effective particles method, which combined the advantages of these two methods. And this paper extends the previously known convergence results for particle filter to prove that improved particle filter converges to the optimal filter in mean square as the number of particles goes to infinity. The experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system to have a better tolerance and robustness.
Modeling error distributions of growth curve models through Bayesian methods.

Science.gov (United States)

Zhang, Zhiyong

2016-06-01

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.

Using internal discharge data in a distributed conceptual model to reduce uncertainty in streamflow simulations

Science.gov (United States)

Guerrero, J.; Halldin, S.; Xu, C.; Lundin, L.

2011-12-01

Distributed hydrological models are important tools in water management as they account for the spatial variability of the hydrological data, as well as being able to produce spatially distributed outputs. They can directly incorporate and assess potential changes in the characteristics of our basins. A recognized problem for models in general is equifinality, which is only exacerbated for distributed models who tend to have a large number of parameters. We need to deal with the fundamentally ill-posed nature of the problem that such models force us to face, i.e. a large number of parameters and very few variables that can be used to constrain them, often only the catchment discharge. There is a growing but yet limited literature showing how the internal states of a distributed model can be used to calibrate/validate its predictions. In this paper, a distributed version of WASMOD, a conceptual rainfall runoff model with only three parameters, combined with a routing algorithm based on the high-resolution HydroSHEDS data was used to simulate the discharge in the Paso La Ceiba basin in Honduras. The parameter space was explored using Monte-Carlo simulations and the region of space containing the parameter-sets that were considered behavioral according to two different criteria was delimited using the geometric concept of alpha-shapes. The discharge data from five internal sub-basins was used to aid in the calibration of the model and to answer the following questions: Can this information improve the simulations at the outlet of the catchment, or decrease their uncertainty? Also, after reducing the number of model parameters needing calibration through sensitivity analysis: Is it possible to relate them to basin characteristics? The analysis revealed that in most cases the internal discharge data can be used to reduce the uncertainty in the discharge at the outlet, albeit with little improvement in the overall simulation results.
A penalized framework for distributed lag non-linear models.

Science.gov (United States)

Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G

2017-09-01

Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

2018-05-01

A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.
A Model of U.S. Commercial Distributed Generation Adoption

Energy Technology Data Exchange (ETDEWEB)

LaCommare, Kristina Hamachi; Ryan Firestone; Zhou, Nan; Maribu,Karl; Marnay, Chris

2006-01-10

Small-scale (100 kW-5 MW) on-site distributed generation (DG) economically driven by combined heat and power (CHP) applications and, in some cases, reliability concerns will likely emerge as a common feature of commercial building energy systems over the next two decades. Forecasts of DG adoption published by the Energy Information Administration (EIA) in the Annual Energy Outlook (AEO) are made using the National Energy Modeling System (NEMS), which has a forecasting module that predicts the penetration of several possible commercial building DG technologies over the period 2005-2025. NEMS is also used for estimating the future benefits of Department of Energy research and development used in support of budget requests and management decisionmaking. The NEMS approach to modeling DG has some limitations, including constraints on the amount of DG allowed for retrofits to existing buildings and a small number of possible sizes for each DG technology. An alternative approach called Commercial Sector Model (ComSeM) is developed to improve the way in which DG adoption is modeled. The approach incorporates load shapes for specific end uses in specific building types in specific regions, e.g., cooling in hospitals in Atlanta or space heating in Chicago offices. The Distributed Energy Resources Customer Adoption Model (DER-CAM) uses these load profiles together with input cost and performance DG technology assumptions to model the potential DG adoption for four selected cities and two sizes of five building types in selected forecast years to 2022. The Distributed Energy Resources Market Diffusion Model (DER-MaDiM) is then used to then tailor the DER-CAM results to adoption projections for the entire U.S. commercial sector for all forecast years from 2007-2025. This process is conducted such that the structure of results are consistent with the structure of NEMS, and can be re-injected into NEMS that can then be used to integrate adoption results into a full forecast.
Modelling and analysis of solar cell efficiency distributions

Science.gov (United States)

Wasmer, Sven; Greulich, Johannes

2017-08-01

We present an approach to model the distribution of solar cell efficiencies achieved in production lines based on numerical simulations, metamodeling and Monte Carlo simulations. We validate our methodology using the example of an industrial feasible p-type multicrystalline silicon “passivated emitter and rear cell” process. Applying the metamodel, we investigate the impact of each input parameter on the distribution of cell efficiencies in a variance-based sensitivity analysis, identifying the parameters and processes that need to be improved and controlled most accurately. We show that if these could be optimized, the mean cell efficiencies of our examined cell process would increase from 17.62% ± 0.41% to 18.48% ± 0.09%. As the method relies on advanced characterization and simulation techniques, we furthermore introduce a simplification that enhances applicability by only requiring two common measurements of finished cells. The presented approaches can be especially helpful for ramping-up production, but can also be applied to enhance established manufacturing.
A model for the distribution channels planning process

NARCIS (Netherlands)

Neves, M.F.; Zuurbier, P.; Campomar, M.C.

2001-01-01

Research of existing literature reveals some models (sequence of steps) for companies that want to plan distribution channels. None of these models uses strong contributions from transaction cost economics, bringing a possibility to elaborate on a "distribution channels planning model", with these
Fire, humans, and climate: modeling distribution dynamics of boreal forest waterbirds.

Science.gov (United States)

Börger, Luca; Nudds, Thomas D

2014-01-01

84 waterbird species breeding on the Ontario Boreal Shield, however, suggested that up to 30 species may instead have altered (short-term) distribution dynamics due to forestry practices. Hence, natural disturbances are critical components of the ecology of the boreal forest and forest practices which aim to approximate them may succeed in allowing the maintenance of the associated species, but improved monitoring and modeling of large-scale boreal forest bird distribution dynamics will be necessary to resolve existing uncertainties, especially on less-common species.
The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model

Directory of Open Access Journals (Sweden)

Shanshan Wang

2017-12-01

Full Text Available In cities’ policy-making, it is a hot issue to grasp the determinants of carbon dioxide emission in Chinese cities. And the common method is to use the STIRPAT model, where its coefficients represent the influence intensity of each determinants of carbon emission. However, less work discusses estimation accuracy, especially in the framework of non-normal distribution and heterogeneity among cities’ emission. To improve the estimation accuracy, this paper employs a new method to estimate the STIRPAT model. The method uses a mixture of Asymmetric Laplace distributions (ALDs to approximate the true distribution of the error term. Meantime, a designed two-layer EM algorithm is used to obtain estimators. We test the robustness via the comparison results of five different models. We find that the ALDs Mixture Model is more reliable the others. Further, a significant Kuznets curve relationship is identified in China.
Asymmetric fan beams (AFB) for improvement of the craniocaudal dose distribution in helical tomotherapy delivery

International Nuclear Information System (INIS)

Gladwish, Adam; Kron, Tomas; McNiven, Andrea; Bauman, Glenn; Van Dyk, Jake

2004-01-01

Helical tomotherapy (HT) is a novel radiotherapy technique that utilizes intensity modulated fan beams that deliver highly conformal dose distributions in a helical beam trajectory. The most significant limitation in dose delivery with a constant fan beam thickness (FBT) is the penumbra width of the dose distribution in the craniocaudal direction, which is equivalent to the FBT. We propose to employ a half-blocked fan beam at start and stop location to reduce the penumbra width by half. By opening the jaw slowly during the helical delivery until the desired FBT is achieved it is possible to create a sharper edge in the superior and inferior direction from the target. The technique was studied using a tomotherapy beam model implemented on a commercial treatment planning system (Theraplan Plus V3.0). It was demonstrated that the dose distribution delivered using a 25 mm fan beam can be improved significantly, to reduce the dose to normal structures located superiorly and inferiorly of the target. Dosimetry for this technique is straightforward down to a FBT of 15 mm and implementation should be simple as no changes in couch movement are required compared to a standard HT delivery. We conclude that the use of asymmetric collimated fan beams for the start and stop of the helical tomotherapeutic dose delivery has the potential of significantly improving the dose distribution in helical tomotherapy
The Agriculture Model Intercomparison and Improvement Project (AgMIP) (Invited)

Science.gov (United States)

Rosenzweig, C.

2010-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and world agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Historical period results will spur model improvement and interaction among major modeling groups, while future period results will lead directly to tests of adaptation and mitigation strategies across a range of scales. AgMIP will consist of a multi-scale impact assessment utilizing the latest methods for climate and agricultural scenario generation. Scenarios and modeling protocols will be distributed on the web, and multi-model results will be collated and analyzed to ensure the widest possible coverage of agricultural crops and regions. AgMIP will place regional changes in agricultural production in a global context that reflects new trading opportunities, imbalances, and shortages in world markets resulting from climate change and other driving forces for food supply. Such projections are essential inputs from the Vulnerability, Impacts, and Adaptation (VIA) research community to the Intergovernmental Panel on Climate Change Fifth Assessment (AR5), now underway, and the UN Framework Convention on Climate Change. They will set the context for local-scale vulnerability and adaptation studies, supply test scenarios for national-scale development of trade policy instruments, provide critical information on changing supply and demand for water resources, and elucidate interactive effects of climate change and land use change. AgMIP will not only provide crucially-needed new global estimates of how climate change will affect food supply and hunger in the
Mathematical Models for Room Air Distribution - Addendum

DEFF Research Database (Denmark)

Nielsen, Peter V.

1982-01-01

A number of different models on the air distribution in rooms are introduced. This includes the throw model, a model on penetration length of a cold wall jet and a model for maximum velocity in the dimensioning of an air distribution system in highly loaded rooms and shows that the amount of heat...... removed from the room at constant penetration length is proportional to the cube of the velocities in the occupied zone. It is also shown that a large number of diffusers increases the amount of heat which may be removed without affecting the thermal conditions. Control strategies for dual duct and single...... duct systems are given and the paper is concluded by mentioning a computer-based prediction method which gives the velocity and temperature distribution in the whole room....
DYNAMIC SOFTWARE TESTING MODELS WITH PROBABILISTIC PARAMETERS FOR FAULT DETECTION AND ERLANG DISTRIBUTION FOR FAULT RESOLUTION DURATION

Directory of Open Access Journals (Sweden)

A. D. Khomonenko

2016-07-01

Full Text Available Subject of Research.Software reliability and test planning models are studied taking into account the probabilistic nature of error detection and discovering. Modeling of software testing enables to plan the resources and final quality at early stages of project execution. Methods. Two dynamic models of processes (strategies are suggested for software testing, using error detection probability for each software module. The Erlang distribution is used for arbitrary distribution approximation of fault resolution duration. The exponential distribution is used for approximation of fault resolution discovering. For each strategy, modified labeled graphs are built, along with differential equation systems and their numerical solutions. The latter makes it possible to compute probabilistic characteristics of the test processes and states: probability states, distribution functions for fault detection and elimination, mathematical expectations of random variables, amount of detected or fixed errors. Evaluation of Results. Probabilistic characteristics for software development projects were calculated using suggested models. The strategies have been compared by their quality indexes. Required debugging time to achieve the specified quality goals was calculated. The calculation results are used for time and resources planning for new projects. Practical Relevance. The proposed models give the possibility to use the reliability estimates for each individual module. The Erlang approximation removes restrictions on the use of arbitrary time distribution for fault resolution duration. It improves the accuracy of software test process modeling and helps to take into account the viability (power of the tests. With the use of these models we can search for ways to improve software reliability by generating tests which detect errors with the highest probability.
Independent tasks scheduling in cloud computing via improved estimation of distribution algorithm

Science.gov (United States)

Sun, Haisheng; Xu, Rui; Chen, Huaping

2018-04-01

To minimize makespan for scheduling independent tasks in cloud computing, an improved estimation of distribution algorithm (IEDA) is proposed to tackle the investigated problem in this paper. Considering that the problem is concerned with multi-dimensional discrete problems, an improved population-based incremental learning (PBIL) algorithm is applied, which the parameter for each component is independent with other components in PBIL. In order to improve the performance of PBIL, on the one hand, the integer encoding scheme is used and the method of probability calculation of PBIL is improved by using the task average processing time; on the other hand, an effective adaptive learning rate function that related to the number of iterations is constructed to trade off the exploration and exploitation of IEDA. In addition, both enhanced Max-Min and Min-Min algorithms are properly introduced to form two initial individuals. In the proposed IEDA, an improved genetic algorithm (IGA) is applied to generate partial initial population by evolving two initial individuals and the rest of initial individuals are generated at random. Finally, the sampling process is divided into two parts including sampling by probabilistic model and IGA respectively. The experiment results show that the proposed IEDA not only gets better solution, but also has faster convergence speed.
A Distributional Representation Model For Collaborative Filtering

OpenAIRE

Junlin, Zhang; Heng, Cai; Tongwen, Huang; Huiping, Xue

2015-01-01

In this paper, we propose a very concise deep learning approach for collaborative filtering that jointly models distributional representation for users and items. The proposed framework obtains better performance when compared against current state-of-art algorithms and that made the distributional representation model a promising direction for further research in the collaborative filtering.
Rapid Prototyping of Formally Modelled Distributed Systems

OpenAIRE

Buchs, Didier; Buffo, Mathieu; Titsworth, Frances M.

1999-01-01

This paper presents various kinds of prototypes, used in the prototyping of formally modelled distributed systems. It presents the notions of prototyping techniques and prototype evolution, and shows how to relate them to the software life-cycle. It is illustrated through the use of the formal modelling language for distributed systems CO-OPN/2.
A novel single-phase phase space-based voltage mode controller for distributed static compensator to improve voltage profile of distribution systems

International Nuclear Information System (INIS)

Shokri, Abdollah; Shareef, Hussain; Mohamed, Azah; Farhoodnea, Masoud; Zayandehroodi, Hadi

2014-01-01

Highlights: • A new phase space based voltage mode controller for D-STATCOM was proposed. • The proposed compensator was tested to mitigate voltage disturbances in distribution systems. • Voltage fluctuation, voltage sag and voltage swell are considered to evaluate the performance of the proposed compensator. - Abstract: Distribution static synchronous compensator (D-STATCOM) has been developed and attained a great interest to compensate the power quality disturbances of distribution systems. In this paper, a novel single-phase control scheme for D-STATCOM is proposed to improve voltage profile at the Point of Common Coupling (PCC). The proposed voltage mode (VM) controller is based on the phase space algorithm, which is able to rapidly detect and mitigate any voltage deviations from reference voltage including voltage sags and voltage swells. To investigate the efficiency and accuracy of the proposed compensator, a system is modeled using Matlab/Simulink. The simulation results approve the capability of the proposed VM controller to provide a regulated and disturbance-free voltage for the connected loads at the PCC
Improvement in the distribution of services in multi-agent systems with SCODA

Directory of Open Access Journals (Sweden)

Jesús Ángel ROMÁN GALLEGO

2016-06-01

Full Text Available The distribution of services on multi-agent systems allows it to reduce to the agents their computational load. The functionality of the system does not reside in the agents themselves, however it is ubiquitously distributed so that allows you to perform tasks in parallel avoiding an additional computational cost to the elements in the system. The distribution of services that offers SCODA (Distributed and Specialized Agent Communities allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA.
Species Distribution Modeling: Comparison of Fixed and Mixed Effects Models Using INLA

Directory of Open Access Journals (Sweden)

Lara Dutra Silva

2017-12-01

Full Text Available Invasive alien species are among the most important, least controlled, and least reversible of human impacts on the world’s ecosystems, with negative consequences affecting biodiversity and socioeconomic systems. Species distribution models have become a fundamental tool in assessing the potential spread of invasive species in face of their native counterparts. In this study we compared two different modeling techniques: (i fixed effects models accounting for the effect of ecogeographical variables (EGVs; and (ii mixed effects models including also a Gaussian random field (GRF to model spatial correlation (Matérn covariance function. To estimate the potential distribution of Pittosporum undulatum and Morella faya (respectively, invasive and native trees, we used geo-referenced data of their distribution in Pico and São Miguel islands (Azores and topographic, climatic and land use EGVs. Fixed effects models run with maximum likelihood or the INLA (Integrated Nested Laplace Approximation approach provided very similar results, even when reducing the size of the presences data set. The addition of the GRF increased model adjustment (lower Deviance Information Criterion, particularly for the less abundant tree, M. faya. However, the random field parameters were clearly affected by sample size and species distribution pattern. A high degree of spatial autocorrelation was found and should be taken into account when modeling species distribution.
Improved water density feedback model for pressurized water reactors

International Nuclear Information System (INIS)

Casadei, A.L.

1976-01-01

An improved water density feedback model has been developed for neutron diffusion calculations of PWR cores. This work addresses spectral effects on few-group cross sections due to water density changes, and water density predictions considering open channel and subcooled boiling effects. An homogenized spectral model was also derived using the unit assembly diffusion method for employment in a coarse mesh 3D diffusion computer program. The spectral and water density evaluation models described were incorporated in a 3D diffusion code, and neutronic calculations for a typical PWR were completed for both nominal and accident conditions. Comparison of neutronic calculations employing the open versus the closed channel model for accident conditions indicates that significant safety margin increases can be obtained if subcooled boiling and open channel effects are considered in accident calculations. This is attributed to effects on both core reactivity and power distribution, which result in increased margin to fuel degradation limits. For nominal operating conditions, negligible differences in core reactivity and power distribution exist since flow redistribution and subcooled voids are not significant at such conditions. The results serve to confirm the conservatism of currently employed closed channel feedback methods in accident analysis, and indicate that the model developed in this work can contribute to show increased safety margins for certain accidents
Robust Hydrological Forecasting for High-resolution Distributed Models Using a Unified Data Assimilation Approach

Science.gov (United States)

Hernandez, F.; Liang, X.

2017-12-01

Reliable real-time hydrological forecasting, to predict important phenomena such as floods, is invaluable to the society. However, modern high-resolution distributed models have faced challenges when dealing with uncertainties that are caused by the large number of parameters and initial state estimations involved. Therefore, to rely on these high-resolution models for critical real-time forecast applications, considerable improvements on the parameter and initial state estimation techniques must be made. In this work we present a unified data assimilation algorithm called Optimized PareTo Inverse Modeling through Inverse STochastic Search (OPTIMISTS) to deal with the challenge of having robust flood forecasting for high-resolution distributed models. This new algorithm combines the advantages of particle filters and variational methods in a unique way to overcome their individual weaknesses. The analysis of candidate particles compares model results with observations in a flexible time frame, and a multi-objective approach is proposed which attempts to simultaneously minimize differences with the observations and departures from the background states by using both Bayesian sampling and non-convex evolutionary optimization. Moreover, the resulting Pareto front is given a probabilistic interpretation through kernel density estimation to create a non-Gaussian distribution of the states. OPTIMISTS was tested on a low-resolution distributed land surface model using VIC (Variable Infiltration Capacity) and on a high-resolution distributed hydrological model using the DHSVM (Distributed Hydrology Soil Vegetation Model). In the tests streamflow observations are assimilated. OPTIMISTS was also compared with a traditional particle filter and a variational method. Results show that our method can reliably produce adequate forecasts and that it is able to outperform those resulting from assimilating the observations using a particle filter or an evolutionary 4D variational

Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models

Directory of Open Access Journals (Sweden)

David M. Makori

2017-02-01

Full Text Available Bee keeping is indispensable to global food production. It is an alternate income source, especially in rural underdeveloped African settlements, and an important forest conservation incentive. However, dwindling honeybee colonies around the world are attributed to pests and diseases whose spatial distribution and influences are not well established. In this study, we used remotely sensed data to improve the reliability of pest ecological niche (EN models to attain reliable pest distribution maps. Occurrence data on four pests (Aethina tumida, Galleria mellonella, Oplostomus haroldi and Varroa destructor were collected from apiaries within four main agro-ecological regions responsible for over 80% of Kenya’s bee keeping. Africlim bioclimatic and derived normalized difference vegetation index (NDVI variables were used to model their ecological niches using Maximum Entropy (MaxEnt. Combined precipitation variables had a high positive logit influence on all remotely sensed and biotic models’ performance. Remotely sensed vegetation variables had a substantial effect on the model, contributing up to 40.8% for G. mellonella and regions with high rainfall seasonality were predicted to be high-risk areas. Projections (to 2055 indicated that, with the current climate change trend, these regions will experience increased honeybee pest risk. We conclude that honeybee pests could be modelled using bioclimatic data and remotely sensed variables in MaxEnt. Although the bioclimatic data were most relevant in all model results, incorporating vegetation seasonality variables to improve mapping the ‘actual’ habitat of key honeybee pests and to identify risk and containment zones needs to be further investigated.
Determination of High-Frequency Current Distribution Using EMTP-Based Transmission Line Models with Resulting Radiated Electromagnetic Fields

Energy Technology Data Exchange (ETDEWEB)

Mork, B; Nelson, R; Kirkendall, B; Stenvig, N

2009-11-30

Application of BPL technologies to existing overhead high-voltage power lines would benefit greatly from improved simulation tools capable of predicting performance - such as the electromagnetic fields radiated from such lines. Existing EMTP-based frequency-dependent line models are attractive since their parameters are derived from physical design dimensions which are easily obtained. However, to calculate the radiated electromagnetic fields, detailed current distributions need to be determined. This paper presents a method of using EMTP line models to determine the current distribution on the lines, as well as a technique for using these current distributions to determine the radiated electromagnetic fields.
Distributed Modelling of Stormflow Generation: Assessing the Effect of Ground Cover

Science.gov (United States)

Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.

2017-12-01

Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.
Simultaneous treatment of unspecified heteroskedastic model error distribution and mismeasured covariates for restricted moment models.

Science.gov (United States)

Garcia, Tanya P; Ma, Yanyuan

2017-10-01

We develop consistent and efficient estimation of parameters in general regression models with mismeasured covariates. We assume the model error and covariate distributions are unspecified, and the measurement error distribution is a general parametric distribution with unknown variance-covariance. We construct root- n consistent, asymptotically normal and locally efficient estimators using the semiparametric efficient score. We do not estimate any unknown distribution or model error heteroskedasticity. Instead, we form the estimator under possibly incorrect working distribution models for the model error, error-prone covariate, or both. Empirical results demonstrate robustness to different incorrect working models in homoscedastic and heteroskedastic models with error-prone covariates.
Species Distribution modeling as a tool to unravel determinants of palm distribution in Thailand

DEFF Research Database (Denmark)

Tovaranonte, Jantrararuk; Barfod, Anders S.; Balslev, Henrik

2011-01-01

As a consequence of the decimation of the forest cover in Thailand from 50% to ca. 20 % since the 1950ies, it is difficult to gain insight in the drivers behind past, present and future distribution ranges of plant species. Species distribution modeling allows visualization of potential species...... distribution under specific sets of assumptions. In this study we used maximum entropy to map potential distributions of 103 species of palms for which more than 5 herbarium records exist. Palms constitute key-stone plant group from both an ecological, economical and conservation perspective. The models were......) and the Area Under the Curve (AUC). All models performed well with AUC scores above 0.95. The predicted distribution ranges showed high suitability for palms in the southern region of Thailand. It also shows that spatial predictor variables are important in cases where historical processes may explain extant...
Constituent quarks as clusters in quark-gluon-parton model. [Total cross sections, probability distributions

Energy Technology Data Exchange (ETDEWEB)

Kanki, T [Osaka Univ., Toyonaka (Japan). Coll. of General Education

1976-12-01

We present a quark-gluon-parton model in which quark-partons and gluons make clusters corresponding to two or three constituent quarks (or anti-quarks) in the meson or in the baryon, respectively. We explicitly construct the constituent quark state (cluster), by employing the Kuti-Weisskopf theory and by requiring the scaling. The quark additivity of the hadronic total cross sections and the quark counting rules on the threshold powers of various distributions are satisfied. For small x (Feynman fraction), it is shown that the constituent quarks and quark-partons have quite different probability distributions. We apply our model to hadron-hadron inclusive reactions, and clarify that the fragmentation and the diffractive processes relate to the constituent quark distributions, while the processes in or near the central region are controlled by the quark-partons. Our model gives the reasonable interpretation for the experimental data and much improves the usual ''constituent interchange model'' result near and in the central region (x asymptotically equals x sub(T) asymptotically equals 0).
Improving diagnostic accuracy using agent-based distributed data mining system.

Science.gov (United States)

Sridhar, S

2013-09-01

The use of data mining techniques to improve the diagnostic system accuracy is investigated in this paper. The data mining algorithms aim to discover patterns and extract useful knowledge from facts recorded in databases. Generally, the expert systems are constructed for automating diagnostic procedures. The learning component uses the data mining algorithms to extract the expert system rules from the database automatically. Learning algorithms can assist the clinicians in extracting knowledge automatically. As the number and variety of data sources is dramatically increasing, another way to acquire knowledge from databases is to apply various data mining algorithms that extract knowledge from data. As data sets are inherently distributed, the distributed system uses agents to transport the trained classifiers and uses meta learning to combine the knowledge. Commonsense reasoning is also used in association with distributed data mining to obtain better results. Combining human expert knowledge and data mining knowledge improves the performance of the diagnostic system. This work suggests a framework of combining the human knowledge and knowledge gained by better data mining algorithms on a renal and gallstone data set.
A distributed snow-evolution modeling system (SnowModel)

Science.gov (United States)

Glen E. Liston; Kelly. Elder

2006-01-01

SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...
Species distribution model transferability and model grain size - finer may not always be better.

Science.gov (United States)

Manzoor, Syed Amir; Griffiths, Geoffrey; Lukac, Martin

2018-05-08

Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.
Affordable non-traditional source data mining for context assessment to improve distributed fusion system robustness

Science.gov (United States)

Bowman, Christopher; Haith, Gary; Steinberg, Alan; Morefield, Charles; Morefield, Michael

2013-05-01

This paper describes methods to affordably improve the robustness of distributed fusion systems by opportunistically leveraging non-traditional data sources. Adaptive methods help find relevant data, create models, and characterize the model quality. These methods also can measure the conformity of this non-traditional data with fusion system products including situation modeling and mission impact prediction. Non-traditional data can improve the quantity, quality, availability, timeliness, and diversity of the baseline fusion system sources and therefore can improve prediction and estimation accuracy and robustness at all levels of fusion. Techniques are described that automatically learn to characterize and search non-traditional contextual data to enable operators integrate the data with the high-level fusion systems and ontologies. These techniques apply the extension of the Data Fusion & Resource Management Dual Node Network (DNN) technical architecture at Level 4. The DNN architecture supports effectively assessment and management of the expanded portfolio of data sources, entities of interest, models, and algorithms including data pattern discovery and context conformity. Affordable model-driven and data-driven data mining methods to discover unknown models from non-traditional and `big data' sources are used to automatically learn entity behaviors and correlations with fusion products, [14 and 15]. This paper describes our context assessment software development, and the demonstration of context assessment of non-traditional data to compare to an intelligence surveillance and reconnaissance fusion product based upon an IED POIs workflow.
Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

Science.gov (United States)

Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

2016-06-01

The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.
Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

DEFF Research Database (Denmark)

Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....
Two-fluid model with droplet size distribution for condensing steam flows

International Nuclear Information System (INIS)

Wróblewski, Włodzimierz; Dykas, Sławomir

2016-01-01

The process of energy conversion in the low pressure part of steam turbines may be improved using new and more accurate numerical models. The paper presents a description of a model intended for the condensing steam flow modelling. The model uses a standard condensation model. A physical and a numerical model of the mono- and polydispersed wet-steam flow are presented. The proposed two-fluid model solves separate flow governing equations for the compressible, inviscid vapour and liquid phase. The method of moments with a prescribed function is used for the reconstruction of the water droplet size distribution. The described model is presented for the liquid phase evolution in the flow through the de Laval nozzle. - Highlights: • Computational Fluid Dynamics. • Steam condensation in transonic flows through the Laval nozzles. • In-house CFD code – two-phase flow, two-fluid monodispersed and polydispersed model.
Charge distribution in an two-chain dual model

International Nuclear Information System (INIS)

Fialkowski, K.; Kotanski, A.

1983-01-01

Charge distributions in the multiple production processes are analysed using the dual chain model. A parametrisation of charge distributions for single dual chains based on the νp and anti vp data is proposed. The rapidity charge distributions are then calculated for pp and anti pp collisions and compared with the previous calculations based on the recursive cascade model of single chains. The results differ at the SPS collider energies and in the energy dependence of the net forward charge supplying the useful tests of the dual chain model. (orig.)
Uncertainty Visualization Using Copula-Based Analysis in Mixed Distribution Models.

Science.gov (United States)

Hazarika, Subhashis; Biswas, Ayan; Shen, Han-Wei

2018-01-01

Distributions are often used to model uncertainty in many scientific datasets. To preserve the correlation among the spatially sampled grid locations in the dataset, various standard multivariate distribution models have been proposed in visualization literature. These models treat each grid location as a univariate random variable which models the uncertainty at that location. Standard multivariate distributions (both parametric and nonparametric) assume that all the univariate marginals are of the same type/family of distribution. But in reality, different grid locations show different statistical behavior which may not be modeled best by the same type of distribution. In this paper, we propose a new multivariate uncertainty modeling strategy to address the needs of uncertainty modeling in scientific datasets. Our proposed method is based on a statistically sound multivariate technique called Copula, which makes it possible to separate the process of estimating the univariate marginals and the process of modeling dependency, unlike the standard multivariate distributions. The modeling flexibility offered by our proposed method makes it possible to design distribution fields which can have different types of distribution (Gaussian, Histogram, KDE etc.) at the grid locations, while maintaining the correlation structure at the same time. Depending on the results of various standard statistical tests, we can choose an optimal distribution representation at each location, resulting in a more cost efficient modeling without significantly sacrificing on the analysis quality. To demonstrate the efficacy of our proposed modeling strategy, we extract and visualize uncertain features like isocontours and vortices in various real world datasets. We also study various modeling criterion to help users in the task of univariate model selection.
The κ-generalized distribution: A new descriptive model for the size distribution of incomes

Science.gov (United States)

Clementi, F.; Di Matteo, T.; Gallegati, M.; Kaniadakis, G.

2008-05-01

This paper proposes the κ-generalized distribution as a model for describing the distribution and dispersion of income within a population. Formulas for the shape, moments and standard tools for inequality measurement-such as the Lorenz curve and the Gini coefficient-are given. A method for parameter estimation is also discussed. The model is shown to fit extremely well the data on personal income distribution in Australia and in the United States.
Studying the Impact of Distributed Solar PV on Power Systems using Integrated Transmission and Distribution Models: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jain, Himanshu [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Palmintier, Bryan S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krad, Ibrahim [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnamurthy, Dheepak [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-24

This paper presents the results of a distributed solar PV impact assessment study that was performed using a synthetic integrated transmission (T) and distribution (D) model. The primary objective of the study was to present a new approach for distributed solar PV impact assessment, where along with detailed models of transmission and distribution networks, consumer loads were modeled using the physics of end-use equipment, and distributed solar PV was geographically dispersed and connected to the secondary distribution networks. The highlights of the study results were (i) increase in the Area Control Error (ACE) at high penetration levels of distributed solar PV; and (ii) differences in distribution voltages profiles and voltage regulator operations between integrated T&D and distribution only simulations.
Designing the Distributed Model Integration Framework – DMIF

NARCIS (Netherlands)

Belete, Getachew F.; Voinov, Alexey; Morales, Javier

2017-01-01

We describe and discuss the design and prototype of the Distributed Model Integration Framework (DMIF) that links models deployed on different hardware and software platforms. We used distributed computing and service-oriented development approaches to address the different aspects of
Distributed leadership, team working and service improvement in healthcare.

Science.gov (United States)

Boak, George; Dickens, Victoria; Newson, Annalisa; Brown, Louise

2015-01-01

The purpose of this paper is to analyse the introduction of distributed leadership and team working in a therapy department in a healthcare organisation and to explore the factors that enabled the introduction to be successful. This paper used a case study methodology. Qualitative and quantitative information was gathered from one physiotherapy department over a period of 24 months. Distributed leadership and team working were central to a number of system changes that were initiated by the department, which led to improvements in patient waiting times for therapy. The paper identifies six factors that appear to have influenced the successful introduction of distributed learning and team working in this case. This is a single case study. It would be interesting to explore whether these factors are found in other cases where distributed leadership is introduced in healthcare organisations. The paper provides an example of successful introduction of distributed leadership, which has had a positive impact on services to patients. Other therapy teams may consider how the approach may be adopted or adapted to their own circumstances. Although distributed leadership is thought to be important in healthcare, particularly when organisational change is needed, there are very few studies of the practicalities of how it can be introduced.
Community energy storage and distribution SCADA improvements

International Nuclear Information System (INIS)

Riggins, M.

2010-01-01

The mission of American Electric Power (AEP) is to sustain the real time balance of energy supply and demand. Approximately 2.5 percent of energy generated in the United States (USA) is stored as pumped hydro, compressed air, or in batteries and other devices. This power point presentation discussed the use of SCADA for improving community energy storage (CES) and distribution systems. CES is a distributed fleet of small energy units connected to the transformers in order to serve houses or small commercial loads. CES is operated as a fleet offering multi-megawatt (MW) multi-hour storage. The benefits of CES include backup power, flicker mitigation, and renewable integration. Benefits to the electricity grid include power factor correct, ancillary services, and load leveling at the substation level. SCADA is being used to determine when emergency load reductions are required or when emergency inspections on fans, oil pumps or other devices are needed. An outline of AEP's monitoring system installation plan was also included. tabs., figs.

Improved road traffic emission inventories by adding mean speed distributions

NARCIS (Netherlands)

Smit, R.; Poelman, M.; Schrijver, J.

2008-01-01

Does consideration of average speed distributions on roads-as compared to single mean speed-lead to different results in emission modelling of large road networks? To address this question, a post-processing method is developed to predict mean speed distributions using available traffic data from a
Working toward integrated models of alpine plant distribution.

Science.gov (United States)

Carlson, Bradley Z; Randin, Christophe F; Boulangeat, Isabelle; Lavergne, Sébastien; Thuiller, Wilfried; Choler, Philippe

2013-10-01

Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial-temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution.
Distributed power quality improvement in residential microgrids

DEFF Research Database (Denmark)

Naderi Zarnaghi, Yahya; Hosseini, Seyed Hossein; Ghassem Zadeh, Saeid

2017-01-01

The importance of power quality issue on micro grids and also the changing nature of power system distortions will lead the future power systems to use distributed power quality improvement (DPQI) devices. One possible choice of these DPQIs are multifunctional DGs that could compensate some...... harmonics in the location of generation and prevent the harmonics to enter main power grid. In this paper a control method based on virtual harmonic impedance is presented for these multifunctional DGs and the effect of the location of these DGs on compensation procedure is studied with simulating...
Robust Improvement in Estimation of a Covariance Matrix in an Elliptically Contoured Distribution Respect to Quadratic Loss Function

Directory of Open Access Journals (Sweden)

Z. Khodadadi

2008-03-01

Full Text Available Let S be matrix of residual sum of square in linear model Y = Aβ + e where matrix e is distributed as elliptically contoured with unknown scale matrix Σ. In present work, we consider the problem of estimating Σ with respect to squared loss function, L(Σˆ , Σ = tr(ΣΣˆ −1 −I 2 . It is shown that improvement of the estimators were obtained by James, Stein [7], Dey and Srivasan [1] under the normality assumption remains robust under an elliptically contoured distribution respect to squared loss function
Automated Student Model Improvement

Science.gov (United States)

Koedinger, Kenneth R.; McLaughlin, Elizabeth A.; Stamper, John C.

2012-01-01

Student modeling plays a critical role in developing and improving instruction and instructional technologies. We present a technique for automated improvement of student models that leverages the DataShop repository, crowd sourcing, and a version of the Learning Factors Analysis algorithm. We demonstrate this method on eleven educational…
A Distributed Snow Evolution Modeling System (SnowModel)

Science.gov (United States)

Liston, G. E.; Elder, K.

2004-12-01

A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.
Validation of a regional distribution model in environmental risk assessment of substances

Energy Technology Data Exchange (ETDEWEB)

Berding, V.

2000-06-26

The regional distribution model SimpleBox proposed in the TGD (Technical Guidance Document) and implemented in the EUSES software (European Union System for the Evaluation of Substances) was validated. The aim of this investigation was to determine the applicability and weaknesses of the model and to make proposals for improvement. The validation was performed using the scheme set up by SCHWARTZ (2000) of which the main aspects are the division into internal and external validation, i.e. into generic and task-specific properties of the model. These two validation parts contain the scrutiny of theory, sensitivity analyses, comparison of predicted environmental concentrations with measured ones by means of scenario analyses, uncertainty analyses and comparison with alternative models. Generally, the model employed is a reasonable compromise between complexity and simplification. Simpler models are applicable, too, but in many cases the results can deviate considerably from the measured values. For the sewage treatment model, it could be shown that its influence on the predicted concentration is very low and a much simpler model fulfils its purpose in a similar way. It is proposed to improve the model in several ways, e.g. by including the pH/pK-correction for dissociating substances or by alternative estimations functions for partition coefficients. But the main focus for future improvements should be on the amelioration of release estimations and substance characteristics as degradation rates and partition coefficients.
Electric Power Distribution System Model Simplification Using Segment Substitution

Energy Technology Data Exchange (ETDEWEB)

Reiman, Andrew P.; McDermott, Thomas E.; Akcakaya, Murat; Reed, Gregory F.

2018-05-01

Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.
Electric Power Distribution System Model Simplification Using Segment Substitution

International Nuclear Information System (INIS)

Reiman, Andrew P.; McDermott, Thomas E.; Akcakaya, Murat; Reed, Gregory F.

2017-01-01

Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). Finally, in contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.
Analytical Business Model for Sustainable Distributed Retail Enterprises in a Competitive Market

Directory of Open Access Journals (Sweden)

Courage Matobobo

2016-02-01

Full Text Available Retail enterprises are organizations that sell goods in small quantities to consumers for personal consumption. In distributed retail enterprises, data is administered per branch. It is important for retail enterprises to make use of data generated within the organization to determine consumer patterns and behaviors. Large organizations find it difficult to ascertain customer preferences by merely observing transactions. This has led to quantifiable losses, such as loss of market share to competitors and targeting the wrong market. Although some enterprises have implemented classical business models to address these challenging issues, they still lack analytics-based marketing programs to gain a competitive advantage to deal with likely catastrophic events. This research develops an analytical business (ARANN model for distributed retail enterprises in a competitive market environment to address the current laxity through the best arrangement of shelf products per branch. The ARANN model is built on association rules, complemented by artificial neural networks to strengthen the results of both mutually. According to experimental analytics, the ARANN model outperforms the state of the art model, implying improved confidence in business information management within the dynamically changing world economy.
Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm

Science.gov (United States)

Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven

2010-05-01

Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.
Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

DEFF Research Database (Denmark)

Demirel, Mehmet C.; Mai, Juliane; Mendiguren Gonzalez, Gorka

2018-01-01

Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target...... and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance...
Overhead distribution line models for harmonics studies

Energy Technology Data Exchange (ETDEWEB)

Nagpal, M.; Xu, W.; Dommel, H.W.

1994-01-01

Carson's formulae and Maxwell's potential coefficients are used for calculating the per unit length series impedances and shunt capacitances of the overhead lines. The per unit length values are then used for building the models, nominal pi-circuit, and equivalent pi-circuit at the harmonic frequencies. This paper studies the accuracy of these models for presenting the overhead distribution lines in steady-state harmonic solutions at frequencies up to 5 kHz. The models are verified with a field test on a 25 kV distribution line and the sensitivity of the models to ground resistivity, skin effect, and multiple grounding is reported.
Subgrid Parameterization of the Soil Moisture Storage Capacity for a Distributed Rainfall-Runoff Model

Directory of Open Access Journals (Sweden)

Weijian Guo

2015-05-01

Full Text Available Spatial variability plays an important role in nonlinear hydrologic processes. Due to the limitation of computational efficiency and data resolution, subgrid variability is usually assumed to be uniform for most grid-based rainfall-runoff models, which leads to the scale-dependence of model performances. In this paper, the scale effect on the Grid-Xinanjiang model was examined. The bias of the estimation of precipitation, runoff, evapotranspiration and soil moisture at the different grid scales, along with the scale-dependence of the effective parameters, highlights the importance of well representing the subgrid variability. This paper presents a subgrid parameterization method to incorporate the subgrid variability of the soil storage capacity, which is a key variable that controls runoff generation and partitioning in the Grid-Xinanjiang model. In light of the similar spatial pattern and physical basis, the soil storage capacity is correlated with the topographic index, whose spatial distribution can more readily be measured. A beta distribution is introduced to represent the spatial distribution of the soil storage capacity within the grid. The results derived from the Yanduhe Basin show that the proposed subgrid parameterization method can effectively correct the watershed soil storage capacity curve. Compared to the original Grid-Xinanjiang model, the model performances are quite consistent at the different grid scales when the subgrid variability is incorporated. This subgrid parameterization method reduces the recalibration necessity when the Digital Elevation Model (DEM resolution is changed. Moreover, it improves the potential for the application of the distributed model in the ungauged basin.
Modelling refrigerant distribution in minichannel evaporators

DEFF Research Database (Denmark)

Brix, Wiebke

of the liquid and vapour in the inlet manifold. Combining non-uniform airflow and non-uniform liquid and vapour distribution shows that a non-uniform airflow distribution to some degree can be compensated by a suitable liquid and vapour distribution. Controlling the superheat out of the individual channels...... to be equal, results in a cooling capacity very close to the optimum. A sensitivity study considering parameter changes shows that the course of the pressure gradient in the channel is significant, considering the magnitude of the capacity reductions due to non-uniform liquid and vapour distribution and non......This thesis is concerned with numerical modelling of flow distribution in a minichannel evaporator for air-conditioning. The study investigates the impact of non-uniform airflow and non-uniform distribution of the liquid and vapour phases in the inlet manifold on the refrigerant mass flow...
Rationalisation of distribution functions for models of nanoparticle magnetism

International Nuclear Information System (INIS)

El-Hilo, M.; Chantrell, R.W.

2012-01-01

A formalism is presented which reconciles the use of different distribution functions of particle diameter in analytical models of the magnetic properties of nanoparticle systems. For the lognormal distribution a transformation is derived which shows that a distribution of volume fraction transforms into a lognormal distribution of particle number albeit with a modified median diameter. This transformation resolves an apparent discrepancy reported in Tournus and Tamion [Journal of Magnetism and Magnetic Materials 323 (2011) 1118]. - Highlights: ► We resolve a problem resulting from the misunderstanding of the nature. ► The nature of dispersion functions in models of nanoparticle magnetism. ► The derived transformation between distributions will be of benefit in comparing models and experimental results.
Pell-Sim - dynamic model for forecasting storage and distribution of wood pellets

International Nuclear Information System (INIS)

Vinterbaeck, Johan

2004-01-01

This study examined the system of wood pellet distribution to residential consumers. The distribution cost for a residential pellet consumer typically represents 30% of the per tonne price and of this share, the inventory cost could be more than 50%. Important administrative activities in physical distribution are forecasting demand and inventory control. One way to improve distribution systems would be to optimise inventory management for pellet distributors. The aim of this study was to propose improvements in pellet distribution management by using tools from systems analysis. The ultimate goal was to present an optimised storage level curve adapted to the mid-Swedish community of Avesta. An internal model for optimising inventory management, Pell-Sim, was constructed, composed of two integrated parts: a simulation unit to forecast residential wood pellet demand and a spreadsheet unit with inventory-related functions. Daily outdoor temperatures basically regulated the simulation unit. An order point system was chosen for reordering. The residential customers of a distribution company were divided into two groups, delivery and collecting customers, which were statistically treated separately. When collecting and delivery customer input inventories were normally distributed in the intervals from 0 to 3500 kg and 6500 kg, respectively, their annual means of total delivery were both about 7000 kg/customer, which was the desired and empirical level. The expected pellet customer orders were negatively correlated to mean daily temperatures, lagging behind about 1 month. Sensitivity analyses showed that monthly results for ordered quantity and total cost were particularly sensitive to ordering and carrying costs. The Pell-Sim programme can easily be adapted for distributors in other geographical regions. (Author)
Pell-Sim - dynamic model for forecasting storage and distribution of wood pellets

Energy Technology Data Exchange (ETDEWEB)

Vinterbaeck, Johan [Swedish Univ. of Agricultural Sciences, Dept. of Forest Management and Products, Uppsala (Sweden)

2004-12-01

This study examined the system of wood pellet distribution to residential consumers. The distribution cost for a residential pellet consumer typically represents 30% of the per tonne price and of this share, the inventory cost could be more than 50%. Important administrative activities in physical distribution are forecasting demand and inventory control. One way to improve distribution systems would be to optimise inventory management for pellet distributors. The aim of this study was to propose improvements in pellet distribution management by using tools from systems analysis. The ultimate goal was to present an optimised storage level curve adapted to the mid-Swedish community of Avesta. An internal model for optimising inventory management, Pell-Sim, was constructed, composed of two integrated parts: a simulation unit to forecast residential wood pellet demand and a spreadsheet unit with inventory-related functions. Daily outdoor temperatures basically regulated the simulation unit. An order point system was chosen for reordering. The residential customers of a distribution company were divided into two groups, delivery and collecting customers, which were statistically treated separately. When collecting and delivery customer input inventories were normally distributed in the intervals from 0 to 3500 kg and 6500 kg, respectively, their annual means of total delivery were both about 7000 kg/customer, which was the desired and empirical level. The expected pellet customer orders were negatively correlated to mean daily temperatures, lagging behind about 1 month. Sensitivity analyses showed that monthly results for ordered quantity and total cost were particularly sensitive to ordering and carrying costs. The Pell-Sim programme can easily be adapted for distributors in other geographical regions. (Author)
Business Models and Regulation | Distributed Generation Interconnection

Science.gov (United States)

Collaborative | NREL Business Models and Regulation Business Models and Regulation Subscribe to new business models and approaches. The growing role of distributed resources in the electricity system is leading to a shift in business models and regulation for electric utilities. These
Tempered stable distributions stochastic models for multiscale processes

CERN Document Server

Grabchak, Michael

2015-01-01

This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.

Efficient Calibration of Distributed Catchment Models Using Perceptual Understanding and Hydrologic Signatures

Science.gov (United States)

Hutton, C.; Wagener, T.; Freer, J. E.; Duffy, C.; Han, D.

2015-12-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models may contain a large number of model parameters which are computationally expensive to calibrate. Even when calibration is possible, insufficient data can result in model parameter and structural equifinality. In order to help reduce the space of feasible models and supplement traditional outlet discharge calibration data, semi-quantitative information (e.g. knowledge of relative groundwater levels), may also be used to identify behavioural models when applied to constrain spatially distributed predictions of states and fluxes. The challenge is to combine these different sources of information together to identify a behavioural region of state-space, and efficiently search a large, complex parameter space to identify behavioural parameter sets that produce predictions that fall within this behavioural region. Here we present a methodology to incorporate different sources of data to efficiently calibrate distributed catchment models. Metrics of model performance may be derived from multiple sources of data (e.g. perceptual understanding and measured or regionalised hydrologic signatures). For each metric, an interval or inequality is used to define the behaviour of the catchment system, accounting for data uncertainties. These intervals are then combined to produce a hyper-volume in state space. The state space is then recast as a multi-objective optimisation problem, and the Borg MOEA is applied to first find, and then populate the hyper-volume, thereby identifying acceptable model parameter sets. We apply the methodology to calibrate the PIHM model at Plynlimon, UK by incorporating perceptual and hydrologic data into the calibration problem. Furthermore, we explore how to improve calibration efficiency through search initialisation from shorter model runs.
Regulation of electricity distribution in Spain. Principles and mechanisms for distribution

International Nuclear Information System (INIS)

Gomez San Roman, T.

2007-01-01

First, a conceptual framework for electricity network regulation is presented. In the second part, this paper reviews the current situation of electricity distribution regulation in Spain highlighting its main shortcomings. Finally, some guidelines for the design of a new remuneration model for each distribution company are proposed. This new regulatory model will increase efficiency, promoting the required investment for improving quality of supply and reducing energy losses. This model is based on two new regulatory tools: regulatory accounting and network reference models. (Author) 15 refs
Improvement of distributed snowmelt energy balance modeling with MODIS-based NDSI-derived fractional snow-covered area data

Science.gov (United States)

Joel W. Homan; Charles H. Luce; James P. McNamara; Nancy F. Glenn

2011-01-01

Describing the spatial variability of heterogeneous snowpacks at a watershed or mountain-front scale is important for improvements in large-scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snowcovered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale-up snowmelt models....
Electricity distribution management Smart Grid system model

Directory of Open Access Journals (Sweden)

Wiesław Nowak

2012-06-01

Full Text Available This paper presents issues concerning the implementation of Smart Grid solutions in a real distribution network. The main components possible to quick implementation were presented. Realization of these ideas should bring tangible benefi ts to both customers and distribution system operators. Moreover the paper shows selected research results which examine proposed solutions in area of improving supply reliability and reducing energy losses in analysed network.
Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Science.gov (United States)

Daigle, Matthew John; Goebel, Kai Frank

2010-01-01

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.
A Traction Control Strategy with an Efficiency Model in a Distributed Driving Electric Vehicle

OpenAIRE

Lin, Cheng; Cheng, Xingqun

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the tw...
An Analysis of Spherical Particles Distribution Randomly Packed in a Medium for the Monte Carlo Implicit Modeling

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Yong; Kim, Song Hyun; Shin, Chang Ho; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of)

2014-05-15

In this study, as a preliminary study to develop an implicit method having high accuracy, the distribution characteristics of spherical particles were evaluated by using explicit modeling techniques in various volume packing fractions. This study was performed to evaluate implicitly simulated distribution of randomly packed spheres in a medium. At first, an explicit modeling method to simulate random packed spheres in a hexahedron medium was proposed. The distributed characteristics of l{sub p} and r{sub p}, which are used in the particle position sampling, was estimated. It is analyzed that the use of the direct exponential distribution, which is generally used in the implicit modeling, can cause the distribution bias of the spheres. It is expected that the findings in this study can be utilized for improving the accuracy in using the implicit method. Spherical particles, which are randomly distributed in medium, are utilized for the radiation shields, fusion reactor blanket, fuels of VHTR reactors. Due to the difficulty on the simulation of the stochastic distribution, Monte Carlo (MC) method has been mainly considered as the tool for the analysis of the particle transport. For the MC modeling of the spherical particles, three methods are known; repeated structure, explicit modeling, and implicit modeling. Implicit method (called as the track length sampling method) is a modeling method that is the sampling based modeling technique of each spherical geometry (or track length of the sphere) during the MC simulation. Implicit modeling method has advantages in high computational efficiency and user convenience. However, it is noted that the implicit method has lower modeling accuracy in various finite mediums.
Distributed MAP in the SpinJa Model Checker

Directory of Open Access Journals (Sweden)

Stefan Vijzelaar

2011-10-01

Full Text Available Spin in Java (SpinJa is an explicit state model checker for the Promela modelling language also used by the SPIN model checker. Designed to be extensible and reusable, the implementation of SpinJa follows a layered approach in which each new layer extends the functionality of the previous one. While SpinJa has preliminary support for shared-memory model checking, it did not yet support distributed-memory model checking. This tool paper presents a distributed implementation of a maximal accepting predecessors (MAP search algorithm on top of SpinJa.
The probability distribution model of air pollution index and its dominants in Kuala Lumpur

Science.gov (United States)

AL-Dhurafi, Nasr Ahmed; Razali, Ahmad Mahir; Masseran, Nurulkamal; Zamzuri, Zamira Hasanah

2016-11-01

This paper focuses on the statistical modeling for the distributions of air pollution index (API) and its sub-indexes data observed at Kuala Lumpur in Malaysia. Five pollutants or sub-indexes are measured including, carbon monoxide (CO); sulphur dioxide (SO2); nitrogen dioxide (NO2), and; particulate matter (PM10). Four probability distributions are considered, namely log-normal, exponential, Gamma and Weibull in search for the best fit distribution to the Malaysian air pollutants data. In order to determine the best distribution for describing the air pollutants data, five goodness-of-fit criteria's are applied. This will help in minimizing the uncertainty in pollution resource estimates and improving the assessment phase of planning. The conflict in criterion results for selecting the best distribution was overcome by using the weight of ranks method. We found that the Gamma distribution is the best distribution for the majority of air pollutants data in Kuala Lumpur.
Model-based software process improvement

Science.gov (United States)

Zettervall, Brenda T.

1994-01-01

The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.
Orbital angular momentum parton distributions in quark models

International Nuclear Information System (INIS)

Scopetta, S.; Vento, V.

2000-01-01

At the low energy, hadronic, scale we calculate Orbital Angular Momentum (OAM) twist-two parton distributions for the relativistic MIT bag model and for nonrelativistic quark models. We reach the scale of the data by leading order evolution in perturbative QCD. We confirm that the contribution of quarks and gluons OAM to the nucleon spin grows with Q 2 , and it can be relevant at the experimental scale, even if it is negligible at the hadronic scale, irrespective of the model used. The sign and shape of the quark OAM distribution at high Q 2 may depend strongly on the relative size of the OAM and spin distributions at the hadronic scale. Sizeable quark OAM distributions at the hadronic scale, as proposed by several authors, can produce the dominant contribution to the nucleon spin at high Q 2 . (author)
Improvement of axial power distribution synthesis methodology in CPC

International Nuclear Information System (INIS)

Kim, H. H.; Gee, S. G.;; Kim, Y. B.; In, W. K.

2003-01-01

The capability of axial power distribution synthesis in CPC plays an important role in determining the DNBR and LPD trip caused by CPC. The axial power distribution is synthesized using the cubic spline function based on the three excore detector signals. The axial power distributions are categorized into 8 function sets and each sets are stored as pre-calculated values in CPC to save the calculation time. In this study, the additional function sets, the real break-point function sets and the polynomial function are suggested to evaluate the possibility of improving the synthesis capability in CPC. In addition, RMS errors are compared and evaluated for each synthesis method. As a result, it was confirmed that the function sets stored in CPC were not optimal. The analysis result showed that RMS error could be reduced by selecting the proper function sets suggested in this study
Energy Loss, Velocity Distribution, and Temperature Distribution for a Baffled Cylinder Model, Special Report

Science.gov (United States)

Brevoort, Maurice J.

1937-01-01

In the design of a cowling a certain pressure drop across the cylinders of a radial air-cooled engine is made available. Baffles are designed to make use of this available pressure drop for cooling. The problem of cooling an air-cooled engine cylinder has been treated, for the most part, from considerations of a large heat-transfer coefficient. The knowledge of the precise cylinder characteristics that give a maximum heat-transfer coefficient should be the first consideration. The next problem is to distribute this ability to cool so that the cylinder cools uniformly. This report takes up the problem of the design of a baffle for a model cylinder. A study has been made of the important principles involved in the operation of a baffle for an engine cylinder and shows that the cooling can be improved 20% by using a correctly designed baffle. Such a gain is as effective in cooling the cylinder with the improved baffle as a 65% increase in pressure drop across the standard baffle and fin tips.
Using regional bird density distribution models to evaluate protected area networks and inform conservation planning

Science.gov (United States)

John D. Alexander; Jaime L. Stephens; Sam Veloz; Leo Salas; Josée S. Rousseau; C. John Ralph; Daniel A. Sarr

2017-01-01

As data about populations of indicator species become available, proactive strategies that improve representation of biological diversity within protected area networks should consider finer-scaled evaluations, especially in regions identified as important through course-scale analyses. We use density distribution models derived from a robust regional bird...
Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency

Science.gov (United States)

Papalexiou, Simon Michael

2018-05-01

Hydroclimatic processes come in all "shapes and sizes". They are characterized by different spatiotemporal correlation structures and probability distributions that can be continuous, mixed-type, discrete or even binary. Simulating such processes by reproducing precisely their marginal distribution and linear correlation structure, including features like intermittency, can greatly improve hydrological analysis and design. Traditionally, modelling schemes are case specific and typically attempt to preserve few statistical moments providing inadequate and potentially risky distribution approximations. Here, a single framework is proposed that unifies, extends, and improves a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific "parent" Gaussian process. A novel mathematical representation of this scheme, introducing parametric correlation transformation functions, enables straightforward estimation of the parent-Gaussian process yielding the target process after the marginal back transformation, while it provides a general description that supersedes previous specific parameterizations, offering a simple, fast and efficient simulation procedure for every stationary process at any spatiotemporal scale. This framework, also applicable for cyclostationary and multivariate modelling, is augmented with flexible parametric correlation structures that parsimoniously describe observed correlations. Real-world simulations of various hydroclimatic processes with different correlation structures and marginals, such as precipitation, river discharge, wind speed, humidity, extreme events per year, etc., as well as a multivariate example, highlight the flexibility, advantages, and complete generality of the method.
Modeling and distributed gain scheduling strategy for load frequency control in smart grids with communication topology changes.

Science.gov (United States)

Liu, Shichao; Liu, Xiaoping P; El Saddik, Abdulmotaleb

2014-03-01

In this paper, we investigate the modeling and distributed control problems for the load frequency control (LFC) in a smart grid. In contrast with existing works, we consider more practical and real scenarios, where the communication topology of the smart grid changes because of either link failures or packet losses. These topology changes are modeled as a time-varying communication topology matrix. By using this matrix, a new closed-loop power system model is proposed to integrate the communication topology changes into the dynamics of a physical power system. The globally asymptotical stability of this closed-loop power system is analyzed. A distributed gain scheduling LFC strategy is proposed to compensate for the potential degradation of dynamic performance (mean square errors of state vectors) of the power system under communication topology changes. In comparison to conventional centralized control approaches, the proposed method can improve the robustness of the smart grid to the variation of the communication network as well as to reduce computation load. Simulation results show that the proposed distributed gain scheduling approach is capable to improve the robustness of the smart grid to communication topology changes. © 2013 ISA. Published by ISA. All rights reserved.
The Transmuted Geometric-Weibull distribution: Properties, Characterizations and Regression Models

Directory of Open Access Journals (Sweden)

Zohdy M Nofal

2017-06-01

Full Text Available We propose a new lifetime model called the transmuted geometric-Weibull distribution. Some of its structural properties including ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Rényi and q-entropies and order statistics are derived. The maximum likelihood method is discussed to estimate the model parameters by means of Monte Carlo simulation study. A new location-scale regression model is introduced based on the proposed distribution. The new distribution is applied to two real data sets to illustrate its flexibility. Empirical results indicate that proposed distribution can be alternative model to other lifetime models available in the literature for modeling real data in many areas.
Modeling the spatial distribution of African buffalo (Syncerus caffer in the Kruger National Park, South Africa.

Directory of Open Access Journals (Sweden)

Kristen Hughes

Full Text Available The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012 and wet (January 2013 seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008, vegetation type (P = 0.002, and vegetation density (P = 0.010 were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005 and during the wet season (P = 0.022 compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission.
Modeling the spatial distribution of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa

Science.gov (United States)

Hughes, Kristen; Budke, Christine M.; Ward, Michael P.; Kerry, Ruth; Ingram, Ben

2017-01-01

The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012) and wet (January 2013) seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE) of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008), vegetation type (P = 0.002), and vegetation density (P = 0.010) were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005) and during the wet season (P = 0.022) compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission. PMID:28902858
A regional distributed hydrological modelling approach for flash-flood understanding and experimental design

Science.gov (United States)

Braud, Isabelle; Anquetin, Sandrine; Roux, Hélène; Vannier, Olivier; Maubourguet, Marie-Madeleine; Viallet, Pierre; Boudevillain, Brice; Dartus, Denis; Creutin, Jean-Dominique

2010-05-01

Flash floods represent the most destructive natural hazard in the Mediterranean region, causing around one billion Euros worth of damage in France over the last two decades. Flash floods are associated with extreme and rare rainfall events and usually occur in ungauged river basins. Amongst them, small-ungauged catchments are recognized as the most vulnerable to storm driven flash floods. In order to limit the damages to the population, there is a need to improve our understanding and the simulation tools for these events. In order to provide information over a whole region, hydrological models applicable at this scale, and able to take into account the spatial variability of rainfall and catchment characteristics, must be proposed. This paper presents such a regional distributed approach applied to the 8-9 September 2002 extreme event which affected the Gard region in the south-east of France. In order to identify the variables and catchment characteristics which require improved knowledge, two distributed hydrological models were set up on a set of catchments, with sizes ranging from 2.5 to 99 km2. The models differ in terms of spatial discretization and process representation. They were forced using radar data with a 1 km2 spatial resolution and 5 min time step. The model parameters were specified using the available information, namely a digital terrain model and a soil data base. The latter provides information about soil texture, soil porosity and soil depths. Soil hydraulic properties were defined using pedo-transfer functions. Data from a post-flood field survey of maximum peak discharge were used to assess the quality of the simulations. A reasonable agreement between modeled and observed values was obtained. Sensitivity studies were then performed to asses the respective impact of rainfall estimation and soil variability on the simulated discharge. The analysis shows that rainfall remains the first controlling factor of flash flood dynamics and that high

Economic Models and Algorithms for Distributed Systems

CERN Document Server

Neumann, Dirk; Altmann, Jorn; Rana, Omer F

2009-01-01

Distributed computing models for sharing resources such as Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. This book intends to discover fresh avenues of research and amendments to existing technologies, aiming at the successful deployment of commercial distributed systems
Modeling coverage gaps in haplotype frequencies via Bayesian inference to improve stem cell donor selection.

Science.gov (United States)

Louzoun, Yoram; Alter, Idan; Gragert, Loren; Albrecht, Mark; Maiers, Martin

2018-05-01

Regardless of sampling depth, accurate genotype imputation is limited in regions of high polymorphism which often have a heavy-tailed haplotype frequency distribution. Many rare haplotypes are thus unobserved. Statistical methods to improve imputation by extending reference haplotype distributions using linkage disequilibrium patterns that relate allele and haplotype frequencies have not yet been explored. In the field of unrelated stem cell transplantation, imputation of highly polymorphic human leukocyte antigen (HLA) genes has an important application in identifying the best-matched stem cell donor when searching large registries totaling over 28,000,000 donors worldwide. Despite these large registry sizes, a significant proportion of searched patients present novel HLA haplotypes. Supporting this observation, HLA population genetic models have indicated that many extant HLA haplotypes remain unobserved. The absent haplotypes are a significant cause of error in haplotype matching. We have applied a Bayesian inference methodology for extending haplotype frequency distributions, using a model where new haplotypes are created by recombination of observed alleles. Applications of this joint probability model offer significant improvement in frequency distribution estimates over the best existing alternative methods, as we illustrate using five-locus HLA frequency data from the National Marrow Donor Program registry. Transplant matching algorithms and disease association studies involving phasing and imputation of rare variants may benefit from this statistical inference framework.
Linear Power-Flow Models in Multiphase Distribution Networks: Preprint

Energy Technology Data Exchange (ETDEWEB)

Bernstein, Andrey; Dall' Anese, Emiliano

2017-05-26

This paper considers multiphase unbalanced distribution systems and develops approximate power-flow models where bus-voltages, line-currents, and powers at the point of common coupling are linearly related to the nodal net power injections. The linearization approach is grounded on a fixed-point interpretation of the AC power-flow equations, and it is applicable to distribution systems featuring (i) wye connections; (ii) ungrounded delta connections; (iii) a combination of wye-connected and delta-connected sources/loads; and, (iv) a combination of line-to-line and line-to-grounded-neutral devices at the secondary of distribution transformers. The proposed linear models can facilitate the development of computationally-affordable optimization and control applications -- from advanced distribution management systems settings to online and distributed optimization routines. Performance of the proposed models is evaluated on different test feeders.
Correlation Structures of Correlated Binomial Models and Implied Default Distribution

OpenAIRE

S. Mori; K. Kitsukawa; M. Hisakado

2006-01-01

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution h...
A semi-classical model for the description of angular distribution of light particles emitted in nuclear reactions

International Nuclear Information System (INIS)

Zhang Jingshang

1990-04-01

A semi-classical model of multi-step direct and compound nuclear reactions has been proposed to describe the angular distributions of light particles emitted in reaction processes induced by nucleons with energies of several tens of MeV. The exact closed solution for the time-dependent master equation of the exciton model is applied. Based on the Fermi gas model, the scattering kernel for two-nucleon collisions includes the influence of the Fermi motion and the Pauli exclusion principle, which give a significant improvement in the description of the rise of the backward distributions. The angle-energy correlation for the first few steps of the collision process (multi-step direct process) yields further improvements in the description of the angular distribution. The pick-up mechanism is employed to describe the composite particle emission. This reasonable physical picture reproduces the experimental data of the energy spectra of composite particles satisfactorily. The angular distribution of the emitted composite particles is determined by an angular factor in terms of the momentum conservation of the nucleons forming the composite cluster. The generalized master equation is employed for the multi-step compound process. Thus a classical approach has been established to calculate the double differential cross sections for all kinds of particles emitted in multi-step nuclear reaction processes. (author). 19 refs, 6 figs, 1 tab
Incorporating plant fossil data into species distribution models is not straightforward: Pitfalls and possible solutions

Science.gov (United States)

Moreno-Amat, Elena; Rubiales, Juan Manuel; Morales-Molino, César; García-Amorena, Ignacio

2017-08-01

The increasing development of species distribution models (SDMs) using palaeodata has created new prospects to address questions of evolution, ecology and biogeography from wider perspectives. Palaeobotanical data provide information on the past distribution of taxa at a given time and place and its incorporation on modelling has contributed to advancing the SDM field. This has allowed, for example, to calibrate models under past climate conditions or to validate projected models calibrated on current species distributions. However, these data also bear certain shortcomings when used in SDMs that may hinder the resulting ecological outcomes and eventually lead to misleading conclusions. Palaeodata may not be equivalent to present data, but instead frequently exhibit limitations and biases regarding species representation, taxonomy and chronological control, and their inclusion in SDMs should be carefully assessed. The limitations of palaeobotanical data applied to SDM studies are infrequently discussed and often neglected in the modelling literature; thus, we argue for the more careful selection and control of these data. We encourage authors to use palaeobotanical data in their SDMs studies and for doing so, we propose some recommendations to improve the robustness, reliability and significance of palaeo-SDM analyses.
Distributed hydrological modelling of the Senegal river basin - model construction and validation

DEFF Research Database (Denmark)

Andersen, J.; Refsgaard, J.C.; Jensen, Karsten Høgh

2001-01-01

A modified version of the physically-based distributed MIKE SHE model code was applied to the 375,000 km(2) Senegal River Basin. On the basis of conventional data from meteorological stations and readily accessible databases on topography, soil types, vegetation type, etc. three models with diffe......A modified version of the physically-based distributed MIKE SHE model code was applied to the 375,000 km(2) Senegal River Basin. On the basis of conventional data from meteorological stations and readily accessible databases on topography, soil types, vegetation type, etc. three models...
Predictive modeling of deep-sea fish distribution in the Azores

Science.gov (United States)

Parra, Hugo E.; Pham, Christopher K.; Menezes, Gui M.; Rosa, Alexandra; Tempera, Fernando; Morato, Telmo

2017-11-01

Understanding the link between fish and their habitat is essential for an ecosystem approach to fisheries management. However, determining such relationship is challenging, especially for deep-sea species. In this study, we applied generalized additive models (GAMs) to relate presence-absence and relative abundance data of eight economically-important fish species to environmental variables (depth, slope, aspect, substrate type, bottom temperature, salinity and oxygen saturation). We combined 13 years of catch data collected from systematic longline surveys performed across the region. Overall, presence-absence GAMs performed better than abundance models and predictions made for the observed data successfully predicted the occurrence of the eight deep-sea fish species. Depth was the most influential predictor of all fish species occurrence and abundance distributions, whereas other factors were found to be significant for some species but did not show such a clear influence. Our results predicted that despite the extensive Azores EEZ, the habitats available for the studied deep-sea fish species are highly limited and patchy, restricted to seamounts slopes and summits, offshore banks and island slopes. Despite some identified limitations, our GAMs provide an improved knowledge of the spatial distribution of these commercially important fish species in the region.
A generalized statistical model for the size distribution of wealth

International Nuclear Information System (INIS)

Clementi, F; Gallegati, M; Kaniadakis, G

2012-01-01

In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature. (paper)
A generalized statistical model for the size distribution of wealth

Science.gov (United States)

Clementi, F.; Gallegati, M.; Kaniadakis, G.

2012-12-01

In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature.
Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

Science.gov (United States)

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.
Confronting species distribution model predictions with species functional traits.

Science.gov (United States)

Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

2016-02-01

Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.
Modelling and analysis of distributed simulation protocols with distributed graph transformation

OpenAIRE

Lara, Juan de; Taentzer, Gabriele

2005-01-01

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. de Lara, and G. Taentzer, "Modelling and analysis of distributed simulation protocols with distributed graph transformation...
An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment

Directory of Open Access Journals (Sweden)

Vinothkumar Muthurajan

2016-01-01

Full Text Available Cloud computing requires the security upgrade in data transmission approaches. In general, key-based encryption/decryption (symmetric and asymmetric mechanisms ensure the secure data transfer between the devices. The symmetric key mechanisms (pseudorandom function provide minimum protection level compared to asymmetric key (RSA, AES, and ECC schemes. The presence of expired content and the irrelevant resources cause unauthorized data access adversely. This paper investigates how the integrity and secure data transfer are improved based on the Elliptic Curve based Schnorr scheme. This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. This paper utilizes the blooming filter concept to avoid the cloud server duplication. The combination of EC-Schnorr and blooming filter efficiently improves the security performance. The comparative analysis between proposed HCSA and the existing Distributed Hash Table (DHT regarding execution time, computational overhead, and auditing time with auditing requests and servers confirms the effectiveness of HCSA in the cloud security model creation.
An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment.

Science.gov (United States)

Muthurajan, Vinothkumar; Narayanasamy, Balaji

2016-01-01

Cloud computing requires the security upgrade in data transmission approaches. In general, key-based encryption/decryption (symmetric and asymmetric) mechanisms ensure the secure data transfer between the devices. The symmetric key mechanisms (pseudorandom function) provide minimum protection level compared to asymmetric key (RSA, AES, and ECC) schemes. The presence of expired content and the irrelevant resources cause unauthorized data access adversely. This paper investigates how the integrity and secure data transfer are improved based on the Elliptic Curve based Schnorr scheme. This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA) to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. This paper utilizes the blooming filter concept to avoid the cloud server duplication. The combination of EC-Schnorr and blooming filter efficiently improves the security performance. The comparative analysis between proposed HCSA and the existing Distributed Hash Table (DHT) regarding execution time, computational overhead, and auditing time with auditing requests and servers confirms the effectiveness of HCSA in the cloud security model creation.
Improving Earth/Prediction Models to Improve Network Processing

Science.gov (United States)

Wagner, G. S.

2017-12-01

The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.
Improved lumped models for transient combined convective and radiative cooling of multi-layer composite slabs

International Nuclear Information System (INIS)

An Chen; Su Jian

2011-01-01

Improved lumped parameter models were developed for the transient heat conduction in multi-layer composite slabs subjected to combined convective and radiative cooling. The improved lumped models were obtained through two-point Hermite approximations for integrals. Transient combined convective and radiative cooling of three-layer composite slabs was analyzed to illustrate the applicability of the proposed lumped models, with respect to different values of the Biot numbers, the radiation-conduction parameter, the dimensionless thermal contact resistances, the dimensionless thickness, and the dimensionless thermal conductivity. It was shown by comparison with numerical solution of the original distributed parameter model that the higher order lumped model (H 1,1 /H 0,0 approximation) yielded significant improvement of average temperature prediction over the classical lumped model. In addition, the higher order (H 1,1 /H 0,0 ) model was applied to analyze the transient heat conduction problem of steel-concrete-steel sandwich plates. - Highlights: → Improved lumped models for convective-radiative cooling of multi-layer slabs were developed. → Two-point Hermite approximations for integrals were employed. → Significant improvement over classical lumped model was achieved. → The model can be applied to high Biot number and high radiation-conduction parameter. → Transient heat conduction in steel-concrete-steel sandwich pipes was analyzed as an example.
Improving the accuracy of livestock distribution estimates through spatial interpolation.

Science.gov (United States)

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level
Improved work zone design guidelines and enhanced model of travel delays in work zones : Phase I, portability and scalability of interarrival and service time probability distribution functions for different locations in Ohio and the establishment of impr

Science.gov (United States)

2006-01-01

The project focuses on two major issues - the improvement of current work zone design practices and an analysis of : vehicle interarrival time (IAT) and speed distributions for the development of a digital computer simulation model for : queues and t...
Improving the cooling performance of electrical distribution transformer using transformer oil – Based MEPCM suspension

Directory of Open Access Journals (Sweden)

Mushtaq Ismael Hasan

2017-04-01

Full Text Available In this paper the electrical distribution transformer has been studied numerically and the effect of outside temperature on its cooling performance has been investigated. The temperature range studied covers the hot climate regions. 250 KVA distribution transformer is chosen as a study model. A novel cooling fluid is proposed to improve the cooling performance of this transformer, transformer oil-based microencapsulated phase change materials suspension is used with volume concentration (5–25% as a cooling fluid instead of pure transformer oil. Paraffin wax is used as a phase change material to make the suspension, in addition to the ability of heat absorption due to melting, the paraffin wax considered as a good electrical insulator. Results obtained show that, using of MEPCM suspension instead of pure transformer oil lead to improve the cooling performance of transformer by reducing its temperature and as a consequence increasing its protection against the breakdown. The melting fraction increased with increasing outside temperature up to certain temperature after which the melting fraction reach maximum constant value (MF = 1 which indicate that, the choosing of PCM depend on the environment in which the transformer is used.

Assessment and Reduction of Model Parametric Uncertainties: A Case Study with A Distributed Hydrological Model

Science.gov (United States)

Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.

2017-12-01

The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40
MODELING COLLISIONAL CASCADES IN DEBRIS DISKS: STEEP DUST-SIZE DISTRIBUTIONS

International Nuclear Information System (INIS)

Gáspár, András; Psaltis, Dimitrios; Rieke, George H.; Özel, Feryal

2012-01-01

We explore the evolution of the mass distribution of dust in collision-dominated debris disks, using the collisional code introduced in our previous paper. We analyze the equilibrium distribution and its dependence on model parameters by evolving over 100 models to 10 Gyr. With our numerical models, we confirm that systems reach collisional equilibrium with a mass distribution that is steeper than the traditional solution by Dohnanyi. Our model yields a quasi-steady-state slope of n(m) ∼ m –1.88 [n(a) ∼ a –3.65 ] as a robust solution for a wide range of possible model parameters. We also show that a simple power-law function can be an appropriate approximation for the mass distribution of particles in certain regimes. The steeper solution has observable effects in the submillimeter and millimeter wavelength regimes of the electromagnetic spectrum. We assemble data for nine debris disks that have been observed at these wavelengths and, using a simplified absorption efficiency model, show that the predicted slope of the particle-mass distribution generates spectral energy distributions that are in agreement with the observed ones.
Multiplicity distributions in the dual parton model

International Nuclear Information System (INIS)

Batunin, A.V.; Tolstenkov, A.N.

1985-01-01

Multiplicity distributions are calculated by means of a new mechanism of production of hadrons in a string, which was proposed previously by the authors and takes into account explicitly the valence character of the ends of the string. It is shown that allowance for this greatly improves the description of the low-energy multiplicity distributions. At superhigh energies, the contribution of the ends of the strings becomes negligibly small, but in this case multi-Pomeron contributions must be taken into account
Development of vortex model with realistic axial velocity distribution

International Nuclear Information System (INIS)

Ito, Kei; Ezure, Toshiki; Ohshima, Hiroyuki

2014-01-01

A vortex is considered as one of significant phenomena which may cause gas entrainment (GE) and/or vortex cavitation in sodium-cooled fast reactors. In our past studies, the vortex is assumed to be approximated by the well-known Burgers vortex model. However, the Burgers vortex model has a simple but unreal assumption that the axial velocity component is horizontally constant, while in real the free surface vortex has the axial velocity distribution which shows large gradient in radial direction near the vortex center. In this study, a new vortex model with realistic axial velocity distribution is proposed. This model is derived from the steady axisymmetric Navier-Stokes equation as well as the Burgers vortex model, but the realistic axial velocity distribution in radial direction is considered, which is defined to be zero at the vortex center and to approach asymptotically to zero at infinity. As the verification, the new vortex model is applied to the evaluation of a simple vortex experiment, and shows good agreements with the experimental data in terms of the circumferential velocity distribution and the free surface shape. In addition, it is confirmed that the Burgers vortex model fails to calculate accurate velocity distribution with the assumption of uniform axial velocity. However, the calculation accuracy of the Burgers vortex model can be enhanced close to that of the new vortex model in consideration of the effective axial velocity which is calculated as the average value only in the vicinity of the vortex center. (author)
A DISTRIBUTED HYPERMAP MODEL FOR INTERNET GIS

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

The rapid development of Internet technology makes it possible to integrate GIS with the Internet,forming Internet GIS.Internet GIS is based on a distributed client/server architecture and TCP/IP & IIOP.When constructing and designing Internet GIS,we face the problem of how to express information units of Internet GIS.In order to solve this problem,this paper presents a distributed hypermap model for Internet GIS.This model provides a solution to organize and manage Internet GIS information units.It also illustrates relations between two information units and in an internal information unit both on clients and servers.On the basis of this model,the paper contributes to the expressions of hypermap relations and hypermap operations.The usage of this model is shown in the implementation of a prototype system.
Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

Science.gov (United States)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.
[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

Science.gov (United States)

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.
Utilizing multiple scale models to improve predictions of extra-axial hemorrhage in the immature piglet.

Science.gov (United States)

Scott, Gregory G; Margulies, Susan S; Coats, Brittany

2016-10-01

Traumatic brain injury (TBI) is a leading cause of death and disability in the USA. To help understand and better predict TBI, researchers have developed complex finite element (FE) models of the head which incorporate many biological structures such as scalp, skull, meninges, brain (with gray/white matter differentiation), and vasculature. However, most models drastically simplify the membranes and substructures between the pia and arachnoid membranes. We hypothesize that substructures in the pia-arachnoid complex (PAC) contribute substantially to brain deformation following head rotation, and that when included in FE models accuracy of extra-axial hemorrhage prediction improves. To test these hypotheses, microscale FE models of the PAC were developed to span the variability of PAC substructure anatomy and regional density. The constitutive response of these models were then integrated into an existing macroscale FE model of the immature piglet brain to identify changes in cortical stress distribution and predictions of extra-axial hemorrhage (EAH). Incorporating regional variability of PAC substructures substantially altered the distribution of principal stress on the cortical surface of the brain compared to a uniform representation of the PAC. Simulations of 24 non-impact rapid head rotations in an immature piglet animal model resulted in improved accuracy of EAH prediction (to 94 % sensitivity, 100 % specificity), as well as a high accuracy in regional hemorrhage prediction (to 82-100 % sensitivity, 100 % specificity). We conclude that including a biofidelic PAC substructure variability in FE models of the head is essential for improved predictions of hemorrhage at the brain/skull interface.
Modelling the potential distribution of Betula utilis in the Himalaya

Directory of Open Access Journals (Sweden)

Maria Bobrowski

2017-07-01

Full Text Available Developing sustainable adaptation pathways under climate change conditions in mountain regions requires accurate predictions of treeline shifts and future distribution ranges of treeline species. Here, we model for the first time the potential distribution of Betula utilis, a principal Himalayan treeline species, to provide a basis for the analysis of future range shifts. Our target species Betula utilis is widespread at alpine treelines in the Himalayan mountains, the distribution range extends across the Himalayan mountain range. Our objective is to model the potential distribution of B. utilis in relation to current climate conditions. We generated a dataset of 590 occurrence records and used 24 variables for ecological niche modelling. We calibrated Generalized Linear Models using the Akaike Information Criterion (AIC and evaluated model performance using threshold-independent (AUC, Area Under the Curve and threshold-dependent (TSS, True Skill Statistics characteristics as well as visual assessments of projected distribution maps. We found two temperature-related (Mean Temperature of the Wettest Quarter, Temperature Annual Range and three precipitation-related variables (Precipitation of the Coldest Quarter, Average Precipitation of March, April and May and Precipitation Seasonality to be useful for predicting the potential distribution of B. utilis. All models had high predictive power (AUC ≥ 0.98 and TSS ≥ 0.89. The projected suitable area in the Himalayan mountains varies considerably, with most extensive distribution in the western and central Himalayan region. A substantial difference between potential and real distribution in the eastern Himalaya points to decreasing competitiveness of B. utilis under more oceanic conditions in the eastern part of the mountain system. A comparison between the vegetation map of Schweinfurth (1957 and our current predictions suggests that B. utilis does not reach the upper elevational limit in
Species distribution models of tropical deep-sea snappers.

Directory of Open Access Journals (Sweden)

Céline Gomez

Full Text Available Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management of these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data for the main harvested species in the Western Central Pacific Ocean. We used bathymetric and water temperature data to develop presence-only species distribution models for the commercially exploited deep-sea snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, and Aphareus Cuvier 1830. We evaluated the performance of four different algorithms (CTA, GLM, MARS, and MAXENT within the BIOMOD framework to obtain an ensemble of predicted distributions. We projected these predictions across the Western Central Pacific Ocean to produce maps of potential deep-sea snapper distributions in 32 countries and territories. Depth was consistently the best predictor of presence for all species groups across all models. Bathymetric slope was consistently the poorest predictor. Temperature at depth was a good predictor of presence for GLM only. Model precision was highest for MAXENT and CTA. There were strong regional patterns in predicted distribution of suitable habitat, with the largest areas of suitable habitat (> 35% of the Exclusive Economic Zone predicted in seven South Pacific countries and territories (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu and Wallis & Futuna. Predicted habitat also varied among species, with the proportion of predicted habitat highest for Aphareus and lowest for Etelis. Despite data paucity, the relationship between deep-sea snapper presence and their environments was sufficiently strong to predict their distribution across a large area of the Pacific Ocean. Our results therefore provide a strong baseline for designing monitoring programs that balance resource exploitation and
Modeling a Distribution of Mortgage Credit Losses

Czech Academy of Sciences Publication Activity Database

Gapko, Petr; Šmíd, Martin

2010-01-01

Roč. 23, č. 23 (2010), s. 1-23 R&D Projects: GA ČR GA402/09/0965; GA ČR GD402/09/H045 Grant - others:Univerzita Karlova - GAUK(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : Credit Risk * Mortgage * Delinquency Rate * Generalized Hyperbolic Distribution * Normal Distribution Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2010/E/gapko-modeling a distribution of mortgage credit losses-ies wp.pdf
The Distributed Geothermal Market Demand Model (dGeo): Documentation

Energy Technology Data Exchange (ETDEWEB)

McCabe, Kevin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mooney, Meghan E [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sigrin, Benjamin O [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Liu, Xiaobing [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-11-06

The National Renewable Energy Laboratory (NREL) developed the Distributed Geothermal Market Demand Model (dGeo) as a tool to explore the potential role of geothermal distributed energy resources (DERs) in meeting thermal energy demands in the United States. The dGeo model simulates the potential for deployment of geothermal DERs in the residential and commercial sectors of the continental United States for two specific technologies: ground-source heat pumps (GHP) and geothermal direct use (DU) for district heating. To quantify the opportunity space for these technologies, dGeo leverages a highly resolved geospatial database and robust bottom-up, agent-based modeling framework. This design is consistent with others in the family of Distributed Generation Market Demand models (dGen; Sigrin et al. 2016), including the Distributed Solar Market Demand (dSolar) and Distributed Wind Market Demand (dWind) models. dGeo is intended to serve as a long-term scenario-modeling tool. It has the capability to simulate the technical potential, economic potential, market potential, and technology deployment of GHP and DU through the year 2050 under a variety of user-defined input scenarios. Through these capabilities, dGeo can provide substantial analytical value to various stakeholders interested in exploring the effects of various techno-economic, macroeconomic, financial, and policy factors related to the opportunity for GHP and DU in the United States. This report documents the dGeo modeling design, methodology, assumptions, and capabilities.
The effects of model and data complexity on predictions from species distributions models

DEFF Research Database (Denmark)

García-Callejas, David; Bastos, Miguel

2016-01-01

How complex does a model need to be to provide useful predictions is a matter of continuous debate across environmental sciences. In the species distributions modelling literature, studies have demonstrated that more complex models tend to provide better fits. However, studies have also shown...... that predictive performance does not always increase with complexity. Testing of species distributions models is challenging because independent data for testing are often lacking, but a more general problem is that model complexity has never been formally described in such studies. Here, we systematically...
Problems with using the normal distribution--and ways to improve quality and efficiency of data analysis.

Directory of Open Access Journals (Sweden)

Eckhard Limpert

Full Text Available BACKGROUND: The gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by mean ± SD, or with the standard error of the mean, mean ± SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. METHODOLOGY/PRINCIPAL FINDINGS: Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the "95% range check", their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log- normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x/, times-divide, and notation. Analogous to mean ± SD, it connects the multiplicative (or geometric mean mean * and the multiplicative standard deviation s* in the form mean * x/s*, that is advantageous and recommended. CONCLUSIONS/SIGNIFICANCE: The corresponding shift from the symmetric to the asymmetric view will substantially increase both, recognition of data distributions, and interpretation quality. It will allow for savings in sample size that can be considerable. Moreover, this is in line with ethical responsibility. Adequate models will improve concepts and theories, and provide deeper insight into science and life.
Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape

International Nuclear Information System (INIS)

Serinaldi, Francesco

2011-01-01

In the context of the liberalized and deregulated electricity markets, price forecasting has become increasingly important for energy company's plans and market strategies. Within the class of the time series models that are used to perform price forecasting, the subclasses of methods based on stochastic time series and causal models commonly provide point forecasts, whereas the corresponding uncertainty is quantified by approximate or simulation-based confidence intervals. Aiming to improve the uncertainty assessment, this study introduces the Generalized Additive Models for Location, Scale and Shape (GAMLSS) to model the dynamically varying distribution of prices. The GAMLSS allow fitting a variety of distributions whose parameters change according to covariates via a number of linear and nonlinear relationships. In this way, price periodicities, trends and abrupt changes characterizing both the position parameter (linked to the expected value of prices), and the scale and shape parameters (related to price volatility, skewness, and kurtosis) can be explicitly incorporated in the model setup. Relying on the past behavior of the prices and exogenous variables, the GAMLSS enable the short-term (one-day ahead) forecast of the entire distribution of prices. The approach was tested on two datasets from the widely studied California Power Exchange (CalPX) market, and the less mature Italian Power Exchange (IPEX). CalPX data allow comparing the GAMLSS forecasting performance with published results obtained by different models. The study points out that the GAMLSS framework can be a flexible alternative to several linear and nonlinear stochastic models. - Research Highlights: ► Generalized Additive Models for Location, Scale and Shape (GAMLSS) are used to model electricity prices' time series. ► GAMLSS provide the entire dynamicaly varying distribution function of prices resorting to a suitable set of covariates that drive the instantaneous values of the parameters
Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models

Science.gov (United States)

Fieberg, John R.; Forester, James D.; Street, Garrett M.; Johnson, Douglas H.; ArchMiller, Althea A.; Matthiopoulos, Jason

2018-01-01

“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.
A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement.

Science.gov (United States)

Kranstauber, Bart; Kays, Roland; Lapoint, Scott D; Wikelski, Martin; Safi, Kamran

2012-07-01

1. The recently developed Brownian bridge movement model (BBMM) has advantages over traditional methods because it quantifies the utilization distribution of an animal based on its movement path rather than individual points and accounts for temporal autocorrelation and high data volumes. However, the BBMM assumes unrealistic homogeneous movement behaviour across all data. 2. Accurate quantification of the utilization distribution is important for identifying the way animals use the landscape. 3. We improve the BBMM by allowing for changes in behaviour, using likelihood statistics to determine change points along the animal's movement path. 4. This novel extension, outperforms the current BBMM as indicated by simulations and examples of a territorial mammal and a migratory bird. The unique ability of our model to work with tracks that are not sampled regularly is especially important for GPS tags that have frequent failed fixes or dynamic sampling schedules. Moreover, our model extension provides a useful one-dimensional measure of behavioural change along animal tracks. 5. This new method provides a more accurate utilization distribution that better describes the space use of realistic, behaviourally heterogeneous tracks. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
Distributed modeling for road authorities

NARCIS (Netherlands)

Luiten, G.T.; Bõhms, H.M.; Nederveen, S. van; Bektas, E.

2013-01-01

A great challenge for road authorities is to improve the effectiveness and efficiency of their core processes by improving data exchange and sharing using new technologies such as building information modeling (BIM). BIM has already been successfully implemented in other sectors, such as
Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

Science.gov (United States)

Huang, Y. F.; Tsang, Y. P.

2017-12-01

Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.
State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

Directory of Open Access Journals (Sweden)

O. Rakovec

2012-09-01

Full Text Available This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property.

Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km², a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1 various sets of the spatially distributed discharge gauges and (2 the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

Species-free species distribution models describe macroecological properties of protected area networks.

Science.gov (United States)

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have
Modeling particle transport and discoloration risk in drinking water distribution networks

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J. van Summeren

2017-10-01

Full Text Available Discoloration of drinking water is a worldwide phenomenon caused by accumulation and subsequent remobilization of particulate matter in drinking water distribution systems (DWDSs. It contributes a substantial fraction of customer complaints to water utilities. Accurate discoloration risk predictions could improve system operation by allowing for more effective programs on cleaning and prevention actions and field measurements, but are challenged by incomplete understanding on the origins and properties of particles and a complex and not fully understood interplay of processes in distribution networks. In this paper, we assess and describe relevant hydraulic processes that govern particle transport in turbulent pipe flow, including gravitational settling, bed-load transport, and particle entrainment into suspension. We assess which transport mechanisms are dominant for a range of bulk flow velocities, particle diameters, and particle mass densities, which includes common conditions for DWDSs in the Netherlands, the UK, and Australia. Our analysis shows that the theoretically predicted particle settling velocity and threshold shear stresses for incipient particle motion are in the same range as, but more variable than, previous estimates from lab experiments, field measurements, and modeling. The presented material will be used in the future development of a numerical modeling tool to determine and predict the spatial distribution of particulate material and discoloration risk in DWDSs. Our approach is aimed at understanding specific causalities and processes, which can complement data-driven approaches.
Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

Science.gov (United States)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark
A Hierarchy Model of Income Distribution

OpenAIRE

Fix, Blair

2018-01-01

Based on worldly experience, most people would agree that firms are hierarchically organized, and that pay tends to increase as one moves up the hierarchy. But how this hierarchical structure affects income distribution has not been widely studied. To remedy this situation, this paper presents a new model of income distribution that explores the effects of social hierarchy. This ‘hierarchy model’ takes the limited available evidence on the structure of firm hierarchies and generalizes it to c...
Anti-3D Weapon Model Detection for Safe 3D Printing Based on Convolutional Neural Networks and D2 Shape Distribution

Directory of Open Access Journals (Sweden)

Giao N. Pham

2018-03-01

Full Text Available With the development of 3D printing, weapons are easily printed without any restriction from the production managers. Therefore, anti-3D weapon model detection is necessary issue in safe 3D printing to prevent the printing of 3D weapon models. In this paper, we would like to propose an anti-3D weapon model detection algorithm to prevent the printing of anti-3D weapon models for safe 3D printing based on the D2 shape distribution and an improved convolutional neural networks (CNNs. The purpose of the proposed algorithm is to detect anti-3D weapon models when they are used in 3D printing. The D2 shape distribution is computed from random points on the surface of a 3D weapon model and their geometric features in order to construct a D2 vector. The D2 vector is then trained by improved CNNs. The CNNs are used to detect anti-3D weapon models for safe 3D printing by training D2 vectors which have been constructed from the D2 shape distribution of 3D weapon models. Experiments with 3D weapon models proved that the D2 shape distribution of 3D weapon models in the same class is the same. Training and testing results also verified that the accuracy of the proposed algorithm is higher than the conventional works. The proposed algorithm is applied in a small application, and it could detect anti-3D weapon models for safe 3D printing.
Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

Science.gov (United States)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model
Correlation Structures of Correlated Binomial Models and Implied Default Distribution

Science.gov (United States)

Mori, Shintaro; Kitsukawa, Kenji; Hisakado, Masato

2008-11-01

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.
Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model

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G. Moretti

2008-08-01

Full Text Available The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero River. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km². The hydrological model is first calibrated by using a 1-year record of hourly meteorological data and river flows observed at the outlet of the 1294 km² wide Secchia River basin, of which the Riarbero is a tributary. The model is then validated by performing a 100-year long simulation of synthetic river flow data, which allowed us to compare the simulated and observed flood frequency distributions at the Secchia River outlet and the internal cross river section of Cavola Bridge, where the basin area is 337 km². Finally, another simulation of hourly river flows was performed by referring to the outlet of the Riarbero River, therefore allowing us to estimate the related flood frequency distribution. The results were validated by using estimates of peak river flow obtained by applying hydrological similarity principles and a regional method. The results show that the flood flow estimated through the application of the distributed model is consistent with the estimate provided by the regional procedure as well as the behaviors of the river banks. Conversely, the method based on hydrological similarity delivers an estimate that seems to be not as reliable. The analysis highlights interesting perspectives for the application of
Improved models of dense anharmonic lattices

Energy Technology Data Exchange (ETDEWEB)

Rosenau, P., E-mail: rosenau@post.tau.ac.il; Zilburg, A.

2017-01-15

We present two improved quasi-continuous models of dense, strictly anharmonic chains. The direct expansion which includes the leading effect due to lattice dispersion, results in a Boussinesq-type PDE with a compacton as its basic solitary mode. Without increasing its complexity we improve the model by including additional terms in the expanded interparticle potential with the resulting compacton having a milder singularity at its edges. A particular care is applied to the Hertz potential due to its non-analyticity. Since, however, the PDEs of both the basic and the improved model are ill posed, they are unsuitable for a study of chains dynamics. Using the bond length as a state variable we manipulate its dispersion and derive a well posed fourth order PDE. - Highlights: • An improved PDE model of a Newtonian lattice renders compacton solutions. • Compactons are classical solutions of the improved model and hence amenable to standard analysis. • An alternative well posed model enables to study head on interactions of lattices' solitary waves. • Well posed modeling of Hertz potential.
Simulating train movement in an urban railway based on an improved car-following model

International Nuclear Information System (INIS)

Ye Jing-Jing; Jin Xin-Min; Li Ke-Ping

2013-01-01

Based on the optimal velocity car-following model, in this paper, we propose an improved model for simulating train movement in an urban railway in which the regenerative energy of a train is considered. Here a new additional term is introduced into a traditional car-following model. Our aim is to analyze and discuss the dynamic characteristics of the train movement when the regenerative energy is utilized by the electric locomotive. The simulation results indicate that the improved car-following model is suitable for simulating the train movement. Further, some qualitative relationships between regenerative energy and dynamic characteristics of a train are investigated, such as the measurement data of regenerative energy presents a power-law distribution. Our results are useful for optimizing the design and plan of urban railway systems. (general)
Video distribution system cost model

Science.gov (United States)

Gershkoff, I.; Haspert, J. K.; Morgenstern, B.

1980-01-01

A cost model that can be used to systematically identify the costs of procuring and operating satellite linked communications systems is described. The user defines a network configuration by specifying the location of each participating site, the interconnection requirements, and the transmission paths available for the uplink (studio to satellite), downlink (satellite to audience), and voice talkback (between audience and studio) segments of the network. The model uses this information to calculate the least expensive signal distribution path for each participating site. Cost estimates are broken downy by capital, installation, lease, operations and maintenance. The design of the model permits flexibility in specifying network and cost structure.
Newtonian nudging for a Richards equation-based distributed hydrological model

Science.gov (United States)

Paniconi, Claudio; Marrocu, Marino; Putti, Mario; Verbunt, Mark

The objective of data assimilation is to provide physically consistent estimates of spatially distributed environmental variables. In this study a relatively simple data assimilation method has been implemented in a relatively complex hydrological model. The data assimilation technique is Newtonian relaxation or nudging, in which model variables are driven towards observations by a forcing term added to the model equations. The forcing term is proportional to the difference between simulation and observation (relaxation component) and contains four-dimensional weighting functions that can incorporate prior knowledge about the spatial and temporal variability and characteristic scales of the state variable(s) being assimilated. The numerical model couples a three-dimensional finite element Richards equation solver for variably saturated porous media and a finite difference diffusion wave approximation based on digital elevation data for surface water dynamics. We describe the implementation of the data assimilation algorithm for the coupled model and report on the numerical and hydrological performance of the resulting assimilation scheme. Nudging is shown to be successful in improving the hydrological simulation results, and it introduces little computational cost, in terms of CPU and other numerical aspects of the model's behavior, in some cases even improving numerical performance compared to model runs without nudging. We also examine the sensitivity of the model to nudging term parameters including the spatio-temporal influence coefficients in the weighting functions. Overall the nudging algorithm is quite flexible, for instance in dealing with concurrent observation datasets, gridded or scattered data, and different state variables, and the implementation presented here can be readily extended to any of these features not already incorporated. Moreover the nudging code and tests can serve as a basis for implementation of more sophisticated data assimilation
Generalization of the normal-exponential model: exploration of a more accurate parametrisation for the signal distribution on Illumina BeadArrays.

Science.gov (United States)

Plancade, Sandra; Rozenholc, Yves; Lund, Eiliv

2012-12-11

Illumina BeadArray technology includes non specific negative control features that allow a precise estimation of the background noise. As an alternative to the background subtraction proposed in BeadStudio which leads to an important loss of information by generating negative values, a background correction method modeling the observed intensities as the sum of the exponentially distributed signal and normally distributed noise has been developed. Nevertheless, Wang and Ye (2012) display a kernel-based estimator of the signal distribution on Illumina BeadArrays and suggest that a gamma distribution would represent a better modeling of the signal density. Hence, the normal-exponential modeling may not be appropriate for Illumina data and background corrections derived from this model may lead to wrong estimation. We propose a more flexible modeling based on a gamma distributed signal and a normal distributed background noise and develop the associated background correction, implemented in the R-package NormalGamma. Our model proves to be markedly more accurate to model Illumina BeadArrays: on the one hand, it is shown on two types of Illumina BeadChips that this model offers a more correct fit of the observed intensities. On the other hand, the comparison of the operating characteristics of several background correction procedures on spike-in and on normal-gamma simulated data shows high similarities, reinforcing the validation of the normal-gamma modeling. The performance of the background corrections based on the normal-gamma and normal-exponential models are compared on two dilution data sets, through testing procedures which represent various experimental designs. Surprisingly, we observe that the implementation of a more accurate parametrisation in the model-based background correction does not increase the sensitivity. These results may be explained by the operating characteristics of the estimators: the normal-gamma background correction offers an improvement
Estimating the cost of improving quality in electricity distribution: A parametric distance function approach

International Nuclear Information System (INIS)

Coelli, Tim J.; Gautier, Axel; Perelman, Sergio; Saplacan-Pop, Roxana

2013-01-01

The quality of electricity distribution is being more and more scrutinized by regulatory authorities, with explicit reward and penalty schemes based on quality targets having been introduced in many countries. It is then of prime importance to know the cost of improving the quality for a distribution system operator. In this paper, we focus on one dimension of quality, the continuity of supply, and we estimated the cost of preventing power outages. For that, we make use of the parametric distance function approach, assuming that outages enter in the firm production set as an input, an imperfect substitute for maintenance activities and capital investment. This allows us to identify the sources of technical inefficiency and the underlying trade-off faced by operators between quality and other inputs and costs. For this purpose, we use panel data on 92 electricity distribution units operated by ERDF (Electricité de France - Réseau Distribution) in the 2003–2005 financial years. Assuming a multi-output multi-input translog technology, we estimate that the cost of preventing one interruption is equal to 10.7€ for an average DSO. Furthermore, as one would expect, marginal quality improvements tend to be more expensive as quality itself improves. - Highlights: ► We estimate the implicit cost of outages for the main distribution company in France. ► For this purpose, we make use of a parametric distance function approach. ► Marginal quality improvements tend to be more expensive as quality itself improves. ► The cost of preventing one interruption varies from 1.8 € to 69.2 € (2005 prices). ► We estimate that, in average, it lays 33% above the regulated price of quality.
Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling

Science.gov (United States)

Fraser, Stuart A.; Wood, Nathan J.; Johnston, David A.; Leonard, Graham S.; Greening, Paul D.; Rossetto, Tiziana

2014-01-01

Evacuation of the population from a tsunami hazard zone is vital to reduce life-loss due to inundation. Geospatial least-cost distance modelling provides one approach to assessing tsunami evacuation potential. Previous models have generally used two static exposure scenarios and fixed travel speeds to represent population movement. Some analyses have assumed immediate departure or a common evacuation departure time for all exposed population. Here, a method is proposed to incorporate time-variable exposure, distributed travel speeds, and uncertain evacuation departure time into an existing anisotropic least-cost path distance framework. The method is demonstrated for hypothetical local-source tsunami evacuation in Napier City, Hawke's Bay, New Zealand. There is significant diurnal variation in pedestrian evacuation potential at the suburb level, although the total number of people unable to evacuate is stable across all scenarios. Whilst some fixed travel speeds approximate a distributed speed approach, others may overestimate evacuation potential. The impact of evacuation departure time is a significant contributor to total evacuation time. This method improves least-cost modelling of evacuation dynamics for evacuation planning, casualty modelling, and development of emergency response training scenarios. However, it requires detailed exposure data, which may preclude its use in many situations.
Assessment of subchannel code ASSERT-PV for flow-distribution predictions

International Nuclear Information System (INIS)

Nava-Dominguez, A.; Rao, Y.F.; Waddington, G.M.

2014-01-01

Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles
Assessment of subchannel code ASSERT-PV for flow-distribution predictions

Energy Technology Data Exchange (ETDEWEB)

Nava-Dominguez, A., E-mail: navadoma@aecl.ca; Rao, Y.F., E-mail: raoy@aecl.ca; Waddington, G.M., E-mail: waddingg@aecl.ca

2014-08-15

Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles.
Improving Clinical Trial Cohort Definition Criteria and Enrollment with Distributional Semantic Matching

OpenAIRE

Shao, Jianyin; Gouripeddi, Ramkiran; Facelli, Julio C.

2016-01-01

Shao, J., Gouripeddi, R., & Facelli, J.C. (2016). Improving Clinical Trial Cohort Definition Criteria and Enrollment with Distributional Semantic Matching (poster). Research Reproducibility 2016. Salt Lake City, UT, USA
A Three-Phase Microgrid Restoration Model Considering Unbalanced Operation of Distributed Generation

International Nuclear Information System (INIS)

Wang, Zeyu; Wang, Jianhui; Chen, Chen

2016-01-01

Recent severe outages highlight the urgency of improving grid resiliency in the U.S. Microgrid formation schemes are proposed to restore critical loads after outages occur. Most distribution networks have unbalanced configurations that are not represented in sufficient detail by single-phase models. This study provides a microgrid formation plan that adopts a three-phase network model to represent unbalanced distribution networks. The problem formulation has a quadratic objective function with mixed-integer linear constraints. The three-phase network model enables us to examine the three-phase power outputs of distributed generators (DGs), preventing unbalanced operation that might trip DGs. Because the DG unbalanced operation constraint is non-convex, an iterative process is presented that checks whether the unbalanced operation limits for DGs are satisfied after each iteration of optimization. We also develop a relatively conservative linear approximation on the unbalanced operation constraint to handle larger networks. Compared with the iterative solution process, the conservative linear approximation is able to accelerate the solution process at the cost of sacrificing optimality to a limited extent. Simulation in the IEEE 34 node and IEEE 123 test feeders indicate that the proposed method yields more practical microgrid formations results. In addition, this paper explores the coordinated operation of DGs and energy storage (ES) installations. The unbalanced three-phase outputs of ESs combined with the relatively balanced outputs of DGs could supply unbalanced loads. In conclusion, the case study also validates the DG-ES coordination.
Multiphase flow modeling of a crude-oil spill site with a bimodal permeability distribution

Science.gov (United States)

Dillard, Leslie A.; Essaid, Hedeff I.; Herkelrath, William N.

1997-01-01

Fluid saturation, particle-size distribution, and porosity measurements were obtained from 269 core samples collected from six boreholes along a 90-m transect at a subregion of a crude-oil spill site, the north pool, near Bemidji, Minnesota. The oil saturation data, collected 11 years after the spill, showed an irregularly shaped oil body that appeared to be affected by sediment spatial variability. The particle-size distribution data were used to estimate the permeability (k) and retention curves for each sample. An additional 344 k estimates were obtained from samples previously collected at the north pool. The 613 k estimates were distributed bimodal lognormally with the two population distributions corresponding to the two predominant lithologies: a coarse glacial outwash deposit and fine-grained interbedded lenses. A two-step geostatistical approach was used to generate a conditioned realization of k representing the bimodal heterogeneity. A cross-sectional multiphase flow model was used to simulate the flow of oil and water in the presence of air along the north pool transect for an 11-year period. The inclusion of a representation of the bimodal aquifer heterogeneity was crucial for reproduction of general features of the observed oil body. If the bimodal heterogeneity was characterized, hysteresis did not have to be incorporated into the model because a hysteretic effect was produced by the sediment spatial variability. By revising the relative permeability functional relation, an improved reproduction of the observed oil saturation distribution was achieved. The inclusion of water table fluctuations in the model did not significantly affect the simulated oil saturation distribution.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

DEFF Research Database (Denmark)

Soares, Tiago; Pereira, Fábio; Morais, Hugo

2015-01-01

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used...... in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed......, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle...
Advanced Distribution Network Modelling with Distributed Energy Resources

Science.gov (United States)

O'Connell, Alison

The addition of new distributed energy resources, such as electric vehicles, photovoltaics, and storage, to low voltage distribution networks means that these networks will undergo major changes in the future. Traditionally, distribution systems would have been a passive part of the wider power system, delivering electricity to the customer and not needing much control or management. However, the introduction of these new technologies may cause unforeseen issues for distribution networks, due to the fact that they were not considered when the networks were originally designed. This thesis examines different types of technologies that may begin to emerge on distribution systems, as well as the resulting challenges that they may impose. Three-phase models of distribution networks are developed and subsequently utilised as test cases. Various management strategies are devised for the purposes of controlling distributed resources from a distribution network perspective. The aim of the management strategies is to mitigate those issues that distributed resources may cause, while also keeping customers' preferences in mind. A rolling optimisation formulation is proposed as an operational tool which can manage distributed resources, while also accounting for the uncertainties that these resources may present. Network sensitivities for a particular feeder are extracted from a three-phase load flow methodology and incorporated into an optimisation. Electric vehicles are the focus of the work, although the method could be applied to other types of resources. The aim is to minimise the cost of electric vehicle charging over a 24-hour time horizon by controlling the charge rates and timings of the vehicles. The results demonstrate the advantage that controlled EV charging can have over an uncontrolled case, as well as the benefits provided by the rolling formulation and updated inputs in terms of cost and energy delivered to customers. Building upon the rolling optimisation, a
Input modeling with phase-type distributions and Markov models theory and applications

CERN Document Server

Buchholz, Peter; Felko, Iryna

2014-01-01

Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in the area. Due to progress made in recent years with respect to new algorithms to generate PH distributions and Markovian arrival processes from measured data, the models outlined are useful alternatives to other distributions or stochastic processes used for input modeling. Graduate students and researchers in applied probability, operations research and computer science along with practitioners using simulation or analytical models for performance analysis and capacity planning will find the unified notation and up-to-date results presented useful. Input modeling is the key step in model based system analysis to adequately describe the load of a system using stochastic models. The goal of input modeling is to find a stochastic model to describe a sequence of measurements from a real system...
Mid-ventilation position planning: Optimal model for dose distribution in lung tumour

International Nuclear Information System (INIS)

Benchalal, M.; Leseur, J.; Chajon, E.; Cazoulat, G.; Haigron, P.; Simon, A.; Bellec, J.; Lena, H.; Crevoisier, R. de

2012-01-01

Purpose. - The dose distribution for lung tumour is estimated using a 3D-CT scan, and since a person breathes while the images are captured, the dose distribution doesn't reflect the reality. A 4D-CT scan integrates the motion of the tumour during breathing and, therefore, provides us with important information regarding tumour's motion in all directions, the motion volume (ITV) and the time-weighted average position (MVP). Patient and methods. - Based on these two concepts, we have estimated, for a lung carcinoma case a 3D dose distribution from a 3D-CT scan, and a 4D dose distribution from a 4-D CT scan. To this, we have applied a non-rigid registration to estimate the cumulative dose. Results. - Our study shows that the 4D dose estimation of the GTV is almost the same when made using MVP and ITV concepts, but sparring of the healthy lung is better done using the MPV model (MVP), as compared to the ITV model. This improvement of the therapeutic index allows, from a projection on the theoretical maximal dose to PTV (strictly restricted to doses for the lungs and the spinal cord), for an increase of about 11% on the total dose (maximal dose of 86 Gy for the ITV and 96 Gy for the MVP). Conclusion. - Further studies with more patients are needed to confirm our data. (authors)
Development of a distributed air pollutant dry deposition modeling framework

International Nuclear Information System (INIS)

Hirabayashi, Satoshi; Kroll, Charles N.; Nowak, David J.

2012-01-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. - Highlights: ► A distributed air pollutant dry deposition modeling system was developed. ► The developed system enhances the functionality of i-Tree Eco. ► The developed system employs nationally available input datasets. ► The developed system is transferable to any U.S. city. ► Future planting and protection spots were visually identified in a case study. - Employing nationally available datasets and a GIS, this study will provide urban forest managers in U.S. cities a framework to quantify and visualize urban forest structure and its air pollution removal effect.
Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

Science.gov (United States)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.
A traction control strategy with an efficiency model in a distributed driving electric vehicle.

Science.gov (United States)

Lin, Cheng; Cheng, Xingqun

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the two-dimensional design space composed of the acceleration pedal signal and the vehicle speed. The sliding mode control strategy for the joint roads and the efficiency model for the typical drive cycles were simulated. Simulation results show that the proposed driving control approach has the potential to apply to different road surfaces. It keeps the wheels' slip ratios within the stable zone and improves the fuel economy on the premise of tracking the driver's intention.
A Traction Control Strategy with an Efficiency Model in a Distributed Driving Electric Vehicle

Science.gov (United States)

Lin, Cheng

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the two-dimensional design space composed of the acceleration pedal signal and the vehicle speed. The sliding mode control strategy for the joint roads and the efficiency model for the typical drive cycles were simulated. Simulation results show that the proposed driving control approach has the potential to apply to different road surfaces. It keeps the wheels' slip ratios within the stable zone and improves the fuel economy on the premise of tracking the driver's intention. PMID:25197697
Orbitally shaken shallow fluid layers. II. An improved wall shear stress model

Science.gov (United States)

Alpresa, Paola; Sherwin, Spencer; Weinberg, Peter; van Reeuwijk, Maarten

2018-03-01

A new model for the analytical prediction of wall shear stress distributions at the base of orbitally shaken shallow fluid layers is developed. This model is a generalisation of the classical extended Stokes solution and will be referred to as the potential theory-Stokes model. The model is validated using a large set of numerical simulations covering a wide range of flow regimes representative of those used in laboratory experiments. It is demonstrated that the model is in much better agreement with the simulation data than the classical Stokes solution, improving the prediction in 63% of the studied cases. The central assumption of the model—which is to link the wall shear stress with the surface velocity—is shown to hold remarkably well over all regimes covered.
Football fever: self-affirmation model for goal distributions

Directory of Open Access Journals (Sweden)

W. Janke

2009-01-01

Full Text Available The outcome of football games, as well as matches of most other popular team sports, depends on a combination of the skills of players and coaches and a number of external factors which, due to their complex nature, are presumably best viewed as random. Such parameters include the unpredictabilities of playing the ball, the players' shape of the day or environmental conditions such as the weather and the behavior of the audience. Under such circumstances, it appears worthwhile to analyze football score data with the toolbox of mathematical statistics in order to separate deterministic from stochastic effects and see what impact the cooperative and social nature of the "agents" of the system has on the resulting stochastic observables. Considering the probability distributions of scored goals for the home and away teams, it turns out that especially the tails of the distributions are not well described by the Poissonian or binomial model resulting from the assumption of uncorrelated random events. On the contrary, some more specific probability densities such as those discussed in the context of extreme-value statistics or the so-called negative binomial distribution fit these data rather well. There seemed to be no good argument to date, however, why the simplest Poissonian model fails and, instead, the latter distributions should be observed. To fill this gap, we introduced a number of microscopic models for the scoring behavior, resulting in a Bernoulli random process with a simple component of self-affirmation. These models allow us to represent the observed probability distributions surprisingly well, and the phenomenological distributions used earlier can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments, including data from all past tournaments of the "FIFA World Cup" series, and found the proposed models to be applicable in
Modeling of Drift Effects on Solar Tower Concentrated Flux Distributions

Directory of Open Access Journals (Sweden)

Luis O. Lara-Cerecedo

2016-01-01

Full Text Available A novel modeling tool for calculation of central receiver concentrated flux distributions is presented, which takes into account drift effects. This tool is based on a drift model that includes different geometrical error sources in a rigorous manner and on a simple analytic approximation for the individual flux distribution of a heliostat. The model is applied to a group of heliostats of a real field to obtain the resulting flux distribution and its variation along the day. The distributions differ strongly from those obtained assuming the ideal case without drift or a case with a Gaussian tracking error function. The time evolution of peak flux is also calculated to demonstrate the capabilities of the model. The evolution of this parameter also shows strong differences in comparison to the case without drift.
Improved steamflood analytical model

Energy Technology Data Exchange (ETDEWEB)

Chandra, S.; Mamora, D.D. [Society of Petroleum Engineers, Richardson, TX (United States)]|[Texas A and M Univ., TX (United States)

2005-11-01

Predicting the performance of steam flooding can help in the proper execution of enhanced oil recovery (EOR) processes. The Jones model is often used for analytical steam flooding performance prediction, but it does not accurately predict oil production peaks. In this study, an improved steam flood model was developed by modifying 2 of the 3 components of the capture factor in the Jones model. The modifications were based on simulation results from a Society of Petroleum Engineers (SPE) comparative project case model. The production performance of a 5-spot steamflood pattern unit was simulated and compared with results obtained from the Jones model. Three reservoir types were simulated through the use of 3-D Cartesian black oil models. In order to correlate the simulation and the Jones analytical model results for the start and height of the production peak, the dimensionless steam zone size was modified to account for a decrease in oil viscosity during steam flooding and its dependence on the steam injection rate. In addition, the dimensionless volume of displaced oil produced was modified from its square-root format to an exponential form. The modified model improved results for production performance by up to 20 years of simulated steam flooding, compared to the Jones model. Results agreed with simulation results for 13 different cases, including 3 different sets of reservoir and fluid properties. Reservoir engineers will benefit from the improved accuracy of the model. Oil displacement calculations were based on methods proposed in earlier research, in which the oil displacement rate is a function of cumulative oil steam ratio. The cumulative oil steam ratio is a function of overall thermal efficiency. Capture factor component formulae were presented, as well as charts of oil production rates and cumulative oil-steam ratios for various reservoirs. 13 refs., 4 tabs., 29 figs.
Modeling a Distribution of Mortgage Credit Losses

Czech Academy of Sciences Publication Activity Database

Gapko, Petr; Šmíd, Martin

2012-01-01

Roč. 60, č. 10 (2012), s. 1005-1023 ISSN 0013-3035 R&D Projects: GA ČR GD402/09/H045; GA ČR(CZ) GBP402/12/G097 Grant - others:Univerzita Karlova(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Institutional support: RVO:67985556 Keywords : credit risk * mortgage * delinquency rate * generalized hyperbolic distribution * normal distribution Subject RIV: AH - Economics Impact factor: 0.194, year: 2012 http://library.utia.cas.cz/separaty/2013/E/smid-modeling a distribution of mortgage credit losses.pdf
Analysis and Comparison of Typical Models within Distribution Network Design

DEFF Research Database (Denmark)

Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.

This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....
Improving Air Quality (and Weather) Predictions using Advanced Data Assimilation Techniques Applied to Coupled Models during KORUS-AQ

Science.gov (United States)

Carmichael, G. R.; Saide, P. E.; Gao, M.; Streets, D. G.; Kim, J.; Woo, J. H.

2017-12-01

Ambient aerosols are important air pollutants with direct impacts on human health and on the Earth's weather and climate systems through their interactions with radiation and clouds. Their role is dependent on their distributions of size, number, phase and composition, which vary significantly in space and time. There remain large uncertainties in simulated aerosol distributions due to uncertainties in emission estimates and in chemical and physical processes associated with their formation and removal. These uncertainties lead to large uncertainties in weather and air quality predictions and in estimates of health and climate change impacts. Despite these uncertainties and challenges, regional-scale coupled chemistry-meteorological models such as WRF-Chem have significant capabilities in predicting aerosol distributions and explaining aerosol-weather interactions. We explore the hypothesis that new advances in on-line, coupled atmospheric chemistry/meteorological models, and new emission inversion and data assimilation techniques applicable to such coupled models, can be applied in innovative ways using current and evolving observation systems to improve predictions of aerosol distributions at regional scales. We investigate the impacts of assimilating AOD from geostationary satellite (GOCI) and surface PM2.5 measurements on predictions of AOD and PM in Korea during KORUS-AQ through a series of experiments. The results suggest assimilating datasets from multiple platforms can improve the predictions of aerosol temporal and spatial distributions.
A simplified model of saltcake moisture distribution. Letter report

International Nuclear Information System (INIS)

Simmons, C.S.

1995-09-01

This letter report describes the formulation of a simplified model for finding the moisture distribution in a saltcake waste profile that has been stabilized by pumping out the drainable interstitial liquid. The model is based on assuming that capillarity mainly governs the distribution of moisture in the porous saltcake waste. A stead upward flow of moisture driven by evaporation from the waste surface is conceptualized to occur for isothermal conditions. To obtain hydraulic parameters for unsaturated conditions, the model is calibrated or matched to the relative saturation distribution as measured by neutron probe scans. The model is demonstrated on Tanks 104-BY and 105-TX as examples. A value of the model is that it identifies the key physical parameters that control the surface moisture content in a waste profile. Moreover, the model can be used to estimate the brine application rate at the waste surface that would raise the moisture content there to a safe level. Thus, the model can be applied to help design a strategy for correcting the moisture conditions in a saltcake waste tank
Distributed Photovoltaics in the Swedish Energy System. Model Development and Simulations

International Nuclear Information System (INIS)

Widen, Joakim

2009-06-01

that the appearance of daily load profiles, and thus the degree of matching to PV generation, are highly variable. Studies of matching of PV generation to aggregate domestic demand showed that load matching at moderate overproduction levels can be improved by PV panel orientation, demand side management (DSM) and storage. At high overproduction levels, however, the only impacting option is storage. Probabilistic power-flow simulations with the developed models yield a versatile picture of how impacts are distributed among customers and over time, as compared to often-used static simulations. Contrary to the trend towards higher time resolution in international research, hourly resolution was found to be sufficient for determining probability distributions for LV grid voltages. Power-flow simulations of three Swedish LV grids showed that a penetration level of 1 kWp PV systems at every customer was most beneficial in terms of on-site coverage of demand, counteracted voltage drops and decreased network losses. However, much higher penetration levels, up to the highest studied level of 5 kWp per household, can be handled without voltage rise above prescribed limits
Distributed Photovoltaics in the Swedish Energy System. Model Development and Simulations

Energy Technology Data Exchange (ETDEWEB)

Widen, Joakim

2009-06-15

showed that the appearance of daily load profiles, and thus the degree of matching to PV generation, are highly variable. Studies of matching of PV generation to aggregate domestic demand showed that load matching at moderate overproduction levels can be improved by PV panel orientation, demand side management (DSM) and storage. At high overproduction levels, however, the only impacting option is storage. Probabilistic power-flow simulations with the developed models yield a versatile picture of how impacts are distributed among customers and over time, as compared to often-used static simulations. Contrary to the trend towards higher time resolution in international research, hourly resolution was found to be sufficient for determining probability distributions for LV grid voltages. Power-flow simulations of three Swedish LV grids showed that a penetration level of 1 kWp PV systems at every customer was most beneficial in terms of on-site coverage of demand, counteracted voltage drops and decreased network losses. However, much higher penetration levels, up to the highest studied level of 5 kWp per household, can be handled without voltage rise above prescribed limits
Applications of species distribution modeling to paleobiology

DEFF Research Database (Denmark)

Svenning, Jens-Christian; Fløjgaard, Camilla; Marske, Katharine Ann

2011-01-01

-Pleistocene megafaunal extinctions, past community assembly, human paleobiogeography, Holocene paleoecology, and even deep-time biogeography (notably, providing insights into biogeographic dynamics >400 million years ago). We discuss important assumptions and uncertainties that affect the SDM approach to paleobiology......Species distribution modeling (SDM: statistical and/or mechanistic approaches to the assessment of range determinants and prediction of species occurrence) offers new possibilities for estimating and studying past organism distributions. SDM complements fossil and genetic evidence by providing (i......) quantitative and potentially high-resolution predictions of the past organism distributions, (ii) statistically formulated, testable ecological hypotheses regarding past distributions and communities, and (iii) statistical assessment of range determinants. In this article, we provide an overview...
Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

International Nuclear Information System (INIS)

1995-01-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A

Model documentation: Natural gas transmission and distribution model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-02-17

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. NEMS was developed in the Office of integrated Analysis and Forecasting of the Energy information Administration (EIA). NEMS is the third in a series of computer-based, midterm energy modeling systems used since 1974 by the EIA and its predecessor, the Federal Energy Administration, to analyze domestic energy-economy markets and develop projections. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The methodology employed allows the analysis of impacts of regional capacity constraints in the interstate natural gas pipeline network and the identification of pipeline capacity expansion requirements. There is an explicit representation of core and noncore markets for natural gas transmission and distribution services, and the key components of pipeline tariffs are represented in a pricing algorithm. Natural gas pricing and flow patterns are derived by obtaining a market equilibrium across the three main elements of the natural gas market: the supply element, the demand element, and the transmission and distribution network that links them. The NGTDM consists of four modules: the Annual Flow Module, the Capacity F-expansion Module, the Pipeline Tariff Module, and the Distributor Tariff Module. A model abstract is provided in Appendix A.
Model Checking Geographically Distributed Interlocking Systems Using UMC

DEFF Research Database (Denmark)

Fantechi, Alessandro; Haxthausen, Anne Elisabeth; Nielsen, Michel Bøje Randahl

2017-01-01

the relevant distributed protocols. By doing that we obey the safety guidelines of the railway signalling domain, that require formal methods to support the certification of such products. We also show how formal modelling can help designing alternative distributed solutions, while maintaining adherence...
Distributed models coupling soakaways, urban drainage and groundwater

DEFF Research Database (Denmark)

Roldin, Maria Kerstin

in receiving waters, urban flooding etc. WSUD structures are generally small, decentralized systems intended to manage stormwater near the source. Many of these alternative techniques are based on infiltration which can affect both the urban sewer system and urban groundwater levels if widely implemented......Alternative methods for stormwater management in urban areas, also called Water Sensitive Urban Design (WSUD) methods, have become increasingly important for the mitigation of urban stormwater management problems such as high runoff volumes, combined sewage overflows, poor water quality......, and how these can be modeled in an integrated environment with distributed urban drainage and groundwater flow models. The thesis: 1. Identifies appropriate models of soakaways for use in an integrated and distributed urban water and groundwater modeling system 2. Develops a modeling concept that is able...
Smoluchowski coagulation models of sea ice thickness distribution dynamics

Science.gov (United States)

Godlovitch, D.; Illner, R.; Monahan, A.

2011-12-01

Sea ice thickness distributions display a ubiquitous exponential decrease with thickness. This tail characterizes the range of ice thickness produced by mechanical redistribution of ice through the process of ridging, rafting, and shearing. We investigate how well the thickness distribution can be simulated by representing mechanical redistribution as a generalized stacking process. Such processes are naturally described by a well-studied class of models known as Smoluchowski Coagulation Models (SCMs), which describe the dynamics of a population of fixed-mass "particles" which combine in pairs to form a "particle" with the combined mass of the constituent pair at a rate which depends on the mass of the interacting particles. Like observed sea ice thickness distributions, the mass distribution of the populations generated by SCMs has an exponential or quasi-exponential form. We use SCMs to model sea ice, identifying mass-increasing particle combinations with thickness-increasing ice redistribution processes. Our model couples an SCM component with a thermodynamic component and generates qualitatively accurate thickness distributions with a variety of rate kernels. Our results suggest that the exponential tail of the sea ice thickness distribution arises from the nature of the ridging process, rather than specific physical properties of sea ice or the spatial arrangement of floes, and that the relative strengths of the dynamic and thermodynamic processes are key in accurately simulating the rate at which the sea ice thickness tail drops off with thickness.
Modelling refrigerant distribution in microchannel evaporators

DEFF Research Database (Denmark)

Brix, Wiebke; Kærn, Martin Ryhl; Elmegaard, Brian

2009-01-01

of the refrigerant distribution is carried out for two channels in parallel and for two different cases. In the first case maldistribution of the inlet quality into the channels is considered, and in the second case a non-uniform airflow on the secondary side is considered. In both cases the total mixed superheat...... out of the evaporator is kept constant. It is shown that the cooling capacity of the evaporator is reduced significantly, both in the case of unevenly distributed inlet quality and for the case of non-uniform airflow on the outside of the channels.......The effects of refrigerant maldistribution in parallel evaporator channels on the heat exchanger performance are investigated numerically. For this purpose a 1D steady state model of refrigerant R134a evaporating in a microchannel tube is built and validated against other evaporator models. A study...
Estimation of rates-across-sites distributions in phylogenetic substitution models.

Science.gov (United States)

Susko, Edward; Field, Chris; Blouin, Christian; Roger, Andrew J

2003-10-01

Previous work has shown that it is often essential to account for the variation in rates at different sites in phylogenetic models in order to avoid phylogenetic artifacts such as long branch attraction. In most current models, the gamma distribution is used for the rates-across-sites distributions and is implemented as an equal-probability discrete gamma. In this article, we introduce discrete distribution estimates with large numbers of equally spaced rate categories allowing us to investigate the appropriateness of the gamma model. With large numbers of rate categories, these discrete estimates are flexible enough to approximate the shape of almost any distribution. Likelihood ratio statistical tests and a nonparametric bootstrap confidence-bound estimation procedure based on the discrete estimates are presented that can be used to test the fit of a parametric family. We applied the methodology to several different protein data sets, and found that although the gamma model often provides a good parametric model for this type of data, rate estimates from an equal-probability discrete gamma model with a small number of categories will tend to underestimate the largest rates. In cases when the gamma model assumption is in doubt, rate estimates coming from the discrete rate distribution estimate with a large number of rate categories provide a robust alternative to gamma estimates. An alternative implementation of the gamma distribution is proposed that, for equal numbers of rate categories, is computationally more efficient during optimization than the standard gamma implementation and can provide more accurate estimates of site rates.
Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

Science.gov (United States)

Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

2017-12-01

Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the Mizu
Distributed model predictive control made easy

CERN Document Server

Negenborn, Rudy

2014-01-01

The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...
Software reliability growth models with normal failure time distributions

International Nuclear Information System (INIS)

Okamura, Hiroyuki; Dohi, Tadashi; Osaki, Shunji

2013-01-01

This paper proposes software reliability growth models (SRGM) where the software failure time follows a normal distribution. The proposed model is mathematically tractable and has sufficient ability of fitting to the software failure data. In particular, we consider the parameter estimation algorithm for the SRGM with normal distribution. The developed algorithm is based on an EM (expectation-maximization) algorithm and is quite simple for implementation as software application. Numerical experiment is devoted to investigating the fitting ability of the SRGMs with normal distribution through 16 types of failure time data collected in real software projects
Probability distributions in conservative energy exchange models of multiple interacting agents

International Nuclear Information System (INIS)

Scafetta, Nicola; West, Bruce J

2007-01-01

Herein we study energy exchange models of multiple interacting agents that conserve energy in each interaction. The models differ regarding the rules that regulate the energy exchange and boundary effects. We find a variety of stochastic behaviours that manifest energy equilibrium probability distributions of different types and interaction rules that yield not only the exponential distributions such as the familiar Maxwell-Boltzmann-Gibbs distribution of an elastically colliding ideal particle gas, but also uniform distributions, truncated exponential distributions, Gaussian distributions, Gamma distributions, inverse power law distributions, mixed exponential and inverse power law distributions, and evolving distributions. This wide variety of distributions should be of value in determining the underlying mechanisms generating the statistical properties of complex phenomena including those to be found in complex chemical reactions
Estimating the Value of Improved Distributed Photovoltaic Adoption Forecasts for Utility Resource Planning

Energy Technology Data Exchange (ETDEWEB)

Gagnon, Pieter [National Renewable Energy Lab. (NREL), Golden, CO (United States); Barbose, Galen L. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stoll, Brady [National Renewable Energy Lab. (NREL), Golden, CO (United States); Ehlen, Ali [National Renewable Energy Lab. (NREL), Golden, CO (United States); Zuboy, Jarret [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mills, Andrew D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2018-05-15

Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities; forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by using a suite of models to explore the capacity expansion and operation of the Western Interconnection over a 15-year period across a wide range of DPV growth rates and misforecast severities. The system costs under a misforecast are compared against the costs under a perfect forecast, to quantify the costs of misforecasting. Using a simplified probabilistic method applied to these modeling results, an analyst can make a first-order estimate of the financial benefit of improving a utility’s forecasting capabilities, and thus be better informed about whether to make such an investment. For example, under our base assumptions, a utility with 10 TWh per year of retail electric sales who initially estimates that DPV growth could range from 2% to 7.5% of total generation over the next 15 years could expect total present-value savings of approximately $4 million if they could reduce the severity of misforecasting to within ±25%. Utility resource planners can compare those savings against the costs needed to achieve that level of precision, to guide their decision on whether to make an investment in tools or resources.
Modelling aspects of distributed processing in telecommunication networks

NARCIS (Netherlands)

Tomasgard, A; Audestad, JA; Dye, S; Stougie, L; van der Vlerk, MH; Wallace, SW

1998-01-01

The purpose of this paper is to formally describe new optimization models for telecommunication networks with distributed processing. Modem distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in
Programming model for distributed intelligent systems

Science.gov (United States)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.
Modeling the Hydrological Cycle in the Atmosphere of Mars: Influence of a Bimodal Size Distribution of Aerosol Nucleation Particles

Science.gov (United States)

Shaposhnikov, Dmitry S.; Rodin, Alexander V.; Medvedev, Alexander S.; Fedorova, Anna A.; Kuroda, Takeshi; Hartogh, Paul

2018-02-01

We present a new implementation of the hydrological cycle scheme into a general circulation model of the Martian atmosphere. The model includes a semi-Lagrangian transport scheme for water vapor and ice and accounts for microphysics of phase transitions between them. The hydrological scheme includes processes of saturation, nucleation, particle growth, sublimation, and sedimentation under the assumption of a variable size distribution. The scheme has been implemented into the Max Planck Institute Martian general circulation model and tested assuming monomodal and bimodal lognormal distributions of ice condensation nuclei. We present a comparison of the simulated annual variations, horizontal and vertical distributions of water vapor, and ice clouds with the available observations from instruments on board Mars orbiters. The accounting for bimodality of aerosol particle distribution improves the simulations of the annual hydrological cycle, including predicted ice clouds mass, opacity, number density, and particle radii. The increased number density and lower nucleation rates bring the simulated cloud opacities closer to observations. Simulations show a weak effect of the excess of small aerosol particles on the simulated water vapor distributions.
Improving cardiovascular care through outpatient cardiac rehabilitation: an analysis of payment models that would improve quality and promote use.

Science.gov (United States)

Mead, Holly; Grantham, Sarah; Siegel, Bruce

2014-01-01

Much attention has been paid to improving the care of patients with cardiovascular disease by focusing attention on delivery system redesign and payment reforms that encompass the healthcare spectrum, from an acute episode to maintenance of care. However, 1 area of cardiovascular disease care that has received little attention in the advancement of quality is cardiac rehabilitation (CR), a comprehensive secondary prevention program that is significantly underused despite evidence-based guidelines that recommending its use. The purpose of this article was to analyze the applicability of 2 payment and reimbursement models-pay-for-performance and bundled payments for episodes of care--that can promote the use of CR. We conclude that a payment model combining elements of both pay-for-performance and episodes of care would increase the use of CR, which would both improve quality and increase efficiency in cardiac care. Specific elements would need to be clearly defined, however, including: (a) how an episode is defined, (b) how to hold providers accountable for the care they provider, (c) how to encourage participation among CR providers, and (d) how to determine an equitable distribution of payment. Demonstrations testing new payment models must be implemented to generate empirical evidence that a melded pay-for-performance and episode-based care payment model will improve quality and efficiency.
Modelling road accident blackspots data with the discrete generalized Pareto distribution.

Science.gov (United States)

Prieto, Faustino; Gómez-Déniz, Emilio; Sarabia, José María

2014-10-01

This study shows how road traffic networks events, in particular road accidents on blackspots, can be modelled with simple probabilistic distributions. We considered the number of crashes and the number of fatalities on Spanish blackspots in the period 2003-2007, from Spanish General Directorate of Traffic (DGT). We modelled those datasets, respectively, with the discrete generalized Pareto distribution (a discrete parametric model with three parameters) and with the discrete Lomax distribution (a discrete parametric model with two parameters, and particular case of the previous model). For that, we analyzed the basic properties of both parametric models: cumulative distribution, survival, probability mass, quantile and hazard functions, genesis and rth-order moments; applied two estimation methods of their parameters: the μ and (μ+1) frequency method and the maximum likelihood method; used two goodness-of-fit tests: Chi-square test and discrete Kolmogorov-Smirnov test based on bootstrap resampling; and compared them with the classical negative binomial distribution in terms of absolute probabilities and in models including covariates. We found that those probabilistic models can be useful to describe the road accident blackspots datasets analyzed. Copyright © 2014 Elsevier Ltd. All rights reserved.
A data-model integration approach toward improved understanding on wetland functions and hydrological benefits at the catchment scale

Science.gov (United States)

Yeo, I. Y.; Lang, M.; Lee, S.; Huang, C.; Jin, H.; McCarty, G.; Sadeghi, A.

2017-12-01

The wetland ecosystem plays crucial roles in improving hydrological function and ecological integrity for the downstream water and the surrounding landscape. However, changing behaviours and functioning of wetland ecosystems are poorly understood and extremely difficult to characterize. Improved understanding on hydrological behaviours of wetlands, considering their interaction with surrounding landscapes and impacts on downstream waters, is an essential first step toward closing the knowledge gap. We present an integrated wetland-catchment modelling study that capitalizes on recently developed inundation maps and other geospatial data. The aim of the data-model integration is to improve spatial prediction of wetland inundation and evaluate cumulative hydrological benefits at the catchment scale. In this paper, we highlight problems arising from data preparation, parameterization, and process representation in simulating wetlands within a distributed catchment model, and report the recent progress on mapping of wetland dynamics (i.e., inundation) using multiple remotely sensed data. We demonstrate the value of spatially explicit inundation information to develop site-specific wetland parameters and to evaluate model prediction at multi-spatial and temporal scales. This spatial data-model integrated framework is tested using Soil and Water Assessment Tool (SWAT) with improved wetland extension, and applied for an agricultural watershed in the Mid-Atlantic Coastal Plain, USA. This study illustrates necessity of spatially distributed information and a data integrated modelling approach to predict inundation of wetlands and hydrologic function at the local landscape scale, where monitoring and conservation decision making take place.
Flash flood modeling with the MARINE hydrological distributed model

Science.gov (United States)

Estupina-Borrell, V.; Dartus, D.; Ababou, R.

2006-11-01

Flash floods are characterized by their violence and the rapidity of their occurrence. Because these events are rare and unpredictable, but also fast and intense, their anticipation with sufficient lead time for warning and broadcasting is a primary subject of research. Because of the heterogeneities of the rain and of the behavior of the surface, spatially distributed hydrological models can lead to a better understanding of the processes and so on they can contribute to a better forecasting of flash flood. Our main goal here is to develop an operational and robust methodology for flash flood forecasting. This methodology should provide relevant data (information) about flood evolution on short time scales, and should be applicable even in locations where direct observations are sparse (e.g. absence of historical and modern rainfalls and streamflows in small mountainous watersheds). The flash flood forecast is obtained by the physically based, space-time distributed hydrological model "MARINE'' (Model of Anticipation of Runoff and INondations for Extreme events). This model is presented and tested in this paper for a real flash flood event. The model consists in two steps, or two components: the first component is a "basin'' flood module which generates flood runoff in the upstream part of the watershed, and the second component is the "stream network'' module, which propagates the flood in the main river and its subsidiaries. The basin flash flood generation model is a rainfall-runoff model that can integrate remotely sensed data. Surface hydraulics equations are solved with enough simplifying hypotheses to allow real time exploitation. The minimum data required by the model are: (i) the Digital Elevation Model, used to calculate slopes that generate runoff, it can be issued from satellite imagery (SPOT) or from French Geographical Institute (IGN); (ii) the rainfall data from meteorological radar, observed or anticipated by the French Meteorological Service (M�
Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city-China

Science.gov (United States)

Tang, Jinjun; Zhang, Shen; Chen, Xinqiang; Liu, Fang; Zou, Yajie

2018-03-01

Understanding Origin-Destination distribution of taxi trips is very important for improving effects of transportation planning and enhancing quality of taxi services. This study proposes a new method based on Entropy-Maximizing theory to model OD distribution in Harbin city using large-scale taxi GPS trajectories. Firstly, a K-means clustering method is utilized to partition raw pick-up and drop-off location into different zones, and trips are assumed to start from and end at zone centers. A generalized cost function is further defined by considering travel distance, time and fee between each OD pair. GPS data collected from more than 1000 taxis at an interval of 30 s during one month are divided into two parts: data from first twenty days is treated as training dataset and last ten days is taken as testing dataset. The training dataset is used to calibrate model while testing dataset is used to validate model. Furthermore, three indicators, mean absolute error (MAE), root mean square error (RMSE) and mean percentage absolute error (MPAE), are applied to evaluate training and testing performance of Entropy-Maximizing model versus Gravity model. The results demonstrate Entropy-Maximizing model is superior to Gravity model. Findings of the study are used to validate the feasibility of OD distribution from taxi GPS data in urban system.
Modifying the dissolved-in-water type natural gas field simulation model based on the distribution of estimated Young's modulus for the Kujukuri region, Japan

Directory of Open Access Journals (Sweden)

T. Nakagawa

2015-11-01

Full Text Available A simulation model, which covers the part of Southern-Kanto natural gas field in Chiba prefecture, was developed to perform studies and make predictions of land subsidence. However, because large differences between simulated and measured subsidence occurred in the northern modeled area of the gas field, the model was modified with an estimated Young's modulus distribution. This distribution was estimated by the yield value distribution and the correlation of yield value with Young's modulus. Consequently, the simulated subsidence in the north area was improved to some extent.

A Comprehensive Strategy for Accurate Reactive Power Distribution, Stability Improvement, and Harmonic Suppression of Multi-Inverter-Based Micro-Grid

Directory of Open Access Journals (Sweden)

Henan Dong

2018-03-01

Full Text Available Among the issues of accurate power distribution, stability improvement, and harmonic suppression in micro-grid, each has been well studied as an individual, and most of the strategies about these issues aim at one inverter-based micro-grid, hence there is a need to establish a model to achieve these functions as a whole, aiming at a multi-inverter-based micro-grid. This paper proposes a comprehensive strategy which achieves this goal successfully; since the output voltage and frequency of micro-grid all consist of fundamental and harmonic components, the strategy contains two parts accordingly. On one hand, a fundamental control strategy is proposed upon the conventional droop control. The virtual impedance is introduced to solve the problem of accurate allocation of reactive power between inverters. Meanwhile, a secondary power balance controller is added to improve the stability of voltage and frequency while considering the aggravating problem of stability because of introducing virtual impedance. On the other hand, the fractional frequency harmonic control strategy is proposed. It can solve the influence of nonlinear loads, micro-grid inverters, and the distribution network on output voltage of inverters, which is focused on eliminating specific harmonics caused by the nonlinear loads, micro-grid converters, and the distribution network so that the power quality of micro-grid can be improved effectively. Finally, small signal analysis is used to analyze the stability of the multi-converter parallel system after introducing the whole control strategy. The simulation results show that the strategy proposed in this paper has a great performance on distributing reactive power, regulating and stabilizing output voltage of inverters and frequency, eliminating harmonic components, and improving the power quality of multi-inverter-based micro-grid.
Energy flow models for the estimation of technical losses in distribution network

International Nuclear Information System (INIS)

Au, Mau Teng; Tan, Chin Hooi

2013-01-01

This paper presents energy flow models developed to estimate technical losses in distribution network. Energy flow models applied in this paper is based on input energy and peak demand of distribution network, feeder length and peak demand, transformer loading capacity, and load factor. Two case studies, an urban distribution network and a rural distribution network are used to illustrate application of the energy flow models. Results on technical losses obtained for the two distribution networks are consistent and comparable to network of similar types and characteristics. Hence, the energy flow models are suitable for practical application.
Predicting bottlenose dolphin distribution along Liguria coast (northwestern Mediterranean Sea) through different modeling techniques and indirect predictors.

Science.gov (United States)

Marini, C; Fossa, F; Paoli, C; Bellingeri, M; Gnone, G; Vassallo, P

2015-03-01

Habitat modeling is an important tool to investigate the quality of the habitat for a species within a certain area, to predict species distribution and to understand the ecological processes behind it. Many species have been investigated by means of habitat modeling techniques mainly to address effective management and protection policies and cetaceans play an important role in this context. The bottlenose dolphin (Tursiops truncatus) has been investigated with habitat modeling techniques since 1997. The objectives of this work were to predict the distribution of bottlenose dolphin in a coastal area through the use of static morphological features and to compare the prediction performances of three different modeling techniques: Generalized Linear Model (GLM), Generalized Additive Model (GAM) and Random Forest (RF). Four static variables were tested: depth, bottom slope, distance from 100 m bathymetric contour and distance from coast. RF revealed itself both the most accurate and the most precise modeling technique with very high distribution probabilities predicted in presence cells (90.4% of mean predicted probabilities) and with 66.7% of presence cells with a predicted probability comprised between 90% and 100%. The bottlenose distribution obtained with RF allowed the identification of specific areas with particularly high presence probability along the coastal zone; the recognition of these core areas may be the starting point to develop effective management practices to improve T. truncatus protection. Copyright © 2014 Elsevier Ltd. All rights reserved.
Comment on "Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?" by Mazzoleni et al. (2017)

Science.gov (United States)

Viero, Daniele P.

2018-01-01

Citizen science and crowdsourcing are gaining increasing attention among hydrologists. In a recent contribution, Mazzoleni et al. (2017) investigated the integration of crowdsourced data (CSD) into hydrological models to improve the accuracy of real-time flood forecasts. The authors used synthetic CSD (i.e. not actually measured), because real CSD were not available at the time of the study. In their work, which is a proof-of-concept study, Mazzoleni et al. (2017) showed that assimilation of CSD improves the overall model performance; the impact of irregular frequency of available CSD, and that of data uncertainty, were also deeply assessed. However, the use of synthetic CSD in conjunction with (semi-)distributed hydrological models deserves further discussion. As a result of equifinality, poor model identifiability, and deficiencies in model structure, internal states of (semi-)distributed models can hardly mimic the actual states of complex systems away from calibration points. Accordingly, the use of synthetic CSD that are drawn from model internal states under best-fit conditions can lead to overestimation of the effectiveness of CSD assimilation in improving flood prediction. Operational flood forecasting, which results in decisions of high societal value, requires robust knowledge of the model behaviour and an in-depth assessment of both model structure and forcing data. Additional guidelines are given that are useful for the a priori evaluation of CSD for real-time flood forecasting and, hopefully, for planning apt design strategies for both model calibration and collection of CSD.
Computational Fluid Dynamics Modeling of The Dalles Project: Effects of Spill Flow Distribution Between the Washington Shore and the Tailrace Spillwall

Energy Technology Data Exchange (ETDEWEB)

Rakowski, Cynthia L.; Serkowski, John A.; Richmond, Marshall C.

2010-12-01

The U.S. Army Corps of Engineers-Portland District (CENWP) has ongoing work to improve the survival of juvenile salmonids (smolt) migrating past The Dalles Dam. As part of that effort, a spillwall was constructed to improve juvenile egress through the tailrace downstream of the stilling basin. The spillwall was designed to improve smolt survival by decreasing smolt retention time in the spillway tailrace and the exposure to predators on the spillway shelf. The spillwall guides spillway flows, and hence smolt, more quickly into the thalweg. In this study, an existing computational fluid dynamics (CFD) model was modified and used to characterize tailrace hydraulics between the new spillwall and the Washington shore for six different total river flows. The effect of spillway flow distribution was simulated for three spill patterns at the lowest total river flow. The commercial CFD solver, STAR-CD version 4.1, was used to solve the unsteady Reynolds-averaged Navier-Stokes equations together with the k-epsilon turbulence model. Free surface motion was simulated using the volume-of-fluid (VOF) technique. The model results were used in two ways. First, results graphics were provided to CENWP and regional fisheries agency representatives for use and comparison to the same flow conditions at a reduced-scale physical model. The CFD results were very similar in flow pattern to that produced by the reduced-scale physical model but these graphics provided a quantitative view of velocity distribution. During the physical model work, an additional spill pattern was tested. Subsequently, that spill pattern was also simulated in the numerical model. The CFD streamlines showed that the hydraulic conditions were likely to be beneficial to fish egress at the higher total river flows (120 kcfs and greater, uniform flow distribution). At the lowest flow case, 90 kcfs, it was necessary to use a non-uniform distribution. Of the three distributions tested, splitting the flow evenly between
Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution.

Science.gov (United States)

Lo, Kenneth; Gottardo, Raphael

2012-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components.
An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

Directory of Open Access Journals (Sweden)

Ainong Li

2015-05-01

Full Text Available Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM images. The model employed Normalized Difference Vegetation Index (NDVI thresholds to approximately divide land targets into eleven groups, due to NDVI’s lower sensitivity to topography and its significant role in indicating land cover type. Within each group of terrestrial targets, corresponding MODIS BRDF (Bidirectional Reflectance Distribution Function products were used to account for land surface’s BRDF effect, and topographic effects are corrected without Lambertian assumption. The methodology was tested with two TM scenes of severely rugged mountain areas acquired under different sun elevation angles. Results demonstrated that reflectance of sun-averted slopes was evidently enhanced, and the overall quality of images was improved with topographic effect being effectively suppressed. Correlation coefficients between Near Infra-Red band reflectance and illumination condition reduced almost to zero, and coefficients of variance also showed some reduction. By comparison with the other two physics-based models (Sandmeier model and Li model, the proposed model showed favorable results on two tested Landsat scenes. With the almost half-century accumulation of Landsat data and the successive launch and operation of Landsat 8, the improved model in this paper can be potentially helpful for the topographic correction of Landsat and Landsat-like data.
Evaluation of performance of distributed delay model for chemotherapy-induced myelosuppression.

Science.gov (United States)

Krzyzanski, Wojciech; Hu, Shuhua; Dunlavey, Michael

2018-04-01

The distributed delay model has been introduced that replaces the transit compartments in the classic model of chemotherapy-induced myelosuppression with a convolution integral. The maturation of granulocyte precursors in the bone marrow is described by the gamma probability density function with the shape parameter (ν). If ν is a positive integer, the distributed delay model coincides with the classic model with ν transit compartments. The purpose of this work was to evaluate performance of the distributed delay model with particular focus on model deterministic identifiability in the presence of the shape parameter. The classic model served as a reference for comparison. Previously published white blood cell (WBC) count data in rats receiving bolus doses of 5-fluorouracil were fitted by both models. The negative two log-likelihood objective function (-2LL) and running times were used as major markers of performance. Local sensitivity analysis was done to evaluate the impact of ν on the pharmacodynamics response WBC. The ν estimate was 1.46 with 16.1% CV% compared to ν = 3 for the classic model. The difference of 6.78 in - 2LL between classic model and the distributed delay model implied that the latter performed significantly better than former according to the log-likelihood ratio test (P = 0.009), although the overall performance was modestly better. The running times were 1 s and 66.2 min, respectively. The long running time of the distributed delay model was attributed to computationally intensive evaluation of the convolution integral. The sensitivity analysis revealed that ν strongly influences the WBC response by controlling cell proliferation and elimination of WBCs from the circulation. In conclusion, the distributed delay model was deterministically identifiable from typical cytotoxic data. Its performance was modestly better than the classic model with significantly longer running time.
Hybrid ATDL-gamma distribution model for predicting area source acid gas concentrations

Energy Technology Data Exchange (ETDEWEB)

Jakeman, A J; Taylor, J A

1985-01-01

An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organization goal for acid gas concentrations.
Effects of interface pressure distribution on human sleep quality.

Directory of Open Access Journals (Sweden)

Zongyong Chen

Full Text Available High sleep quality promotes efficient performance in the following day. Sleep quality is influenced by environmental factors, such as temperature, light, sound and smell. Here, we investigated whether differences in the interface pressure distribution on healthy individuals during sleep influenced sleep quality. We defined four types of pressure models by differences in the area distribution and the subjective feelings that occurred when participants slept on the mattresses. One type of model was showed "over-concentrated" distribution of pressure; one was displayed "over-evenly" distributed interface pressure while the other two models were displayed intermediate distribution of pressure. A polysomnography analysis demonstrated an increase in duration and proportion of non-rapid-eye-movement sleep stages 3 and 4, as well as decreased number of micro-arousals, in subjects sleeping on models with pressure intermediately distributed compared to models with over-concentrated or over-even distribution of pressure. Similarly, higher scores of self-reported sleep quality were obtained in subjects sleeping on the two models with intermediate pressure distribution. Thus, pressure distribution, at least to some degree, influences sleep quality and self-reported feelings of sleep-related events, though the underlying mechanisms remain unknown. The regulation of pressure models imposed by external sleep environment may be a new direction for improving sleep quality. Only an appropriate interface pressure distribution is beneficial for improving sleep quality, over-concentrated or -even distribution of pressure do not help for good sleep.
A Review of Distributed Control Techniques for Power Quality Improvement in Micro-grids

Science.gov (United States)

Zeeshan, Hafiz Muhammad Ali; Nisar, Fatima; Hassan, Ahmad

2017-05-01

Micro-grid is typically visualized as a small scale local power supply network dependent on distributed energy resources (DERs) that can operate simultaneously with grid as well as in standalone manner. The distributed generator of a micro-grid system is usually a converter-inverter type topology acting as a non-linear load, and injecting harmonics into the distribution feeder. Hence, the negative effects on power quality by the usage of distributed generation sources and components are clearly witnessed. In this paper, a review of distributed control approaches for power quality improvement is presented which encompasses harmonic compensation, loss mitigation and optimum power sharing in multi-source-load distributed power network. The decentralized subsystems for harmonic compensation and active-reactive power sharing accuracy have been analysed in detail. Results have been validated to be consistent with IEEE standards.
Integrated production-distribution planning optimization models: A review in collaborative networks context

Directory of Open Access Journals (Sweden)

Beatriz Andres

2017-01-01

Full Text Available Researchers in the area of collaborative networks are more and more aware of proposing collaborative approaches to address planning processes, due to the advantages associated when enterprises perform integrated planning models. Collaborative production-distribution planning, among the supply network actors, is considered a proper mechanism to support enterprises on dealing with uncertainties and dynamicity associated to the current markets. Enterprises, and especially SMEs, should be able to overcome the continuous changes of the market by increasing their agility. Carrying out collaborative planning allows enterprises to enhance their readiness and agility for facing the market turbulences. However, SMEs have limited access when incorporating optimization tools to deal with collaborative planning, reducing their ability to respond to the competition. The problem to solve is to provide SMEs affordable solutions to support collaborative planning. In this regard, new optimisation algorithms are required in order to improve the collaboration within the supply network partners. As part of the H2020 Cloud Collaborative Manufacturing Networks (C2NET research project, this paper presents a study on integrated production and distribution plans. The main objective of the research is to identify gaps in current optimization models, proposed to address integrated planning, taking into account the requirements and needs of the industry. Thus, the needs of the companies belonging to the industrial pilots, defined in the C2NET project, are identified; analysing how these needs are covered by the optimization models proposed in the literature, to deal with the integrated production-distribution planning.
Modelling the distribution of domestic ducks in Monsoon Asia

Science.gov (United States)

Van Bockel, Thomas P.; Prosser, Diann; Franceschini, Gianluca; Biradar, Chandra; Wint, William; Robinson, Tim; Gilbert, Marius

2011-01-01

Domestic ducks are considered to be an important reservoir of highly pathogenic avian influenza (HPAI), as shown by a number of geospatial studies in which they have been identified as a significant risk factor associated with disease presence. Despite their importance in HPAI epidemiology, their large-scale distribution in Monsoon Asia is poorly understood. In this study, we created a spatial database of domestic duck census data in Asia and used it to train statistical distribution models for domestic duck distributions at a spatial resolution of 1km. The method was based on a modelling framework used by the Food and Agriculture Organisation to produce the Gridded Livestock of the World (GLW) database, and relies on stratified regression models between domestic duck densities and a set of agro-ecological explanatory variables. We evaluated different ways of stratifying the analysis and of combining the prediction to optimize the goodness of fit of the predictions. We found that domestic duck density could be predicted with reasonable accuracy (mean RMSE and correlation coefficient between log-transformed observed and predicted densities being 0.58 and 0.80, respectively), using a stratification based on livestock production systems. We tested the use of artificially degraded data on duck distributions in Thailand and Vietnam as training data, and compared the modelled outputs with the original high-resolution data. This showed, for these two countries at least, that these approaches could be used to accurately disaggregate provincial level (administrative level 1) statistical data to provide high resolution model distributions.
Multivariate Birnbaum-Saunders Distributions: Modelling and Applications

Directory of Open Access Journals (Sweden)

Robert G. Aykroyd

2018-03-01

Full Text Available Since its origins and numerous applications in material science, the Birnbaum–Saunders family of distributions has now found widespread uses in some areas of the applied sciences such as agriculture, environment and medicine, as well as in quality control, among others. It is able to model varied data behaviour and hence provides a flexible alternative to the most usual distributions. The family includes Birnbaum–Saunders and log-Birnbaum–Saunders distributions in univariate and multivariate versions. There are now well-developed methods for estimation and diagnostics that allow in-depth analyses. This paper gives a detailed review of existing methods and of relevant literature, introducing properties and theoretical results in a systematic way. To emphasise the range of suitable applications, full analyses are included of examples based on regression and diagnostics in material science, spatial data modelling in agricultural engineering and control charts for environmental monitoring. However, potential future uses in new areas such as business, economics, finance and insurance are also discussed. This work is presented to provide a full tool-kit of novel statistical models and methods to encourage other researchers to implement them in these new areas. It is expected that the methods will have the same positive impact in the new areas as they have had elsewhere.
Application of the MacCormack scheme to overland flow routing for high-spatial resolution distributed hydrological model

Science.gov (United States)

Zhang, Ling; Nan, Zhuotong; Liang, Xu; Xu, Yi; Hernández, Felipe; Li, Lianxia

2018-03-01

Although process-based distributed hydrological models (PDHMs) are evolving rapidly over the last few decades, their extensive applications are still challenged by the computational expenses. This study attempted, for the first time, to apply the numerically efficient MacCormack algorithm to overland flow routing in a representative high-spatial resolution PDHM, i.e., the distributed hydrology-soil-vegetation model (DHSVM), in order to improve its computational efficiency. The analytical verification indicates that both the semi and full versions of the MacCormack schemes exhibit robust numerical stability and are more computationally efficient than the conventional explicit linear scheme. The full-version outperforms the semi-version in terms of simulation accuracy when a same time step is adopted. The semi-MacCormack scheme was implemented into DHSVM (version 3.1.2) to solve the kinematic wave equations for overland flow routing. The performance and practicality of the enhanced DHSVM-MacCormack model was assessed by performing two groups of modeling experiments in the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The experiments show that DHSVM-MacCormack can considerably improve the computational efficiency without compromising the simulation accuracy of the original DHSVM model. More specifically, with the same computational environment and model settings, the computational time required by DHSVM-MacCormack can be reduced to several dozen minutes for a simulation period of three months (in contrast with one day and a half by the original DHSVM model) without noticeable sacrifice of the accuracy. The MacCormack scheme proves to be applicable to overland flow routing in DHSVM, which implies that it can be coupled into other PHDMs for watershed routing to either significantly improve their computational efficiency or to make the kinematic wave routing for high resolution modeling computational feasible.
A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems

DEFF Research Database (Denmark)

Han, Pujie; Zhai, Zhengjun; Nielsen, Brian

2018-01-01

This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL...
Cost/worth assessment of reliability improvement in distribution networks by means of artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Bouhouras, Aggelos S.; Labridis, Dimitris P.; Bakirtzis, Anastasios G. [Power Systems Laboratory, Aristotle University of Thessaloniki, Dept. of Electrical and Computer Engineering, 54124 Thessaloniki (Greece)

2010-06-15

A major challenge for the power utilities today is to ensure a high level of reliability of supply to customers. Two main factors determine the feasibility of a project that improves the reliability of supply: the project cost (investment and operational) and the benefits that result from the implementation of the project. This paper examines the implementation of an Artificial Intelligence System in an urban distribution network, capable to locate and isolate short circuit faults in the feeder, thus accomplishing immediate restoration of electric supply to the customers. The paper describes the benefits of the project, which are supply reliability improvement and distribution network loss reduction through network reconfigurations. By comparison of the project benefits and costs the economic feasibility of such a project for an underground distribution feeder in Greece is demonstrated. (author)
Updating known distribution models for forecasting climate change impact on endangered species.

Science.gov (United States)

Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

2013-01-01

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.
Power Flow Distribution Strategy for Improved Power Electronics Energy Efficiency in Battery Storage Systems: Development and Implementation in a Utility-Scale System

Directory of Open Access Journals (Sweden)

Michael Schimpe

2018-03-01

Full Text Available Utility-scale battery storage systems typically consist of multiple smaller units contributing to the overall power dispatch of the system. Herein, the power distribution among these units is analyzed and optimized to operate the system with increased energy efficiency. To improve the real-life storage operation, a holistic system model for battery storage systems has been developed that enables a calculation of the energy efficiency. A utility-scale Second-Life battery storage system with a capacity of 3.3 MWh/3 MW is operated and evaluated in this work. The system is in operation for the provision of primary control reserve in combination with intraday trading for controlling the battery state of charge. The simulation model is parameterized with the system data. Results show that losses in power electronics dominate. An operational strategy improving the energy efficiency through an optimized power flow distribution within the storage system is developed. The power flow distribution strategy is based on the reduction of the power electronics losses at no-load/partial-load by minimizing their in-operation time. The simulation derived power flow distribution strategy is implemented in the real-life storage system. Field-test measurements and analysis prove the functionality of the power flow distribution strategy and reveal the reduction of the energy throughput of the units by 7%, as well as a significant reduction of energy losses in the units by 24%. The cost savings for electricity over the system’s lifetime are approximated to 4.4% of its investment cost.
A Distributive Model of Treatment Acceptability

Science.gov (United States)

Carter, Stacy L.

2008-01-01

A model of treatment acceptability is proposed that distributes overall treatment acceptability into three separate categories of influence. The categories are comprised of societal influences, consultant influences, and influences associated with consumers of treatments. Each of these categories are defined and their inter-relationships within…

Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

Science.gov (United States)

Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

2010-01-01

Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.
Modeling of scroll compressors - Improvements

Energy Technology Data Exchange (ETDEWEB)

Duprez, Marie-Eve; Dumont, Eric; Frere, Marc [Thermodynamics Department, Universite de Mons - Faculte Polytechnique, 31 bd Dolez, 7000 Mons (Belgium)

2010-06-15

This paper presents an improvement of the scroll compressors model previously published by. This improved model allows the calculation of refrigerant mass flow rate, power consumption and heat flow rate that would be released at the condenser of a heat pump equipped with the compressor, from the knowledge of operating conditions and parameters. Both basic and improved models have been tested on scroll compressors using different refrigerants. This study has been limited to compressors with a maximum electrical power of 14 kW and for evaporation temperatures ranging from -40 to 15 C and condensation temperatures from 10 to 75 C. The average discrepancies on mass flow rate, power consumption and heat flow rate are respectively 0.50%, 0.93% and 3.49%. Using a global parameter determination (based on several refrigerants data), this model can predict the behavior of a compressor with another fluid for which no manufacturer data are available. (author)
Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach

Science.gov (United States)

Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Fréderic; Garçon, Rémy; Gailhard, Joël; Paquet, Emmanuel; Mathevet, Thibault

2017-08-01

Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration-validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.
The Government Incentive Regulation Model and Pricing Mechanism in Power Transmission and Distribution Market

Directory of Open Access Journals (Sweden)

Huan Zhang

2016-01-01

Full Text Available The power transmission and distribution (T&D market’s natural monopoly and individual information have been the impediment to improving the energy efficiency in the whole T&D market. In order to improve the whole social welfare, T&D market should be controlled by government. An incentive regulation model with the target of maximizing social welfare has been studied. A list of contracts with transferring payment and quantity of T&D are given to motivate the corporation to reveal the true technical parameter and input the optimal investment. The corporate revenue, optimal investment, and effort are proved to depend on its own technical parameter. The part of incentive regulation model ends with the optimal pricing mechanism of T&D market. At the end of this paper, we give a numerical example to explain our research and confirm its function graphically.
Modelling simple helically delivered dose distributions

International Nuclear Information System (INIS)

Fenwick, John D; Tome, Wolfgang A; Kissick, Michael W; Mackie, T Rock

2005-01-01

In a previous paper, we described quality assurance procedures for Hi-Art helical tomotherapy machines. Here, we develop further some ideas discussed briefly in that paper. Simple helically generated dose distributions are modelled, and relationships between these dose distributions and underlying characteristics of Hi-Art treatment systems are elucidated. In particular, we describe the dependence of dose levels along the central axis of a cylinder aligned coaxially with a Hi-Art machine on fan beam width, couch velocity and helical delivery lengths. The impact on these dose levels of angular variations in gantry speed or output per linear accelerator pulse is also explored
Applying an orographic precipitation model to improve mass balance modeling of the Juneau Icefield, AK

Science.gov (United States)

Roth, A. C.; Hock, R.; Schuler, T.; Bieniek, P.; Aschwanden, A.

2017-12-01

a distributed mass balance model for future mass balance modeling studies of the Juneau Icefield. The LT model has potential to be used in other regions in Alaska and elsewhere with strong orographic effects for improved glacier mass balance modeling and/or hydrological modeling.
A formalism to generate probability distributions for performance-assessment modeling

International Nuclear Information System (INIS)

Kaplan, P.G.

1990-01-01

A formalism is presented for generating probability distributions of parameters used in performance-assessment modeling. The formalism is used when data are either sparse or nonexistent. The appropriate distribution is a function of the known or estimated constraints and is chosen to maximize a quantity known as Shannon's informational entropy. The formalism is applied to a parameter used in performance-assessment modeling. The functional form of the model that defines the parameter, data from the actual field site, and natural analog data are analyzed to estimate the constraints. A beta probability distribution of the example parameter is generated after finding four constraints. As an example of how the formalism is applied to the site characterization studies of Yucca Mountain, the distribution is generated for an input parameter in a performance-assessment model currently used to estimate compliance with disposal of high-level radioactive waste in geologic repositories, 10 CFR 60.113(a)(2), commonly known as the ground water travel time criterion. 8 refs., 2 figs
Optimisation of distributed maintenance: Modelling and application to the multi-factory production

Energy Technology Data Exchange (ETDEWEB)

Simeu-Abazi, Zineb, E-mail: Zineb.Simeu-Abazi@g-scop.inpg.fr [Laboratory G-SCOP, 46 Avenue Felix Viallet, 38031 Grenoble Cedex 1 (France); Ahmad, Alali Alhouaij [Laboratory G-SCOP, 46 Avenue Felix Viallet, 38031 Grenoble Cedex 1 (France)

2011-11-15

This paper concerns the modelling and the cost evaluation of maintenance activities in a distributed context. In this work we study the particular case where the maintenance activities are executed by two workshops: a central maintenance workshop (CMW) and a mobile maintenance workshop (MMW). The CMW concerns the repairing process for the corrective maintenance and the MMW executes all preventive maintenance in several factories according to a defined scheduling. The aim is to take into account the resources (spare parts in the MMW) and maintenance actions for a given operating budget. A modular approach for modelling a multi-site structure is proposed to achieve the aim of improving the availability of facilities on production sites while minimising the cost of maintenance.
Advanced air distribution: Improving health and comfort while reducing energy use

DEFF Research Database (Denmark)

Melikov, Arsen Krikor

2015-01-01

-quality indoor environments at the same time as low-energy consumption. Advanced air distribution, designed to supply clean air where, when, and as much as needed, makes it possible to efficiently achieve thermal comfort, control exposure to contaminants, provide high-quality air for breathing and minimizing......Indoor environment affects the health, comfort, and performance of building occupants. The energy used for heating, cooling, ventilating, and air conditioning of buildings is substantial. Ventilation based on total volume air distribution in spaces is not always an efficient way to provide high...... the risk of airborne cross-infection while reducing energy use. This study justifies the need for improving the present air distribution design in occupied spaces, and in general the need for a paradigm shift from the design of collective environments to the design of individually controlled environments...
Modeling the distribution of extreme share return in Malaysia using Generalized Extreme Value (GEV) distribution

Science.gov (United States)

Hasan, Husna; Radi, Noor Fadhilah Ahmad; Kassim, Suraiya

2012-05-01

Extreme share return in Malaysia is studied. The monthly, quarterly, half yearly and yearly maximum returns are fitted to the Generalized Extreme Value (GEV) distribution. The Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are performed to test for stationarity, while Mann-Kendall (MK) test is for the presence of monotonic trend. Maximum Likelihood Estimation (MLE) is used to estimate the parameter while L-moments estimate (LMOM) is used to initialize the MLE optimization routine for the stationary model. Likelihood ratio test is performed to determine the best model. Sherman's goodness of fit test is used to assess the quality of convergence of the GEV distribution by these monthly, quarterly, half yearly and yearly maximum. Returns levels are then estimated for prediction and planning purposes. The results show all maximum returns for all selection periods are stationary. The Mann-Kendall test indicates the existence of trend. Thus, we ought to model for non-stationary model too. Model 2, where the location parameter is increasing with time is the best for all selection intervals. Sherman's goodness of fit test shows that monthly, quarterly, half yearly and yearly maximum converge to the GEV distribution. From the results, it seems reasonable to conclude that yearly maximum is better for the convergence to the GEV distribution especially if longer records are available. Return level estimates, which is the return level (in this study return amount) that is expected to be exceeded, an average, once every t time periods starts to appear in the confidence interval of T = 50 for quarterly, half yearly and yearly maximum.
Application distribution model and related security attacks in VANET

Science.gov (United States)

Nikaein, Navid; Kanti Datta, Soumya; Marecar, Irshad; Bonnet, Christian

2013-03-01

In this paper, we present a model for application distribution and related security attacks in dense vehicular ad hoc networks (VANET) and sparse VANET which forms a delay tolerant network (DTN). We study the vulnerabilities of VANET to evaluate the attack scenarios and introduce a new attacker`s model as an extension to the work done in [6]. Then a VANET model has been proposed that supports the application distribution through proxy app stores on top of mobile platforms installed in vehicles. The steps of application distribution have been studied in detail. We have identified key attacks (e.g. malware, spamming and phishing, software attack and threat to location privacy) for dense VANET and two attack scenarios for sparse VANET. It has been shown that attacks can be launched by distributing malicious applications and injecting malicious codes to On Board Unit (OBU) by exploiting OBU software security holes. Consequences of such security attacks have been described. Finally, countermeasures including the concepts of sandbox have also been presented in depth.
A Data Flow Model to Solve the Data Distribution Changing Problem in Machine Learning

Directory of Open Access Journals (Sweden)

Shang Bo-Wen

2016-01-01

Full Text Available Continuous prediction is widely used in broad communities spreading from social to business and the machine learning method is an important method in this problem.When we use the machine learning method to predict a problem. We use the data in the training set to fit the model and estimate the distribution of data in the test set.But when we use machine learning to do the continuous prediction we get new data as time goes by and use the data to predict the future data, there may be a problem. As the size of the data set increasing over time, the distribution changes and there will be many garbage data in the training set.We should remove the garbage data as it reduces the accuracy of the prediction. The main contribution of this article is using the new data to detect the timeliness of historical data and remove the garbage data.We build a data flow model to describe how the data flow among the test set, training set, validation set and the garbage set and improve the accuracy of prediction. As the change of the data set, the best machine learning model will change.We design a hybrid voting algorithm to fit the data set better that uses seven machine learning models predicting the same problem and uses the validation set putting different weights on the learning models to give better model more weights. Experimental results show that, when the distribution of the data set changes over time, our time flow model can remove most of the garbage data and get a better result than the traditional method that adds all the data to the data set; our hybrid voting algorithm has a better prediction result than the average accuracy of other predict models
Description of Supply Openings in Numerical Models for Room Air Distribution

DEFF Research Database (Denmark)

Nielsen, Peter V.

This paper discusses various possibilities for describing supply openings in numerical models of room air distribution.......This paper discusses various possibilities for describing supply openings in numerical models of room air distribution....
Volatility modeling for IDR exchange rate through APARCH model with student-t distribution

Science.gov (United States)

Nugroho, Didit Budi; Susanto, Bambang

2017-08-01

The aim of this study is to empirically investigate the performance of APARCH(1,1) volatility model with the Student-t error distribution on five foreign currency selling rates to Indonesian rupiah (IDR), including the Swiss franc (CHF), the Euro (EUR), the British pound (GBP), Japanese yen (JPY), and the US dollar (USD). Six years daily closing rates over the period of January 2010 to December 2016 for a total number of 1722 observations have analysed. The Bayesian inference using the efficient independence chain Metropolis-Hastings and adaptive random walk Metropolis methods in the Markov chain Monte Carlo (MCMC) scheme has been applied to estimate the parameters of model. According to the DIC criterion, this study has found that the APARCH(1,1) model under Student-t distribution is a better fit than the model under normal distribution for any observed rate return series. The 95% highest posterior density interval suggested the APARCH models to model the IDR/JPY and IDR/USD volatilities. In particular, the IDR/JPY and IDR/USD data, respectively, have significant negative and positive leverage effect in the rate returns. Meanwhile, the optimal power coefficient of volatility has been found to be statistically different from 2 in adopting all rate return series, save the IDR/EUR rate return series.
Using the Weibull distribution reliability, modeling and inference

CERN Document Server

McCool, John I

2012-01-01

Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution
Enhanced Vehicle Beddown Approximations for the Improved Theater Distribution Model

Science.gov (United States)

2014-03-27

processed utilizing a heuristic routing and scheduling procedure the authors called the Airlift Planning Algorithm ( APA ). The linear programming model...LINGO 13 environment. The model is then solved by LINGO 13 and solution data is passed back to the Excel environment in a readable format . All original...DSS is relatively unchanged when solutions to the ITDM are referenced for comparison testing. Readers are encouraged to see Appendix I for ITDM VBA
Distribution load estimation - DLE

Energy Technology Data Exchange (ETDEWEB)

Seppaelae, A. [VTT Energy, Espoo (Finland)

1996-12-31

The load research project has produced statistical information in the form of load models to convert the figures of annual energy consumption to hourly load values. The reliability of load models is limited to a certain network because many local circumstances are different from utility to utility and time to time. Therefore there is a need to make improvements in the load models. Distribution load estimation (DLE) is the method developed here to improve load estimates from the load models. The method is also quite cheap to apply as it utilises information that is already available in SCADA systems
Distribution load estimation - DLE

Energy Technology Data Exchange (ETDEWEB)

Seppaelae, A [VTT Energy, Espoo (Finland)

1997-12-31

The load research project has produced statistical information in the form of load models to convert the figures of annual energy consumption to hourly load values. The reliability of load models is limited to a certain network because many local circumstances are different from utility to utility and time to time. Therefore there is a need to make improvements in the load models. Distribution load estimation (DLE) is the method developed here to improve load estimates from the load models. The method is also quite cheap to apply as it utilises information that is already available in SCADA systems
Siting and sizing of distributed generators based on improved simulated annealing particle swarm optimization.

Science.gov (United States)

Su, Hongsheng

2017-12-18

Distributed power grids generally contain multiple diverse types of distributed generators (DGs). Traditional particle swarm optimization (PSO) and simulated annealing PSO (SA-PSO) algorithms have some deficiencies in site selection and capacity determination of DGs, such as slow convergence speed and easily falling into local trap. In this paper, an improved SA-PSO (ISA-PSO) algorithm is proposed by introducing crossover and mutation operators of genetic algorithm (GA) into SA-PSO, so that the capabilities of the algorithm are well embodied in global searching and local exploration. In addition, diverse types of DGs are made equivalent to four types of nodes in flow calculation by the backward or forward sweep method, and reactive power sharing principles and allocation theory are applied to determine initial reactive power value and execute subsequent correction, thus providing the algorithm a better start to speed up the convergence. Finally, a mathematical model of the minimum economic cost is established for the siting and sizing of DGs under the location and capacity uncertainties of each single DG. Its objective function considers investment and operation cost of DGs, grid loss cost, annual purchase electricity cost, and environmental pollution cost, and the constraints include power flow, bus voltage, conductor current, and DG capacity. Through applications in an IEEE33-node distributed system, it is found that the proposed method can achieve desirable economic efficiency and safer voltage level relative to traditional PSO and SA-PSO algorithms, and is a more effective planning method for the siting and sizing of DGs in distributed power grids.
Comparison of sparse point distribution models

DEFF Research Database (Denmark)

Erbou, Søren Gylling Hemmingsen; Vester-Christensen, Martin; Larsen, Rasmus

2010-01-01

This paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior m...

NHPP-Based Software Reliability Models Using Equilibrium Distribution

Science.gov (United States)

Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.
Linear Model for Optimal Distributed Generation Size Predication

Directory of Open Access Journals (Sweden)

Ahmed Al Ameri

2017-01-01

Full Text Available This article presents a linear model predicting optimal size of Distributed Generation (DG that addresses the minimum power loss. This method is based fundamentally on strong coupling between active power and voltage angle as well as between reactive power and voltage magnitudes. This paper proposes simplified method to calculate the total power losses in electrical grid for different distributed generation sizes and locations. The method has been implemented and tested on several IEEE bus test systems. The results show that the proposed method is capable of predicting approximate optimal size of DG when compared with precision calculations. The method that linearizes a complex model showed a good result, which can actually reduce processing time required. The acceptable accuracy with less time and memory required can help the grid operator to assess power system integrated within large-scale distribution generation.
Reexamination of shell model tests of the Porter-Thomas distribution

International Nuclear Information System (INIS)

Grimes, S.M.

1983-01-01

Recent shell model calculations have yielded width amplitude distributions which have apparently not agreed with the Porter-Thomas distribution. This result conflicts with the present experimental evidence. A reanalysis of these calculations suggests that, although correct, they do not imply that the Porter-Thomas distribution will fail to describe the width distributions observed experimentally. The conditions for validity of the Porter-Thomas distribution are discussed
Lightning Performance on Overhead Distribution Lines : After Improvement Field Observation

Directory of Open Access Journals (Sweden)

Reynaldo Zoro

2009-11-01

Full Text Available Two feeders of 20 kV overhead distribution lines which are located in a high lightning density area are chosen to be observed as a field study due to their good lightning performance after improvement of lightning protection system. These two feeders used the new overhead ground wire and new line arrester equipped with lightning counter on the main lines. The significant reduced of lines outages are reported. Study was carried out to observe these improvements by comparing to the other two feeders line which are not improved and not equipped yet with the ground wire and line arrester. These two feeders located in the nearby area. Two cameras were installed to record the trajectory of the lightning strikes on the improved lines. Lightning peak currents are measured using magnetic tape measurement system installed on the grounding lead of lightning arrester. Lightning overvoltage calculations are carried out by using several scenarios based on observation results and historical lightning data derived from lightning detection network. Lightning overvoltages caused by indirect or direct strikes are analyzed to get the lightning performance of the lines. The best scenario was chosen and performance of the lines were improved significantly by installing overhead ground wire and improvement of lightning arrester installation.
Directional statistics-based reflectance model for isotropic bidirectional reflectance distribution functions.

Science.gov (United States)

Nishino, Ko; Lombardi, Stephen

2011-01-01

We introduce a novel parametric bidirectional reflectance distribution function (BRDF) model that can accurately encode a wide variety of real-world isotropic BRDFs with a small number of parameters. The key observation we make is that a BRDF may be viewed as a statistical distribution on a unit hemisphere. We derive a novel directional statistics distribution, which we refer to as the hemispherical exponential power distribution, and model real-world isotropic BRDFs as mixtures of it. We derive a canonical probabilistic method for estimating the parameters, including the number of components, of this novel directional statistics BRDF model. We show that the model captures the full spectrum of real-world isotropic BRDFs with high accuracy, but a small footprint. We also demonstrate the advantages of the novel BRDF model by showing its use for reflection component separation and for exploring the space of isotropic BRDFs.
The evaluation of distributed damage in concrete based on sinusoidal modeling of the ultrasonic response.

Science.gov (United States)

Sepehrinezhad, Alireza; Toufigh, Vahab

2018-05-25

, the modified amplitude ratio method is introduced as an improvement of the classical method. The proposed methods were validated to be effective descriptors of distributed damage. The presented models were also in good agreement with the experimental data. Copyright © 2018 Elsevier B.V. All rights reserved.
Networked Timetable Stability Improvement Based on a Bilevel Optimization Programming Model

Directory of Open Access Journals (Sweden)

Xuelei Meng

2014-01-01

Full Text Available Train timetable stability is the possibility to recover the status of the trains to serve as arranged according to the original timetable when the trains are disturbed. To improve the train timetable stability from the network perspective, the bilevel programming model is constructed, in which the upper level programming is to optimize the timetable stability on the network level and the lower is to improve the timetable stability on the dispatching railway segments. Timetable stability on the network level is defined with the variances of the utilization coefficients of the section capacity and station capacity. Weights of stations and sections are decided by the capacity index number and the degrees. The lower level programming focuses on the buffer time distribution plan of the trains operating on the sections and stations, taking the operating rules of the trains as constraints. A novel particle swarm algorithm is proposed and designed for the bilevel programming model. The computing case proves the feasibility of the model and the efficiency of the algorithm. The method outlined in this paper can be embedded in the networked train operation dispatching system.
Analysing the distribution of synaptic vesicles using a spatial point process model

DEFF Research Database (Denmark)

Khanmohammadi, Mahdieh; Waagepetersen, Rasmus; Nava, Nicoletta

2014-01-01

functionality by statistically modelling the distribution of the synaptic vesicles in two groups of rats: a control group subjected to sham stress and a stressed group subjected to a single acute foot-shock (FS)-stress episode. We hypothesize that the synaptic vesicles have different spatial distributions...... in the two groups. The spatial distributions are modelled using spatial point process models with an inhomogeneous conditional intensity and repulsive pairwise interactions. Our results verify the hypothesis that the two groups have different spatial distributions....
Distributed simulation a model driven engineering approach

CERN Document Server

Topçu, Okan; Oğuztüzün, Halit; Yilmaz, Levent

2016-01-01

Backed by substantive case studies, the novel approach to software engineering for distributed simulation outlined in this text demonstrates the potent synergies between model-driven techniques, simulation, intelligent agents, and computer systems development.
A void distribution model-flashing flow

International Nuclear Information System (INIS)

Riznic, J.; Ishii, M.; Afgan, N.

1987-01-01

A new model for flashing flow based on wall nucleations is proposed here and the model predictions are compared with some experimental data. In order to calculate the bubble number density, the bubble number transport equation with a distributed source from the wall nucleation sites was used. Thus it was possible to avoid the usual assumption of a constant bubble number density. Comparisons of the model with the data shows that the model based on the nucleation site density correlation appears to be acceptable to describe the vapor generation in the flashing flow. For the limited data examined, the comparisons show rather satisfactory agreement without using a floating parameter to adjust the model. This result indicated that, at least for the experimental conditions considered here, the mechanistic predictions of the flashing phenomenon is possible on the present wall nucleation based model
Understanding the geographic distribution of tropical cyclone formation for applications in climate models

Science.gov (United States)

Tory, Kevin J.; Ye, H.; Dare, R. A.

2018-04-01

Projections of Tropical cyclone (TC) formation under future climate scenarios are dependent on climate model simulations. However, many models produce unrealistic geographical distributions of TC formation, especially in the north and south Atlantic and eastern south Pacific TC basins. In order to improve confidence in projections it is important to understand the reasons behind these model errors. However, considerable effort is required to analyse the many models used in projection studies. To address this problem, a novel diagnostic is developed that provides compelling insight into why TCs form where they do, using a few summary diagrams. The diagnostic is developed after identifying a relationship between seasonal climatologies of atmospheric variables in 34 years of ECMWF reanalysis data, and TC detection distributions in the same data. Geographic boundaries of TC formation are constructed from four threshold quantities. TCs form where Emanuel's Maximum Potential Intensity, V_{{PI}}, exceeds 40 {ms}^{{ - 1}}, 700 hPa relative humidity, RH_{{700}}, exceeds 40%, and the magnitude of the difference in vector winds between 850 and 200 hPa, V_{{sh}}, is less than 20 {ms}^{{ - 1}}. The equatorial boundary is best defined by a composite quantity containing the ratio of absolute vorticity (η ) to the meridional gradient of absolute vorticity (β ^{*}), rather than η alone. {β ^*} is also identified as a potentially important ingredient for TC genesis indices. A comparison of detected Tropical Depression (TD) and Tropical Storm (TS) climatologies revealed TDs more readily intensify further to TS where {V_{PI}} is elevated and {V_{sh}} is relatively weak. The distributions of each threshold quantity identify the factors that favour and suppress TC formation throughout the tropics in the real world. This information can be used to understand why TC formation is poorly represented in some climate models, and shows potential for understanding anomalous TC formation
Cyber Physical System Modelling of Distribution Power Systems for Dynamic Demand Response

Science.gov (United States)

Chu, Xiaodong; Zhang, Rongxiang; Tang, Maosen; Huang, Haoyi; Zhang, Lei

2018-01-01

Dynamic demand response (DDR) is a package of control methods to enhance power system security. A CPS modelling and simulation platform for DDR in distribution power systems is presented in this paper. CPS modelling requirements of distribution power systems are analyzed. A coupled CPS modelling platform is built for assessing DDR in the distribution power system, which combines seamlessly modelling tools of physical power networks and cyber communication networks. Simulations results of IEEE 13-node test system demonstrate the effectiveness of the modelling and simulation platform.
Five (or so) challenges for species distribution modelling

DEFF Research Database (Denmark)

Bastos Araujo, Miguel; Guisan, Antoine

2006-01-01

Species distribution modelling is central to both fundamental and applied research in biogeography. Despite widespread use of models, there are still important conceptual ambiguities as well as biotic and algorithmic uncertainties that need to be investigated in order to increase confidence in mo...
RF model of the distribution system as a communication channel, phase 2. Volume 1: Summary Report

Science.gov (United States)

Rustay, R. C.; Gajjar, J. T.; Rankin, R. W.; Wentz, R. C.; Wooding, R.

1982-01-01

The design, implementation, and verification of a computerized model for predicting the steady-state sinusoidal response of radial (tree) configured distribution feeders was undertaken. That work demonstrated the feasibility and validity based on verification measurements made on a limited size portion of an actual live feeder. On that basis a follow-on effort concerned with (1) extending the verification based on a greater variety of situations and network size, (2) extending the model capabilities for reverse direction propagation, (3) investigating parameter sensitivities, (4) improving transformer models, and (5) investigating procedures/fixes for ameliorating propagation trouble spots was conducted. Results are summarized.
Simulation and optimization of logistics distribution for an engine production line

Energy Technology Data Exchange (ETDEWEB)

Song, L.; Jin, S.; Tang, P.

2016-07-01

In order to analyze and study the factors about Logistics distribution system, solve the problems of out of stock on the production line and improve the efficiency of the assembly line. Using the method of industrial engineering, put forward the optimization scheme of distribution system. The simulation model of logistics distribution system for engine assembly line was build based on Witness software. The optimization plan is efficient to improve Logistics distribution efficiency, production of assembly line efficiency and reduce the storage of production line. Based on the study of the modeling and simulation of engine production logistics distribution system, the result reflects some influence factors about production logistics system, which has reference value to improving the efficiency of the production line. (Author)
An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Nur Faziera Napis

2018-05-01

Full Text Available The presence of optimized distributed generation (DG with suitable distribution network reconfiguration (DNR in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO is proposed in this research. The objective function is formulated to minimize the total power losses (TPL and to improve the voltage stability index (VSI. The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO and iteration particle swarm optimization (IPSO. Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms.
Turboelectric Distributed Propulsion System Modelling

OpenAIRE

Liu, Chengyuan

2013-01-01

The Blended-Wing-Body is a conceptual aircraft design with rear-mounted, over wing engines. Turboelectric distributed propulsion system with boundary layer ingestion has been considered for this aircraft. It uses electricity to transmit power from the core turbine to the fans, therefore dramatically increases bypass ratio to reduce fuel consumption and noise. This dissertation presents methods on designing the TeDP system, evaluating effects of boundary layer ingestion, modelling engine perfo...
Income Distribution Over Educational Levels: A Simple Model.

Science.gov (United States)

Tinbergen, Jan

An econometric model is formulated that explains income per person in various compartments of the labor market defined by three main levels of education and by education required. The model enables an estimation of the effect of increased access to education on that distribution. The model is based on a production for the economy as a whole; a…
Assigning probability distributions to input parameters of performance assessment models

Energy Technology Data Exchange (ETDEWEB)

Mishra, Srikanta [INTERA Inc., Austin, TX (United States)

2002-02-01

This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.
Assigning probability distributions to input parameters of performance assessment models

International Nuclear Information System (INIS)

Mishra, Srikanta

2002-02-01

This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available

A MODEL OF HETEROGENEOUS DISTRIBUTED SYSTEM FOR FOREIGN EXCHANGE PORTFOLIO ANALYSIS

Directory of Open Access Journals (Sweden)

Dragutin Kermek

2006-06-01

Full Text Available The paper investigates the design of heterogeneous distributed system for foreign exchange portfolio analysis. The proposed model includes few separated and dislocated but connected parts through distributed mechanisms. Making system distributed brings new perspectives to performance busting where software based load balancer gets very important role. Desired system should spread over multiple, heterogeneous platforms in order to fulfil open platform goal. Building such a model incorporates different patterns from GOF design patterns, business patterns, J2EE patterns, integration patterns, enterprise patterns, distributed design patterns to Web services patterns. The authors try to find as much as possible appropriate patterns for planned tasks in order to capture best modelling and programming practices.
Modeling the probability distribution of peak discharge for infiltrating hillslopes

Science.gov (United States)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.
A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

Science.gov (United States)

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.
Evolution of a Family Nurse Practitioner Program to Improve Primary Care Distribution

Science.gov (United States)

Andrus, Len Hughes; Fenley, Mary D.

1976-01-01

Describes a Family Nurse Practitioner Program that has effectively improved the distribution of primary health care manpower in rural areas. Program characteristics include selection of personnel from areas of need, decentralization of clinical and didactic training sites, competency-based portable curriculum, and circuit-riding institutionally…
Building a generalized distributed system model

Science.gov (United States)

Mukkamala, R.

1993-01-01

The key elements in the 1992-93 period of the project are the following: (1) extensive use of the simulator to implement and test - concurrency control algorithms, interactive user interface, and replica control algorithms; and (2) investigations into the applicability of data and process replication in real-time systems. In the 1993-94 period of the project, we intend to accomplish the following: (1) concentrate on efforts to investigate the effects of data and process replication on hard and soft real-time systems - especially we will concentrate on the impact of semantic-based consistency control schemes on a distributed real-time system in terms of improved reliability, improved availability, better resource utilization, and reduced missed task deadlines; and (2) use the prototype to verify the theoretically predicted performance of locking protocols, etc.
Comparison of different reliability improving investment strategies of Finnish medium-voltage distribution systems

Energy Technology Data Exchange (ETDEWEB)

Laagland, H.

2012-07-01

The electricity distribution sector in Finland is highly regulated and the return on investments in distribution networks is low. Low profits don't make the electricity distribution sector attractive to outside investors. During the second regulatory period of 2008-2011 incentives are included into the Finnish regulation model which allows higher profits for the network owners for right allocated network investments leading to lower operation and interruption costs. The goal of the thesis is to find cost-effective medium-voltage distribution system investment strategies for the Finnish power distribution companies with respect to the incentives of the second regulatory period. In this work the sectionalisation concept is further developed by deriving equations for a homogeneous electricity distribution system for the economical and reliability indices as a function of the number of sectionalisation zones. The cost-effective medium-voltage distribution system investment strategies are found by studying the technical and economic interaction of feeder automation on different network structures. Ten feeder automation schemes have been applied to six urban/rural area generic feeders and two real rural area feeders of a distribution company in western Finland. The analytical approach includes modelling of the feeders and feeder functions and calculation of the economical and reliability indices. The following investment areas are included: different electricity distribution systems, new substation, new switching station, central earth-fault current compensation, cabling and feeder automation. The value of the results of this work is that they reveal the influence that feeder automation has on the reliability and economy of different distribution structures. This created transparency enables a national and/or distribution company network investment strategy to optimise the economic benefits of investments. (orig.)
Evaluating Domestic Hot Water Distribution System Options with Validated Analysis Models

Energy Technology Data Exchange (ETDEWEB)

Weitzel, E. [Alliance for Residential Building Innovation, Davis, CA (United States); Hoeschele, E. [Alliance for Residential Building Innovation, Davis, CA (United States)

2014-09-01

A developing body of work is forming that collects data on domestic hot water consumption, water use behaviors, and energy efficiency of various distribution systems. Transient System Simulation Tool (TRNSYS) is a full distribution system developed that has been validated using field monitoring data and then exercised in a number of climates to understand climate impact on performance. In this study, the Building America team built upon previous analysis modeling work to evaluate differing distribution systems and the sensitivities of water heating energy and water use efficiency to variations of climate, load, distribution type, insulation and compact plumbing practices. Overall, 124 different TRNSYS models were simulated. The results of this work are useful in informing future development of water heating best practices guides as well as more accurate (and simulation time efficient) distribution models for annual whole house simulation programs.
Influence of Hardening Model on Weld Residual Stress Distribution

Energy Technology Data Exchange (ETDEWEB)

Mullins, Jonathan; Gunnars, Jens (Inspecta Technology AB, Stockholm (Sweden))

2009-06-15

This study is the third stage of a project sponsored by the Swedish Radiation Safety Authority (SSM) to improve the weld residual stress modelling procedures currently used in Sweden. The aim of this study was to determine which material hardening model gave the best agreement with experimentally measured weld residual stress distributions. Two girth weld geometries were considered: 19mm and 65mm thick girth welds with Rin/t ratios of 10.5 and 2.8, respectively. The FE solver ABAQUS Standard v6.5 was used for analysis. As a preliminary step some improvements were made to the welding simulation procedure used in part one of the project. First, monotonic stress strain curves and a mixed isotropic/kinematic hardening model were sourced from the literature for 316 stainless steel. Second, more detailed information was obtained regarding the geometry and welding sequence for the Case 1 weld (compared with phase 1 of this project). Following the preliminary step, welding simulations were conducted using isotropic, kinematic and mixed hardening models. The isotropic hardening model gave the best overall agreement with experimental measurements; it is therefore recommended for future use in welding simulations. The mixed hardening model gave good agreement for predictions of the hoop stress but tended to under estimate the magnitude of the axial stress. It must be noted that two different sources of data were used for the isotropic and mixed models in this study and this may have contributed to the discrepancy in predictions. When defining a mixed hardening model it is difficult to delineate the relative contributions of isotropic and kinematic hardening and for the model used it may be that a greater isotropic hardening component should have been specified. The kinematic hardening model consistently underestimated the magnitude of both the axial and hoop stress and is not recommended for use. Two sensitivity studies were also conducted. In the first the effect of using a
Influence of Hardening Model on Weld Residual Stress Distribution

International Nuclear Information System (INIS)

Mullins, Jonathan; Gunnars, Jens

2009-06-01

This study is the third stage of a project sponsored by the Swedish Radiation Safety Authority (SSM) to improve the weld residual stress modelling procedures currently used in Sweden. The aim of this study was to determine which material hardening model gave the best agreement with experimentally measured weld residual stress distributions. Two girth weld geometries were considered: 19mm and 65mm thick girth welds with Rin/t ratios of 10.5 and 2.8, respectively. The FE solver ABAQUS Standard v6.5 was used for analysis. As a preliminary step some improvements were made to the welding simulation procedure used in part one of the project. First, monotonic stress strain curves and a mixed isotropic/kinematic hardening model were sourced from the literature for 316 stainless steel. Second, more detailed information was obtained regarding the geometry and welding sequence for the Case 1 weld (compared with phase 1 of this project). Following the preliminary step, welding simulations were conducted using isotropic, kinematic and mixed hardening models. The isotropic hardening model gave the best overall agreement with experimental measurements; it is therefore recommended for future use in welding simulations. The mixed hardening model gave good agreement for predictions of the hoop stress but tended to under estimate the magnitude of the axial stress. It must be noted that two different sources of data were used for the isotropic and mixed models in this study and this may have contributed to the discrepancy in predictions. When defining a mixed hardening model it is difficult to delineate the relative contributions of isotropic and kinematic hardening and for the model used it may be that a greater isotropic hardening component should have been specified. The kinematic hardening model consistently underestimated the magnitude of both the axial and hoop stress and is not recommended for use. Two sensitivity studies were also conducted. In the first the effect of using a
Improving simulated spatial distribution of productivity and biomass in Amazon forests using the ACME land model

Science.gov (United States)

Yang, X.; Thornton, P. E.; Ricciuto, D. M.; Shi, X.; Xu, M.; Hoffman, F. M.; Norby, R. J.

2017-12-01

Tropical forests play a crucial role in the global carbon cycle, accounting for one third of the global NPP and containing about 25% of global vegetation biomass and soil carbon. This is particularly true for tropical forests in the Amazon region, as it comprises approximately 50% of the world's tropical forests. It is therefore important for us to understand and represent the processes that determine the fluxes and storage of carbon in these forests. In this study, we show that the implementation of phosphorus (P) cycle and P limitation in the ACME Land Model (ALM) improves simulated spatial pattern of NPP. The P-enabled ALM is able to capture the west-to-east gradient of productivity, consistent with field observations. We also show that by improving the representation of mortality processes, ALM is able to reproduce the observed spatial pattern of above ground biomass across the Amazon region.
Towards an Information Model of Consistency Maintenance in Distributed Interactive Applications

Directory of Open Access Journals (Sweden)

Xin Zhang

2008-01-01

Full Text Available A novel framework to model and explore predictive contract mechanisms in distributed interactive applications (DIAs using information theory is proposed. In our model, the entity state update scheme is modelled as an information generation, encoding, and reconstruction process. Such a perspective facilitates a quantitative measurement of state fidelity loss as a result of the distribution protocol. Results from an experimental study on a first-person shooter game are used to illustrate the utility of this measurement process. We contend that our proposed model is a starting point to reframe and analyse consistency maintenance in DIAs as a problem in distributed interactive media compression.
Shell model test of the Porter-Thomas distribution

International Nuclear Information System (INIS)

Grimes, S.M.; Bloom, S.D.

1981-01-01

Eigenvectors have been calculated for the A=18, 19, 20, 21, and 26 nuclei in an sd shell basis. The decomposition of these states into their shell model components shows, in agreement with other recent work, that this distribution is not a single Gaussian. We find that the largest amplitudes are distributed approximately in a Gaussian fashion. Thus, many experimental measurements should be consistent with the Porter-Thomas predictions. We argue that the non-Gaussian form of the complete distribution can be simply related to the structure of the Hamiltonian
Idealized models of the joint probability distribution of wind speeds

Science.gov (United States)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.
Sectional modeling of nanoparticle size and charge distributions in dusty plasmas

International Nuclear Information System (INIS)

Agarwal, Pulkit; Girshick, Steven L

2012-01-01

Sectional models of the dynamics of aerosol populations are well established in the aerosol literature but have received relatively less attention in numerical models of dusty plasmas, where most modeling studies have assumed the existence of monodisperse dust particles. In the case of plasmas in which nanoparticles nucleate and grow, significant polydispersity can exist in particle size distributions, and stochastic charging can cause particles of given size to have a broad distribution of charge states. Sectional models, while computationally expensive, are well suited to treating such distributions. This paper presents an overview of sectional modeling of nanodusty plasmas, and presents examples of simulation results that reveal important qualitative features of the spatiotemporal evolution of such plasmas, many of which could not be revealed by models that consider only monodisperse dust particles and average particle charge. These features include the emergence of bimodal particle populations consisting of very small neutral particles and larger negatively charged particles, the effects of size and charge distributions on coagulation, spreading and structure of the particle cloud, and the dynamics of dusty plasma afterglows. (paper)
Improving streamflow simulations and forecasting performance of SWAT model by assimilating remotely sensed soil moisture observations

Science.gov (United States)

Patil, Amol; Ramsankaran, RAAJ

2017-12-01

This article presents a study carried out using EnKF based assimilation of coarser-scale SMOS soil moisture retrievals to improve the streamflow simulations and forecasting performance of SWAT model in a large catchment. This study has been carried out in Munneru river catchment, India, which is about 10,156 km2. In this study, an EnkF based new approach is proposed for improving the inherent vertical coupling of soil layers of SWAT hydrological model during soil moisture data assimilation. Evaluation of the vertical error correlation obtained between surface and subsurface layers indicates that the vertical coupling can be improved significantly using ensemble of soil storages compared to the traditional static soil storages based EnKF approach. However, the improvements in the simulated streamflow are moderate, which is due to the limitations in SWAT model in reflecting the profile soil moisture updates in surface runoff computations. Further, it is observed that the durability of streamflow improvements is longer when the assimilation system effectively updates the subsurface flow component. Overall, the results of the present study indicate that the passive microwave-based coarser-scale soil moisture products like SMOS hold significant potential to improve the streamflow estimates when assimilating into large-scale distributed hydrological models operating at a daily time step.
UV Stellar Distribution Model for the Derivation of Payload

Directory of Open Access Journals (Sweden)

Young-Jun Choi

1999-12-01

Full Text Available We present the results of a model calculation of the stellar distribution in a UV and centered at 2175Å corresponding to the well-known bump in the interstellar extinction curve. The stellar distribution model used here is based on the Bahcall-Soneira galaxy model (1980. The source code for model calculation was designed by Brosch (1991 and modified to investigate various designing factors for UV satellite payload. The model predicts UV stellar densities in different sky directions, and its results are compared with the TD-1 star counts for a number of sky regions. From this study, we can determine the field of view, size of optics, angular resolution, and number of stars in one orbit. There will provide the basic constrains in designing a satellite payload for UV observations.
Improvements of Physical Models in TRITGO code for Tritium Behavior Analysis in VHTR

International Nuclear Information System (INIS)

Yoo, Jun Soo; Tak, Nam Il; Lim, Hong Sik

2010-01-01

Since tritium is radioactive material with 12.32 year of half-life and is generated by a ternary fission reaction in fuel as well as by neutron absorption reactions of impurities in Very High Temperature gas-cooled Reactor (VHTR) core, accurate prediction of tritium behavior and its concentration in product hydrogen is definitely important in terms of public safety for its construction. In this respect, TRITGO code was developed for estimating the tritium production and distribution in high temperature gas-cooled reactors by General Atomics (GA). However, some models in it are hard-wired to specific reactor type or too simplified, which makes the analysis results less applicable. Thus, major improvements need to be considered for better predictions. In this study, some of model improvements have been suggested and its effect is evaluated based on the analysis work against PMR600 design concept
Maxent modelling for predicting the potential distribution of Thai Palms

DEFF Research Database (Denmark)

Tovaranonte, Jantrararuk; Barfod, Anders S.; Overgaard, Anne Blach

2011-01-01

on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...
Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

The Natural Gas Transmission and Distribution Model (NGTDM) is the component of the National Energy Modeling System (NEMS) that is used to represent the domestic natural gas transmission and distribution system. The NGTDM is the model within the NEMS that represents the transmission, distribution, and pricing of natural gas. The model also includes representations of the end-use demand for natural gas, the production of domestic natural gas, and the availability of natural gas traded on the international market based on information received from other NEMS models. The NGTDM determines the flow of natural gas in an aggregate, domestic pipeline network, connecting domestic and foreign supply regions with 12 demand regions. The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic design, provides detail on the methodology employed, and describes the model inputs, outputs, and key assumptions. Subsequent chapters of this report provide: an overview of NGTDM; a description of the interface between the NEMS and NGTDM; an overview of the solution methodology of the NGTDM; the solution methodology for the Annual Flow Module; the solution methodology for the Distributor Tariff Module; the solution methodology for the Capacity Expansion Module; the solution methodology for the Pipeline Tariff Module; and a description of model assumptions, inputs, and outputs.
Deterioration and optimal rehabilitation modelling for urban water distribution systems

NARCIS (Netherlands)

Zhou, Y.

2018-01-01

Pipe failures in water distribution systems can have a serious impact and hence it’s important to maintain the condition and integrity of the distribution system. This book presents a whole-life cost optimisation model for the rehabilitation of water distribution systems. It combines a pipe breakage

Modeling and Control for Islanding Operation of Active Distribution Systems

DEFF Research Database (Denmark)

Cha, Seung-Tae; Wu, Qiuwei; Saleem, Arshad

2011-01-01

to stabilize the frequency. Different agents are defined to represent different resources in the distribution systems. A test platform with a real time digital simulator (RTDS), an OPen Connectivity (OPC) protocol server and the multi-agent based intelligent controller is established to test the proposed multi......Along with the increasing penetration of distributed generation (DG) in distribution systems, there are more resources for system operators to improve the operation and control of the whole system and enhance the reliability of electricity supply to customers. The distribution systems with DG...... are able to operate in is-landing operation mode intentionally or unintentionally. In order to smooth the transition from grid connected operation to islanding operation for distribution systems with DG, a multi-agent based controller is proposed to utilize different re-sources in the distribution systems...
SimpleTreat 3.0: a model to predict the distribution and elimination of Chemicals by Sewage Treatment Plants

NARCIS (Netherlands)

Struijs J; ECO

1996-01-01

The spreadsheet SimpelTreat 3.0 is a model to predict the distribution and elimination of chemicals by sewage treatment. Simpeltreat 3.0 is an improved version of SimpleTreat, applied in the Netherlands in the Uniform System for the Evaluation of Substances (USES version 1.0, 1994). Although in the
Modelling Framework and the Quantitative Analysis of Distributed Energy Resources in Future Distribution Networks

DEFF Research Database (Denmark)

Han, Xue; Sandels, Claes; Zhu, Kun

2013-01-01

There has been a large body of statements claiming that the large-scale deployment of Distributed Energy Resources (DERs) could eventually reshape the future distribution grid operation in numerous ways. Thus, it is necessary to introduce a framework to measure to what extent the power system......, comprising distributed generation, active demand and electric vehicles. Subsequently, quantitative analysis was made on the basis of the current and envisioned DER deployment scenarios proposed for Sweden. Simulations are performed in two typical distribution network models for four seasons. The simulation...... results show that in general the DER deployment brings in the possibilities to reduce the power losses and voltage drops by compensating power from the local generation and optimizing the local load profiles....
Improved time series prediction with a new method for selection of model parameters

International Nuclear Information System (INIS)

Jade, A M; Jayaraman, V K; Kulkarni, B D

2006-01-01

A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)
Improved TOPSIS decision model for NPP emergencies

International Nuclear Information System (INIS)

Zhang Jin; Liu Feng; Huang Lian

2011-01-01

In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants. Given the complexity of multi-attribute emergency decision-making on nuclear accident, the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index. A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect. (authors)
Improved spectral absorption coefficient grouping strategy of wide band k-distribution model used for calculation of infrared remote sensing signal of hot exhaust systems

Science.gov (United States)

Hu, Haiyang; Wang, Qiang

2018-07-01

A new strategy for grouping spectral absorption coefficients, considering the influences of both temperature and species mole ratio inhomogeneities on correlated-k characteristics of the spectra of gas mixtures, has been deduced to match the calculation method of spectral overlap parameter used in multiscale multigroup wide band k-distribution model. By comparison with current spectral absorption coefficient grouping strategies, for which only the influence of temperature inhomogeneity on the correlated-k characteristics of spectra of single species was considered, the improvements in calculation accuracies resulting from the new grouping strategy were evaluated using a series of 0D cases in which radiance under 3-5-μm wave band emitted by hot combustion gas of hydrocarbon fuel was attenuated by atmosphere with quite different temperature and mole ratios of water vapor and carbon monoxide to carbon dioxide. Finally, evaluations are presented on the calculation of remote sensing thermal images of transonic hot jet exhausted from a chevron ejecting nozzle with solid wall cooling system.
A Distributed Model of Oilseed Biorefining, via Integrated Industrial Ecology Exchanges

Science.gov (United States)

Ferrell, Jeremy C.

As the demand for direct petroleum substitutes increases, biorefineries are poised to become centers for conversion of biomass into fuels, energy, and biomaterials. A distributed model offers reduced transportation, tailored process technology to available feedstock, and increased local resilience. Oilseeds are capable of producing a wide variety of useful products additive to food, feed, and fuel needs. Biodiesel manufacturing technology lends itself to smaller-scale distributed facilities able to process diverse feedstocks and meet demand of critical diesel fuel for basic municipal services, safety, sanitation, infrastructure repair, and food production. Integrating biodiesel refining facilities as tenants of eco-industrial parks presents a novel approach for synergistic energy and material exchanges whereby environmental and economic metrics can be significantly improved upon compared to stand alone models. This research is based on the Catawba County NC EcoComplex and the oilseed crushing and biodiesel processing facilities (capacity-433 tons biodiesel per year) located within. Technical and environmental analyses of the biorefinery components as well as agronomic and economic models are presented. The life cycle assessment for the two optimal biodiesel feedstocks, soybeans and used cooking oil, resulted in fossil energy ratios of 7.19 and 12.1 with carbon intensity values of 12.51 gCO2-eq/MJ and 7.93 gCO2-eq/MJ, respectively within the industrial ecology system. Economic modeling resulted in a biodiesel conversion cost of 1.43 per liter of fuel produced with used cooking oil, requiring a subsidy of 0.58 per liter to reach the break-even point. As subsidies continue significant fluctuation, metrics other than operating costs are required to justify small-scale biofuel projects.
Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

Science.gov (United States)

Assmus, Frauke; Houston, J Brian; Galetin, Aleksandra

2017-11-15

The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pK a ≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among
An improved interfacial bonding model for material interface modeling

Science.gov (United States)

Lin, Liqiang; Wang, Xiaodu; Zeng, Xiaowei

2016-01-01

An improved interfacial bonding model was proposed from potential function point of view to investigate interfacial interactions in polycrystalline materials. It characterizes both attractive and repulsive interfacial interactions and can be applied to model different material interfaces. The path dependence of work-of-separation study indicates that the transformation of separation work is smooth in normal and tangential direction and the proposed model guarantees the consistency of the cohesive constitutive model. The improved interfacial bonding model was verified through a simple compression test in a standard hexagonal structure. The error between analytical solutions and numerical results from the proposed model is reasonable in linear elastic region. Ultimately, we investigated the mechanical behavior of extrafibrillar matrix in bone and the simulation results agreed well with experimental observations of bone fracture. PMID:28584343
Gravity model improvement investigation. [improved gravity model for determination of ocean geoid

Science.gov (United States)

Siry, J. W.; Kahn, W. D.; Bryan, J. W.; Vonbun, F. F.

1973-01-01

This investigation was undertaken to improve the gravity model and hence the ocean geoid. A specific objective is the determination of the gravity field and geoid with a space resolution of approximately 5 deg and a height resolution of the order of five meters. The concept of the investigation is to utilize both GEOS-C altimeter and satellite-to-satellite tracking data to achieve the gravity model improvement. It is also planned to determine the geoid in selected regions with a space resolution of about a degree and a height resolution of the order of a meter or two. The short term objectives include the study of the gravity field in the GEOS-C calibration area outlined by Goddard, Bermuda, Antigua, and Cape Kennedy, and also in the eastern Pacific area which is viewed by ATS-F.
Research on the control strategy of distributed energy resources inverter based on improved virtual synchronous generator.

Science.gov (United States)

Gao, Changwei; Liu, Xiaoming; Chen, Hai

2017-08-22

This paper focus on the power fluctuations of the virtual synchronous generator(VSG) during the transition process. An improved virtual synchronous generator(IVSG) control strategy based on feed-forward compensation is proposed. Adjustable parameter of the compensation section can be modified to achieve the goal of reducing the order of the system. It can effectively suppress the power fluctuations of the VSG in transient process. To verify the effectiveness of the proposed control strategy for distributed energy resources inverter, the simulation model is set up in MATLAB/SIMULINK platform and physical experiment platform is established. Simulation and experiment results demonstrate the effectiveness of the proposed IVSG control strategy.
Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

Science.gov (United States)

Norton, P. A., II

2015-12-01

The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.
Income and Wealth Distribution in a Neoclassical Two-Sector Heterogeneous-Households Growth Model with Elastic Labor Supply and Consumer Durable Goods

Directory of Open Access Journals (Sweden)

Wei-Bin ZHANG

2017-06-01

Full Text Available This paper proposes a two-sector two-group growth model with elastic labor supply and consumer durable goods. We study dynamics of wealth and income distribution in a competitive economy with capital accumulation as the main engine of economic growth. The model is built on the Uzawa two-sector model. It is also influenced by the neoclassical growth theory and the post-Keynesian theory of growth and distribution. We plot the motion of the economic system and determine the economic equilibrium. We carry out comparative dynamic analysis with regard to the propensity to save and improvements in human capital and technology.
A model for the distribution of watermarked digital content on mobile networks

Science.gov (United States)

Frattolillo, Franco; D'Onofrio, Salvatore

2006-10-01

Although digital watermarking can be considered one of the key technologies to implement the copyright protection of digital contents distributed on the Internet, most of the content distribution models based on watermarking protocols proposed in literature have been purposely designed for fixed networks and cannot be easily adapted to mobile networks. On the contrary, the use of mobile devices currently enables new types of services and business models, and this makes the development of new content distribution models for mobile environments strategic in the current scenario of the Internet. This paper presents and discusses a distribution model of watermarked digital contents for such environments able to achieve a trade-off between the needs of efficiency and security.
Modeling Word Burstiness Using the Dirichlet Distribution

DEFF Research Database (Denmark)

Madsen, Rasmus Elsborg; Kauchak, David; Elkan, Charles

2005-01-01

Multinomial distributions are often used to model text documents. However, they do not capture well the phenomenon that words in a document tend to appear in bursts: if a word appears once, it is more likely to appear again. In this paper, we propose the Dirichlet compound multinomial model (DCM......) as an alternative to the multinomial. The DCM model has one additional degree of freedom, which allows it to capture burstiness. We show experimentally that the DCM is substantially better than the multinomial at modeling text data, measured by perplexity. We also show using three standard document collections...
Transverse momentum distribution in the Nielsen-Olesen model

Energy Technology Data Exchange (ETDEWEB)

Sakai, S [Tokyo Univ. of Education (Japan). Dept. of Physics

1976-05-01

The power dependence in the inclusive ksub(T)-distribution in the large ksub(T)-region is derived in the extended hadron model of Nielsen and Olesen without relying upon hard scattering of hadron constituents. The ksub(T)-dependence behaves like -- -ln ksub(T) when ksub(T) is small, then it becomes exp(-..gamma..ksub(T)) in the medium ksub(T) region (ksub(T)<=1.5(GeV/c)), and further it changes to behave like (ksub(T))sup(-n(ksub(T)), when ksub(T) becomes much larger. Our ksub(T)-dependence is consistent with the experimental data. This ksub(T)-distribution is derived by the strong repulsive force between two vortex lines (identified as hadron). This repulsive force is caused by the pressure of the spontaneously broken vacuum state which is necessary to confine the vector field. Our model on the ksub(T)-distribution is very analogous to the production of massive resonances and their successive decay.
Modeling the Distribution of Rare or Cryptic Bird Species of Taiwan

Directory of Open Access Journals (Sweden)

Tsai-Yu Wu

2012-12-01

Full Text Available For the study of the macroecology and conservation of Taiwan’s birds, there was an urgent need to develop distribution models of bird species whose distribution had never before been modeled. Therefore, we here model the distributions of 27 mostly rare and cryptic breeding bird species using a statistical approach which has been shown to be especially reliable for modeling species with a low sample size of presence localities, namely the maximum entropy (Maxent modeling technique. For this purpose, we began with a dedicated attempt to collate as much high-quality distributional data as possible, assembling databases from several scientific reports, contacting individual data recorders and searching publicly accessible database, the internet and the available literature. This effort resulted in 2022 grid cells of 1 × 1 km size being associated with a presence record for one of the 27 species. These records and 10 pre-selected environmental variables were then used to model each species’ probability distribution which we show here with all grid cells below the lowest presence threshold being converted to zeros. We then in detail discuss the interpretation and applicability of these distributions, whereby we pay close attention to habitat requirements, the intactness and fragmentation of their habitat, the general detectability of the species and data reliability. This study is another one in an ongoing series of studies which highlight the usefulness of using large electronic databases and modern analytical methods to help with the monitoring and assessment of Taiwan’s bird species.
A distributed dynamic model of a monolith hydrogen membrane reactor

International Nuclear Information System (INIS)

Michelsen, Finn Are; Wilhelmsen, Øivind; Zhao, Lei; Aasen, Knut Ingvar

2013-01-01

Highlights: ► We model a rigorous distributed dynamic model for a HMR unit. ► The model includes enough complexity for steady-state and dynamic analysis. ► Simulations show that the model is non-linear within the normal operating range. ► The model is useful for studying and handling disturbances such as inlet changes and membrane leakage. - Abstract: This paper describes a distributed mechanistic dynamic model of a hydrogen membrane reformer unit (HMR) used for methane steam reforming. The model is based on a square channel monolith structure concept, where air flows adjacent to a mix of natural gas and water distributed in a chess pattern of channels. Combustion of hydrogen gives energy to the endothermic steam reforming reactions. The model is used for both steady state and dynamic analyses. It therefore needs to be computationally attractive, but still include enough complexity to study the important steady state and dynamic features of the process. Steady-state analysis of the model gives optimum for the steam to carbon and steam to oxygen ratios, where the conversion of methane is 92% and the hydrogen used as energy for the endothermic reactions is 28% at the nominal optimum. The dynamic analysis shows that non-linear control schemes may be necessary for satisfactory control performance
Simulation and optimization of logistics distribution for an engine production line

Directory of Open Access Journals (Sweden)

Lijun Song

2016-02-01

Full Text Available Purpose: In order to analyze and study the factors about Logistics distribution system, solve the problems of out of stock on the production line and improve the efficiency of the assembly line. Design/methodology/approach: Using the method of industrial engineering, put forward the optimization scheme of distribution system. The simulation model of logistics distribution system for engine assembly line was build based on Witness software. Findings: The optimization plan is efficient to improve Logistics distribution efficiency, production of assembly line efficiency and reduce the storage of production line Originality/value: Based on the study of the modeling and simulation of engine production logistics distribution system, the result reflects some influence factors about production logistics system, which has reference value to improving the efficiency of the production line.
Dynamical Analysis of SIR Epidemic Models with Distributed Delay

Directory of Open Access Journals (Sweden)

Wencai Zhao

2013-01-01

Full Text Available SIR epidemic models with distributed delay are proposed. Firstly, the dynamical behaviors of the model without vaccination are studied. Using the Jacobian matrix, the stability of the equilibrium points of the system without vaccination is analyzed. The basic reproduction number R is got. In order to study the important role of vaccination to prevent diseases, the model with distributed delay under impulsive vaccination is formulated. And the sufficient conditions of globally asymptotic stability of “infection-free” periodic solution and the permanence of the model are obtained by using Floquet’s theorem, small-amplitude perturbation skills, and comparison theorem. Lastly, numerical simulation is presented to illustrate our main conclusions that vaccination has significant effects on the dynamical behaviors of the model. The results can provide effective tactic basis for the practical infectious disease prevention.

Approximations to the Non-Isothermal Distributed Activation Energy Model for Biomass Pyrolysis Using the Rayleigh Distribution

Directory of Open Access Journals (Sweden)

Dhaundiyal Alok

2017-09-01

Full Text Available This paper deals with the influence of some parameters relevant to biomass pyrolysis on the numerical solutions of the nonisothermal nth order distributed activation energy model using the Rayleigh distribution. Investigated parameters are the integral upper limit, the frequency factor, the heating rate, the reaction order and the scale parameters of the Rayleigh distribution. The influence of these parameters has been considered for the determination of the kinetic parameters of the non-isothermal nth order Rayleigh distribution from the experimentally derived thermoanalytical data of biomass pyrolysis.
A salient region detection model combining background distribution measure for indoor robots.

Science.gov (United States)

Li, Na; Xu, Hui; Wang, Zhenhua; Sun, Lining; Chen, Guodong

2017-01-01

Vision system plays an important role in the field of indoor robot. Saliency detection methods, capturing regions that are perceived as important, are used to improve the performance of visual perception system. Most of state-of-the-art methods for saliency detection, performing outstandingly in natural images, cannot work in complicated indoor environment. Therefore, we propose a new method comprised of graph-based RGB-D segmentation, primary saliency measure, background distribution measure, and combination. Besides, region roundness is proposed to describe the compactness of a region to measure background distribution more robustly. To validate the proposed approach, eleven influential methods are compared on the DSD and ECSSD dataset. Moreover, we build a mobile robot platform for application in an actual environment, and design three different kinds of experimental constructions that are different viewpoints, illumination variations and partial occlusions. Experimental results demonstrate that our model outperforms existing methods and is useful for indoor mobile robots.
An improved method for calculating force distributions in moment-stiff timber connections

DEFF Research Database (Denmark)

Ormarsson, Sigurdur; Blond, Mette

2012-01-01

An improved method for calculating force distributions in moment-stiff metal dowel-type timber connections is presented, a method based on use of three-dimensional finite element simulations of timber connections subjected to moment action. The study that was carried out aimed at determining how...... the slip modulus varies with the angle between the direction of the dowel forces and the fibres in question, as well as how the orthotropic stiffness behaviour of the wood material affects the direction and the size of the forces. It was assumed that the force distribution generated by the moment action...
Improvement and comparison of likelihood functions for model calibration and parameter uncertainty analysis within a Markov chain Monte Carlo scheme

Science.gov (United States)

Cheng, Qin-Bo; Chen, Xi; Xu, Chong-Yu; Reinhardt-Imjela, Christian; Schulte, Achim

2014-11-01

In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash-Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box-Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions-NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)-are applied for SWAT-WB-VSA (Soil and Water Assessment Tool - Water Balance - Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach.
A GIS model-based assessment of the environmental distribution of γ-hexachlorocyclohexane in European soils and waters

International Nuclear Information System (INIS)

Vizcaino, P.; Pistocchi, A.

2010-01-01

The MAPPE GIS based multimedia model is used to produce a quantitative description of the behaviour of γ-hexachlorocyclohexane (γ-HCH) in Europe, with emphasis on continental surface waters. The model is found to reasonably reproduce γ-HCH distributions and variations along the years in atmosphere and soil; for continental surface waters, concentrations were reasonably well predicted for year 1995, when lindane was still used in agriculture, while for 2005, assuming severe restrictions in use, yields to substantial underestimation. Much better results were yielded when same mode of release as in 1995 was considered, supporting the conjecture that for γ-HCH, emission data rather that model structure and parameterization can be responsible for wrong estimation of concentrations. Future research should be directed to improve the quality of emission data. Joint interpretation of monitoring and modelling results, highlights that lindane emissions in Europe, despite the marked decreasing trend, persist beyond the provisions of existing legislation. - An spatially-explicit multimedia modelling strategy was applied to describe the historical distribution of γ-HCH in European soils and surface waters.
Various models for pion probability distributions from heavy-ion collisions

International Nuclear Information System (INIS)

Mekjian, A.Z.; Mekjian, A.Z.; Schlei, B.R.; Strottman, D.; Schlei, B.R.

1998-01-01

Various models for pion multiplicity distributions produced in relativistic heavy ion collisions are discussed. The models include a relativistic hydrodynamic model, a thermodynamic description, an emitting source pion laser model, and a description which generates a negative binomial description. The approach developed can be used to discuss other cases which will be mentioned. The pion probability distributions for these various cases are compared. Comparison of the pion laser model and Bose-Einstein condensation in a laser trap and with the thermal model are made. The thermal model and hydrodynamic model are also used to illustrate why the number of pions never diverges and why the Bose-Einstein correction effects are relatively small. The pion emission strength η of a Poisson emitter and a critical density η c are connected in a thermal model by η/n c =e -m/T <1, and this fact reduces any Bose-Einstein correction effects in the number and number fluctuation of pions. Fluctuations can be much larger than Poisson in the pion laser model and for a negative binomial description. The clan representation of the negative binomial distribution due to Van Hove and Giovannini is discussed using the present description. Applications to CERN/NA44 and CERN/NA49 data are discussed in terms of the relativistic hydrodynamic model. copyright 1998 The American Physical Society
Mechanistic species distribution modelling as a link between physiology and conservation.

Science.gov (United States)

Evans, Tyler G; Diamond, Sarah E; Kelly, Morgan W

2015-01-01

Climate change conservation planning relies heavily on correlative species distribution models that estimate future areas of occupancy based on environmental conditions encountered in present-day ranges. The approach benefits from rapid assessment of vulnerability over a large number of organisms, but can have poor predictive power when transposed to novel environments and reveals little in the way of causal mechanisms that define changes in species distribution or abundance. Having conservation planning rely largely on this single approach also increases the risk of policy failure. Mechanistic models that are parameterized with physiological information are expected to be more robust when extrapolating distributions to future environmental conditions and can identify physiological processes that set range boundaries. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance, and because this information is currently restricted to a comparatively small number of well-studied organisms, use of mechanistic modelling in the context of climate change conservation is limited. In this review, we propose that the need to develop mechanistic models that incorporate physiological data presents an opportunity for physiologists to contribute more directly to climate change conservation and advance the field of conservation physiology. We begin by describing the prevalence of species distribution modelling in climate change conservation, highlighting the benefits and drawbacks of both mechanistic and correlative approaches. Next, we emphasize the need to expand mechanistic models and discuss potential metrics of physiological performance suitable for integration into mechanistic models. We conclude by summarizing other factors, such as the need to consider demography, limiting broader application of mechanistic models in climate change conservation. Ideally, modellers, physiologists and
Model of charge-state distributions for electron cyclotron resonance ion source plasmas

Directory of Open Access Journals (Sweden)

D. H. Edgell

1999-12-01

Full Text Available A computer model for the ion charge-state distribution (CSD in an electron cyclotron resonance ion source (ECRIS plasma is presented that incorporates non-Maxwellian distribution functions, multiple atomic species, and ion confinement due to the ambipolar potential well that arises from confinement of the electron cyclotron resonance (ECR heated electrons. Atomic processes incorporated into the model include multiple ionization and multiple charge exchange with rate coefficients calculated for non-Maxwellian electron distributions. The electron distribution function is calculated using a Fokker-Planck code with an ECR heating term. This eliminates the electron temperature as an arbitrary user input. The model produces results that are a good match to CSD data from the ANL-ECRII ECRIS. Extending the model to 1D axial will also allow the model to determine the plasma and electrostatic potential profiles, further eliminating arbitrary user input to the model.
Improving Shade Modelling in a Regional River Temperature Model Using Fine-Scale LIDAR Data

Science.gov (United States)

Hannah, D. M.; Loicq, P.; Moatar, F.; Beaufort, A.; Melin, E.; Jullian, Y.

2015-12-01

Air temperature is often considered as a proxy of the stream temperature to model the distribution areas of aquatic species water temperature is not available at a regional scale. To simulate the water temperature at a regional scale (105 km²), a physically-based model using the equilibrium temperature concept and including upstream-downstream propagation of the thermal signal was developed and applied to the entire Loire basin (Beaufort et al., submitted). This model, called T-NET (Temperature-NETwork) is based on a hydrographical network topology. Computations are made hourly on 52,000 reaches which average 1.7 km long in the Loire drainage basin. The model gives a median Root Mean Square Error of 1.8°C at hourly time step on the basis of 128 water temperature stations (2008-2012). In that version of the model, tree shadings is modelled by a constant factor proportional to the vegetation cover on 10 meters sides the river reaches. According to sensitivity analysis, improving the shade representation would enhance T-NET accuracy, especially for the maximum daily temperatures, which are currently not very well modelized. This study evaluates the most efficient way (accuracy/computing time) to improve the shade model thanks to 1-m resolution LIDAR data available on tributary of the LoireRiver (317 km long and an area of 8280 km²). Two methods are tested and compared: the first one is a spatially explicit computation of the cast shadow for every LIDAR pixel. The second is based on averaged vegetation cover characteristics of buffers and reaches of variable size. Validation of the water temperature model is made against 4 temperature sensors well spread along the stream, as well as two airborne thermal infrared imageries acquired in summer 2014 and winter 2015 over a 80 km reach. The poster will present the optimal length- and crosswise scale to characterize the vegetation from LIDAR data.
Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Science.gov (United States)

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.
Yield shear stress model of magnetorheological fluids based on exponential distribution

International Nuclear Information System (INIS)

Guo, Chu-wen; Chen, Fei; Meng, Qing-rui; Dong, Zi-xin

2014-01-01

The magnetic chain model that considers the interaction between particles and the external magnetic field in a magnetorheological fluid has been widely accepted. Based on the chain model, a yield shear stress model of magnetorheological fluids was proposed by introducing the exponential distribution to describe the distribution of angles between the direction of magnetic field and the chain formed by magnetic particles. The main influencing factors were considered in the model, such as magnetic flux density, intensity of magnetic field, particle size, volume fraction of particles, the angle of magnetic chain, and so on. The effect of magnetic flux density on the yield shear stress was discussed. The yield stress of aqueous Fe 3 O 4 magnetreological fluids with volume fraction of 7.6% and 16.2% were measured by a device designed by ourselves. The results indicate that the proposed model can be used for calculation of yield shear stress with acceptable errors. - Highlights: • A yield shear stress model of magnetorheological fluids was proposed. • Use exponential distribution to describe the distribution of magnetic chain angles. • Experimental and predicted results were in good agreement for 2 types of MR
Optimal dimensioning model of water distribution systems | Gomes ...

African Journals Online (AJOL)

This study is aimed at developing a pipe-sizing model for a water distribution system. The optimal solution minimises the system's total cost, which comprises the hydraulic network capital cost, plus the capitalised cost of pumping energy. The developed model, called Lenhsnet, may also be used for economical design when ...
Natural gas distribution in Brazil - opportunities of improvement; Distribuicao de gas natural no pais - oportunidades de melhoria

Energy Technology Data Exchange (ETDEWEB)

Correa, Silvia R. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Quintella, Odair M.; Farias Filho, Jose R. de [Universidade Federal Fluminense, Niteroi, RJ (Brazil)

2005-07-01

Great are the challenges established by the Brazilian Government related to goals to be achieved for the increment of the Natural Gas participation in brazilian energetic matrix, from current 5% to 12%, up to 2010. The enlargement of the distribution infrastructure of the gas (gas-pipelines 'mesh') in Brazil is considered one of the greatest challenges for the growth of the Brazilian market of Natural Gas, accomplishment that involves elevated investments. This paper presents a model of Management System for the good organizational performance of the small Natural Gas Supplying Brazilian Companies focused on criteria of Leadership, Strategies and Plans and Results, established by the Premio TOP Empresarial and by the 'Rumo a Excelencia', held by the 'Progama Qualidade Rio' and 'Fundacao para o Premio Nacional da Qualidade', respectively. The management practices of these companies were reviewed, considering the context of the energetic Brazilian scenario, subjected to the political and operational definitions and uncertainties, the available financial resources, limited or not prioritized, and actual barriers to be surpassed by the Gas Supplying Companies in order to achieve the pre-established government goals for this segment. The implementation of the proposed simplified Model, seen as improvement opportunities for the segment of Natural Gas distribution, will lead the Gas Distribution Companies to a intermediary stage envisioning the real steps towards the excellence of the performance. (author)
A cooperative model for IS security risk management in distributed environment.

Science.gov (United States)

Feng, Nan; Zheng, Chundong

2014-01-01

Given the increasing cooperation between organizations, the flexible exchange of security information across the allied organizations is critical to effectively manage information systems (IS) security in a distributed environment. In this paper, we develop a cooperative model for IS security risk management in a distributed environment. In the proposed model, the exchange of security information among the interconnected IS under distributed environment is supported by Bayesian networks (BNs). In addition, for an organization's IS, a BN is utilized to represent its security environment and dynamically predict its security risk level, by which the security manager can select an optimal action to safeguard the firm's information resources. The actual case studied illustrates the cooperative model presented in this paper and how it can be exploited to manage the distributed IS security risk effectively.
Modeling and optimization of an electric power distribution network ...

African Journals Online (AJOL)

Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...
Mathematical modeling of current density distribution in composite cathode of solid oxide fuel cells. Paper no. IGEC-1-099

International Nuclear Information System (INIS)

Kenney, B.; Karan, K.

2005-01-01

Cathodes processes in a solid oxide fuel cell (SOFC) are thought to dominate the overall electrochemical losses. One strategy for minimizing the cathode electrochemical losses in a state-of-the-art SOFC that utilize lanthanum-strontium-manganate (LSM) electrocatalyst and yttria-stabilized-zirconia (YSZ) electrolyte is to utilize composite cathodes comprising a mixture of LSM and YSZ. Composite cathodes improve performance by extending the active reaction zone from electrolyte-electrode interface to throughout the electrode. In this study, a two-dimensional composite cathode model was developed to assess cathode performance in terms of current density distributions. The model results indicate that geometric and microstructural parameters strongly influence current density distribution. In addition electrode composition affects magnitude and distribution of current. An optimum composition for equal-sized LSM/YSZ is 40 vol% LSM and 60 vol% YSZ at 900 o C. (author)
Distributionally Robust Return-Risk Optimization Models and Their Applications

Directory of Open Access Journals (Sweden)

Li Yang

2014-01-01

Full Text Available Based on the risk control of conditional value-at-risk, distributionally robust return-risk optimization models with box constraints of random vector are proposed. They describe uncertainty in both the distribution form and moments (mean and covariance matrix of random vector. It is difficult to solve them directly. Using the conic duality theory and the minimax theorem, the models are reformulated as semidefinite programming problems, which can be solved by interior point algorithms in polynomial time. An important theoretical basis is therefore provided for applications of the models. Moreover, an application of the models to a practical example of portfolio selection is considered, and the example is evaluated using a historical data set of four stocks. Numerical results show that proposed methods are robust and the investment strategy is safe.
From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

Science.gov (United States)

Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

2016-02-01

This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the
Modified polarized geometrical attenuation model for bidirectional reflection distribution function based on random surface microfacet theory.

Science.gov (United States)

Liu, Hong; Zhu, Jingping; Wang, Kai

2015-08-24

The geometrical attenuation model given by Blinn was widely used in the geometrical optics bidirectional reflectance distribution function (BRDF) models. Blinn's geometrical attenuation model based on symmetrical V-groove assumption and ray scalar theory causes obvious inaccuracies in BRDF curves and negatives the effects of polarization. Aiming at these questions, a modified polarized geometrical attenuation model based on random surface microfacet theory is presented by combining of masking and shadowing effects and polarized effect. The p-polarized, s-polarized and unpolarized geometrical attenuation functions are given in their separate expressions and are validated with experimental data of two samples. It shows that the modified polarized geometrical attenuation function reaches better physical rationality, improves the precision of BRDF model, and widens the applications for different polarization.
Improved Shape Parameter Estimation in Pareto Distributed Clutter with Neural Networks

Directory of Open Access Journals (Sweden)

José Raúl Machado-Fernández

2016-12-01

Full Text Available The main problem faced by naval radars is the elimination of the clutter input which is a distortion signal appearing mixed with target reflections. Recently, the Pareto distribution has been related to sea clutter measurements suggesting that it may provide a better fit than other traditional distributions. The authors propose a new method for estimating the Pareto shape parameter based on artificial neural networks. The solution achieves a precise estimation of the parameter, having a low computational cost, and outperforming the classic method which uses Maximum Likelihood Estimates (MLE. The presented scheme contributes to the development of the NATE detector for Pareto clutter, which uses the knowledge of clutter statistics for improving the stability of the detection, among other applications.

The Business Cluster's Distribution e-Channels

OpenAIRE

Milan Davidovic

2011-01-01

The business cluster cooperative potential and business capability improvement are dependent on e-business implementation and business model change dynamics in cluster and his members based in new and existing distribution channels, customer relationships management and supplychain integration. In this work analyse cluster’s e-business models, e-commerce forms and distribution e-channels for three business cases: when cluster members are oriented on own business, on cooperative’s project or c...
Modified Normal Demand Distributions in (R,S)-Inventory Models

NARCIS (Netherlands)

Strijbosch, L.W.G.; Moors, J.J.A.

2003-01-01

To model demand, the normal distribution is by far the most popular; the disadvantage that it takes negative values is taken for granted.This paper proposes two modi.cations of the normal distribution, both taking non-negative values only.Safety factors and order-up-to-levels for the familiar (R,
Finessing atlas data for species distribution models

NARCIS (Netherlands)

Niamir, A.; Skidmore, A.K.; Toxopeus, A.G.; Munoz, A.R.; Real, R.

2011-01-01

Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This
State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

Science.gov (United States)

Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

2012-12-01

This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of
The importance of distribution-choice in modeling substance use data: a comparison of negative binomial, beta binomial, and zero-inflated distributions.

Science.gov (United States)

Wagner, Brandie; Riggs, Paula; Mikulich-Gilbertson, Susan

2015-01-01

It is important to correctly understand the associations among addiction to multiple drugs and between co-occurring substance use and psychiatric disorders. Substance-specific outcomes (e.g. number of days used cannabis) have distributional characteristics which range widely depending on the substance and the sample being evaluated. We recommend a four-part strategy for determining the appropriate distribution for modeling substance use data. We demonstrate this strategy by comparing the model fit and resulting inferences from applying four different distributions to model use of substances that range greatly in the prevalence and frequency of their use. Using Timeline Followback (TLFB) data from a previously-published study, we used negative binomial, beta-binomial and their zero-inflated counterparts to model proportion of days during treatment of cannabis, cigarettes, alcohol, and opioid use. The fit for each distribution was evaluated with statistical model selection criteria, visual plots and a comparison of the resulting inferences. We demonstrate the feasibility and utility of modeling each substance individually and show that no single distribution provides the best fit for all substances. Inferences regarding use of each substance and associations with important clinical variables were not consistent across models and differed by substance. Thus, the distribution chosen for modeling substance use must be carefully selected and evaluated because it may impact the resulting conclusions. Furthermore, the common procedure of aggregating use across different substances may not be ideal.
Distributional Language Learning: Mechanisms and Models of ategory Formation.

Science.gov (United States)

Aslin, Richard N; Newport, Elissa L

2014-09-01

In the past 15 years, a substantial body of evidence has confirmed that a powerful distributional learning mechanism is present in infants, children, adults and (at least to some degree) in nonhuman animals as well. The present article briefly reviews this literature and then examines some of the fundamental questions that must be addressed for any distributional learning mechanism to operate effectively within the linguistic domain. In particular, how does a naive learner determine the number of categories that are present in a corpus of linguistic input and what distributional cues enable the learner to assign individual lexical items to those categories? Contrary to the hypothesis that distributional learning and category (or rule) learning are separate mechanisms, the present article argues that these two seemingly different processes---acquiring specific structure from linguistic input and generalizing beyond that input to novel exemplars---actually represent a single mechanism. Evidence in support of this single-mechanism hypothesis comes from a series of artificial grammar-learning studies that not only demonstrate that adults can learn grammatical categories from distributional information alone, but that the specific patterning of distributional information among attested utterances in the learning corpus enables adults to generalize to novel utterances or to restrict generalization when unattested utterances are consistently absent from the learning corpus. Finally, a computational model of distributional learning that accounts for the presence or absence of generalization is reviewed and the implications of this model for linguistic-category learning are summarized.
A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Science.gov (United States)

Zinnecker, Alicia M.; Culley, Dennis E.; Aretskin-Hariton, Eliot D.

2015-01-01

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a SimulinkR library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.
Reconsideration of mass-distribution models

Directory of Open Access Journals (Sweden)

Ninković S.

2014-01-01

Full Text Available The mass-distribution model proposed by Kuzmin and Veltmann (1973 is revisited. It is subdivided into two models which have a common case. Only one of them is subject of the present study. The study is focused on the relation between the density ratio (the central one to that corresponding to the core radius and the total-mass fraction within the core radius. The latter one is an increasing function of the former one, but it cannot exceed one quarter, which takes place when the density ratio tends to infinity. Therefore, the model is extended by representing the density as a sum of two components. The extension results into possibility of having a correspondence between the infinite density ratio and 100% total-mass fraction. The number of parameters in the extended model exceeds that of the original model. Due to this, in the extended model, the correspondence between the density ratio and total-mass fraction is no longer one-to-one; several values of the total-mass fraction can correspond to the same value for the density ratio. In this way, the extended model could explain the contingency of having two, or more, groups of real stellar systems (subsystems in the diagram total-mass fraction versus density ratio. [Projekat Ministarstva nauke Republike Srbije, br. 176011: Dynamics and Kinematics of Celestial Bodies and Systems
Parton distributions and EMC ratios of the 6Li nucleus in the constituent quark exchange model

Science.gov (United States)

Modarres, M.; Hadian, A.

2017-10-01

While the constituent quark model (CQM), in which the quarks are assumed to be the complex objects, is used to calculate the parton distribution functions of the iso-scalar lithium-6 (6Li) nucleus, the u-d constituent quark distribution functions of the 6Li nucleus are evaluated from the valence quark exchange formalism (VQEF) for the A = 6 iso-scalar system. After computing the valence quark, sea quark, and gluon distribution functions in the constituent quark exchange model (CQEM, i.e., CQM +VQEF), the nucleus structure function is calculated for the 6Li nucleus at the leading order (LO) and the next-to-leading-order (NLO) levels to extract the European muon collaboration (EMC) ratio, at different hard scales, using the standard Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGALP) evolution equations. The outcomes are compared with those of our previous works and the available NMC experimental data, and various physical points are discussed. It is observed that the present EMC ratios are considerably improved compared with those of our previous works, in which only the valence quark distributions were considered to calculate the EMC ratio, and are closer to the NMC data. Finally, it is concluded that at a given appropriate hard scale, the LO approximation may be enough for calculating the nucleus EMC ratio.
Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?

Science.gov (United States)

Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Monego, Martina; Norbiato, Daniele; Ferri, Miche; Solomatine, Dimitri P.

2017-02-01

Monitoring stations have been used for decades to properly measure hydrological variables and better predict floods. To this end, methods to incorporate these observations into mathematical water models have also been developed. Besides, in recent years, the continued technological advances, in combination with the growing inclusion of citizens in participatory processes related to water resources management, have encouraged the increase of citizen science projects around the globe. In turn, this has stimulated the spread of low-cost sensors to allow citizens to participate in the collection of hydrological data in a more distributed way than the classic static physical sensors do. However, two main disadvantages of such crowdsourced data are the irregular availability and variable accuracy from sensor to sensor, which makes them challenging to use in hydrological modelling. This study aims to demonstrate that streamflow data, derived from crowdsourced water level observations, can improve flood prediction if integrated in hydrological models. Two different hydrological models, applied to four case studies, are considered. Realistic (albeit synthetic) time series are used to represent crowdsourced data in all case studies. In this study, it is found that the data accuracies have much more influence on the model results than the irregular frequencies of data availability at which the streamflow data are assimilated. This study demonstrates that data collected by citizens, characterized by being asynchronous and inaccurate, can still complement traditional networks formed by few accurate, static sensors and improve the accuracy of flood forecasts.
Estimation of watershed-level distributed forest structure metrics relevant to hydrologic modeling using LiDAR and Landsat

Science.gov (United States)

Varhola, Andrés; Coops, Nicholas C.

2013-04-01

SummaryA detailed characterization of vegetation structure is fundamental for physically-based hydrologic models to simulate various processes that determine rates of snow accumulation and ablation, evapotranspiration and water dynamics. However, major efforts focused on developing complex equations to describe hydrologic processes as a function of vegetation structure at the plot level have not been accompanied by corresponding attempts to adequately extrapolate these metrics over the wider landscape in order to parameterize fully-distributed models. Recent advances in remote sensing technologies offer alternatives to overcome these difficulties and therefore improve our capacity to monitor vegetation and hydrologic processes extensively. Airborne Laser Scanning (ALS) stands out as the most promising tool to provide detailed, 3-dimensional representations of vegetation from which a wide array of structural metrics can be estimated. On the other hand, moderate scale optical remote sensing imagery such as Landsat Thematic Mapper (TM) offers the capacity to extrapolate these metrics across the landscape by virtue of its spatial and temporal resolutions. Here we correlate ALS-derived forest cover (FC), tree height (H), leaf area index (LAI) and sky view-factor (SVF) - the four main structural parameters used by hydrologic models - with a suite of spectral indices obtained from six spectral bands of a Landsat 5 TM image. Despite numerous sources of variation that affect the relationships between 2-dimensional spectral indices and three-dimensional structural metrics, models to predict FC, H, LAI and SVF with reasonable accuracy were developed. The extrapolation of these variables across a watershed in British Columbia severely affected by insect disturbance resulted in highly-detailed 30 m spatial resolution maps and frequency distributions consistent with the natural variation ranges of each metric - a major improvement compared to traditional approaches that use
In-medium pion valence distributions in a light-front model

Energy Technology Data Exchange (ETDEWEB)

Melo, J.P.B.C. de, E-mail: joao.mello@cruzeirodosul.edu.br [Laboratório de Física Teórica e Computacional – LFTC, Universidade Cruzeiro do Sul, 01506-000 São Paulo (Brazil); Tsushima, K. [Laboratório de Física Teórica e Computacional – LFTC, Universidade Cruzeiro do Sul, 01506-000 São Paulo (Brazil); Ahmed, I. [Laboratório de Física Teórica e Computacional – LFTC, Universidade Cruzeiro do Sul, 01506-000 São Paulo (Brazil); National Center for Physics, Quaidi-i-Azam University Campus, Islamabad 45320 (Pakistan)

2017-03-10

Pion valence distributions in nuclear medium and vacuum are studied in a light-front constituent quark model. The in-medium input for studying the pion properties is calculated by the quark-meson coupling model. We find that the in-medium pion valence distribution, as well as the in-medium pion valence wave function, are substantially modified at normal nuclear matter density, due to the reduction in the pion decay constant.
The modelled raindrop size distribution of Skudai, Peninsular Malaysia, using exponential and lognormal distributions.

Science.gov (United States)

Yakubu, Mahadi Lawan; Yusop, Zulkifli; Yusof, Fadhilah

2014-01-01

This paper presents the modelled raindrop size parameters in Skudai region of the Johor Bahru, western Malaysia. Presently, there is no model to forecast the characteristics of DSD in Malaysia, and this has an underpinning implication on wet weather pollution predictions. The climate of Skudai exhibits local variability in regional scale. This study established five different parametric expressions describing the rain rate of Skudai; these models are idiosyncratic to the climate of the region. Sophisticated equipment that converts sound to a relevant raindrop diameter is often too expensive and its cost sometimes overrides its attractiveness. In this study, a physical low-cost method was used to record the DSD of the study area. The Kaplan-Meier method was used to test the aptness of the data to exponential and lognormal distributions, which were subsequently used to formulate the parameterisation of the distributions. This research abrogates the concept of exclusive occurrence of convective storm in tropical regions and presented a new insight into their concurrence appearance.
The Modelled Raindrop Size Distribution of Skudai, Peninsular Malaysia, Using Exponential and Lognormal Distributions

Science.gov (United States)

Yakubu, Mahadi Lawan; Yusop, Zulkifli; Yusof, Fadhilah

2014-01-01

This paper presents the modelled raindrop size parameters in Skudai region of the Johor Bahru, western Malaysia. Presently, there is no model to forecast the characteristics of DSD in Malaysia, and this has an underpinning implication on wet weather pollution predictions. The climate of Skudai exhibits local variability in regional scale. This study established five different parametric expressions describing the rain rate of Skudai; these models are idiosyncratic to the climate of the region. Sophisticated equipment that converts sound to a relevant raindrop diameter is often too expensive and its cost sometimes overrides its attractiveness. In this study, a physical low-cost method was used to record the DSD of the study area. The Kaplan-Meier method was used to test the aptness of the data to exponential and lognormal distributions, which were subsequently used to formulate the parameterisation of the distributions. This research abrogates the concept of exclusive occurrence of convective storm in tropical regions and presented a new insight into their concurrence appearance. PMID:25126597
Modelling the distribution of pig production and diseases in Thailand

OpenAIRE

Thanapongtharm, Weerapong

2015-01-01

This thesis, entitled “Modelling the distribution of pig production and diseases in Thailand”, presents many aspects of pig production in Thailand including the characteristics of pig farming system, distribution of pig population and pig farms, spatio-temporal distribution and risk of most important diseases in pig at present, and the suitability area for pig farming. Spatial distribution and characteristics of pig farming in Thailand were studied using time-series pig population data to des...
Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

Science.gov (United States)

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.
Application of Improved Radiation Modeling to General Circulation Models

Energy Technology Data Exchange (ETDEWEB)

Michael J Iacono

2011-04-07

This research has accomplished its primary objectives of developing accurate and efficient radiation codes, validating them with measurements and higher resolution models, and providing these advancements to the global modeling community to enhance the treatment of cloud and radiative processes in weather and climate prediction models. A critical component of this research has been the development of the longwave and shortwave broadband radiative transfer code for general circulation model (GCM) applications, RRTMG, which is based on the single-column reference code, RRTM, also developed at AER. RRTMG is a rigorously tested radiation model that retains a considerable level of accuracy relative to higher resolution models and measurements despite the performance enhancements that have made it possible to apply this radiation code successfully to global dynamical models. This model includes the radiative effects of all significant atmospheric gases, and it treats the absorption and scattering from liquid and ice clouds and aerosols. RRTMG also includes a statistical technique for representing small-scale cloud variability, such as cloud fraction and the vertical overlap of clouds, which has been shown to improve cloud radiative forcing in global models. This development approach has provided a direct link from observations to the enhanced radiative transfer provided by RRTMG for application to GCMs. Recent comparison of existing climate model radiation codes with high resolution models has documented the improved radiative forcing capability provided by RRTMG, especially at the surface, relative to other GCM radiation models. Due to its high accuracy, its connection to observations, and its computational efficiency, RRTMG has been implemented operationally in many national and international dynamical models to provide validated radiative transfer for improving weather forecasts and enhancing the prediction of global climate change.
Fast Performance Computing Model for Smart Distributed Power Systems

Directory of Open Access Journals (Sweden)

Umair Younas

2017-06-01

Full Text Available Plug-in Electric Vehicles (PEVs are becoming the more prominent solution compared to fossil fuels cars technology due to its significant role in Greenhouse Gas (GHG reduction, flexible storage, and ancillary service provision as a Distributed Generation (DG resource in Vehicle to Grid (V2G regulation mode. However, large-scale penetration of PEVs and growing demand of energy intensive Data Centers (DCs brings undesirable higher load peaks in electricity demand hence, impose supply-demand imbalance and threaten the reliability of wholesale and retail power market. In order to overcome the aforementioned challenges, the proposed research considers smart Distributed Power System (DPS comprising conventional sources, renewable energy, V2G regulation, and flexible storage energy resources. Moreover, price and incentive based Demand Response (DR programs are implemented to sustain the balance between net demand and available generating resources in the DPS. In addition, we adapted a novel strategy to implement the computational intensive jobs of the proposed DPS model including incoming load profiles, V2G regulation, battery State of Charge (SOC indication, and fast computation in decision based automated DR algorithm using Fast Performance Computing resources of DCs. In response, DPS provide economical and stable power to DCs under strict power quality constraints. Finally, the improved results are verified using case study of ISO California integrated with hybrid generation.
Mixed Platoon Flow Dispersion Model Based on Speed-Truncated Gaussian Mixture Distribution

Directory of Open Access Journals (Sweden)

Weitiao Wu

2013-01-01

Full Text Available A mixed traffic flow feature is presented on urban arterials in China due to a large amount of buses. Based on field data, a macroscopic mixed platoon flow dispersion model (MPFDM was proposed to simulate the platoon dispersion process along the road section between two adjacent intersections from the flow view. More close to field observation, truncated Gaussian mixture distribution was adopted as the speed density distribution for mixed platoon. Expectation maximum (EM algorithm was used for parameters estimation. The relationship between the arriving flow distribution at downstream intersection and the departing flow distribution at upstream intersection was investigated using the proposed model. Comparison analysis using virtual flow data was performed between the Robertson model and the MPFDM. The results confirmed the validity of the proposed model.
Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization

Science.gov (United States)

Pakyuz-Charrier, Evren; Lindsay, Mark; Ogarko, Vitaliy; Giraud, Jeremie; Jessell, Mark

2018-04-01

Three-dimensional (3-D) geological structural modeling aims to determine geological information in a 3-D space using structural data (foliations and interfaces) and topological rules as inputs. This is necessary in any project in which the properties of the subsurface matters; they express our understanding of geometries in depth. For that reason, 3-D geological models have a wide range of practical applications including but not restricted to civil engineering, the oil and gas industry, the mining industry, and water management. These models, however, are fraught with uncertainties originating from the inherent flaws of the modeling engines (working hypotheses, interpolator's parameterization) and the inherent lack of knowledge in areas where there are no observations combined with input uncertainty (observational, conceptual and technical errors). Because 3-D geological models are often used for impactful decision-making it is critical that all 3-D geological models provide accurate estimates of uncertainty. This paper's focus is set on the effect of structural input data measurement uncertainty propagation in implicit 3-D geological modeling. This aim is achieved using Monte Carlo simulation for uncertainty estimation (MCUE), a stochastic method which samples from predefined disturbance probability distributions that represent the uncertainty of the original input data set. MCUE is used to produce hundreds to thousands of altered unique data sets. The altered data sets are used as inputs to produce a range of plausible 3-D models. The plausible models are then combined into a single probabilistic model as a means to propagate uncertainty from the input data to the final model. In this paper, several improved methods for MCUE are proposed. The methods pertain to distribution selection for input uncertainty, sample analysis and statistical consistency of the sampled distribution. Pole vector sampling is proposed as a more rigorous alternative than dip vector

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