WorldWideScience

Sample records for waste predictive modeling

  1. Ship waste quantities prediction model for the port of Belgrade

    Directory of Open Access Journals (Sweden)

    VLADANKA PRESBURGER ULNIKOVIĆ

    2011-06-01

    Full Text Available This study focuses on the issues related to the waste management in river ports in general and especially in the port of Belgrade. Data on solid waste, waste oils, oily waters, gray water and black water have been collected for a period of five years. The methodology of data collection is presented. Trends of data were analyzed and the regression model was used to predict the waste quantities in the Belgrade port. This data could be utilized as a basis for the calculation of the equipment capacity for waste selective collection, treatment and storage. The results presented in this study establish the need for an orga¬nized management system for this type of waste which can be achieved either by constructing and providing new specialized terminal or by providing mobile floating facilities and other plants in the Port of Belgrade for these kinds of ser¬vices. In addition to the above, the legislative and organizational strategy of waste management has been explored to complete the study because the im¬pact of good waste management on environment and prevention of environ¬mental accidents would be highly beneficial. This study demonstrated that ad¬dressing these issues should be considered at international as well as national level.

  2. A Multistep Chaotic Model for Municipal Solid Waste Generation Prediction.

    Science.gov (United States)

    Song, Jingwei; He, Jiaying

    2014-08-01

    In this study, a univariate local chaotic model is proposed to make one-step and multistep forecasts for daily municipal solid waste (MSW) generation in Seattle, Washington. For MSW generation prediction with long history data, this forecasting model was created based on a nonlinear dynamic method called phase-space reconstruction. Compared with other nonlinear predictive models, such as artificial neural network (ANN) and partial least square-support vector machine (PLS-SVM), and a commonly used linear seasonal autoregressive integrated moving average (sARIMA) model, this method has demonstrated better prediction accuracy from 1-step ahead prediction to 14-step ahead prediction assessed by both mean absolute percentage error (MAPE) and root mean square error (RMSE). Max error, MAPE, and RMSE show that chaotic models were more reliable than the other three models. As chaotic models do not involve random walk, their performance does not vary while ANN and PLS-SVM make different forecasts in each trial. Moreover, this chaotic model was less time consuming than ANN and PLS-SVM models.

  3. Developing models for the prediction of hospital healthcare waste generation rate.

    Science.gov (United States)

    Tesfahun, Esubalew; Kumie, Abera; Beyene, Abebe

    2016-01-01

    An increase in the number of health institutions, along with frequent use of disposable medical products, has contributed to the increase of healthcare waste generation rate. For proper handling of healthcare waste, it is crucial to predict the amount of waste generation beforehand. Predictive models can help to optimise healthcare waste management systems, set guidelines and evaluate the prevailing strategies for healthcare waste handling and disposal. However, there is no mathematical model developed for Ethiopian hospitals to predict healthcare waste generation rate. Therefore, the objective of this research was to develop models for the prediction of a healthcare waste generation rate. A longitudinal study design was used to generate long-term data on solid healthcare waste composition, generation rate and develop predictive models. The results revealed that the healthcare waste generation rate has a strong linear correlation with the number of inpatients (R(2) = 0.965), and a weak one with the number of outpatients (R(2) = 0.424). Statistical analysis was carried out to develop models for the prediction of the quantity of waste generated at each hospital (public, teaching and private). In these models, the number of inpatients and outpatients were revealed to be significant factors on the quantity of waste generated. The influence of the number of inpatients and outpatients treated varies at different hospitals. Therefore, different models were developed based on the types of hospitals.

  4. Prediction of the amount of urban waste solids by applying a gray theoretical model

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Urban waste solids are now becoming one of the most crucial environmental problems. There are several different kinds of technologies normally used for waste solids disposal, among which landfill is more favorable in China than others, especially for urban waste solids. Most of the design works up to now are based on a roughly estimation of the amount of urban waste solids without any theoretical support, which lead to a series problems. To meet the basic information requirements for the design work, the amount of the urban waste solids was predicted in this research by applying the gray theoretical model GM (1,1) through non-linear differential equation simulation. The model parameters were estimated with the least square method (LSM) by running a certain MATALAB program, and the hypothesis test results show that the residual between the prediction value and the actual value approximately comply with the normal distribution , and the probability of the residual within the range (-0.17, 0.19) is more than 95%, which indicate obviously that the model can be well used for the prediction of the amount of waste solids and those had been already testified by the latest two years data about the urban waste solids from Loudi City of China. With this model, the predicted amount of the waste solids produced in Loudi City in the next 30 years is 8049000 ton in total.

  5. Model predictive control of a waste heat recovery system for automotive diesel engines

    NARCIS (Netherlands)

    Feru, E.; Willems, F.; De Jager, B.; Steinbuch, M.

    2014-01-01

    In this paper, a switching Model Predictive Control strategy is designed for an automotive Waste Heat Recovery system with two parallel evaporators. The objective is to maximize Waste Heat Recovery system output power, while satisfying safe operation under highly dynamic disturbances from the engine

  6. Patterns of waste generation: A gradient boosting model for short-term waste prediction in New York City.

    Science.gov (United States)

    Johnson, Nicholas E; Ianiuk, Olga; Cazap, Daniel; Liu, Linglan; Starobin, Daniel; Dobler, Gregory; Ghandehari, Masoud

    2017-04-01

    Historical municipal solid waste (MSW) collection data supplied by the New York City Department of Sanitation (DSNY) was used in conjunction with other datasets related to New York City to forecast municipal solid waste generation across the city. Spatiotemporal tonnage data from the DSNY was combined with external data sets, including the Longitudinal Employer Household Dynamics data, the American Community Survey, the New York City Department of Finance's Primary Land Use and Tax Lot Output data, and historical weather data to build a Gradient Boosting Regression Model. The model was trained on historical data from 2005 to 2011 and validation was performed both temporally and spatially. With this model, we are able to accurately (R2>0.88) forecast weekly MSW generation tonnages for each of the 232 geographic sections in NYC across three waste streams of refuse, paper and metal/glass/plastic. Importantly, the model identifies regularity of urban waste generation and is also able to capture very short timescale fluctuations associated to holidays, special events, seasonal variations, and weather related events. This research shows New York City's waste generation trends and the importance of comprehensive data collection (especially weather patterns) in order to accurately predict waste generation. Copyright © 2017. Published by Elsevier Ltd.

  7. Model Predictive Control of Offshore Power Stations With Waste Heat Recovery

    DEFF Research Database (Denmark)

    Pierobon, Leonardo; Chan, Richard; Li, Xiangan;

    2016-01-01

    The implementation of waste heat recovery units on oil and gas offshore platforms demands advances in both design methods and control systems. Model-based control algorithms can play an important role in the operation of offshore power stations. A novel regulator based on a linear model predictive...

  8. Corrosion models for predictions of performance of high-level radioactive-waste containers

    Energy Technology Data Exchange (ETDEWEB)

    Farmer, J.C.; McCright, R.D. [Lawrence Livermore National Lab., CA (United States); Gdowski, G.E. [KMI Energy Services, Livermore, CA (United States)

    1991-11-01

    The present plan for disposal of high-level radioactive waste in the US is to seal it in containers before emplacement in a geologic repository. A proposed site at Yucca Mountain, Nevada, is being evaluated for its suitability as a geologic repository. The containers will probably be made of either an austenitic or a copper-based alloy. Models of alloy degradation are being used to predict the long-term performance of the containers under repository conditions. The models are of uniform oxidation and corrosion, localized corrosion, and stress corrosion cracking, and are applicable to worst-case scenarios of container degradation. This paper reviews several of the models.

  9. Predicting Mineral N Release during Decomposition of Organic Wastes in Soil by Use of the SOILN_NO Model

    Directory of Open Access Journals (Sweden)

    Trine A. Sogn

    2011-01-01

    Full Text Available In order to predict the mineral N release associated with the use of organic waste as fertilizer in agricultural plant production, the adequacy of the SOILN_NO model has been evaluated. The original thought was that the model calibrated to data from simple incubation experiments could predict the mineral N release from organic waste products used as N fertilizer on agricultural land. First, the model was calibrated to mineral N data achieved in a laboratory experiment where different organic wastes were added to soil and incubated at 15°C for 8 weeks. Secondly, the calibrated model was tested by use of NO3 − leaching data from soil columns with barley growing in 4 different soil types, added organic waste and exposed to natural climatic conditions during three growing seasons. The SOILN_NO model reproduced relatively well the NO3 − leaching from some of the soils included in the outdoor experiment, but failed to reproduce others. Use of the calibrated model often induced underestimation of the observed NO3 − leaching. To achieve a satisfactory simulation of the NO3 − leaching, recalibration of the model had to be carried out. Thus, SOILN_NO calibrated to data from simple incubation experiments in the laboratory could not directly be used as a tool to predict the N-leaching following organic waste application in more natural agronomic plant production systems. The results emphasised the need for site- and system-specific data for model calibration before using a model for predictive purposes related to fertilizer N value of organic wastes applied to agricultural land.

  10. Approach to first principles model prediction of measured WIPP (Waste Isolation Pilot Plant) in-situ room closure in salt

    Energy Technology Data Exchange (ETDEWEB)

    Munson, D.E.; Fossum, A.F.; Senseny, P.E. (Sandia National Labs., Albuquerque, NM (USA))

    1990-01-01

    The discrepancies between predicted and measured Waste Isolation Pilot Plant (WIPP) in-situ Room D closures are markedly reduced through the use of a Tresca flow potential, an improved small strain constitutive model, an improved set of material parameters, and a modified stratigraphy. (author).

  11. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well.

  12. Development of a hybrid model to predict construction and demolition waste: China as a case study.

    Science.gov (United States)

    Song, Yiliao; Wang, Yong; Liu, Feng; Zhang, Yixin

    2017-01-01

    Construction and demolition waste (C&DW) is currently a worldwide issue, and the situation is the worst in China due to a rapid increase in the construction industry and the short life span of China's buildings. To create an opportunity out of this problem, comprehensive prevention measures and effective management strategies are urgently needed. One major gap in the literature of waste management is a lack of estimations on future C&DW generation. Therefore, this paper presents a forecasting procedure for C&DW in China that can forecast the quantity of each component in such waste. The proposed approach is based on a GM-SVR model that improves the forecasting effectiveness of the gray model (GM), which is achieved by adjusting the residual series by a support vector regression (SVR) method and a transition matrix that aims to estimate the discharge of each component in the C&DW. Through the proposed method, future C&DW volume are listed and analyzed containing their potential components and distribution in different provinces in China. Besides, model testing process provides mathematical evidence to validate the proposed model is an effective way to give future information of C&DW for policy makers.

  13. Progress toward bridging from atomistic to continuum modeling to predict nuclear waste glass dissolution.

    Energy Technology Data Exchange (ETDEWEB)

    Zapol, Peter (Argonne National Laboratory, Argonne, IL); Bourg, Ian (Lawrence Berkeley National Laboratories, Berkeley, CA); Criscenti, Louise Jacqueline; Steefel, Carl I. (Lawrence Berkeley National Laboratories, Berkeley, CA); Schultz, Peter Andrew

    2011-10-01

    This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers, classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.

  14. Prediction of stress-strain state of municipal solid waste with application of soft soil creep model

    Directory of Open Access Journals (Sweden)

    Ofrikhter Vadim Grigor'evich

    Full Text Available The deformation of municipal solid waste is a complex process caused by the nature of MSW, the properties of which differ from the properties of common soils. The mass of municipal solid waste shows the mixed behaviour partially similar to granular soils, and partially - to cohesive. So, one of mechanical characteristics of MSW is the cohesion typical to cohesive soils, but at the same time the filtration coefficient of MSW has an order of 1 m/day that is characteristic for granular soils. It has been established that MSW massif can be simulated like the soil reinforced by randomly oriented fibers. Today a significant amount of the verified and well proved software products are available for numerical modelling of soils. The majority of them use finite element method (FEM. The soft soil creep model (SSC-model seems to be the most suitable for modelling of municipal solid waste, as it allows estimating the development of settlements in time with separation of primary and secondary consolidation. Unlike the soft soil, one of the factors of secondary consolidation of MSW is biological degradation, the influence of which is possible to consider at the definition of the modified parameters essential for soft soil model. Application of soft soil creep model allows carrying out the calculation of stress-strain state of waste from the beginning of landfill filling up to any moment of time both during the period of operation and in postclosure period. The comparative calculation presented in the paper is executed in Plaxis software using the soft-soil creep model in contrast to the calculation using the composite model of MSW. All the characteristics for SSC-model were derived from the composite model. The comparative results demonstrate the advantage of SSC-model for prediction of the development of MSW stress-strain state. As far as after the completion of the biodegradation processes MSW behaviour is similar to cohesion-like soils, the demonstrated

  15. Integrated model for predicting the fate of organics in waste-water treatment plants

    Energy Technology Data Exchange (ETDEWEB)

    Govind, R.; Lai, L.; Dobbs, R.

    1991-01-01

    An integrated Fate Model has been developed for predicting the fate of organics in a wastewater treatment plant. The Fate Model has been validated using experimental data from a pilot-scale facility. The biodegradation kinetic constants for some compounds in the Fate Model were estimated using the group contribution approach. The Fate Model has been compared with other existing models in the literature. Potential applications of the Fate Model include assessment of volatile organic compound (VOC) emissions from a wastewater treatment plant, evaluate pretreatment requirements prior to discharge to the sewer system, predict concentrations of toxic compounds on sludges, and provide a general framework for estimating the removal of toxic compounds during activated sludge treatment.

  16. New mechanistically based model for predicting reduction of biosolids waste by ozonation of return activated sludge.

    Science.gov (United States)

    Isazadeh, Siavash; Feng, Min; Urbina Rivas, Luis Enrique; Frigon, Dominic

    2014-04-15

    Two pilot-scale activated sludge reactors were operated for 98 days to provide the necessary data to develop and validate a new mathematical model predicting the reduction of biosolids production by ozonation of the return activated sludge (RAS). Three ozone doses were tested during the study. In addition to the pilot-scale study, laboratory-scale experiments were conducted with mixed liquor suspended solids and with pure cultures to parameterize the biomass inactivation process during exposure to ozone. The experiments revealed that biomass inactivation occurred even at the lowest doses, but that it was not associated with extensive COD solubilization. For validation, the model was used to simulate the temporal dynamics of the pilot-scale operational data. Increasing the description accuracy of the inactivation process improved the precision of the model in predicting the operational data.

  17. Predictive Models for the Determination of Pitting Corrosion Versus Inhibitor Concentrations and Temperature for Radioactive Sludge in Carbon Steel Waste Tanks

    Energy Technology Data Exchange (ETDEWEB)

    Mickalonis, J.I.

    1998-10-06

    Statistical models have been developed to predict the occurrence of pitting corrosion in carbon steel waste storage tanks exposed to radioactive nuclear waste. The levels of nitrite concentrations necessary to inhibit pitting at various temperatures and nitrate concentrations were experimentally determined via electrochemical polarization and coupon immersion corrosion tests. Models for the pitting behavior were developed based on various statistical analyses of the experimental data. Feed-forward Artificial Neural Network (ANN) models, trained using the Back-Propagation of Error Algorithm, more accurately predicted conditions at which pitting occurred than the logistic regression models developed using the same data.

  18. Predicting the Lifetimes of Nuclear Waste Containers

    Science.gov (United States)

    King, Fraser

    2014-03-01

    As for many aspects of the disposal of nuclear waste, the greatest challenge we have in the study of container materials is the prediction of the long-term performance over periods of tens to hundreds of thousands of years. Various methods have been used for predicting the lifetime of containers for the disposal of high-level waste or spent fuel in deep geological repositories. Both mechanical and corrosion-related failure mechanisms need to be considered, although until recently the interactions of mechanical and corrosion degradation modes have not been considered in detail. Failure from mechanical degradation modes has tended to be treated through suitable container design. In comparison, the inevitable loss of container integrity due to corrosion has been treated by developing specific corrosion models. The most important aspect, however, is to be able to justify the long-term predictions by demonstrating a mechanistic understanding of the various degradation modes.

  19. Prediction models of long-term leaching behavior and leaching mechanism of glass components and surrogated nuclides in radioactive vitrified waste forms

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Y. C.; Lee, K. S. [Department of Industrial Environment and Health, Yonsei University, Wonju (Korea, Republic of); Kim, I. T.; Kim, H. T.; Kim, J. H. [Korea Atomic Energy Research Institute (KAERI), Taejon (Korea, Republic of)

    1999-07-01

    Melting solidification is considered to be a perspective technology for stabilizing incineration ash remaining after incineration of combustible radioactive waste since it has the advantage of improving the physicochemical properties of waste forms. Final waste forms should be characterized to determine the degree to which they fulfills the acceptance criteria of the disposal facility. Chemical durability (leaching resistance) is known to be the most important factor in the assessment of waste forms. In this study, vitrified waste forms are manufactured and characterized. Feed materials consist of simulated radioactive incineration ash and base-glass with different mixing ratios. To assess the chemical durability of vitrified waste forms, the International Standard Organization (ISO) leach test has been conducted at 70 degree C with deionized distilled water as a leachant for 820 days, and the concentrations of glass components and surrogates in the leachates are then analyzed. Two models for predicting long-term leaching behavior of glass components and radionuclides in a glass form are applied to the leached data after 820 days. The model including a fitted parameter from the longer experimental data shows more accuracy, however, the model with shorter leaching test results offers the advantage of being able to predict the long-term behavior from the short-term experimental data. The leaching mechanisms of surrogates and glass components were also investigated by using two semi-empirical kinetic models and were found to be dissolution with diffusion. (author)

  20. Validation of predictive models for geologic disposal of radioactive waste via natural analogs

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, J.J.; Smith, C.F.

    1981-03-01

    The incorporation of toxic or hazardous material in the earth's crust is a phenomenon not unique to radioactive waste burial. Useful insights on the environmental transport and effects of underground toxic or radioactive material can be derived from comparative analysis against natural (mineral) analogs. This paper includes a discussion of the background and rationale for the analog approach, a descripton of several variations of the approach, and some sample applications to illustrate the concept, focusing on Radium-226 and Iodine-129 as specific case studies.

  1. A logistic model for the prediction of the influence of water on the solid waste methanization in landfills.

    Science.gov (United States)

    Pommier, S; Chenu, D; Quintard, M; Lefebvre, X

    2007-06-15

    This article deals with the impact of water content of solid waste on biogas production kinetics in landfills. This impact has been proved in the laboratory thanks to anaerobic biodegradation experiments on paper/cardboard waste samples. A strong dependence with the moisture level was observed for both kinetic rates and maximum methane production. In this article, a logistic model is proposed to simulate the biogas production rate. It is chosen as simple as possible in order to allow for a correct identification of the model parameters given the experimental data available. The moisture dependency is introduced through a linear weighing of the biomass specific growth rate and of the amount of accessible organic substrate. It is directly linked to physical properties of the waste: the holding capacity and the minimal moisture level allowing the presence of free water.

  2. Prototyping the Use of Dispersion Models to Predict Ground Concentrations During Burning of Deployed Military Waste

    Science.gov (United States)

    2012-03-22

    and that approximately 40% of the pollutant was deposited in the 10 by 10 grid ( Schaum et al., 2010). In the late 90’s EPA and American...Sawyer, P. (2007). Atmospheric dispersion model validation in low wind conditions. National Security Technologies, LLC. Schaum , J., Cohen, M., Perry, S

  3. Prediction of dissolved actinide concentrations in concentrated electrolyte solutions: a conceptual model and model results for the Waste Isolation Pilot Plant (WIPP)

    Energy Technology Data Exchange (ETDEWEB)

    Novak, C.F.; Moore, R.C. [Sandia National Labs., Albuquerque, NM (United States); Bynum, R.V. [Science Applications International Corp., Albuquerque, NM (United States)

    1996-10-25

    The conceptual model for WIPP dissolved concentrations is a description of the complex natural and artificial chemical conditions expected to influence dissolved actinide concentrations in the repository. By a set of physical and chemical assumptions regarding chemical kinetics, sorption substrates, and waste-brine interactions, the system was simplified to be amenable to mathematical description. The analysis indicated that an equilibrium thermodynamic model for describing actinide solubilities in brines would be tractable and scientifically supportable. This paper summarizes the conceptualization and modeling approach and the computational results as used in the WIPP application for certification of compliance with relevant regulations for nuclear waste repositories. The WIPP site contains complex natural brines ranging from sea water to 10x more concentrated than sea water. Data bases for predicting solubility of Am(III) (as well as Pu(III) and Nd(III)), Th(IV), and Np(V) in these brines under potential repository conditions have been developed, focusing on chemical interactions with Na, K, Mg, Cl, SO{sub 4}, and CO{sub 3} ions, and the organic acid anions acetate, citrate, EDTA, and oxalate. The laboratory and modeling effort augmented the Harvie et al. parameterization of the Pitzer activity coefficient model so that it could be applied to the actinides and oxidation states important to the WIPP system.

  4. Long-term behaviour of concrete: development of operational model to predict the evolution of its containment performance. Application to cemented waste packages

    Energy Technology Data Exchange (ETDEWEB)

    Peycelon, H.; Le Bescop, P.; Richet, C. [CEA Saclay, Dept. de Physico-Chimie, DPC, 91 - Gif-sur-Yvette (France); Adenot, F. [CEA Cadarache, 13 - Saint Paul lez Durance (France). Dept. d' Entreposage et de Stockage des Dechets; Blanc, V. [Cogema, 78 - Saint Quentin en Yvelines (France)

    2001-07-01

    In order to describe the main phenomena during different stages of cement waste packages life-time and to predict the long-term behaviour (containment performance) of concrete, coupled experiments and modelling studies are achieved. With respect to logical methodology, improvement of these studies is accomplished. Degradation of concrete in low mineralized, carbonated and sulfated water lead to an evolution of chemical characteristics (dissolution/precipitation of solid phases) and of transport properties which must be included or coupled in retention/transport modelling of radio nuclides to predict containment performance. (author)

  5. Usefulness of TAO model to predict and manage the transformation in soil of carbon and nitrogen forms from West-Africa urban solid wastes.

    Science.gov (United States)

    Kaboré, W T; Pansu, M; Hien, E; Houot, S; Zombré, N P; Masse, D

    2011-01-01

    The TAO model of Transformation of Added Organic materials (AOM) calibrated on AOMs and substrates of temperate areas was used to assess the transformations in soil of carbon and nitrogen forms of AOMs: raw materials, selected mixtures and composts from Ouagadougou urban wastes. AOMs were studied in terms of chemical and biochemical contents and for their C and N mineralization during incubations in a typical Ferric Lixisol of the sub-urban agriculture of Ouagadougou. The TAO model was used to predict the transformations of C (very labile, resistant and stable organic C) and N (very labile, resistant and stable organic N, produced and immobilized inorganic N) forms driven by AOM biochemical data. Without any change in calibration formulae, TAO predicted accurately the C transformations and inorganic N production of most of the tested AOMs, with a tendency to slightly overestimate C mineralization of previously well-composted materials and re-mineralization of immobilized N. Complementary adjustments using more complete data from laboratory experiments are suggested, but the model agrees with other data collected in the field and appears as a promising tool to optimise the management of urban wastes in the tropical area as well as for agro industrial organic fertilizers of the temperate zone. This application suggests ways to improve the management of urban wastes aiming to optimize agricultural yields, system sustainability and C sequestration in soil. Copyright © 2010 Elsevier Ltd. All rights reserved.

  6. Halomonas desiderata as a bacterial model to predict the possible biological nitrate reduction in concrete cells of nuclear waste disposals.

    Science.gov (United States)

    Alquier, Marjorie; Kassim, Caroline; Bertron, Alexandra; Sablayrolles, Caroline; Rafrafi, Yan; Albrecht, Achim; Erable, Benjamin

    2014-01-01

    After closure of a waste disposal cell in a repository for radioactive waste, resaturation is likely to cause the release of soluble species contained in cement and bituminous matrices, such as ionic species (nitrates, sulfates, calcium and alkaline ions, etc.), organic matter (mainly organic acids), or gases (from steel containers and reinforced concrete structures as well as from radiolysis within the waste packages). However, in the presence of nitrates in the near-field of waste, the waste cell can initiate oxidative conditions leading to enhanced mobility of redox-sensitive radionuclides (RN). In biotic conditions and in the presence of organic matter and/or hydrogen as electron donors, nitrates may be microbiologically reduced, allowing a return to reducing conditions that promote the safety of storage. Our work aims to analyze the possible microbial reactivity of nitrates at the bitumen - concrete interface in conditions as close as possible to radioactive waste storage conditions in order (i) to evaluate the nitrate reaction kinetics; (ii) to identify the by-products (NO2(-), NH4(+), N2, N2O, etc.); and (iii) to discriminate between the roles of planktonic bacteria and those adhering as a biofilm structure in the denitrifying activity. Leaching experiments on solid matrices (bitumen and cement pastes) were first implemented to define the physicochemical conditions that microorganisms are likely to meet at the bitumen-concrete interface, e.g. highly alkaline pH conditions (10 < pH < 11) imposed by the cement matrix. The screening of a range of anaerobic denitrifying bacterial strains led us to select Halomonas desiderata as a model bacterium capable of catalyzing the reaction of nitrate reduction in these particular conditions of pH. The denitrifying activity of H. desiderata was quantified in a batch bioreactor in the presence of solid matrices and/or leachate from bitumen and cement matrices. Denitrification was relatively fast in the presence of cement

  7. Similar evolution in delta 13CH4 and model-predicted relative rate of aceticlastic methanogenesis during mesophilic methanization of municipal solid wastes.

    Science.gov (United States)

    Vavilin, V A; Qu, X; Qu, X; Mazéas, L; Lemunier, M; Duquennoi, C; Mouchel, J M; He, P; Bouchez, T

    2009-01-01

    Similar evolution was obtained for the stable carbon isotope signatures delta (13)CH(4) and the model-predicted relative rate of aceticlastic methanogenesis during mesophilic methanization of municipal solid wastes. In batch incubations, the importance of aceticlastic and hydrogenotrophic methanogenesis changes in time. Initially, hydrogenotrophic methanogenesis dominated, but increasing population of Methanosarcina sp. enhances aceticlastic methanogenesis. Later, hydrogenotrophic methanogenesis intensified again. A mathematical model was developed to evaluate the relative contribution of hydrogenotrophic and aceticlastic pathways of methane generation during mesophilic batch anaerobic biodegradation of the French and the Chinese Municipal Solid Wastes (FMSW and CMSW). Taking into account molecular biology analysis reported earlier three groups of methanogens including strictly hydrogenotrophic methanogens, strictly aceticlastic methanogens (Methanosaeta sp.) and Methanosarcina sp., consuming both acetate and H(2)/H(2)CO(3) were considered in the model. The total organic and inorganic carbon concentrations, methane production volume, methane and carbon dioxide partial pressures values were used for the model calibration and validation. Methane isotopic composition (delta (13)CH(4)) evolution during the incubations was used to independently validate the model results. The model demonstrated that only the putrescible solid waste was totally converted to methane.

  8. A MODEL FOR PREDICTING FISSION PRODUCT ACTIVITIES IN REACTOR COOLANT: APPLICATION OF MODEL FOR ESTIMATING I-129 LEVELS IN RADIOACTIVE WASTE

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, B.J.; Husain, A.

    2003-02-27

    A general model was developed to estimate the activities of fission products in reactor coolant and hence to predict a value for the I-129/Cs-137 scaling factor; the latter can be applied along with measured Cs-137 activities to estimate I-129 levels in reactor waste. The model accounts for fission product release from both defective fuel rods and uranium contamination present on in-core reactor surfaces. For simplicity, only the key release mechanisms were modeled. A mass balance, considering the two fuel source terms and a loss term due to coolant cleanup was solved to estimate fission product activity in the primary heat transport system coolant. Steady state assumptions were made to solve for the activity of shortlived fission products. Solutions for long-lived fission products are time-dependent. Data for short-lived radioiodines I-131, I-132, I-133, I-134 and I-135 were analyzed to estimate model parameters for I-129. The estimated parameter values were then used to determine I-1 29 coolant activities. Because of the chemical affinity between iodine and cesium, estimates of Cs-137 coolant concentrations were also based on parameter values similar to those for the radioiodines; this assumption was tested by comparing measured and predicted Cs-137 coolant concentrations. Application of the derived model to Douglas Point and Darlington Nuclear Generating Station plant data yielded estimates for I-129/I-131 and I-129/Cs-137 which are consistent with values reported for pressurized water reactors (PWRs) and boiling water reactors (BWRs). The estimated magnitude for the I-129/Cs-137 ratio was 10-8 - 10-7.

  9. Preliminary ECLSS waste water model

    Science.gov (United States)

    Carter, Donald L.; Holder, Donald W., Jr.; Alexander, Kevin; Shaw, R. G.; Hayase, John K.

    1991-01-01

    A preliminary waste water model for input to the Space Station Freedom (SSF) Environmental Control and Life Support System (ECLSS) Water Processor (WP) has been generated for design purposes. Data have been compiled from various ECLSS tests and flight sample analyses. A discussion of the characterization of the waste streams comprising the model is presented, along with a discussion of the waste water model and the rationale for the inclusion of contaminants in their respective concentrations. The major objective is to establish a methodology for the development of a waste water model and to present the current state of that model.

  10. Preliminary ECLSS waste water model

    Science.gov (United States)

    Carter, Donald L.; Holder, Donald W., Jr.; Alexander, Kevin; Shaw, R. G.; Hayase, John K.

    1991-01-01

    A preliminary waste water model for input to the Space Station Freedom (SSF) Environmental Control and Life Support System (ECLSS) Water Processor (WP) has been generated for design purposes. Data have been compiled from various ECLSS tests and flight sample analyses. A discussion of the characterization of the waste streams comprising the model is presented, along with a discussion of the waste water model and the rationale for the inclusion of contaminants in their respective concentrations. The major objective is to establish a methodology for the development of a waste water model and to present the current state of that model.

  11. Approach to first principles model prediction of measured WIPP (Waste Isolation Pilot Plant) in situ room closure in salt

    Energy Technology Data Exchange (ETDEWEB)

    Munson, D.E.; Fossum, A.F.; Senseny, P.E. (Sandia National Labs., Albuquerque, NM (USA); Southwest Research Inst., San Antonio, TX (USA); RE/SPEC, Inc., Rapid City, SD (USA))

    1989-08-01

    The discrepancies between predicted and measured WIPP in situ Room D closures are markedly reduced through the use of a Tresca flow potential, an improved small strain constitutive model, an improved set of material parameters, and a modified stratigraphy. 12 refs., 5 figs., 1 tab.

  12. Approach to first principles model prediction of measured WIPP (Waste Isolation Pilot Plant) in situ room closure in salt

    Energy Technology Data Exchange (ETDEWEB)

    Munson, D.E.; Fossum, A.F.; Senseny, P.E.

    1989-01-01

    The discrepancies between predicted and measured WIPP in situ Room D closures are markedly reduced through the use of a Tresca flow potential, an improved small strain constitutive model, an improved set of material parameters, and a modified stratigraphy. 17 refs., 8 figs., 1 tab.

  13. Reliable predictions of waste performance in a geologic repository

    Energy Technology Data Exchange (ETDEWEB)

    Pigford, T.H.; Chambre, P.L.

    1985-08-01

    Establishing reliable estimates of long-term performance of a waste repository requires emphasis upon valid theories to predict performance. Predicting rates that radionuclides are released from waste packages cannot rest upon empirical extrapolations of laboratory leach data. Reliable predictions can be based on simple bounding theoretical models, such as solubility-limited bulk-flow, if the assumed parameters are reliably known or defensibly conservative. Wherever possible, performance analysis should proceed beyond simple bounding calculations to obtain more realistic - and usually more favorable - estimates of expected performance. Desire for greater realism must be balanced against increasing uncertainties in prediction and loss of reliability. Theoretical predictions of release rate based on mass-transfer analysis are bounding and the theory can be verified. Postulated repository analogues to simulate laboratory leach experiments introduce arbitrary and fictitious repository parameters and are shown not to agree with well-established theory. 34 refs., 3 figs., 2 tabs.

  14. Interim Report on Development of a Model to Predict Dissolution Behavior of the Titanate Waste Form in a Repository

    Energy Technology Data Exchange (ETDEWEB)

    Bourcier, W.L.

    1999-08-16

    Dissolution testing performed to date on a titanate waste form under development for plutonium immobilization reveals the following: (1) The wasteform is very durable. Many of the test results have shown the dissolution rate to be below detection or less than background levels of the constituent elements; (2) elemental release is non-stoichiometric with Pu, U, Ca, and Gd released faster than Ti and Hf at most pH conditions; (3) dissolution rates measured in flow-through tests sometimes show a continuous decrease with time in tests of up to two years duration; (4) attempts to model the dissolution as a transport-controlled process with diffusion through a leached layer as the rate limiting mechanism show reasonable agreement at low pH conditions but poor agreement at neutral to alkaline pHs. Based on present uncertainties in our understanding of rate control, we have provided conservative estimates of radionuclide release rates based on the fastest observed release rates measured in short-term tests. These dissolution rates under repository-relevant conditions are in the range of 10{sup -3} to 10{sup -6}g/m{sup 2}/day.

  15. Prediction of municipal solid waste generation using nonlinear autoregressive network.

    Science.gov (United States)

    Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; Maulud, K N A

    2015-12-01

    Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.

  16. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  17. Medium term municipal solid waste generation prediction by autoregressive integrated moving average

    Energy Technology Data Exchange (ETDEWEB)

    Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan [Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)

    2014-09-12

    Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

  18. Medium term municipal solid waste generation prediction by autoregressive integrated moving average

    Science.gov (United States)

    Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

    2014-09-01

    Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

  19. Development and validation of a building design waste reduction model.

    Science.gov (United States)

    Llatas, C; Osmani, M

    2016-10-01

    Reduction in construction waste is a pressing need in many countries. The design of building elements is considered a pivotal process to achieve waste reduction at source, which enables an informed prediction of their wastage reduction levels. However the lack of quantitative methods linking design strategies to waste reduction hinders designing out waste practice in building projects. Therefore, this paper addresses this knowledge gap through the design and validation of a Building Design Waste Reduction Strategies (Waste ReSt) model that aims to investigate the relationships between design variables and their impact on onsite waste reduction. The Waste ReSt model was validated in a real-world case study involving 20 residential buildings in Spain. The validation process comprises three stages. Firstly, design waste causes were analyzed. Secondly, design strategies were applied leading to several alternative low waste building elements. Finally, their potential source reduction levels were quantified and discussed within the context of the literature. The Waste ReSt model could serve as an instrumental tool to simulate designing out strategies in building projects. The knowledge provided by the model could help project stakeholders to better understand the correlation between the design process and waste sources and subsequently implement design practices for low-waste buildings.

  20. Review Of Rheology Models For Hanford Waste Blending

    Energy Technology Data Exchange (ETDEWEB)

    Koopman, D. C.; Stone, M.

    2013-09-26

    The area of rheological property prediction was identified as a technology need in the Hanford Tank Waste - waste feed acceptance initiative area during a series of technical meetings among the national laboratories, Department of Energy-Office of River Protection, and Hanford site contractors. Meacham et al. delivered a technical report in June 2012, RPP-RPT-51652 ''One System Evaluation of Waste Transferred to the Waste Treatment Plant'' that included estimating of single shell tank waste Bingham plastic rheological model constants along with a discussion of the issues inherent in predicting the rheological properties of blended wastes. This report was selected as the basis for moving forward during the technical meetings. The report does not provide an equation for predicting rheological properties of blended waste slurries. The attached technical report gives an independent review of the provided Hanford rheological data, Hanford rheological models for single tank wastes, and Hanford rheology after blending provided in the Meacham report. The attached report also compares Hanford to SRS waste rheology and discusses some SRS rheological model equations for single tank wastes, as well as discussing SRS experience with the blending of waste sludges with aqueous material, other waste sludges, and frit slurries. Some observations of note: Savannah River Site (SRS) waste samples from slurried tanks typically have yield stress >1 Pa at 10 wt.% undissolved solids (UDS), while core samples largely have little or no yield stress at 10 wt.% UDS. This could be due to how the waste has been processed, stored, retrieved, and sampled or simply in the differences in the speciation of the wastes. The equations described in Meacham's report are not recommended for extrapolation to wt.% UDS beyond the available data for several reasons; weak technical basis, insufficient data, and large data scatter. When limited data are available, for example two to

  1. Review Of Rheology Models For Hanford Waste Blending

    Energy Technology Data Exchange (ETDEWEB)

    Koopman, D. C.; Stone, M.

    2013-09-26

    The area of rheological property prediction was identified as a technology need in the Hanford Tank Waste - waste feed acceptance initiative area during a series of technical meetings among the national laboratories, Department of Energy-Office of River Protection, and Hanford site contractors. Meacham et al. delivered a technical report in June 2012, RPP-RPT-51652 ''One System Evaluation of Waste Transferred to the Waste Treatment Plant'' that included estimating of single shell tank waste Bingham plastic rheological model constants along with a discussion of the issues inherent in predicting the rheological properties of blended wastes. This report was selected as the basis for moving forward during the technical meetings. The report does not provide an equation for predicting rheological properties of blended waste slurries. The attached technical report gives an independent review of the provided Hanford rheological data, Hanford rheological models for single tank wastes, and Hanford rheology after blending provided in the Meacham report. The attached report also compares Hanford to SRS waste rheology and discusses some SRS rheological model equations for single tank wastes, as well as discussing SRS experience with the blending of waste sludges with aqueous material, other waste sludges, and frit slurries. Some observations of note: Savannah River Site (SRS) waste samples from slurried tanks typically have yield stress >1 Pa at 10 wt.% undissolved solids (UDS), while core samples largely have little or no yield stress at 10 wt.% UDS. This could be due to how the waste has been processed, stored, retrieved, and sampled or simply in the differences in the speciation of the wastes. The equations described in Meacham's report are not recommended for extrapolation to wt.% UDS beyond the available data for several reasons; weak technical basis, insufficient data, and large data scatter. When limited data are available, for example two to

  2. Computational Efficient Upscaling Methodology for Predicting Thermal Conductivity of Nuclear Waste forms

    Energy Technology Data Exchange (ETDEWEB)

    Li, Dongsheng; Sun, Xin; Khaleel, Mohammad A.

    2011-09-28

    This study evaluated different upscaling methods to predict thermal conductivity in loaded nuclear waste form, a heterogeneous material system. The efficiency and accuracy of these methods were compared. Thermal conductivity in loaded nuclear waste form is an important property specific to scientific researchers, in waste form Integrated performance and safety code (IPSC). The effective thermal conductivity obtained from microstructure information and local thermal conductivity of different components is critical in predicting the life and performance of waste form during storage. How the heat generated during storage is directly related to thermal conductivity, which in turn determining the mechanical deformation behavior, corrosion resistance and aging performance. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling models were developed and implemented. Due to the absence of experimental data, prediction results from finite element method (FEM) were used as reference to determine the accuracy of different upscaling models. Micrographs from different loading of nuclear waste were used in the prediction of thermal conductivity. Prediction results demonstrated that in term of efficiency, boundary models (Taylor and Sachs model) are better than self consistent model, statistical upscaling method and FEM. Balancing the computation resource and accuracy, statistical upscaling is a computational efficient method in predicting effective thermal conductivity for nuclear waste form.

  3. Mathematical model of the Savannah River Site waste tank farm

    Energy Technology Data Exchange (ETDEWEB)

    Smith, F.G. III.

    1991-07-15

    A mathematical model has been developed to simulate operation of the waste tank farm and the associated evaporator systems at the Savannah River Site. The model solves material balance equations to predict the volumes of liquid waste, salt, and sludge for all of the tanks within each of the evaporator systems. Additional logic is included to model the behavior of waste tanks not directly associated with the evaporators. Input parameters include the Material Management Plan forecast of canyon operations, specification of other waste sources for the evaporator systems, evaporator operating characteristics, and salt and sludge removal schedules. The model determines how the evaporators will operate, when waste transfers can be made, and waste accumulation rates. Output from the model includes waste tank contents, summaries of systems operations, and reports of space gain and the remaining capacity to store waste materials within the tank farm. Model simulations can be made to predict waste tank capacities on a daily basis for up to 20 years. The model is coded as a set of three computer programs designed to run on either IBM compatible or Apple Macintosh II personal computers.

  4. Non-linear model predictive supervisory controller for building, air handling unit with recuperator and refrigeration system with heat waste recovery

    DEFF Research Database (Denmark)

    Minko, Tomasz; Wisniewski, Rafal; Bendtsen, Jan Dimon

    2016-01-01

    In this paper we examine a supermarket system. In order to grasp the most important dynamics we present a model that includes the single zone building thermal envelope with its heating, cooling and ventilation. Moreover we include heat waste recovery from the refrigeration high pressure side. The...

  5. MODEL PREDIKSI PENGARUH LIMBAH CAIR HOTEL TERHADAP KUALITAS AIR LAUT DI PESISIR TELUK KUPANG (A Prediction Model of Liquid Waste Hotel Impact on The Sea Water along The Coast of Kupang Bay

    Directory of Open Access Journals (Sweden)

    Inty Megarini

    2015-11-01

    Full Text Available ABSTRAK Hotel-hotel di pesisir Teluk Kupang sebagian besar membuang efluen limbah cairnya ke laut. Kondisi ini akan berpengaruh terhadap kualitas air laut dan berdampak pada kelangsungan hidup biota dan mikroorganisme laut. Penelitian ini bertujuan untuk membuat prediksi pengaruh efluen limbah cair hotel yang dibuang terhadap kualitas air laut di hadapannya. Parameter yang diteliti adalah minyak dan lemak dan ortofosfat efluen limbah cair hotel. Parameter kualitas air laut yang diteliti adalah kekeruhan, minyak dan lemak dan klorofil. Metode pengambilan sampel dan pengujian menggunakan SNI dan USEPA. Analisis data menggunakan uji korelasi dan regresi. Hasil penelitian menunjukkan bahwa kekeruhan air laut pada jarak 0 meter dan 25 meter dapat diprediksi dari kadar minyak dan lemak efluen limbah cair hotel melalui model regresi y = 0,0051 x + 4,8456 dan y = 0,0015 x + 4,5440. Kadar klorofil air laut pada jarak 25 meter dan 75 meter dapat diprediksi dari kadar ortofosfat efluen limbah cair hotel melalui persamaan regresi y = 0,0430 x + 0,0004 dan y = 0,0075 x + 0,0001. ABSTRACT Most of the hotels located along the coast of Kupang Bay dump their effluent liquid waste to the sea. This action will definitely affect the sea water quality and in turn, will unavoidably give deep impact on the life of both microorganism and all the living things in the sea. This research intends to make an impact prediction on the sea water quality over the dumping hotels’ affluent liquid waste to the sea. The parameters which are observed are oil and fat and orthophosphate of the hotels’ affluent liquid waste. While the observed parameters of the sea water quality are turbidity, oil and fat, and chlorophyll. The methods used to take and test the sample are SNI and USEPA. And to analyze the data, testing on both correlation and regression are applied. The result of the study reveals that the turbidity of the sea water within the range of 0 to 25 meters can be

  6. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg.

  7. The Construction Waste Production Based on the Grey Prediction Model GM(1, 1)%基于灰色预测模型GM(1,1)的建筑垃圾产量研究

    Institute of Scientific and Technical Information of China (English)

    周豪奇; 张云宁; 赵杰

    2016-01-01

    At present, the research of recycling of construction waste is still in the initial stage in our country, construction waste production research can provide powerful data for its data foundation.The paper uses construction area estimation, and combines with the construction area related data of 2004—2013 to estimate the output of construction waste.And it uses the grey prediction model GM (1,1) to predict and analyse the waste production, the results shows that the output of construction waste is huge in China, construction waste will be showed a trend of sustained growth in the next few years.And it puts forward the devel-opment of construction waste resource industry, and provide an effective solution to this problem.%目前,对于建筑垃圾的资源化研究,我国尚处于起步阶段,建筑垃圾的产量研究可为其提供有力的数据基础。通过分析2004—2013年的建筑施工面积,利用面积估算法对建筑垃圾的产量进行估算。采用灰色预测模型对垃圾产量进行精确预测和分析,发现我国建筑垃圾的产量巨大,在未来几年内将呈现持续增长趋势,并因此提出了发展建筑垃圾资源化产业,为有效解决这一问题提供思路。

  8. Advances in modeling plastic waste pyrolysis processes

    Directory of Open Access Journals (Sweden)

    Y. Safadi, J. Zeaiter

    2014-01-01

    Full Text Available The tertiary recycling of plastics via pyrolysis is recently gaining momentum due to promising economic returns from the generated products that can be used as a chemical feedstock or fuel. The need for prediction models to simulate such processes is essential in understanding in depth the mechanisms that take place during the thermal or catalytic degradation of the waste polymer. This paper presents key different models used successfully in literature so far. Three modeling schemes are identified: Power-Law, Lumped-Empirical, and Population-Balance based equations. The categorization is based mainly on the level of detail and prediction capability from each modeling scheme. The data shows that the reliability of these modeling approaches vary with the degree of details the experimental work and product analysis are trying to achieve.

  9. Thermal Predictions of the Cooling of Waste Glass Canisters

    Energy Technology Data Exchange (ETDEWEB)

    Donna Post Guillen

    2014-11-01

    Radioactive liquid waste from five decades of weapons production is slated for vitrification at the Hanford site. The waste will be mixed with glass forming additives and heated to a high temperature, then poured into canisters within a pour cave where the glass will cool and solidify into a stable waste form for disposal. Computer simulations were performed to predict the heat rejected from the canisters and the temperatures within the glass during cooling. Four different waste glass compositions with different thermophysical properties were evaluated. Canister centerline temperatures and the total amount of heat transfer from the canisters to the surrounding air are reported.

  10. LCA Modeling of Waste Management Scenarios

    DEFF Research Database (Denmark)

    Christensen, Thomas Højlund; Simion, F.; Tonini, Davide

    2011-01-01

    and shows that recycling is superior to incineration with energy recovery, which again is better than landfilling. Cleary (2010) reviewed 20 waste management scenarios assessed in 11 studies published in the period 2002–2008 and concluded that, due to lack of transparency regarding boundary conditions...... and exchange with the energy systems, a comparison of results was hampered on a system level. In addition, differences in waste composition may affect the LCA results. This chapter provides results of LCA modeling of 40 waste management scenarios handling the same municipal waste (MSW) and using different...... management systems. The study focuses on Europe in terms of waste composition and exchange with the energy system. The waste management systems modeled are described with respect to waste composition, waste management technologies, mass flows and energy exchange in the systems. Results are first presented...

  11. WASTE CONTAINER AND WASTE PACKAGE PERFORMANCE MODELING TO SUPPORT SAFETY ASSESSMENT OF LOW AND INTERMEDIATE-LEVEL RADIOACTIVE WASTE DISPOSAL.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN, T.

    2004-06-30

    Prior to subsurface burial of low- and intermediate-level radioactive wastes, a demonstration that disposal of the wastes can be accomplished while protecting the health and safety of the general population is required. The long-time frames over which public safety must be insured necessitates that this demonstration relies, in part, on computer simulations of events and processes that will occur in the future. This demonstration, known as a Safety Assessment, requires understanding the performance of the disposal facility, waste containers, waste forms, and contaminant transport to locations accessible to humans. The objective of the coordinated research program is to examine the state-of-the-art in testing and evaluation short-lived low- and intermediate-level waste packages (container and waste form) in near surface repository conditions. The link between data collection and long-term predictions is modeling. The objective of this study is to review state-of-the-art modeling approaches for waste package performance. This is accomplished by reviewing the fundamental concepts behind safety assessment and demonstrating how waste package models can be used to support safety assessment. Safety assessment for low- and intermediate-level wastes is a complicated process involving assumptions about the appropriate conceptual model to use and the data required to support these models. Typically due to the lack of long-term data and the uncertainties from lack of understanding and natural variability, the models used in safety assessment are simplistic. However, even though the models are simplistic, waste container and waste form performance are often central to the case for making a safety assessment. An overview of waste container and waste form performance and typical models used in a safety assessment is supplied. As illustrative examples of the role of waste container and waste package performance, three sample test cases are provided. An example of the impacts of

  12. GISCOD: general integrated solid waste co-digestion model.

    Science.gov (United States)

    Zaher, Usama; Li, Rongping; Jeppsson, Ulf; Steyer, Jean-Philippe; Chen, Shulin

    2009-06-01

    This paper views waste as a resource and anaerobic digestion (AD) as an established biological process for waste treatment, methane production and energy generation. A powerful simulation tool was developed for the optimization and the assessment of co-digestion of any combination of solid waste streams. Optimization was aimed to determine the optimal ratio between different waste streams and hydraulic retention time by changing the digester feed rates to maximize the biogas production rate. Different model nodes based on the ADM1 were integrated and implemented on the Matlab-Simulink simulation platform. Transformer model nodes were developed to generate detailed input for ADM1, estimating the particulate waste fractions of carbohydrates, proteins, lipids and inerts. Hydrolysis nodes were modeled separately for each waste stream. The fluxes from the hydrolysis nodes were combined and generated a detailed input vector to the ADM1. The integrated model was applied to a co-digestion case study of diluted dairy manure and kitchen wastes. The integrated model demonstrated reliable results in terms of calibration and optimization of this case study. The hydrolysis kinetics were calibrated for each waste fraction, and led to accurate simulation results of the process and prediction of the biogas production. The optimization simulated 200,000 days of virtual experimental time in 8 h and determined the feedstock ratio and retention time to set the digester operation for maximum biogas production rate.

  13. Landfill area estimation based on integrated waste disposal options and solid waste forecasting using modified ANFIS model.

    Science.gov (United States)

    Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; Younes, Mohammed Y

    2016-09-01

    Solid waste prediction is crucial for sustainable solid waste management. The collection of accurate waste data records is challenging in developing countries. Solid waste generation is usually correlated with economic, demographic and social factors. However, these factors are not constant due to population and economic growth. The objective of this research is to minimize the land requirements for solid waste disposal for implementation of the Malaysian vision of waste disposal options. This goal has been previously achieved by integrating the solid waste forecasting model, waste composition and the Malaysian vision. The modified adaptive neural fuzzy inference system (MANFIS) was employed to develop a solid waste prediction model and search for the optimum input factors. The performance of the model was evaluated using the root mean square error (RMSE) and the coefficient of determination (R(2)). The model validation results are as follows: RMSE for training=0.2678, RMSE for testing=3.9860 and R(2)=0.99. Implementation of the Malaysian vision for waste disposal options can minimize the land requirements for waste disposal by up to 43%.

  14. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  15. Analysis on 3RWB model (Reduce, reuse, recycle, and waste bank) in comprehensive waste management toward community-based zero waste

    Science.gov (United States)

    Affandy, Nur Azizah; Isnaini, Enik; Laksono, Arif Budi

    2017-06-01

    Waste management becomes a serious issue in Indonesia. Significantly, waste production in Lamongan Regency is increasing in linear with the growth of population and current people activities, creating a gap between waste production and waste management. It is a critical problem that should be solved immediately. As a reaction to the issue, the Government of Lamongan Regency has enacted a new policy regarding waste management through a program named Lamongan Green and Clean (LGC). From the collected data, it showed that the "wet waste" or "organic waste" was approximately 63% of total domestic waste. With such condition, it can be predicted that the trashes will decompose quite quickly. From the observation, it was discovered that the generated waste was approximately 0.25 kg/person/day. Meanwhile, the number of population in Tumenggungan Village, Lamongan (data obtained from Monograph in Lamongan district, 2012) was 4651 people. Thus, it can be estimated the total waste in Lamongan was approximately 0.25 kg/person/day x 4651 characters = 930 kg/day. Within 3RWB Model, several stages have to be conducted. In the planning stage, the promotion of self-awareness among the communities in selecting and managing waste due to their interest in a potential benefit, is done. It indicated that community's awareness of waste management waste grew significantly. Meanwhile in socialization stage, each village staff, environmental expert, and policymaker should bear significant role in disseminating the awareness among the people. In the implementation phase, waste management with 3RWB model is promoted by applying it among of the community, starting from selection, waste management, until recycled products sale through the waste bank. In evaluation stage, the village managers, environmental expert, and waste managers are expected to regularly supervise and evaluate the whole activity of the waste management.

  16. SimpleTreat: a spreadsheet-based box model to predict the fate of xenobiotics in a municipal waste water treatment plant

    NARCIS (Netherlands)

    Struijs J; van de Meent D; Stoltenkamp J

    1991-01-01

    A non-equilibrium steady state box model is reported, that predicts the fate of new chemicals in a conventional sewage treatment plant from a minimal input data set. The model, written in an electronic spreadsheet (Lotus TM 123), requires a minimum input: some basic properties of the chemical, its

  17. CFD modeling and experience of waste-to-energy plant burning waste wood

    DEFF Research Database (Denmark)

    Rajh, B.; Yin, Chungen; Samec, N.

    2013-01-01

    Computational Fluid Dynamics (CFD) is being increasingly used in industry for in-depth understanding of the fundamental mixing, combustion, heat transfer and pollutant formation in combustion processes and for design and optimization of Waste-to-Energy (WtE) plants. In this paper, CFD modeling...... of waste wood combustion in a 13 MW grate-fired boiler in a WtE plant is presented. As a validation effort, the temperature profiles at a number of ports in the furnace are measured and the experimental results are compared with the CFD predictions. In the simulation, a 1D model is developed to simulate...... the conversion of the waste wood in the fuel bed on the grate, which provides the appropriate inlet boundary condition for the freeboard 3D CFD simulation. The CFD analysis reveals the detailed mixing and combustion characteristics in the waste wood-fired furnace, pinpointing how to improve the design...

  18. Comparison between classical Kelvin-Voigt and fractional derivative Kelvin-Voigt models in prediction of linear viscoelastic behaviour of waste activated sludge.

    Science.gov (United States)

    Farno, Ehsan; Baudez, Jean-Christophe; Eshtiaghi, Nicky

    2017-09-22

    Appropriate sewage sludge rheological models are essential for computational fluid dynamic simulation of wastewater treatment processes, in particular aerobic and anaerobic digestions. The liquid-like behaviour of sludge is well documented but the solid-like behaviour remains poorly described despite its importance for dead-zone formation. In this study, classical Kelvin-Voigt model, commonly used for sludge in literature, were compared with fractional derivative Kelvin-Voigt model regarding their predictive ability for describing the solid-like behaviour. Results showed that the fractional Kelvin-Voigt model best fitted the experimental data obtained from creep and frequency sweep tests. Whereas, classical Kelvin-Voigt could not fit the frequency sweep data as this model is not a function of angular velocity. Also, the Kelvin-Voigt model was unable to predict the creep data at low stresses. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Solid waste integrated cost analysis model: 1991 project year report

    Energy Technology Data Exchange (ETDEWEB)

    1991-01-01

    The purpose of the City of Houston's 1991 Solid Waste Integrated Cost Analysis Model (SWICAM) project was to continue the development of a computerized cost analysis model. This model is to provide solid waste managers with tool to evaluate the dollar cost of real or hypothetical solid waste management choices. Those choices have become complicated by the implementation of Subtitle D of the Resources Conservation and Recovery Act (RCRA) and the EPA's Integrated Approach to managing municipal solid waste;. that is, minimize generation, maximize recycling, reduce volume (incinerate), and then bury (landfill) only the remainder. Implementation of an integrated solid waste management system involving all or some of the options of recycling, waste to energy, composting, and landfilling is extremely complicated. Factors such as hauling distances, markets, and prices for recyclable, costs and benefits of transfer stations, and material recovery facilities must all be considered. A jurisdiction must determine the cost impacts of implementing a number of various possibilities for managing, handling, processing, and disposing of waste. SWICAM employs a single Lotus 123 spreadsheet to enable a jurisdiction to predict or assess the costs of its waste management system. It allows the user to select his own process flow for waste material and to manipulate the model to include as few or as many options as he or she chooses. The model will calculate the estimated cost for those choices selected. The user can then change the model to include or exclude waste stream components, until the mix of choices suits the user. Graphs can be produced as a visual communication aid in presenting the results of the cost analysis. SWICAM also allows future cost projections to be made.

  20. Wet oxidation of a spacecraft model waste

    Science.gov (United States)

    Johnson, C. C.; Wydeven, T.

    1985-01-01

    Wet oxidation was used to oxidize a spacecraft model waste under different oxidation conditions. The variables studied were pressure, temperature, duration of oxidation, and the use of one homogeneous and three heterogeneous catalysts. Emphasis is placed on the final oxidation state of carbon and nitrogen since these are the two major components of the spacecraft model waste and two important plant nutrients.

  1. Two Domain Flow Method for Leachate PredictionThrough Municipal Solid Waste Layers in Al–Amari Landfill Site

    Directory of Open Access Journals (Sweden)

    Hayder Mohammed Abdul–Hameed

    2008-01-01

    Full Text Available Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to 0.12 and effective storage and hydraulic conductivity of the wasted must be increased to 0.2 and 2.2 cm/s respectively. In the long term, a new modeling approach must be developed to adequately describe the moisture movement mechanisms.

  2. Modelling Waste Output from Trout Farms

    DEFF Research Database (Denmark)

    Frier, J. O.; From, J.; Larsen, Torben

    1995-01-01

    The aim of waste modelling in aquaculture is to provide tools for simulating input, transformation, output and subsidiary degradation in recipients of organic compounds, nitrogen, and phosphorus. The direct purpose of this modelling is to make it possible for caretakers and water authorities...... to calculate waste discharge from existing and planned aquaculture activities. A special purpose is simulating outcome of waste water treatment and altered feeding programmes. Different submodels must be applied for P, N, and organics, as well as for the different phases of food and waste treatment. Altogether...

  3. Mathematical-statistical models of generated hazardous hospital solid waste.

    Science.gov (United States)

    Awad, A R; Obeidat, M; Al-Shareef, M

    2004-01-01

    This research work was carried out under the assumption that wastes generated from hospitals in Irbid, Jordan were hazardous. The hazardous and non-hazardous wastes generated from the different divisions in the three hospitals under consideration were not separated during collection process. Three hospitals, Princess Basma hospital (public), Princess Bade'ah hospital (teaching), and Ibn Al-Nafis hospital (private) in Irbid were selected for this study. The research work took into account the amounts of solid waste accumulated from each division and also determined the total amount generated from each hospital. The generation rates were determined (kilogram per patient, per day; kilogram per bed, per day) for the three hospitals. These generation rates were compared with similar hospitals in Europe. The evaluation suggested that the current situation regarding the management of these wastes in the three studied hospitals needs revision as these hospitals do not follow methods of waste disposals that would reduce risk to human health and the environment practiced in developed countries. Statistical analysis was carried out to develop models for the prediction of the quantity of waste generated at each hospital (public, teaching, private). In these models number of patients, beds, and type of hospital were revealed to be significant factors on quantity of waste generated. Multiple regressions were also used to estimate the quantities of wastes generated from similar divisions in the three hospitals (surgery, internal diseases, and maternity).

  4. Measurements and predictions of surface gas fluxes and actual evaporation on mine waste rock dump

    Energy Technology Data Exchange (ETDEWEB)

    Kabwe, L.K.; Wilson, G.W. [British Columbia Univ., Vancouver, BC (Canada). Dept. of Mining and Mineral Process Engineering

    2006-07-01

    Long-term closure issues with respect to the mining industry and acid rock drainage (ARD) management require accurate measurements, predictions and monitoring of surface gas fluxes and actual evaporation on mine waste-rock dumps. This study uses a technique, called the dynamic closed chamber system (DCC) that measures the oxygen flux into mine waste dumps. The technique was used with an oxygen gas analyzer to directly measure the change in the oxygen concentration in the headspace of the chamber installed at the surface of the waste dumps. A SoilCover model was also used to predict evaporation fluxes on a waste-rock pile after heavy rainfall events. Measurement of actual evaporation across the surfaces of waste dumps is important in the design of soil covers. The paper discussed the site locations including the Key Lake uranium mine located at the southern rim of the Athabasca Basin in north central Saskatchewan as well as the Syncrude Canada Ltd. mine, located 30 km north of Fort McMurray, Alberta. Materials and methods used in the study as well as results and subsequent discussion were also presented. The effect of relative humidity and the effect of soil cover system on oxygen diffusion was reviewed. It was concluded that the SoilCover numerical model can be a useful tool for prediction of actual evaporation on mine waste dumps. 21 refs., 4 figs.

  5. LCA Modeling of Waste Management Scenarios

    DEFF Research Database (Denmark)

    Christensen, Thomas Højlund; Simion, F.; Tonini, Davide

    2011-01-01

    Lifecycle assessment (LCA) modeling provides a quantitative statement about resource issues and environmental issues in waste management useful in evaluating alternative management systems and in mapping where major loads and savings take place within existing systems. Chapter 3.1 describes...... the concepts behind LCA modeling and Chapter 3.2 gives an overview of existing models and shows examples of their application. A recent comprehensive review of publicly available LCA studies (WRAP, 2006) concluded that, on a material basis, LCA modeling in general confirms the validity of the waste hierarchy...... and exchange with the energy systems, a comparison of results was hampered on a system level. In addition, differences in waste composition may affect the LCA results. This chapter provides results of LCA modeling of 40 waste management scenarios handling the same municipal waste (MSW) and using different...

  6. Prediction of radionuclide inventory for the low-and intermediated-level radioactive waste disposal facility the radioactive waste classification

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Kang Il; Jeong, Noh Gyeom; Moon, Young Pyo; Jeong, Mi Seon; Park, Jin Beak [Korea Radioactive Waste Agency, Daejeon (Korea, Republic of)

    2016-03-15

    To meet nuclear regulatory requirements, more than 95% individual radionuclides in the low- and intermediate-level radioactive waste inventory have to be identified. In this study, the radionuclide inventory has been estimated by taking the long-term radioactive waste generation, the development plan of disposal facility, and the new radioactive waste classification into account. The state of radioactive waste cumulated from 2014 was analyzed for various radioactive sources and future prospects for predicting the long-term radioactive waste generation. The predicted radionuclide inventory results are expected to contribute to secure the development of waste disposal facility and to deploy the safety case for its long-term safety assessment.

  7. Enhanced Waste Tank Level Model

    Energy Technology Data Exchange (ETDEWEB)

    Duignan, M.R.

    1999-06-24

    'With the increased sensitivity of waste-level measurements in the H-Area Tanks and with periods of isolation, when no mass transfer occurred for certain tanks, waste-level changes have been recorded with are unexplained.'

  8. Enhanced Waste Tank Level Model

    Energy Technology Data Exchange (ETDEWEB)

    Duignan, M.R.

    1999-06-24

    'With the increased sensitivity of waste-level measurements in the H-Area Tanks and with periods of isolation, when no mass transfer occurred for certain tanks, waste-level changes have been recorded with are unexplained.'

  9. Model development for household waste prevention behaviour

    Energy Technology Data Exchange (ETDEWEB)

    Bortoleto, Ana Paula, E-mail: a.bortoleto@sheffield.ac.uk [Department of Urban Engineering, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Kurisu, Kiyo H.; Hanaki, Keisuke [Department of Urban Engineering, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer We model waste prevention behaviour using structure equation modelling. Black-Right-Pointing-Pointer We merge attitude-behaviour theories with wider models from environmental psychology. Black-Right-Pointing-Pointer Personal norms and perceived behaviour control are the main behaviour predictors. Black-Right-Pointing-Pointer Environmental concern, moral obligation and inconvenience are the main influence on the behaviour. Black-Right-Pointing-Pointer Waste prevention and recycling are different dimensions of waste management behaviour. - Abstract: Understanding waste prevention behaviour (WPB) could enable local governments and decision makers to design more-effective policies for reducing the amount of waste that is generated. By merging well-known attitude-behaviour theories with elements from wider models from environmental psychology, an extensive cognitive framework that provides new and valuable insights is developed for understanding the involvement of individuals in waste prevention. The results confirm the usefulness of the theory of planned behaviour and of Schwartz's altruistic behaviour model as bases for modelling participation in waste prevention. A more elaborate integrated model of prevention was shown to be necessary for the complete analysis of attitudinal aspects associated with waste prevention. A postal survey of 158 respondents provided empirical support for eight of 12 hypotheses. The proposed structural equation indicates that personal norms and perceived behaviour control are the main predictors and that, unlike the case of recycling, subjective norms have a weak influence on WPB. It also suggests that, since social norms have not presented a direct influence, WPB is likely to be influenced by a concern for the environment and the community as well by perceptions of moral obligation and inconvenience. Results also proved that recycling and waste prevention represent different dimensions of waste

  10. Predicting the Effects of Medical Waste in the Environment Using Artificial Neural Networks: A Case Study

    Directory of Open Access Journals (Sweden)

    Qeethara Al-Shayea

    2013-01-01

    Full Text Available Protection of the environment from medical waste hazards is becoming a serious problem. There is a big relation between medical waste and disease injury. The main idea of this study is predict the relation between medical wastes and diseases in Hashemite Kingdom of Jordan using Artificial Neural Networks (ANNs model. There are six predictor parameters associated with solid and liquid wastes in the medical services sector which are affecting the diseases injury. This study deals with two types of diseases the first one is acute hepatitis and the other is typhoid. Generalized Regression Neural Network (GRNN is used to predict the diseases injury. It is noticed a significant improvement in the prediction made by GRNN due to its generalization property. Results showed that all six parameters associated with solid and liquid medical wastes which have the largest regression value affect the acute hepatitis injuries and the typhoid injuries. It is also showed that the medical waste affected the typhoid injuries in large percentage so the regression is very large.

  11. Predictive models in urology.

    Science.gov (United States)

    Cestari, Andrea

    2013-01-01

    Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology.

  12. Life-cycle assessment of municipal solid wastes: development of the WASTED model.

    Science.gov (United States)

    Diaz, R; Warith, M

    2006-01-01

    This paper describes the development of the Waste Analysis Software Tool for Environmental Decisions (WASTED) model. This model provides a comprehensive view of the environmental impacts of municipal solid waste management systems. The model consists of a number of separate submodels that describe a typical waste management process: waste collection, material recovery, composting, energy recovery from waste and landfilling. These submodels are combined to represent a complete waste management system. WASTED uses compensatory systems to account for the avoided environmental impacts derived from energy recovery and material recycling. The model is designed to provide solid waste decision-makers and environmental researchers with a tool to evaluate waste management plans and to improve the environmental performance of solid waste management strategies. The model is user-friendly and compares favourably with other earlier models.

  13. Modeling of urban solid waste management system: the case of Dhaka city.

    Science.gov (United States)

    Sufian, M A; Bala, B K

    2007-01-01

    This paper presents a system dynamics computer model to predict solid waste generation, collection capacity and electricity generation from solid waste and to assess the needs for waste management of the urban city of Dhaka, Bangladesh. Simulated results show that solid waste generation, collection capacity and electricity generation potential from solid waste increase with time. Population, uncleared waste, untreated waste, composite index and public concern are projected to increase with time for Dhaka city. Simulated results also show that increasing the budget for collection capacity alone does not improve environmental quality; rather an increased budget is required for both collection and treatment of solid wastes of Dhaka city. Finally, this model can be used as a computer laboratory for urban solid waste management (USWM) policy analysis.

  14. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... paper, we will present an introduction to the theory and application of MPC with Matlab codes written to ... model predictive control, linear systems, discrete-time systems, ... and then compute very rapidly for this open-loop con-.

  15. Model development for household waste prevention behaviour.

    Science.gov (United States)

    Bortoleto, Ana Paula; Kurisu, Kiyo H; Hanaki, Keisuke

    2012-12-01

    Understanding waste prevention behaviour (WPB) could enable local governments and decision makers to design more-effective policies for reducing the amount of waste that is generated. By merging well-known attitude-behaviour theories with elements from wider models from environmental psychology, an extensive cognitive framework that provides new and valuable insights is developed for understanding the involvement of individuals in waste prevention. The results confirm the usefulness of the theory of planned behaviour and of Schwartz's altruistic behaviour model as bases for modelling participation in waste prevention. A more elaborate integrated model of prevention was shown to be necessary for the complete analysis of attitudinal aspects associated with waste prevention. A postal survey of 158 respondents provided empirical support for eight of 12 hypotheses. The proposed structural equation indicates that personal norms and perceived behaviour control are the main predictors and that, unlike the case of recycling, subjective norms have a weak influence on WPB. It also suggests that, since social norms have not presented a direct influence, WPB is likely to be influenced by a concern for the environment and the community as well by perceptions of moral obligation and inconvenience. Results also proved that recycling and waste prevention represent different dimensions of waste management behaviour requiring particular approaches to increase individuals' engagement in future policies.

  16. Applying waste logistics modeling to regional planning

    Energy Technology Data Exchange (ETDEWEB)

    Holter, G.M.; Khawaja, A.; Shaver, S.R.; Peterson, K.L.

    1995-05-01

    Waste logistics modeling is a powerful analytical technique that can be used for effective planning of future solid waste storage, treatment, and disposal activities. Proper waste management is essential for preventing unacceptable environmental degradation from ongoing operations, and is also a critical part of any environmental remediation activity. Logistics modeling allows for analysis of alternate scenarios for future waste flowrates and routings, facility schedules, and processing or handling capacities. Such analyses provide an increased understanding of the critical needs for waste storage, treatment, transport, and disposal while there is still adequate lead time to plan accordingly. They also provide a basis for determining the sensitivity of these critical needs to the various system parameters. This paper discusses the application of waste logistics modeling concepts to regional planning. In addition to ongoing efforts to aid in planning for a large industrial complex, the Pacific Northwest Laboratory (PNL) is currently involved in implementing waste logistics modeling as part of the planning process for material recovery and recycling within a multi-city region in the western US.

  17. Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.

    Science.gov (United States)

    Azadi, Sama; Karimi-Jashni, Ayoub

    2016-02-01

    Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verified to predict mean Seasonal Municipal Solid Waste Generation (SMSWG) rate. The accuracy of the proposed models is illustrated through a case study of 20 cities located in Fars Province, Iran. Four performance measures, MAE, MAPE, RMSE and R were used to evaluate the performance of these models. The MLR, as a conventional model, showed poor prediction performance. On the other hand, the results indicated that the ANN model, as a non-linear model, has a higher predictive accuracy when it comes to prediction of the mean SMSWG rate. As a result, in order to develop a more cost-effective strategy for waste management in the future, the ANN model could be used to predict the mean SMSWG rate.

  18. Degradation modeling of the ANL ceramic waste form

    Energy Technology Data Exchange (ETDEWEB)

    Fanning, T. H.; Morss, L. R.

    2000-03-28

    A ceramic waste form composed of glass-bonded sodalite is being developed at Argonne National Laboratory (ANL) for immobilization and disposition of the molten salt waste stream from the electrometallurgical treatment process for metallic DOE spent nuclear fuel. As part of the spent fuel treatment program at ANL, a model is being developed to predict the long-term release of radionuclides under repository conditions. Dissolution tests using dilute, pH-buffered solutions have been conducted at 40, 70, and 90 C to determine the temperature and pH dependence of the dissolution rate. Parameter values measured in these tests have been incorporated into the model, and preliminary repository performance assessment modeling has been completed. Results indicate that the ceramic waste form should be acceptable in a repository environment.

  19. Nominal model predictive control

    OpenAIRE

    Grüne, Lars

    2013-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  20. Nominal Model Predictive Control

    OpenAIRE

    Grüne, Lars

    2014-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  1. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  2. High Level Waste Tank Closure Modeling with Geographic Information Systems (GIS)

    Energy Technology Data Exchange (ETDEWEB)

    BOLLINGER, JAMES

    2004-07-29

    Waste removal from 49 underground storage tanks located in two tank farms involves three steps: bulk waste removal, water washing to remove residual waste, and in some cases chemical cleaning to remove additional residual waste. Not all waste can be completely removed by these processes-resulting in some residual waste loading following cleaning. Completely removing this residual waste would be prohibitively expensive; therefore, it will be stabilized by filling the tanks with grout. Acceptable residual waste loading inventories were determined using one-dimensional groundwater transport modeling to predict future human exposure based on several scenarios. These modeling results have been incorporated into a geographic information systems (GIS) application for rapid evaluation of various tank closure options.

  3. Stochastic modelling of landfill leachate and biogas production incorporating waste heterogeneity. Model formulation and uncertainty analysis.

    Science.gov (United States)

    Zacharof, A I; Butler, A P

    2004-01-01

    A mathematical model simulating the hydrological and biochemical processes occurring in landfilled waste is presented and demonstrated. The model combines biochemical and hydrological models into an integrated representation of the landfill environment. Waste decomposition is modelled using traditional biochemical waste decomposition pathways combined with a simplified methodology for representing the rate of decomposition. Water flow through the waste is represented using a statistical velocity model capable of representing the effects of waste heterogeneity on leachate flow through the waste. Given the limitations in data capture from landfill sites, significant emphasis is placed on improving parameter identification and reducing parameter requirements. A sensitivity analysis is performed, highlighting the model's response to changes in input variables. A model test run is also presented, demonstrating the model capabilities. A parameter perturbation model sensitivity analysis was also performed. This has been able to show that although the model is sensitive to certain key parameters, its overall intuitive response provides a good basis for making reasonable predictions of the future state of the landfill system. Finally, due to the high uncertainty associated with landfill data, a tool for handling input data uncertainty is incorporated in the model's structure. It is concluded that the model can be used as a reasonable tool for modelling landfill processes and that further work should be undertaken to assess the model's performance.

  4. Model Predictive Control of Sewer Networks

    Science.gov (United States)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.

    2017-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and controlled have thus become essential factors for effcient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.

  5. Modeling the flows of engineered nanomaterials during waste handling.

    Science.gov (United States)

    Mueller, Nicole C; Buha, Jelena; Wang, Jing; Ulrich, Andrea; Nowack, Bernd

    2013-01-01

    Little is known about the behavior of engineered nanomaterials (ENM) at the interface from the technosphere to the ecosphere. Previous modeling of ENM flows to the environment revealed that significant amounts of ENM enter the waste stream and therefore waste incineration plants and landfills. It is the aim of this study to model the flows of ENM during waste incineration and landfilling in greater depth by including a more detailed description of the different processes and considering ENM-specific transformation reactions. Four substances were modeled: nano-TiO2, nano-ZnO, nano-Ag and carbon nanotube (CNT). These ENM are representative for commonly used materials and products, illustrating a variety of ENM with different behavior. The modeling was performed for Switzerland where almost 100% of the municipal waste and sewage sludge are burned. The mass-based modeling showed that – despite several differences among the models for nano-TiO2, nano-ZnO and nano-Ag (e.g. partial dissolution of nano-ZnO in acid washing of exhaust air or fly ash) – the major ENM flows go from the waste incineration plant to the landfill as bottom ash. All other flows within the system boundary (e.g. with the fly ash) were predicted to be about one magnitude smaller than the bottom ash flow. A different ENM distribution was found for CNTs that are expected to burn to a large extent (94%) so that only insignificant amounts remain in the system. The results of the modeling show that waste incineration can have a strong influence on some ENM but that still the majority of the ENM-mass is expected to end up in landfills.

  6. Predicted growth of world urban food waste and methane production.

    Science.gov (United States)

    Adhikari, Bijaya K; Barrington, Suzelle; Martinez, José

    2006-10-01

    Landfill gas emissions are one of the largest anthropogenic sources of methane especially because of food waste (FW). To prevent these emissions growing with world population, future FW best management practices need to be evaluated. The objective of this paper was therefore to predict FW production for 2025 if present management practices are maintained, and then, to compare the impact of scenario 1: encouraging people to stay in rural areas and composting 75% of their FW, and; of scenario 2, where in addition to scenario 1, composting or anaerobically digesting 75% of urban FW (UFW). A relationship was established between per capita gross domestic product (GDP) and the population percentage living in urban areas (%UP), as well as production of municipal solid waste (MSW) and UFW. With estimated GDP and population growth per country, %UP and production of MSW and UFW could be predicted for 2025. A relatively accurate (R(2) > 0.85) correlation was found between GDP and %UP, and between GDP and mass of MSW and FW produced. On a global scale, MSW and UFW productions were predicted to increase by 51 and 44%, respectively, from 2005 to 2025. During the same period, and because of its expected economic development, Asia was predicted to experience the largest increase in UFW production, of 278 to 416 Gkg. If present MSW management trends are maintained, landfilled UFW was predicted to increase world CH4 emissions from 34 to 48 Gkg and the landfill share of global anthropogenic emissions from 8 to 10%. In comparison with maintaining present FW management practices, scenario 1 can lower UFW production by 30% and maintain the landfill share of the global anthropogenic emissions at 8%. With scenario 2, the landfill share of global anthropogenic emissions could be further reduced from 8 to 6% and leachate production could be reduced by 40%.

  7. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...

  8. Chemical speciation of strontium, americium, and curium in high level waste: Predictive modeling of phase partitioning during tank processing. Annual progress report, October 1996--September 1997

    Energy Technology Data Exchange (ETDEWEB)

    Felmy, A.R. [Pacific Northwest National Lab., Richland, WA (US); Choppin, G. [Florida State Univ., Tallahassee, FL (US)

    1997-12-31

    'The program at Florida State University was funded to collaborate with Dr. A. Felmy (PNNL) on speciation in high level wastes and with Dr. D. Rai (PNNL) on redox of Pu under high level waste conditions. The funding provided support for 3 research associates (postdoctoral researchers) under Professor G. R. Choppin as P.I. Dr. Kath Morris from U. Manchester (Great Britain), Dr. Dean Peterman and Dr. Amy Irwin (both from U. Cincinnati) joined the laboratory in the latter part of 1996. After an initial training period to become familiar with basic actinide chemistry and radiochemical techniques, they began their research. Dr. Peterman was assigned the task of measuring Th-EDTA complexation prior to measuring Pu(IV)-EDTA complexation. These studies are associated with the speciation program with Dr. Felmy. Drs. Morris and Irwin initiated research on redox of plutonium with agents present in the Hanford Tanks as a result of radiolysis or from use in separations. The preliminary results obtained thus far are described in this report. It is expected that the rate of progress will continue to increase significantly as the researchers gain more experience with plutonium chemistry.'

  9. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena

    2014-01-01

    Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were

  10. Life cycle assessment modelling of waste-to-energy incineration in Spain and Portugal.

    Science.gov (United States)

    Margallo, M; Aldaco, R; Irabien, A; Carrillo, V; Fischer, M; Bala, A; Fullana, P

    2014-06-01

    In recent years, waste management systems have been evaluated using a life cycle assessment (LCA) approach. A main shortcoming of prior studies was the focus on a mixture of waste with different characteristics. The estimation of emissions and consumptions associated with each waste fraction in these studies presented allocation problems. Waste-to-energy (WTE) incineration is a clear example in which municipal solid waste (MSW), comprising many types of materials, is processed to produce several outputs. This paper investigates an approach to better understand incineration processes in Spain and Portugal by applying a multi-input/output allocation model. The application of this model enabled predictions of WTE inputs and outputs, including the consumption of ancillary materials and combustibles, air emissions, solid wastes, and the energy produced during the combustion of each waste fraction. © The Author(s) 2014.

  11. Energy and time modelling of kerbside waste collection: Changes incurred when adding source separated food waste.

    Science.gov (United States)

    Edwards, Joel; Othman, Maazuza; Burn, Stewart; Crossin, Enda

    2016-10-01

    The collection of source separated kerbside municipal FW (SSFW) is being incentivised in Australia, however such a collection is likely to increase the fuel and time a collection truck fleet requires. Therefore, waste managers need to determine whether the incentives outweigh the cost. With literature scarcely describing the magnitude of increase, and local parameters playing a crucial role in accurately modelling kerbside collection; this paper develops a new general mathematical model that predicts the energy and time requirements of a collection regime whilst incorporating the unique variables of different jurisdictions. The model, Municipal solid waste collect (MSW-Collect), is validated and shown to be more accurate at predicting fuel consumption and trucks required than other common collection models. When predicting changes incurred for five different SSFW collection scenarios, results show that SSFW scenarios require an increase in fuel ranging from 1.38% to 57.59%. There is also a need for additional trucks across most SSFW scenarios tested. All SSFW scenarios are ranked and analysed in regards to fuel consumption; sensitivity analysis is conducted to test key assumptions. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  12. A simple method for predicting the lower heating value of municipal solid waste in China based on wet physical composition.

    Science.gov (United States)

    Lin, Xuebin; Wang, Fei; Chi, Yong; Huang, Qunxing; Yan, Jianhua

    2015-02-01

    A rapid and cost-effective prediction method based on wet physical composition has been developed to determine the lower heating value (LHV) of municipal solid waste (MSW) for practical applications in China. The heating values (HVs) of clean combustibles were measured in detail, and the effect of combustibles, food waste, and ash content on HV was studied to develop the model. The weighted average HV can be used to predict the MSW HV with high accuracy. Based on the moisture measurements of each major real combustible and the HV of clean solid waste, a predictive model of the LHV of real MSW was developed. To assess the prediction performance, information was collected on 103 MSW samples from 31 major cities in China from 1994 to 2012. Compared with five predictive models based on the wet physical composition from different regions in the world, the predictive result of the developed model is the most accurate. The prediction performance can be improved further if the MSW is sorted better and if more information is collected on the individual moisture contents of the waste. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Reinvestigation into Closure Predictions of Room D at the Waste Isolation Pilot Plant

    Energy Technology Data Exchange (ETDEWEB)

    Reedlunn, Benjamin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-09-27

    Room D was an in-situ, isothermal, underground experiment conducted at the Waste Isolation Pilot Plant between 1984 and 1991. The room was carefully instrumented to measure the horizontal and vertical closure immediately upon excavation and for several years thereafter. Early finite element simulations of salt creep around Room D under-predicted the vertical closure by 4.5×, causing investigators to explore a series of changes to the way Room D was modeled. Discrepancies between simulations and measurements were resolved through a series of adjustments to model parameters, which were openly acknowledged in published reports. Interest in Room D has been rekindled recently by the U.S./German Joint Project III and Project WEIMOS, which seek to improve the predictions of rock salt constitutive models. Joint Project participants calibrate their models solely against laboratory tests, and benchmark the models against underground experiments, such as room D. This report describes updating legacy Room D simulations to today’s computational standards by rectifying several numerical issues. Subsequently, the constitutive model used in previous modeling is recalibrated two different ways against a suite of new laboratory creep experiments on salt extracted from the repository horizon of the Waste Isolation Pilot Plant. Simulations with the new, laboratory-based, calibrations under-predict Room D vertical closure by 3.1×. A list of potential improvements is discussed.

  14. Reinvestigation into Closure Predictions of Room D at the Waste Isolation Pilot Plant

    Energy Technology Data Exchange (ETDEWEB)

    Reedlunn, Benjamin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-10-01

    Room D was an in-situ, isothermal, underground experiment conducted at theWaste Isolation Pilot Plant between 1984 and 1991. The room was carefully instrumented to measure the horizontal and vertical closure immediately upon excavation and for several years thereafter. Early finite element simulations of salt creep around Room D under predicted the vertical closure by 4.5×, causing investigators to explore a series of changes to the way Room D was modeled. Discrepancies between simulations and measurements were resolved through a series of adjustments to model parameters, which were openly acknowledged in published reports. Interest in Room D has been rekindled recently by the U.S./German Joint Project III and Project WEIMOS, which seek to improve the predictions of rock salt constitutive models. Joint Project participants calibrate their models solely against laboratory tests, and benchmark the models against underground experiments, such as room D. This report describes updating legacy Room D simulations to today’s computational standards by rectifying several numerical issues. Subsequently, the constitutive model used in previous modeling is recalibrated two different ways against a suite of new laboratory creep experiments on salt extracted from the repository horizon of the Waste Isolation Pilot Plant. Simulations with the new, laboratory-based, calibrations under predict Room D vertical closure by 3.1×. A list of potential improvements is discussed.

  15. Sensitivity analysis of the waste composition and water content parameters on the biogas production models on solid waste landfills

    Science.gov (United States)

    Rodrigo-Ilarri, Javier; Segura-Sobrino, Francisco; Rodrigo-Clavero, Maria-Elena

    2014-05-01

    Landfills are commonly used as the final deposit of urban solid waste. Despite the waste is previously processed on a treatment plant, the final amount of organic matter which reaches the landfill is large however. The biodegradation of this organic matter forms a mixture of greenhouse gases (essentially Methane and Carbon-Dioxide as well as Ammonia and Hydrogen Sulfide). From the environmental point of view, solid waste landfills are therefore considered to be one of the main greenhouse gas sources. Different mathematical models are usually applied to predict the amount of biogas produced on real landfills. The waste chemical composition and the availability of water in the solid waste appear to be the main parameters of these models. Results obtained when performing a sensitivity analysis over the biogas production model parameters under real conditions are shown. The importance of a proper characterizacion of the waste as well as the necessity of improving the understanding of the behaviour and development of the water on the unsaturated mass of waste are emphasized.

  16. Reinvestigation into Closure Predictions of Room D at the Waste Isolation Pilot Plant.

    Energy Technology Data Exchange (ETDEWEB)

    Reedlunn, Benjamin

    2016-10-01

    Room D was an in-situ ,isothermal,undergroundexperimentconductedattheWasteIsola- tion Pilot Plant between 1984 and 1991. The room was carefully instrumented to measure the horizontal and vertical closure immediately upon excavation and for several years thereafter. Early finite element simulations of salt creep around Room D under predicted the vertical closure by 4 . 5 - , causing investigators to explore a series of changes to the way Room D was modeled. Discrepancies between simulations and measurements were resolved through aseriesofadjustmentstomodelparameters,whichwereopenlyacknowledgedinpublished reports. Interest in Room D has been rekindled recently by the U.S./German Joint Project III and Project WEIMOS, which seek to improve the predictions of rock salt constitutive models. Joint Project participants calibrate their models solely against laboratory tests, and bench- mark the models against underground experiments, such as room D. This report describes updating legacy Room D simulations to today's computational standards by rectifying sev- eral numerical issues. Subsequently, the constitutive model used in previous modeling is recalibrated two di %7C erent ways against a suite of new laboratory creep experiments on salt extracted from the repository horizon of the Waste Isolation Pilot Plant. Simulations with the new, laboratory-based, calibrations under predict Room D vertical closure by 3 . 1 - .A list of potential improvements is discussed.

  17. GENERAL REQUIREMENTS FOR SIMULATION MODELS IN WASTE MANAGEMENT

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Ian; Kossik, Rick; Voss, Charlie

    2003-02-27

    Most waste management activities are decided upon and carried out in a public or semi-public arena, typically involving the waste management organization, one or more regulators, and often other stakeholders and members of the public. In these environments, simulation modeling can be a powerful tool in reaching a consensus on the best path forward, but only if the models that are developed are understood and accepted by all of the parties involved. These requirements for understanding and acceptance of the models constrain the appropriate software and model development procedures that are employed. This paper discusses requirements for both simulation software and for the models that are developed using the software. Requirements for the software include transparency, accessibility, flexibility, extensibility, quality assurance, ability to do discrete and/or continuous simulation, and efficiency. Requirements for the models that are developed include traceability, transparency, credibility/validity, and quality control. The paper discusses these requirements with specific reference to the requirements for performance assessment models that are used for predicting the long-term safety of waste disposal facilities, such as the proposed Yucca Mountain repository.

  18. Waste tyre pyrolysis: modelling of a moving bed reactor.

    Science.gov (United States)

    Aylón, E; Fernández-Colino, A; Murillo, R; Grasa, G; Navarro, M V; García, T; Mastral, A M

    2010-12-01

    This paper describes the development of a new model for waste tyre pyrolysis in a moving bed reactor. This model comprises three different sub-models: a kinetic sub-model that predicts solid conversion in terms of reaction time and temperature, a heat transfer sub-model that calculates the temperature profile inside the particle and the energy flux from the surroundings to the tyre particles and, finally, a hydrodynamic model that predicts the solid flow pattern inside the reactor. These three sub-models have been integrated in order to develop a comprehensive reactor model. Experimental results were obtained in a continuous moving bed reactor and used to validate model predictions, with good approximation achieved between the experimental and simulated results. In addition, a parametric study of the model was carried out, which showed that tyre particle heating is clearly faster than average particle residence time inside the reactor. Therefore, this fast particle heating together with fast reaction kinetics enables total solid conversion to be achieved in this system in accordance with the predictive model.

  19. A NEW WASTE CLASSIFYING MODEL: HOW WASTE CLASSIFICATION CAN BECOME MORE OBJECTIVE?

    Directory of Open Access Journals (Sweden)

    Burcea Stefan Gabriel

    2015-07-01

    documents available in the virtual space, on the websites of certain international organizations involved in the wide and complex issue of waste management. The second part of the paper contains a proposal classification model with four main criteria in order to make waste classification a more objective process. The new classification model has the main role of transforming the traditional patterns of waste classification into an objective waste classification system and a second role of eliminating the strong contextuality of the actual waste classification models.

  20. An approach to thermochemical modeling of nuclear waste glass

    Energy Technology Data Exchange (ETDEWEB)

    Besmann, T.M.; Beahm, E.C. [Oak Ridge National Lab., TN (United States); Spear, K.E. [Pennsylvania State Univ., University Park, PA (United States)

    1998-11-01

    This initial work is aimed at developing a basic understanding of the phase equilibria and solid solution behavior of the constituents of waste glass. Current, experimentally determined values are less than desirable since they depend on measurement of the leach rate under non-realistic conditions designed to accelerate processes that occur on a geologic time scale. The often-used assumption that the activity of a species is either unity or equal to the overall concentration of the metal can also yield misleading results. The associate species model, a recent development in thermochemical modeling, will be applied to these systems to more accurately predict chemical activities in such complex systems as waste glasses.

  1. Predictive Models for Music

    OpenAIRE

    Paiement, Jean-François; Grandvalet, Yves; Bengio, Samy

    2008-01-01

    Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic modeling into two subtasks. We first propose a rhythm model based on the distributions of distances between subsequences. Then, we define a generative model for melodies given chords and rhythms based on modeling sequences of Narmour featur...

  2. A degradation model for high kitchen waste content municipal solid waste.

    Science.gov (United States)

    Chen, Yunmin; Guo, Ruyang; Li, Yu-Chao; Liu, Hailong; Zhan, Tony Liangtong

    2016-12-01

    Municipal solid waste (MSW) in developing countries has a high content of kitchen waste (KW), and therefore contains large quantities of water and non-hollocellulose degradable organics. The degradation of high KW content MSW cannot be well simulated by the existing degradation models, which are mostly established for low KW content MSW in developed countries. This paper presents a two-stage anaerobic degradation model for high KW content MSW with degradations of hollocellulose, sugars, proteins and lipids considered. The ranges of the proportions of chemical compounds in MSW components are summarized with the recommended values given. Waste components are grouped into rapidly or slowly degradable categories in terms of the degradation rates under optimal water conditions for degradation. In the proposed model, the unionized VFA inhibitions of hydrolysis/acidogenesis and methanogenesis are considered as well as the pH inhibition of methanogenesis. Both modest and serious VFA inhibitions can be modeled by the proposed model. Default values for the parameters in the proposed method can be used for predictions of degradations of both low and high KW content MSW. The proposed model was verified by simulating two laboratory experiments, in which low and high KW content MSW were used, respectively. The simulated results are in good agreement with the measured data of the experiments. The results show that under low VFA concentrations, the pH inhibition of methanogenesis is the main inhibition to be considered, while the inhibitions of both hydrolysis/acidogenesis and methanogenesis caused by unionized VFA are significant under high VFA concentrations. The model is also used to compare the degradation behaviors of low and high KW content MSW under a favorable environmental condition, and it shows that the gas potential of high KW content MSW releases more quickly.

  3. Two-phase plate-fin heat exchanger modeling for waste heat recovery systems in diesel engines

    NARCIS (Netherlands)

    Feru, E.; de Jager, B.; Willems, F.; Steinbuch, M.

    2014-01-01

    This paper presents the modeling and model validation for a modular two-phase heat exchanger that recovers energy in heavy-duty diesel engines. The model is developed for temperature and vapor quality prediction and for control design of the waste heat recovery system. In the studied waste heat reco

  4. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg

    2001-01-01

    This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Dani...

  5. Electrochemical Corrosion Studies for Modeling Metallic Waste Form Release Rates

    Energy Technology Data Exchange (ETDEWEB)

    Poineau, Frederic [Univ. of Nevada, Las Vegas, NV (United States); Tamalis, Dimitri [Florida Memorial Univ., Miami Gardens, FL (United States)

    2016-08-01

    The isotope 99Tc is an important fission product generated from nuclear power production. Because of its long half-life (t1/2 = 2.13 ∙ 105 years) and beta-radiotoxicity (β⁻ = 292 keV), it is a major concern in the long-term management of spent nuclear fuel. In the spent nuclear fuel, Tc is present as an alloy with Mo, Ru, Rh, and Pd called the epsilon-phase, the relative amount of which increases with fuel burn-up. In some separation schemes for spent nuclear fuel, Tc would be separated from the spent fuel and disposed of in a durable waste form. Technetium waste forms under consideration include metallic alloys, oxide ceramics and borosilicate glass. In the development of a metallic waste form, after separation from the spent fuel, Tc would be converted to the metal, incorporated into an alloy and the resulting waste form stored in a repository. Metallic alloys under consideration include Tc–Zr alloys, Tc–stainless steel alloys and Tc–Inconel alloys (Inconel is an alloy of Ni, Cr and iron which is resistant to corrosion). To predict the long-term behavior of the metallic Tc waste form, understanding the corrosion properties of Tc metal and Tc alloys in various chemical environments is needed, but efforts to model the behavior of Tc metallic alloys are limited. One parameter that should also be considered in predicting the long-term behavior of the Tc waste form is the ingrowth of stable Ru that occurs from the radioactive decay of 99Tc (99Tc → 99Ru + β⁻). After a geological period of time, significant amounts of Ru will be present in the Tc and may affect its corrosion properties. Studying the effect of Ru on the corrosion behavior of Tc is also of importance. In this context, we studied the electrochemical behavior of Tc metal, Tc-Ni alloys (to model Tc-Inconel alloy) and Tc-Ru alloys in acidic media. The study of Tc-U alloys has also been performed in order to better understand the

  6. Models for waste life cycle assessment: Review of technical assumptions

    DEFF Research Database (Denmark)

    Gentil, Emmanuel; Damgaard, Anders; Hauschild, Michael Zwicky

    2010-01-01

    A number of waste life cycle assessment (LCA) models have been gradually developed since the early 1990s, in a number of countries, usually independently from each other. Large discrepancies in results have been observed among different waste LCA models, although it has also been shown that results......, such as the functional unit, system boundaries, waste composition and energy modelling. The modelling assumptions of waste management processes, ranging from collection, transportation, intermediate facilities, recycling, thermal treatment, biological treatment, and landfilling, are obviously critical when comparing...... waste LCA models. This review infers that some of the differences in waste LCA models are inherent to the time they were developed. It is expected that models developed later, benefit from past modelling assumptions and knowledge and issues. Models developed in different countries furthermore rely...

  7. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...

  8. Conceptual Model for Systematic Construction Waste Management

    OpenAIRE

    Abd Rahim Mohd Hilmi Izwan; Kasim Narimah

    2017-01-01

    Development of the construction industry generated construction waste which can contribute towards environmental issues. Weaknesses of compliance in construction waste management especially in construction site have also contributed to the big issues of waste generated in landfills and illegal dumping area. This gives sign that construction projects are needed a systematic construction waste management. To date, a comprehensive criteria of construction waste management, particularly for const...

  9. Towards optimization of nuclear waste glass: Constraints, property models, and waste loading

    Energy Technology Data Exchange (ETDEWEB)

    Hrma, P.

    1994-04-01

    Vitrification of both low- and high-level wastes from 177 tanks at Hanford poses a great challenge to glass makers, whose task is to formulate a system of glasses that are acceptable to the federal repository for disposal. The enormous quantity of the waste requires a glass product of the lowest possible volume. The incomplete knowledge of waste composition, its variability, and lack of an appropriate vitrification technology further complicates this difficult task. A simple relationship between the waste loading and the waste glass volume is presented and applied to the predominantly refractory (usually high-activity) and predominantly alkaline (usually low-activity) waste types. Three factors that limit waste loading are discussed, namely product acceptability, melter processing, and model validity. Glass formulation and optimization problems are identified and a broader approach to uncertainties is suggested.

  10. Modelling, controlling, predicting blackouts

    CERN Document Server

    Wang, Chengwei; Baptista, Murilo S

    2016-01-01

    The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...

  11. Life-cycle modelling of waste management in Europe: tools, climate change and waste prevention

    DEFF Research Database (Denmark)

    Gentil, Emmanuel

    of these models most importantly depend on the technical assumptions and parameters defining waste management technologies. Some of these technical assumptions have evolved significantly from the early models to the more recent ones. An important purpose of waste LCA models is to perform environmental assessments......Europe has a long history of waste management, where regulation, implementation and enforcement have been the main drivers for the development and diversification of waste management technologies since the late 70s. Despite strong engineering development to minimise impacts to human health...... disposal to resources management, requiring modelling tools, such as life-cycle assessment (LCA) models, for carrying out environmental assessment, because of the complexity of the systems. A review of the key waste LCA models was performed in the present PhD project and showed that the results...

  12. Mechanism and kinetics model of hydrolysis in anaerobic digestion of kitchen wastes

    Institute of Scientific and Technical Information of China (English)

    吴云; 张代钧; 杨钢

    2009-01-01

    The profile of hydrolysates during the anaerobic digestion of kitchen wastes was investigated. The experimental results show that the hysteresis of hydrolytic rate is mainly controlled by the diffusion effect. The hydrolytic mechanism of kitchen wastes is elaborated by taking the diffusion effect into consideration. A segment model of the hydrolysis for kitchen waste is formulated including the coefficient of diffusion resistance in the model. The coefficients of diffusion resistance for different particle sizes are 1.42,2.12 and 2.78 respectively based on the experimental data,in which the coefficients of diffusion resistance conform an exponential function. So,the partitioning kinetic model could be integrated as a unified experience model. The model is verified with experimental data,which shows that the model could predict the concentration of organic substances during the anaerobic digestion of kitchen wastes.

  13. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. EASEWASTE-life cycle modeling capabilities for waste management technologies

    DEFF Research Database (Denmark)

    Bhander, Gurbakhash Singh; Christensen, Thomas Højlund; Hauschild, Michael Zwicky

    2010-01-01

    Background, Aims and Scope The management of municipal solid waste and the associated environmental impacts are subject of growing attention in industrialized countries. EU has recently strongly emphasized the role of LCA in its waste and resource strategies. The development of sustainable solid...... waste management systems applying a life-cycle perspective requires readily understandable tools for modelling the life cycle impacts of waste management systems. The aim of the paper is to demonstrate the structure, functionalities and LCA modelling capabilities of the PC-based life cycle oriented...... waste management model EASEWASTE, developed at the Technical University of Denmark specifically to meet the needs of the waste system developer with the objective to evaluate the environmental performance of the various elements of existing or proposed solid waste management systems. Materials...

  15. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production......The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...... and HIRLAM predictions. The statistical models belong to the class of conditional parametric models. The models are estimated using local polynomial regression, but the estimation method is here extended to be adaptive in order to allow for slow changes in the system e.g. caused by the annual variations...

  16. Establishment the code for prediction of waste volume on NPP decommissioning

    Energy Technology Data Exchange (ETDEWEB)

    Cho, W. H.; Park, S. K.; Choi, Y. D.; Kim, I. S.; Moon, J. K. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    -2 and developed DEMOS(DEcommissioning MOdeling System) and DEPES(DEcommissioning Process Establish System) using these data. These systems may be able to help to establish decommissioning strategy of nuclear power plant. We tried to apply research reactor data to OPR-1000 which is commercial nuclear power plant. But code for research reactor was not consistent when applying to nuclear power plant. The decommissioning activity of nuclear power plant is basically performed by the unit facility or room. In order to apply research reactor data, each WBS code is needed to apply to the object of each facility. This means that one FAC code may have several WBS codes. However, current codes in DECOMMIS are hard to map WBS code to FAC code one by one, and are specialized to research reactor. So it is difficult to apply to nuclear power plant directly. In order to solve this problem, the common code that can be adapted to commercial nuclear power plant as well as to research reactor is required. It may be inferred from the mapping data in the case of mismatching, or it can be applied with some modifications in the case of similar facility. In this paper, the establishment method of the code which uses the research reactor data in decommissioning project of nuclear power plant was studied. Method for prediction of the decommissioning waste volume was discussed on the basis of the domestic nuclear power plant, OPR-1000. Decommissioning experience is very important to apply to the estimation of decommissioning waste volume. So method for the estimation of decommissioning waste volume using common code that link OPR-1000 and KRR-2 was suggested. This research result will be helpful to reliable estimation of decommissioning waste volume and further estimation of the decommissioning cost and establishment of decommissioning strategies.

  17. Life Cycle Costing Model for Solid Waste Management

    DEFF Research Database (Denmark)

    Martinez-Sanchez, Veronica; Astrup, Thomas Fruergaard

    2014-01-01

    To ensure sustainability of solid waste management, there is a need for cost assessment models which are consistent with environmental and social assessments. However, there is a current lack of standardized terminology and methodology to evaluate economic performances and this complicates...... LCC, e.g. waste generator, waste operator and public finances and the perspective often defines the systemboundaries of the study, e.g. waste operators often focus on her/his own cost, i.e. technology based,whereas waste generators and public finances often focus on the entire waste system, i.......e. system based. Figure 1 illustrates the proposed modeling framework that distinguishes between: a) budget cost, b) externality costs and 3) transfers and defines unit costs of each technology (per ton of input waste). Unitcosts are afterwards combined with a mass balance to calculate the technology cost...

  18. Geothermal reservoir simulation to enhance confidence in predictions for nuclear waste disposal

    Energy Technology Data Exchange (ETDEWEB)

    Kneafsey, Timothy J.; Pruess, Karsten; O' Sullivan, Michael J.; Bodvarsson, Gudmundur S.

    2002-06-15

    Numerical simulation of geothermal reservoirs is useful and necessary in understanding and evaluating reservoir structure and behavior, designing field development, and predicting performance. Models vary in complexity depending on processes considered, heterogeneity, data availability, and study objectives. They are evaluated using computer codes written and tested to study single and multiphase flow and transport under nonisothermal conditions. Many flow and heat transfer processes modeled in geothermal reservoirs are expected to occur in anthropogenic thermal (AT) systems created by geologic disposal of heat-generating nuclear waste. We examine and compare geothermal systems and the AT system expected at Yucca Mountain, Nevada, and their modeling. Time frames and spatial scales are similar in both systems, but increased precision is necessary for modeling the AT system, because flow through specific repository locations will affect long-term ability radionuclide retention. Geothermal modeling experience has generated a methodology, used in the AT modeling for Yucca Mountain, yielding good predictive results if sufficient reliable data are available and an experienced modeler is involved. Codes used in geothermal and AT modeling have been tested extensively and successfully on a variety of analytical and laboratory problems.

  19. Numerical modeling of batch formation in waste incineration plants

    Directory of Open Access Journals (Sweden)

    Obroučka Karel

    2015-03-01

    Full Text Available The aim of this paper is a mathematical description of algorithm for controlled assembly of incinerated batch of waste. The basis for formation of batch is selected parameters of incinerated waste as its calorific value or content of pollutants or the combination of both. The numerical model will allow, based on selected criteria, to compile batch of wastes which continuously follows the previous batch, which is a prerequisite for optimized operation of incinerator. The model was prepared as for waste storage in containers, as well as for waste storage in continuously refilled boxes. The mathematical model was developed into the computer program and its functionality was verified either by practical measurements or by numerical simulations. The proposed model can be used in incinerators for hazardous and municipal waste.

  20. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...

  1. System dynamics model for hospital waste characterization and generation in developing countries.

    Science.gov (United States)

    Eleyan, Derar; Al-Khatib, Issam A; Garfield, Joy

    2013-10-01

    Waste management policy makers always face the problem of how to predict the future amount and composition of medical solid waste, which, in turn, helps to determine the most appropriate treatment, recycling and disposal strategy. An accurate prediction can assist in both the planning and design of medical solid waste management systems. Insufficient budget and unavailable management capacity are the main reasons for the scarcity of medical solid waste quantities and components historical records, which are so important in long-term system planning and short-term expansion programs. This article presents a new technique, using System Dynamics modeling, to predict generated medical solid waste in a developing urban area, based on a set of limited samples from Jenin District hospitals, Palestine. The findings of the model present the trend of medical solid waste generation together with its different components and indicate that a new forecasting approach may cover a variety of possible causative models and track inevitable uncertainties when traditional statistical least-squared regression methods are unable to handle such issues.

  2. Solid waste integrated cost analysis model: 1991 project year report. Part 2

    Energy Technology Data Exchange (ETDEWEB)

    1991-12-31

    The purpose of the City of Houston`s 1991 Solid Waste Integrated Cost Analysis Model (SWICAM) project was to continue the development of a computerized cost analysis model. This model is to provide solid waste managers with tool to evaluate the dollar cost of real or hypothetical solid waste management choices. Those choices have become complicated by the implementation of Subtitle D of the Resources Conservation and Recovery Act (RCRA) and the EPA`s Integrated Approach to managing municipal solid waste;. that is, minimize generation, maximize recycling, reduce volume (incinerate), and then bury (landfill) only the remainder. Implementation of an integrated solid waste management system involving all or some of the options of recycling, waste to energy, composting, and landfilling is extremely complicated. Factors such as hauling distances, markets, and prices for recyclable, costs and benefits of transfer stations, and material recovery facilities must all be considered. A jurisdiction must determine the cost impacts of implementing a number of various possibilities for managing, handling, processing, and disposing of waste. SWICAM employs a single Lotus 123 spreadsheet to enable a jurisdiction to predict or assess the costs of its waste management system. It allows the user to select his own process flow for waste material and to manipulate the model to include as few or as many options as he or she chooses. The model will calculate the estimated cost for those choices selected. The user can then change the model to include or exclude waste stream components, until the mix of choices suits the user. Graphs can be produced as a visual communication aid in presenting the results of the cost analysis. SWICAM also allows future cost projections to be made.

  3. Predictive models of forest dynamics.

    Science.gov (United States)

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  4. Modelling animal waste pathogen transport from agricultural land to streams

    Science.gov (United States)

    Pandey, Pramod K.; Soupir, Michelle L.; Ikenberry, Charles

    2014-03-01

    The transport of animal waste pathogens from crop land to streams can potentially elevate pathogen levels in stream water. Applying animal manure into crop land as fertilizers is a common practice in developing as well as in developed countries. Manure application into the crop land, however, can cause potential human health. To control pathogen levels in ambient water bodies such as streams, improving our understanding of pathogen transport at farm scale as well as at watershed scale is required. To understand the impacts of crop land receiving animal waste as fertilizers on stream's pathogen levels, here we investigate pathogen indicator transport at watershed scale. We exploited watershed scale hydrological model to estimate the transport of pathogens from the crop land to streams. Pathogen indicator levels (i.e., E. coli levels) in the stream water were predicted. With certain assumptions, model results are reasonable. This study can be used as guidelines for developing the models for calculating the impacts of crop land's animal manure on stream water.

  5. Challenges in Modeling the Degradation of Ceramic Waste Forms

    Energy Technology Data Exchange (ETDEWEB)

    Devanathan, Ramaswami; Gao, Fei; Sun, Xin

    2011-09-01

    We identify the state of the art, gaps in current understanding, and key research needs in the area of modeling the long-term degradation of ceramic waste forms for nuclear waste disposition. The directed purpose of this report is to define a roadmap for Waste IPSC needs to extend capabilities of waste degradation to ceramic waste forms, which overlaps with the needs of the subconsinuum scale of FMM interests. The key knowledge gaps are in the areas of (i) methodology for developing reliable interatomic potentials to model the complex atomic-level interactions in waste forms; (ii) characterization of water interactions at ceramic surfaces and interfaces; and (iii) extension of atomic-level insights to the long time and distance scales relevant to the problem of actinide and fission product immobilization.

  6. Challenges in Modeling the Degradation of Ceramic Waste Forms

    Energy Technology Data Exchange (ETDEWEB)

    Devanathan, Ramaswami; Gao, Fei; Sun, Xin

    2011-09-01

    We identify the state of the art, gaps in current understanding, and key research needs in the area of modeling the long-term degradation of ceramic waste forms for nuclear waste disposition. The directed purpose of this report is to define a roadmap for Waste IPSC needs to extend capabilities of waste degradation to ceramic waste forms, which overlaps with the needs of the subconsinuum scale of FMM interests. The key knowledge gaps are in the areas of (i) methodology for developing reliable interatomic potentials to model the complex atomic-level interactions in waste forms; (ii) characterization of water interactions at ceramic surfaces and interfaces; and (iii) extension of atomic-level insights to the long time and distance scales relevant to the problem of actinide and fission product immobilization.

  7. Modeling and low-level waste management: an interagency workshop

    Energy Technology Data Exchange (ETDEWEB)

    Little, C.A.; Stratton, L.E. (comps.)

    1980-01-01

    The interagency workshop on Modeling and Low-Level Waste Management was held on December 1-4, 1980 in Denver, Colorado. Twenty papers were presented at this meeting which consisted of three sessions. First, each agency presented its point of view concerning modeling and the need for models in low-level radioactive waste applications. Second, a larger group of more technical papers was presented by persons actively involved in model development or applications. Last of all, four workshops were held to attempt to reach a consensus among participants regarding numerous waste modeling topics. Abstracts are provided for the papers presented at this workshop.

  8. Standard practice for prediction of the long-term behavior of materials, including waste forms, used in engineered barrier systems (EBS) for geological disposal of high-level radioactive waste

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2007-01-01

    1.1 This practice describes test methods and data analyses used to develop models for the prediction of the long-term behavior of materials, such as engineered barrier system (EBS) materials and waste forms, used in the geologic disposal of spent nuclear fuel (SNF) and other high-level nuclear waste in a geologic repository. The alteration behavior of waste form and EBS materials is important because it affects the retention of radionuclides by the disposal system. The waste form and EBS materials provide a barrier to release either directly (as in the case of waste forms in which the radionuclides are initially immobilized), or indirectly (as in the case of containment materials that restrict the ingress of groundwater or the egress of radionuclides that are released as the waste forms and EBS materials degrade). 1.1.1 Steps involved in making such predictions include problem definition, testing, modeling, and model confirmation. 1.1.2 The predictions are based on models derived from theoretical considerat...

  9. Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC).

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, Peter Andrew

    2011-12-01

    The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. Achieving the objective of modeling the performance of a disposal scenario requires describing processes involved in waste form degradation and radionuclide release at the subcontinuum scale, beginning with mechanistic descriptions of chemical reactions and chemical kinetics at the atomic scale, and upscaling into effective, validated constitutive models for input to high-fidelity continuum scale codes for coupled multiphysics simulations of release and transport. Verification and validation (V&V) is required throughout the system to establish evidence-based metrics for the level of confidence in M&S codes and capabilities, including at the subcontiunuum scale and the constitutive models they inform or generate. This Report outlines the nature of the V&V challenge at the subcontinuum scale, an approach to incorporate V&V concepts into subcontinuum scale modeling and simulation (M&S), and a plan to incrementally incorporate effective V&V into subcontinuum scale M&S destined for use in the NEAMS Waste IPSC work flow to meet requirements of quantitative confidence in the constitutive models informed by subcontinuum scale phenomena.

  10. Household Food Insecurity May Predict Underweightand Wasting among Children Aged 24-59 Months.

    Science.gov (United States)

    Abdurahman, Ahmed A; Mirzaei, Khadijeh; Dorosty, Ahmed Reza; Rahimiforoushani, A; Kedir, Haji

    2016-01-01

    The aim of this study was to examine the association between household food insecurity and nutritional status among children aged 24-59 months in Haromaya District. Children (N = 453) aged 24-59 months were recruited in a community-based cross-sectional survey with a representative sample of households selected by a multistage sampling procedure in Haromaya District. Household Food Insecurity Access Scale and anthropometry were administered. Multinomial logistic regression models were applied to select variables that are candidate for multivariable model. The prevalences of stunting, underweight, and wasting among children aged 24-59 months were 61.1%, 28.1%, and 11.8%, respectively. The mean household food insecurity access scale score was 3.34, and 39.7% of households experienced some degree of food insecurity. By logistic regression analysis and after adjusting for the confounding factors, household food insecurity was significantly predictive of underweight (AOR = 2.48, CI = 1.17-5.24, p = .05) and chronic energy deficiency (AOR = 0.47, CI = 0.23-0.97, p = .04) and marginally significant for wasting (AOR = 0.53, CI = 0.27-1.03, p = .06). It is concluded that household food security improves child growth and nutritional status.

  11. Leaching, geochemical modelling and field verification of a municipal solid waste and a predominantly non-degradable waste landfill.

    Science.gov (United States)

    van der Sloot, H A; Kosson, D S; van Zomeren, A

    2017-05-01

    In spite of the known heterogeneity, wastes destined for landfilling can be characterised for their leaching behaviour by the same protocols as soil, contaminated soil, sediments, sludge, compost, wood, waste and construction products. Characterisation leaching tests used in conjunction with chemical speciation modelling results in much more detailed insights into release controlling processes and factors than single step batch leaching tests like TCLP (USEPA) and EN12457 (EU Landfill Directive). Characterisation testing also can provide the potential for mechanistic impact assessments by making use of a chemical speciation fingerprint (CSF) derived from pH dependence leaching test results. This CSF then forms the basis for subsequent chemical equilibrium and reactive transport modelling to assess environmental impact in a landfill scenario under relevant exposure conditions, including conditions not readily evaluated through direct laboratory testing. This approach has been applied to municipal solid waste (MSW) and predominantly non-degradable waste (PNW) that is representative of a significant part of waste currently being landfilled. This work has shown that a multi-element modelling approach provides a useful description of the release from each of these matrices because relevant release controlling properties and parameters (mineral dissolution/precipitation, sorption on Fe and Al oxides, clay interaction, interaction with dissolved and particulate organic carbon and incorporation in solid solutions) are taken into consideration. Inclusion of dissolved and particulate organic matter in the model is important to properly describe release of the low concentration trace constituents observed in the leachate. The CSF allows the prediction of release under different redox and degradation conditions in the landfill by modifying the redox status and level of dissolved and particulate organic matter in the model runs. The CSF for MSW provides a useful starting point

  12. Optimising the anaerobic co-digestion of urban organic waste using dynamic bioconversion mathematical modelling.

    Science.gov (United States)

    Fitamo, T; Boldrin, A; Dorini, G; Boe, K; Angelidaki, I; Scheutz, C

    2016-12-01

    Mathematical anaerobic bioconversion models are often used as a convenient way to simulate the conversion of organic materials to biogas. The aim of the study was to apply a mathematical model for simulating the anaerobic co-digestion of various types of urban organic waste, in order to develop strategies for controlling and optimising the co-digestion process. The model parameters were maintained in the same way as the original dynamic bioconversion model, albeit with minor adjustments, to simulate the co-digestion of food and garden waste with mixed sludge from a wastewater treatment plant in a continuously stirred tank reactor. The model's outputs were validated with experimental results obtained in thermophilic conditions, with mixed sludge as a single substrate and urban organic waste as a co-substrate at hydraulic retention times of 30, 20, 15 and 10 days. The predicted performance parameter (methane productivity and yield) and operational parameter (concentration of ammonia and volatile fatty acid) values were reasonable and displayed good correlation and accuracy. The model was later applied to identify optimal scenarios for an urban organic waste co-digestion process. The simulation scenario analysis demonstrated that increasing the amount of mixed sludge in the co-substrate had a marginal effect on the reactor performance. In contrast, increasing the amount of food waste and garden waste resulted in improved performance.

  13. Managing Dog Waste: Campaign Insights from the Health Belief Model

    Science.gov (United States)

    Typhina, Eli; Yan, Changmin

    2014-01-01

    Aiming to help municipalities develop effective education and outreach campaigns to reduce stormwater pollutants, such as pet waste, this study applied the Health Belief Model (HBM) to identify perceptions of dog waste and corresponding collection behaviors from dog owners living in a small U.S. city. Results of 455 online survey responses…

  14. Impact of microbial activity on the radioactive waste disposal: long term prediction of biocorrosion processes.

    Science.gov (United States)

    Libert, Marie; Schütz, Marta Kerber; Esnault, Loïc; Féron, Damien; Bildstein, Olivier

    2014-06-01

    This study emphasizes different experimental approaches and provides perspectives to apprehend biocorrosion phenomena in the specific disposal environment by investigating microbial activity with regard to the modification of corrosion rate, which in turn can have an impact on the safety of radioactive waste geological disposal. It is found that iron-reducing bacteria are able to use corrosion products such as iron oxides and "dihydrogen" as new energy sources, especially in the disposal environment which contains low amounts of organic matter. Moreover, in the case of sulphate-reducing bacteria, the results show that mixed aerobic and anaerobic conditions are the most hazardous for stainless steel materials, a situation which is likely to occur in the early stage of a geological disposal. Finally, an integrated methodological approach is applied to validate the understanding of the complex processes and to design experiments aiming at the acquisition of kinetic data used in long term predictive modelling of biocorrosion processes.

  15. Prediction of effluent concentration in a wastewater treatment plant using machine learning models.

    Science.gov (United States)

    Guo, Hong; Jeong, Kwanho; Lim, Jiyeon; Jo, Jeongwon; Kim, Young Mo; Park, Jong-pyo; Kim, Joon Ha; Cho, Kyung Hwa

    2015-06-01

    Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen (T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models-artificial neural networks (ANNs) and support vector machines (SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination (R2), Nash-Sutcliff efficiency (NSE), relative efficiency criteria (drel). Additionally, Latin-Hypercube one-factor-at-a-time (LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage. However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process. Copyright © 2015. Published by Elsevier B.V.

  16. A conflict model for the international hazardous waste disposal dispute

    Energy Technology Data Exchange (ETDEWEB)

    Hu Kaixian, E-mail: k2hu@engmail.uwaterloo.ca [Department of Systems Design Engineering, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1 (Canada); Hipel, Keith W., E-mail: kwhipel@uwaterloo.ca [Department of Systems Design Engineering, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1 (Canada); Fang, Liping, E-mail: lfang@ryerson.ca [Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3 (Canada)

    2009-12-15

    A multi-stage conflict model is developed to analyze international hazardous waste disposal disputes. More specifically, the ongoing toxic waste conflicts are divided into two stages consisting of the dumping prevention and dispute resolution stages. The modeling and analyses, based on the methodology of graph model for conflict resolution (GMCR), are used in both stages in order to grasp the structure and implications of a given conflict from a strategic viewpoint. Furthermore, a specific case study is investigated for the Ivory Coast hazardous waste conflict. In addition to the stability analysis, sensitivity and attitude analyses are conducted to capture various strategic features of this type of complicated dispute.

  17. Los Alamos Waste Management Cost Estimation Model; Final report: Documentation of waste management process, development of Cost Estimation Model, and model reference manual

    Energy Technology Data Exchange (ETDEWEB)

    Matysiak, L.M.; Burns, M.L.

    1994-03-01

    This final report completes the Los Alamos Waste Management Cost Estimation Project, and includes the documentation of the waste management processes at Los Alamos National Laboratory (LANL) for hazardous, mixed, low-level radioactive solid and transuranic waste, development of the cost estimation model and a user reference manual. The ultimate goal of this effort was to develop an estimate of the life cycle costs for the aforementioned waste types. The Cost Estimation Model is a tool that can be used to calculate the costs of waste management at LANL for the aforementioned waste types, under several different scenarios. Each waste category at LANL is managed in a separate fashion, according to Department of Energy requirements and state and federal regulations. The cost of the waste management process for each waste category has not previously been well documented. In particular, the costs associated with the handling, treatment and storage of the waste have not been well understood. It is anticipated that greater knowledge of these costs will encourage waste generators at the Laboratory to apply waste minimization techniques to current operations. Expected benefits of waste minimization are a reduction in waste volume, decrease in liability and lower waste management costs.

  18. Waste management system optimisation for Southern Italy with MARKAL model

    Energy Technology Data Exchange (ETDEWEB)

    Salvia, M.; Cosmi, C. [Istituto di Metodologie Avanzate di Analisi Ambientale, Consiglio Nazionale delle Ricerche, C. da S. Loja, 85050 (PZ) Tito Scalo (Italy); Macchiato, M. [Dipartimento di Scienze Fisiche, Universita Federico II, Via Cintia, 80126 Napoli (Italy); Mangiamele, L. [Dipartimento di Ingegneria e Fisica dell' Ambiente, Universita degli Studi della Basilicata, C. da Macchia Romana, 85100 Potenza (Italy)

    2002-01-01

    The MARKAL models generator was utilised to build up a comprehensive model of the anthropogenic activities system which points out the linkages between productive processes and waste disposal technologies. The aim of such a study is to determine the optimal configuration of the waste management system for the Basilicata region (Southern Italy), in order to support the definition of the regional waste management plan in compliance with the Italian laws. A sensitivity analysis was performed to evaluate the influence of landfilling fees on the choice of waste processing technologies, in order to foster waste management strategies which are environmentally sustainable, economically affordable and highly efficient. The results show the key role of separate collection and mechanical pre-treatments in the achievement of the legislative targets.

  19. MODELING ANALYSIS FOR GROUT HOPPER WASTE TANK

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S.

    2012-01-04

    The Saltstone facility at Savannah River Site (SRS) has a grout hopper tank to provide agitator stirring of the Saltstone feed materials. The tank has about 300 gallon capacity to provide a larger working volume for the grout nuclear waste slurry to be held in case of a process upset, and it is equipped with a mechanical agitator, which is intended to keep the grout in motion and agitated so that it won't start to set up. The primary objective of the work was to evaluate the flow performance for mechanical agitators to prevent vortex pull-through for an adequate stirring of the feed materials and to estimate an agitator speed which provides acceptable flow performance with a 45{sup o} pitched four-blade agitator. In addition, the power consumption required for the agitator operation was estimated. The modeling calculations were performed by taking two steps of the Computational Fluid Dynamics (CFD) modeling approach. As a first step, a simple single-stage agitator model with 45{sup o} pitched propeller blades was developed for the initial scoping analysis of the flow pattern behaviors for a range of different operating conditions. Based on the initial phase-1 results, the phase-2 model with a two-stage agitator was developed for the final performance evaluations. A series of sensitivity calculations for different designs of agitators and operating conditions have been performed to investigate the impact of key parameters on the grout hydraulic performance in a 300-gallon hopper tank. For the analysis, viscous shear was modeled by using the Bingham plastic approximation. Steady state analyses with a two-equation turbulence model were performed. All analyses were based on three-dimensional results. Recommended operational guidance was developed by using the basic concept that local shear rate profiles and flow patterns can be used as a measure of hydraulic performance and spatial stirring. Flow patterns were estimated by a Lagrangian integration technique along

  20. MODELING ANALYSIS FOR GROUT HOPPER WASTE TANK

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S.

    2012-01-04

    The Saltstone facility at Savannah River Site (SRS) has a grout hopper tank to provide agitator stirring of the Saltstone feed materials. The tank has about 300 gallon capacity to provide a larger working volume for the grout nuclear waste slurry to be held in case of a process upset, and it is equipped with a mechanical agitator, which is intended to keep the grout in motion and agitated so that it won't start to set up. The primary objective of the work was to evaluate the flow performance for mechanical agitators to prevent vortex pull-through for an adequate stirring of the feed materials and to estimate an agitator speed which provides acceptable flow performance with a 45{sup o} pitched four-blade agitator. In addition, the power consumption required for the agitator operation was estimated. The modeling calculations were performed by taking two steps of the Computational Fluid Dynamics (CFD) modeling approach. As a first step, a simple single-stage agitator model with 45{sup o} pitched propeller blades was developed for the initial scoping analysis of the flow pattern behaviors for a range of different operating conditions. Based on the initial phase-1 results, the phase-2 model with a two-stage agitator was developed for the final performance evaluations. A series of sensitivity calculations for different designs of agitators and operating conditions have been performed to investigate the impact of key parameters on the grout hydraulic performance in a 300-gallon hopper tank. For the analysis, viscous shear was modeled by using the Bingham plastic approximation. Steady state analyses with a two-equation turbulence model were performed. All analyses were based on three-dimensional results. Recommended operational guidance was developed by using the basic concept that local shear rate profiles and flow patterns can be used as a measure of hydraulic performance and spatial stirring. Flow patterns were estimated by a Lagrangian integration technique along

  1. A Spanish model for quantification and management of construction waste.

    Science.gov (United States)

    Solís-Guzmán, Jaime; Marrero, Madelyn; Montes-Delgado, Maria Victoria; Ramírez-de-Arellano, Antonio

    2009-09-01

    Currently, construction and demolition waste (C&D waste) is a worldwide issue that concerns not only governments but also the building actors involved in construction activity. In Spain, a new national decree has been regulating the production and management of C&D waste since February 2008. The present work describes the waste management model that has inspired this decree: the Alcores model implemented with good results in Los Alcores Community (Seville, Spain). A detailed model is also provided to estimate the volume of waste that is expected to be generated on the building site. The quantification of C&D waste volume, from the project stage, is essential for the building actors to properly plan and control its disposal. This quantification model has been developed by studying 100 dwelling projects, especially their bill of quantities, and defining three coefficients to estimate the demolished volume (CT), the wreckage volume (CR) and the packaging volume (CE). Finally, two case studies are included to illustrate the usefulness of the model to estimate C&D waste volume in both new construction and demolition projects.

  2. Modeling transient heat transfer in nuclear waste repositories.

    Science.gov (United States)

    Yang, Shaw-Yang; Yeh, Hund-Der

    2009-09-30

    The heat of high-level nuclear waste may be generated and released from a canister at final disposal sites. The waste heat may affect the engineering properties of waste canisters, buffers, and backfill material in the emplacement tunnel and the host rock. This study addresses the problem of the heat generated from the waste canister and analyzes the heat distribution between the buffer and the host rock, which is considered as a radial two-layer heat flux problem. A conceptual model is first constructed for the heat conduction in a nuclear waste repository and then mathematical equations are formulated for modeling heat flow distribution at repository sites. The Laplace transforms are employed to develop a solution for the temperature distributions in the buffer and the host rock in the Laplace domain, which is numerically inverted to the time-domain solution using the modified Crump method. The transient temperature distributions for both the single- and multi-borehole cases are simulated in the hypothetical geological repositories of nuclear waste. The results show that the temperature distributions in the thermal field are significantly affected by the decay heat of the waste canister, the thermal properties of the buffer and the host rock, the disposal spacing, and the thickness of the host rock at a nuclear waste repository.

  3. System dynamic modeling on construction waste management in Shenzhen, China.

    Science.gov (United States)

    Tam, Vivian W Y; Li, Jingru; Cai, Hong

    2014-05-01

    This article examines the complexity of construction waste management in Shenzhen, Mainland China. In-depth analysis of waste generation, transportation, recycling, landfill and illegal dumping of various inherent management phases is explored. A system dynamics modeling using Stella model is developed. Effects of landfill charges and also penalties from illegal dumping are also simulated. The results show that the implementation of comprehensive policy on both landfill charges and illegal dumping can effectively control the illegal dumping behavior, and achieve comprehensive construction waste minimization. This article provides important recommendations for effective policy implementation and explores new perspectives for Shenzhen policy makers.

  4. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre

    2005-07-01

    Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.

  5. Generation amount prediction and material flow analysis of electronic waste: a case study in Beijing, China.

    Science.gov (United States)

    Liu, Xianbing; Tanaka, Masaru; Matsui, Yasuhiro

    2006-10-01

    The draft legislation on e-waste prepared by the Chinese national government assigns management responsibility to local governments. It is an urgent task for the municipal government to plan an effective system as soon as possible to divert the e-waste flow from the existing informal e-waste recycling processes. This paper presents a case study implemented in Beijing, the capital city of China, with the purpose of predicting the amount of obsolete equipment for five main kinds of electronic appliances from urban households and to analyse the flow after the end of their useful phase. The amount to be handled was 885,354 units in 2005 and is predicted to double by 2010. Due to consumption growth and the expansion of urbanization it is estimated that the amount will increase to approximate 2,820,000 units by 2020: 70% of the obsolete appliances will be awaiting collection for possible recycling, 7% will be stored at the owner's home for 1 year on average and 4% will be discarded directly and enter the municipal solid waste collecting system. The remaining items will be reused for about 3 years on average after the change of ownership. The results of this study will assist the waste management authorities of Beijing to plan the collecting system and facilities needed for management of e-waste generated in the near future.

  6. Development of a Novel Food Waste Collection Kiosk and Waste-to-Energy Business Model

    Directory of Open Access Journals (Sweden)

    Matthew Franchetti

    2016-08-01

    Full Text Available The U.S. generates more than 37 million metric tons of food waste each year, and over 95% of it is disposed of at U.S. landfills. This paper describes the development of a novel food waste collection kiosk and business model called “Greenbox” that will collect and store food waste from households and restaurants with incentives for user participation to spur food waste-to-energy production in a local community. Greenbox offers a low-cost collection point to divert food waste from landfills, reduce greenhouse gases from decomposition, and aid in generating cleaner energy. A functional prototype was successfully developed by a team of engineering students and a business model was created as part of a senior design capstone course. Each Greenbox unit has the potential to reduce 275 metric tons of food waste per year, remove 1320 kg of greenhouse gases, and create 470,000 liters of methane gas while providing a payback period of 4.2 years and a rate of return of 14.9%.

  7. Measurements and modeling of gas fluxes in unsaturated mine waste materials

    Energy Technology Data Exchange (ETDEWEB)

    Kabwe, L.K.

    2008-07-01

    A technique known as dynamic closed chamber (DDC) was recently developed to measure carbon dioxide (CO{sub 2}) fluxes from the soil surface to the atmosphere. The field application of the DCC was investigated in this thesis with a particular focus on quantifying reaction rates in 2 waste-rock piles at the Key Lake uranium mine in northern Saskatchewan. The dominant geochemical reactions in both waste-rock piles were not typical of acid rock drainage (ARD) waste-rock piles. The CO{sub 2} fluxes measured in this study occur in the organic material underlying the waste rocks. The study provided a complete suite of measurements needed to characterize spatial distribution of CO{sub 2} fluxes on larger-scale studies of waste-rock piles. In comparison to other CO{sub 2} flux measuring techniques, the DCC method accurately quantified field soil respiration and had an added advantage in terms of speed and repeatability. The DCC was also used to investigate CO{sub 2} fluxes under the climatic variables that affect soil water content in waste-rock piles. A simple model for predicting the effects of soil water content on CO{sub 2} diffusion coefficient and concentration profiles was developed and verified. It was concluded that the DCC method is suitable for field applications to quantify CO{sub 2} fluxes and to characterize the spatial and temporal dynamics of CO{sub 2} fluxes from unsaturated C-horizon soils and waste-rock piles.

  8. Buried Waste Integrated Demonstration stakeholder involvement model

    Energy Technology Data Exchange (ETDEWEB)

    Kaupanger, R.M.; Kostelnik, K.M.; Milam, L.M.

    1994-04-01

    The Buried Waste Integrated Demonstration (BWID) is a program funded by the US Department of Energy (DOE) Office of Technology Development. BWID supports the applied research, development, demonstration, and evaluation of a suite of advanced technologies that together form a comprehensive remediation system for the effective and efficient remediation of buried waste. Stakeholder participation in the DOE Environmental Management decision-making process is critical to remediation efforts. Appropriate mechanisms for communication with the public, private sector, regulators, elected officials, and others are being aggressively pursued by BWID to permit informed participation. This document summarizes public outreach efforts during FY-93 and presents a strategy for expanded stakeholder involvement during FY-94.

  9. A model for heat flow in deep borehole disposals of high-level nuclear waste

    Science.gov (United States)

    Gibb, Fergus G. F.; Travis, Karl P.; McTaggart, Neil A.; Burley, David

    2008-05-01

    Deep borehole disposal (DBD) is emerging as a viable alternative to mined repositories for many forms of highly radioactive waste. It is geologically safer, more secure, less environmentally disruptive and potentially more cost-effective. All high-level wastes generate heat leading to elevated temperatures in and around the disposal. In some versions of DBD this heat is an essential part of the disposal while in others it affects the performances of materials and waste forms and can threaten the success of the disposal. Different versions of DBD are outlined, for all of which it is essential to predict the distribution of temperature with time. A generic physical model is established and a mathematical model set up involving the transient conductive heat flow differential equation for a cylindrical source term with realistic decay. This equation is solved using the method of Finite Differences. A Fortran computer code (GRANITE) has been developed for the model in the context of DBD and validated against theoretical and other benchmarks. The limitations of the model, code, input parameters and data used are discussed and it is concluded that the model provides a satisfactory basis for predicting temperatures in DBD. Examples of applications to some DBD scenarios are given and it is shown that the results are essential to the design strategy of the DBD versions, geometric details and choice of materials used. Without such modeling it would be impossible to progress DBD of nuclear wastes; something that is now being given serious consideration in several countries.

  10. PREDICT : model for prediction of survival in localized prostate cancer

    NARCIS (Netherlands)

    Kerkmeijer, Linda G W; Monninkhof, Evelyn M.; van Oort, Inge M.; van der Poel, Henk G.; de Meerleer, Gert; van Vulpen, Marco

    2016-01-01

    Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I

  11. BIOLEACH: Coupled modeling of leachate and biogas production on solid waste landfills

    Science.gov (United States)

    Rodrigo-Clavero, Maria-Elena; Rodrigo-Ilarri, Javier

    2015-04-01

    One of the most important factors to address when performing the environmental impact assessment of urban solid waste landfills is to evaluate the leachate production. Leachate management (collection and treatment) is also one of the most relevant economical aspects to take into account during the landfill life. Leachate is formed as a solution of biological and chemical components during operational and post-operational phases on urban solid waste landfills as a combination of different processes that involve water gains and looses inside the solid waste mass. Infiltration of external water coming from precipitation is the most important component on this water balance. However, anaerobic waste decomposition and biogas formation processes play also a role on the balance as water-consuming processes. The production of leachate one biogas is therefore a coupled process. Biogas production models usually consider optimal conditions of water content on the solid waste mass. However, real conditions during the operational phase of the landfill may greatly differ from these optimal conditions. In this work, the first results obtained to predict both the leachate and the biogas production as a single coupled phenomenon on real solid waste landfills are shown. The model is applied on a synthetic case considering typical climatological conditions of Mediterranean catchments.

  12. Energy recovery from solid waste. [production engineering model

    Science.gov (United States)

    Dalton, C.; Huang, C. J.

    1974-01-01

    A recent group study on the problem of solid waste disposal provided a decision making model for a community to use in determining the future for its solid waste. The model is a combination of the following factors: technology, legal, social, political, economic and environmental. An assessment of local or community needs determines what form of energy recovery is desirable. A market for low pressure steam or hot water would direct a community to recover energy from solid waste by incineration to generate steam. A fuel gas could be produced by a process known as pyrolysis if there is a local market for a low heating value gaseous fuel. Solid waste can also be used directly as a fuel supplemental to coal in a steam generator. An evaluation of these various processes is made.

  13. Energy recovery from solid waste. [production engineering model

    Science.gov (United States)

    Dalton, C.; Huang, C. J.

    1974-01-01

    A recent group study on the problem of solid waste disposal provided a decision making model for a community to use in determining the future for its solid waste. The model is a combination of the following factors: technology, legal, social, political, economic and environmental. An assessment of local or community needs determines what form of energy recovery is desirable. A market for low pressure steam or hot water would direct a community to recover energy from solid waste by incineration to generate steam. A fuel gas could be produced by a process known as pyrolysis if there is a local market for a low heating value gaseous fuel. Solid waste can also be used directly as a fuel supplemental to coal in a steam generator. An evaluation of these various processes is made.

  14. Tank waste remediation system simulation analysis retrieval model

    Energy Technology Data Exchange (ETDEWEB)

    Fordham, R.A.

    1996-09-30

    The goal of simulation was to test tll(., consequences of assumptions. For the TWRS SIMAN Retrieval Model, l@lie specific assumptions are primarily defined with respect to waste processing arid transfer timing. The model tracks 73 chem1913ical constituents from underground waste tanks to glass; yet, the detailed (@hemistrv and complete set of unit operations of the TWRS process flow sheet are represented only at the level necessary to define the waste processing and transfer logic and to estimate the feed composition for the treatment facilities. Tlierefor(,, the model should net be regarded as a substitute for the TWRS process flow sheet. Pra(!ticallv the model functions as a dyrt(imic extension of the flow sheet model. I I The following sections present the description, assunipt@ions, architecture, arid evalua- tion of the TWRS SIMAN Retrieval Model. Section 2 describes the model in terms of an overview of the processes represented. Section 3 presents the assumptions for the simulation model. Specific assumptions 9.tt(l parameter values used in the model are provided for waste retrieval, pretreatment, low-level waste (LLNN7) immobilization, and high-level waste (HLW) immobilization functions. Section 4 describes the model in terms of its functional architec- rare to d(@fine a basis for a systematic evaluation of the model. Finally, Section 5 documents an independent test and evaluation of the niodel`s performance (i.e., the verification and validation). Additionally, Appendix A gives a complete listing of the tank inventory used. Appendix B documents the verification and validation plan that was used for the (Section 5) evaluation work. A description and listing of all the model variables is given in Appendix C along with a complete source listing.

  15. Predictive Modeling of Cardiac Ischemia

    Science.gov (United States)

    Anderson, Gary T.

    1996-01-01

    The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.

  16. CHEMICAL ANALYSIS OF SIMULATED HIGH LEVEL WASTE GLASSES TO SUPPORT SULFATE SOLUBILITY MODELING

    Energy Technology Data Exchange (ETDEWEB)

    Fox, K.; Marra, J.

    2014-08-14

    The U.S. Department of Energy (DOE), Office of Environmental Management (EM) is sponsoring an international, collaborative project to develop a fundamental model for sulfate solubility in nuclear waste glass. The solubility of sulfate has a significant impact on the achievable waste loading for nuclear waste forms both within the DOE complex and to some extent at U.K. sites. The development of enhanced borosilicate glass compositions with improved sulfate solubility will allow for higher waste loadings and accelerated cleanup missions. Much of the previous work on improving sulfate retention in waste glasses has been done on an empirical basis, making it difficult to apply the findings to future waste compositions despite the large number of glass systems studied. A more fundamental, rather than empirical, model of sulfate solubility in glass, under development at Sheffield Hallam University (SHU), could provide a solution to the issues of sulfate solubility. The model uses the normalized cation field strength index as a function of glass composition to predict sulfate capacity, and has shown early success for some glass systems. The objective of the current scope is to mature the sulfate solubility model to the point where it can be used to guide glass composition development for DOE waste vitrification efforts, allowing for enhanced waste loadings and waste throughput. A series of targeted glass compositions was selected to resolve data gaps in the current model. SHU fabricated these glasses and sent samples to the Savannah River National Laboratory (SRNL) for chemical composition analysis. SHU will use the resulting data to enhance the sulfate solubility model and resolve any deficiencies. In this report, SRNL provides chemical analyses for simulated waste glasses fabricated SHU in support of sulfate solubility model development. A review of the measured compositions revealed that there are issues with the B{sub 2}O{sub 3} and Fe{sub 2}O{sub 3} concentrations

  17. Prediction and Control of Air Flow in Acid-Generating Waste Rock Dumps

    Science.gov (United States)

    Wels, C.; Lefebvre, R.; Robertson, A. M.

    2004-05-01

    Air movement and associated oxygen transport through waste rock dumps has the potential to significantly enhance the rate of oxidation of pyrite-bearing material. While this is a desired outcome for most heap leach operations, airflow in waste rock storage facilities can result in significant increases in generation and acceleration of acid rock drainage. Hence, a good understanding of internal airflow through waste rock dumps is required to control ARD and minimize any associated liability. The principal mechanisms contributing to airflow and oxygen transport in a waste rock pile include (i) diffusion, (ii) advection due to a thermal gradient (chimney effect) and/or wind pressure gradients and (iii) advection due to barometric pumping. While diffusion is typically limited to a near-surface zone of a few meters depth, advection and barometric pumping have the potential to move air (and oxygen) to much greater depths into the pile. In general, the more permeable the waste rock material, and the greater the height-to-width ratio of the waste rock pile, the greater is the potential for advective air movement. The reactivity of the waste rock material as well as the coarseness (hence air permeability), and the spatial variability of these properties within a pile, have a strong influence on the magnitude of thermally induced advection. In contrast, air movement due to barometric pumping is controlled by the waste rock porosity, changes in ambient air pressure and the heterogeneity of air permeability of the waste rock dump. Results of field monitoring and numerical modeling using TOUGH AMD are presented to illustrate the concepts on air movement in waste rock piles. During the design and construction phase, airflow can be controlled by judicious placement of reactive waste rock and use of selective placement techniques to control the internal structure of the waste rock facility (e.g. introduction of horizontal layering, prevention of inclined, high

  18. Numerical weather prediction model tuning via ensemble prediction system

    Science.gov (United States)

    Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

    2011-12-01

    This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

  19. CFD modeling and experience of waste-to-energy plant burning waste wood

    OpenAIRE

    Rajh, B.; Yin, Chungen; Samec, N.; M. HRIBERSEK; Kokalj, F.

    2013-01-01

    Computational Fluid Dynamics (CFD) is being increasingly used in industry for in-depth understanding of the fundamental mixing, combustion, heat transfer and pollutant formation in combustion processes and for design and optimization of Waste-to-Energy (WtE) plants. In this paper, CFD modeling of waste wood combustion in a 13 MW grate-fired boiler in a WtE plant is presented. As a validation effort, the temperature profiles at a number of ports in the furnace are measured and the experimental...

  20. Mass Transfer Model for a Breached Waste Package

    Energy Technology Data Exchange (ETDEWEB)

    C. Hsu; J. McClure

    2004-07-26

    The degradation of waste packages, which are used for the disposal of spent nuclear fuel in the repository, can result in configurations that may increase the probability of criticality. A mass transfer model is developed for a breached waste package to account for the entrainment of insoluble particles. In combination with radionuclide decay, soluble advection, and colloidal transport, a complete mass balance of nuclides in the waste package becomes available. The entrainment equations are derived from dimensionless parameters such as drag coefficient and Reynolds number and based on the assumption that insoluble particles are subjected to buoyant force, gravitational force, and drag force only. Particle size distributions are utilized to calculate entrainment concentration along with geochemistry model abstraction to calculate soluble concentration, and colloid model abstraction to calculate colloid concentration and radionuclide sorption. Results are compared with base case geochemistry model, which only considers soluble advection loss.

  1. Modelling agronomic properties of Technosols constructed with urban wastes.

    Science.gov (United States)

    Rokia, S; Séré, G; Schwartz, C; Deeb, M; Fournier, F; Nehls, T; Damas, O; Vidal-Beaudet, L

    2014-11-01

    The greening of urban and suburban areas requires large amounts of arable earth that is a non-renewable resource. However, concentration of population in cities leads to the production of high amounts of wastes and by-products that are nowadays partly recycled as a resource and quite systematically exported out of urban areas. To preserve natural soil resources, a strategy of waste recycling as fertile substitutes is proposed. Eleven wastes are selected for their environmental harmlessness and their contrasted physico-chemical properties for their potential use in pedological engineering. The aim is (i) to demonstrate the feasibility of the formulation of fertile substrates exclusively with wastes and (ii) to model their physico-chemical properties following various types, number and proportions of constitutive wastes. Twenty-five binary and ternary combinations are tested at different ratios for total carbon, Olsen available phosphorus, cation exchange capacity, water pH, water retention capacity and bulk density. Dose-response curves describe the variation of physico-chemical properties of mixtures depending on the type and ratio of selected wastes. If these mixtures mainly mimic natural soils, some of them present more extreme urban soil features, especially for pH and P(Olsen). The fertility of the new substrates is modelled by multilinear regressions for the main soil properties.

  2. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...

  3. Model of truly closed circuit of waste stream flow in metallurgical enterprise

    Directory of Open Access Journals (Sweden)

    B. Gajdzik

    2014-04-01

    Full Text Available The publication presents flows of metallurgical waste in manufacturing metallurgical enterprise. On the basis of analysis the structure of waste flows and the way of waste management within the enterprise or outside it were described. In the observation of the metallurgical waste flow a universal model of waste flow structure was created. It may be used in waste management of a metallurgical enterprise with full production cycle (from raw materials processes, through steel production up to final products.

  4. An evaluation of the applicability of the EPA Organic Leachate Model to leaching of solvent and non-solvent wastes

    OpenAIRE

    Bosserman, Carolyn Whitney

    1989-01-01

    The author evaluated the applicability of the Environmental Protection Agency's Organic Leachate Model to wastes containing organic solvents and other organic compounds ("non-solvents"), and determined that the model tends to overestimate the leaching of organic solvents and other organic compounds. Furthermore, when evaluated for its ability to predict leaching of organic compounds, the model was found to predict the leaching of organic solvent compounds with some accuracy, with a correlatio...

  5. Mixture experiment techniques for reducing the number of components applied for modeling waste glass sodium release

    Energy Technology Data Exchange (ETDEWEB)

    Piepel, G.; Redgate, T. [Pacific Northwest National Lab., Richland, WA (United States). Statistics Group

    1997-12-01

    Statistical mixture experiment techniques were applied to a waste glass data set to investigate the effects of the glass components on Product Consistency Test (PCT) sodium release (NR) and to develop a model for PCT NR as a function of the component proportions. The mixture experiment techniques indicate that the waste glass system can be reduced from nine to four components for purposes of modeling PCT NR. Empirical mixture models containing four first-order terms and one or two second-order terms fit the data quite well, and can be used to predict the NR of any glass composition in the model domain. The mixture experiment techniques produce a better model in less time than required by another approach.

  6. Predictive Model Assessment for Count Data

    Science.gov (United States)

    2007-09-05

    critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts...the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. We consider a recent suggestion by Baker and...Figure 5. Boxplots for various scores for patent data count regressions. 11 Table 1 Four predictive models for larynx cancer counts in Germany, 1998–2002

  7. Comparing urban solid waste recycling from the viewpoint of urban metabolism based on physical input-output model: A case of Suzhou in China.

    Science.gov (United States)

    Liang, Sai; Zhang, Tianzhu

    2012-01-01

    Investigating impacts of urban solid waste recycling on urban metabolism contributes to sustainable urban solid waste management and urban sustainability. Using a physical input-output model and scenario analysis, urban metabolism of Suzhou in 2015 is predicted and impacts of four categories of solid waste recycling on urban metabolism are illustrated: scrap tire recycling, food waste recycling, fly ash recycling and sludge recycling. Sludge recycling has positive effects on reducing all material flows. Thus, sludge recycling for biogas is regarded as an accepted method. Moreover, technical levels of scrap tire recycling and food waste recycling should be improved to produce positive effects on reducing more material flows. Fly ash recycling for cement production has negative effects on reducing all material flows except solid wastes. Thus, other fly ash utilization methods should be exploited. In addition, the utilization and treatment of secondary wastes from food waste recycling and sludge recycling should be concerned.

  8. Prediction of syngas quality for two-stage gasification of selected waste feedstocks.

    Science.gov (United States)

    De Filippis, Paolo; Borgianni, Carlo; Paolucci, Martino; Pochetti, Fausto

    2004-01-01

    This paper compares the syngas produced from methane with the syngas obtained from the gasification, in a two-stage reactor, of various waste feedstocks. The syngas composition and the gasification conditions were simulated using a simple thermodynamic model. The waste feedstocks considered are: landfill gas, waste oil, municipal solid waste (MSW) typical of a low-income country, the same MSW blended with landfill gas, refuse derived fuel (RDF) made from the same MSW, the same RDF blended with waste oil and a MSW typical of a high-income country. Energy content, the sum of H2 and CO gas percentages, and the ratio of H2 to CO are considered as measures of syngas quality. The simulation shows that landfill gas gives the best results in terms of both H2+CO and H2/CO, and that the MSW of low-income countries can be expected to provide inferior syngas on all three quality measures. Co-gasification of the MSW from low-income countries with landfill gas, and the mixture of waste oil with RDF from low-income MSW are considered as options to improve gas quality.

  9. Description of waste pretreatment and interfacing systems dynamic simulation model

    Energy Technology Data Exchange (ETDEWEB)

    Garbrick, D.J.; Zimmerman, B.D.

    1995-05-01

    The Waste Pretreatment and Interfacing Systems Dynamic Simulation Model was created to investigate the required pretreatment facility processing rates for both high level and low level waste so that the vitrification of tank waste can be completed according to the milestones defined in the Tri-Party Agreement (TPA). In order to achieve this objective, the processes upstream and downstream of the pretreatment facilities must also be included. The simulation model starts with retrieval of tank waste and ends with vitrification for both low level and high level wastes. This report describes the results of three simulation cases: one based on suggested average facility processing rates, one with facility rates determined so that approximately 6 new DSTs are required, and one with facility rates determined so that approximately no new DSTs are required. It appears, based on the simulation results, that reasonable facility processing rates can be selected so that no new DSTs are required by the TWRS program. However, this conclusion must be viewed with respect to the modeling assumptions, described in detail in the report. Also included in the report, in an appendix, are results of two sensitivity cases: one with glass plant water recycle steams recycled versus not recycled, and one employing the TPA SST retrieval schedule versus a more uniform SST retrieval schedule. Both recycling and retrieval schedule appear to have a significant impact on overall tank usage.

  10. Mixing-controlled uncertainty in long-term predictions of acid rock drainage from heterogeneous waste-rock piles

    Science.gov (United States)

    Pedretti, D.; Beckie, R. D.; Mayer, K. U.

    2015-12-01

    The chemistry of drainage from waste-rock piles at mine sites is difficult to predict because of a number of uncertainties including heterogeneous reactive mineral content, distribution of minerals, weathering rates and physical flow properties. In this presentation, we examine the effects of mixing on drainage chemistry over timescales of 100s of years. We use a 1-D streamtube conceptualization of flow in waste rocks and multicomponent reactive transport modeling. We simplify the reactive system to consist of acid-producing sulfide minerals and acid-neutralizing carbonate minerals and secondary sulfate and iron oxide minerals. We create multiple realizations of waste-rock piles with distinct distributions of reactive minerals along each flow path and examine the uncertainty of drainage geochemistry through time. The limited mixing of streamtubes that is characteristic of the vertical unsaturated flow in many waste-rock piles, allows individual flowpaths to sustain acid or neutral conditions to the base of the pile, where the streamtubes mix. Consequently, mixing and the acidity/alkalinity balance of the streamtube waters, and not the overall acid- and base-producing mineral contents, control the instantaneous discharge chemistry. Our results show that the limited mixing implied by preferential flow and the heterogeneous distribution of mineral contents lead to large uncertainty in drainage chemistry over short and medium time scales. However, over longer timescales when one of either the acid-producing or neutralizing primary phases is depleted, the drainage chemistry becomes less controlled by mixing and in turn less uncertain. A correct understanding of the temporal variability of uncertainty is key to make informed long-term decisions in mining settings regarding the management of waste material.

  11. Demolition waste generation for development of a regional management chain model.

    Science.gov (United States)

    Bernardo, Miguel; Gomes, Marta Castilho; de Brito, Jorge

    2016-03-01

    Even though construction and demolition waste (CDW) is the bulkiest waste stream, its estimation and composition in specific regions still faces major difficulties. Therefore new methods are required especially when it comes to make predictions limited to small areas, such as counties. This paper proposes one such method, which makes use of data collected from real demolition works and statistical information on the geographical area under study. Based on a correlation analysis between the demolition waste estimates and indicators such as population density, buildings ageing index, buildings density and land occupation type, relationships are established that can be used to determine demolition waste outputs in a given area. The derived models are presented and explained. This methodology is independent from the specific region with which it is exemplified (the Lisbon Metropolitan Area) and can therefore be applied to any region of the world, from the country to the county level. Generation of demolition waste data at the county level is the basis of the design of a systemic model for CDW management in a region. Future developments proposed include a mixed-integer linear programming formulation of such recycling network.

  12. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  13. Nonlinear chaotic model for predicting storm surges

    NARCIS (Netherlands)

    Siek, M.; Solomatine, D.P.

    This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables.

  14. Model comparison of flow through a municipal solid waste incinerator ash landfill

    Science.gov (United States)

    Johnson, C. A.; Schaap, M. G.; Abbaspour, K. C.

    2001-03-01

    The drainage discharge of a municipal solid waste incinerator (MSWI) bottom ash landfill was simulated using various modelling approaches. Two functional models including a neural networks approach and a hydrological linear storage model, and two mechanistic models requiring physical/hydrodynamic properties of the waste material, HYDRUS5 and MACRO (Version 4.0) were used. The models were calibrated using an 8-month data set from 1996 and validated on a 3-month data set from winter 1994/1995. The data sets comprised hourly values of rainfall, evaporation (estimated from the Penman-Monteith relationship), drainage discharge and electrical conductivity. Predicted and measured discharges were compared. The discharge predicted by the functional models more exactly followed the discharge patterns of the measured data but, particularly the linear storage model, could not cope with the non-linearity of the system that was caused by seasonal changes in water content of the MSWI bottom ash. The fit of the neural networks model to the data improved with increasing prior information but was less smooth than the measured data. The mechanistic model that included preferential discharge, MACRO, better modelled the discharge characteristics when inversely applied, indicating that preferential flow does occur in this system. However, even the inverse application of HYDRUS5 could not describe the system discharge as well as the linear storage model. All model approaches would have benefited from a more exact knowledge of initial water content.

  15. Biosphere models for safety assesment of radioactive waste disposal

    Energy Technology Data Exchange (ETDEWEB)

    Proehl, G.; Olyslaegers, G.; Zeevaert, T. [SCK/CEN, Mol (Belgium); Kanyar, B. [University of Veszprem (Hungary). Dept. of Radiochemistry; Pinedo, P.; Simon, I. [Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain); Bergstroem, U.; Hallberg, B. [Studsvik Ecosafe, Nykoeping (Sweden); Mobbs, S.; Chen, Q.; Kowe, R. [NRPB, Chilton, Didcot (United Kingdom)

    2004-07-01

    The aim of the BioMoSA project has been to contribute in the confidence building of biosphere models, for application in performance assessments of radioactive waste disposal. The detailed objectives of this project are: development and test of practical biosphere models for application in long-term safety studies of radioactive waste disposal to different European locations, identification of features, events and processes that need to be modelled on a site-specific rather than on a generic base, comparison of the results and quantification of the variability of site-specific models developed according to the reference biosphere methodology, development of a generic biosphere tool for application in long term safety studies, comparison of results from site-specific models to those from generic one, Identification of possibilities and limitations for the application of the generic biosphere model. (orig.)

  16. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain,...

  17. Analysis of source term modeling for low-level radioactive waste performance assessments

    Energy Technology Data Exchange (ETDEWEB)

    Icenhour, A.S.

    1995-03-01

    Site-specific radiological performance assessments are required for the disposal of low-level radioactive waste (LLW) at both commercial and US Department of Energy facilities. This work explores source term modeling of LLW disposal facilities by using two state-of-the-art computer codes, SOURCEI and SOURCE2. An overview of the performance assessment methodology is presented, and the basic processes modeled in the SOURCE1 and SOURCE2 codes are described. Comparisons are made between the two advective models for a variety of radionuclides, transport parameters, and waste-disposal technologies. These comparisons show that, in general, the zero-order model predicts undecayed cumulative fractions leached that are slightly greater than or equal to those of the first-order model. For long-lived radionuclides, results from the two models eventually reach the same value. By contrast, for short-lived radionuclides, the zero-order model predicts a slightly higher undecayed cumulative fraction leached than does the first-order model. A new methodology, based on sensitivity and uncertainty analyses, is developed for predicting intruder scenarios. This method is demonstrated for {sup 137}Cs in a tumulus-type disposal facility. The sensitivity and uncertainty analyses incorporate input-parameter uncertainty into the evaluation of a potential time of intrusion and the remaining radionuclide inventory. Finally, conclusions from this study are presented, and recommendations for continuing work are made.

  18. Mixture models versus free energy of hydration models for waste glass durability

    Energy Technology Data Exchange (ETDEWEB)

    Piepel, G.; Redgate, T.; Masuga, P.

    1996-03-01

    Two approaches for modeling high-level waste glass durability as a function of glass composition are compared. The mixture approach utilizes first-order mixture (FOM) or second-order mixture (SOM) polynomials in composition, whereas the free energy of hydration (FEH) approach assumes durability is linearly related to the FEH of glass. Both approaches fit their models to data using least squares regression. The mixture and FEH approaches are used to model glass durability as a function of glass composition for several simulated waste glass data sets. The resulting FEH and FOM model coefficients and goodness-of-fit statistics are compared, both within and across data sets. The goodness-of-fit statistics show that the FOM model fits/predicts durability in each data set better (sometimes much better) than the FEH model. Considerable differences also exist between some FEH and FOM model component coefficients for each of the data sets. These differences are due to the mixture approach having a greater flexibility to account for the effect of a glass component depending on the level and range of the component and on the levels of other glass components. The mixture approach can also account for higher-order (e.g., curvilinear or interactive) effects of components, whereas the FEH approach cannot. SOM models were developed for three of the data sets, and are shown to improve on the corresponding FOM models. Thus, the mixture approach has much more flexibility than the FEH approach for approximating the relationship between glass composition and durability for various glass composition regions.

  19. Modelling sensitivity and uncertainty in a LCA model for waste management systems - EASETECH

    DEFF Research Database (Denmark)

    Damgaard, Anders; Clavreul, Julie; Baumeister, Hubert

    2013-01-01

    In the new model, EASETECH, developed for LCA modelling of waste management systems, a general approach for sensitivity and uncertainty assessment for waste management studies has been implemented. First general contribution analysis is done through a regular interpretation of inventory and impact...

  20. How to Establish Clinical Prediction Models

    Directory of Open Access Journals (Sweden)

    Yong-ho Lee

    2016-03-01

    Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

  1. FRIDA: A model for the generation and handling of solid waste in Denmark

    DEFF Research Database (Denmark)

    Larsen, Helge V.; Møller Andersen, Frits

    2012-01-01

    Since 1994, Danish waste treatment plants have been obliged to report to the Danish EPA the annual amounts of waste treated. Applying these data, we analyse the development, link amounts of waste to economic and demographic variables, and present a model for the generation and treatment of waste...... in Denmark. Using the model and official projections of the economic development, a baseline projection for the generation and treatment of waste is presented. © 2012 Elsevier B.V. All rights reserved....

  2. Characterize and Model Final Waste Formulations and Offgas Solids from Thermal Treatment Processes - FY-98 Final Report for LDRD 2349

    Energy Technology Data Exchange (ETDEWEB)

    Kessinger, Glen Frank; Nelson, Lee Orville; Grandy, Jon Drue; Zuck, Larry Douglas; Kong, Peter Chuen Sun; Anderson, Gail

    1999-08-01

    The purpose of LDRD #2349, Characterize and Model Final Waste Formulations and Offgas Solids from Thermal Treatment Processes, was to develop a set of tools that would allow the user to, based on the chemical composition of a waste stream to be immobilized, predict the durability (leach behavior) of the final waste form and the phase assemblages present in the final waste form. The objectives of the project were: • investigation, testing and selection of thermochemical code • development of auxiliary thermochemical database • synthesis of materials for leach testing • collection of leach data • using leach data for leach model development • thermochemical modeling The progress toward completion of these objectives and a discussion of work that needs to be completed to arrive at a logical finishing point for this project will be presented.

  3. Waste Reduction Model (WARM) Resources for Small Businesses and Organizations

    Science.gov (United States)

    This page provides a brief overview of how EPA’s Waste Reduction Model (WARM) can be used by small businesses and organizations. The page includes a brief summary of uses of WARM for the audience and links to other resources.

  4. Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

    Science.gov (United States)

    Karanjekar, Richa V; Bhatt, Arpita; Altouqui, Said; Jangikhatoonabad, Neda; Durai, Vennila; Sattler, Melanie L; Hossain, M D Sahadat; Chen, Victoria

    2015-12-01

    Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual.

  5. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    is a realization of a continuous-discrete multivariate stochastic transfer function model. The proposed prediction error-methods are demonstrated for a SISO system parameterized by the transfer functions with time delays of a continuous-discrete-time linear stochastic system. The simulations for this case suggest......Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which...... computational resources. The identification method is suitable for predictive control....

  6. Ensuring Longevity: Ancient Glasses Help Predict Durability of Vitrified Nuclear Waste

    Energy Technology Data Exchange (ETDEWEB)

    Weaver, Jamie L.; McCloy, John S.; Ryan, Joseph V.; Kruger, Albert A.

    2016-05-01

    How does glass alter with time? For the last hundred years this has been an important question to the fields of object conservation and archeology to ensure the preservation of glass artifacts. This same question is part of the development and assessment of durable glass waste forms for the immobilization of nuclear wastes. Researchers have developed experiments ranging from simple to highly sophisticated to answer this question, and, as a result, have gained significant insight into the mechanisms that drive glass alteration. However, the gathered data have been predominately applicable to only short-term alteration times, i.e. over the course of decades. What has remained elusive is the long-term mechanisms of glass alteration[1]. These mechanisms are of particular interest to the international nuclear waste glass community as they strive to ensure that vitrified products will be durable for thousands to tens of thousands of years. For the last thirty years this community has been working to fill this research gap by partnering with archeologists, museum curators, and geologists to identify hundred to million-year old glass analogues that have altered in environments representative of those expected at potential nuclear waste disposal sites. The process of identifying a waste glass relevant analogue is challenging as it requires scientists to relate data collected from short-term laboratory experiments to observations made from long-term analogues and extensive geochemical modeling.

  7. Hydromechanical modelling with application in sealing for underground waste deposition

    Energy Technology Data Exchange (ETDEWEB)

    Hasal, Martin, E-mail: martin.hasal@vsb.cz; Michalec, Zdeněk; Blaheta, Radim [Institute of Geonics AS CR, Studentska 1768, 70800 Ostrava-Poruba (Czech Republic)

    2015-03-10

    Hydro-mechanical models appear in simulation of many environmental problems related to construction of engineering barriers for contaminant spreading. The presented work aims in modelling bentonite-sand barriers, which can be used for nuclear waste isolation and similar problems. Particularly, we use hydro-mechanical model coupling unsaturated flow and (nonlinear) elasticity, implement such model in COMSOL software and show application in simulation of an infiltration test (2D axisymmetric model) and the SEALEX Water test WT1 experiment (3D model). Finally, we discuss the needs and possibilities of parallel high performance computing.

  8. Correlation models for waste tank sludges and slurries

    Energy Technology Data Exchange (ETDEWEB)

    Mahoney, L.A.; Trent, D.S.

    1995-07-01

    This report presents the results of work conducted to support the TEMPEST computer modeling under the Flammable Gas Program (FGP) and to further the comprehension of the physical processes occurring in the Hanford waste tanks. The end products of this task are correlation models (sets of algorithms) that can be added to the TEMPEST computer code to improve the reliability of its simulation of the physical processes that occur in Hanford tanks. The correlation models can be used to augment, not only the TEMPEST code, but other computer codes that can simulate sludge motion and flammable gas retention. This report presents the correlation models, also termed submodels, that have been developed to date. The submodel-development process is an ongoing effort designed to increase our understanding of sludge behavior and improve our ability to realistically simulate the sludge fluid characteristics that have an impact on safety analysis. The effort has employed both literature searches and data correlation to provide an encyclopedia of tank waste properties in forms that are relatively easy to use in modeling waste behavior. These properties submodels will be used in other tasks to simulate waste behavior in the tanks. Density, viscosity, yield strength, surface tension, heat capacity, thermal conductivity, salt solubility, and ammonia and water vapor pressures were compiled for solutions and suspensions of sodium nitrate and other salts (where data were available), and the data were correlated by linear regression. In addition, data for simulated Hanford waste tank supernatant were correlated to provide density, solubility, surface tension, and vapor pressure submodels for multi-component solutions containing sodium hydroxide, sodium nitrate, sodium nitrite, and sodium aluminate.

  9. Macroscopic modelling of bioethanol production from potato peel wastes in batch cultures supplemented with inorganic nitrogen.

    Science.gov (United States)

    Richelle, A; Ben Tahar, I; Hassouna, M; Bogaerts, Ph

    2015-09-01

    Inorganic nitrogen supplementation is commonly used to boost fermentation metabolism in yeast cultures. However, an excessive addition can induce an opposite effect. Hence, it is important to ensure that the ammonia supplemented to the culture leads to an improvement of the ethanol production while avoiding undesirable inhibition effects. To this end, a macroscopic model describing the influence of ammonia addition on Saccharomyces cerevisiae metabolism during bioethanol production from potato peel wastes has been developed. The model parameters are obtained by a simplified identification methodology in five steps. It is validated with experimental data and successfully predicts the dynamics of growth, substrate consumption (ammonia and fermentable sugar sources) and bioethanol production, even in cross validation. The model is used to determine the optimal quantity of supplemented ammonia required for maximizing bioethanol production from potato peel wastes in batch cultures.

  10. Models for estimation of service life of concrete barriers in low-level radioactive waste disposal

    Energy Technology Data Exchange (ETDEWEB)

    Walton, J.C.; Plansky, L.E.; Smith, R.W. (EG and G Idaho, Inc., Idaho Falls, ID (USA))

    1990-09-01

    Concrete barriers will be used as intimate parts of systems for isolation of low level radioactive wastes subsequent to disposal. This work reviews mathematical models for estimating the degradation rate of concrete in typical service environments. The models considered cover sulfate attack, reinforcement corrosion, calcium hydroxide leaching, carbonation, freeze/thaw, and cracking. Additionally, fluid flow, mass transport, and geochemical properties of concrete are briefly reviewed. Example calculations included illustrate the types of predictions expected of the models. 79 refs., 24 figs., 6 tabs.

  11. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing p

  12. Childhood asthma prediction models: a systematic review.

    Science.gov (United States)

    Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup

    2015-12-01

    Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

  13. GEOCHEMICAL TESTING AND MODEL DEVELOPMENT - RESIDUAL TANK WASTE TEST PLAN

    Energy Technology Data Exchange (ETDEWEB)

    CANTRELL KJ; CONNELLY MP

    2010-03-09

    This Test Plan describes the testing and chemical analyses release rate studies on tank residual samples collected following the retrieval of waste from the tank. This work will provide the data required to develop a contaminant release model for the tank residuals from both sludge and salt cake single-shell tanks. The data are intended for use in the long-term performance assessment and conceptual model development.

  14. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  15. Waste incineration models for operation optimization. Phase 1: Advanced measurement equipment for improved operation of waste fired plants; Affaldsforbraendingsmodeller til driftsoptimering. Fase 1: Avanceret maeleudstyr til forbedret drift af affaldsfyrede anlaeg

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-06-01

    This report describes results from the PSO projects ELTRA-5294 and ELTRA-5348: Waste incineration models for operation optimization. Phase 1, and Advanced measurement equipment for improved operation of waste fired plants. Phase 1. The two projects form the first step in a project course build on a long-term vision of a fully automatic system using a wide range of advanced measurement data, advanced dynamic models for prediction of operation and advanced regulation methods for optimization of the operation of waste incinerator plants. (BA)

  16. Numerical modeling capabilities to predict repository performance

    Energy Technology Data Exchange (ETDEWEB)

    1979-09-01

    This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used.

  17. Modeling and Control of a Parallel Waste Heat Recovery System for Euro-VI Heavy-Duty Diesel Engines

    Directory of Open Access Journals (Sweden)

    Emanuel Feru

    2014-10-01

    Full Text Available This paper presents the modeling and control of a waste heat recovery systemfor a Euro-VI heavy-duty truck engine. The considered waste heat recovery system consists of two parallel evaporators with expander and pumps mechanically coupled to the engine crankshaft. Compared to previous work, the waste heat recovery system modeling is improved by including evaporator models that combine the finite difference modeling approach with a moving boundary one. Over a specific cycle, the steady-state and dynamic temperature prediction accuracy improved on average by 2% and 7%. From a control design perspective, the objective is to maximize the waste heat recovery system output power.However, for safe system operation, the vapor state needs to be maintained before the expander under highly dynamic engine disturbances. To achieve this, a switching model predictive control strategy is developed. The proposed control strategy performance is demonstrated using the high-fidelity waste heat recovery system model subject to measured disturbances from an Euro-VI heavy-duty diesel engine. Simulations are performed usinga cold-start World Harmonized Transient cycle that covers typical urban, rural and highway driving conditions. The model predictive control strategy provides 15% more time in vaporand recovered thermal energy than a classical proportional-integral (PI control strategy. In the case that the model is accurately known, the proposed control strategy performance can be improved by 10% in terms of time in vapor and recovered thermal energy. This is demonstrated with an offline nonlinear model predictive control strategy.

  18. Three multimedia models used at hazardous and radioactive waste sites

    Energy Technology Data Exchange (ETDEWEB)

    Moskowitz, P.D.; Pardi, R.; Fthenakis, V.M.; Holtzman, S.; Sun, L.C. [Brookhaven National Lab., Upton, NY (United States); Rambaugh, J.O.; Potter, S. [Geraghty and Miller, Inc., Plainview, NY (United States)

    1996-02-01

    Multimedia models are used commonly in the initial phases of the remediation process where technical interest is focused on determining the relative importance of various exposure pathways. This report provides an approach for evaluating and critically reviewing the capabilities of multimedia models. This study focused on three specific models MEPAS Version 3.0, MMSOILS Version 2.2, and PRESTO-EPA-CPG Version 2.0. These models evaluate the transport and fate of contaminants from source to receptor through more than a single pathway. The presence of radioactive and mixed wastes at a site poses special problems. Hence, in this report, restrictions associated with the selection and application of multimedia models for sites contaminated with radioactive and mixed wastes are highlighted. This report begins with a brief introduction to the concept of multimedia modeling, followed by an overview of the three models. The remaining chapters present more technical discussions of the issues associated with each compartment and their direct application to the specific models. In these analyses, the following components are discussed: source term; air transport; ground water transport; overland flow, runoff, and surface water transport; food chain modeling; exposure assessment; dosimetry/risk assessment; uncertainty; default parameters. The report concludes with a description of evolving updates to the model; these descriptions were provided by the model developers.

  19. Modeling of Stress Corrosion Cracking for High Level Radioactive-Waste Packages

    Energy Technology Data Exchange (ETDEWEB)

    Lu, S C; Gordon, G M; Andresen, P L; Herrera, M L

    2003-06-20

    A stress corrosion cracking (SCC) model has been adapted for performance prediction of high level radioactive-waste packages to be emplaced in the proposed Yucca Mountain radioactive-waste repository. SCC is one form of environmentally assisted cracking due to three factors, which must be present simultaneously: metallurgical susceptibility, critical environment, and static (or sustained) tensile stresses. For waste packages of the proposed Yucca Mountain repository, the outer barrier material is Alloy 22, a highly corrosion resistant alloy, the environment is represented by the water film present on the surface of the waste package from dripping or deliquescence of soluble salts present in any surface deposits, and the stress is principally the weld induced residual stress. SCC has historically been separated into ''initiation'' and ''propagation'' phases. Initiation of SCC will not occur on a smooth surface if the surface stress is below a threshold value defined as the threshold stress. Cracks can also initiate at and propagate from flaws (or defects) resulting from manufacturing processes (such as welding). To account for crack propagation, the slip dissolution/film rupture (SDFR) model is adopted to provide mathematical formulas for prediction of the crack growth rate. Once the crack growth rate at an initiated SCC is determined, the time to through-wall penetration for the waste package can be calculated. The SDFR model relates the advance (or propagation) of cracks, subsequent to the crack initiation from bare metal surface, to the metal oxidation transients that occur when the protective film at the crack tip is continually ruptured and repassivated. A crack, however, may reach the ''arrest'' state before it enters the ''propagation'' phase. There exists a threshold stress intensity factor, which provides a criterion for determining if an initiated crack or pre

  20. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik;

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored...... and controlled have thus become essential factors for efficient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona...

  1. Biosphere model for high level waste repository.

    Science.gov (United States)

    Barrdahl, R

    1997-10-01

    Method for environmental impact modeling involving uncertainty, overcoming the disadvantage of providing only one upper bound based on accumulated effects from all extreme events. This method provides a suite of upper and lower bounds based on any subset of such extreme events, to be chosen among by the decision maker.

  2. Integrated economic model of waste management: Case study for South Moravia region

    Directory of Open Access Journals (Sweden)

    Jiří Hřebíček

    2013-01-01

    Full Text Available The paper introduces and discusses the developed integrated economic model of municipal waste management of the Czech Republic, which was developed by authors as a balanced network model for a set of sources (mostly municipalities of municipal solid waste connected with a set of chosen waste treatment facilities processing their waste. Model is implemented as a combination of several economic submodels including environmental and economic point of view. It enables to formulate the optimisation problem in a concise way and the resulting model is easily scalable. Model involves submodels of waste prevention, collection and transport optimization, submodels of waste energy utilization (incineration and biogas plants and material recycling (composting and submodel of landfilling. Its size (number of sources and facilities depends only upon available data. Its application is used in the case study of the South Moravia region with verification of using time series waste data. The results enable to improve decision making in waste management sector.

  3. Quantifying uncertainty in LCA-modelling of waste management systems.

    Science.gov (United States)

    Clavreul, Julie; Guyonnet, Dominique; Christensen, Thomas H

    2012-12-01

    Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining the selected methods: (Step 1) a sensitivity analysis evaluating the sensitivities of the results with respect to the input uncertainties, (Step 2) an uncertainty propagation providing appropriate tools for representing uncertainties and calculating the overall uncertainty of the model results, (Step 3) an uncertainty contribution analysis quantifying the contribution of each parameter uncertainty to the final uncertainty and (Step 4) as a new approach, a combined sensitivity analysis providing a visualisation of the shift in the ranking of different options due to variations of selected key parameters. This tiered approach optimises the resources available to LCA practitioners by only propagating the most influential uncertainties.

  4. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...

  5. Massive Predictive Modeling using Oracle R Enterprise

    CERN Document Server

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  6. Geographical Information Systems (GIS) as a Simple Tool to Aid Modelling of Particulate Waste Distribution at Marine Fish Cage Sites

    Science.gov (United States)

    Pérez, O. M.; Telfer, T. C.; Beveridge, M. C. M.; Ross, L. G.

    2002-04-01

    Deposition of particulate organic waste from marine fish farm cages on to sea-bed sediments can cause major changes to the benthic ecosystem. Validated spatial models are considered as the most cost-effective tools for predicting environmental impacts. An improved version of an existing predictive particulate waste distribution model for farmed Atlantic salmon ( Salmo salar L.) is presented, which uses Geographic Information Systems (GIS) combined with a spreadsheet. The model presented uses existing distribution algorithms but also incorporates functions to calculate feed loading for all the cages within a pontoon independently, spreads the input load over the whole cage area and simulates post-depositional distribution of the carbon. The model uses approximate estimates of feed and faecal waste derived from dietary considerations (mass balance model) and separate, unique settling velocities for waste feed and faecal particles. The model incorporates values of current speed and direction recorded over spring and neap tides. Output from the model is in the form of a contour plot of organic carbon (g C m -2), showing distribution of the particulate organic carbon material as deposited on the sea-bed. During this study using hydrographic data collected from near a fish farm, the model predicted a smooth gradient of sediment carbon concentrations which decreased with distance from the cages. Model performance was validated using measured levels of sediment carbon, and showed a significant correlation between predicted and actual sediment loading (R=0·7; P <0·01). The differences between predicted and measured quantities of carbon found at some sampling stations are likely to be due to processes not included in the model, such as small differences in bathymetry, differences in bottom type which may have increased or decreased the carbon distribution through saltation, or natural variation in the sediment composition.

  7. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Posterior Predictive Model Checking in Bayesian Networks

    Science.gov (United States)

    Crawford, Aaron

    2014-01-01

    This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

  20. State-of-the-Art Solid Waste Management Life-Cycle Modeling Workshop

    DEFF Research Database (Denmark)

    Damgaard, Anders; Levis, James W.

    There are many alternatives for the management of solid waste including recycling, biological treatment, thermal treatment and landfill disposal. In many cases, solid waste management systems include the use of several of these processes. Solid waste life-cycle assessment models are often used...... to evaluate the environmental consequences of various waste management strategies. The foundation of every life-cycle model is the development and use of process models to estimate the emissions from solid waste unit processes. The objective of this workshop is to describe life-cycle modeling of the solid...... waste processes and systems. The workshop will begin with an introduction to solid waste life-cycle modeling and available models, which will be followed by sessions on life-cycle process modeling for individual processes (e.g., landfills, biological treatment, and thermal treatment). The first part...

  1. A Course in... Model Predictive Control.

    Science.gov (United States)

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  2. Evaluating a model of anaerobic digestion of organic wastes through system identification

    Energy Technology Data Exchange (ETDEWEB)

    Anex, R.P.; Kiely, G.

    1999-07-01

    Anaerobic digestion of the organic fraction of municipal solid waste (MSW), on its own or co-digested with primary sewage sludge (PSS), produces high quality biogas, suitable as renewable energy. Parameter estimation and evaluation of a two-stage mathematical model of the anaerobic co-digestion of the organic fraction of MSW and PSS are described. Measured data are from a bench scale laboratory experiment using a continuously stirred tank reactor and operated at 36 C for 115 days. The two-stage model simulates acidogenesis and methanogenesis, including ammonia inhibition. Model parameters are estimated using an output error, Levenberg-Marquardt (LM) algorithm. Sensitivity of the estimated parameter values and the model outputs to non-estimated model parameters and measurement errors are evaluated. The estimated mathematical model successfully predicts the performance of the anaerobic reactor. Sensitivity results provide guidance for improving the model structure and experimental procedures.

  3. Equivalency and unbiasedness of grey prediction models

    Institute of Scientific and Technical Information of China (English)

    Bo Zeng; Chuan Li; Guo Chen; Xianjun Long

    2015-01-01

    In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction mo-dels, the equivalence and unbiasedness of grey prediction mo-dels are analyzed and verified. The results show that al the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homoge-neous exponential sequence can be accomplished. However, the models derived from dx(1)/dt+ax(1) =b are only close to those derived from x(0)(k)+az(1)(k)=b provided that|a|has to satisfy|a| < 0.1; neither could the unbiased simulation for the homoge-neous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.

  4. Simulation and modeling of vegetable market wastes pyrolysis under progressive deactivation condition

    Energy Technology Data Exchange (ETDEWEB)

    Ray, R.; Bhattacharya, P.; Chowdhury, R. [Jadavpur University, Chemical Engineering Dept., Kolkata (India)

    2004-06-01

    Pyrolytic behaviour of sun-dried vegetable market waste was investigated using thermogravimetric analysis within the temperature range of 523 to 923 K under inert atmosphere. Results were compared with other lignocellulosic materials in order to highlight the difference between the pyrolysis of nearly homogenous and perfectly mixed homogenous biomass. The vegetable waste analysis indicated a structural change of the biomass, which ultimately led to the deactivation phenomenon. When compared to the pyrolysis behaviour of other nearly pure lignocellulosic materials, the conversion rate of the reacting materials was appreciably lower. This was attributed to the low concentration of active material in the vegetable waste. Simulation and modelling have been carried out to explain the kinetic behaviour of pyrolysis reaction. A reaction mechanism involving two parallel first order reactions evolving gaseous products, lumped as volatiles and solid products lumped as char, has been proposed for prediction of rate constants as a function of normalized fractional change. Four kinetic models incorporating the effect of deactivation have been used for this purpose, however, no single set of model equations was found to be adequate to explain the entire pyrolysis process. At the same time, separating the pyrolysis operation into two temperature segments -- one at low to moderate, and one at higher temperatures -- satisfactory correspondence (segment-wise) can be established between experimental results and model equations. 15 refs., 1 tab., 9 figs.

  5. Predictability of extreme values in geophysical models

    Directory of Open Access Journals (Sweden)

    A. E. Sterk

    2012-09-01

    Full Text Available Extreme value theory in deterministic systems is concerned with unlikely large (or small values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical models. We study whether finite-time Lyapunov exponents are larger or smaller for initial conditions leading to extremes. General statements on whether extreme values are better or less predictable are not possible: the predictability of extreme values depends on the observable, the attractor of the system, and the prediction lead time.

  6. Forecasting of municipal solid waste quantity in a developing country using multivariate grey models

    Energy Technology Data Exchange (ETDEWEB)

    Intharathirat, Rotchana, E-mail: rotchana.in@gmail.com [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, KlongLuang, Pathumthani 12120 (Thailand); Abdul Salam, P., E-mail: salam@ait.ac.th [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, KlongLuang, Pathumthani 12120 (Thailand); Kumar, S., E-mail: kumar@ait.ac.th [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, KlongLuang, Pathumthani 12120 (Thailand); Untong, Akarapong, E-mail: akarapong_un@hotmail.com [School of Tourism Development, Maejo University, Chiangmai (Thailand)

    2015-05-15

    Highlights: • Grey model can be used to forecast MSW quantity accurately with the limited data. • Prediction interval overcomes the uncertainty of MSW forecast effectively. • A multivariate model gives accuracy associated with factors affecting MSW quantity. • Population, urbanization, employment and household size play role for MSW quantity. - Abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435–44,994 tonnes per day in 2013 to 55,177–56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.

  7. Hybrid modeling and prediction of dynamical systems

    Science.gov (United States)

    Lloyd, Alun L.; Flores, Kevin B.

    2017-01-01

    Scientific analysis often relies on the ability to make accurate predictions of a system’s dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic model’s equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data. PMID:28692642

  8. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.

  9. Development of a computer code to predict a ventilation requirement for an underground radioactive waste storage tank

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Y.J.; Dalpiaz, E.L. [ICF Kaiser Hanford Co., Richland, WA (United States)

    1997-08-01

    Computer code, WTVFE (Waste Tank Ventilation Flow Evaluation), has been developed to evaluate the ventilation requirement for an underground storage tank for radioactive waste. Heat generated by the radioactive waste and mixing pumps in the tank is removed mainly through the ventilation system. The heat removal process by the ventilation system includes the evaporation of water from the waste and the heat transfer by natural convection from the waste surface. Also, a portion of the heat will be removed through the soil and the air circulating through the gap between the primary and secondary tanks. The heat loss caused by evaporation is modeled based on recent evaporation test results by the Westinghouse Hanford Company using a simulated small scale waste tank. Other heat transfer phenomena are evaluated based on well established conduction and convection heat transfer relationships. 10 refs., 3 tabs.

  10. A simple protein-energy wasting score predicts survival in maintenance hemodialysis patients.

    Science.gov (United States)

    Moreau-Gaudry, Xavier; Jean, Guillaume; Genet, Leslie; Lataillade, Dominique; Legrand, Eric; Kuentz, François; Fouque, Denis

    2014-11-01

    Nutritional status is a powerful predictor of survival in maintenance hemodialysis patients but remains challenging to assess. We defined a new Protein Energy Wasting (PEW) score based on the nomenclature proposed by the International Society of Renal Nutrition and Metabolism in 2008. This score, graded from 0 (worse) to 4 (best) was derived from 4 body nutrition compartments: serum albumin, body mass index, a normalized serum creatinine value, and protein intake as assessed by nPNA. We applied this score to 1443 patients from the ARNOS prospective dialysis cohort and provide survival data from 2005 until 2008. Patients survival at 3.5 year. Survival ranged from 84%-69% according to the protein-energy wasting score. There was a clear-cut reduction in survival (5%-7%; P < 0.01) for each unit decrement in the score grade. There was a 99% survival at 1 year for patients with the score of 4. In addition, the 6-month variation of this PEW score also strongly predicted patients' survival (P < 0.01). A new simple and easy-to-get PEW score predicts survival in maintenance hemodialysis patients. Furthermore, increase of this nutritional score over time also indicates survival improvement, and may help to better identify subgroups of patients with a high mortality rate, in which nutrition support should be enforced. Copyright © 2014 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  11. Property predictions using microstructural modeling

    Energy Technology Data Exchange (ETDEWEB)

    Wang, K.G. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)]. E-mail: wangk2@rpi.edu; Guo, Z. [Sente Software Ltd., Surrey Technology Centre, 40 Occam Road, Guildford GU2 7YG (United Kingdom); Sha, W. [Metals Research Group, School of Civil Engineering, Architecture and Planning, The Queen' s University of Belfast, Belfast BT7 1NN (United Kingdom); Glicksman, M.E. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States); Rajan, K. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)

    2005-07-15

    Precipitation hardening in an Fe-12Ni-6Mn maraging steel during overaging is quantified. First, applying our recent kinetic model of coarsening [Phys. Rev. E, 69 (2004) 061507], and incorporating the Ashby-Orowan relationship, we link quantifiable aspects of the microstructures of these steels to their mechanical properties, including especially the hardness. Specifically, hardness measurements allow calculation of the precipitate size as a function of time and temperature through the Ashby-Orowan relationship. Second, calculated precipitate sizes and thermodynamic data determined with Thermo-Calc[copyright] are used with our recent kinetic coarsening model to extract diffusion coefficients during overaging from hardness measurements. Finally, employing more accurate diffusion parameters, we determined the hardness of these alloys independently from theory, and found agreement with experimental hardness data. Diffusion coefficients determined during overaging of these steels are notably higher than those found during the aging - an observation suggesting that precipitate growth during aging and precipitate coarsening during overaging are not controlled by the same diffusion mechanism.

  12. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  13. Assessment of municipal solid waste management scenarios in Irkutsk (Russia) using a life cycle assessment-integrated waste management model.

    Science.gov (United States)

    Tulokhonova, Alisa; Ulanova, Olga

    2013-05-01

    Continuous growth in the quantity of municipal solid waste (MSW) and increasing demands for their environmentally-friendly treatment are one of the main consequences of the growing social and economic development rate in modern society. Despite ecologically sustainable trends in waste management systems around the world, open dumps are still the main waste treatment option in Russia. This study aims to help the local municipality administration in Irkutsk (Russia) identify the most appropriate direction for current waste management and its optimization. Within this study four developed MSW management scenarios were assessed and compared with respect to their ecological, economic and social aspects using a life cycle-based integrated waste management model. The evaluation results of these scenarios show that the development of environmental sustainability and the reduction of social effects lead to an increase in handling of costs of waste. The best scenario, regarding both environmental and social aspects, is scenario four, which includes the separate collection and reprocessing of recyclables in combination with an aerobic mechanical-biological pre-treatment of the residual waste before landfilling. However, this scenario is 3.6 times more expensive than the existing system. The results of all assessed scenarios were further analyzed and recommendations were made to design integrated waste management solutions that are optimal not only from the ecological and social points of view, but which are also realistic within the given economic situation.

  14. A mathematical model for municipal solid waste management - A case study in Hong Kong.

    Science.gov (United States)

    Lee, C K M; Yeung, C L; Xiong, Z R; Chung, S H

    2016-12-01

    With the booming economy and increasing population, the accumulation of waste has become an increasingly arduous issue and has aroused the attention from all sectors of society. Hong Kong which has a relative high daily per capita domestic waste generation rate in Asia has not yet established a comprehensive waste management system. This paper conducts a review of waste management approaches and models. Researchers highlight that mathematical models provide useful information for decision-makers to select appropriate choices and save cost. It is suggested to consider municipal solid waste management in a holistic view and improve the utilization of waste management infrastructures. A mathematical model which adopts integer linear programming and mixed integer programming has been developed for Hong Kong municipal solid waste management. A sensitivity analysis was carried out to simulate different scenarios which provide decision-makers important information for establishing Hong Kong waste management system.

  15. Modeling of concrete carbonation in deep geological disposal of intermediate level waste

    Directory of Open Access Journals (Sweden)

    Poyet S.

    2013-07-01

    Full Text Available Simulations of atmospheric carbonation of Intermediate-Level Long-lived radioactive Waste (ILLW concrete packages were conducted to evaluate their possible chemical degradations. Two-phase liquid water-air flow is combined with gas component diffusion processes leading to a progressive drying of the concrete.Complete drying of the 11 cm thick waste disposal package wall occurs over a period ranging from 2 years for the low-performance concrete to 10 years for the high-performance concrete. The drying process slows down when transport characteristics of concretes are enhanced. Carbonation depths in the order of 2 to 3 cm in 100 years are predicted for this cementitious component. However, these values are slightly overestimated compared to experimental data. Also the kinetic model of mineral reactivity requires improvements with respect to the protective effect of secondary carbonates and to thermodynamic data.

  16. Numerical Modeling of Fin and Tube Heat Exchanger for Waste Heat Recovery

    DEFF Research Database (Denmark)

    Singh, Shobhana; Sørensen, Kim; Condra, Thomas Joseph

    associates conjugate heat transfer phenomenon with the turbulent flow to describe the variable temperature and velocity profile. The performance of heat exchanger design is investigated in terms of overall heat transfer coefficient, Nusselt number, Colburn j-factor, flow resistance factor, and efficiency......In the present work, multiphysics numerical modeling is carried out to predict the performance of a liquid-gas fin and tube heat exchanger design. Three-dimensional (3D) steady-state numerical model using commercial software COMSOL based on finite element method (FEM) is developed. The study...... between fin and tube. The present numerical model predicts the performance of the heat exchanger design, therefore, can be applied to existing waste heat recovery systems to improve the overall performance with optimized design and process-dependent parameters....

  17. Experimental simulation and fuzzy modelling of landfill biogas production from low-biodegradable MBT waste under leachate recirculation.

    Science.gov (United States)

    Di Addario, Martina; Ruggeri, Bernardo

    2017-08-10

    In the perspective of a sustainable waste management, biodegradable waste destined to landfilling should be reduced. This work aims to study a combination of waste pretreatments and leachate recirculation. A lab-scale experiment and fuzzy-modelling were chosen to predict cumulative methane production from low-biodegradable waste (LBW) under leachate recirculation. Thanks to moisture increase, the degradation of LBW was reactivated and the cumulative methane production reached 28 NL CH4 kg(-1) after 442 days. The organic fraction was stabilized with a final chemical oxygen demand (COD) of 81 mg L(-1). Fuzzy model was proposed as an alternative to the common deterministic models, affected by high uncertainties. Eleven inputs (pH, Redox potential, COD, volatile fatty acids, ammonium content, age, temperature, moisture content, organic fraction concentration, particle size and recirculation flow rate) were identified as antecedent, and two outputs, or consequents, were chosen: methane production rate and methane fraction in biogas. Antecedents and consequents were linked by 84 IF-THEN rules in a linguistic form. The model was also tested on six literature studies chosen to test different operational conditions and waste qualities. The model outputs fitted the experimental data reasonably well, confirming the potential use of fuzzy macro-approach to model sustainable landfilling.

  18. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...

  19. Precision Plate Plan View Pattern Predictive Model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yang; YANG Quan; HE An-rui; WANG Xiao-chen; ZHANG Yun

    2011-01-01

    According to the rolling features of plate mill, a 3D elastic-plastic FEM (finite element model) based on full restart method of ANSYS/LS-DYNA was established to study the inhomogeneous plastic deformation of multipass plate rolling. By analyzing the simulation results, the difference of head and tail ends predictive models was found and modified. According to the numerical simulation results of 120 different kinds of conditions, precision plate plan view pattern predictive model was established. Based on these models, the sizing MAS (mizushima automatic plan view pattern control system) method was designed and used on a 2 800 mm plate mill. Comparing the rolled plates with and without PVPP (plan view pattern predictive) model, the reduced width deviation indicates that the olate !olan view Dattern predictive model is preeise.

  20. Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction

    Directory of Open Access Journals (Sweden)

    Jingwei Song

    2014-01-01

    Full Text Available A simulated annealing (SA based variable weighted forecast model is proposed to combine and weigh local chaotic model, artificial neural network (ANN, and partial least square support vector machine (PLS-SVM to build a more accurate forecast model. The hybrid model was built and multistep ahead prediction ability was tested based on daily MSW generation data from Seattle, Washington, the United States. The hybrid forecast model was proved to produce more accurate and reliable results and to degrade less in longer predictions than three individual models. The average one-week step ahead prediction has been raised from 11.21% (chaotic model, 12.93% (ANN, and 12.94% (PLS-SVM to 9.38%. Five-week average has been raised from 13.02% (chaotic model, 15.69% (ANN, and 15.92% (PLS-SVM to 11.27%.

  1. Modeling of waste to energy systems for rural applications

    Energy Technology Data Exchange (ETDEWEB)

    Namuli, Rachel; Pragasen, Pillay

    2010-09-15

    A system to convert waste into heat and electricity is presented, where biogas is generated from anaerobic digestion of manure, and fed to an internal combustion engine and generator. An overall system model that would meet annual heating and electrical loads, is formulated. The model is suited to rural farms that have no access to electricity or are connected to a diesel grid. The system is applicable to warm and cold climates. The sizing of the engines is such that they will adequately meet the annual heating and electrical load profile according to a given biogas sharing ratio.

  2. NBC Hazard Prediction Model Capability Analysis

    Science.gov (United States)

    1999-09-01

    Puff( SCIPUFF ) Model Verification and Evaluation Study, Air Resources Laboratory, NOAA, May 1998. Based on the NOAA review, the VLSTRACK developers...TO SUBSTANTIAL DIFFERENCES IN PREDICTIONS HPAC uses a transport and dispersion (T&D) model called SCIPUFF and an associated mean wind field model... SCIPUFF is a model for atmospheric dispersion that uses the Gaussian puff method - an arbitrary time-dependent concentration field is represented

  3. Global warming factors modelled for 40 generic municipal waste management scenarios

    DEFF Research Database (Denmark)

    Christensen, Thomas Højlund; Simion, F.; Tonini, Davide

    2009-01-01

    Global warming factors (kg CO2-eq.-tonne—1 of waste) have been modelled for 40 different municipal waste management scenarios involving a variety of recycling systems (paper, glass, plastic and organics) and residual waste management by landfilling, incineration or mechanical—biological waste...... treatment. For average European waste composition most waste management scenarios provided negative global warming factors and hence overall savings in greenhouse gas emissions: Scenarios with landfilling saved 0—400, scenarios with incineration saved 200—700, and scenarios with mechanical...

  4. The Sort on Radioactive Waste Type model: A method to sort single-shell tanks into characteristic groups. Revision 2

    Energy Technology Data Exchange (ETDEWEB)

    Hill, J.G.; Anderson, G.S. [Pacific Northwest Lab., Richland, WA (United States); Simpson, B.C. [Westinghouse Hanford Co., Richland, WA (United States)

    1995-03-01

    The SORWT model presents a methodology to group SSTs that is both simple to understand and logical in its assumptions and construction. The SORWT model has predicted the existence of 24 groups of SSTs ranging from 22 tanks per group to two tanks per group. These 24 groups encompass 133 tanks and 93% of the total waste contained in SSTs. The first 14 groups (i.e., those that contain four tanks per group or more) represent 109 tanks and 83% of the total waste volume. This demonstrates the potential for using the SORWT model to efficiently allocate resources and to maximize characterization information gained by a minimum number of sampling events. The verification study has shown that the SST groups predicted by the SORWT model are statistically significant and reduce the variability in the concentrations for all analytes examined. The SORWT model organizes a vast amount of information and presents clear options on which SSTs are more desirable to sample. The model is also simple and flexible in its ability to incorporate new parameters such as new SST analytical data, shifting programmatic needs, and/or risk assessment-oriented criteria. This report presents the nominal composition, inventory, and uncertainty for five of the 24 SORWT groups, representing 28 tanks, 10% of the total waste volume, and 29% of the total sludge volume in SSTs. Consequently, this document provides a logical beginning framework for tank waste characterization until further information becomes available or different programmatic needs are identified.

  5. A comprehensive waste collection cost model applied to post-consumer plastic packaging waste

    NARCIS (Netherlands)

    Groot, J.J.; Bing, X.; Bos-Brouwers, H.E.J.; Bloemhof, J.M.

    2014-01-01

    Post-consumer plastic packaging waste (PPW) can be collected for recycling via source separation or post-separation. In source separation, households separate plastics from other waste before collection, whereas in post-separation waste is separated at a treatment centre after collection. There are

  6. A comprehensive waste collection cost model applied to post-consumer plastic packaging waste

    NARCIS (Netherlands)

    Groot, J.J.; Bing, X.; Bos-Brouwers, H.E.J.; Bloemhof, J.M.

    2014-01-01

    Post-consumer plastic packaging waste (PPW) can be collected for recycling via source separation or post-separation. In source separation, households separate plastics from other waste before collection, whereas in post-separation waste is separated at a treatment centre after collection. There are

  7. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  8. Modelling Chemical Reasoning to Predict Reactions

    CERN Document Server

    Segler, Marwin H S

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically ac...

  9. Nuclide separation modeling through reverse osmosis membranes in radioactive liquid waste

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Byung Sik [KEPCO Engineering and Construction, Gimcheon (Korea, Republic of)

    2015-12-15

    The aim of this work is to investigate the transport mechanism of radioactive nuclides through the reverse osmosis (RO) membrane and to estimate its effectiveness for nuclide separation from radioactive liquid waste. An analytical model is developed to simulate the RO separation, and a series of experiments are set up to confirm its estimated separation behavior. The model is based on the extended Nernst-Plank equation, which handles the convective flux, diffusive flux, and electromigration flux under electroneutrality and zero electric current conditions. The distribution coefficient which arises due to ion interactions with the membrane material and the electric potential jump at the membrane interface are included as boundary conditions in solving the equation. A high Peclet approximation is adopted to simplify the calculation, but the effect of concentration polarization is included for a more accurate prediction of separation. Cobalt and cesium are specifically selected for the experiments in order to check the separation mechanism from liquid waste composed of various radioactive nuclides and nonradioactive substances, and the results are compared with the estimated cobalt and cesium rejections of the RO membrane using the model. Experimental and calculated results are shown to be in excellent agreement. The proposed model will be very useful for the prediction of separation behavior of various radioactive nuclides by the RO membrane.

  10. Nuclide separation modeling through reverse osmosis membranes in radioactive liquid waste

    Directory of Open Access Journals (Sweden)

    Byung-Sik Lee

    2015-12-01

    Full Text Available The aim of this work is to investigate the transport mechanism of radioactive nuclides through the reverse osmosis (RO membrane and to estimate its effectiveness for nuclide separation from radioactive liquid waste. An analytical model is developed to simulate the RO separation, and a series of experiments are set up to confirm its estimated separation behavior. The model is based on the extended Nernst–Plank equation, which handles the convective flux, diffusive flux, and electromigration flux under electroneutrality and zero electric current conditions. The distribution coefficient which arises due to ion interactions with the membrane material and the electric potential jump at the membrane interface are included as boundary conditions in solving the equation. A high Peclet approximation is adopted to simplify the calculation, but the effect of concentration polarization is included for a more accurate prediction of separation. Cobalt and cesium are specifically selected for the experiments in order to check the separation mechanism from liquid waste composed of various radioactive nuclides and nonradioactive substances, and the results are compared with the estimated cobalt and cesium rejections of the RO membrane using the model. Experimental and calculated results are shown to be in excellent agreement. The proposed model will be very useful for the prediction of separation behavior of various radioactive nuclides by the RO membrane.

  11. Mathematical Modelling of Leachate Production from Waste Contained Site

    Directory of Open Access Journals (Sweden)

    Ojolo S. Joshua

    2012-07-01

    Full Text Available In this work, mathematical models of leachate production from Waste Contained Site (WCS was developed and validated using the existing experimental data with aid of MATLAB, 2007a. When the leachate generation potentials (Lo were 100m3, 80m3 and 50m3, the maximum amount of leachate generated were about 2920m3, 2338m3 and 1461m3 for about 130 days respectively. It was noted that as the leachate percolates through a selected distance, the concentration keeps decreasing for one-dimensional flow in all the cases considered. Decreasing in concentration continues until a point was reached when the concentration was almost zero and later constant. The effects of diffusivity, amount of organic content present within the waste and gravity, as cases, were also considered in various occasions during the percolation. Comparison of their effects was also taken into account. In case of gravity at constant diffusivity, decrease in concentration was not rapid but gradually while much organic content in the waste caused the rate of leachate production to be rapid; hence, giving rise to a sharp sloped curve. It can be concluded that gravity influences the rate of change in the concentration of the leachate generation as the leachate percolate downward to the underground water. When the diffusivity and gravity are put into consideration, the concentration of the leachate decreases gradually and slowly.

  12. CREVICE CORROSION & PITTING OF HIGH-LEVEL WASTE CONTAINERS: INTEGRATION OF DETERMINISTIC & PROBABILISTIC MODELS

    Energy Technology Data Exchange (ETDEWEB)

    JOSEPH C. FARMER AND R. DANIEL MCCRIGHT

    1997-10-01

    A key component of the Engineered Barrier System (EBS) being designed for containment of spent-fuel and high-level waste at the proposed geological repository at Yucca Mountain, Nevada is a two-layer canister. In this particular design, the inner barrier is made of a corrosion resistant material (CRM) such as Alloy 625 or C-22, while the outer barrier is made of a corrosion-allowance material (CAM) such as carbon steel or Monel 400. An integrated predictive model is being developed to account for the effects of localized environmental conditions in the CRM-CAM crevice on the initiation and propagation of pits through the CRM.

  13. A Model of Solid Waste Management Based Multilateral Co-Operation in Semi-Urban Community

    Science.gov (United States)

    Kanchanabhandhu, Chanchai; Woraphong, Seree

    2016-01-01

    The purpose of this research was to construct a model of solid waste management based on multilateral cooperation in semi-urban community. Its specific objectives were to 1) study the solid waste situation and involvement of community in the solid waste management in Wangtaku Sub-district, Muang District, Nakhon Pathom Province; 2) construct a…

  14. Mathematical modeling of the emission of heavy metals into water bodies from building materials derived from production waste

    Directory of Open Access Journals (Sweden)

    Pugin Konstantin Georgievich

    2016-01-01

    Full Text Available At the present time industrial waste is considered to be an alternative to primary natural resources when producing construction materials and products. The use of industrial waste in the construction branch allows reducing ecological load on the environment and population as a result of reducing the amount of unrecyclable waste and reducing the use of primary natural resources. Though when involving waste products as raw material in the preparation of building materials there occur environmental risks of anthropogenic impact increase on the environment. These risks are related to possible emission of heavy metals from construction materials in use. The article describes a tool which allows predicting this issue, depending on the acidity of the medium, the residence time of the material in the environment. The experimental data obtained in determining the migration activity of metals from cement concretes to aqueous solutions served as the basis for the mathematical model. The proposed model allows us to make a prediction of anthropogenic impact on the environment and commensurate this impact with the possibility of assimilation of the environment area where the building materials are applied. This will allow conducting an effective assessment of the created and applied technologies of waste disposal, taking into account the operating conditions of the materials produced.

  15. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  16. Genetic models of homosexuality: generating testable predictions

    OpenAIRE

    Gavrilets, Sergey; Rice, William R.

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality inclu...

  17. Descriptive models for single-jet sluicing of sludge waste

    Energy Technology Data Exchange (ETDEWEB)

    Erian, F.F.; Mahoney, L.A.; Terrones, G.

    1997-12-01

    Mobilization of sludge waste stored in underground storage tanks can be achieved safely and reliably by sluicing. In the project discussed in this report, the waste in Hanford single-shell Tank 241-C-106 will be mobilized by sluicing, retrieved by a slurry retrieval pump, and transferred via an 1800-ft slurry pipeline to Tank 241-AY-102. A sluicing strategy must be developed that ensures efficient use of the deployed configuration of the sluicing system: the nozzle(s) and the retrieval pump(s). Given a sluicing system configuration in a particular tank, it is desirable to prescribe the sequential locations at which the sludge will be mobilized and retrieved and the rate at which these mobilization and retrieval processes take place. In addition, it is necessary to know whether the retrieved waste slurry meets the requirements for cross-site slurry transport. Some of the physical phenomena that take place during mobilization and retrieval and certain aspects of the sluicing process are described in this report. First, a mathematical model gives (1) an idealized geometrical representation of where, within the confines of a storage tank containing a certain amount of settled waste, sludge can be removed and mobilized; and (2) a quantitative measure of the amount of sludge that can be removed during a sluicing campaign. A model describing an idealized water jet issuing from a circular nozzle located at a given height above a flat surface is also presented in this report. This dynamic water-jet model provides the basis for improving the geometrical sluicing model presented next. In this model the authors assume that the water jet follows a straight trajectory toward a target point on a flat surface. However, the water jet does not follow a straight line in the actual tank, and using the true trajectory will allow a more accurate estimate of the amount of disturbed material. Also, the authors hope that developing accurate force and pressure fields will lead to a better

  18. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  19. PREDICTING WATER ACTIVITY IN ELECTROLYTE SOLUTIONS WITH THE CISTERNAS-LAM MODEL

    Energy Technology Data Exchange (ETDEWEB)

    REYNOLDS JG; GREER DA; DISSELKAMP RL

    2011-03-01

    Water activity is an important parameter needed to predict the solubility of hydrated salts in Hanford nuclear waste supernatants. A number of models available in the scientific literature predict water activity from electrolyte solution composition. The Cisternas-Lam model is one of those models and has several advantages for nuclear waste application. One advantage is that it has a single electrolyte specific parameter that is temperature independent. Thus, this parameter can be determined from very limited data and extrapolated widely. The Cisternas-Lam model has five coefficients that are used for all aqueous electrolytes. The present study aims to determine if there is a substantial improvement in making all six coefficients electrolyte specific. The Cisternas-Lam model was fit to data for six major electrolytes in Hanford nuclear waste supernatants. The model was first fit to all data to determine the five global coefficients, when they were held constant for all electrolytes it yielded a substantially better fit. Subsequently, the model was fit to each electrolyte dataset separately, where all six coefficients were allowed to be electrolyte specific. Treating all six coefficients as electrolyte specific did not make sufficient difference, given the complexity of applying the electrolyte specific parameters to multi-solute systems. Revised water specific parameters, optimized to the electrolytes relevant to Hanford waste, are also reported.

  20. Waste pretreatment and interfacing system dynamic simulation model (ITHINK model) FY-96 year-end report

    Energy Technology Data Exchange (ETDEWEB)

    Harmsen, R.W.

    1996-09-30

    The Waste Pretreatment and Interfacing Systems Dynamic Simulation (ITHINK) Model (see WHC-SD-WM-DR-013) was originally created to investigate the required pretreatment facility processing rates required to meet the Tri-Party Agreement (TPA) waste vitrification milestones. The TPA milestones are satisfied by retrieving the TX tank farm (salt cake) single-shell tanks (SSTs)first and by utilizing a relatively constant retrieval rate to the year 2018 when retrieval is completed.

  1. A Computer Program for Modeling the Conversion of Organic Waste to Energy

    Directory of Open Access Journals (Sweden)

    Pragasen Pillay

    2011-11-01

    Full Text Available This paper presents a tool for the analysis of conversion of organic waste into energy. The tool is a program that uses waste characterization parameters and mass flow rates at each stage of the waste treatment process to predict the given products. The specific waste treatment process analysed in this paper is anaerobic digestion. The different waste treatment stages of the anaerobic digestion process are: conditioning of input waste, secondary treatment, drying of sludge, conditioning of digestate, treatment of digestate, storage of liquid and solid effluent, disposal of liquid and solid effluents, purification, utilization and storage of combustible gas. The program uses mass balance equations to compute the amount of CH4, NH3, CO2 and H2S produced from anaerobic digestion of organic waste, and hence the energy available. Case studies are also presented.

  2. Solid municipal wastes system using MIME/WASTE model Alava (Spain); Sistema para la gestion de residuos solidos municipales a partir del modelo MIMES/WASTE: el caso de Alava

    Energy Technology Data Exchange (ETDEWEB)

    Artaraz Minon, M.

    2001-07-01

    Environmental policies in European Union should be able to evolve looking for sustainable development. MIMES/Waste Models (Model for description and optimisation of Integrated Materials Flows and Energy Systems) have been developed for analysing solid waste management systems. This article describes the model and the methodology for using it to analyse municipal waste management systems, and processes to apply it in Alava (Spain). The author explains particularly the possibility of making source separation and later treatment of biodegradable waste fraction of household wastes on the one hand, and efficiency of a waste disposal tax on the other hand. (Author) 7 refs.

  3. Predictive model for segmented poly(urea

    Directory of Open Access Journals (Sweden)

    Frankl P.

    2012-08-01

    Full Text Available Segmented poly(urea has been shown to be of significant benefit in protecting vehicles from blast and impact and there have been several experimental studies to determine the mechanisms by which this protective function might occur. One suggested route is by mechanical activation of the glass transition. In order to enable design of protective structures using this material a constitutive model and equation of state are needed for numerical simulation hydrocodes. Determination of such a predictive model may also help elucidate the beneficial mechanisms that occur in polyurea during high rate loading. The tool deployed to do this has been Group Interaction Modelling (GIM – a mean field technique that has been shown to predict the mechanical and physical properties of polymers from their structure alone. The structure of polyurea has been used to characterise the parameters in the GIM scheme without recourse to experimental data and the equation of state and constitutive model predicts response over a wide range of temperatures and strain rates. The shock Hugoniot has been predicted and validated against existing data. Mechanical response in tensile tests has also been predicted and validated.

  4. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  5. Predictive QSAR modeling of phosphodiesterase 4 inhibitors.

    Science.gov (United States)

    Kovalishyn, Vasyl; Tanchuk, Vsevolod; Charochkina, Larisa; Semenuta, Ivan; Prokopenko, Volodymyr

    2012-02-01

    A series of diverse organic compounds, phosphodiesterase type 4 (PDE-4) inhibitors, have been modeled using a QSAR-based approach. 48 QSAR models were compared by following the same procedure with different combinations of descriptors and machine learning methods. QSAR methodologies used random forests and associative neural networks. The predictive ability of the models was tested through leave-one-out cross-validation, giving a Q² = 0.66-0.78 for regression models and total accuracies Ac=0.85-0.91 for classification models. Predictions for the external evaluation sets obtained accuracies in the range of 0.82-0.88 (for active/inactive classifications) and Q² = 0.62-0.76 for regressions. The method showed itself to be a potential tool for estimation of IC₅₀ of new drug-like candidates at early stages of drug development. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Preliminary study on enhancing waste management best practice model in Malaysia construction industry

    Science.gov (United States)

    Jamaludin, Amril Hadri; Karim, Nurulzatushima Abdul; Noor, Raja Nor Husna Raja Mohd; Othman, Nurulhidayah; Malik, Sulaiman Abdul

    2017-08-01

    Construction waste management (CWM) is the practice of minimizing and diverting construction waste, demolition debris, and land-clearing debris from disposal and redirecting recyclable resources back into the construction process. Best practice model means best choice from the collection of other practices that was built for purpose of construction waste management. The practice model can help the contractors in minimizing waste before the construction activities will be started. The importance of minimizing wastage will have direct impact on time, cost and quality of a construction project. This paper is focusing on the preliminary study to determine the factors of waste generation in the construction sites and identify the effectiveness of existing construction waste management practice conducted in Malaysia. The paper will also include the preliminary works of planned research location, data collection method, and analysis to be done by using the Analytical Hierarchy Process (AHP) to help in developing suitable waste management best practice model that can be used in the country.

  7. Time- and stress-dependent model for predicting moisture retention capacity of high-food-waste-content municipal solid waste:based on experimental evidence%题目:考虑应力和时间作用的高厨余含量生活垃圾的持水量预测模型:基于试验现象

    Institute of Scientific and Technical Information of China (English)

    Hui XU; Liang-tong ZHAN; He LI; Ji-wu LAN; Yun-min CHEN; Hai-yan ZHOU

    2016-01-01

    , being subjected to incremental stresses. The following findings were obtained from the test re-sults: (1) The MRC of fresh HFWC-MSW decreased exponentially with degradation time under a sustained stress. The higher waste temperature or oxygen introduction would result in a faster declining of MRC. (2) The MRCs decreased linearly with a logarithmic increase of stress for all the MSW samples with different food waste contents. TheMRC of HFWC-MSW was higher than that of NFWC-MSW under a given stress, and the decomposed MSW took the second place. (3) The variation of MRC appeared to be independent of stress path in terms of stress and degradation time. Based on the test results, the dependen-cies of the MRC of HFWC-MSW on degradation and stress were interpreted. Then, a time- and stress-dependent model was proposed for predicting the MRC of HFWC-MSW. The model was relatively simple and convenient for design purposes, and was verified by the measured data of leachate production at the pretreatment container of Laogang Incineration Plant. Finally, the model was developed to evaluate the dewatering effect of the HFWC-MSW pile. The strategy of combining the degradation-enhancing measures with stress-increasing measures is recommended in a rapid dewatering project.

  8. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-02-01

    Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan.Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities.Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems.Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk.Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product.Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  9. Calibrated predictions for multivariate competing risks models.

    Science.gov (United States)

    Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni

    2014-04-01

    Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.

  10. A two-stage support-vector-regression optimization model for municipal solid waste management - a case study of Beijing, China.

    Science.gov (United States)

    Dai, C; Li, Y P; Huang, G H

    2011-12-01

    In this study, a two-stage support-vector-regression optimization model (TSOM) is developed for the planning of municipal solid waste (MSW) management in the urban districts of Beijing, China. It represents a new effort to enhance the analysis accuracy in optimizing the MSW management system through coupling the support-vector-regression (SVR) model with an interval-parameter mixed integer linear programming (IMILP). The developed TSOM can not only predict the city's future waste generation amount, but also reflect dynamic, interactive, and uncertain characteristics of the MSW management system. Four kernel functions such as linear kernel, polynomial kernel, radial basis function, and multi-layer perception kernel are chosen based on three quantitative simulation performance criteria [i.e. prediction accuracy (PA), fitting accuracy (FA) and over all accuracy (OA)]. The SVR with polynomial kernel has accurate prediction performance for MSW generation rate, with all of the three quantitative simulation performance criteria being over 96%. Two cases are considered based on different waste management policies. The results are valuable for supporting the adjustment of the existing waste-allocation patterns to raise the city's waste diversion rate, as well as the capacity planning of waste management system to satisfy the city's increasing waste treatment/disposal demands.

  11. Modelling language evolution: Examples and predictions.

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  12. Modelling language evolution: Examples and predictions

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  13. Global Solar Dynamo Models: Simulations and Predictions

    Indian Academy of Sciences (India)

    Mausumi Dikpati; Peter A. Gilman

    2008-03-01

    Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.

  14. Glass Property Data and Models for Estimating High-Level Waste Glass Volume

    Energy Technology Data Exchange (ETDEWEB)

    Vienna, John D.; Fluegel, Alexander; Kim, Dong-Sang; Hrma, Pavel R.

    2009-10-05

    This report describes recent efforts to develop glass property models that can be used to help estimate the volume of high-level waste (HLW) glass that will result from vitrification of Hanford tank waste. The compositions of acceptable and processable HLW glasses need to be optimized to minimize the waste-form volume and, hence, to save cost. A database of properties and associated compositions for simulated waste glasses was collected for developing property-composition models. This database, although not comprehensive, represents a large fraction of data on waste-glass compositions and properties that were available at the time of this report. Glass property-composition models were fit to subsets of the database for several key glass properties. These models apply to a significantly broader composition space than those previously publised. These models should be considered for interim use in calculating properties of Hanford waste glasses.

  15. Subcritical and supercritical water oxidation of CELSS model wastes

    Science.gov (United States)

    Takahashi, Y.; Wydeven, T.; Koo, C.

    1989-01-01

    A mixture of ammonium hydroxide with acetic acid and a slurry of human feces, urine, and wipes were used as CELSS model wastes to be wet-oxidized at temperatures from 250 to 500 C, i.e. below and above the critical point of water (374 C and 218 kg/sq cm or 21.4 MPa). The effects of oxidation temperature ( 250-500 C) and residence time (0-120 mn) on carbon and nitrogen and on metal corrosion from the reactor material were studied. Almost all of the organic matter in the model wastes was oxidized in the temperature range from 400 to 500 C, above the critical conditions for water. In contrast, only a small portion of the organic matter was oxidized at subcritical conditions. A substantial amount of nitrogen remained in solution in the form of ammonia at temperatures ranging from 350 to 450 C suggesting that, around 400 C, organic carbon is completely oxidized and most of the nitrogen is retained in solution. The Hastelloy C-276 alloy reactor corroded during subcritical and supercritical water oxidation.

  16. DKIST Polarization Modeling and Performance Predictions

    Science.gov (United States)

    Harrington, David

    2016-05-01

    Calibrating the Mueller matrices of large aperture telescopes and associated coude instrumentation requires astronomical sources and several modeling assumptions to predict the behavior of the system polarization with field of view, altitude, azimuth and wavelength. The Daniel K Inouye Solar Telescope (DKIST) polarimetric instrumentation requires very high accuracy calibration of a complex coude path with an off-axis f/2 primary mirror, time dependent optical configurations and substantial field of view. Polarization predictions across a diversity of optical configurations, tracking scenarios, slit geometries and vendor coating formulations are critical to both construction and contined operations efforts. Recent daytime sky based polarization calibrations of the 4m AEOS telescope and HiVIS spectropolarimeter on Haleakala have provided system Mueller matrices over full telescope articulation for a 15-reflection coude system. AEOS and HiVIS are a DKIST analog with a many-fold coude optical feed and similar mirror coatings creating 100% polarization cross-talk with altitude, azimuth and wavelength. Polarization modeling predictions using Zemax have successfully matched the altitude-azimuth-wavelength dependence on HiVIS with the few percent amplitude limitations of several instrument artifacts. Polarization predictions for coude beam paths depend greatly on modeling the angle-of-incidence dependences in powered optics and the mirror coating formulations. A 6 month HiVIS daytime sky calibration plan has been analyzed for accuracy under a wide range of sky conditions and data analysis algorithms. Predictions of polarimetric performance for the DKIST first-light instrumentation suite have been created under a range of configurations. These new modeling tools and polarization predictions have substantial impact for the design, fabrication and calibration process in the presence of manufacturing issues, science use-case requirements and ultimate system calibration

  17. Modelling Chemical Reasoning to Predict Reactions

    OpenAIRE

    Segler, Marwin H. S.; Waller, Mark P.

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outpe...

  18. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert; Knox, James

    2016-01-01

    Fully predictive models of the Four Bed Molecular Sieve of the Carbon Dioxide Removal Assembly on the International Space Station are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  19. Raman Model Predicting Hardness of Covalent Crystals

    OpenAIRE

    Zhou, Xiang-Feng; Qian, Quang-Rui; Sun, Jian; Tian, Yongjun; Wang, Hui-Tian

    2009-01-01

    Based on the fact that both hardness and vibrational Raman spectrum depend on the intrinsic property of chemical bonds, we propose a new theoretical model for predicting hardness of a covalent crystal. The quantitative relationship between hardness and vibrational Raman frequencies deduced from the typical zincblende covalent crystals is validated to be also applicable for the complex multicomponent crystals. This model enables us to nondestructively and indirectly characterize the hardness o...

  20. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts

  1. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  2. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ

  3. Prediction modelling for population conviction data

    NARCIS (Netherlands)

    Tollenaar, N.

    2017-01-01

    In this thesis, the possibilities of using prediction models for judicial penal case data are investigated. The development and refinement of a risk taxation scale based on these data is discussed. When false positives are weighted equally severe as false negatives, 70% can be classified correctly.

  4. A Predictive Model for MSSW Student Success

    Science.gov (United States)

    Napier, Angela Michele

    2011-01-01

    This study tested a hypothetical model for predicting both graduate GPA and graduation of University of Louisville Kent School of Social Work Master of Science in Social Work (MSSW) students entering the program during the 2001-2005 school years. The preexisting characteristics of demographics, academic preparedness and culture shock along with…

  5. Predictability of extreme values in geophysical models

    NARCIS (Netherlands)

    Sterk, A.E.; Holland, M.P.; Rabassa, P.; Broer, H.W.; Vitolo, R.

    2012-01-01

    Extreme value theory in deterministic systems is concerned with unlikely large (or small) values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical model

  6. A revised prediction model for natural conception

    NARCIS (Netherlands)

    Bensdorp, A.J.; Steeg, J.W. van der; Steures, P.; Habbema, J.D.; Hompes, P.G.; Bossuyt, P.M.; Veen, F. van der; Mol, B.W.; Eijkemans, M.J.; Kremer, J.A.M.; et al.,

    2017-01-01

    One of the aims in reproductive medicine is to differentiate between couples that have favourable chances of conceiving naturally and those that do not. Since the development of the prediction model of Hunault, characteristics of the subfertile population have changed. The objective of this analysis

  7. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  8. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ

  9. Leptogenesis in minimal predictive seesaw models

    CERN Document Server

    Björkeroth, Fredrik; Varzielas, Ivo de Medeiros; King, Stephen F

    2015-01-01

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to $(\

  10. Ion Exchange Modeling Of Cesium Removal From Hanford Waste Using Spherical Resorcinol-Formaldehyde Resin

    Energy Technology Data Exchange (ETDEWEB)

    Aleman, S. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Hamm, L. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Smith, F. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2007-06-27

    This report discusses the expected performance of spherical Resorcinol-Formaldehyde (RF) ion exchange resin for the removal of cesium from alkaline Hanford radioactive waste. Predictions of full scale column performance in a carousel mode are made for the Hot Commissioning, Envelope B, and Subsequent Operations waste compositions under nominal operating conditions and for perturbations from the nominal. Only the loading phase of the process cycle is addressed in this report. Pertinent bench-scale column tests, kinetic experiments, and batch equilibrium experiments are used to estimate model parameters and to benchmark the ion-exchange model. The methodology and application presented in this report reflect the expected behavior of spherical RF resin manufactured at the intermediate-scale (i.e., approximately 100 gallon batch size; batch 5E-370/641). It is generally believed that scale-up to production-scale in resin manufacturing will result in similarly behaving resin batches whose chemical selectivity is unaffected while total capacity per gram of resin may vary some. As such, the full-scale facility predictions provided within this report should provide reasonable estimates of production-scale column performance.

  11. Specialized Language Models using Dialogue Predictions

    CERN Document Server

    Popovici, C; Popovici, Cosmin; Baggia, Paolo

    1996-01-01

    This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter. The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover other methods to increase performance, like automatic clustering of vocabulary words or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models. The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues coll...

  12. Caries risk assessment models in caries prediction

    Directory of Open Access Journals (Sweden)

    Amila Zukanović

    2013-11-01

    Full Text Available Objective. The aim of this research was to assess the efficiency of different multifactor models in caries prediction. Material and methods. Data from the questionnaire and objective examination of 109 examinees was entered into the Cariogram, Previser and Caries-Risk Assessment Tool (CAT multifactor risk assessment models. Caries risk was assessed with the help of all three models for each patient, classifying them as low, medium or high-risk patients. The development of new caries lesions over a period of three years [Decay Missing Filled Tooth (DMFT increment = difference between Decay Missing Filled Tooth Surface (DMFTS index at baseline and follow up], provided for examination of the predictive capacity concerning different multifactor models. Results. The data gathered showed that different multifactor risk assessment models give significantly different results (Friedman test: Chi square = 100.073, p=0.000. Cariogram is the model which identified the majority of examinees as medium risk patients (70%. The other two models were more radical in risk assessment, giving more unfavorable risk –profiles for patients. In only 12% of the patients did the three multifactor models assess the risk in the same way. Previser and CAT gave the same results in 63% of cases – the Wilcoxon test showed that there is no statistically significant difference in caries risk assessment between these two models (Z = -1.805, p=0.071. Conclusions. Evaluation of three different multifactor caries risk assessment models (Cariogram, PreViser and CAT showed that only the Cariogram can successfully predict new caries development in 12-year-old Bosnian children.

  13. Disease prediction models and operational readiness.

    Directory of Open Access Journals (Sweden)

    Courtney D Corley

    Full Text Available The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011. We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4, spatial (26, ecological niche (28, diagnostic or clinical (6, spread or response (9, and reviews (3. The model parameters (e.g., etiology, climatic, spatial, cultural and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological were recorded and reviewed. A component of this review is the identification of verification and validation (V&V methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology

  14. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...

  15. The modeling method of diffusion of radio activated materials in clay waste disposals

    Energy Technology Data Exchange (ETDEWEB)

    Saberi, Reza; Sepanloo, Kamran [NSTRI, Tehran (Iran, Islamic Republic of); Alinejad, Majid [Engineering Research Institute of Natural Hazard, Isfahan (Iran, Islamic Republic of); Mozaffari, Ali [KNT Univ. of Technology, Tehran (Iran, Islamic Republic of)

    2017-02-15

    New nuclear power plants are necessary to meet today's and future challenges of energy supply. Nuclear power is the only large-scale energy source that takes full responsibility for all its wastes. Nuclear wastes are particularly hazardous and hard to manage relative to different toxic industrial wastes. Three methods are presented and analysed to model the diffusion of the waste from the waste disposal to the bottom surface. For this purpose three software programmes such as ABAQUS, Matlab coding, Geostudio and ArcGIS have been applied.

  16. A model for improving sustainble green waste recovery

    NARCIS (Netherlands)

    Inghels, D.; Dullaert, W.; Bloemhof-Ruwaard, J.M.

    2016-01-01

    Green waste, consisting of leaves, wood cuttings from pruning, and grass collected from parks and gardens, is a source of biomass that can be used for material and energy valorization. Until recently, the EU-Waste Directive 2009/28/EC allowed green waste to be used as feedstock only for compost. Thi

  17. Development of a methodology for electronic waste estimation: A material flow analysis-based SYE-Waste Model.

    Science.gov (United States)

    Yedla, Sudhakar

    2016-01-01

    Improved living standards and the share of services sector to the economy in Asia, and the use of electronic equipment is on the rise and results in increased electronic waste generation. A peculiarity of electronic waste is that it has a 'significant' value even after its life time, and to add complication, even after its extended life in its 'dump' stage. Thus, in Indian situations, after its life time is over, the e-material changes hands more than once and finally ends up either in the hands of informal recyclers or in the store rooms of urban dwellings. This character makes it extremely difficult to estimate electronic waste generation. The present study attempts to develop a functional model based on a material flow analysis approach by considering all possible end uses of the material, its transformed goods finally arriving at disposal. It considers various degrees of uses derived of the e-goods regarding their primary use (life time), secondary use (first degree extension of life), third-hand use (second degree extension of life), donation, retention at the respective places (without discarding), fraction shifted to scrap vendor, and the components reaching the final dump site from various end points of use. This 'generic functional model' named SYE-Waste Model, developed based on a material flow analysis approach, can be used to derive 'obsolescence factors' for various degrees of usage of e-goods and also to make a comprehensive estimation of electronic waste in any city/country.

  18. Property-Composition-Temperature Modeling of Waste Glass Melt Data Subject to a Randomization Restriction

    Energy Technology Data Exchange (ETDEWEB)

    Piepel, Gregory F.; Heredia-Langner, Alejandro; Cooley, Scott K.

    2008-10-01

    Properties such as viscosity and electrical conductivity of glass melts are functions of melt temperature as well as glass composition. When measuring such a property for several glasses, the property is typically measured at several temperatures for one glass, then at several temperatures for the next glass, and so on. This data-collection process involves a restriction on randomization, which is referred to as split-plot experiment. The split-plot data structure must be accounted for in developing property-composition-temperature models and the corresponding uncertainty equations for model predictions. Instead of ordinary least squares (OLS) regression methods, generalized least squares (GLS) regression methods using restricted maximum likelihood (REML) estimation must be used. This article describes the methodology for developing property-composition-temperature models and corresponding prediction uncertainty equations using the GLS/REML regression approach. Viscosity data collected on 197 simulated nuclear waste glasses are used to illustrate the GLS/REML methods for developing a viscosity-composition-temperature model and corresponding equations for model prediction uncertainties. The correct results using GLS/REML regression are compared to the incorrect results obtained using OLS regression.

  19. Trickling filter for urea and bio-waste processing - dynamic modelling of nitrogen cycle

    Science.gov (United States)

    Zhukov, Anton; Hauslage, Jens; Tertilt, Gerin; Bornemann, Gerhild

    Mankind’s exploration of the solar system requires reliable Life Support Systems (LSS) enabling long duration manned space missions. In the absence of frequent resupply missions, closure of the LSS will play a very important role and its maximisation will to a large extent drive the selection of appropriate LSS architectures. One of the significant issues on the way to full closure is to effectively utilise biological wastes such as urine, inedible biomass etc. A very promising concept of biological waste reprocessing is the use of trickling filters which are currently being developed and investigated by DLR, Cologne, Germany. The concept is called Combined Regenerative Organic-Food Production (C.R.O.P.) and is based on the microbiological treatment of biological wastes and reprocessing them into aqueous fertilizer which can directly be used in a greenhouse for food production. Numerous experiments have been and are being conducted by DLR in order to fully understand and characterize the process. The human space exploration group of the Technical University of Munich (TUM) in cooperation with DLR has started to establish a dynamic model of the trickling filter system to be able to assess its performance on the LSS level. In the first development stage the model covers the nitrogen cycle enabling to simulate urine processing. This paper describes briefly the C.R.O.P. concept and the status of the trickling filter model development. The model is based on enzyme-catalyzed reaction kinetics for the fundamental microbiological reaction chain and is created in MATLAB. Verification and correlation of the developed model with experiment results has been performed. Several predictive studies for batch sequencing behavior have been performed, demonstrating a good capability of C.R.O.P. concept to be used in closed LSS. Achieved results are critically discussed and way forward is presented.

  20. Environmental modelling of use of treated organic waste on agricultural land

    DEFF Research Database (Denmark)

    Hansen, Trine Lund; Christensen, Thomas Højlund; Schmidt, S.

    2006-01-01

    . THE IFEU PROJECT, ORWARE and EASEWASTE are life cycle assessment (LCA) models containing more detailed land application modules. A case study estimating the environmental impacts from land application of 1 ton of composted source sorted organic household waste was performed to compare the results from......Modelling of environmental impacts from the application of treated organic municipal solid waste (MSW) in agriculture differs widely between different models for environmental assessment of waste systems. In this comparative study five models were examined concerning quantification and impact...... assessment of environmental effects from land application of treated organic MSW: DST (Decision Support Tool, USA), IWM (Integrated Waste Management, UK), THE IFEU PROJECT (Germany), ORWARE (ORganic WAste REsearch, Sweden) and EASEWASTE (Environmental Assessment of Solid Waste Systems and Technologies...

  1. ENSO Prediction using Vector Autoregressive Models

    Science.gov (United States)

    Chapman, D. R.; Cane, M. A.; Henderson, N.; Lee, D.; Chen, C.

    2013-12-01

    A recent comparison (Barnston et al, 2012 BAMS) shows the ENSO forecasting skill of dynamical models now exceeds that of statistical models, but the best statistical models are comparable to all but the very best dynamical models. In this comparison the leading statistical model is the one based on the Empirical Model Reduction (EMR) method. Here we report on experiments with multilevel Vector Autoregressive models using only sea surface temperatures (SSTs) as predictors. VAR(L) models generalizes Linear Inverse Models (LIM), which are a VAR(1) method, as well as multilevel univariate autoregressive models. Optimal forecast skill is achieved using 12 to 14 months of prior state information (i.e 12-14 levels), which allows SSTs alone to capture the effects of other variables such as heat content as well as seasonality. The use of multiple levels allows the model advancing one month at a time to perform at least as well for a 6 month forecast as a model constructed to explicitly forecast 6 months ahead. We infer that the multilevel model has fully captured the linear dynamics (cf. Penland and Magorian, 1993 J. Climate). Finally, while VAR(L) is equivalent to L-level EMR, we show in a 150 year cross validated assessment that we can increase forecast skill by improving on the EMR initialization procedure. The greatest benefit of this change is in allowing the prediction to make effective use of information over many more months.

  2. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  3. Gas explosion prediction using CFD models

    Energy Technology Data Exchange (ETDEWEB)

    Niemann-Delius, C.; Okafor, E. [RWTH Aachen Univ. (Germany); Buhrow, C. [TU Bergakademie Freiberg Univ. (Germany)

    2006-07-15

    A number of CFD models are currently available to model gaseous explosions in complex geometries. Some of these tools allow the representation of complex environments within hydrocarbon production plants. In certain explosion scenarios, a correction is usually made for the presence of buildings and other complexities by using crude approximations to obtain realistic estimates of explosion behaviour as can be found when predicting the strength of blast waves resulting from initial explosions. With the advance of computational technology, and greater availability of computing power, computational fluid dynamics (CFD) tools are becoming increasingly available for solving such a wide range of explosion problems. A CFD-based explosion code - FLACS can, for instance, be confidently used to understand the impact of blast overpressures in a plant environment consisting of obstacles such as buildings, structures, and pipes. With its porosity concept representing geometry details smaller than the grid, FLACS can represent geometry well, even when using coarse grid resolutions. The performance of FLACS has been evaluated using a wide range of field data. In the present paper, the concept of computational fluid dynamics (CFD) and its application to gas explosion prediction is presented. Furthermore, the predictive capabilities of CFD-based gaseous explosion simulators are demonstrated using FLACS. Details about the FLACS-code, some extensions made to FLACS, model validation exercises, application, and some results from blast load prediction within an industrial facility are presented. (orig.)

  4. Genetic models of homosexuality: generating testable predictions.

    Science.gov (United States)

    Gavrilets, Sergey; Rice, William R

    2006-12-22

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism.

  5. Characterizing Attention with Predictive Network Models.

    Science.gov (United States)

    Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

    2017-04-01

    Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. A Study On Distributed Model Predictive Consensus

    CERN Document Server

    Keviczky, Tamas

    2008-01-01

    We investigate convergence properties of a proposed distributed model predictive control (DMPC) scheme, where agents negotiate to compute an optimal consensus point using an incremental subgradient method based on primal decomposition as described in Johansson et al. [2006, 2007]. The objective of the distributed control strategy is to agree upon and achieve an optimal common output value for a group of agents in the presence of constraints on the agent dynamics using local predictive controllers. Stability analysis using a receding horizon implementation of the distributed optimal consensus scheme is performed. Conditions are given under which convergence can be obtained even if the negotiations do not reach full consensus.

  7. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    R. G. SILVA

    1999-03-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  8. Models for recurrent gas release event behavior in hazardous waste tanks

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, D.N. [Pacific Northwest Lab., Richland, WA (United States); Arnold, B.C. [California Univ., Riverside, CA (United States). Dept. of Statistics

    1994-08-01

    Certain radioactive waste storage tanks at the United States Department of Energy Hanford facilities continuously generate gases as a result of radiolysis and chemical reactions. The congealed sludge in these tanks traps the gases and causes the level of the waste within the tanks to rise. The waste level continues to rise until the sludge becomes buoyant and ``rolls over``, changing places with heavier fluid on top. During a rollover, the trapped gases are released, resulting, in a sudden drop in the waste level. This is known as a gas release event (GRE). After a GRE, the wastes leading to another GRE. We present nonlinear time waste re-congeals and gas again accumulates leading to another GRE. We present nonlinear time series models that produce simulated sample paths that closely resemble the temporal history of waste levels in these tanks. The models also imitate the random GRE, behavior observed in the temporal waste level history of a storage tank. We are interested in using the structure of these models to understand the probabilistic behavior of the random variable ``time between consecutive GRE`s``. Understanding the stochastic nature of this random variable is important because the hydrogen and nitrous oxide gases released from a GRE, are flammable and the ammonia that is released is a health risk. From a safety perspective, activity around such waste tanks should be halted when a GRE is imminent. With credible GRE models, we can establish time windows in which waste tank research and maintenance activities can be safely performed.

  9. Explanation of Significant Differences Between Models used to Assess Groundwater Impacts for the Disposal of Greater-Than-Class C Low-Level Radioactive Waste and Greater-Than-Class C-Like Waste Environmental Impact Statement (DOE/EIS-0375-D) and the

    Energy Technology Data Exchange (ETDEWEB)

    Annette Schafer; Arthur S. Rood; A. Jeffrey Sondrup

    2011-08-01

    Models have been used to assess the groundwater impacts to support the Draft Environmental Impact Statement for the Disposal of Greater-Than-Class C (GTCC) Low-Level Radioactive Waste and GTCC-Like Waste (DOE-EIS 2011) for a facility sited at the Idaho National Laboratory and the Environmental Assessment for the INL Remote-Handled Low-Level Waste Disposal Project (INL 2011). Groundwater impacts are primarily a function of (1) location determining the geologic and hydrologic setting, (2) disposal facility configuration, and (3) radionuclide source, including waste form and release from the waste form. In reviewing the assumptions made between the model parameters for the two different groundwater impacts assessments, significant differences were identified. This report presents the two sets of model assumptions and discusses their origins and implications for resulting dose predictions. Given more similar model parameters, predicted doses would be commensurate.

  10. Extraction of lycopene from tomato processing waste: kinetics and modelling.

    Science.gov (United States)

    Poojary, Mahesha M; Passamonti, Paolo

    2015-04-15

    Lycopene, a nutraceutical compound, was extracted from tomato processing waste, an abundantly available food industry by-product in Italy. The extraction kinetics was mathematically described using the first order kinetic model, the mass transfer model and Peleg's model to understand the physicochemical behaviour of the extraction. Samples were extracted using acetone/n-hexane mixtures at different ratios (1:3, 2:2 and 3:1, v/v) and at different temperatures (30, 40 and 50 °C) and simultaneously analysed using UV-VIS spectrophotometry. The lycopene yield was in the range 3.47-4.03 mg/100g, which corresponds to a percentage recovery of 65.22-75.75. All kinetic models gave a good fit to the experimental data, but the best one was Peleg's model, having the highest RAdj(2) and the lowest RMSE, MBE and χ(2) values. All the models confirmed that a temperature of 30 °C and solvent mixture of acetone/n-hexane 1:3 (v/v) provided optimal conditions for extraction of lycopene.

  11. Modeling Coupled Processes in Clay Formations for Radioactive Waste Disposal

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui-Hai; Rutqvist, Jonny; Zheng, Liange; Sonnenthal, Eric; Houseworth, Jim; Birkholzer, Jens

    2010-08-31

    As a result of the termination of the Yucca Mountain Project, the United States Department of Energy (DOE) has started to explore various alternative avenues for the disposition of used nuclear fuel and nuclear waste. The overall scope of the investigation includes temporary storage, transportation issues, permanent disposal, various nuclear fuel types, processing alternatives, and resulting waste streams. Although geologic disposal is not the only alternative, it is still the leading candidate for permanent disposal. The realm of geologic disposal also offers a range of geologic environments that may be considered, among those clay shale formations. Figure 1-1 presents the distribution of clay/shale formations within the USA. Clay rock/shale has been considered as potential host rock for geological disposal of high-level nuclear waste throughout the world, because of its low permeability, low diffusion coefficient, high retention capacity for radionuclides, and capability to self-seal fractures induced by tunnel excavation. For example, Callovo-Oxfordian argillites at the Bure site, France (Fouche et al., 2004), Toarcian argillites at the Tournemire site, France (Patriarche et al., 2004), Opalinus clay at the Mont Terri site, Switzerland (Meier et al., 2000), and Boom clay at Mol site, Belgium (Barnichon et al., 2005) have all been under intensive scientific investigations (at both field and laboratory scales) for understanding a variety of rock properties and their relations with flow and transport processes associated with geological disposal of nuclear waste. Clay/shale formations may be generally classified as indurated and plastic clays (Tsang et al., 2005). The latter (including Boom clay) is a softer material without high cohesion; its deformation is dominantly plastic. For both clay rocks, coupled thermal, hydrological, mechanical and chemical (THMC) processes are expected to have a significant impact on the long-term safety of a clay repository. For

  12. Performance model to predict overall defect density

    Directory of Open Access Journals (Sweden)

    J Venkatesh

    2012-08-01

    Full Text Available Management by metrics is the expectation from the IT service providers to stay as a differentiator. Given a project, the associated parameters and dynamics, the behaviour and outcome need to be predicted. There is lot of focus on the end state and in minimizing defect leakage as much as possible. In most of the cases, the actions taken are re-active. It is too late in the life cycle. Root cause analysis and corrective actions can be implemented only to the benefit of the next project. The focus has to shift left, towards the execution phase than waiting for lessons to be learnt post the implementation. How do we pro-actively predict defect metrics and have a preventive action plan in place. This paper illustrates the process performance model to predict overall defect density based on data from projects in an organization.

  13. Chemical analysis of simulated high level waste glasses to support stage III sulfate solubility modeling

    Energy Technology Data Exchange (ETDEWEB)

    Fox, K. M. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2016-03-17

    The U.S. Department of Energy (DOE), Office of Environmental Management (EM) is sponsoring an international, collaborative project to develop a fundamental model for sulfate solubility in nuclear waste glass. The solubility of sulfate has a significant impact on the achievable waste loading for nuclear waste forms within the DOE complex. These wastes can contain relatively high concentrations of sulfate, which has low solubility in borosilicate glass. This is a significant issue for low-activity waste (LAW) glass and is projected to have a major impact on the Hanford Tank Waste Treatment and Immobilization Plant (WTP). Sulfate solubility has also been a limiting factor for recent high level waste (HLW) sludge processed at the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF). The low solubility of sulfate in glass, along with melter and off-gas corrosion constraints, dictate that the waste be blended with lower sulfate concentration waste sources or washed to remove sulfate prior to vitrification. The development of enhanced borosilicate glass compositions with improved sulfate solubility will allow for higher waste loadings and accelerate mission completion.The objective of the current scope being pursued by SHU is to mature the sulfate solubility model to the point where it can be used to guide glass composition development for DWPF and WTP, allowing for enhanced waste loadings and waste throughput at these facilities. A series of targeted glass compositions was selected to resolve data gaps in the model and is identified as Stage III. SHU fabricated these glasses and sent samples to SRNL for chemical composition analysis. SHU will use the resulting data to enhance the sulfate solubility model and resolve any deficiencies. In this report, SRNL provides chemical analyses for the Stage III, simulated HLW glasses fabricated by SHU in support of the sulfate solubility model development.

  14. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  15. Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

    Science.gov (United States)

    Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved. PMID:24516363

  16. Neural and hybrid modeling: an alternative route to efficiently predict the behavior of biotechnological processes aimed at biofuels obtainment.

    Science.gov (United States)

    Curcio, Stefano; Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

  17. The Component Slope Linear Model for Calculating Intensive Partial Molar Properties: Application to Waste Glasses

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, Jacob G. [Washington River Protection Solutions, Richland, WA (United States)

    2013-01-11

    Partial molar properties are the changes occurring when the fraction of one component is varied while the fractions of all other component mole fractions change proportionally. They have many practical and theoretical applications in chemical thermodynamics. Partial molar properties of chemical mixtures are difficult to measure because the component mole fractions must sum to one, so a change in fraction of one component must be offset with a change in one or more other components. Given that more than one component fraction is changing at a time, it is difficult to assign a change in measured response to a change in a single component. In this study, the Component Slope Linear Model (CSLM), a model previously published in the statistics literature, is shown to have coefficients that correspond to the intensive partial molar properties. If a measured property is plotted against the mole fraction of a component while keeping the proportions of all other components constant, the slope at any given point on a graph of this curve is the partial molar property for that constituent. Actually plotting this graph has been used to determine partial molar properties for many years. The CSLM directly includes this slope in a model that predicts properties as a function of the component mole fractions. This model is demonstrated by applying it to the constant pressure heat capacity data from the NaOH-NaAl(OH{sub 4}H{sub 2}O system, a system that simplifies Hanford nuclear waste. The partial molar properties of H{sub 2}O, NaOH, and NaAl(OH){sub 4} are determined. The equivalence of the CSLM and the graphical method is verified by comparing results detennined by the two methods. The CSLM model has been previously used to predict the liquidus temperature of spinel crystals precipitated from Hanford waste glass. Those model coefficients are re-interpreted here as the partial molar spinel liquidus temperature of the glass components.

  18. Pressure prediction model for compression garment design.

    Science.gov (United States)

    Leung, W Y; Yuen, D W; Ng, Sun Pui; Shi, S Q

    2010-01-01

    Based on the application of Laplace's law to compression garments, an equation for predicting garment pressure, incorporating the body circumference, the cross-sectional area of fabric, applied strain (as a function of reduction factor), and its corresponding Young's modulus, is developed. Design procedures are presented to predict garment pressure using the aforementioned parameters for clinical applications. Compression garments have been widely used in treating burning scars. Fabricating a compression garment with a required pressure is important in the healing process. A systematic and scientific design method can enable the occupational therapist and compression garments' manufacturer to custom-make a compression garment with a specific pressure. The objectives of this study are 1) to develop a pressure prediction model incorporating different design factors to estimate the pressure exerted by the compression garments before fabrication; and 2) to propose more design procedures in clinical applications. Three kinds of fabrics cut at different bias angles were tested under uniaxial tension, as were samples made in a double-layered structure. Sets of nonlinear force-extension data were obtained for calculating the predicted pressure. Using the value at 0° bias angle as reference, the Young's modulus can vary by as much as 29% for fabric type P11117, 43% for fabric type PN2170, and even 360% for fabric type AP85120 at a reduction factor of 20%. When comparing the predicted pressure calculated from the single-layered and double-layered fabrics, the double-layered construction provides a larger range of target pressure at a particular strain. The anisotropic and nonlinear behaviors of the fabrics have thus been determined. Compression garments can be methodically designed by the proposed analytical pressure prediction model.

  19. Statistical assessment of predictive modeling uncertainty

    Science.gov (United States)

    Barzaghi, Riccardo; Marotta, Anna Maria

    2017-04-01

    When the results of geophysical models are compared with data, the uncertainties of the model are typically disregarded. We propose a method for defining the uncertainty of a geophysical model based on a numerical procedure that estimates the empirical auto and cross-covariances of model-estimated quantities. These empirical values are then fitted by proper covariance functions and used to compute the covariance matrix associated with the model predictions. The method is tested using a geophysical finite element model in the Mediterranean region. Using a novel χ2 analysis in which both data and model uncertainties are taken into account, the model's estimated tectonic strain pattern due to the Africa-Eurasia convergence in the area that extends from the Calabrian Arc to the Alpine domain is compared with that estimated from GPS velocities while taking into account the model uncertainty through its covariance structure and the covariance of the GPS estimates. The results indicate that including the estimated model covariance in the testing procedure leads to lower observed χ2 values that have better statistical significance and might help a sharper identification of the best-fitting geophysical models.

  20. Seasonal Predictability in a Model Atmosphere.

    Science.gov (United States)

    Lin, Hai

    2001-07-01

    The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.

  1. Proposed Model For Industrial Waste Management Practices and Its Impact on Organisational Performance

    Directory of Open Access Journals (Sweden)

    Suzy Noviyanti

    2015-03-01

    Full Text Available Due to environment protection issue, waste management becomes one of important factors in maintaining organization sustainability. In developed country, a growing number of companies began to integrate the pro environment practices, such as waste management practices, into their business strategy. In contrast, the implementation of waste management practices by business organizations in developing country, like Indonesia, is still rare. Waste generated by industries is greater than the capacity to manage this volume of waste. This poses a problem that leads to improper disposal of waste and pollution. This study aims to design a research model which investigates the relation of institutional environment including cognitive, regulatory, and normative element; manager environmental attitudes, worker environmental attitudes, environmental policy, strategic waste management practices, and financial performance.

  2. A kinetic model for predicting biodegradation.

    Science.gov (United States)

    Dimitrov, S; Pavlov, T; Nedelcheva, D; Reuschenbach, P; Silvani, M; Bias, R; Comber, M; Low, L; Lee, C; Parkerton, T; Mekenyan, O

    2007-01-01

    Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a '10 day window' criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the '10-day window' criterion.

  3. A survey of the influencing factors and models for resident's household waste management behavior

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The problem of household solid waste has been concerned and researched on by municipalities and researchers.At present, household solid waste has been changed to management problem from technical one. From the point view of management, the research on household solid waste is to study the factors which influence resident's behavior of managtng their waste. Based on the literature review, firstly, this paper summarizes those factors which have already been identified to have impact on resident's behavior of managing their waste. They are social-demographic variables,knowledge, environmental values, psychological factors, publicity and system design. Secondly, three typical models of the relationship between factors and behavior, which are factors determining task performance in waste management,conceptualization of waste management behavior and the theoretical model of repeated behavior on household waste management, are analyzed and the deficiencies of these models are also analyzed. Finally, according to the current situation in household waste management and the culture and resident's habits in China, this paper puts forward a research focus and suggestions about resident 's behavior of household solid waste management.

  4. Disease Prediction Models and Operational Readiness

    Energy Technology Data Exchange (ETDEWEB)

    Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.

    2014-03-19

    INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the

  5. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  6. A micromechanical model for predicting hydride embrittlement in nuclear fuel cladding material

    Science.gov (United States)

    Chan, K. S.

    1996-01-01

    A major concern about nuclear fuel cladding under waste repository conditions is that the slow cooling rate anticipated in the repository may lead to the formation of excessive radial hydrides, and cause embrittlement of the cladding materials. In this paper, the development of a micromechanical model for predicting hydride-induced embrittlement in nuclear fuel cladding is presented. The important features of the proposed model are: (1) the capability to predict the orientation, morphology, and types of hydrides under the influence of key variables such as cooling rate, internal pressure, and time, and (2) the ability to predict the influence of hydride orientation and morphology on the tensile ductility and fracture toughness of the cladding material. Various model calculations are presented to illustrate the characteristics and utilities of the proposed methodology. A series of experiments was also performed to check assumptions used and to verify some of the model predictions.

  7. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  8. Modelling of Evaporator in Waste Heat Recovery System using Finite Volume Method and Fuzzy Technique

    Directory of Open Access Journals (Sweden)

    Jahedul Islam Chowdhury

    2015-12-01

    Full Text Available The evaporator is an important component in the Organic Rankine Cycle (ORC-based Waste Heat Recovery (WHR system since the effective heat transfer of this device reflects on the efficiency of the system. When the WHR system operates under supercritical conditions, the heat transfer mechanism in the evaporator is unpredictable due to the change of thermo-physical properties of the fluid with temperature. Although the conventional finite volume model can successfully capture those changes in the evaporator of the WHR process, the computation time for this method is high. To reduce the computation time, this paper develops a new fuzzy based evaporator model and compares its performance with the finite volume method. The results show that the fuzzy technique can be applied to predict the output of the supercritical evaporator in the waste heat recovery system and can significantly reduce the required computation time. The proposed model, therefore, has the potential to be used in real time control applications.

  9. Applying Neural Network to Dynamic Modeling of Biosurfactant Production Using Soybean Oil Refinery Wastes

    Directory of Open Access Journals (Sweden)

    Shokoufe Tayyebi

    2013-01-01

    Full Text Available Biosurfactants are surface active compounds produced by various microorganisms. Production of biosurfactants via fermentation of immiscible wastes has the dual benefit of creating economic opportunities for manufacturers, while improving environmental health. A predictor system, recommended in such processes, must be scaled-up. Hence, four neural networks were developed for the dynamic modeling of the biosurfactant production kinetics, in presence of soybean oil or refinery wastes including acid oil, deodorizer distillate and soap stock. Each proposed feed forward neural network consists of three layers which are not fully connected. The input and output data for the training and validation of the neural network models were gathered from batch fermentation experiments. The proposed neural network models were evaluated by three statistical criteria (R2, RMSE and SE. The typical regression analysis showed high correlation coefficients greater than 0.971, demonstrating that the neural network is an excellent estimator for prediction of biosurfactant production kinetic data in a two phase liquid-liquid batch fermentation system. In addition, sensitivity analysis indicates that residual oil has the significant effect (i.e. 49% on the biosurfactant in the process.

  10. Modeling and simulation of lab-scale anaerobic co-digestion of MEA waste

    Directory of Open Access Journals (Sweden)

    Shuai Wang

    2014-01-01

    Full Text Available Anaerobic digestion model No.1 (ADM1 was applied and expanded in this study to model and simulate anaerobic digestion (AD of an industrial carbon capture reclaimer MEA (monoethanolamine waste (MEAw together with easily degradable organics. The general structure of ADM1 was not changed except for introducing state variables of MEA and complex organics (CO in the waste and biochemical reactions of MEA uptake and CO hydrolysis in the model ADM1_MEAw. Experimental batch test results were used for calibrating kinetics variables. The obtained kinetics were employed in the ADM1_MEAw to simulate semi-continuously fed experimental test for 486 days at room temperature (22 +/- 2oC. The validation results show that the ADM1_MEAw was able to predict the process performance with reasonable accuracy, including process pH, biogas generation and inorganic nitrogen concentrations, for a wide range of feed scenarios. Free ammonia inhibition, was observed to be the main inhibitory effects on acetoclastic methanogenesis, leading to volatile fatty acids (VFA accumulation at high loads. Inhibition assumed to be caused by potentially toxic constituents of MEAw appears to be much less important than ammonia, suggesting that such constituents were broken down by AD.

  11. Probabilistic prediction models for aggregate quarry siting

    Science.gov (United States)

    Robinson, G.R.; Larkins, P.M.

    2007-01-01

    Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

  12. Comparison of short term rainfall forecasts for model based flow prediction in urban drainage systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas;

    2012-01-01

    Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 hours. The best...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  13. Comparison Of Short Term Rainfall Forecasts For Model Based Flow Prediction In Urban Drainage Systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Poulsen, Troels Sander; Bøvith, Thomas;

    2012-01-01

    Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 hours. The best...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  14. Comparison of short term rainfall forecasts for model based flow prediction in urban drainage systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas

    2012-01-01

    Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 hours. The best...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  15. Comparison Of Short Term Rainfall Forecasts For Model Based Flow Prediction In Urban Drainage Systems

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Poulsen, Troels Sander; Bøvith, Thomas

    2012-01-01

    Forecast based flow prediction in drainage systems can be used to implement real time control of drainage systems. This study compares two different types of rainfall forecasts – a radar rainfall extrapolation based nowcast model and a numerical weather prediction model. The models are applied...... as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 hours. The best...... performance of the system is found using the radar nowcast for the short leadtimes and weather model for larger lead times....

  16. Predicting Footbridge Response using Stochastic Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2013-01-01

    Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing s...... as it pinpoints which decisions to be concerned about when the goal is to predict footbridge response. The studies involve estimating footbridge responses using Monte-Carlo simulations and focus is on estimating vertical structural response to single person loading....

  17. Nonconvex Model Predictive Control for Commercial Refrigeration

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp

    2013-01-01

    is to minimize the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost...... the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...

  18. Integrated Models for Solid Waste Management in Tourism Regions: Langkawi Island, Malaysia

    Directory of Open Access Journals (Sweden)

    Elmira Shamshiry

    2011-01-01

    Full Text Available The population growth, changing consumption patterns, and rapid urbanization contribute significantly to the growing volumes of solid waste that are generated in urban settings. As the rate of urbanization increases, demand on the services of solid waste management increases. The rapid urban growth in Langkawi Island, Malaysia, combined with the increasing rates of solid waste production has provided evidence that the traditional solid waste management practices, particularly the methods of waste collection and disposal, are inefficient and quite nonsustainable. Accordingly, municipal managers and planners in Langkawi need to look for and adopt a model for solid waste management that emphasizes an efficient and sustainable management of solid wastes in Langkawi Island. This study presents the current practices of solid waste management in Langkawi Island, describes the composition of the solid waste generated in that area, and presents views of local residents and tourist on issues related to solid waste management like the aesthetic value of the island environment. The most important issue of this paper is that it is the first time that integrated solid waste management is investigated in the Langkawi Island.

  19. Integrated Models for Solid Waste Management in Tourism Regions: Langkawi Island, Malaysia

    Science.gov (United States)

    Shamshiry, Elmira; Nadi, Behzad; Bin Mokhtar, Mazlin; Komoo, Ibrahim; Saadiah Hashim, Halimaton; Yahaya, Nadzri

    2011-01-01

    The population growth, changing consumption patterns, and rapid urbanization contribute significantly to the growing volumes of solid waste that are generated in urban settings. As the rate of urbanization increases, demand on the services of solid waste management increases. The rapid urban growth in Langkawi Island, Malaysia, combined with the increasing rates of solid waste production has provided evidence that the traditional solid waste management practices, particularly the methods of waste collection and disposal, are inefficient and quite nonsustainable. Accordingly, municipal managers and planners in Langkawi need to look for and adopt a model for solid waste management that emphasizes an efficient and sustainable management of solid wastes in Langkawi Island. This study presents the current practices of solid waste management in Langkawi Island, describes the composition of the solid waste generated in that area, and presents views of local residents and tourist on issues related to solid waste management like the aesthetic value of the island environment. The most important issue of this paper is that it is the first time that integrated solid waste management is investigated in the Langkawi Island. PMID:21904559

  20. Integrated models for solid waste management in tourism regions: Langkawi Island, Malaysia.

    Science.gov (United States)

    Shamshiry, Elmira; Nadi, Behzad; Mokhtar, Mazlin Bin; Komoo, Ibrahim; Hashim, Halimaton Saadiah; Yahaya, Nadzri

    2011-01-01

    The population growth, changing consumption patterns, and rapid urbanization contribute significantly to the growing volumes of solid waste that are generated in urban settings. As the rate of urbanization increases, demand on the services of solid waste management increases. The rapid urban growth in Langkawi Island, Malaysia, combined with the increasing rates of solid waste production has provided evidence that the traditional solid waste management practices, particularly the methods of waste collection and disposal, are inefficient and quite nonsustainable. Accordingly, municipal managers and planners in Langkawi need to look for and adopt a model for solid waste management that emphasizes an efficient and sustainable management of solid wastes in Langkawi Island. This study presents the current practices of solid waste management in Langkawi Island, describes the composition of the solid waste generated in that area, and presents views of local residents and tourist on issues related to solid waste management like the aesthetic value of the island environment. The most important issue of this paper is that it is the first time that integrated solid waste management is investigated in the Langkawi Island.

  1. Predictive In Vivo Models for Oncology.

    Science.gov (United States)

    Behrens, Diana; Rolff, Jana; Hoffmann, Jens

    2016-01-01

    Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.

  2. Constructing predictive models of human running.

    Science.gov (United States)

    Maus, Horst-Moritz; Revzen, Shai; Guckenheimer, John; Ludwig, Christian; Reger, Johann; Seyfarth, Andre

    2015-02-06

    Running is an essential mode of human locomotion, during which ballistic aerial phases alternate with phases when a single foot contacts the ground. The spring-loaded inverted pendulum (SLIP) provides a starting point for modelling running, and generates ground reaction forces that resemble those of the centre of mass (CoM) of a human runner. Here, we show that while SLIP reproduces within-step kinematics of the CoM in three dimensions, it fails to reproduce stability and predict future motions. We construct SLIP control models using data-driven Floquet analysis, and show how these models may be used to obtain predictive models of human running with six additional states comprising the position and velocity of the swing-leg ankle. Our methods are general, and may be applied to any rhythmic physical system. We provide an approach for identifying an event-driven linear controller that approximates an observed stabilization strategy, and for producing a reduced-state model which closely recovers the observed dynamics. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  3. Statistical Seasonal Sea Surface based Prediction Model

    Science.gov (United States)

    Suarez, Roberto; Rodriguez-Fonseca, Belen; Diouf, Ibrahima

    2014-05-01

    The interannual variability of the sea surface temperature (SST) plays a key role in the strongly seasonal rainfall regime on the West African region. The predictability of the seasonal cycle of rainfall is a field widely discussed by the scientific community, with results that fail to be satisfactory due to the difficulty of dynamical models to reproduce the behavior of the Inter Tropical Convergence Zone (ITCZ). To tackle this problem, a statistical model based on oceanic predictors has been developed at the Universidad Complutense of Madrid (UCM) with the aim to complement and enhance the predictability of the West African Monsoon (WAM) as an alternative to the coupled models. The model, called S4CAST (SST-based Statistical Seasonal Forecast) is based on discriminant analysis techniques, specifically the Maximum Covariance Analysis (MCA) and Canonical Correlation Analysis (CCA). Beyond the application of the model to the prediciton of rainfall in West Africa, its use extends to a range of different oceanic, atmospheric and helth related parameters influenced by the temperature of the sea surface as a defining factor of variability.

  4. A multi-objective model for sustainable recycling of municipal solid waste.

    Science.gov (United States)

    Mirdar Harijani, Ali; Mansour, Saeed; Karimi, Behrooz

    2017-04-01

    The efficient management of municipal solid waste is a major problem for large and populated cities. In many countries, the majority of municipal solid waste is landfilled or dumped owing to an inefficient waste management system. Therefore, an optimal and sustainable waste management strategy is needed. This study introduces a recycling and disposal network for sustainable utilisation of municipal solid waste. In order to optimise the network, we develop a multi-objective mixed integer linear programming model in which the economic, environmental and social dimensions of sustainability are concurrently balanced. The model is able to: select the best combination of waste treatment facilities; specify the type, location and capacity of waste treatment facilities; determine the allocation of waste to facilities; consider the transportation of waste and distribution of processed products; maximise the profit of the system; minimise the environmental footprint; maximise the social impacts of the system; and eventually generate an optimal and sustainable configuration for municipal solid waste management. The proposed methodology could be applied to any region around the world. Here, the city of Tehran, Iran, is presented as a real case study to show the applicability of the methodology.

  5. A Bayesian Network Model for Assessing Estrogen Fate and Transport in a Swine Waste Lagoon

    Science.gov (United States)

    Lee, Boknam; Kullman, Seth W.; Yost, Erin; Meyer, Michael T.; Worley-Davis, Lynn; Reckhow, Kenneth H.

    2017-01-01

    Commercial swine waste lagoons are regarded as a major reservoir of natural estrogens, which have the potential to produce adverse physiological effects on exposed aquatic organisms and wildlife. However, there remains limited understanding of the complex mechanisms of physical, chemical, and biological processes that govern the fate and transport of natural estrogens within an anaerobic swine lagoon. To improve lagoon management and ultimately help control the offsite transport of these compounds from swine operations, a Bayesian network model was developed to predict estrogen fate and budget and compared against data collected from a commercial swine field site. In general, the model was able to predict the estrogen fate and budget in both the slurry and sludge stores within the swine lagoon. Sensitivity analysis within the model, demonstrated that the estrogen input loading from the associated barn facility was the most important factor in controlling estrogen concentrations within the lagoon slurry storage, while the settling rate was the most significant factor in the lagoon sludge storage. The degradation reactions were shown to be minor in both stores based on prediction of average total estrogen concentrations. Management scenario evaluations showed that the best possible management options to reduce estrogen levels in the lagoon are either to adjust the estrogen input loading from swine barn facilities or to effectively enhancing estrogen bonding with suspended solids through the use of organic polymers or inorganic coagulants. PMID:24798317

  6. Modelling biogas production of solid waste: application of the BGP model to a synthetic landfill

    Science.gov (United States)

    Rodrigo-Ilarri, Javier; Segura-Sobrino, Francisco

    2013-04-01

    Production of biogas as a result of the decomposition of organic matter included on solid waste landfills is still an issue to be understood. Reports on this matter are rarely included on the engineering construction projects of solid waste landfills despite it can be an issue of critical importance while operating the landfill and after its closure. This paper presents an application of BGP (Bio-Gas-Production) model to a synthetic landfill. The evolution in time of the concentrations of the different chemical compounds of biogas is studied. Results obtained show the impact on the air quality of different management alternatives which are usually performed in real landfills.

  7. Predictive modeling by the cerebellum improves proprioception.

    Science.gov (United States)

    Bhanpuri, Nasir H; Okamura, Allison M; Bastian, Amy J

    2013-09-04

    Because sensation is delayed, real-time movement control requires not just sensing, but also predicting limb position, a function hypothesized for the cerebellum. Such cerebellar predictions could contribute to perception of limb position (i.e., proprioception), particularly when a person actively moves the limb. Here we show that human cerebellar patients have proprioceptive deficits compared with controls during active movement, but not when the arm is moved passively. Furthermore, when healthy subjects move in a force field with unpredictable dynamics, they have active proprioceptive deficits similar to cerebellar patients. Therefore, muscle activity alone is likely insufficient to enhance proprioception and predictability (i.e., an internal model of the body and environment) is important for active movement to benefit proprioception. We conclude that cerebellar patients have an active proprioceptive deficit consistent with disrupted movement prediction rather than an inability to generally enhance peripheral proprioceptive signals during action and suggest that active proprioceptive deficits should be considered a fundamental cerebellar impairment of clinical importance.

  8. DOE model conference on waste management and environmental restoration

    Energy Technology Data Exchange (ETDEWEB)

    1990-01-01

    Reports dealing with current topics in waste management and environmental restoration were presented at this conference in six sessions. Session 1 covered the Hot Topics'' including regulations and risk assessment. Session 2 dealt with waste reduction and minimization; session 3 dealt with waste treatment and disposal. Session 4 covered site characterization and analysis. Environmental restoration and associated technologies wee discussed in session 5 and 6. Individual papers have been cataloged separately.

  9. Application of integral methods to prediction of heat transfer from a nuclear waste repository

    Energy Technology Data Exchange (ETDEWEB)

    Blesch, C J; Kulacki, F A; Christensen, R N

    1983-10-01

    Integral methods have been developed and applied to the prediction of the far field thermal impact of a nuclear waste repository. Specifically, the heat balance integral has been applied to a semi-infinite layered domain in which a limited number of sublayers form the repository overburden, and the repository is represented by an infinite plane beneath either one or two sublayers. Calculations for PWR spent fuel with an initial areal thermal loading of 60 kW/acre are carried out for various stratigraphies and overburden compositions. Results of the analyses are temperature distributions and heat fluxes to the surface as a function to time. Based on this study, the thermophysical properties of the individual layers are identified as the most important influence on temperature distributions and maximum temperature rise at any position above the repository. The thicknesses of the sublayers play a secondary role for a given rock composition. Where a comparison to exact or numerical solutions is possible, the method predicts maximum temperature increases in the overburden to within 10 percent. Heat fluxes to the surface are found to be relatively insensitive to overburden composition. For dome salt, a maximum of 1.2 percent to 2.7 percent of the initial areal thermal power of a five-term source reaches the surface. For bedded salt, a maximum of 1 percent to 1.8 percent of the initial areal thermal power reaches the surface over a wide range of sublayer compositions. Similarly, low percentages of initial areal thermal power reach the surface for the other stratigraphies considered in the calculations.

  10. Cookoff Modeling of a WIPP waste drum (68660)

    Energy Technology Data Exchange (ETDEWEB)

    Hobbs, Michael L. [Sandia National Laboratories, Albuquerque, NM (United States)

    2014-11-24

    A waste drum located 2150 feet underground may have been the root cause of a radiation leak on February 14, 2014. Information provided to the WIPP Technical Assessment Team (TAT) was used to describe the approximate content of the drum, which included an organic cat litter (Swheat Scoop®, or Swheat) composed of 100% wheat products. The drum also contained various nitrate salts, oxalic acid, and a nitric acid solution that was neutralized with triethanolamine (TEA). CTH-TIGER was used with the approximate drum contents to specify the products for an exothermic reaction for the drum. If an inorganic adsorbent such as zeolite had been used in lieu of the kitty litter, the overall reaction would have been endothermic. Dilution with a zeolite adsorbent might be a useful method to remediate drums containing organic kitty litter. SIERRA THERMAL was used to calculate the pressurization and ignition of the drum. A baseline simulation of drum 68660 was performed by assuming a background heat source of 0.5-10 W of unknown origin. The 0.5 W source could be representative of heat generated by radioactive decay. The drum ignited after about 70 days. Gas generation at ignition was predicted to be 300-500 psig with a sealed drum (no vent). At ignition, the wall temperature increases modestly by about 1°C, demonstrating that heating would not be apparent prior to ignition. The ignition location was predicted to be about 0.43 meters above the bottom center portion of the drum. At ignition only 3-5 kg (out of 71.6 kg total) has been converted into gas, indicating that most of the material remained available for post-ignition reaction.

  11. Quantifying uncertainty in LCA-modelling of waste management systems

    DEFF Research Database (Denmark)

    Clavreul, Julie; Guyonnet, D.; Christensen, Thomas Højlund

    2012-01-01

    Uncertainty analysis in LCA studies has been subject to major progress over the last years. In the context of waste management, various methods have been implemented but a systematic method for uncertainty analysis of waste-LCA studies is lacking. The objective of this paper is (1) to present...... the sources of uncertainty specifically inherent to waste-LCA studies, (2) to select and apply several methods for uncertainty analysis and (3) to develop a general framework for quantitative uncertainty assessment of LCA of waste management systems. The suggested method is a sequence of four steps combining...

  12. Application of the IPCC Waste Model to solid waste disposal sites in tropical countries: case study of Thailand.

    Science.gov (United States)

    Wangyao, Komsilp; Towprayoon, Sirintornthep; Chiemchaisri, Chart; Gheewala, Shabbir H; Nopharatana, Annop

    2010-05-01

    Measurements of landfill methane emission were performed at nine solid waste disposal sites in Thailand, including five managed sanitary landfills (four deep and one shallow landfills) and four unmanaged landfills (three deep and one shallow dumpsites). It was found that methane emissions during the rainy season were about five to six times higher than those during the winter and summer seasons in the case of managed landfills and two to five times higher in the case of unmanaged landfills. Methane emission estimate using the Intergovernmental Panel on Climate Change (IPCC) Waste Model was compared with the actual field measurement from the studied disposal sites with methane correction factors and methane oxidation factors that were obtained by error function analysis with default values of half-life parameters. The methane emissions from the first-order decay model from the IPCC Waste Model yielded fair results compared to field measurements. The best fitting values of methane correction factor were 0.65, 0.20, 0.15, and 0.1 for deep landfills, shallow landfills, deep dumpsites, and shallow dumpsites, respectively. Using these key parameters in the case of Thailand, it was estimated that 89.22 Gg of methane were released from solid waste disposal sites into the atmosphere in 2006.

  13. A prediction model for Clostridium difficile recurrence

    Directory of Open Access Journals (Sweden)

    Francis D. LaBarbera

    2015-02-01

    Full Text Available Background: Clostridium difficile infection (CDI is a growing problem in the community and hospital setting. Its incidence has been on the rise over the past two decades, and it is quickly becoming a major concern for the health care system. High rate of recurrence is one of the major hurdles in the successful treatment of C. difficile infection. There have been few studies that have looked at patterns of recurrence. The studies currently available have shown a number of risk factors associated with C. difficile recurrence (CDR; however, there is little consensus on the impact of most of the identified risk factors. Methods: Our study was a retrospective chart review of 198 patients diagnosed with CDI via Polymerase Chain Reaction (PCR from February 2009 to Jun 2013. In our study, we decided to use a machine learning algorithm called the Random Forest (RF to analyze all of the factors proposed to be associated with CDR. This model is capable of making predictions based on a large number of variables, and has outperformed numerous other models and statistical methods. Results: We came up with a model that was able to accurately predict the CDR with a sensitivity of 83.3%, specificity of 63.1%, and area under curve of 82.6%. Like other similar studies that have used the RF model, we also had very impressive results. Conclusions: We hope that in the future, machine learning algorithms, such as the RF, will see a wider application.

  14. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  15. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  16. Ground Motion Prediction Models for Caucasus Region

    Science.gov (United States)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  17. Modeling and Prediction of Krueger Device Noise

    Science.gov (United States)

    Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

    2016-01-01

    This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

  18. A generative model for predicting terrorist incidents

    Science.gov (United States)

    Verma, Dinesh C.; Verma, Archit; Felmlee, Diane; Pearson, Gavin; Whitaker, Roger

    2017-05-01

    A major concern in coalition peace-support operations is the incidence of terrorist activity. In this paper, we propose a generative model for the occurrence of the terrorist incidents, and illustrate that an increase in diversity, as measured by the number of different social groups to which that an individual belongs, is inversely correlated with the likelihood of a terrorist incident in the society. A generative model is one that can predict the likelihood of events in new contexts, as opposed to statistical models which are used to predict the future incidents based on the history of the incidents in an existing context. Generative models can be useful in planning for persistent Information Surveillance and Reconnaissance (ISR) since they allow an estimation of regions in the theater of operation where terrorist incidents may arise, and thus can be used to better allocate the assignment and deployment of ISR assets. In this paper, we present a taxonomy of terrorist incidents, identify factors related to occurrence of terrorist incidents, and provide a mathematical analysis calculating the likelihood of occurrence of terrorist incidents in three common real-life scenarios arising in peace-keeping operations

  19. Physical modeling of joule heated ceramic glass melters for high level waste immobilization

    Energy Technology Data Exchange (ETDEWEB)

    Quigley, M.S.; Kreid, D.K.

    1979-03-01

    This study developed physical modeling techniques and apparatus suitable for experimental analysis of joule heated ceramic glass melters designed for immobilizing high level waste. The physical modeling experiments can give qualitative insight into the design and operation of prototype furnaces and, if properly verified with prototype data, the physical models could be used for quantitative analysis of specific furnaces. Based on evaluation of the results of this study, it is recommended that the following actions and investigations be undertaken: It was not shown that the isothermal boundary conditions imposed by this study established prototypic heat losses through the boundaries of the model. Prototype wall temperatures and heat fluxes should be measured to provide better verification of the accuracy of the physical model. The VECTRA computer code is a two-dimensional analytical model. Physical model runs which are isothermal in the Y direction should be made to provide two-dimensional data for more direct comparison to the VECTRA predictions. The ability of the physical model to accurately predict prototype operating conditions should be proven before the model can become a reliable design tool. This will require significantly more prototype operating and glass property data than were available at the time of this study. A complete set of measurements covering power input, heat balances, wall temperatures, glass temperatures, and glass properties should be attempted for at least one prototype run. The information could be used to verify both physical and analytical models. Particle settling and/or sludge buildup should be studied directly by observing the accumulation of the appropriate size and density particles during feeding in the physical model. New designs should be formulated and modeled to minimize the potential problems with melter operation identifed by this study.

  20. Determination of the optimal area of waste incineration in a rotary kiln using a simulation model.

    Science.gov (United States)

    Bujak, J

    2015-08-01

    The article presents a mathematical model to determine the flux of incinerated waste in terms of its calorific values. The model is applicable in waste incineration systems equipped with rotary kilns. It is based on the known and proven energy flux balances and equations that describe the specific losses of energy flux while considering the specificity of waste incineration systems. The model is universal as it can be used both for the analysis and testing of systems burning different types of waste (municipal, medical, animal, etc.) and for allowing the use of any kind of additional fuel. Types of waste incinerated and additional fuel are identified by a determination of their elemental composition. The computational model has been verified in three existing industrial-scale plants. Each system incinerated a different type of waste. Each waste type was selected in terms of a different calorific value. This allowed the full verification of the model. Therefore the model can be used to optimize the operation of waste incineration system both at the design stage and during its lifetime. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Optimal feedback scheduling of model predictive controllers

    Institute of Scientific and Technical Information of China (English)

    Pingfang ZHOU; Jianying XIE; Xiaolong DENG

    2006-01-01

    Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FSCBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.

  2. Objective calibration of numerical weather prediction models

    Science.gov (United States)

    Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

    2017-07-01

    Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

  3. A particulate model of solid waste incineration in a fluidized bed combining combustion and heavy metal vaporization

    Energy Technology Data Exchange (ETDEWEB)

    Mazza, G. [Facultad de Ingenieria, Departamento de Quimica, Universidad Nacional del Comahue, UE Neuquen (CONICET - UNCo), Buenos Aires 1400, 8300 Neuquen (Argentina); Falcoz, Q.; Gauthier, D.; Flamant, G. [Laboratoire Procedes Materiaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France)

    2009-11-15

    This study aims to develop a particulate model combining solid waste particle combustion and heavy metal vaporization from burning particles during MSW incineration in a fluidized bed. The original approach for this model combines an asymptotic combustion model for the carbonaceous solid combustion and a shrinking core model to describe the heavy metal vaporization. A parametric study is presented. The global metal vaporization process is strongly influenced by temperature. Internal mass transfer controls the metal vaporization rate at low temperatures. At high temperatures, the chemical reactions associated with particle combustion control the metal vaporization rate. A comparison between the simulation results and experimental data obtained with a laboratory-scale fluid bed incinerator and Cd-spiked particles shows that the heavy metal vaporization is correctly predicted by the model. The predictions are better at higher temperatures because of the temperature gradient inside the particle. Future development of the model will take this into account. (author)

  4. Development of a multimedia radionuclide exposure model for low-level waste management

    Energy Technology Data Exchange (ETDEWEB)

    Onishi, Y.; Whelan, G.; Skaggs, R.L.

    1982-03-01

    A method is being developed for assessing exposures of the air, water, and plants to low-level waste (LLW) as a part of an overall development effort of a LLW site evaluation methodology. The assessment methodology will predict LLW exposure levels in the environment by simulating dominant mechanisms of LLW migration and fate. The methodology consists of a series of physics-based models with proven histories of success; the models interact with each other to simulate LLW transport in the ecosystem. A scaled-down version of the methodology was developed first by combining the terrestrial ecological model, BIOTRAN; the overland transport model, ARM; the instream hydrodynamic model, DKWAV; and the instream sediment-contaminant transport model, TODAM (a one-dimensional version of SERATRA). The methodology was used to simulate the migration of /sup 239/Pu from a shallow-land disposal site (known as Area C) located near the head of South Mortandad Canyon on the LANL site in New Mexico. The scenario assumed that /sup 239/Pu would be deposited on the land surface through the natural processes of plant growth, LLW uptake, dryfall, and litter decomposition. Runoff events would then transport /sup 239/Pu to and in the canyon. The model provided sets of simulated LLW levels in soil, water and terrestrial plants in the region surrounding the site under a specified land-use and a waste management option. Over a 100-yr simulation period, only an extremely small quantity (6 x 10/sup -9/ times the original concentration) of buried /sup 239/Pu was taken up by plants and deposited on the land surface. Only a small fraction (approximately 1%) of that contamination was further removed by soil erosion from the site and carried to the canyon, where it remained. Hence, the study reveals that the environment around Area C has integrity high enough to curtail LLW migration under recreational land use.

  5. Local CFD kinetic model of cadmium vaporization during fluid bed incineration of municipal solid waste

    Energy Technology Data Exchange (ETDEWEB)

    Soria, J. [Instituto Multidisciplinario de Investigación y Desarrollo de la Patagonia Norte (IDEPA, CONICET-UNCo) y Facultad de Ingeniería, Universidad Nacional del Comahue, Buenos Aires 1400, 8300 Neuquén (Argentina); Laboratoire Procédés, Matériaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France); Gauthier, D., E-mail: Daniel.Gauthier@promes.cnrs.fr [Laboratoire Procédés, Matériaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France); Falcoz, Q.; Flamant, G. [Laboratoire Procédés, Matériaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France); Mazza, G. [Instituto Multidisciplinario de Investigación y Desarrollo de la Patagonia Norte (IDEPA, CONICET-UNCo) y Facultad de Ingeniería, Universidad Nacional del Comahue, Buenos Aires 1400, 8300 Neuquén (Argentina)

    2013-03-15

    Highlights: ► A 2-D local CFD model for simulating the Cd vaporization process is presented. ► It includes a kinetic expression of Cd vaporization into the incineration process. ► Pyrolysis, volatiles’ combustion and residual carbon combustion are also taken into account. ► It fits very well the experimental results obtained on a lab-scale fluidized bed reported in literature. ► It also compares favorably with a model developed previously by the group. -- Abstract: The emissions of heavy metals during incineration of Municipal Solid Waste (MSW) are a major issue to health and the environment. It is then necessary to well quantify these emissions in order to accomplish an adequate control and prevent the heavy metals from leaving the stacks. In this study the kinetic behavior of Cadmium during Fluidized Bed Incineration (FBI) of artificial MSW pellets, for bed temperatures ranging from 923 to 1073 K, was modeled. FLUENT 12.1.4 was used as the modeling framework for the simulations and implemented together with a complete set of user-defined functions (UDFs). The CFD model combines the combustion of a single solid waste particle with heavy metal (HM) vaporization from the burning particle, and it takes also into account both pyrolysis and volatiles’ combustion. A kinetic rate law for the Cd release, derived from the CFD thermal analysis of the combusting particle, is proposed. The simulation results are compared with experimental data obtained in a lab-scale fluidized bed incinerator reported in literature, and with the predicted values from a particulate non-isothermal model, formerly developed by the authors. The comparison shows that the proposed CFD model represents very well the evolution of the HM release for the considered range of bed temperature.

  6. Prediction models from CAD models of 3D objects

    Science.gov (United States)

    Camps, Octavia I.

    1992-11-01

    In this paper we present a probabilistic prediction based approach for CAD-based object recognition. Given a CAD model of an object, the PREMIO system combines techniques of analytic graphics and physical models of lights and sensors to predict how features of the object will appear in images. In nearly 4,000 experiments on analytically-generated and real images, we show that in a semi-controlled environment, predicting the detectability of features of the image can successfully guide a search procedure to make informed choices of model and image features in its search for correspondences that can be used to hypothesize the pose of the object. Furthermore, we provide a rigorous experimental protocol that can be used to determine the optimal number of correspondences to seek so that the probability of failing to find a pose and of finding an inaccurate pose are minimized.

  7. Model predictive control of MSMPR crystallizers

    Science.gov (United States)

    Moldoványi, Nóra; Lakatos, Béla G.; Szeifert, Ferenc

    2005-02-01

    A multi-input-multi-output (MIMO) control problem of isothermal continuous crystallizers is addressed in order to create an adequate model-based control system. The moment equation model of mixed suspension, mixed product removal (MSMPR) crystallizers that forms a dynamical system is used, the state of which is represented by the vector of six variables: the first four leading moments of the crystal size, solute concentration and solvent concentration. Hence, the time evolution of the system occurs in a bounded region of the six-dimensional phase space. The controlled variables are the mean size of the grain; the crystal size-distribution and the manipulated variables are the input concentration of the solute and the flow rate. The controllability and observability as well as the coupling between the inputs and the outputs was analyzed by simulation using the linearized model. It is shown that the crystallizer is a nonlinear MIMO system with strong coupling between the state variables. Considering the possibilities of the model reduction, a third-order model was found quite adequate for the model estimation in model predictive control (MPC). The mean crystal size and the variance of the size distribution can be nearly separately controlled by the residence time and the inlet solute concentration, respectively. By seeding, the controllability of the crystallizer increases significantly, and the overshoots and the oscillations become smaller. The results of the controlling study have shown that the linear MPC is an adaptable and feasible controller of continuous crystallizers.

  8. An Anisotropic Hardening Model for Springback Prediction

    Science.gov (United States)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  9. Modelling the potential radiological consequences of radioactive waste dumping in the Kara Sea

    Energy Technology Data Exchange (ETDEWEB)

    Scott, E.M.; Povinec, P.P.; Osvath, I.; Harms, I.; Baxter, M.S. [International Atomic Energy Agency, Marine Environment Laboratory, MC-98012 (Monaco)

    1998-02-01

    There has recently been growing concern over the dumping of high- and medium-level solid radioactive wastes in the Kara Sea by the former Soviet Union. The largest amounts of radioactive wastes were dumped primarily as nuclear reactors containing spent nuclear fuel. The present radionuclide inventory in dumped nuclear reactors is estimated at 4{center_dot}7 PBq. Compartmental and hydrodynamic models have been developed and applied to describe the possible dispersal of radioactive contaminants and to predict the long-term radiological impact on global, regional and local scales. The collective committed effective dose to the world population based on the marine food ingestion pathway has been calculated as 2{center_dot}2 man Sv. Modelling results suggest that only radiological effects on a local scale may be of importance. The global radiological impact of the disposals in the Kara Sea will be smaller than from other anthropogenic sources of radioactivity. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)

  10. A steady state model of agricultural waste pyrolysis: A mini review.

    Science.gov (United States)

    Trninić, M; Jovović, A; Stojiljković, D

    2016-09-01

    Agricultural waste is one of the main renewable energy resources available, especially in an agricultural country such as Serbia. Pyrolysis has already been considered as an attractive alternative for disposal of agricultural waste, since the technique can convert this special biomass resource into granular charcoal, non-condensable gases and pyrolysis oils, which could furnish profitable energy and chemical products owing to their high calorific value. In this regard, the development of thermochemical processes requires a good understanding of pyrolysis mechanisms. Experimental and some literature data on the pyrolysis characteristics of corn cob and several other agricultural residues under inert atmosphere were structured and analysed in order to obtain conversion behaviour patterns of agricultural residues during pyrolysis within the temperature range from 300 °C to 1000 °C. Based on experimental and literature data analysis, empirical relationships were derived, including relations between the temperature of the process and yields of charcoal, tar and gas (CO2, CO, H2 and CH4). An analytical semi-empirical model was then used as a tool to analyse the general trends of biomass pyrolysis. Although this semi-empirical model needs further refinement before application to all types of biomass, its prediction capability was in good agreement with results obtained by the literature review. The compact representation could be used in other applications, to conveniently extrapolate and interpolate these results to other temperatures and biomass types.

  11. Prediction total specific pore volume of geopolymers produced from waste ashes by fuzzy logic

    Directory of Open Access Journals (Sweden)

    Ali Nazari

    2012-04-01

    Full Text Available In the present work, total specific pore volume of inorganic polymers (geopolymers made from seeded fly ash and rice husk bark ash has been predicted by fuzzy logic. Different specimens, made from a mixture of fly ash and rice husk bark ash in fine and coarse form together with alkali activator made of water glass and NaOH solution, were subjected to porosimetry tests at 7 and 28 days of curing. The curing regime was different: one set of the specimens were cured at room temperature until reaching to 7 and 28 days and the other sets were oven cured for 36 hours at the range of 40-90 °C and then cured at room temperature until 7 and 28 days. A model based on fuzzy logic for predicting the total specific pore volume of the specimens has been presented. To build the model, training and testing using experimental results from 120 specimens were conducted. The used data as the inputs of fuzzy logic models are arranged in a format of six parameters that cover the percentage of fine fly ash in the ashes mixture, the percentage of coarse fly ash in the ashes mixture, the percentage of fine rice husk bark ash in the ashes mixture, the percentage of coarse rice husk bark ash in the ashes mixture, the temperature of curing and the time of water curing. According to the input parameters, in the fuzzy logic model, the pore volume of each specimen was predicted. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the total specific pore volume of the geopolymer specimens in the considered range.

  12. Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor.

    Science.gov (United States)

    Pandey, Daya Shankar; Das, Saptarshi; Pan, Indranil; Leahy, James J; Kwapinski, Witold

    2016-12-01

    In this paper, multi-layer feed forward neural networks are used to predict the lower heating value of gas (LHV), lower heating value of gasification products including tars and entrained char (LHVp) and syngas yield during gasification of municipal solid waste (MSW) during gasification in a fluidized bed reactor. These artificial neural networks (ANNs) with different architectures are trained using the Levenberg-Marquardt (LM) back-propagation algorithm and a cross validation is also performed to ensure that the results generalise to other unseen datasets. A rigorous study is carried out on optimally choosing the number of hidden layers, number of neurons in the hidden layer and activation function in a network using multiple Monte Carlo runs. Nine input and three output parameters are used to train and test various neural network architectures in both multiple output and single output prediction paradigms using the available experimental datasets. The model selection procedure is carried out to ascertain the best network architecture in terms of predictive accuracy. The simulation results show that the ANN based methodology is a viable alternative which can be used to predict the performance of a fluidized bed gasifier. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Predictive modelling of ferroelectric tunnel junctions

    Science.gov (United States)

    Velev, Julian P.; Burton, John D.; Zhuravlev, Mikhail Ye; Tsymbal, Evgeny Y.

    2016-05-01

    Ferroelectric tunnel junctions combine the phenomena of quantum-mechanical tunnelling and switchable spontaneous polarisation of a nanometre-thick ferroelectric film into novel device functionality. Switching the ferroelectric barrier polarisation direction produces a sizable change in resistance of the junction—a phenomenon known as the tunnelling electroresistance effect. From a fundamental perspective, ferroelectric tunnel junctions and their version with ferromagnetic electrodes, i.e., multiferroic tunnel junctions, are testbeds for studying the underlying mechanisms of tunnelling electroresistance as well as the interplay between electric and magnetic degrees of freedom and their effect on transport. From a practical perspective, ferroelectric tunnel junctions hold promise for disruptive device applications. In a very short time, they have traversed the path from basic model predictions to prototypes for novel non-volatile ferroelectric random access memories with non-destructive readout. This remarkable progress is to a large extent driven by a productive cycle of predictive modelling and innovative experimental effort. In this review article, we outline the development of the ferroelectric tunnel junction concept and the role of theoretical modelling in guiding experimental work. We discuss a wide range of physical phenomena that control the functional properties of ferroelectric tunnel junctions and summarise the state-of-the-art achievements in the field.

  14. Simple predictions from multifield inflationary models.

    Science.gov (United States)

    Easther, Richard; Frazer, Jonathan; Peiris, Hiranya V; Price, Layne C

    2014-04-25

    We explore whether multifield inflationary models make unambiguous predictions for fundamental cosmological observables. Focusing on N-quadratic inflation, we numerically evaluate the full perturbation equations for models with 2, 3, and O(100) fields, using several distinct methods for specifying the initial values of the background fields. All scenarios are highly predictive, with the probability distribution functions of the cosmological observables becoming more sharply peaked as N increases. For N=100 fields, 95% of our Monte Carlo samples fall in the ranges ns∈(0.9455,0.9534), α∈(-9.741,-7.047)×10-4, r∈(0.1445,0.1449), and riso∈(0.02137,3.510)×10-3 for the spectral index, running, tensor-to-scalar ratio, and isocurvature-to-adiabatic ratio, respectively. The expected amplitude of isocurvature perturbations grows with N, raising the possibility that many-field models may be sensitive to postinflationary physics and suggesting new avenues for testing these scenarios.

  15. Fungal protein from corn waste effluents : a model study

    NARCIS (Netherlands)

    Schellart, J.A.

    1975-01-01

    The purpose of this investigation was to study the microbiological aspects of the production of microbial protein ('single cell protein'; SCP) from corn waste effluents with simultaneous reduction of the COD of these effluents.For practical reasons the corn waste water itself was not used in the exp

  16. Modelling the effects of waste components on cement hydration

    NARCIS (Netherlands)

    Eijk, van R.J.; Brouwers, H.J.H.

    2001-01-01

    Ordinary Portland Cement (OPC) is often used for the solidification/stabilization (S/S) of waste containing heavy metals and salts. These waste components will precipitate in the form of insoluble compounds on to unreacted cement clinker grains preventing further hydration. In this study the long te

  17. Modelling the effects of waste components on cement hydration

    NARCIS (Netherlands)

    Eijk, van R.J.; Brouwers, H.J.H.

    2000-01-01

    Ordinary Portland Cement (OPC) is often used for the Solidification/Stabilization (S/S) of waste containing heavy metals and salts. These waste componenents will precipitate in the form of insoluble compounds onto unreacted cement clinker grains preventing further hydration. In this study the long t

  18. Fungal protein from corn waste effluents : a model study

    NARCIS (Netherlands)

    Schellart, J.A.

    1975-01-01

    The purpose of this investigation was to study the microbiological aspects of the production of microbial protein ('single cell protein'; SCP) from corn waste effluents with simultaneous reduction of the COD of these effluents.

    For practical reasons the corn waste water itself was

  19. Predictions of models for environmental radiological assessment

    Energy Technology Data Exchange (ETDEWEB)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa, E-mail: suelip@ird.gov.br, E-mail: dejanira@irg.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Servico de Avaliacao de Impacto Ambiental, Rio de Janeiro, RJ (Brazil); Mahler, Claudio Fernando [Coppe. Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia, Universidade Federal do Rio de Janeiro (UFRJ) - Programa de Engenharia Civil, RJ (Brazil)

    2011-07-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for {sup 137}Cs and {sup 60}Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  20. Application of macro material flow modeling to the decision making process for integrated waste management systems

    Energy Technology Data Exchange (ETDEWEB)

    Vigil, S.A. [California Polytechnic State Univ., San Luis Obispo, CA (United States); Holter, G.M. [Battelle Pacific Northwest Laboratory, Richland, WA (United States)

    1995-04-01

    Computer models have been used for almost a decade to model and analyze various aspects of solid waste management Commercially available models exist for estimating the capital and operating costs of landfills, waste-to-energy facilities and compost systems and for optimizing system performance along a single dimension (e.g. cost or transportation distance). An alternative to the use of currently available models is the more flexible macro material flow modeling approach in which a macro scale or regional level approach is taken. Waste materials are tracked through the complete integrated waste management cycle from generation through recycling and reuse, and finally to ultimate disposal. Such an approach has been applied by the authors to two different applications. The STELLA simulation language (for Macintosh computers) was used to model the solid waste management system of Puerto Rico. The model incorporated population projections for all 78 municipalities in Puerto Rico from 1990 to 2010, solid waste generation factors, remaining life for the existing landfills, and projected startup time for new facilities. The Pacific Northwest Laboratory has used the SimScript simulation language (for Windows computers) to model the management of solid and hazardous wastes produced during cleanup and remediation activities at the Hanford Nuclear Site.

  1. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...

  2. A Modified Model Predictive Control Scheme

    Institute of Scientific and Technical Information of China (English)

    Xiao-Bing Hu; Wen-Hua Chen

    2005-01-01

    In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.

  3. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... facilitates plug-and-play addition of subsystems without redesign of any controllers. The method is supported by a number of simulations featuring a three-level smart-grid power control system for a small isolated power grid....

  4. Explicit model predictive control accuracy analysis

    OpenAIRE

    Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano

    2015-01-01

    Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...

  5. Critical conceptualism in environmental modeling and prediction.

    Science.gov (United States)

    Christakos, G

    2003-10-15

    Many important problems in environmental science and engineering are of a conceptual nature. Research and development, however, often becomes so preoccupied with technical issues, which are themselves fascinating, that it neglects essential methodological elements of conceptual reasoning and theoretical inquiry. This work suggests that valuable insight into environmental modeling can be gained by means of critical conceptualism which focuses on the software of human reason and, in practical terms, leads to a powerful methodological framework of space-time modeling and prediction. A knowledge synthesis system develops the rational means for the epistemic integration of various physical knowledge bases relevant to the natural system of interest in order to obtain a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, generate meaningful predictions of environmental processes in space-time, and produce science-based decisions. No restriction is imposed on the shape of the distribution model or the form of the predictor (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated). The scientific reasoning structure underlying knowledge synthesis involves teleologic criteria and stochastic logic principles which have important advantages over the reasoning method of conventional space-time techniques. Insight is gained in terms of real world applications, including the following: the study of global ozone patterns in the atmosphere using data sets generated by instruments on board the Nimbus 7 satellite and secondary information in terms of total ozone-tropopause pressure models; the mapping of arsenic concentrations in the Bangladesh drinking water by assimilating hard and soft data from an extensive network of monitoring wells; and the dynamic imaging of probability distributions of pollutants across the Kalamazoo river.

  6. A mathematical model for the municipal solid waste location-routing problem with intermediate transfer stations

    Directory of Open Access Journals (Sweden)

    Hossein Asefi

    2015-09-01

    Full Text Available Municipal solid waste management is one of the challenging issues in mega cities due to various interrelated factors such as operational costs and environmental concerns. Cost as one of the most significant constraints of municipal solid waste management can be effectively economized by efficient planning approaches. Considering diverse waste types in an integrated municipal solid waste system, a mathematical model of the location-routing problem is formulated and solved in this study in order to minimize the total cost of transportation and facility establishment.

  7. Analysis of Ecodesign Implementation and Solutions for Packaging Waste System by Using System Dynamics Modeling

    Science.gov (United States)

    Berzina, Alise; Dace, Elina; Bazbauers, Gatis

    2010-01-01

    This paper discusses the findings of a research project which explored the packaging waste management system in Latvia. The paper focuses on identifying how the policy mechanisms can promote ecodesign implementation and material efficiency improvement and therefore reduce the rate of packaging waste accumulation in landfill. The method used for analyzing the packaging waste management policies is system dynamics modeling. The main conclusion is that the existing legislative instruments can be used to create an effective policy for ecodesign implementation but substantially higher tax rates on packaging materials and waste disposal than the existing have to be applied.

  8. Hanford Site Tank 241-C-108 Residual Waste Contaminant Release Models and Supporting Data

    Energy Technology Data Exchange (ETDEWEB)

    Cantrell, Kirk J.; Krupka, Kenneth M.; Geiszler, Keith N.; Arey, Bruce W.; Schaef, Herbert T.

    2010-06-18

    This report presents the results of laboratory characterization, testing, and analysis for a composite sample (designated 20578) of residual waste collected from single-shell tank C-108 during the waste retrieval process after modified sluicing. These studies were completed to characterize concentration and form of contaminant of interest in the residual waste; assess the leachability of contaminants from the solids; and develop release models for contaminants of interest. Because modified sluicing did not achieve 99% removal of the waste, it is expected that additional retrieval processing will take place. As a result, the sample analyzed here is not expected to represent final retrieval sample.

  9. Atmospheric Dispersion Modeling of the February 2014 Waste Isolation Pilot Plant Release

    Energy Technology Data Exchange (ETDEWEB)

    Nasstrom, John [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Piggott, Tom [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Simpson, Matthew [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lobaugh, Megan [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Tai, Lydia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pobanz, Brenda [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Yu, Kristen [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-07-22

    This report presents the results of a simulation of the atmospheric dispersion and deposition of radioactivity released from the Waste Isolation Pilot Plant (WIPP) site in New Mexico in February 2014. These simulations were made by the National Atmospheric Release Advisory Center (NARAC) at Lawrence Livermore National Laboratory (LLNL), and supersede NARAC simulation results published in a previous WIPP report (WIPP, 2014). The results presented in this report use additional, more detailed data from WIPP on the specific radionuclides released, radioactivity release amounts and release times. Compared to the previous NARAC simulations, the new simulation results in this report are based on more detailed modeling of the winds, turbulence, and particle dry deposition. In addition, the initial plume rise from the exhaust vent was considered in the new simulations, but not in the previous NARAC simulations. The new model results show some small differences compared to previous results, but do not change the conclusions in the WIPP (2014) report. Presented are the data and assumptions used in these model simulations, as well as the model-predicted dose and deposition on and near the WIPP site. A comparison of predicted and measured radionuclide-specific air concentrations is also presented.

  10. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  11. Artificial neural networks for prediction of percentage of water absorption of geopolymers produced by waste ashes

    Indian Academy of Sciences (India)

    Ali Nazari

    2012-11-01

    In the present work, percentage of water absorption of geopolymers made from seeded fly ash and rice husk bark ash has been predicted by artificial neural networks. Different specimens, made from a mixture of fly ash and rice husk bark ash in fine and coarse form together with alkali activatormade of water glass and NaOH solution, were subjected to permeability tests at 7 and 28 days of curing. The curing regime was different: one set cured at room temperature until reaching to 7 and 28 days and the other sets were oven cured for 36 h at a range of 40–90 °C and then cured at room temperature for 7 and 28 days. To build the model, training and testing using experimental results from 120 specimens were conducted. According to these input parameters, in the neural networks model, the percentage of water absorption of each specimen was predicted. The training and testing results in the neural networks model have shown a strong potential for predicting the percentage of water absorption of the geopolymer specimens.

  12. Modeling Pumped Thermal Energy Storage with Waste Heat Harvesting

    Science.gov (United States)

    Abarr, Miles L. Lindsey

    This work introduces a new concept for a utility scale combined energy storage and generation system. The proposed design utilizes a pumped thermal energy storage (PTES) system, which also utilizes waste heat leaving a natural gas peaker plant. This system creates a low cost utility-scale energy storage system by leveraging this dual-functionality. This dissertation first presents a review of previous work in PTES as well as the details of the proposed integrated bottoming and energy storage system. A time-domain system model was developed in Mathworks R2016a Simscape and Simulink software to analyze this system. Validation of both the fluid state model and the thermal energy storage model are provided. The experimental results showed the average error in cumulative fluid energy between simulation and measurement was +/- 0.3% per hour. Comparison to a Finite Element Analysis (FEA) model showed energy of a recently proposed Pumped Thermal Energy Storage and Bottoming System (Bot-PTES) that uses ammonia as the working fluid. This analysis focused on the effects of hot thermal storage utilization, system pressure, and evaporator/condenser size on the system performance. This work presents the estimated performance for a proposed baseline Bot-PTES. Results of this analysis showed that all selected parameters had significant effects on efficiency, with the evaporator/condenser size having the largest effect over the selected ranges. Results for the baseline case showed stand-alone energy storage efficiencies between 51 and 66% for varying power levels and charge states, and a stand-alone bottoming efficiency of 24%. The resulting efficiencies for this case were low compared to competing technologies; however, the dual-functionality of the Bot-PTES enables it to have higher capacity factor, leading to 91-197/MWh levelized cost of energy compared to 262-284/MWh for batteries and $172-254/MWh for Compressed Air Energy Storage.

  13. MATHEMATICAL MODELLING FOR THE CONVERSION OF ANIMAL WASTE TO METHANE IN BATCH BIOREACTOR

    Directory of Open Access Journals (Sweden)

    O.A. Aworanti

    2011-01-01

    Full Text Available An investigation was conducted to predict the behaviour of microbial processes leading to the production of biogas from animal waste. Mathematical model were developed for the prediction of the behaviour of microbial processes. The development of the models was based upon a material balance analysis of the digester operation, substrate utilization, cell growth and product formation. The model was solved using Runge kutta numerical technique embedded in polymath software. The digesters’ operations simulated with a starting valve of 300g/dm3 as the concentration of the substrate and 1.5g/dm3 as the concentration of the cell, within a period of 13days. The results of the simulation show that the substrate concentration shows exponential decline from (300g/dm3 to 6.88g/dm3, the cells growth shows exponential trend from (1.5g/dm3to 39g/dm3 The rate of growth of cell was increased from (0.5g/dm3-2.53g/dm3, death increased from (0.015g/dm3 to 0.161g/dm3 over the 13days and the biogas production which is the product also follow the exponential trend from (zeroconcentration to 219g/dm3. In all the model does the prediction well on all the parameters simulated, so it was can be used to predict the product formation rate as well as the design of reactor or digester.

  14. Evaluation and prediction of emissions from a road built with bottom ash from municipal solid waste incineration (MSWI).

    Science.gov (United States)

    Aberg, Annika; Kumpiene, Jurate; Ecke, Holger

    2006-02-15

    In autumn 2001, a full-scale test road was built with municipal solid waste incineration (MSWI) bottom ash at the Dåvamyran landfill, Umeå, Northern Sweden. Leachates were collected from asphalted sections with either bottom ash or gravel as filling material. In this research, 12 months of ash leachate sampling were evaluated with respect to emissions of contaminants such as trace metals and chlorides (Cl). The usefulness of regression models describing trace metal mobility from bottom ash was also tested as predictive tools for reusability applications of MSWI bottom ash. Cl, Cu, and Cr had the highest mobility (considering leachate concentrations) in the ash leachate, though concentrations of Cl and Cu decreased during the sampling period (Cl from 10,000 to 600 mg l(-1); Cu from 1600 to 500 microg l(-1)). An increased mobility of Cr during the autumns (about 3-4 times higher compared to the summer) was noted with a maximum value of nearly 70 microg l(-1) during autumn 2001. Pb showed a very low mobility over the entire year with leachate concentrations of around 3-4 microg l(-1). Chemical equilibrium calculations using Minteq indicated that several Cu minerals were oversaturated in the leachate, thus mineral precipitation could be responsible for declining amounts of Cu in the leachate. Adsorption to iron oxides was found to be a probable explanation for the low mobility of Pb. A reasonably good agreement between regression models and field values were achieved for Ni, Pb, Zn, and Cu, while the models for Cd and Cr were less promising. Even though a large part of the variation (R2=61-97%) in the leaching experiment could be explained by only pH and L/S, field data were much more scattered than expected from field pH.

  15. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euro per km per year [1]. Aiming to reduce such maintenance expenditure, this paper...... presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time...... recovery on the track quality after tamping operation and (5) Tamping machine operation factors. A Danish railway track between Odense and Fredericia with 57.2 km of length is applied for a time period of two to four years in the proposed maintenance model. The total cost can be reduced with up to 50...

  16. Overview of chemical modeling of nuclear waste glass dissolution

    Energy Technology Data Exchange (ETDEWEB)

    Bourcier, W.L.

    1991-02-01

    Glass dissolution takes place through metal leaching and hydration of the glass surface accompanied by development of alternation layers of varying crystallinity. The reaction which controls the long-term glass dissolution rate appears to be surface layer dissolution. This reaction is reversible because the buildup of dissolved species in solution slows the dissolution rate due to a decreased dissolution affinity. Glass dissolution rates are therefore highly dependent on silica concentrations in solution because silica is the major component of the alteration layer. Chemical modeling of glass dissolution using reaction path computer codes has successfully been applied to short term experimental tests and used to predict long-term repository performance. Current problems and limitations of the models include a poorly defined long-term glass dissolution mechanism, the use of model parameters determined from the same experiments that the model is used to predict, and the lack of sufficient validation of key assumptions in the modeling approach. Work is in progress that addresses these issues. 41 refs., 7 figs., 2 tabs.

  17. Model for the conversion of nuclear waste melter feed to glass

    Science.gov (United States)

    Pokorny, Richard; Hrma, Pavel

    2014-02-01

    The rate of batch-to-glass conversion is a primary concern for the vitrification of nuclear waste, as it directly influences the life cycle of the cleanup process. This study describes the development of an advanced model of the cold cap, which augments the previous model by further developments on the structure and the dynamics of the foam layer. The foam layer on the bottom of the cold cap consists of the primary foam, cavities, and the secondary foam, and forms an interface through which the heat is transferred to the cold cap. Other model enhancements include the behavior of intermediate crystalline phases and the dissolution of quartz particles. The model relates the melting rate to feed properties and melter conditions, such as the molten glass temperature, foaminess of the melt, or the heat fraction supplied to the cold cap from the plenum space. The model correctly predicts a 25% increase in melting rate when changing the alumina source in the melter feed from Al(OH)3 to AlO(OH). It is expected that this model will be incorporated in the full glass melter model as its integral component.

  18. Model for the conversion of nuclear waste melter feed to glass

    Energy Technology Data Exchange (ETDEWEB)

    Pokorny, Richard [Inst. of Chemical Technology Prague (Czech Republic). Dept. of Chemical Engineering; Hrma, Pavel R. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Pohang Univ. of Science and Technology, Pohang (Korea, Republic of). Division of Advanced Nuclear Engineering

    2014-02-01

    The rate of batch-to-glass conversion is a primary concern for the vitrification of nuclear waste, as it directly influences the life cycle of the cleanup process. This study describes the development of an advanced model of the cold cap, which augments the previous model by further developments on the structure and the dynamics of the foam layer. The foam layer on the bottom of the cold cap consists of the primary foam, cavities, and the secondary foam, and forms an interface through which the heat is transferred to the cold cap. Other model enhancements include the behavior of intermediate crystalline phases and the dissolution of quartz particles. The model relates the melting rate to feed properties and melter conditions, such as the molten glass temperature, foaminess of the feed, or the heat fraction supplied to the cold cap from the plenum space. The model correctly predicts a 25% increase in melting rate when changing the alumina source in the melter feed from Al(OH)3 to AlO(OH). It is expected that this model will be incorporated in the full glass melter model as its integral component.

  19. A predictive fitness model for influenza

    Science.gov (United States)

    Łuksza, Marta; Lässig, Michael

    2014-03-01

    The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.

  20. Predictive Model of Radiative Neutrino Masses

    CERN Document Server

    Babu, K S

    2013-01-01

    We present a simple and predictive model of radiative neutrino masses. It is a special case of the Zee model which introduces two Higgs doublets and a charged singlet. We impose a family-dependent Z_4 symmetry acting on the leptons, which reduces the number of parameters describing neutrino oscillations to four. A variety of predictions follow: The hierarchy of neutrino masses must be inverted; the lightest neutrino mass is extremely small and calculable; one of the neutrino mixing angles is determined in terms of the other two; the phase parameters take CP-conserving values with \\delta_{CP} = \\pi; and the effective mass in neutrinoless double beta decay lies in a narrow range, m_{\\beta \\beta} = (17.6 - 18.5) meV. The ratio of vacuum expectation values of the two Higgs doublets, tan\\beta, is determined to be either 1.9 or 0.19 from neutrino oscillation data. Flavor-conserving and flavor-changing couplings of the Higgs doublets are also determined from neutrino data. The non-standard neutral Higgs bosons, if t...

  1. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...

  2. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  3. Calculational technique to predict combustible gas generation in sealed radioactive waste containers

    Energy Technology Data Exchange (ETDEWEB)

    Flaherty, J.E.; Fujita, A.; Deltete, C.P.; Quinn, G.J.

    1986-05-01

    Certain forms of nuclear waste, when subjected to ionizing radiation, produce combustible mixtures of gases. The production of these gases in sealed radioactive waste containers represents a significant safety concern for the handling, shipment and storage of waste. The US Nuclear Regulatory Commission (NRC) acted on this safety concern in September 1984 by publishing an information notice requiring waste generators to demonstrate, by tests or measurements, that combustible mixtures of gases are not present in radioactive waste shipments; otherwise the waste must be vented within 10 days of shipping. A task force, formed by the Edison Electric Institute to evaluate these NRC requirements, developed a calculational method to quantify hydrogen gas generation in sealed containers. This report presents the calculational method along with comparisons to actual measured hydrogen concentrations from EPICOR II liners, vented during their preparation for shipment. As a result of this, the NRC recently altered certain waste shipment Certificates-Of-Compliance to allow calculations, as well as tests and measurements, as acceptable means of determining combustible gas concentration. This modification was due in part to work described herein.

  4. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...

  5. Modelling of environmental impacts from biological treatment of organic municipal waste in EASEWASTE

    DEFF Research Database (Denmark)

    Boldrin, Alessio; Neidel, Trine Lund; Damgaard, Anders

    2011-01-01

    The waste-LCA model EASEWASTE quantifies potential environmental effects from biological treatment of organic waste, based on mass and energy flows, emissions to air, water, soil and groundwater as well as effects from upstream and downstream processes. Default technologies for composting......, anaerobic digestion and combinations hereof are available in the model, but the user can change all key parameters in the biological treatment module so that specific local plants and processes can be modelled. EASEWASTE is one of the newest waste LCA models and the biological treatment module was built...... partly on features of earlier waste-LCA models, but offers additional facilities, more flexibility, transparency and user-friendliness. The paper presents the main features of the module and provides some examples illustrating the capability of the model in environmentally assessing and discriminating...

  6. Modelling of environmental impacts from biological treatment of organic municipal waste in EASEWASTE.

    Science.gov (United States)

    Boldrin, Alessio; Neidel, Trine Lund; Damgaard, Anders; Bhander, Gurbakhash S; Møller, Jacob; Christensen, Thomas H

    2011-04-01

    The waste-LCA model EASEWASTE quantifies potential environmental effects from biological treatment of organic waste, based on mass and energy flows, emissions to air, water, soil and groundwater as well as effects from upstream and downstream processes. Default technologies for composting, anaerobic digestion and combinations hereof are available in the model, but the user can change all key parameters in the biological treatment module so that specific local plants and processes can be modelled. EASEWASTE is one of the newest waste LCA models and the biological treatment module was built partly on features of earlier waste-LCA models, but offers additional facilities, more flexibility, transparency and user-friendliness. The paper presents the main features of the module and provides some examples illustrating the capability of the model in environmentally assessing and discriminating the environmental performance of alternative biological treatment technologies in relation to their mass flows, energy consumption, gaseous emissions, biogas recovery and compost/digestate utilization.

  7. Biogas production from Pongamia biomass wastes and a model to estimate biodegradability from their composition.

    Science.gov (United States)

    Gunaseelan, Victor Nallathambi

    2014-02-01

    In this study, I investigated the chemical characteristics, biochemical methane potential, conversion kinetics and biodegradability of untreated and NaOH-treated Pongamia plant parts, and pod husk and press cake from the biodiesel industry to evaluate their suitability as an alternative feedstock for biogas production. The untreated Pongamia seeds exhibited the maximum CH4 yield of 473 ml g (-1) volatile solid (VS) added. Yellow, withered leaves gave a yield as low as 122 ml CH4 g (-1) VS added. There were significant variations in the CH4 production rate constants, which ranged from 0.02 to 0.15 d (-1), and biodegradability, which ranged from 0.25 to 0.98. NaOH treatment of leaf and pod husk, which were highly rich in fibers, increased the yields by 15-22% and CH4 production rate constants by 20-75%. Utilization of Pongamia wastes in biogas digesters not only influences the economics of biodiesel production but also yields CH4 fuel and protects the environment. The experimental data from this study were used to develop a multiple regression model, which could estimate biodegradability based on biochemical characteristics. The model predicted the biodegradability of previously published biomass wastes (r(2) = 0.88) from their biochemical composition. The theoretical CH4 yields estimated as 350 ml g(-1) chemical oxygen demand destroyed are much higher than the experimental yields as 100% biodegradability is assumed for each substrate. Upon correcting the theoretical CH4 yields with biodegradability data obtained from chemical analyses of substrates, their ultimate CH4 yields could be predicted rapidly.

  8. Two criteria for evaluating risk prediction models.

    Science.gov (United States)

    Pfeiffer, R M; Gail, M H

    2011-09-01

    We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.

  9. Methods for Handling Missing Variables in Risk Prediction Models

    NARCIS (Netherlands)

    Held, Ulrike; Kessels, Alfons; Aymerich, Judith Garcia; Basagana, Xavier; ter Riet, Gerben; Moons, Karel G. M.; Puhan, Milo A.

    2016-01-01

    Prediction models should be externally validated before being used in clinical practice. Many published prediction models have never been validated. Uncollected predictor variables in otherwise suitable validation cohorts are the main factor precluding external validation.We used individual patient

  10. Coupling scales for modelling heavy metal vaporization from municipal solid waste incineration in a fluid bed by CFD

    Energy Technology Data Exchange (ETDEWEB)

    Soria, José, E-mail: jose.soria@probien.gob.ar [Institute for Research and Development in Process Engineering, Biotechnology and Alternative Energies (PROBIEN, CONICET – UNCo), 1400 Buenos Aires St., 8300 Neuquén (Argentina); Gauthier, Daniel; Flamant, Gilles [Processes, Materials and Solar Energy Laboratory (PROMES-CNRS, UPR 8521), 7 Four Solaire Street, Odeillo, 66120 Font-Romeu (France); Rodriguez, Rosa [Chemical Engineering Institute, National University of San Juan, 1109 Libertador (O) Avenue, 5400 San Juan (Argentina); Mazza, Germán [Institute for Research and Development in Process Engineering, Biotechnology and Alternative Energies (PROBIEN, CONICET – UNCo), 1400 Buenos Aires St., 8300 Neuquén (Argentina)

    2015-09-15

    Highlights: • A CFD two-scale model is formulated to simulate heavy metal vaporization from waste incineration in fluidized beds. • MSW particle is modelled with the macroscopic particle model. • Influence of bed dynamics on HM vaporization is included. • CFD predicted results agree well with experimental data reported in literature. • This approach may be helpful for fluidized bed reactor modelling purposes. - Abstract: Municipal Solid Waste Incineration (MSWI) in fluidized bed is a very interesting technology mainly due to high combustion efficiency, great flexibility for treating several types of waste fuels and reduction in pollutants emitted with the flue gas. However, there is a great concern with respect to the fate of heavy metals (HM) contained in MSW and their environmental impact. In this study, a coupled two-scale CFD model was developed for MSWI in a bubbling fluidized bed. It presents an original scheme that combines a single particle model and a global fluidized bed model in order to represent the HM vaporization during MSW combustion. Two of the most representative HM (Cd and Pb) with bed temperatures ranging between 923 and 1073 K have been considered. This new approach uses ANSYS FLUENT 14.0 as the modelling platform for the simulations along with a complete set of self-developed user-defined functions (UDFs). The simulation results are compared to the experimental data obtained previously by the research group in a lab-scale fluid bed incinerator. The comparison indicates that the proposed CFD model predicts well the evolution of the HM release for the bed temperatures analyzed. It shows that both bed temperature and bed dynamics have influence on the HM vaporization rate. It can be concluded that CFD is a rigorous tool that provides valuable information about HM vaporization and that the original two-scale simulation scheme adopted allows to better represent the actual particle behavior in a fluid bed incinerator.

  11. Waste production and regional growth of marine activities an econometric model.

    Science.gov (United States)

    Bramati, Maria Caterina

    2016-11-15

    Coastal regions are characterized by intense human activity and climatic pressures, often intensified by competing interests in the use of marine waters. To assess the effect of public spending on the regional economy, an econometric model is here proposed. Not only are the regional investment and the climatic risks included in the model, but also variables related to the anthropogenic pressure, such as population, economic activities and waste production. Feedback effects of economic and demographic expansion on the pollution of coastal areas are also considered. It is found that dangerous waste increases with growing shipping and transportation activities and with growing population density in non-touristic coastal areas. On the other hand, the amount of non-dangerous wastes increases with marine mining, defense and offshore energy production activities. However, lower waste production occurs in areas where aquaculture and touristic industry are more exploited, and accompanied by increasing regional investment in waste disposal.

  12. Estimating the magnitude of prediction uncertainties for the APLE model

    Science.gov (United States)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analysis for the Annual P ...

  13. Equilibrium and kinetic modelling of Cd(II) biosorption by algae Gelidium and agar extraction algal waste.

    Science.gov (United States)

    Vilar, Vítor J P; Botelho, Cidália M S; Boaventura, Rui A R

    2006-01-01

    In this study an industrial algal waste from agar extraction has been used as an inexpensive and effective biosorbent for cadmium (II) removal from aqueous solutions. This biosorbent was compared with the algae Gelidium itself, which is the raw material for agar extraction. Equilibrium data follow both Langmuir and Redlich-Peterson models. The parameters of Langmuir equilibrium model are q(max)=18.0 mgg(-1), b=0.19 mgl(-1) and q(max)=9.7 mgg(-1), b=0.16 mgl(-1), respectively for Gelidium and the algal waste. Kinetic experiments were conducted at initial Cd(II) concentrations in the range 6-91 mgl(-1). Data were fitted to pseudo-first- and second-order Lagergren models. For an initial Cd(II) concentration of 91 mgl(-1) the parameters of the pseudo-first-order Lagergren model are k(1,ads)=0.17 and 0.87 min(-1); q(eq)=16.3 and 8.7 mgg(-1), respectively, for Gelidium and algal waste. Kinetic constants vary with the initial metal concentration. The adsorptive behaviour of biosorbent particles was modelled using a batch reactor mass transfer kinetic model. The model successfully predicts Cd(II) concentration profiles and provides significant insights on the biosorbents performance. The homogeneous diffusivity, D(h), is in the range 0.5-2.2 x10(-8) and 2.1-10.4 x10(-8)cm(2)s(-1), respectively, for Gelidium and algal waste.

  14. Prediction of Catastrophes: an experimental model

    CERN Document Server

    Peters, Randall D; Pomeau, Yves

    2012-01-01

    Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in both of two dynamical models. The first is an "abstract" model in which a time dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for creep). Hope thus exists that similar changes in the response to ...

  15. Predictive modeling of low solubility semiconductor alloys

    Science.gov (United States)

    Rodriguez, Garrett V.; Millunchick, Joanna M.

    2016-09-01

    GaAsBi is of great interest for applications in high efficiency optoelectronic devices due to its highly tunable bandgap. However, the experimental growth of high Bi content films has proven difficult. Here, we model GaAsBi film growth using a kinetic Monte Carlo simulation that explicitly takes cation and anion reactions into account. The unique behavior of Bi droplets is explored, and a sharp decrease in Bi content upon Bi droplet formation is demonstrated. The high mobility of simulated Bi droplets on GaAsBi surfaces is shown to produce phase separated Ga-Bi droplets as well as depressions on the film surface. A phase diagram for a range of growth rates that predicts both Bi content and droplet formation is presented to guide the experimental growth of high Bi content GaAsBi films.

  16. 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 ...

  17. Leptogenesis in minimal predictive seesaw models

    Science.gov (United States)

    Björkeroth, Fredrik; de Anda, Francisco J.; de Medeiros Varzielas, Ivo; King, Stephen F.

    2015-10-01

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to ( ν e , ν μ , ν τ ) proportional to (0, 1, 1) and (1, n, n - 2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A 4 vacuum alignment provides the required Yukawa structures with n = 3, while a {{Z}}_9 symmetry fixes the relatives phase to be a ninth root of unity.

  18. Forecasting municipal solid waste generation using prognostic tools and regression analysis.

    Science.gov (United States)

    Ghinea, Cristina; Drăgoi, Elena Niculina; Comăniţă, Elena-Diana; Gavrilescu, Marius; Câmpean, Teofil; Curteanu, Silvia; Gavrilescu, Maria

    2016-11-01

    For an adequate planning of waste management systems the accurate forecast of waste generation is an essential step, since various factors can affect waste trends. The application of predictive and prognosis models are useful tools, as reliable support for decision making processes. In this paper some indicators such as: number of residents, population age, urban life expectancy, total municipal solid waste were used as input variables in prognostic models in order to predict the amount of solid waste fractions. We applied Waste Prognostic Tool, regression analysis and time series analysis to forecast municipal solid waste generation and composition by considering the Iasi Romania case study. Regression equations were determined for six solid waste fractions (paper, plastic, metal, glass, biodegradable and other waste). Accuracy Measures were calculated and the results showed that S-curve trend model is the most suitable for municipal solid waste (MSW) prediction.

  19. Modelling the anaerobic digestion of solid organic waste - Substrate characterisation method for ADM1 using a combined biochemical and kinetic parameter estimation approach.

    Science.gov (United States)

    Poggio, D; Walker, M; Nimmo, W; Ma, L; Pourkashanian, M

    2016-07-01

    This work proposes a novel and rigorous substrate characterisation methodology to be used with ADM1 to simulate the anaerobic digestion of solid organic waste. The proposed method uses data from both direct substrate analysis and the methane production from laboratory scale anaerobic digestion experiments and involves assessment of four substrate fractionation models. The models partition the organic matter into a mixture of particulate and soluble fractions with the decision on the most suitable model being made on quality of fit between experimental and simulated data and the uncertainty of the calibrated parameters. The method was tested using samples of domestic green and food waste and using experimental data from both short batch tests and longer semi-continuous trials. The results showed that in general an increased fractionation model complexity led to better fit but with increased uncertainty. When using batch test data the most suitable model for green waste included one particulate and one soluble fraction, whereas for food waste two particulate fractions were needed. With richer semi-continuous datasets, the parameter estimation resulted in less uncertainty therefore allowing the description of the substrate with a more complex model. The resulting substrate characterisations and fractionation models obtained from batch test data, for both waste samples, were used to validate the method using semi-continuous experimental data and showed good prediction of methane production, biogas composition, total and volatile solids, ammonia and alkalinity.

  20. Site-Specific Seismic Site Response Model for the Waste Treatment Plant, Hanford, Washington

    Energy Technology Data Exchange (ETDEWEB)

    Rohay, Alan C.; Reidel, Steve P.

    2005-02-24

    This interim report documents the collection of site-specific geologic and geophysical data characterizing the Waste Treatment Plant site and the modeling of the site-specific structure response to earthquake ground motions.

  1. Evaluation of high-level waste pretreatment processes with an approximate reasoning model

    Energy Technology Data Exchange (ETDEWEB)

    Bott, T.F.; Eisenhawer, S.W.; Agnew, S.F.

    1999-04-01

    The development of an approximate-reasoning (AR)-based model to analyze pretreatment options for high-level waste is presented. AR methods are used to emulate the processes used by experts in arriving at a judgment. In this paper, the authors first consider two specific issues in applying AR to the analysis of pretreatment options. They examine how to combine quantitative and qualitative evidence to infer the acceptability of a process result using the example of cesium content in low-level waste. They then demonstrate the use of simple physical models to structure expert elicitation and to produce inferences consistent with a problem involving waste particle size effects.

  2. Optimising the anaerobic co-digestion of urban organic waste using dynamic bioconversion mathematical modelling

    DEFF Research Database (Denmark)

    Fitamo, Temesgen Mathewos; Boldrin, Alessio; Dorini, G.

    2016-01-01

    strategies for controlling and optimising the co-digestion process. The model parameters were maintained in the same way as the original dynamic bioconversion model, albeit with minor adjustments, to simulate the co-digestion of food and garden waste with mixed sludge from a wastewater treatment plant...... scenario analysis demonstrated that increasing the amount of mixed sludge in the co-substrate had a marginal effect on the reactor performance. In contrast, increasing the amount of food waste and garden waste resulted in improved performance....

  3. An incentive-based source separation model for sustainable municipal solid waste management in China.

    Science.gov (United States)

    Xu, Wanying; Zhou, Chuanbin; Lan, Yajun; Jin, Jiasheng; Cao, Aixin

    2015-05-01

    Municipal solid waste (MSW) management (MSWM) is most important and challenging in large urban communities. Sound community-based waste management systems normally include waste reduction and material recycling elements, often entailing the separation of recyclable materials by the residents. To increase the efficiency of source separation and recycling, an incentive-based source separation model was designed and this model was tested in 76 households in Guiyang, a city of almost three million people in southwest China. This model embraced the concepts of rewarding households for sorting organic waste, government funds for waste reduction, and introducing small recycling enterprises for promoting source separation. Results show that after one year of operation, the waste reduction rate was 87.3%, and the comprehensive net benefit under the incentive-based source separation model increased by 18.3 CNY tonne(-1) (2.4 Euros tonne(-1)), compared to that under the normal model. The stakeholder analysis (SA) shows that the centralized MSW disposal enterprises had minimum interest and may oppose the start-up of a new recycling system, while small recycling enterprises had a primary interest in promoting the incentive-based source separation model, but they had the least ability to make any change to the current recycling system. The strategies for promoting this incentive-based source separation model are also discussed in this study.

  4. Comparing model predictions for ecosystem-based management

    DEFF Research Database (Denmark)

    Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste

    2016-01-01

    Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (Ew......E)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing...... on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects...

  5. ION EXCHANGE MODELING FOR REMOVAL OF CESIUM FROM HANFORD WASTE USING SUPERLIG 644 RESIN

    Energy Technology Data Exchange (ETDEWEB)

    Hamm, L

    2004-05-01

    The expected performance of a proposed ion exchange column using SuperLig{reg_sign} 644 resin for the removal of cesium from Hanford high level radioactive alkaline waste is discussed. This report represents a final report on the ability and knowledge with regard to modeling the Cesium-SuperLig{reg_sign} 644 resin ion exchange system. Only the loading phase of the cycle process is addressed within this report. Pertinent bench-scale column tests and batch equilibrium experiments are addressed. The methodology employed and sensitivity analyses are also included (i.e., existing methodology employed is referenced to prior developmental efforts while updated methodology is discussed). Pilot-scale testing is not assessed since no pilot-scale testing was available at the time of this report. Column performance predictions are made considering three selected feed compositions under nominal operating conditions. The sensitivity analyses provided help to identify key parameters that aid in resin procurement acceptance criteria. The methodology and application presented within this report reflect the expected behavior of SuperLig{reg_sign} 644 resin manufactured at the production-scale (i.e, 250 gallon batch size level). The primary objective of this work was, through modeling and verification based on experimental assessments, to predict the cesium removal performance of SuperLig{reg_sign} 644 resin for application in the RPP pretreatment facility.

  6. CHALLENGES IN SOURCE TERM MODELING OF DECONTAMINATION AND DECOMMISSIONING WASTES.

    Energy Technology Data Exchange (ETDEWEB)

    SULLIVAN, T.M.

    2006-08-01

    Development of real-time predictive modeling to identify the dispersion and/or source(s) of airborne weapons of mass destruction including chemical, biological, radiological, and nuclear material in urban environments is needed to improve response to potential releases of these materials via either terrorist or accidental means. These models will also prove useful in defining airborne pollution dispersion in urban environments for pollution management/abatement programs. Predicting gas flow in an urban setting on a scale of less than a few kilometers is a complicated and challenging task due to the irregular flow paths that occur along streets and alleys and around buildings of different sizes and shapes, i.e., ''urban canyons''. In addition, air exchange between the outside and buildings and subway areas further complicate the situation. Transport models that are used to predict dispersion of WMD/CBRN materials or to back track the source of the release require high-density data and need defensible parameterizations of urban processes. Errors in the data or any of the parameter inputs or assumptions will lead to misidentification of the airborne spread or source release location(s). The need for these models to provide output in a real-time fashion if they are to be useful for emergency response provides another challenge. To improve the ability of New York City's (NYC's) emergency management teams and first response personnel to protect the public during releases of hazardous materials, the New York City Urban Dispersion Program (UDP) has been initiated. This is a four year research program being conducted from 2004 through 2007. This paper will discuss ground level and subway Perfluorocarbon tracer (PFT) release studies conducted in New York City. The studies released multiple tracers to study ground level and vertical transport of contaminants. This paper will discuss the results from these tests and how these results can be used

  7. Remaining Useful Lifetime (RUL - Probabilistic Predictive Model

    Directory of Open Access Journals (Sweden)

    Ephraim Suhir

    2011-01-01

    Full Text Available Reliability evaluations and assurances cannot be delayed until the device (system is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications, by electrical, optical and mechanical measurements and testing; checked (screened during manufacturing (fabrication; and, if necessary and appropriate, maintained in the field during the product’s operation Simple and physically meaningful probabilistic predictive model is suggested for the evaluation of the remaining useful lifetime (RUL of an electronic device (system after an appreciable deviation from its normal operation conditions has been detected, and the increase in the failure rate and the change in the configuration of the wear-out portion of the bathtub has been assessed. The general concepts are illustrated by numerical examples. The model can be employed, along with other PHM forecasting and interfering tools and means, to evaluate and to maintain the high level of the reliability (probability of non-failure of a device (system at the operation stage of its lifetime.

  8. A Predictive Model of Geosynchronous Magnetopause Crossings

    CERN Document Server

    Dmitriev, A; Chao, J -K

    2013-01-01

    We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...

  9. Predictive modeling for EBPC in EBDW

    Science.gov (United States)

    Zimmermann, Rainer; Schulz, Martin; Hoppe, Wolfgang; Stock, Hans-Jürgen; Demmerle, Wolfgang; Zepka, Alex; Isoyan, Artak; Bomholt, Lars; Manakli, Serdar; Pain, Laurent

    2009-10-01

    We demonstrate a flow for e-beam proximity correction (EBPC) to e-beam direct write (EBDW) wafer manufacturing processes, demonstrating a solution that covers all steps from the generation of a test pattern for (experimental or virtual) measurement data creation, over e-beam model fitting, proximity effect correction (PEC), and verification of the results. We base our approach on a predictive, physical e-beam simulation tool, with the possibility to complement this with experimental data, and the goal of preparing the EBPC methods for the advent of high-volume EBDW tools. As an example, we apply and compare dose correction and geometric correction for low and high electron energies on 1D and 2D test patterns. In particular, we show some results of model-based geometric correction as it is typical for the optical case, but enhanced for the particularities of e-beam technology. The results are used to discuss PEC strategies, with respect to short and long range effects.

  10. Accurate Holdup Calculations with Predictive Modeling & Data Integration

    Energy Technology Data Exchange (ETDEWEB)

    Azmy, Yousry [North Carolina State Univ., Raleigh, NC (United States). Dept. of Nuclear Engineering; Cacuci, Dan [Univ. of South Carolina, Columbia, SC (United States). Dept. of Mechanical Engineering

    2017-04-03

    In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use

  11. Solid waste management based on cost-benefit analysis using the WAMED model

    Energy Technology Data Exchange (ETDEWEB)

    Mutavchi, Viacheslav

    2012-11-01

    Efficient waste management enables the protection of human health, reducing environmental pollution, saving of natural resources, and achieving sustainable and profitable management of energy. In many countries, the general guidelines for waste management are set by national or local waste management plans. Various models provide local authorities with decision-making tools in planning long-term waste management scenarios. This study aims at providing a special model framework for the evaluation of ecological-economic efficiency (ECO-EE) of waste management. This will serve as an information support tool for decision making by actors of a solid waste management (SWM) scheme, primarily at the municipal and regional levels. The objective of this study is to apply the waste management's efficient decision (WAMED) model along with the company statistical business tool for environmental recovery indicator (COSTBUSTER) model to SWM and municipal solid waste (MSW) schemes in general in order to evaluate and improve their ECO-EE. COSTBUSTER is a mathematical indicator for the size and extent of implementation costs of a certain SWM scheme, compared with the total size of the average financial budget of a SWM actor of a certain kind. In particular, WAMED is proposed for evaluating the suitability to invest in baling technology. Baling of solid waste is an emerging technology which is extensively used worldwide to temporarily store waste for either incineration or recovery of raw materials. The model for efficient use of resources for optimal production economy (the EUROPE model) is for the first time applied to emissions from baling facilities. It has been analysed how cost-benefit analysis (CBA) and full cost accounting (FCA) can facilitate environmental optimisation of SWM schemes. The effort in this work represents a continuation of such ambitions as an enlargement of the research area of CBAbased modelling within SWM. In the thesis, certain theoretical and economic

  12. Natural Analogues - One Way to Help Build Public Confidence in the Predicted Performance of a Mined Geologic Repository for Nuclear Waste

    Energy Technology Data Exchange (ETDEWEB)

    Stuckless, J. S.

    2002-02-26

    The general public needs to have a way to judge the predicted long-term performance of the potential high-level nuclear waste repository at Yucca Mountain. The applicability and reliability of mathematical models used to make this prediction are neither easily understood nor accepted by the public. Natural analogues can provide the average person with a tool to assess the predicted performance and other scientific conclusions. For example, hydrologists with the Yucca Mountain Project have predicted that most of the water moving through the unsaturated zone at Yucca Mountain, Nevada will move through the host rock and around tunnels. Thus, seepage into tunnels is predicted to be a small percentage of available infiltration. This hypothesis can be tested experimentally and with some quantitative analogues. It can also be tested qualitatively using a variety of analogues such as (1) well-preserved Paleolithic to Neolithic paintings in caves and rock shelters, (2) biological remains preserved in caves and rock shelters, and (3) artifacts and paintings preserved in man-made underground openings. These examples can be found in materials that are generally available to the non-scientific public and can demonstrate the surprising degree of preservation of fragile and easily destroyed materials for very long periods of time within the unsaturated zone.

  13. Upgrade to Ion Exchange Modeling for Removal of Technetium from Hanford Waste Using SuperLig® 639 Resin

    Energy Technology Data Exchange (ETDEWEB)

    Hamm, L. [Savannah River Site (SRS), Aiken, SC (United States); Smith, F. [Savannah River Site (SRS), Aiken, SC (United States); Aleman, S. [Savannah River Site (SRS), Aiken, SC (United States); McCabe, D. [Savannah River Site (SRS), Aiken, SC (United States)

    2013-05-16

    This report documents the development and application of computer models to describe the sorption of pertechnetate [TcO₄⁻], and its surrogate perrhenate [ReO₄⁻], on SuperLig® 639 resin. Two models have been developed: 1) A thermodynamic isotherm model, based on experimental data, that predicts [TcO₄⁻] and [ReO₄⁻] sorption as a function of solution composition and temperature and 2) A column model that uses the isotherm calculated by the first model to simulate the performance of a full-scale sorption process. The isotherm model provides a synthesis of experimental data collected from many different sources to give a best estimate prediction of the behavior of the pertechnetate-SuperLig® 639 system and an estimate of the uncertainty in this prediction. The column model provides a prediction of the expected performance of the plant process by determining the volume of waste solution that can be processed based on process design parameters such as column size, flow rate and resin physical properties.

  14. Upgrade to Ion Exchange Modeling for Removal of Technetium from Hanford Waste Using SuperLig® 639 Resin

    Energy Technology Data Exchange (ETDEWEB)

    Hamm, L. [Savannah River Site (SRS), Aiken, SC (United States); Smith, F. [Savannah River Site (SRS), Aiken, SC (United States); Aleman, S. [Savannah River Site (SRS), Aiken, SC (United States); McCabe, D. [Savannah River Site (SRS), Aiken, SC (United States)

    2013-05-16

    This report documents the development and application of computer models to describe the sorption of pertechnetate [TcO₄⁻], and its surrogate perrhenate [ReO₄⁻], on SuperLig® 639 resin. Two models have been developed: 1) A thermodynamic isotherm model, based on experimental data, that predicts [TcO₄⁻] and [ReO₄⁻] sorption as a function of solution composition and temperature and 2) A column model that uses the isotherm calculated by the first model to simulate the performance of a full-scale sorption process. The isotherm model provides a synthesis of experimental data collected from many different sources to give a best estimate prediction of the behavior of the pertechnetate-SuperLig® 639 system and an estimate of the uncertainty in this prediction. The column model provides a prediction of the expected performance of the plant process by determining the volume of waste solution that can be processed based on process design parameters such as column size, flow rate and resin physical properties.

  15. Model for predicting mountain wave field uncertainties

    Science.gov (United States)

    Damiens, Florentin; Lott, François; Millet, Christophe; Plougonven, Riwal

    2017-04-01

    Studying the propagation of acoustic waves throughout troposphere requires knowledge of wind speed and temperature gradients from the ground up to about 10-20 km. Typical planetary boundary layers flows are known to present vertical low level shears that can interact with mountain waves, thereby triggering small-scale disturbances. Resolving these fluctuations for long-range propagation problems is, however, not feasible because of computer memory/time restrictions and thus, they need to be parameterized. When the disturbances are small enough, these fluctuations can be described by linear equations. Previous works by co-authors have shown that the critical layer dynamics that occur near the ground produces large horizontal flows and buoyancy disturbances that result in intense downslope winds and gravity wave breaking. While these phenomena manifest almost systematically for high Richardson numbers and when the boundary layer depth is relatively small compare to the mountain height, the process by which static stability affects downslope winds remains unclear. In the present work, new linear mountain gravity wave solutions are tested against numerical predictions obtained with the Weather Research and Forecasting (WRF) model. For Richardson numbers typically larger than unity, the mesoscale model is used to quantify the effect of neglected nonlinear terms on downslope winds and mountain wave patterns. At these regimes, the large downslope winds transport warm air, a so called "Foehn" effect than can impact sound propagation properties. The sensitivity of small-scale disturbances to Richardson number is quantified using two-dimensional spectral analysis. It is shown through a pilot study of subgrid scale fluctuations of boundary layer flows over realistic mountains that the cross-spectrum of mountain wave field is made up of the same components found in WRF simulations. The impact of each individual component on acoustic wave propagation is discussed in terms of

  16. Prediction of the waste stabilization pond performance using linear multiple regression and multi-layer perceptron neural network: a case study of Birjand, Iran

    Directory of Open Access Journals (Sweden)

    Maryam Khodadadi

    2016-06-01

    Full Text Available Background: Data mining (DM is an approach used in extracting valuable information from environmental processes. This research depicts a DM approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond (WSP in Birjand, a city in Eastern Iran. Methods: Multiple regression (MR and neural network (NN models were examined using influent characteristics (pH, Biochemical oxygen demand [BOD5], temperature, chemical oxygen demand [COD], total suspended solids [TSS], total dissolved solid [TDS], electrical conductivity [EC] and turbidity as the regression input vectors. Models were adjusted to input attributes, effluent BOD5 (BODout and COD (CODout. The models performances were estimated by 10-fold external cross-validation. An internal 5-fold cross-validation was also used for the training data set in NN model. The models were compared using regression error characteristic (REC plot and other statistical measures such as relative absolute error (RAE. Sensitivity analysis was also applied to extract useful knowledge from NN model. Results: NN models (with RAE = 78.71 ± 1.16 for BODout and 83.67 ± 1.35 for CODout and MR models (with RAE = 84.40% ± 1.07 for BODout and 88.07 ± 0.80 for CODout indicate different performances and the former was better (P < 0.05 for the prediction of both effluent BOD5 and COD parameters. For the prediction of CODout the NN model with hidden layer size (H = 4 and decay factor = 0.75 ± 0.03 presented the best predictive results. For BODout the H and decay factor were found to be 4 and 0.73 ± 0.03, respectively. TDS was found as the most descriptive influent wastewater characteristics for the prediction of the WSP performance. The REC plots confirmed the NN model performance superiority for both BOD and COD effluent prediction. Conclusion: Modeling the performance of WSP systems using NN models along with sensitivity analysis can offer better

  17. Thermoelectric Generators for Automotive Waste Heat Recovery Systems Part I: Numerical Modeling and Baseline Model Analysis

    Science.gov (United States)

    Kumar, Sumeet; Heister, Stephen D.; Xu, Xianfan; Salvador, James R.; Meisner, Gregory P.

    2013-04-01

    A numerical model has been developed to simulate coupled thermal and electrical energy transfer processes in a thermoelectric generator (TEG) designed for automotive waste heat recovery systems. This model is capable of computing the overall heat transferred, the electrical power output, and the associated pressure drop for given inlet conditions of the exhaust gas and the available TEG volume. Multiple-filled skutterudites and conventional bismuth telluride are considered for thermoelectric modules (TEMs) for conversion of waste heat from exhaust into usable electrical power. Heat transfer between the hot exhaust gas and the hot side of the TEMs is enhanced with the use of a plate-fin heat exchanger integrated within the TEG and using liquid coolant on the cold side. The TEG is discretized along the exhaust flow direction using a finite-volume method. Each control volume is modeled as a thermal resistance network which consists of integrated submodels including a heat exchanger and a thermoelectric device. The pressure drop along the TEG is calculated using standard pressure loss correlations and viscous drag models. The model is validated to preserve global energy balances and is applied to analyze a prototype TEG with data provided by General Motors. Detailed results are provided for local and global heat transfer and electric power generation. In the companion paper, the model is then applied to consider various TEG topologies using skutterudite and bismuth telluride TEMs.

  18. Development of models for predicting carbon mineralization and associated phytotoxicity in compost-amended soil.

    Science.gov (United States)

    Aslam, Danielle N; Vandergheynst, Jean S; Rumsey, Thomas R

    2008-12-01

    Phytotoxicity of compost-amended soil is related to carbon mineralization associated with compost decomposition. The objective of this research was to determine if compost carbon mineralization potential, estimated using compost respiration rate measurements, could be combined with carbon mineralization kinetic models to predict phytotoxicity of compost-amended soil. First-order, second-order, and Monod kinetic models that include compost carbon mineralization potential, compost amendment rate, incubation time, and temperature were developed and compared for their ability to predict carbon mineralization kinetics. Experiments utilized two soil types amended with 0%, 5%, and 50% (v/v) food waste and green waste composts, incubated at 20 degrees C, 25 degrees C, 30 degrees C, 35 degrees C, and 45 degrees C for model development and under a diurnal temperature cycle from 20 degrees C to 30 degrees C for model validation. For most cases, a first-order model had an equivalent or better fit to the data than the other models. Mineralizable carbon estimated using the first-order model was significantly correlated to the probability of phytotoxicity in compost-amended soil.

  19. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  20. RFI modeling and prediction approach for SATOP applications: RFI prediction models

    Science.gov (United States)

    Nguyen, Tien M.; Tran, Hien T.; Wang, Zhonghai; Coons, Amanda; Nguyen, Charles C.; Lane, Steven A.; Pham, Khanh D.; Chen, Genshe; Wang, Gang

    2016-05-01

    This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.

  1. Developing a New Dynamic Model for Cultural Waste Management

    Directory of Open Access Journals (Sweden)

    Mitra Aftab Azari

    2013-01-01

    Full Text Available As it stands, there is a dramatic increase on cultural management studies, although majorities of them are related to ecology, sociology, anthropology. In this case, the present study examined the most important factors in cultural development via cause-effect method. Consequently, the aim of this study is presenting a comprehensive model for cultural development management based on elite opinions. In order to build a community which has been developed based upon the perspective document "developed, moral-based, focused on religious democracy, social justice, legitimate freedoms, human rights and generosity, advance knowledge included, health, activity, responsibility, inspirational, a human being is selected who is the origin of all positive behavioral developments. In this respect, as it is almost impossible to predict the complex, ambiguous and somehow paradoxical behavior of a human being with linear planning, who is capable of playing many different roles in the chronological process, in this survey Vensim DSS is considered as the research software according to its dynamic features. The results focused on the first theory of order in Chaos entitled as Butterfly Effect, proves that it is possible to predict the effects of changes in the cultural development variable until 2025. In addition, according to the simulated model, cultural development is more sensitive than the production process as compared to distribution and consumption processes. However, it shouldn't be ignored the fact that the effect of creativity is institutionalized in the essence of model and according to theories of natural order and order in Chaos; the core of its changes is based on dynamism, development and innovation.

  2. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to unders

  3. Kinetic modelling of anaerobic hydrolysis of solid wastes, including disintegration processes

    Energy Technology Data Exchange (ETDEWEB)

    García-Gen, Santiago [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Sousbie, Philippe; Rangaraj, Ganesh [INRA, UR50, Laboratoire de Biotechnologie de l’Environnement, Avenue des Etangs, Narbonne F-11100 (France); Lema, Juan M. [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Rodríguez, Jorge, E-mail: jrodriguez@masdar.ac.ae [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Institute Centre for Water and Environment (iWater), Masdar Institute of Science and Technology, PO Box 54224 Abu Dhabi (United Arab Emirates); Steyer, Jean-Philippe; Torrijos, Michel [INRA, UR50, Laboratoire de Biotechnologie de l’Environnement, Avenue des Etangs, Narbonne F-11100 (France)

    2015-01-15

    Highlights: • Fractionation of solid wastes into readily and slowly biodegradable fractions. • Kinetic coefficients estimation from mono-digestion batch assays. • Validation of kinetic coefficients with a co-digestion continuous experiment. • Simulation of batch and continuous experiments with an ADM1-based model. - Abstract: A methodology to estimate disintegration and hydrolysis kinetic parameters of solid wastes and validate an ADM1-based anaerobic co-digestion model is presented. Kinetic parameters of the model were calibrated from batch reactor experiments treating individually fruit and vegetable wastes (among other residues) following a new protocol for batch tests. In addition, decoupled disintegration kinetics for readily and slowly biodegradable fractions of solid wastes was considered. Calibrated parameters from batch assays of individual substrates were used to validate the model for a semi-continuous co-digestion operation treating simultaneously 5 fruit and vegetable wastes. The semi-continuous experiment was carried out in a lab-scale CSTR reactor for 15 weeks at organic loading rate ranging between 2.0 and 4.7 g VS/L d. The model (built in Matlab/Simulink) fit to a large extent the experimental results in both batch and semi-continuous mode and served as a powerful tool to simulate the digestion or co-digestion of solid wastes.

  4. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  5. MODELING SOLIDIFICATION-INDUCED STRESSES IN CERAMIC WASTE FORMS CONTAINING NUCLEAR WASTES

    Energy Technology Data Exchange (ETDEWEB)

    Charles W. Solbrig; Kenneth J. Bateman

    2010-11-01

    The goal of this work is to produce a ceramic waste form (CWF) that permanently occludes radioactive waste. This is accomplished by absorbing radioactive salts into zeolite, mixing with glass frit, heating to a molten state 915 C to form a sodalite glass matrix, and solidifying for long-term storage. Less long term leaching is expected if the solidifying cooling rate doesn’t cause cracking. In addition to thermal stress, this paper proposes that a stress is formed during solidification which is very large for fast cooling rates during solidification and can cause severe cracking. A solidifying glass or ceramic cylinder forms a dome on the cylinder top end. The temperature distribution at the time of solidification causes the stress and the dome. The dome height, “the length deficit,” produces an axial stress when the solid returns to room temperature with the inherent outer region in compression, the inner in tension. Large tensions will cause cracking of the specimen. The temperature deficit, derived by dividing the length deficit by the coefficient of thermal expansion, allows solidification stress theory to be extended to the circumferential stress. This paper derives the solidification stress theory, gives examples, explains how to induce beneficial stresses, and compares theory to experimental data.

  6. Predictability of the Indian Ocean Dipole in the coupled models

    Science.gov (United States)

    Liu, Huafeng; Tang, Youmin; Chen, Dake; Lian, Tao

    2017-03-01

    In this study, the Indian Ocean Dipole (IOD) predictability, measured by the Indian Dipole Mode Index (DMI), is comprehensively examined at the seasonal time scale, including its actual prediction skill and potential predictability, using the ENSEMBLES multiple model ensembles and the recently developed information-based theoretical framework of predictability. It was found that all model predictions have useful skill, which is normally defined by the anomaly correlation coefficient larger than 0.5, only at around 2-3 month leads. This is mainly because there are more false alarms in predictions as leading time increases. The DMI predictability has significant seasonal variation, and the predictions whose target seasons are boreal summer (JJA) and autumn (SON) are more reliable than that for other seasons. All of models fail to predict the IOD onset before May and suffer from the winter (DJF) predictability barrier. The potential predictability study indicates that, with the model development and initialization improvement, the prediction of IOD onset is likely to be improved but the winter barrier cannot be overcome. The IOD predictability also has decadal variation, with a high skill during the 1960s and the early 1990s, and a low skill during the early 1970s and early 1980s, which is very consistent with the potential predictability. The main factors controlling the IOD predictability, including its seasonal and decadal variations, are also analyzed in this study.

  7. Construction waste management based on industrial management models: a Swedish case study.

    Science.gov (United States)

    Stenis, Jan

    2005-02-01

    This paper describes a methodology for estimating the true internal costs of construction waste, aimed at promoting environmentally friendly waste management. The study employs cost-benefit analysis, contribution margin analysis, the polluter-pays principle and a mathematical model: the model for Efficient Use of Resources for Optimal Production Economy (EUROPE), which has been introduced previously by the author for assigning industrial costs to waste. The calculations are performed on construction waste created in a case study of a building project. Moreover, waste is regarded as, in a business sense, having the same basic status as any normal industrial product, namely the 'equality principle'. Application of the methodology is suggested to create incentives for environmental and profitability improvement in construction companies and other types of industrial sectors. The results of the case study show the generation of construction waste to substantially decrease the final operating income, due to the internal shadow price cost it creates. This paper is intended to reduce the gap between the choice of waste management procedures and their economic impact, the overall objective being to accomplish an improved industrial environmental situation.

  8. Modeling of 3d Space-time Surface of Potential Fields and Hydrogeologic Modeling of Nuclear Waste Disposal Sites

    Science.gov (United States)

    Shestopalov, V.; Bondarenko, Y.; Zayonts, I.; Rudenko, Y.

    extracted from the total vertical and hori- zontal gradient respectively, both shaded from the 5 northeast to 355 northwest. The dip of multi-layer surfaces indicates the down -"gradient" direction in the fields. The methodology of 3D STSI is based on the analysis of vertical and horizontal anisotropy of gravity and magnetic fields, as well as of multi-layer 3D space-time surface model (3D STSM) of the stress fields. The 3D STSM is multi-layer topology structure of 1 lineaments or gradients (edges) and surfaces calculated by uniform matrices of the geophysical fields. One of the information components of the stress fields character- istics is the aspects and slopes for compressive and tensile stresses. Overlaying of the 3D STSI and lineaments with maps of multi-layer gradients enables to create highly reliable 3D Space-Time Kinematic Model "3D STKM". The analysis of 3D STKM in- cluded: - the space-time reconstruct of forces direction and strain distribution scheme during formation of geological structures and structural paragenesis (lineaments) of potential fields; - predict the real location of expected tectonic dislocations, zones of rock fracturing and disintegration, and mass-stable blocks. Based on these data, the 3D STSM are drawn which reflect the geodynamics of territory development on the ground of paleotectonic reconstruction of successive activity stages having formed the present-day lithosphere. Thus three-dimensional STSM allows to construct an un- mixing geodynamic processes in any interval of fixed space-time in coordinates x, y, t(z). The integrated of the 3D STSM and 3D seismic models enables also to create structural-kinematic and geodynamic maps of the Earth's crust at different depth. As a result, the classification of CNPP areas is performed into zones of compressive and tensile stresses characterized by enhanced permeability of rocks, and zones of consoli- dation with minimal rocks permeability. In addition, the vertically alternating zones of

  9. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  10. Leptogenesis in minimal predictive seesaw models

    Energy Technology Data Exchange (ETDEWEB)

    Björkeroth, Fredrik [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom); Anda, Francisco J. de [Departamento de Física, CUCEI, Universidad de Guadalajara,Guadalajara (Mexico); Varzielas, Ivo de Medeiros; King, Stephen F. [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom)

    2015-10-15

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the “atmospheric” and “solar” neutrino masses with Yukawa couplings to (ν{sub e},ν{sub μ},ν{sub τ}) proportional to (0,1,1) and (1,n,n−2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A{sub 4} vacuum alignment provides the required Yukawa structures with n=3, while a ℤ{sub 9} symmetry fixes the relatives phase to be a ninth root of unity.

  11. QSPR Models for Octane Number Prediction

    Directory of Open Access Journals (Sweden)

    Jabir H. Al-Fahemi

    2014-01-01

    Full Text Available Quantitative structure-property relationship (QSPR is performed as a means to predict octane number of hydrocarbons via correlating properties to parameters calculated from molecular structure; such parameters are molecular mass M, hydration energy EH, boiling point BP, octanol/water distribution coefficient logP, molar refractivity MR, critical pressure CP, critical volume CV, and critical temperature CT. Principal component analysis (PCA and multiple linear regression technique (MLR were performed to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The results of PCA explain the interrelationships between octane number and different variables. Correlation coefficients were calculated using M.S. Excel to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The data set was split into training of 40 hydrocarbons and validation set of 25 hydrocarbons. The linear relationship between the selected descriptors and the octane number has coefficient of determination (R2=0.932, statistical significance (F=53.21, and standard errors (s =7.7. The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving RCV2=0.942 and s=6.328.

  12. Modeling Solute Thermokinetics in LiCI-KCI Molten Salt for Nuclear Waste Separation

    Energy Technology Data Exchange (ETDEWEB)

    Morgan, Dane; Eapen, Jacob

    2013-10-01

    Recovery of actinides is an integral part of a closed nuclear fuel cycle. Pyrometallurgical nuclear fuel recycling processes have been developed in the past for recovering actinides from spent metallic and nitride fuels. The process is essentially to dissolve the spent fuel in a molten salt and then extract just the actinides for reuse in a reactor. Extraction is typically done through electrorefining, which involves electrochemical reduction of the dissolved actinides and plating onto a cathode. Knowledge of a number of basic thermokinetic properties of salts and salt-fuel mixtures is necessary for optimizing present and developing new approaches for pyrometallurgical waste processing. The properties of salt-fuel mixtures are presently being studied, but there are so many solutes and varying concentrations that direct experimental investigation is prohibitively time consuming and expensive (particularly for radioactive elements like Pu). Therefore, there is a need to reduce the number of required experiments through modeling of salt and salt-fuel mixture properties. This project will develop first-principles-based molecular modeling and simulation approaches to predict fundamental thermokinetic properties of dissolved actinides and fission products in molten salts. The focus of the proposed work is on property changes with higher concentrations (up to 5 mol%) of dissolved fuel components, where there is still very limited experimental data. The properties predicted with the modeling will be density, which is used to assess the amount of dissolved material in the salt; diffusion coefficients, which can control rates of material transport during separation; and solute activity, which determines total solubility and reduction potentials used during electrorefining. The work will focus on La, Sr, and U, which are chosen to include the important distinct categories of lanthanides, alkali earths, and actinides, respectively. Studies will be performed using LiCl-KCl salt

  13. Use of glazed ceramic waste as additive in mortar and the mathematical modelling of its strength.

    Science.gov (United States)

    Altin, Zehra Gulten; Erturan, Seyfettin; Tepecik, Abdulkadir

    2008-04-01

    This study investigated the reusability of waste material from the tile manufacturing industry as an alternative material to natural pozzolan trass. Yield strength values of mortar made from Portland cement (CEM 142.5), were measured by adding glazed ceramic waste and trass at various weight ratios (5 to 40%). The test results proved that the strength values at 2, 7, and 28 days gave good results for concentrations of waste materials less than 5-10% in the cement. A decrease in strength was observed at higher concentrations. Mathematical modelling results showed a logarithmic correlation between the mortar strength and weight fraction of cement.

  14. Genome-Based Models to Optimize In Situ Bioremediation of Uranium and Harvesting Electrical Energy from Waste Organic Matter

    Energy Technology Data Exchange (ETDEWEB)

    Lovley, Derek R

    2012-12-28

    The goal of this research was to provide computational tools to predictively model the behavior of two microbial communities of direct relevance to Department of Energy interests: 1) the microbial community responsible for in situ bioremediation of uranium in contaminated subsurface environments; and 2) the microbial community capable of harvesting electricity from waste organic matter and renewable biomass. During this project the concept of microbial electrosynthesis, a novel form of artificial photosynthesis for the direct production of fuels and other organic commodities from carbon dioxide and water was also developed and research was expanded into this area as well.

  15. Computer models used to support cleanup decision-making at hazardous and radioactive waste sites

    Energy Technology Data Exchange (ETDEWEB)

    Moskowitz, P.D.; Pardi, R.; DePhillips, M.P.; Meinhold, A.F.

    1992-07-01

    Massive efforts are underway to cleanup hazardous and radioactive waste sites located throughout the US To help determine cleanup priorities, computer models are being used to characterize the source, transport, fate and effects of hazardous chemicals and radioactive materials found at these sites. Although, the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the US Nuclear Regulatory Commission (NRC) have provided preliminary guidance to promote the use of computer models for remediation purposes, no Agency has produced directed guidance on models that must be used in these efforts. To identify what models are actually being used to support decision-making at hazardous and radioactive waste sites, a project jointly funded by EPA, DOE and NRC was initiated. The purpose of this project was to: (1) Identify models being used for hazardous and radioactive waste site assessment purposes; and (2) describe and classify these models. This report presents the results of this study.

  16. Computer models used to support cleanup decision-making at hazardous and radioactive waste sites

    Energy Technology Data Exchange (ETDEWEB)

    Moskowitz, P.D.; Pardi, R.; DePhillips, M.P.; Meinhold, A.F.

    1992-07-01

    Massive efforts are underway to cleanup hazardous and radioactive waste sites located throughout the US To help determine cleanup priorities, computer models are being used to characterize the source, transport, fate and effects of hazardous chemicals and radioactive materials found at these sites. Although, the US Environmental Protection Agency (EPA), the US Department of Energy (DOE), and the US Nuclear Regulatory Commission (NRC) have provided preliminary guidance to promote the use of computer models for remediation purposes, no Agency has produced directed guidance on models that must be used in these efforts. To identify what models are actually being used to support decision-making at hazardous and radioactive waste sites, a project jointly funded by EPA, DOE and NRC was initiated. The purpose of this project was to: (1) Identify models being used for hazardous and radioactive waste site assessment purposes; and (2) describe and classify these models. This report presents the results of this study.

  17. Municipal household solid waste fee based on an increasing block pricing model in Beijing, China.

    Science.gov (United States)

    Chu, Zhujie; Wu, Yunga; Zhuang, Jun

    2017-03-01

    This article aims to design an increasing block pricing model to estimate the waste fee with the consideration of the goals and principles of municipal household solid waste pricing. The increasing block pricing model is based on the main consideration of the per capita disposable income of urban residents, household consumption expenditure, production rate of waste disposal industry, and inflation rate. The empirical analysis is based on survey data of 5000 households in Beijing, China. The results indicate that the current uniform price of waste disposal is set too high for low-income people, and waste fees to the household disposable income or total household spending ratio are too low for the medium- and high-income families. An increasing block pricing model can prevent this kind of situation, and not only solve the problem of lack of funds, but also enhance the residents' awareness of environmental protection. A comparative study based on the grey system model is made by having a preliminary forecast for the waste emissions reduction effect of the pay-as-you-throw programme in the next 5 years of Beijing, China. The results show that the effect of the pay-as-you-throw programme is not only to promote the energy conservation and emissions reduction, but also giving a further improvement of the environmental quality.

  18. Comparison between a steady-state and a transient flow model and related radionuclide concentration predictions

    Science.gov (United States)

    Gedeon, M.; Mallants, D.

    2012-04-01

    Radionuclide concentration predictions in aquifers play an important role in estimating impact of planned surface disposal of radioactive waste in Belgium, developed by the Belgian Agency for Radioactive Waste and Enriched Fissile Materials (ONDRAF), who also coordinates and leads the corresponding research. Long-term concentration predictions are based on a steady-state flow solution obtained by a cascade of multi-scale models from the catchment to the detailed (site) scale performed in MODFLOW. To test the concept and accuracy of the groundwater flow solution and conservativeness of the concentration predictions obtained therewith, a transient model, considered more realistic, was set up in a sub-domain of the intermediate scale steady-state model. Besides the modelling domain reduction, the transient model was and exact copy of the steady-state model, having the infiltration as the only time-varying parameter. The transient model was run for a twenty-year period, whereas the results were compared to the steady-state results based on infiltration value and observations averaged over the same period. The comparison of the steady-state and transient flow solutions includes the analyses of the goodness of fit, the parameter sensitivities, relative importance of the individual observations and one-percent sensitivity maps. The steady-state and transient flow solutions were subsequently translated into a site-scale transport model, used to predict the radionuclide concentrations in a hypothetical well in the aquifers. The translation of the flow solutions between the models of distinct scales was performed using the Local grid refinement method available in MODFLOW. In the site-scale models, MT3DMS transport simulations were performed to obtain respective concentration predictions in a hypothetical well, situated at 70 meters from the disposal tumuli. The equilibrium concentrations based on a constant source flux achieved using a steady-state solution were then

  19. Monthly to seasonal low flow prediction: statistical versus dynamical models

    Science.gov (United States)

    Ionita-Scholz, Monica; Klein, Bastian; Meissner, Dennis; Rademacher, Silke

    2016-04-01

    While the societal and economical impacts of floods are well documented and assessable, the impacts of lows flows are less studied and sometimes overlooked. For example, over the western part of Europe, due to intense inland waterway transportation, the economical loses due to low flows are often similar compared to the ones due to floods. In general, the low flow aspect has the tendency to be underestimated by the scientific community. One of the best examples in this respect is the facts that at European level most of the countries have an (early) flood alert system, but in many cases no real information regarding the development, evolution and impacts of droughts. Low flows, occurring during dry periods, may result in several types of problems to society and economy: e.g. lack of water for drinking, irrigation, industrial use and power production, deterioration of water quality, inland waterway transport, agriculture, tourism, issuing and renewing waste disposal permits, and for assessing the impact of prolonged drought on aquatic ecosystems. As such, the ever-increasing demand on water resources calls for better a management, understanding and prediction of the water deficit situation and for more reliable and extended studies regarding the evolution of the low flow situations. In order to find an optimized monthly to seasonal forecast procedure for the German waterways, the Federal Institute of Hydrology (BfG) is exploring multiple approaches at the moment. On the one hand, based on the operational short- to medium-range forecasting chain, existing hydrological models are forced with two different hydro-meteorological inputs: (i) resampled historical meteorology generated by the Ensemble Streamflow Prediction approach and (ii) ensemble (re-) forecasts of ECMWF's global coupled ocean-atmosphere general circulation model, which have to be downscaled and bias corrected before feeding the hydrological models. As a second approach BfG evaluates in cooperation with

  20. Waste biorefinery models towards sustainable circular bioeconomy: Critical review and future perspectives.

    Science.gov (United States)

    Venkata Mohan, S; Nikhil, G N; Chiranjeevi, P; Nagendranatha Reddy, C; Rohit, M V; Kumar, A Naresh; Sarkar, Omprakash

    2016-09-01

    Increased urbanization worldwide has resulted in a substantial increase in energy and material consumption as well as anthropogenic waste generation. The main source for our current needs is petroleum refinery, which have grave impact over energy-environment nexus. Therefore, production of bioenergy and biomaterials have significant potential to contribute and need to meet the ever increasing demand. In this perspective, a biorefinery concept visualizes negative-valued waste as a potential renewable feedstock. This review illustrates different bioprocess based technological models that will pave sustainable avenues for the development of biobased society. The proposed models hypothesize closed loop approach wherein waste is valorised through a cascade of various biotechnological processes addressing circular economy. Biorefinery offers a sustainable green option to utilize waste and to produce a gamut of marketable bioproducts and bioenergy on par to petro-chemical refinery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Numerical modeling of rock stresses within a basaltic nuclear waste repository. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Hardy, M.P.; Hocking, G.

    1978-10-01

    The modeling undertaken during this project incorporated a wide range of problems that impact the design of the waste repository. Interaction of groundwater, heat and stress were considered on a regional scale, whereas on the room and canister scale thermo-mechanical analyses were undertaken. In the Phase II report, preliminary guidelines for waste densities were established based primarily on short-term stress criteria required to maintain stability during the retrievability period. Additional analyses are required to evaluate the effect of joints, borehole linings, room support and ventilation on these preliminary waste loading densities. The regional analyses did not indicate any adverse effect that could control the allowable waste loading densities. However, further refinements of geologic structure, hydrologic models, seismicity and possible induced seismicity are required before firm estimates of the loading densities can be made.

  2. Geochemical modelling of bentonite porewater in high-level waste repositories

    Science.gov (United States)

    Wersin, Paul

    2003-03-01

    The description of the geochemical properties of the bentonite backfill that serves as engineered barrier for nuclear repositories is a central issue for perfomance assessment since these play a large role in determining the fate of contaminants released from the waste. In this study the porewater chemistry of bentonite was assessed with a thermodynamic modelling approach that includes ion exchange, surface complexation and mineral equilibrium reactions. The focus was to identify the geochemical reactions controlling the major ion chemistry and acid-base properties and to explore parameter uncertainties specifically at high compaction degrees. First, the adequacy of the approach was tested with two distinct surface complexation models by describing recent experimental data performed at highly varying solid/liquid ratios and ionic strengths. The results indicate adequate prediction of the entire experimental data set. Second, the modelling was extended to repository conditions, taking as an example the current Swiss concept for high-level waste where the compacted bentonite backfill is surrounded by argillaceous rock. The main reactions controlling major ion chemistry were found to be calcite equilibrium and concurrent Na-Ca exchange reactions and de-protonation of functional surface groups. Third, a sensitivity analysis of the main model parameters was performed. The results thereof indicate a remarkable robustness of the model with regard to parameter uncertainties. The bentonite system is characterised by a large acid-base buffering capacity which leads to stable pH-conditions. The uncertainty in pH was found to be mainly induced by the pCO 2 of the surrounding host rock. The results of a simple diffusion-reaction model indicate only minor changes of porewater composition with time, which is primarily due to the geochemical similarities of the bentonite and the argillaceous host rock. Overall, the results show the usefulness of simple thermodynamic models to

  3. A Bayesian network model for assessing natural estrogen fate and transport in a swine waste lagoon.

    Science.gov (United States)

    Lee, Boknam; Kullman, Seth W; Yost, Erin; Meyer, Michael T; Worley-Davis, Lynn; Williams, C Michael; Reckhow, Kenneth H

    2014-10-01

    Commercial swine waste lagoons are regarded as a major reservoir of natural estrogens, which have the potential to produce adverse physiological effects on exposed aquatic organisms and wildlife. However, there remains limited understanding of the complex mechanisms of physical, chemical, and biological processes that govern the fate and transport of natural estrogens within an anaerobic swine lagoon. To improve lagoon management and ultimately help control the offsite transport of these compounds from swine operations, a probabilistic Bayesian network model was developed to assess natural estrogen fate and budget and then compared against data collected from a commercial swine field site. In general, the model was able to describe the estrogen fate and budget in both the slurry and sludge stores within the swine lagoon. Sensitivity analysis within the model demonstrated that the estrogen input loading from the associated barn facility was the most important factor in controlling estrogen concentrations within the lagoon slurry storage, whereas the settling rate was the most significant factor in the lagoon sludge storage. The degradation reactions were shown to be minor in both stores based on prediction of average total estrogen concentrations. Management scenario evaluations demonstrated that the best possible management options to reduce estrogen levels in the lagoon are either to adjust the estrogen input loading from swine barn facilities or to effectively enhance estrogen bonding with suspended solids through the use of organic polymers or inorganic coagulants.

  4. Predictability in models of the atmospheric circulation.

    NARCIS (Netherlands)

    Houtekamer, P.L.

    1992-01-01

    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error are. The

  5. Risk assessment modelling of fecal shedding caused by extended-spectrum cephalosporin-resistant Escherichia coli transmitted through waste milk fed to dairy pre-weaned calves.

    Science.gov (United States)

    Awosile, Babafela B; Smith, Ben A

    2017-10-04

    Waste milk feeding is a common practice in dairy operations. Regardless of the benefits of this practice to the dairy farmers, concerns from the potential dissemination of antimicrobial-resistant bacteria through the gut and subsequent shedding by calves into the environment are increasing. In this study, we employed Monte Carlo simulation to assess the risk of shedding extended-spectrum cephalosporin-resistant Escherichia coli (ESC-R E. coli) caused by waste milk feeding in pre-weaned calves using an exponential dose-response model fit to data for E. coli O157:H7 in cattle. Data from pertinent studies were included in our model to predict the risk of shedding. The median (5th and 95th percentiles) for the daily risk of shedding ESC-R E. coli by calves fed only contaminated waste milk was predicted to be 2.9 × 10(-3) (2.1 × 10(-3), 3.7 × 10(-3)), representing a median daily risk of 29 out of 10,000 calves shedding ESC-R E. coli due to exclusive feeding of waste milk containing ESC-R E. coli. This median value was reduced by 94% when accounting for the proportion of waste milk that does not contain ESC-R E. coli. The overall risk of shedding ESC-R E. coli through the pre-weaning period for farms that feed waste milk to calves was 5.7 × 10(-3) (2.4 × 10(-3), 1.1 × 10(-2)), representing 57 out of 10,000 calves. When accounting for the proportion of farms that do not feed waste milk, the pre-weaning period risk was reduced by 23%. By varying the prevalence of ESC-R E. coli in waste milk using values of 3, 1.5, and 1%, the daily risk of shedding decreased by factors of 50, 65, and 82%, respectively, which supports the reduction of contamination or discontinuation of feeding waste milk containing ESC-R E. coli as major mitigation measures to reduce the risk of shedding caused by ingestion of resistant bacteria. It is anticipated that the effects of antimicrobial residues in waste milk, which was not considered herein due to lack of data, would further increase

  6. A model standardized risk assessment protocol for use with hazardous waste sites.

    OpenAIRE

    Marsh, G M; Day, R.

    1991-01-01

    This paper presents a model standardized risk assessment protocol (SRAP) for use with hazardous waste sites. The proposed SRAP focuses on the degree and patterns of evidence that exist for a significant risk to human populations from exposure to a hazardous waste site. The SRAP was designed with at least four specific goals in mind: to organize the available scientific data on a specific site and to highlight important gaps in this knowledge; to facilitate rational, cost-effective decision ma...

  7. Thermal control of high energy nuclear waste, space option. [mathematical models

    Science.gov (United States)

    Peoples, J. A.

    1979-01-01

    Problems related to the temperature and packaging of nuclear waste material for disposal in space are explored. An approach is suggested for solving both problems with emphasis on high energy density waste material. A passive cooling concept is presented which utilized conduction rods that penetrate the inner core. Data are presented to illustrate the effectiveness of the rods and the limit of their capability. A computerized thermal model is discussed and developed for the cooling concept.

  8. Streamtube Fate and Transport Modeling of the Source Term for the Old Radioactive Waste

    Energy Technology Data Exchange (ETDEWEB)

    Brewer, K.

    2000-11-16

    The modeling described in this report is an extension of previous fate and transport modeling for the Old Radioactive Waste Burial Ground Corrective Measures Study/Feasibility Study. The purpose of this and the previous modeling is to provide quantitative input to the screening of remedial alternatives for the CMS/FS for this site.

  9. Source term model evaluations for the low-level waste facility performance assessment

    Energy Technology Data Exchange (ETDEWEB)

    Yim, M.S.; Su, S.I. [North Carolina State Univ., Raleigh, NC (United States)

    1995-12-31

    The estimation of release of radionuclides from various waste forms to the bottom boundary of the waste disposal facility (source term) is one of the most important aspects of LLW facility performance assessment. In this work, several currently used source term models are comparatively evaluated for the release of carbon-14 based on a test case problem. The models compared include PRESTO-EPA-CPG, IMPACTS, DUST and NEFTRAN-II. Major differences in assumptions and approaches between the models are described and key parameters are identified through sensitivity analysis. The source term results from different models are compared and other concerns or suggestions are discussed.

  10. Modelling and Numerical Simulation of Gas Migration in a Nuclear Waste Repository

    CERN Document Server

    Bourgeat, Alain; Smai, Farid

    2010-01-01

    We present a compositional compressible two-phase, liquid and gas, flow model for numerical simulations of hydrogen migration in deep geological radioactive waste repository. This model includes capillary effects and the gas diffusivity. The choice of the main variables in this model, Total or Dissolved Hydrogen Mass Concentration and Liquid Pressure, leads to a unique and consistent formulation of the gas phase appearance and disappearance. After introducing this model, we show computational evidences of its adequacy to simulate gas phase appearance and disappearance in different situations typical of underground radioactive waste repository.

  11. Pyrolysis of waste tires: A modeling and parameter estimation study using Aspen Plus(®).

    Science.gov (United States)

    Ismail, Hamza Y; Abbas, Ali; Azizi, Fouad; Zeaiter, Joseph

    2017-02-01

    This paper presents a simulation flowsheet model of a waste tire pyrolysis process with feed capacity of 150kg/h. A kinetic rate-based reaction model is formulated in a form implementable in the simulation package Aspen Plus, giving the flowsheet model the capability to predict more than 110 tire pyrolysis products as reported in experiments by Laresgoiti et al. (2004) and Williams (2013) for the oil and gas products respectively. The simulation model is successfully validated in two stages: firstly against experimental data from Olazar et al. (2008) by comparing the mass fractions for the oil products (gas, liquids (non-aromatics), aromatics, and tar) at temperatures of 425, 500, 550 and 610°C, and secondly against experimental results of main hydrocarbon products (C7 to C15) obtained by Laresgoiti et al. (2004) at temperatures of 400, 500, 600, and 700°C. The model was then used to analyze the effect of pyrolysis process temperature and showed that increased temperatures led to chain fractions from C10 and higher to decrease while smaller chains increased; this is attributed to the extensive cracking of the larger hydrocarbon chains at higher temperatures. The utility of the flowsheet model was highlighted through an energy analysis that targeted power efficiency of the process determined through production profiles of gasoline and diesel at various temperatures. This shows, through the summation of the net power gain from the plant for gasoline plus diesel that the maximum net power lies at the lower temperatures corresponding to minimum production of gasoline and maximum production of diesel. This simulation model can thus serve as a robust tool to respond to market conditions that dictate fuel demand and prices while at the same time identifying optimum process conditions (e.g. temperature) driven by process economics.

  12. Modeling seasonal behavior changes and disease transmission with application to chronic wasting disease.

    Science.gov (United States)

    Oraby, Tamer; Vasilyeva, Olga; Krewski, Daniel; Lutscher, Frithjof

    2014-01-07

    Behavior and habitat of wildlife animals change seasonally according to environmental conditions. Mathematical models need to represent this seasonality to be able to make realistic predictions about the future of a population and the effectiveness of human interventions. Managing and modeling disease in wild animal populations requires particular care in that disease transmission dynamics is a critical consideration in the etiology of both human and animal diseases, with different transmission paradigms requiring different disease risk management strategies. Since transmission of infectious diseases among wildlife depends strongly on social behavior, mechanisms of disease transmission could also change seasonally. A specific consideration in this regard confronted by modellers is whether the contact rate between individuals is density-dependent or frequency-dependent. We argue that seasonal behavior changes could lead to a seasonal shift between density and frequency dependence. This hypothesis is explored in the case of chronic wasting disease (CWD), a fatal disease that affects deer, elk and moose in many areas of North America. Specifically, we introduce a strategic CWD risk model based on direct disease transmission that accounts for the seasonal change in the transmission dynamics and habitats occupied, guided by information derived from cervid ecology. The model is composed of summer and winter susceptible-infected (SI) equations, with frequency-dependent and density-dependent transmission dynamics, respectively. The model includes impulsive birth events with density-dependent birth rate. We determine the basic reproduction number as a weighted average of two seasonal reproduction numbers. We parameterize the model from data derived from the scientific literature on CWD and deer ecology, and conduct global and local sensitivity analyses of the basic reproduction number. We explore the effectiveness of different culling strategies for the management of CWD

  13. Allostasis: a model of predictive regulation.

    Science.gov (United States)

    Sterling, Peter

    2012-04-12

    The premise of the standard regulatory model, "homeostasis", is flawed: the goal of regulation is not to preserve constancy of the internal milieu. Rather, it is to continually adjust the milieu to promote survival and reproduction. Regulatory mechanisms need to be efficient, but homeostasis (error-correction by feedback) is inherently inefficient. Thus, although feedbacks are certainly ubiquitous, they could not possibly serve as the primary regulatory mechanism. A newer model, "allostasis", proposes that efficient regulation requires anticipating needs and preparing to satisfy them before they arise. The advantages: (i) errors are reduced in magnitude and frequency; (ii) response capacities of different components are matched -- to prevent bottlenecks and reduce safety factors; (iii) resources are shared between systems to minimize reserve capacities; (iv) errors are remembered and used to reduce future errors. This regulatory strategy requires a dedicated organ, the brain. The brain tracks multitudinous variables and integrates their values with prior knowledge to predict needs and set priorities. The brain coordinates effectors to mobilize resources from modest bodily stores and enforces a system of flexible trade-offs: from each organ according to its ability, to each organ according to its need. The brain also helps regulate the internal milieu by governing anticipatory behavior. Thus, an animal conserves energy by moving to a warmer place - before it cools, and it conserves salt and water by moving to a cooler one before it sweats. The behavioral strategy requires continuously updating a set of specific "shopping lists" that document the growing need for each key component (warmth, food, salt, water). These appetites funnel into a common pathway that employs a "stick" to drive the organism toward filling the need, plus a "carrot" to relax the organism when the need is satisfied. The stick corresponds broadly to the sense of anxiety, and the carrot broadly to

  14. Multi-objective reverse logistics model for integrated computer waste management.

    Science.gov (United States)

    Ahluwalia, Poonam Khanijo; Nema, Arvind K

    2006-12-01

    This study aimed to address the issues involved in the planning and design of a computer waste management system in an integrated manner. A decision-support tool is presented for selecting an optimum configuration of computer waste management facilities (segregation, storage, treatment/processing, reuse/recycle and disposal) and allocation of waste to these facilities. The model is based on an integer linear programming method with the objectives of minimizing environmental risk as well as cost. The issue of uncertainty in the estimated waste quantities from multiple sources is addressed using the Monte Carlo simulation technique. An illustrated example of computer waste management in Delhi, India is presented to demonstrate the usefulness of the proposed model and to study tradeoffs between cost and risk. The results of the example problem show that it is possible to reduce the environmental risk significantly by a marginal increase in the available cost. The proposed model can serve as a powerful tool to address the environmental problems associated with exponentially growing quantities of computer waste which are presently being managed using rudimentary methods of reuse, recovery and disposal by various small-scale vendors.

  15. Modeling barriers of solid waste to energy practices: An Indian perspective

    Directory of Open Access Journals (Sweden)

    S. Bag

    2016-01-01

    Full Text Available In recent years managing solid wastes has been one of the burning problems in front of state and local municipal authorities. This is mainly due to scarcity of lands for landfill sites. In this context experts suggest that conversion of solid waste to energy and useful component is the best approach to reduce space and public health related problems. The entire process has to be managed by technologies that prevent pollution and protect the environment and at the same time minimize the cost through recovery of energy. Energy recovery in the form of electricity, heat and fuel from the waste using different technologies is possible through a variety of processes, including incineration, gasification, pyrolysis and anaerobic digestion. These processes are often grouped under “Waste to Energy technologies”. The objective of the study is twofold. First authors assessed the current status of solid waste management practices in India. Secondly the leading barriers are identified and Interpretive structural modeling technique and MICMAC analysis is performed to identify the contextual interrelationships between leading barriers influencing the solid waste to energy programs in the country. Finally the conclusions are drawn which will assist policy makers in designing sustainable waste management programs.

  16. Modelling fuel consumption in kerbside source segregated food waste collection: separate collection and co-collection.

    Science.gov (United States)

    Chu, T W; Heaven, S; Gredmaier, L

    2015-01-01

    Source separated food waste is a valuable feedstock for renewable energy production through anaerobic digestion, and a variety of collection schemes for this material have recently been introduced. The aim of this study was to identify options that maximize collection efficiency and reduce fuel consumption as part of the overall energy balance. A mechanistic model was developed to calculate the fuel consumption of kerbside collection of source segregated food waste, co-mingled dry recyclables and residual waste. A hypothetical city of 20,000 households was considered and nine scenarios were tested with different combinations of collection frequencies, vehicle types and waste types. The results showed that the potential fuel savings from weekly and fortnightly co-collection of household waste range from 7.4% to 22.4% and 1.8% to 26.6%, respectively, when compared to separate collection. A compartmentalized vehicle split 30:70 always performed better than one with two compartments of equal size. Weekly food waste collection with alternate weekly collection of the recyclables and residual waste by two-compartment collection vehicles was the best option to reduce the overall fuel consumption.

  17. Required Collaborative Work in Online Courses: A Predictive Modeling Approach

    Science.gov (United States)

    Smith, Marlene A.; Kellogg, Deborah L.

    2015-01-01

    This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

  18. A prediction model for assessing residential radon concentration in Switzerland

    NARCIS (Netherlands)

    Hauri, D.D.; Huss, A.; Zimmermann, F.; Kuehni, C.E.; Roosli, M.

    2012-01-01

    Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the

  19. Aspen Plus® and economic modeling of equine waste utilization for localized hot water heating via fast pyrolysis.

    Science.gov (United States)

    Hammer, Nicole L; Boateng, Akwasi A; Mullen, Charles A; Wheeler, M Clayton

    2013-10-15

    Aspen Plus(®) based simulation models have been developed to design a pyrolysis process for on-site production and utilization of pyrolysis oil from equine waste at the Equine Rehabilitation Center at Morrisville State College (MSC). The results indicate that utilization of all the available waste from the site's 41 horses requires a 6 oven dry metric ton per day (ODMTPD) pyrolysis system but it will require a 15 ODMTPD system for waste generated by an additional 150 horses at the expanded area including the College and its vicinity. For this a dual fluidized bed combustion reduction integrated pyrolysis system (CRIPS) developed at USDA's Agricultural Research Service (ARS) was identified as the technology of choice for pyrolysis oil production. The Aspen Plus(®) model was further used to consider the combustion of the produced pyrolysis oil (bio-oil) in the existing boilers that generate hot water for space heating at the Equine Center. The model results show the potential for both the equine facility and the College to displace diesel fuel (fossil) with renewable pyrolysis oil and alleviate a costly waste disposal problem. We predict that all the heat required to operate the pyrolyzer could be supplied by non-condensable gas and about 40% of the biochar co-produced with bio-oil. Techno-economic Analysis shows neither design is economical at current market conditions; however the 15 ODMTPD CRIPS design would break even when diesel prices reach $11.40/gal. This can be further improved to $7.50/gal if the design capacity is maintained at 6 ODMTPD but operated at 4950 h per annum.

  20. Modeling of kinetics of Cr(VI) sorption onto grape stalk waste in a stirred batch reactor.

    Science.gov (United States)

    Escudero, Carlos; Fiol, Nuria; Poch, Jordi; Villaescusa, Isabel

    2009-10-15

    Recently, Cr(VI) removal by grape stalks has been postulated to follow two mechanisms, adsorption and reduction to trivalent chromium. Nevertheless, the rate at which both processes take place and the possible simultaneity of both processes has not been investigated. In this work, kinetics of Cr(VI) sorption onto grape stalk waste has been studied. Experiments were carried out at different temperatures but at a constant pH (3+/-0.1) in a stirred batch reactor. Results showed that three steps take place in the process of Cr(VI) sorption onto grape stalk waste: Cr(VI) sorption, Cr(VI) reduction to Cr(III) and the adsorption of the formed Cr(III). Taking into account the evidences above mentioned, a model has been developed to predict Cr(VI) sorption on grape stalks on the basis of (i) irreversible reduction of Cr(VI) to Cr(III) reaction, whose reaction rate is assumed to be proportional to the Cr(VI) concentration in solution and (ii) adsorption and desorption of Cr(VI) and formed Cr(III) assuming that all the processes follow Langmuir type kinetics. The proposed model fits successfully the kinetic data obtained at different temperatures and describes the kinetics profile of total, hexavalent and trivalent chromium. The proposed model would be helpful for researchers in the field of Cr(VI) biosorption to design and predict the performance of sorption processes.

  1. Distributional Analysis for Model Predictive Deferrable Load Control

    OpenAIRE

    Chen, Niangjun; Gan, Lingwen; Low, Steven H.; Wierman, Adam

    2014-01-01

    Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In ...

  2. Conceptual modeling to optimize the haul and transfer of municipal solid waste.

    Science.gov (United States)

    Komilis, D P

    2008-11-01

    Two conceptual mixed integer linear optimization models were developed to optimize the haul and transfer of municipal solid waste (MSW) prior to landfilling. One model is based on minimizing time (h/d), whilst the second model is based on minimizing total cost (euro/d). Both models aim to calculate the optimum pathway to haul MSW from source nodes (waste production nodes, such as urban centers or municipalities) to sink nodes (landfills) via intermediate nodes (waste transfer stations). The models are applicable provided that the locations of the source, intermediate and sink nodes are fixed. The basic input data are distances among nodes, average vehicle speeds, haul cost coefficients (in euro/ton km), equipment and facilities' operating and investment cost, labor cost and tipping fees. The time based optimization model is easier to develop, since it is based on readily available data (distances among nodes). It can be used in cases in which no transfer stations are included in the system. The cost optimization model is more reliable compared to the time model provided that accurate cost data are available. The cost optimization model can be a useful tool to optimally allocate waste transfer stations in a region and can aid a community to investigate the threshold distance to a landfill above which the construction of a transfer station becomes financially beneficial. A sensitivity analysis reveals that queue times at the landfill or at the waste transfer station are key input variables. In addition, the waste transfer station ownership and the initial cost data affect the optimum path. A case study at the Municipality of Athens is used to illustrate the presented models.

  3. Prediction for Major Adverse Outcomes in Cardiac Surgery: Comparison of Three Prediction Models

    Directory of Open Access Journals (Sweden)

    Cheng-Hung Hsieh

    2007-09-01

    Conclusion: The Parsonnet score performed as well as the logistic regression models in predicting major adverse outcomes. The Parsonnet score appears to be a very suitable model for clinicians to use in risk stratification of cardiac surgery.

  4. On hydrological model complexity, its geometrical interpretations and prediction uncertainty

    NARCIS (Netherlands)

    Arkesteijn, E.C.M.M.; Pande, S.

    2013-01-01

    Knowledge of hydrological model complexity can aid selection of an optimal prediction model out of a set of available models. Optimal model selection is formalized as selection of the least complex model out of a subset of models that have lower empirical risk. This may be considered equivalent to

  5. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...

  6. Comparison of Uncertainty of Two Precipitation Prediction Models

    CERN Document Server

    Shield, Stephen

    2015-01-01

    Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has significant impacts on the results of subsurface flow and transport studies. One method to obtain the meteorological data required for flow and transport studies is the use of weather generating models. This paper compares the difference in performance of two weather generating models at Technical Area 54 of Los Alamos National Lab. Technical Area 54 is contains several waste pits for low-level radioactive waste and is the site for subsurface flow and transport studies. This makes the comparison of the performance of the two weather generators at this site particularly valuable.

  7. Predictive modeling of dental pain using neural network.

    Science.gov (United States)

    Kim, Eun Yeob; Lim, Kun Ok; Rhee, Hyun Sill

    2009-01-01

    The mouth is a part of the body for ingesting food that is the most basic foundation and important part. The dental pain predicted by the neural network model. As a result of making a predictive modeling, the fitness of the predictive modeling of dental pain factors was 80.0%. As for the people who are likely to experience dental pain predicted by the neural network model, preventive measures including proper eating habits, education on oral hygiene, and stress release must precede any dental treatment.

  8. Waste inventory and preliminary source term model for the Greater Confinement Disposal site at the Nevada Test Site

    Energy Technology Data Exchange (ETDEWEB)

    Chu, M.S.Y.; Bernard, E.A.

    1991-12-01

    Currently, there are several Greater Confinement Disposal (GCD) boreholes at the Radioactive Waste Management Site (RWMS) for the Nevada Test Site. These are intermediate-depth boreholes used for the disposal of special case wastes, that is, radioactive waste within the Department of Energy complex that do not meet the criteria established for disposal of high-level waste, transuranic waste, or low-level waste. A performance assessment is needed to evaluate the safety of the GCD site, and to examine the feasibility of the GCD disposal concept as a disposal solution for special case wastes in general. This report documents the effort in defining all the waste inventory presently disposed of at the GCD site, and the inventory and release model to be used in a performance assessment for compliance with the Environmental Protection Agency`s 40 CFR 191.

  9. LCA of waste management systems: Development of tools for modeling and uncertainty analysis

    DEFF Research Database (Denmark)

    Clavreul, Julie

    to be modelled rather than monitored as in classical LCA (e.g. landfilling or the application of processed waste on agricultural land). Therefore LCA-tools are needed which specifically address these issues and enable practitioners to model properly their systems. In this thesis several pieces of work...... are presented. First a review was carried out on all LCA studies of waste management systems published before mid-2012. This provided a global overview of the technologies and waste fractions which have attracted focus within LCA while enabling an analysis of methodological tendencies, the use of tools...... and databases and the application of uncertainty analysis methods. The major outcome of this thesis was the development of a new LCA model, called EASETECH, building on the experience with previous LCA-tools, in particular the EASEWASTE model. Before the actual implementation phase, a design phase involved...

  10. Process Options Description for Vitrification Flowsheet Model of INEEL Sodium Bearing Waste

    Energy Technology Data Exchange (ETDEWEB)

    Nichols, T.T.; Taylor, D.D.; Lauerhass, L.; Barnes, C.M.

    2002-02-21

    The technical information required for the development of a basic steady-state process simulation of the vitrification treatment train of sodium bearing waste (SBW) at Idaho National Engineering and Environmental Laboratory (INEEL) is presented. The objective of the modeling effort is to provide the predictive capability required to optimize an entire treatment train and assess system-wide impacts of local changes at individual unit operations, with the aim of reducing the schedule and cost of future process/facility design efforts. All the information required a priori for engineers to construct and link unit operation modules in a commercial software simulator to represent the alternative treatment trains is presented. The information is of a mid- to high-level nature and consists of the following: (1) a description of twenty-four specific unit operations--their operating conditions and constraints, primary species and key outputs, and the initial modeling approaches that will be used in the first year of the simulation's development; (2) three potential configurations of the unit operations (trains) and their interdependencies via stream connections; and (3) representative stream compositional makeups.

  11. Process Options Description for Vitrification Flowsheet Model of INEEL Sodium Bearing Waste

    Energy Technology Data Exchange (ETDEWEB)

    Nichols, T.T.; Taylor, D.D.; Lauerhass, L.; Barnes, C.M.

    2002-02-21

    The technical information required for the development of a basic steady-state process simulation of the vitrification treatment train of sodium bearing waste (SBW) at Idaho National Engineering and Environmental Laboratory (INEEL) is presented. The objective of the modeling effort is to provide the predictive capability required to optimize an entire treatment train and assess system-wide impacts of local changes at individual unit operations, with the aim of reducing the schedule and cost of future process/facility design efforts. All the information required a priori for engineers to construct and link unit operation modules in a commercial software simulator to represent the alternative treatment trains is presented. The information is of a mid- to high-level nature and consists of the following: (1) a description of twenty-four specific unit operations--their operating conditions and constraints, primary species and key outputs, and the initial modeling approaches that will be used in the first year of the simulation's development; (2) three potential configurations of the unit operations (trains) and their interdependencies via stream connections; and (3) representative stream compositional makeups.

  12. Developing a Sustainability Assessment Model to Analyze China’s Municipal Solid Waste Management Enhancement Strategy

    Directory of Open Access Journals (Sweden)

    Hua Li

    2015-01-01

    Full Text Available This study develops a sustainability assessment model for analysis and decision-making of the impact of China’s municipal solid waste management enhancement strategy options based on three waste treatment scenarios: landfill disposal, waste-to-energy incineration, and a combination of a material recovery facility and composting. The model employs life cycle assessment, health risk assessment, and full cost accounting to evaluate the treatment scenarios regarding safeguarding public health, protecting the environment and conserving resources, and economic feasibility. The model then uses an analytic hierarchy process for an overall appraisal of sustainability. Results suggest that a combination of material recovery and composting is the most efficient option. The study results clarify sustainable attributes, suitable predications, evaluation modeling, and stakeholder involvement issues in solid waste management. The demonstration of the use of sustainability assessment model (SAM provides flexibility by allowing assessment for a municipal solid waste management (MSWM strategy on a case-by-case basis, taking into account site-specific factors, therefore it has the potential for flexible applications in different communities/regions.

  13. An inexact reverse logistics model for municipal solid waste management systems.

    Science.gov (United States)

    Zhang, Yi Mei; Huang, Guo He; He, Li

    2011-03-01

    This paper proposed an inexact reverse logistics model for municipal solid waste management systems (IRWM). Waste managers, suppliers, industries and distributors were involved in strategic planning and operational execution through reverse logistics management. All the parameters were assumed to be intervals to quantify the uncertainties in the optimization process and solutions in IRWM. To solve this model, a piecewise interval programming was developed to deal with Min-Min functions in both objectives and constraints. The application of the model was illustrated through a classical municipal solid waste management case. With different cost parameters for landfill and the WTE, two scenarios were analyzed. The IRWM could reflect the dynamic and uncertain characteristics of MSW management systems, and could facilitate the generation of desired management plans. The model could be further advanced through incorporating methods of stochastic or fuzzy parameters into its framework. Design of multi-waste, multi-echelon, multi-uncertainty reverse logistics model for waste management network would also be preferred.

  14. Prediction of peptide bonding affinity: kernel methods for nonlinear modeling

    CERN Document Server

    Bergeron, Charles; Sundling, C Matthew; Krein, Michael; Katt, Bill; Sukumar, Nagamani; Breneman, Curt M; Bennett, Kristin P

    2011-01-01

    This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporation of transferable atom equivalent features improves predictive capability.

  15. Waste Classification based on Waste Form Heat Generation in Advanced Nuclear Fuel Cycles Using the Fuel-Cycle Integration and Tradeoffs (FIT) Model

    Energy Technology Data Exchange (ETDEWEB)

    Denia Djokic; Steven J. Piet; Layne F. Pincock; Nick R. Soelberg

    2013-02-01

    This study explores the impact of wastes generated from potential future fuel cycles and the issues presented by classifying these under current classification criteria, and discusses the possibility of a comprehensive and consistent characteristics-based classification framework based on new waste streams created from advanced fuel cycles. A static mass flow model, Fuel-Cycle Integration and Tradeoffs (FIT), was used to calculate the composition of waste streams resulting from different nuclear fuel cycle choices. This analysis focuses on the impact of waste form heat load on waste classification practices, although classifying by metrics of radiotoxicity, mass, and volume is also possible. The value of separation of heat-generating fission products and actinides in different fuel cycles is discussed. It was shown that the benefits of reducing the short-term fission-product heat load of waste destined for geologic disposal are neglected under the current source-based radioactive waste classification system , and that it is useful to classify waste streams based on how favorable the impact of interim storage is in increasing repository capacity.

  16. A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem

    Directory of Open Access Journals (Sweden)

    Omid Boyer

    2013-01-01

    Full Text Available Technology progress is a cause of industrial hazardous wastes increasing in the whole world . Management of hazardous waste is a significant issue due to the imposed risk on environment and human life. This risk can be a result of location of undesirable facilities and also routing hazardous waste. In this paper a biobjective mixed integer programing model for location-routing industrial hazardous waste with two objectives is developed. First objective is total cost minimization including transportation cost, operation cost, initial investment cost, and cost saving from selling recycled waste. Second objective is minimization of transportation risk. Risk of population exposure within bandwidth along route is used to measure transportation risk. This model can help decision makers to locate treatment, recycling, and disposal centers simultaneously and also to route waste between these facilities considering risk and cost criteria. The results of the solved problem prove conflict between two objectives. Hence, it is possible to decrease the cost value by marginally increasing the transportation risk value and vice versa. A weighted sum method is utilized to combine two objectives function into one objective function. To solve the problem GAMS software with CPLEX solver is used. The problem is applied in Markazi province in Iran.

  17. Emission model for landfills with mechanically-biologically pretreated waste, with the emphasis on modelling the gas balance; Emissionsprognosemodell fuer Deponien mit mechanisch-biologisch vorbehandelten Abfaellen - Schwerpunkt: Modellierung des Gashaushaltes

    Energy Technology Data Exchange (ETDEWEB)

    Danhamer, H.

    2001-07-01

    The objective of this work was to determine influence factors on processes going on in landfills with mechanically-biologically pretreated waste (MBP-landfills) in order to predict emissions. For this purpose a computer based model has been developed. The model allows to simulate the gas, water and heat balance as well as settlement processes and was called DESIM2005 (version MB). It is based on theoretical modeling approaches as well as data from lab and reactor experiments. The main focus of model application was to determine factors influencing the gas phase and the emissions of landfill gas and methane during operation and aftercare of MBP-landfills. By performing simulations the effects of changing parameters for the processes gas transport and biological degradation as well as the effects of different qualities in waste pretreatment and of varying landfill operation techniques were investigated. Possibilities for increasing the environmental sustainability of landfills containing mechanically-biologically pretreated waste were shown. (orig.)

  18. Assessment of municipal solid waste settlement models based on field-scale data analysis.

    Science.gov (United States)

    Bareither, Christopher A; Kwak, Seungbok

    2015-08-01

    An evaluation of municipal solid waste (MSW) settlement model performance and applicability was conducted based on analysis of two field-scale datasets: (1) Yolo and (2) Deer Track Bioreactor Experiment (DTBE). Twelve MSW settlement models were considered that included a range of compression behavior (i.e., immediate compression, mechanical creep, and biocompression) and range of total (2-22) and optimized (2-7) model parameters. A multi-layer immediate settlement analysis developed for Yolo provides a framework to estimate initial waste thickness and waste thickness at the end-of-immediate compression. Model application to the Yolo test cells (conventional and bioreactor landfills) via least squares optimization yielded high coefficient of determinations for all settlement models (R(2)>0.83). However, empirical models (i.e., power creep, logarithmic, and hyperbolic models) are not recommended for use in MSW settlement modeling due to potential non-representative long-term MSW behavior, limited physical significance of model parameters, and required settlement data for model parameterization. Settlement models that combine mechanical creep and biocompression into a single mathematical function constrain time-dependent settlement to a single process with finite magnitude, which limits model applicability. Overall, all models evaluated that couple multiple compression processes (immediate, creep, and biocompression) provided accurate representations of both Yolo and DTBE datasets. A model presented in Gourc et al. (2010) included the lowest number of total and optimized model parameters and yielded high statistical performance for all model applications (R(2)⩾0.97).

  19. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  20. Estimating national landfill methane emissions: an application of the 2006 Intergovernmental Panel on Climate Change Waste Model in Panama.

    Science.gov (United States)

    Weitz, Melissa; Coburn, Jeffrey B; Salinas, Edgar

    2008-05-01

    This paper estimates national methane emissions from solid waste disposal sites in Panama over the time period 1990-2020 using both the 2006 Intergovernmental Panel on Climate Change (IPCC) Waste Model spreadsheet and the default emissions estimate approach presented in the 1996 IPCC Good Practice Guidelines. The IPCC Waste Model has the ability to calculate emissions from a variety of solid waste disposal site types, taking into account country- or region-specific waste composition and climate information, and can be used with a limited amount of data. Countries with detailed data can also run the model with country-specific values. The paper discusses methane emissions from solid waste disposal; explains the differences between the two methodologies in terms of data needs, assumptions, and results; describes solid waste disposal circumstances in Panama; and presents the results of this analysis. It also demonstrates the Waste Model's ability to incorporate landfill gas recovery data and to make projections. The former default method methane emissions estimates are 25 Gg in 1994, and range from 23.1 Gg in 1990 to a projected 37.5 Gg in 2020. The Waste Model estimates are 26.7 Gg in 1994, ranging from 24.6 Gg in 1990 to 41.6 Gg in 2020. Emissions estimates for Panama produced by the new model were, on average, 8% higher than estimates produced by the former default methodology. The increased estimate can be attributed to the inclusion of all solid waste disposal in Panama (as opposed to only disposal in managed landfills), but the increase was offset somewhat by the different default factors and regional waste values between the 1996 and 2006 IPCC guidelines, and the use of the first-order decay model with a time delay for waste degradation in the IPCC Waste Model.