WorldWideScience

Sample records for building predictive models

  1. 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...

  2. Model Predictive Control for the Operation of Building Cooling Systems

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Yudong; Borrelli, Francesco; Hencey, Brandon; Coffey, Brian; Bengea, Sorin; Haves, Philip

    2010-06-29

    A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

  3. Hierarchical Model Predictive Control for Sustainable Building Automation

    Directory of Open Access Journals (Sweden)

    Barbara Mayer

    2017-02-01

    Full Text Available A hierarchicalmodel predictive controller (HMPC is proposed for flexible and sustainable building automation. The implications of a building automation system for sustainability are defined, and model predictive control is introduced as an ideal tool to cover all requirements. The HMPC is presented as a development suitable for the optimization of modern buildings, as well as retrofitting. The performance and flexibility of the HMPC is demonstrated by simulation studies of a modern office building, and the perfect interaction with future smart grids is shown.

  4. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...... for solving the nonconvex optimization problem is proposed in this paper. A simulation using the nonlinear model-based controller to control the temperature levels of an intelligent office building (PowerFlexHouse) is addressed. Its performance is compared with a linear model-based controller. The nonlinear...

  5. Building predictive models of soil particle-size distribution

    Directory of Open Access Journals (Sweden)

    Alessandro Samuel-Rosa

    2013-04-01

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

  6. Construction Cost Prediction by Using Building Information Modeling

    National Research Council Canada - National Science Library

    Remon F. Aziz

    2015-01-01

    The increased interest in using Building Information Modeling (BIM) in detailed construction cost estimates calls for methodologies to evaluate the effectiveness of BIM-Assisted Detailed Estimating (BADE...

  7. Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model

    Directory of Open Access Journals (Sweden)

    Yu-Ri Kim

    2016-03-01

    Full Text Available Recently, the Korean government has enforced disclosure of building energy performance, so that such information can help owners and prospective buyers to make suitable investment plans. Such a building energy performance policy of the government makes it mandatory for the building owners to obtain engineering audits and thereby evaluate the energy performance levels of their buildings. However, to calculate energy performance levels (i.e., asset rating methodology, a qualified expert needs to have access to at least the full project documentation and/or conduct an on-site inspection of the buildings. Energy performance certification costs a lot of time and money. Moreover, the database of certified buildings is still actually quite small. A need, therefore, is increasing for a simplified and user-friendly energy performance prediction tool for non-specialists. Also, a database which allows building owners and users to compare best practices is required. In this regard, the current study developed a simplified performance prediction model through experimental design, energy simulations and ANOVA (analysis of variance. Furthermore, using the new prediction model, a related mobile application was also developed.

  8. A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control

    DEFF Research Database (Denmark)

    Arendt, Krzysztof; Ionesi, Ana; Jradi, Muhyiddine;

    Model Predictive Control (MPC) of building systems is a promising approach to optimize building energy performance. In contrast to traditional control strategies which are reactive in nature, MPC optimizes the utilization of resources based on the predicted effects. It has been shown that energy...... savings potential of this technique can reach up to 40% compared to conventional control strategies depending on the particular building type. However, the effort needed to implement MPC in buildings is significant and often considered prohibitive. That is why until now fully-functional MPC has been...

  9. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    Science.gov (United States)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  10. Building Bridges between Neuroscience, Cognition and Education with Predictive Modeling

    Science.gov (United States)

    Stringer, Steve; Tommerdahl, Jodi

    2015-01-01

    As the field of Mind, Brain, and Education seeks new ways to credibly bridge the gap between neuroscience, the cognitive sciences, and education, various connections are being developed and tested. This article presents a framework and offers examples of one approach, predictive modeling within a virtual educational system that can include…

  11. Building Bridges between Neuroscience, Cognition and Education with Predictive Modeling

    Science.gov (United States)

    Stringer, Steve; Tommerdahl, Jodi

    2015-01-01

    As the field of Mind, Brain, and Education seeks new ways to credibly bridge the gap between neuroscience, the cognitive sciences, and education, various connections are being developed and tested. This article presents a framework and offers examples of one approach, predictive modeling within a virtual educational system that can include…

  12. Prediction model for sound transmission from machinery in buildings: feasible approaches and problems to be solved

    NARCIS (Netherlands)

    Gerretsen, E.

    2000-01-01

    Prediction models for the airborne and impact sound transmission in buildings have recently been established (EN 12354- 1&2:1999). However, these models do not cover technical installations and machinery as a source of sound in buildings. Yet these can cause unacceptable sound levels and it is

  13. Evaluation of the Predictive Accuracy of Five Whole Building Baseline Models

    Energy Technology Data Exchange (ETDEWEB)

    Granderson, Jessica [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Price, Phillip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2012-08-31

    This report documents the relative and absolute performance of five baseline models used to characterize whole­building energy consumption. The Pulse Adaptive Model1, multi-­parameter change-­point, mean-week, day-­time-emperature, and LBNL models were evaluated according to a number of statistical ‘goodness of fit’ metrics, to determine their accuracy in characterizing the energy consumption of a set of 29 buildings. The baseline training period, prediction horizon, and predicted energy quantity (daily, weekly, and monthly energy consumption) were varied, and model predictions were compared to interval meter data to determine the accuracy of each model. Three combinations of baseline training periods and prediction horizons were considered: 6 months of training to generate a 12-­month prediction; 9 months of training to generate a 7-month prediction; and 12 months of training to generate a 6- month prediction.

  14. Construction cost prediction model for conventional and sustainable college buildings in North America

    Directory of Open Access Journals (Sweden)

    Othman Subhi Alshamrani

    2017-03-01

    Full Text Available The literature lacks in initial cost prediction models for college buildings, especially comparing costs of sustainable and conventional buildings. A multi-regression model was developed for conceptual initial cost estimation of conventional and sustainable college buildings in North America. RS Means was used to estimate the national average of construction costs for 2014, which was subsequently utilized to develop the model. The model could predict the initial cost per square feet with two structure types made of steel and concrete. The other predictor variables were building area, number of floors and floor height. The model was developed in three major stages, such as preliminary diagnostics on data quality, model development and validation. The developed model was successfully tested and validated with real-time data.

  15. A mass transfer model for predicting emission of the volatile organic compounds in wet building materials

    Institute of Scientific and Technical Information of China (English)

    ZHANG Tao; JIA Li

    2008-01-01

    A new mass transfer model is developped to predict the volatile organic compounds (VOCs) from fresh wet building materials. The dry section of wet materials during the process of VOC emission from wet building materials is considered in this new model, differing from the mass transfer-based models in other literatures. The mechanism of effect of saturated vapor pressure on the surface of wet building materials in the process of VOC emission is discussed. The concentration of total volatile organic compounds (TVOC) in the building materials gradually decreases as the emission of VOCs begins, and the vapor pressure of VOCs on the surface of wet building materials decreases in the case of newly wet building materials. To ensure the partial pressure of VOCs on the surface of wet building materials to be saturated vapor pressure, the interface of gas-wet layer is lowered, and a dry layer of no-volatile gases in the material is formed. Compared with the results obtained by VB model, CFD model and the ex-periment data, the results obtained by the present model agree well with the results obtained by CFD model and the experiment data. The present model is more accurate in predicting emission of VOC from wet building materials than VB model.

  16. Using Models to Provide Predicted Ranges for Building-Human Interfaces: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Long, N.; Scheib, J.; Pless, S.; Schott, M.

    2013-09-01

    Most building energy consumption dashboards provide only a snapshot of building performance; whereas some provide more detailed historic data with which to compare current usage. This paper will discuss the Building Agent(tm) platform, which has been developed and deployed in a campus setting at the National Renewable Energy Laboratory as part of an effort to maintain the aggressive energyperformance achieved in newly constructed office buildings and laboratories. The Building Agent(tm) provides aggregated and coherent access to building data, including electric energy, thermal energy, temperatures, humidity, and lighting levels, and occupant feedback, which are displayed in various manners for visitors, building occupants, facility managers, and researchers. This paper focuseson the development of visualizations for facility managers, or an energy performance assurance role, where metered data are used to generate models that provide live predicted ranges of building performance by end use. These predicted ranges provide simple, visual context for displayed performance data without requiring users to also assess historical information or trends. Several energymodelling techniques were explored including static lookup-based performance targets, reduced-order models derived from historical data using main effect variables such as solar radiance for lighting performance, and integrated energy models using a whole-building energy simulation program.

  17. Economic Model Predictive Control for Hot Water Based Heating Systems in Smart Buildings

    DEFF Research Database (Denmark)

    Awadelrahman, M. A. Ahmed; Zong, Yi; Li, Hongwei

    2017-01-01

    This paper presents a study to optimize the heating energy costs in a residential building with varying electricity price signals based on an Economic Model Predictive Controller (EMPC). The investigated heating system consists of an air source heat pump (ASHP) incorporated with a hot water tank...... as active Thermal Energy Storage (TES), where two optimization problems are integrated together to optimize both the ASHP electricity consumption and the building heating consumption utilizing a heat dynamic model of the building. The results show that the proposed EMPC can save the energy cost by load...

  18. Using Data Mining Techniques to Build a Classification Model for Predicting Employees Performance

    Directory of Open Access Journals (Sweden)

    Qasem A. Al-Radaideh

    2012-02-01

    Full Text Available Human capital is of a high concern for companies’ management where their most interest is in hiring the highly qualified personnel which are expected to perform highly as well. Recently, there has been a growing interest in the data mining area, where the objective is the discovery of knowledge that is correct and of high benefit for users. In this paper, data mining techniques were utilized to build a classification model to predict the performance of employees. To build the classification model the CRISP-DM data mining methodology was adopted. Decision tree was the main data mining tool used to build the classification model, where several classification rules were generated. To validate the generated model, several experiments were conducted using real data collected from several companies. The model is intended to be used for predicting new applicants’ performance.

  19. USE OF ROUGH SETS AND SPECTRAL DATA FOR BUILDING PREDICTIVE MODELS OF REACTION RATE CONSTANTS

    Science.gov (United States)

    A model for predicting the log of the rate constants for alkaline hydrolysis of organic esters has been developed with the use of gas-phase min-infrared library spectra and a rule-building software system based on the mathematical theory of rough sets. A diverse set of 41 esters ...

  20. Summary of best guidelines and validation of CFD modeling in livestock buildings to ensure prediction quality

    DEFF Research Database (Denmark)

    Rong, Li; Nielsen, Peter V.; Bjerg, Bjarne

    2016-01-01

    scale pig barns was simulated to show the procedures of validating a CFD simulation in livestock buildings. After summarizing the guideline and/or best practice for CFD modeling, the authors addressed the issues related to numerical methods and the governing equations, which were limited to RANS models....... Although it is not necessary to maintain the same format of reporting the CFD modeling as presented in this paper, the authors would suggest including all the information related to the selection of turbulence models, difference schemes, convergence criteria, boundary conditions, geometry simplification......Computational Fluid Dynamics (CFD) is increasingly used to study airflow around and in livestock buildings, to develop technologies to mitigate emissions and to predict the contaminant dispersion from livestock buildings. In this paper, an example of air flow distribution in a room with two full...

  1. A Comparison of Energy Consumption Prediction Models Based on Neural Networks of a Bioclimatic Building

    Directory of Open Access Journals (Sweden)

    Hamid R. Khosravani

    2016-01-01

    Full Text Available Energy consumption has been increasing steadily due to globalization and industrialization. Studies have shown that buildings are responsible for the biggest proportion of energy consumption; for example in European Union countries, energy consumption in buildings represents around 40% of the total energy consumption. In order to control energy consumption in buildings, different policies have been proposed, from utilizing bioclimatic architectures to the use of predictive models within control approaches. There are mainly three groups of predictive models including engineering, statistical and artificial intelligence models. Nowadays, artificial intelligence models such as neural networks and support vector machines have also been proposed because of their high potential capabilities of performing accurate nonlinear mappings between inputs and outputs in real environments which are not free of noise. The main objective of this paper is to compare a neural network model which was designed utilizing statistical and analytical methods, with a group of neural network models designed benefiting from a multi objective genetic algorithm. Moreover, the neural network models were compared to a naïve autoregressive baseline model. The models are intended to predict electric power demand at the Solar Energy Research Center (Centro de Investigación en Energía SOLar or CIESOL in Spanish bioclimatic building located at the University of Almeria, Spain. Experimental results show that the models obtained from the multi objective genetic algorithm (MOGA perform comparably to the model obtained through a statistical and analytical approach, but they use only 0.8% of data samples and have lower model complexity.

  2. Indoor environmental quality (IEQ) and building energy optimization through model predictive control (MPC)

    Science.gov (United States)

    Woldekidan, Korbaga

    This dissertation aims at developing a novel and systematic approach to apply Model Predictive Control (MPC) to improve energy efficiency and indoor environmental quality in office buildings. Model predictive control is one of the advanced optimal control approaches that use models to predict the behavior of the process beyond the current time to optimize the system operation at the present time. In building system, MPC helps to exploit buildings' thermal storage capacity and to use the information on future disturbances like weather and internal heat gains to estimate optimal control inputs ahead of time. In this research the major challenges of applying MPC to building systems are addressed. A systematic framework has been developed for ease of implementation. New methods are proposed to develop simple and yet reasonably accurate models that can minimize the MPC development effort as well as computational time. The developed MPC is used to control a detailed building model represented by whole building performance simulation tool, EnergyPlus. A co-simulation strategy is used to communicate the MPC control developed in Matlab platform with the case building model in EnergyPlus. The co-simulation tool used (MLE+) also has the ability to talk to actual building management systems that support the BACnet communication protocol which makes it easy to implement the developed MPC control in actual buildings. A building that features an integrated lighting and window control and HVAC system with a dedicated outdoor air system and ceiling radiant panels was used as a case building. Though this study is specifically focused on the case building, the framework developed can be applied to any building type. The performance of the developed MPC was compared against a baseline control strategy using Proportional Integral and Derivative (PID) control. Various conventional and advanced thermal comfort as well as ventilation strategies were considered for the comparison. These

  3. Predictor characteristics necessary for building a clinically useful risk prediction model: a simulation study

    Directory of Open Access Journals (Sweden)

    Laura Schummers

    2016-09-01

    Full Text Available Abstract Background Compelled by the intuitive appeal of predicting each individual patient’s risk of an outcome, there is a growing interest in risk prediction models. While the statistical methods used to build prediction models are increasingly well understood, the literature offers little insight to researchers seeking to gauge a priori whether a prediction model is likely to perform well for their particular research question. The objective of this study was to inform the development of new risk prediction models by evaluating model performance under a wide range of predictor characteristics. Methods Data from all births to overweight or obese women in British Columbia, Canada from 2004 to 2012 (n = 75,225 were used to build a risk prediction model for preeclampsia. The data were then augmented with simulated predictors of the outcome with pre-set prevalence values and univariable odds ratios. We built 120 risk prediction models that included known demographic and clinical predictors, and one, three, or five of the simulated variables. Finally, we evaluated standard model performance criteria (discrimination, risk stratification capacity, calibration, and Nagelkerke’s r2 for each model. Results Findings from our models built with simulated predictors demonstrated the predictor characteristics required for a risk prediction model to adequately discriminate cases from non-cases and to adequately classify patients into clinically distinct risk groups. Several predictor characteristics can yield well performing risk prediction models; however, these characteristics are not typical of predictor-outcome relationships in many population-based or clinical data sets. Novel predictors must be both strongly associated with the outcome and prevalent in the population to be useful for clinical prediction modeling (e.g., one predictor with prevalence ≥20 % and odds ratio ≥8, or 3 predictors with prevalence ≥10 % and odds ratios ≥4. Area

  4. Economic Model Predictive Control for Building Climate Control in a Smart Grid

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2012-01-01

    Model Predictive Control (MPC) can be used to control a system of energy producers and consumers in a Smart Grid. In this paper, we use heat pumps for heating residential buildings with a floor heating system. We use the thermal capacity of the building to shift the electricity consumptions...... to periods with low energy prices. In this way the heating system of the house becomes a flexible power consumer in the Smart Grid. This scenario is relevant for systems with a significant share of stochastic energy producers, e.g. wind turbines, where the ability to shift power consumption according...... to production is crucial. We present a model for a house with a heat pump used for supplying thermal energy to a floor heating system. The model is a linear state space model and the resulting controller is an Economic MPC formulated as a linear program. The model includes forecasts of both weather...

  5. A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control

    DEFF Research Database (Denmark)

    Arendt, Krzysztof; Ionesi, Ana; Jradi, Muhyiddine

    2016-01-01

    implemented only in few buildings. The following difficulties hinder the widespread usage of MPC: (1) significant model development time, (2) limited portability of models, (3) model computational demand. In the present study a new model development framework for an MPC system based on a Genetic Algorithm (GA...

  6. Vibrations inside buildings due to subway railway traffic. Experimental validation of a comprehensive prediction model.

    Science.gov (United States)

    Lopes, Patrícia; Ruiz, Jésus Fernández; Alves Costa, Pedro; Medina Rodríguez, L; Cardoso, António Silva

    2016-10-15

    The present paper focuses on the experimental validation of a numerical approach previously proposed by the authors for the prediction of vibrations inside buildings due to railway traffic in tunnels. The numerical model is based on the concept of dynamic substructuring and is composed by three autonomous models to simulate the following main parts of the problem: i) generation of vibrations (train-track interaction); ii) propagation of vibrations (track-tunnel-ground system); iii) reception of vibrations (building coupled to the ground). The experimental validation consists in the comparison between the results predicted by the proposed numerical model and the measurements performed inside a building due to the railway traffic in a shallow tunnel located in Madrid. Apart from the brief description of the numerical model and of the case study, the main options and simplifications adopted on the numerical modeling strategy are discussed. The balance adopted between accuracy and simplicity of the numerical approach proved to be a path to follow in order to transfer knowledge to engineering practice. Finally, the comparison between numerical and experimental results allowed finding a good agreement between both, fact that ensures the ability of the proposed modeling strategy to deal with real engineering practical problems. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Analytical Model of Underground Train Induced Vibrations on Nearby Building Structures in Cameroon: Assessment and Prediction

    Directory of Open Access Journals (Sweden)

    Lezin Seba MINSILI

    2013-11-01

    Full Text Available The purpose of this research paper was to assess and predict the effect of vibrations induced by an underground railway on nearby-existing buildings prior to the construction of projected new railway lines of the National Railway Master Plan of Cameroon and after upgrading of the railway conceded to CAMRAIL linking the two most densely populated cities of Cameroon: Douala and Yaoundé. With the source-transmitter-receiver mathematical model as the train-soil-structure interaction model, taking into account sub-model parameters such as type of the train-railway system, typical geotechnical conditions of the ground and the sensitivity of the nearby buildings, the analysis is carried out over the entire system using the dynamic finite element method in the time domain. This subdivision of the model is a powerful tool that allows to consider different alternatives of sub-models with different characteristics, and thus to determine any critical excessive vibration impact. Based on semi-empirical analytical results obtained from presented models, the present work assesses and predicts characteristics of traffic-induced vibrations as a function of time duration, intensity and vehicle speed, as well as their influence on buildings at different levels.

  8. Comparative analysis of modified PMV models and SET models to predict human thermal sensation in naturally ventilated buildings

    DEFF Research Database (Denmark)

    Gao, Jie; Wang, Yi; Wargocki, Pawel

    2015-01-01

    In this paper, a comparative analysis was performed on the human thermal sensation estimated by modified predicted mean vote (PMV) models and modified standard effective temperature (SET) models in naturally ventilated buildings; the data were collected in field study. These prediction models were...... between the measured and predicted values using the modified PMV models exceeded 25%, while the difference between the measured thermal sensation and the predicted thermal sensation using modified SET models was approximately less than 25%. It is concluded that the modified SET models can predict human...... developed on the basis of the original PMV/SET models and consider the influence of occupants' expectations and human adaptive functions, including the extended PMV/SET models and the adaptive PMV/SET models. The results showed that when the indoor air velocity ranged from 0 to 0.2m/s and from 0.2 to 0.8m...

  9. Model Based Predictive Control of Thermal Comfort for Integrated Building System

    Science.gov (United States)

    Georgiev, Tz.; Jonkov, T.; Yonchev, E.; Tsankov, D.

    2011-12-01

    This article deals with the indoor thermal control problem in HVAC (heating, ventilation and air conditioning) systems. Important outdoor and indoor variables in these systems are: air temperature, global and diffuse radiations, wind speed and direction, temperature, relative humidity, mean radiant temperature, and so on. The aim of this article is to obtain the thermal comfort optimisation by model based predictive control algorithms (MBPC) of an integrated building system. The control law is given by a quadratic programming problem and the obtained control action is applied to the process. The derived models and model based predictive control algorithms are investigated based on real—live data. All researches are derived in MATLAB environment. The further research will focus on synthesis of robust energy saving control algorithms.

  10. Practical approach to determine sample size for building logistic prediction models using high-throughput data.

    Science.gov (United States)

    Son, Dae-Soon; Lee, DongHyuk; Lee, Kyusang; Jung, Sin-Ho; Ahn, Taejin; Lee, Eunjin; Sohn, Insuk; Chung, Jongsuk; Park, Woongyang; Huh, Nam; Lee, Jae Won

    2015-02-01

    An empirical method of sample size determination for building prediction models was proposed recently. Permutation method which is used in this procedure is a commonly used method to address the problem of overfitting during cross-validation while evaluating the performance of prediction models constructed from microarray data. But major drawback of such methods which include bootstrapping and full permutations is prohibitively high cost of computation required for calculating the sample size. In this paper, we propose that a single representative null distribution can be used instead of a full permutation by using both simulated and real data sets. During simulation, we have used a dataset with zero effect size and confirmed that the empirical type I error approaches to 0.05. Hence this method can be confidently applied to reduce overfitting problem during cross-validation. We have observed that pilot data set generated by random sampling from real data could be successfully used for sample size determination. We present our results using an experiment that was repeated for 300 times while producing results comparable to that of full permutation method. Since we eliminate full permutation, sample size estimation time is not a function of pilot data size. In our experiment we have observed that this process takes around 30min. With the increasing number of clinical studies, developing efficient sample size determination methods for building prediction models is critical. But empirical methods using bootstrap and permutation usually involve high computing costs. In this study, we propose a method that can reduce required computing time drastically by using representative null distribution of permutations. We use data from pilot experiments to apply this method for designing clinical studies efficiently for high throughput data.

  11. Simplified prediction model for lighting energy consumption in office building scheme design

    Institute of Scientific and Technical Information of China (English)

    余琼; 周潇儒; 林波荣; 朱颖心

    2009-01-01

    At the scheme design stage,the potential of daylighting is significant due to the saving for electric lighting use. There are few simple tools for architects to optimize the daylighting design. Therefore,it is useful to develop a design guideline related to the evaluation of lighting energy saving potential and sunlight design strategies. This paper analyzes the impacts of different artificial lighting control methods and design parameters on daylighting. A direct correlation between lighting energy consumption and parameters such as orientations,window to wall ratio (WWR) and perimeter depth is established. A simplified prediction model is proposed to estimate lighting energy consumption with the given perimeter depth,WWR,and window transparency. Validation of the model is carried out compared with detailed lighting simulation software for an office building. After the variation analysis for these parameters,design advises for the daylighting design at scheme design phase are summarized.

  12. Tensile Property Analysis and Prediction Model Building for Coir Rope Reinforced Unsaturated Polyester Composite

    Directory of Open Access Journals (Sweden)

    Jia Yao

    2014-12-01

    Full Text Available Because of the light weight and environmental advantages of natural fibers, an increasing amount of natural fibers have been used to replace synthetic fibers in reinforced unsaturated polyester (UPE. Because of the impact property advantage of coir fibers, coir toughened UPE composites can achieve excellent impacting toughness, but at the cost of a lower tensile performance. In order to get the better comprehensive performance, the tensile strength must be maintained in a higher level, so coir ropes as an appropriate reinforced form were added to UPE matrix. The different weight-percent contents for the coir rope addition were set to achieve coir rope reinforced UPE composites with different coir contents. The tensile test results showed increasing tensile strength with the increased content of coir ropes. To reasonably and accurately predict the composite performance, taking the original performance prediction model based on a continuous reinforced fiber composite (using the Classical Mixed Law as a reference and assuming each coir rope was ideally continuous fiber, the destructive principle of coir rope reinforced UPE composite under the action of tensile load was analyzed and the tensile failure mechanics model was improved. According to the experimental proof, the new model can be proven to have higher precision accuracy, which can provide new train of thought for the building of the theoretical models for natural fiber reinforced composites, thus guiding the actual production application.

  13. Model Predictive Controller for Active Demand Side Management with PV Self-consumption in an Intelligent Building

    DEFF Research Database (Denmark)

    Zong, Yi; Mihet-Popa, Lucian; Kullmann, Daniel

    2012-01-01

    This paper presents a Model Predictive Controller (MPC) for electrical heaters’ predictive power consumption including maximizing the use of local generation (e.g. solar power) in an intelligent building. The MPC is based on dynamic power price and weather forecast, considering users’ comfort...

  14. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    Science.gov (United States)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  15. Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings

    Directory of Open Access Journals (Sweden)

    Avril Challoner

    2015-12-01

    Full Text Available NO2 and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person’s well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM, to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO2 indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO2 exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts.

  16. Influence of precision of emission characteristic parameters on model prediction error of VOCs/formaldehyde from dry building material.

    Directory of Open Access Journals (Sweden)

    Wenjuan Wei

    Full Text Available Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0, the diffusion coefficient (D, and the partition coefficient (K, can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.

  17. Influence of precision of emission characteristic parameters on model prediction error of VOCs/formaldehyde from dry building material.

    Science.gov (United States)

    Wei, Wenjuan; Xiong, Jianyin; Zhang, Yinping

    2013-01-01

    Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs) and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0), the diffusion coefficient (D), and the partition coefficient (K), can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.

  18. Development and application of a statistical methodology to evaluate the predictive accuracy of building energy baseline models

    Energy Technology Data Exchange (ETDEWEB)

    Granderson, Jessica [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Energy Technologies Area Div.; Price, Phillip N. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Energy Technologies Area Div.

    2014-03-01

    This paper documents the development and application of a general statistical methodology to assess the accuracy of baseline energy models, focusing on its application to Measurement and Verification (M&V) of whole-­building energy savings. The methodology complements the principles addressed in resources such as ASHRAE Guideline 14 and the International Performance Measurement and Verification Protocol. It requires fitting a baseline model to data from a ``training period’’ and using the model to predict total electricity consumption during a subsequent ``prediction period.’’ We illustrate the methodology by evaluating five baseline models using data from 29 buildings. The training period and prediction period were varied, and model predictions of daily, weekly, and monthly energy consumption were compared to meter data to determine model accuracy. Several metrics were used to characterize the accuracy of the predictions, and in some cases the best-­performing model as judged by one metric was not the best performer when judged by another metric.

  19. Predicting the microbial exposure risks in urban floods using GIS, building simulation, and microbial models.

    Science.gov (United States)

    Taylor, Jonathon; Biddulph, Phillip; Davies, Michael; Lai, Ka man

    2013-01-01

    London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. Damp and flooded dwellings can support microbial growth, including mould, bacteria, and protozoa, as well as persistence of flood-borne microorganisms. The amount of time flooded dwellings remain damp will depend on the duration and height of the flood, the contents of the flood water, the drying conditions, and the building construction, leading to particular properties and property types being prone to lingering damp and human pathogen growth or persistence. The impact of flooding on buildings can be simulated using Heat Air and Moisture (HAM) models of varying complexity in order to understand how water can be absorbed and dry out of the building structure. This paper describes the simulation of the drying of building archetypes representative of the English building stock using the EnergyPlus based tool 'UCL-HAMT' in order to determine the drying rates of different abandoned structures flooded to different heights and during different seasons. The results are mapped out using GIS in order to estimate the spatial risk across London in terms of comparative flood vulnerability, as well as for specific flood events. Areas of South and East London were found to be particularly vulnerable to long-term microbial exposure following major flood events.

  20. Predicted and actual indoor environmental quality: Verification of occupants' behaviour models in residential buildings

    DEFF Research Database (Denmark)

    Andersen, Rune Korsholm; Fabi, Valentina; Corgnati, Stefano P.

    2016-01-01

    performance using building energy performance simulations (BEPS). However, the validity of these models has only been sparsely tested. In this paper, stochastic models of occupants' behaviour from literature were tested against measurements in five apartments. In a monitoring campaign, measurements of indoor...... station close by. The stochastic models of window opening and heating set-point adjustments were implemented in the BEPS tool IDA ICE. Two apartments from the monitoring campaign were simulated using the implemented models and the measured weather data. The results were compared to measurements from...

  1. Building a Tax Predictive Model Based on the Cloud Neural Network

    Institute of Scientific and Technical Information of China (English)

    田永青; 李志; 朱仲英

    2003-01-01

    Tax is very important to the whole country, so a scientific tax predictive model is needed. This paper introduces the theory of the cloud model. On this basis, it presents a cloud neural network, and analyzes the main factors which influence the tax revenue. Then if proposes a tax predictive model based on the cloud neural network. The model combines the strongpoints of the cloud model and the neural network. The experiment and simulation results show the effectiveness of the algorithm in this paper.

  2. A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control

    DEFF Research Database (Denmark)

    Arendt, Krzysztof; Ionesi, Ana; Jradi, Muhyiddine

    2016-01-01

    Mock-Up Interface, which is used to link the models with the MPC system. The framework was used to develop and run initial thermal and CO2 models. Their performance and the implementation procedure are discussed in the present paper. The framework is going to be implemented in the MPC system planned...

  3. Building Models and Building Modelling

    DEFF Research Database (Denmark)

    Jørgensen, Kaj Asbjørn; Skauge, Jørn

    I rapportens indledende kapitel beskrives de primære begreber vedrørende bygningsmodeller og nogle fundamentale forhold vedrørende computerbaseret modulering bliver opstillet. Desuden bliver forskellen mellem tegneprogrammer og bygnings­model­lerings­programmer beskrevet. Vigtige aspekter om......­lering og bygningsmodeller. Det bliver understreget at modellering bør udføres på flere abstraktions­niveauer og i to dimensioner i den såkaldte modelleringsmatrix. Ud fra dette identificeres de primære faser af bygningsmodel­lering. Dernæst beskrives de basale karakteristika for bygningsmodeller. Heri...... inkluderes en præcisering af begreberne objektorienteret software og objektorienteret modeller. Det bliver fremhævet at begrebet objektbaseret modellering giver en tilstrækkelig og bedre forståelse. Endelig beskrives forestillingen om den ideale bygningsmodel som værende én samlet model, der anvendes gennem...

  4. Green building performance prediction/assessment

    Energy Technology Data Exchange (ETDEWEB)

    Papamichael, Konstantinos

    2000-02-01

    To make decisions, building designers need to predict and assess the performance of their ideas with respect to various criteria, such as comfort, esthetics, energy, environmental impact, economics, etc. Performance prediction with respect to environmental impact requires complicated models and massive computations, which are usually possible only through computer-based tools. This paper focuses on the use of computer-based tools for predicting and assessing building performance with respect to environmental impact criteria for the design of green buildings. It contains analyses of green performance prediction/assessment and descriptions of available tools, along with discussions on their use by different types of users. Finally, it includes analyses of the cost and benefits of green performance prediction and assessment.

  5. Building Models and Building Modelling

    DEFF Research Database (Denmark)

    Jørgensen, Kaj; Skauge, Jørn

    2008-01-01

    I rapportens indledende kapitel beskrives de primære begreber vedrørende bygningsmodeller og nogle fundamentale forhold vedrørende computerbaseret modulering bliver opstillet. Desuden bliver forskellen mellem tegneprogrammer og bygnings­model­lerings­programmer beskrevet. Vigtige aspekter om comp...

  6. Building factorial regression models to explain and predict nitrate concentrations in groundwater under agricultural land

    Science.gov (United States)

    Stigter, T. Y.; Ribeiro, L.; Dill, A. M. M. Carvalho

    2008-07-01

    SummaryFactorial regression models, based on correspondence analysis, are built to explain the high nitrate concentrations in groundwater beneath an agricultural area in the south of Portugal, exceeding 300 mg/l, as a function of chemical variables, electrical conductivity (EC), land use and hydrogeological setting. Two important advantages of the proposed methodology are that qualitative parameters can be involved in the regression analysis and that multicollinearity is avoided. Regression is performed on eigenvectors extracted from the data similarity matrix, the first of which clearly reveals the impact of agricultural practices and hydrogeological setting on the groundwater chemistry of the study area. Significant correlation exists between response variable NO3- and explanatory variables Ca 2+, Cl -, SO42-, depth to water, aquifer media and land use. Substituting Cl - by the EC results in the most accurate regression model for nitrate, when disregarding the four largest outliers (model A). When built solely on land use and hydrogeological setting, the regression model (model B) is less accurate but more interesting from a practical viewpoint, as it is based on easily obtainable data and can be used to predict nitrate concentrations in groundwater in other areas with similar conditions. This is particularly useful for conservative contaminants, where risk and vulnerability assessment methods, based on assumed rather than established correlations, generally produce erroneous results. Another purpose of the models can be to predict the future evolution of nitrate concentrations under influence of changes in land use or fertilization practices, which occur in compliance with policies such as the Nitrates Directive. Model B predicts a 40% decrease in nitrate concentrations in groundwater of the study area, when horticulture is replaced by other land use with much lower fertilization and irrigation rates.

  7. Demand response-enabled model predictive HVAC load control in buildings using real-time electricity pricing

    Science.gov (United States)

    Avci, Mesut

    A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy is built based on a proposed model that jointly minimizes the total energy consumption and hence, cost of electricity for the user, and the deviation of the inside temperature from the consumer's preference. An algorithm that assigns temperature set-points (reference temperatures) to price ranges based on the consumer's discomfort tolerance index is developed. A practical parameter prediction model is also designed for mapping between the HVAC load and the inside temperature. The prediction model and the produced temperature set-points are integrated as inputs into the MPC controller, which is then used to generate signal actions for the AC unit. To investigate and demonstrate the effectiveness of the proposed approach, a simulation based experimental analysis is presented using real-life pricing data. An actual prototype for the proposed HVAC load control strategy is then built and a series of prototype experiments are conducted similar to the simulation studies. The experiments reveal that the MPC strategy can lead to significant reductions in overall energy consumption and cost savings for the consumer. Results suggest that by providing an efficient response strategy for the consumers, the proposed MPC strategy can enable the utility providers to adopt efficient demand management policies using real-time pricing. Finally, a cost-benefit analysis is performed to display the economic feasibility of implementing such a controller as part of a building energy management system, and the payback period is identified considering cost of prototype build and cost savings to help the adoption of this controller in the building HVAC control industry.

  8. Thermal comfort in residential buildings - Failure to predict by Standard model

    Energy Technology Data Exchange (ETDEWEB)

    Becker, R. [Faculty of Civil and Environmental Engineering, Technion - Israel Institute of Technology, Rabin Building, Technion City, Haifa 32000 (Israel); Paciuk, M. [National Building Research Institute, Technion - IIT, Haifa 32000 (Israel)

    2009-05-15

    A field study, conducted in 189 dwellings in winter and 205 dwellings in summer, included measurement of hygro-thermal conditions and documentation of occupant responses and behavior patterns. Both samples included both passive and actively space-conditioned dwellings. Predicted mean votes (PMV) computed using Fanger's model yielded significantly lower-than-reported thermal sensation (TS) values, especially for the winter heated and summer air-conditioned groups. The basic model assumption of a proportional relationship between thermal response and thermal load proved to be inadequate, with actual thermal comfort achieved at substantially lower loads than predicted. Survey results also refuted the model's second assumption that symmetrical responses in the negative and positive directions of the scale represent similar comfort levels. Results showed that the model's curve of predicted percentage of dissatisfied (PPD) substantially overestimated the actual percentage of dissatisfied within the partial group of respondents who voted TS > 0 in winter as well as within the partial group of respondents who voted TS < 0 in summer. Analyses of sensitivity to possible survey-related inaccuracy factors (metabolic rate, clothing thermal resistance) did not explain the systematic discrepancies. These discrepancies highlight the role of contextual variables (local climate, expectations, available control) in thermal adaptation in actual settings. Collected data was analyzed statistically to establish baseline data for local standardized thermal and energy calculations. A 90% satisfaction criterion yielded 19.5 C and 26 C as limit values for passive winter and summer design conditions, respectively, while during active conditioning periods, set-point temperatures of 21.5 C and 23 C should be assumed for winter and summer, respectively. (author)

  9. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-21

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  10. User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-03

    This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

  11. A Comparison of Two Strategies for Building an Exposure Prediction Model.

    Science.gov (United States)

    Heiden, Marina; Mathiassen, Svend Erik; Garza, Jennifer; Liv, Per; Wahlström, Jens

    2016-01-01

    Cost-efficient assessments of job exposures in large populations may be obtained from models in which 'true' exposures assessed by expensive measurement methods are estimated from easily accessible and cheap predictors. Typically, the models are built on the basis of a validation study comprising 'true' exposure data as well as an extensive collection of candidate predictors from questionnaires or company data, which cannot all be included in the models due to restrictions in the degrees of freedom available for modeling. In these situations, predictors need to be selected using procedures that can identify the best possible subset of predictors among the candidates. The present study compares two strategies for selecting a set of predictor variables. One strategy relies on stepwise hypothesis testing of associations between predictors and exposure, while the other uses cluster analysis to reduce the number of predictors without relying on empirical information about the measured exposure. Both strategies were applied to the same dataset on biomechanical exposure and candidate predictors among computer users, and they were compared in terms of identified predictors of exposure as well as the resulting model fit using bootstrapped resamples of the original data. The identified predictors were, to a large part, different between the two strategies, and the initial model fit was better for the stepwise testing strategy than for the clustering approach. Internal validation of the models using bootstrap resampling with fixed predictors revealed an equally reduced model fit in resampled datasets for both strategies. However, when predictor selection was incorporated in the validation procedure for the stepwise testing strategy, the model fit was reduced to the extent that both strategies showed similar model fit. Thus, the two strategies would both be expected to perform poorly with respect to predicting biomechanical exposure in other samples of computer users.

  12. Active load management in an intelligent building using model predictive control strategy

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2011-01-01

    This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load...... shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power...

  13. Challenges of implementing economic model predictive control strategy for buildings interacting with smart energy systems

    DEFF Research Database (Denmark)

    Zong, Yi; Böning, Georg Martin; Santos, Rui Mirra

    2016-01-01

    ) strategy for energy management in smart buildings, which can act as active users interacting with smart energy systems. The challenges encountered during the implementation of EMPC for active demand side management are investigated in detail in this paper. A pilot testing study shows energy savings...

  14. Predicting night-time natural ventilation in Stanford's Y2E2 building using an integral model in combination with a CFD model

    Science.gov (United States)

    Lamberti, Giacomo; Gorle', Catherine

    2016-11-01

    Natural ventilation can significantly reduce energy consumption in buildings, but the presence of uncertainty makes robust design a challenging task. We will discuss the prediction of the natural ventilation performance during a 4 hour night-flush in Stanford's Y2E2 building using a combination of two models with different levels of fidelity: an integral model that solves for the average air and thermal mass temperature and a CFD model, used to calculate discharge and heat transfer coefficients to update the integral model. Uncertainties are propagated using polynomial chaos expansion to compute the mean and 95% confidence intervals of the quantities of interest. Comparison with building measurements shows that, despite a slightly to fast cooling rate, the measured air temperature is inside the 95% confidence interval predicted by the integral model. The use of information from the CFD model in the integral model reduces the maximum standard deviation of the volume-averaged air temperature by 20% when compared to using literature-based estimates for these quantities. The heat transfer coefficient resulting from the CFD model was found to be within the literature-based interval initially assumed for the integral model, but the discharge coefficients were found to be different.

  15. Building a Predictive Model of Galaxy Formation - I: Phenomenological Model Constrained to the $z=0$ Stellar Mass Function

    CERN Document Server

    Benson, A J

    2014-01-01

    We constrain a highly simplified semi-analytic model of galaxy formation using the $z\\approx 0$ stellar mass function of galaxies. Particular attention is paid to assessing the role of random and systematic errors in the determination of stellar masses, to systematic uncertainties in the model, and to correlations between bins in the measured and modeled stellar mass functions, in order to construct a realistic likelihood function. We derive constraints on model parameters and explore which aspects of the observational data constrain particular parameter combinations. We find that our model, once constrained, provides a remarkable match to the measured evolution of the stellar mass function to $z=1$, although fails dramatically to match the local galaxy HI mass function. Several "nuisance parameters" contribute significantly to uncertainties in model predictions. In particular, systematic errors in stellar mass estimate are the dominant source of uncertainty in model predictions at $z\\approx 1$, with addition...

  16. The potential of large studies for building genetic risk prediction models

    Science.gov (United States)

    NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

  17. Comparing artificial neural networks, general linear models and support vector machines in building predictive models for small interfering RNAs.

    Directory of Open Access Journals (Sweden)

    Kyle A McQuisten

    Full Text Available BACKGROUND: Exogenous short interfering RNAs (siRNAs induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models. PRINCIPAL FINDINGS: Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs, General Linear Models (GLMs and Support Vector Machines (SVMs. Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation. CONCLUSIONS: The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features

  18. Economic Model Predictive Control for Building Climate Control in a Smart Grid

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2012-01-01

    to production is crucial. We present a model for a house with a heat pump used for supplying thermal energy to a floor heating system. The model is a linear state space model and the resulting controller is an Economic MPC formulated as a linear program. The model includes forecasts of both weather...

  19. Building information modelling (BIM)

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2009-02-01

    Full Text Available The concept of a Building Information Model (BIM) also known as a Building Product Model (BPM) is nothing new. A short article on BIM will never cover the entire filed, because it is a particularly complex filed that is recently beginning to receive...

  20. Bankruptcy prediction: The influence of the year prior to failure selected for model building and the effects in a period of economic decline

    NARCIS (Netherlands)

    Pompe, P.P.M.; Bilderbeek, J.

    2005-01-01

    Using large amounts of data from small and medium-sized industrial firms, this study examines two aspects of bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline. The results show that especially models

  1. Bankruptcy prediction: The influence of the year prior to failure selected for model building and the effects in a period of economic decline

    NARCIS (Netherlands)

    Pompe, P.P.M.; Bilderbeek, J.

    2005-01-01

    Using large amounts of data from small and medium-sized industrial firms, this study examines two aspects of bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline. The results show that especially models generate

  2. Automated model building

    CERN Document Server

    Caferra, Ricardo; Peltier, Nicholas

    2004-01-01

    This is the first book on automated model building, a discipline of automated deduction that is of growing importance Although models and their construction are important per se, automated model building has appeared as a natural enrichment of automated deduction, especially in the attempt to capture the human way of reasoning The book provides an historical overview of the field of automated deduction, and presents the foundations of different existing approaches to model construction, in particular those developed by the authors Finite and infinite model building techniques are presented The main emphasis is on calculi-based methods, and relevant practical results are provided The book is of interest to researchers and graduate students in computer science, computational logic and artificial intelligence It can also be used as a textbook in advanced undergraduate courses

  3. What should be considered if you decide to build your mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature.

    Directory of Open Access Journals (Sweden)

    Maria eArepeva

    2015-04-01

    Full Text Available Acquired bacterial resistance is one of the causes of mortality and morbidity from infectious diseases. Mathematical modeling allows us to predict the spread of resistance and to some extent to control its dynamics. The purpose of this review was to examine existing mathematical models in order to understand pros and cons of currently used approaches and to build our own model. During the analysis, seven articles about the mathematical approaches to studying resistance that satisfied the inclusion / exclusion criteria were selected. All models were classified according to the approach used to study resistance in the presence of antibiotic and were analyzed in terms of our research. Some models require modifications associated with the specific of the research. Further work plan of model building is as follows: modify some models, according to our research, check all obtained models on our data, and select the optimal model or several models with the best quality of prediction. After that we would be able to build a model for the development of resistance using the obtained results.

  4. Building a Better Applicant Pool--A Case Study of the Use of Predictive Modeling and Market Segmentation to Build and Enroll Better Pools of Students

    Science.gov (United States)

    Herridge, Bart; Heil, Robert

    2003-01-01

    Predictive modeling has been a popular topic in higher education for the last few years. This case study shows an example of an effective use of modeling combined with market segmentation to strategically divide large, unmanageable prospect and inquiry pools and convert them into applicants, and eventually, enrolled students. (Contains 6 tables.)

  5. Building a Better Applicant Pool--A Case Study of the Use of Predictive Modeling and Market Segmentation to Build and Enroll Better Pools of Students

    Science.gov (United States)

    Herridge, Bart; Heil, Robert

    2003-01-01

    Predictive modeling has been a popular topic in higher education for the last few years. This case study shows an example of an effective use of modeling combined with market segmentation to strategically divide large, unmanageable prospect and inquiry pools and convert them into applicants, and eventually, enrolled students. (Contains 6 tables.)

  6. Influence of Three Dynamic Predictive Clothing Insulation Models on Building Energy Use, HVAC Sizing and Thermal Comfort

    Directory of Open Access Journals (Sweden)

    Kwang Ho Lee

    2014-03-01

    Full Text Available In building energy simulation, indoor thermal comfort condition, energy use and equipment size are typically calculated based on the assumption that the clothing insulation is equal to a constant value of 0.5 clo during the cooling season and 1.0 clo during the heating season. The assumption is not reflected in practice and thus it may lead to errors. In reality, occupants frequently adjust their clothing depending on the thermal conditions, as opposed to the assumption of constant clothing values above, indicating that the clothing insulation variation should be captured in building simulation software to obtain more reliable and accurate results. In this study, the impact of three newly developed dynamic clothing insulation models on the building simulation is quantitatively assessed using the detailed whole-building energy simulation program, EnergyPlus version 6.0. The results showed that when the heating ventilation and air conditioning system (HVAC is controlled based on indoor temperature the dynamic clothing models do not affect indoor operative temperatures, energy consumption and equipment sizing. When the HVAC is controlled based on the PMV model the use of a fixed clothing insulation during the cooling (0.5 clo and heating (1.0 clo season leads to the incorrect estimation of the indoor operative temperatures, energy consumption and equipment sizing. The dynamic clothing models significantly (p < 0.0001 improve the ability of energy simulation tools to assess thermal comfort. The authors recommend that the dynamic clothing models should be implemented in dynamic building energy simulation software such as EnergyPlus.

  7. Building a Model Astrolabe

    CERN Document Server

    Ford, Dominic

    2012-01-01

    This paper presents a hands-on introduction to the medieval astrolabe, based around a working model which can be constructed from photocopies of the supplied figures. As well as describing how to assemble the model, I also provide a brief explanation of how each of its various parts might be used. The printed version of this paper includes only the parts needed to build a single model prepared for use at latitudes around 52{\\deg}N, but an accompanying electronic file archive includes equivalent images which can be used to build models prepared for use at any other latitude. The vector graphics scripts used to generate the models are also available for download, allowing customised astrolabes to be made.

  8. 基于PSO-RBF的建筑能耗预测模型研究%Prediction Model of Building Energy Consumption Based on PSO-RBF

    Institute of Scientific and Technical Information of China (English)

    季文娟; 顾永松

    2015-01-01

    Themodelofenergyconsumptionpredictionisbuiltafteranalyzingcharacteristicson energy consumption changes of public building in hot summer and cold winter area. Particle swarm optimization algorithm is used to optimize the model, and the PSO-RBF neural network prediction model is established. Using the energy consumption data of subject research, the samples of building energy consumption is built. Then the RBF neural network and PSO-RBF neural network are trained on MATLAB. Experiments are conducted to predict energy consumption values of typical public buildings. The results show that accuracy of the prediction model is improved obviously after being optimized, and it has strong learning and predicting ability. The model can predict energy consumption value of public buildings accurately.%通过研究分析夏热冬冷地区公共建筑能耗变化特点, 建立了RBF神经网络建筑能耗预测模型. 在此基础上运用微粒群算法对模型优化,建立了基于PSO-RBF的建筑能耗预测模型. 利用大量数据构造样本集,运用软件分别对优化前后的预测模型进行训练,并运用到典型公共建筑能耗值的预测实例中. 结果表明基于PSO-RBF的建筑能耗预测模型的学习能力和预测能力强,能较准确地实现公共建筑能耗预测.

  9. Power Admission Control with Predictive Thermal Management in Smart Buildings

    DEFF Research Database (Denmark)

    Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan

    2015-01-01

    This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...

  10. A model predictive control strategy for the space heating of a smart building including cogeneration of a fuel cell-electrolyzer system

    DEFF Research Database (Denmark)

    Sossan, Fabrizio; Bindner, Henrik W.; Madsen, Henrik

    2014-01-01

    The objective of this paper is to analyze the value of energy replacement in the context of demand response. Energy replacement is dened as the possibility of the consumer to choose the most convenient source for providing space heating to a smart building according to a dynamic electricity price....... In the proposed setup, heat is provided by conventional electric radiators and a combined heat and power generation system, composed by a fuel cell and an electrolyzer. The energy replacement strategy is formulated using model predictive control and mathematical models of the components involved. Simulations show...... that the predictive energy replacement strategy reduces the operating costs of the system and is able to provide a larger amount of regulating power to the grid. In the paper, we also develop a novel dynamic model of a PEM fuel cell suitable for micro-grid applications. The model is realized applying a grey...

  11. Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

    Science.gov (United States)

    Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

    2017-01-01

    Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

  12. A prediction model for energy consumption of building based on KPCA-WLSSVM%基于 KPCA-WLSSVM 的建筑能耗预测模型

    Institute of Scientific and Technical Information of China (English)

    赵超; 戴坤成; 王贵评

    2015-01-01

    为降低建筑能耗影响因素间复杂相关性对模型性能的影响,建立了一种基于 KPCA-WLSSVM 的建筑能耗预测模型。利用核主元分析(KPCA)对输入变量进行数据压缩,消除变量之间的相关性,简化模型结构;进一步采用加权最小二乘支持向量机(WLSSVM)方法建立建筑能耗预测模型,同时结合一种新型混沌粒子群-模拟退火混合优化(CPSO-SA)算法对模型参数进行优化,以提高模型的预测性能及泛化能力。通过将 KPCA-WLSSVM 模型方法应用于某办公建筑能耗的预测中,并与 WLSSVM、LSSVM 及 RBFNN 模型相比,实验结果表明,KPCA-WLSSVM 模型方法能有效提高建筑能耗预测精度。%The correlations among the building energy consumption factors can corrupt the prediction model’ s performance,and get undesirable results.A prediction model based on KPCA-WLSSVM is proposed to forecast building energy consumption.The kernel principal component analysis (KPCA)method could not only solve the linear correlation of the input and compress data but also simplify the model structure.A novel hybrid chaos particle swarm optimization simulated annealing (CPSO-SA)algorithm is applied to optimize WLSSVM parameters to improve learning performance and generalization ability of the model. Furthermore,the KPCA-WLSSVM model is applied to the energy consumption prediction for an office building,and the results show that the KPCA-WLSSVM has better accuracy compared with WLSSVM model,LSSVM model and RBF neural network model.and the KPCA-WLSSVM is effective for building energy consumption prediction.

  13. Actual service life prediction of building components

    DEFF Research Database (Denmark)

    Aagaard, Niels-Jørgen; Brandt, Erik; Hansen, Ernst Jan de Place

    2014-01-01

    In recent years, sustainability and life cycle cost in the construction industry have been given great attention in many countries due to the heavy climatic and environmental impact from this sector. In Denmark, a sustainability certification scheme for buildings has been developed including...... such as economics, aesthetics and use of the building. Each of these factors is regarded as a stochastic variable and can be seen as competing causes of bringing service life to an end. A model is proposed for combining such variables resulting in the actual service life of building components. Furthermore...

  14. Field theoretical Lie symmetry analysis: The Möbius group, exact solutions of conformal autonomous systems, and predictive model-building

    Science.gov (United States)

    Christodoulides, Kyriakos

    2014-07-01

    We study single and coupled first-order differential equations (ODEs) that admit symmetries with tangent vector fields, which satisfy the N-dimensional Cauchy-Riemann equations. In the two-dimensional case, classes of first-order ODEs which are invariant under Möbius transformations are explored. In the N dimensional case we outline a symmetry analysis method for constructing exact solutions for conformal autonomous systems. A very important aspect of this work is that we propose to extend the traditional technical usage of Lie groups to one that could provide testable predictions and guidelines for model-building and model-validation. The Lie symmetries in this paper are constrained and classified by field theoretical considerations and their phenomenological implications. Our results indicate that conformal transformations are appropriate for elucidating a variety of linear and nonlinear systems which could be used for, or inspire, future applications. The presentation is pragmatic and it is addressed to a wide audience.

  15. Simplified building model of districts

    NARCIS (Netherlands)

    Koene, F.G.H.; Bakker, L.G.; Lanceta, D.; Narmsara, S.

    2014-01-01

    In the setting of this paper, a building is represented by a simple model consisting of two thermal masses. Generic values were obtained for two unknown parameters in the model, capable of representing an office building, a single family dwelling and a multifamily dwelling, at three levels of therma

  16. Flavored model building

    Energy Technology Data Exchange (ETDEWEB)

    Hagedorn, C.

    2008-01-15

    In this thesis we discuss possibilities to solve the family replication problem and to understand the observed strong hierarchy among the fermion masses and the diverse mixing pattern of quarks and leptons. We show that non-abelian discrete symmetries which act non-trivially in generation space can serve as profound explanation. We present three low energy models with the permutation symmetry S{sub 4}, the dihedral group D{sub 5} and the double-valued group T' as flavor symmetry. The T' model turns out to be very predictive, since it explains tri-bimaximal mixing in the lepton sector and, moreover, leads to two non-trivial relations in the quark sector, {radical}((m{sub d})/(m{sub s}))= vertical stroke V{sub us} vertical stroke and {radical}((m{sub d})/(m{sub s}))= vertical stroke (V{sub td})/(V{sub ts}) vertical stroke. The main message of the T' model is the observation that the diverse pattern in the quark and lepton mixings can be well-understood, if the flavor symmetry is not broken in an arbitrary way, but only to residual (non-trivial) subgroups. Apart from leading to deeper insights into the origin of the fermion mixings this idea enables us to perform systematic studies of large classes of discrete groups. This we show in our study of dihedral symmetries D{sub n} and D'{sub n}. As a result we find only five distinct (Dirac) mass matrix structures arising from a dihedral group, if we additionally require partial unification of either left-handed or left-handed conjugate fermions and the determinant of the mass matrix to be non-vanishing. Furthermore, we reveal the ability of dihedral groups to predict the Cabibbo angle {theta}{sub C}, i.e. vertical stroke V{sub us(cd)} vertical stroke = cos((3{pi})/(7)), as well as maximal atmospheric mixing, {theta}{sub 23}=({pi})/(4), and vanishing {theta}{sub 13} in the lepton sector. (orig.)

  17. Building performance modelling for sustainable building design

    National Research Council Canada - National Science Library

    Oduyemi, Olufolahan; Okoroh, Michael

    2016-01-01

    ...) called Ecotect for sustainable building design. Finally, it introduces a design tool analysis of a case study using Ecotect to evaluate various what if scenarios on a proposed multi-use building...

  18. Buildings Lean Maintenance Implementation Model

    Science.gov (United States)

    Abreu, Antonio; Calado, João; Requeijo, José

    2016-11-01

    Nowadays, companies in global markets have to achieve high levels of performance and competitiveness to stay "alive".Within this assumption, the building maintenance cannot be done in a casual and improvised way due to the costs related. Starting with some discussion about lean management and building maintenance, this paper introduces a model to support the Lean Building Maintenance (LBM) approach. Finally based on a real case study from a Portuguese company, the benefits, challenges and difficulties are presented and discussed.

  19. Whole-building Hygrothermal Simulation Model

    DEFF Research Database (Denmark)

    Rode, Carsten; Grau, Karl

    2003-01-01

    An existing integrated simulation tool for dynamic thermal simulation of building was extended with a transient model for moisture release and uptake in building materials. Validation of the new model was begun with comparison against measurements in an outdoor test cell furnished with single...... materials. Almost quasi-steady, cyclic experiments were used to compare the indoor humidity variation and the numerical results of the integrated simulation tool with the new moisture model. Except for the case with chipboard as furnishing, the predictions of indoor humidity with the detailed model were...

  20. Tox21Challenge to build predictive models of nuclear receptor and stress response pathways as mediated by exposure to environmental chemicals and drugs

    Directory of Open Access Journals (Sweden)

    Ruili eHuang

    2016-01-01

    Full Text Available Tens of thousands of chemicals with poorly understood biological properties are released into the environment each day. High-throughput screening (HTS is potentially a more efficient and cost-effective alternative to traditional toxicity tests. Using HTS, one can profile chemicals for potential adverse effects and prioritize a manageable number for more in-depth testing. Importantly, it can provide clues to mechanism of toxicity. The Tox21 program has generated >50 million quantitative high-throughput screening (qHTS data points. A library of several thousands of compounds, including environmental chemicals and drugs, is screened against a panel of nuclear receptor and stress response pathway assays. The National Center for Advancing Translational Sciences (NCATS has organized an International data challenge in order to crowd-source data and build predictive toxicity models. This Challenge asks a crowd of researchers to use these data to elucidate the extent to which the interference of biochemical and cellular pathways by compounds can be inferred from chemical structure data. The data generated against the Tox21 library served as the training set for this modeling Challenge. The competition attracted participants from 18 different countries to develop computational models aimed at better predicting chemical toxicity. The winning models from nearly 400 model submissions all achieved >80% accuracy. Several models exceeded 90% accuracy, which was measured by area under the receiver operating characteristic curve (AUC-ROC. Combining the winning models with the knowledge already gained from Tox21 screening data are expected to improve the community’s ability to prioritize novel chemicals with respect to potential human health concern.

  1. Predictive Model for Corrosion Rate of Oil Tubes in CO2/H2 S Coexistent Environment Part Ⅰ :Building of Model

    Institute of Scientific and Technical Information of China (English)

    李全安; 白真权; 黄得志; 张清; 文九巴; 李鹤林

    2004-01-01

    Based on an analysis of the existing models of CO2 corrosion in literatures and the autoclave simulative experiments, a predictive model of corrosion rate (rcorr) in CO2/H2 S corrosion for oil tubes has been established, in which rcorr is expressed as a function of pH, temperature ( T), pressure of CO2 ( Pco2 ) and pressure of H2S ( PH2S ). The model has been verified by experimental data obtained on N80 steel. The improved features of the predictive model include the following aspects: ( 1 ) The influence of temperature on the protectiveness of corrosion film is taken into consideration for establishment of predictive model of the rcorr in CO2/H2S corrosion. The Equations of scale temperature and scale factor are put forward, and they fit the experimental result very well. (2)The linear relationship still exists between In rcorr and In Pco2 in CO2/H2S corrosion (as same as that in CO2 corrosion). Therefore,a correction factor as a function of PH2S has been introduced into the predictive model in CO2/H2S corrosion. (3) The model is compatible with the main existing models.

  2. Building Mental Models by Dissecting Physical Models

    Science.gov (United States)

    Srivastava, Anveshna

    2016-01-01

    When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to…

  3. Nonlinear predictive energy management of residential buildings with photovoltaics & batteries

    Science.gov (United States)

    Sun, Chao; Sun, Fengchun; Moura, Scott J.

    2016-09-01

    This paper studies a nonlinear predictive energy management strategy for a residential building with a rooftop photovoltaic (PV) system and second-life lithium-ion battery energy storage. A key novelty of this manuscript is closing the gap between building energy management formulations, advanced load forecasting techniques, and nonlinear battery/PV models. Additionally, we focus on the fundamental trade-off between lithium-ion battery aging and economic performance in energy management. The energy management problem is formulated as a model predictive controller (MPC). Simulation results demonstrate that the proposed control scheme achieves 96%-98% of the optimal performance given perfect forecasts over a long-term horizon. Moreover, the rate of battery capacity loss can be reduced by 25% with negligible losses in economic performance, through an appropriate cost function formulation.

  4. Modeling and Simulation of Multi-Room Buildings

    Directory of Open Access Journals (Sweden)

    D.W.U. Perera

    2016-04-01

    Full Text Available Buildings are one of the largest energy consumers in the world which accounts for nearly 40% of the total global energy consumption. In the countries where cold climate conditions predominate, space heating is the key contributor to the increased energy consumption. Today there is a growing trend to use Building Energy Management Systems (BEMS to control the energy consumption of buildings in an efficient manner. BEMS require a good heating model of the building to be integrated for better control purposes. This article refers to the development of different types of physics based buillding heating models, regarding single-zone, multi-floor and multi-room buildings. They address the propriety of each model in building heating control concerning the prediction accuracy and the prediction time. These models are verified for a residential building having three floors. According to the results, the multi-floor model is recognized to have the best qualifications obliged as a model for control.

  5. Building Chaotic Model From Incomplete Time Series

    Science.gov (United States)

    Siek, Michael; Solomatine, Dimitri

    2010-05-01

    This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual

  6. Building performance modelling for sustainable building design

    Directory of Open Access Journals (Sweden)

    Olufolahan Oduyemi

    2016-12-01

    The output revealed that BPM delivers information needed for enhanced design and building performance. Recommendations such as the establishment of proper mechanisms to monitor the performance of BPM related construction are suggested to allow for its continuous implementation. This research consolidates collective movements towards wider implementation of BPM and forms a base for developing a sound BIM strategy and guidance.

  7. Method for simulating predictive control of building systems operation in the early stages of building design

    DEFF Research Database (Denmark)

    Petersen, Steffen; Svendsen, Svend

    2011-01-01

    A method for simulating predictive control of building systems operation in the early stages of building design is presented. The method uses building simulation based on weather forecasts to predict whether there is a future heating or cooling requirement. This information enables the thermal...... control systems of the building to respond proactively to keep the operational temperature within the thermal comfort range with the minimum use of energy. The method is implemented in an existing building simulation tool designed to inform decisions in the early stages of building design through...... parametric analysis. This enables building designers to predict the performance of the method and include it as a part of the solution space. The method furthermore facilitates the task of configuring appropriate building systems control schemes in the tool, and it eliminates time consuming manual...

  8. 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...

  9. 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.

  10. Quantification of Uncertainty in Predicting Building Energy Consumption

    DEFF Research Database (Denmark)

    Brohus, Henrik; Frier, Christian; Heiselberg, Per;

    2012-01-01

    for the dynamic thermal behaviour of buildings. However, for air flow and energy consumption it is found to be much more significant due to less “damping”. Probabilistic methods establish a new approach to the prediction of building energy consumption, enabling designers to include stochastic parameters like......Traditional building energy consumption calculation methods are characterised by rough approaches providing approximate figures with high and unknown levels of uncertainty. Lack of reliable energy resources and increasing concerns about climate change call for improved predictive tools. A new...... approach for the prediction of building energy consumption is presented. The approach quantifies the uncertainty of building energy consumption by means of stochastic differential equations. The approach is applied to a general heat balance for an arbitrary number of loads and zones in a building...

  11. Implementation of Models for Building Envelope Air Flow Fields in a Whole Building Hygrothermal Simulation Tool

    DEFF Research Database (Denmark)

    Rode, Carsten; Grau, Karl

    2009-01-01

    Simulation tools are becoming available which predict the heat and moisture conditions in the indoor environment as well as in the envelope of buildings, and thus it has become possible to consider the important interaction between the different components of buildings and the different physical...... phenomena which occur. However, there is still room for further development of such tools. This paper will present an attempt to integrate modelling of air flows in building envelopes into a whole building hygrothermal simulation tool. Two kinds of air flows have been considered: 1. Air flow in ventilated...... cavity such as in the exterior cladding of building envelopes, i.e. a flow which is parallel to the construction plane. 2. Infiltration/exfiltration of air through the building envelope, i.e. a flow which is perpendicular to the construction plane. The new models make it possible to predict the thermal...

  12. Landing Gear Aerodynamic Noise Prediction Using Building-Cube Method

    Directory of Open Access Journals (Sweden)

    Daisuke Sasaki

    2012-01-01

    Full Text Available Landing gear noise prediction method is developed using Building-Cube Method (BCM. The BCM is a multiblock-structured Cartesian mesh flow solver, which aims to enable practical large-scale computation. The computational domain is composed of assemblage of various sizes of building blocks where small blocks are used to capture flow features in detail. Because of Cartesian-based mesh, easy and fast mesh generation for complicated geometries is achieved. The airframe noise is predicted through the coupling of incompressible Navier-Stokes flow solver and the aeroacoustic analogy-based Curle’s equation. In this paper, Curle’s equation in noncompact form is introduced to predict the acoustic sound from an object in flow. This approach is applied to JAXA Landing gear Evaluation Geometry model to investigate the influence of the detail components to flows and aerodynamic noises. The position of torque link and the wheel cap geometry are changed to discuss the influence. The present method showed good agreement with the preceding experimental result and proved that difference of the complicated components to far field noise was estimated. The result also shows that the torque link position highly affects the flow acceleration at the axle region between two wheels, which causes the change in SPL at observation point.

  13. Coupled Outdoor and Indoor Airflow Prediction for Buildings Using Computational Fluid Dynamics (CFD

    Directory of Open Access Journals (Sweden)

    Deo Prasad

    2013-05-01

    Full Text Available The objective of this study is to investigate the accuracy of Computational Fluid Dynamics (CFD for simultaneously predicting the outdoor and indoor airflows of single-cell and multi-storey buildings. Empirical models and two existing wind tunnel experimental data are used for validation. This study found that coupled CFD simulations provide sufficiently accurate airflow predictions and, in cases of buildings with complex façade treatments, accurately accounts for changes in ventilation performance, which may be impossible using empirical models. This study concludes that coupled CFD simulations can generally be used to predict ventilation performance in small and large buildings.

  14. Selecting the group method of data handling as one of the most perspective algorithmes for building a predictive model of petroleum consumption in the system of energy balance of Ukraine

    Directory of Open Access Journals (Sweden)

    Trachuk A.R.

    2017-06-01

    Full Text Available This paper deals with issues of petroleum consumption in Ukraine. The dynamics of consumption of petroleum is analysed and proposed guidelines for the efficient production, consumption and import of petroleum in Ukraine. Constructed and developed predictive models of petroleum consumption in Ukraine through the use of modern software and using the group method of data handling, which allowed building adequate predictive models of petroleum consumption in the system of Ukraine’s energy balance. Researched and forecasted scenarios of petroleum consumption in the Ukraine. The problem of efficient use of energy resources is critical for sustainable economic development against the backdrop of energy saving national economy depends on energy imports, on the one hand, and rising prices for these resources. The basic foundation of the formation energy system of Ukraine is to build forecasting scenarios for different types of energy and different criteria for effective use of energy resources. Solving this problem is not only with ensuring energy security, but also with the level of development of regions of Ukraine and ensuring quality of life. Prediction of petroleum consumption in Ukraine today is an extremely important issue of strategic importance since conducted through analysis and building predictive models will be possible to develop guidelines for the efficient production and consumption of petroleum across Ukraine as a whole.

  15. Irregular Shaped Building Design Optimization with Building Information Modelling

    Directory of Open Access Journals (Sweden)

    Lee Xia Sheng

    2016-01-01

    Full Text Available This research is to recognise the function of Building Information Modelling (BIM in design optimization for irregular shaped buildings. The study focuses on a conceptual irregular shaped “twisted” building design similar to some existing sculpture-like architectures. Form and function are the two most important aspects of new buildings, which are becoming more sophisticated as parts of equally sophisticated “systems” that we are living in. Nowadays, it is common to have irregular shaped or sculpture-like buildings which are very different when compared to regular buildings. Construction industry stakeholders are facing stiff challenges in many aspects such as buildability, cost effectiveness, delivery time and facility management when dealing with irregular shaped building projects. Building Information Modelling (BIM is being utilized to enable architects, engineers and constructors to gain improved visualization for irregular shaped buildings; this has a purpose of identifying critical issues before initiating physical construction work. In this study, three variations of design options differing in rotating angle: 30 degrees, 60 degrees and 90 degrees are created to conduct quantifiable comparisons. Discussions are focused on three major aspects including structural planning, usable building space, and structural constructability. This research concludes that Building Information Modelling is instrumental in facilitating design optimization for irregular shaped building. In the process of comparing different design variations, instead of just giving “yes or no” type of response, stakeholders can now easily visualize, evaluate and decide to achieve the right balance based on their own criteria. Therefore, construction project stakeholders are empowered with superior evaluation and decision making capability.

  16. Predicting Energy Performance of a Net-Zero Energy Building: A Statistical Approach.

    Science.gov (United States)

    Kneifel, Joshua; Webb, David

    2016-09-01

    Performance-based building requirements have become more prevalent because it gives freedom in building design while still maintaining or exceeding the energy performance required by prescriptive-based requirements. In order to determine if building designs reach target energy efficiency improvements, it is necessary to estimate the energy performance of a building using predictive models and different weather conditions. Physics-based whole building energy simulation modeling is the most common approach. However, these physics-based models include underlying assumptions and require significant amounts of information in order to specify the input parameter values. An alternative approach to test the performance of a building is to develop a statistically derived predictive regression model using post-occupancy data that can accurately predict energy consumption and production based on a few common weather-based factors, thus requiring less information than simulation models. A regression model based on measured data should be able to predict energy performance of a building for a given day as long as the weather conditions are similar to those during the data collection time frame. This article uses data from the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility (NZERTF) to develop and validate a regression model to predict the energy performance of the NZERTF using two weather variables aggregated to the daily level, applies the model to estimate the energy performance of hypothetical NZERTFs located in different cities in the Mixed-Humid climate zone, and compares these estimates to the results from already existing EnergyPlus whole building energy simulations. This regression model exhibits agreement with EnergyPlus predictive trends in energy production and net consumption, but differs greatly in energy consumption. The model can be used as a framework for alternative and more complex models based on the

  17. Computer Prediction of Air Quality in Livestock Buildings

    DEFF Research Database (Denmark)

    Svidt, Kjeld; Bjerg, Bjarne

    In modem livestock buildings the design of ventilation systems is important in order to obtain good air quality. The use of Computational Fluid Dynamics for predicting the air distribution makes it possible to include the effect of room geometry and heat sources in the design process. This paper...... presents numerical prediction of air flow in a livestock building compared with laboratory measurements. An example of the calculation of contaminant distribution is given, and the future possibilities of the method are discussed....

  18. 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.

  19. Predicting the build/drop tendency of rotary drilling assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Jogl, P.N.; Burgess, T.M.; Bowling, J.P.

    1988-06-01

    Today, the majority of rotary bottomhole assemblies (BHA's) for directional control are designed through practical experience and trial and error. This approach can produce satisfactory results when a great deal of local experience can be drawn on. It can prove costly, however, during drilling in a new area because of the increased number of trips and correction runs. This paper demonstrates how a BHA model can be used to predict the directional inclination tendencies of rotary assemblies, thus limiting the uncertainty associated with the traditional BHA design techniques. The technique is demonstrated on data from 17 bit runs from three wells on the same platform in the Gulf of Mexico. Predicted tendencies from BHA descriptions alone proved to be accurate (to an error of +-0.1/sup 0//100 ft-0.03/sup 0//10 ml) in more than half the cases. The uncertainty of other predictions appeared to depend on the hole gauge. The distance taken for a BHA to reach a stable build/drop rate after the start of a bit run depends on the length of the BHA. This factor must be taken into account in the prediction of BHA performance.

  20. A first-order thermal model for building design

    Energy Technology Data Exchange (ETDEWEB)

    Mathews, E.H. [Centre for Experimental and Numerical Thermoflow, Univ. of Pretoria (South Africa); Richards, P.G. [Centre for Experimental and Numerical Thermoflow, Univ. of Pretoria (South Africa); Lombard, C. [Centre for Experimental and Numerical Thermoflow, Univ. of Pretoria (South Africa)

    1994-12-31

    Simplified thermal models of buildings can successfully be applied in building design. This paper describes the derivation and validation of a first-order thermal model which has a clear physical interpretation, is based on uncomplicated calculation procedures and requires limited input information. Because extensive simplifications and assumptions are inherent in the development of the model, a comprehensive validation study is reported. The validity of the thermal model was proven with 70 validation studies in 32 buildings comprising a wide range of thermal characteristics. The accuracy of predictions compares well with other sophisticated programs. The proposed model is considered to be eminently suitable for incorporation in an efficient design tool. (orig.)

  1. Systematic model building with flavor symmetries

    Energy Technology Data Exchange (ETDEWEB)

    Plentinger, Florian

    2009-12-19

    The observation of neutrino masses and lepton mixing has highlighted the incompleteness of the Standard Model of particle physics. In conjunction with this discovery, new questions arise: why are the neutrino masses so small, which form has their mass hierarchy, why is the mixing in the quark and lepton sectors so different or what is the structure of the Higgs sector. In order to address these issues and to predict future experimental results, different approaches are considered. One particularly interesting possibility, are Grand Unified Theories such as SU(5) or SO(10). GUTs are vertical symmetries since they unify the SM particles into multiplets and usually predict new particles which can naturally explain the smallness of the neutrino masses via the seesaw mechanism. On the other hand, also horizontal symmetries, i.e., flavor symmetries, acting on the generation space of the SM particles, are promising. They can serve as an explanation for the quark and lepton mass hierarchies as well as for the different mixings in the quark and lepton sectors. In addition, flavor symmetries are significantly involved in the Higgs sector and predict certain forms of mass matrices. This high predictivity makes GUTs and flavor symmetries interesting for both, theorists and experimentalists. These extensions of the SM can be also combined with theories such as supersymmetry or extra dimensions. In addition, they usually have implications on the observed matter-antimatter asymmetry of the universe or can provide a dark matter candidate. In general, they also predict the lepton flavor violating rare decays {mu} {yields} e{gamma}, {tau} {yields} {mu}{gamma}, and {tau} {yields} e{gamma} which are strongly bounded by experiments but might be observed in the future. In this thesis, we combine all of these approaches, i.e., GUTs, the seesaw mechanism and flavor symmetries. Moreover, our request is to develop and perform a systematic model building approach with flavor symmetries and

  2. Virtual building environments (VBE) - Applying information modeling to buildings

    Energy Technology Data Exchange (ETDEWEB)

    Bazjanac, Vladimir

    2004-06-21

    A Virtual Building Environment (VBE) is a ''place'' where building industry project staffs can get help in creating Building Information Models (BIM) and in the use of virtual buildings. It consists of a group of industry software that is operated by industry experts who are also experts in the use of that software. The purpose of a VBE is to facilitate expert use of appropriate software applications in conjunction with each other to efficiently support multidisciplinary work. This paper defines BIM and virtual buildings, and describes VBE objectives, set-up and characteristics of operation. It informs about the VBE Initiative and the benefits from a couple of early VBE projects.

  3. Methods for implementing Building Information Modeling and Building Performance Simulation approaches

    DEFF Research Database (Denmark)

    Mondrup, Thomas Fænø

    In the present thesis, a number of studies into the adoption of Building Information Modeling (BIM) and Building Performance Simulation (BPS) are presented. The thesis has two main goals. The first is to explore the benefits and challenges of adopting (a) BIM as a platform for Architecture......, Engineering, Construction, and Facility Management (AEC/ FM) communication, and (b) BPS as a platform for early-stage building performance prediction. The second is to develop (a) relevant AEC/FM communication support instruments, and (b) standardized BIM and BPS execution guidelines and information exchange...... to improve early-stage building performance prediction. However, because of complex BPS information exchange structures, the BPS process is not always practical, highlighting the need for these structures to be simplified and more, clearly articulated. In this thesis, buildingSMART standard approaches...

  4. 联合速度建模及其在反射波法隧道超前预报中的应用%Combined migration velocity model-building and its application in tunnel seismic prediction*

    Institute of Scientific and Technical Information of China (English)

    巩向博; 韩立国; 牛建军; 张晓培; 王德利; 杜立志

    2010-01-01

    We propose a combined migration velocity analysis and imaging method based on Kirchhoff integral migration and reverse time migration,using the residual curvature analysis and layer stripping strategy to build the velocity model.This method improves the image resolution of Kirchhoff integral migration and reduces the computations of the reverse time migration.It combines the advantages of efficiency and accuracy of the two migration methods.Its application in tunnel seismic prediction shows good results.Numerical experiments show that the imaging results of reverse time migration are better than the imaging results of Kirchhoff integral migration in many aspects of tunnel prediction.Field data show that this method has efficient computations and can establish a reasonable velocity model and a high quality imaging section.Combination with geological information can make an accurate prediction of the front of the tunnel geological structure.

  5. The application Of Fourier Prediction Models To Schedule Paddy Growing Season With High Resolution For Upgrading Farm Capacity Building (Case Study in Indramayu Regency)

    Science.gov (United States)

    Martuani Siregar, Plato

    2016-08-01

    Indonesian government still has obstacles in the production of annual paddy harvest and planting which causes a decrease 20 percent drop in National production. The failure of one of them caused by weather patterns and climate change that makes farmers difficult to plan future activities with good crop calender. That is because the coming of the rainy season at this moment cannot be predicted precisely. To that end, the role of technology in model and estimate the precise rainfall (high resolution) becomes very important. The developing Fourier prediction models to become agriculture information system was user friendly for instructor/extension officers and farmers who can overcome this problem. The agriculture information models are developed to determine the time of crop calendar weighted maps with rice terraces whom government services, scout and farmers at Indramayu regency easily wears it. The sum of sinus models is used alternatively to predict deciles futures and monthly rainfalls for one year ahead produce a 0.97 correlation with the observed data in Indramayu region. The residue of the sum of sinus models became anomalous rainfall for instan ENSO can cause forward and late in rainfall season. Basically by using a method of curve fitting Sum of Sine results turned out to be related to the monsoon event and climate classification that indicate to distribute annual. While residue model shows cycles of 28.89,61.79 and 80.9 months. These frequencies are related to ENSO event. The Schmidt & Ferguson climate classification of rainfalls and wind monthly conclude Indramayu Regency dominate by type of wet and dry monthly. Map early in the season prediction and map early the planting of rice that have been tested since the start built 2008 is currently being updated with a system software, so that will make it easier for farmers and extension officers as well as related service to apply it on crop calendar.

  6. Optimizing Energy Consumption in Building Designs Using Building Information Model (BIM)

    Science.gov (United States)

    Egwunatum, Samuel; Joseph-Akwara, Esther; Akaigwe, Richard

    2016-09-01

    Given the ability of a Building Information Model (BIM) to serve as a multi-disciplinary data repository, this paper seeks to explore and exploit the sustainability value of Building Information Modelling/models in delivering buildings that require less energy for their operation, emit less CO2 and at the same time provide a comfortable living environment for their occupants. This objective was achieved by a critical and extensive review of the literature covering: (1) building energy consumption, (2) building energy performance and analysis, and (3) building information modeling and energy assessment. The literature cited in this paper showed that linking an energy analysis tool with a BIM model helped project design teams to predict and create optimized energy consumption. To validate this finding, an in-depth analysis was carried out on a completed BIM integrated construction project using the Arboleda Project in the Dominican Republic. The findings showed that the BIM-based energy analysis helped the design team achieve the world's first 103% positive energy building. From the research findings, the paper concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results as well as deliver energy-efficient buildings. The study further recommends that the adoption of a level 2 BIM and the integration of BIM in energy optimization analyse should be made compulsory for all projects irrespective of the method of procurement (government-funded or otherwise) or its size.

  7. Optimizing Energy Consumption in Building Designs Using Building Information Model (BIM

    Directory of Open Access Journals (Sweden)

    Egwunatum Samuel

    2016-09-01

    Full Text Available Given the ability of a Building Information Model (BIM to serve as a multi-disciplinary data repository, this paper seeks to explore and exploit the sustainability value of Building Information Modelling/models in delivering buildings that require less energy for their operation, emit less CO2 and at the same time provide a comfortable living environment for their occupants. This objective was achieved by a critical and extensive review of the literature covering: (1 building energy consumption, (2 building energy performance and analysis, and (3 building information modeling and energy assessment. The literature cited in this paper showed that linking an energy analysis tool with a BIM model helped project design teams to predict and create optimized energy consumption. To validate this finding, an in-depth analysis was carried out on a completed BIM integrated construction project using the Arboleda Project in the Dominican Republic. The findings showed that the BIM-based energy analysis helped the design team achieve the world’s first 103% positive energy building. From the research findings, the paper concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results as well as deliver energy-efficient buildings. The study further recommends that the adoption of a level 2 BIM and the integration of BIM in energy optimization analyse should be made compulsory for all projects irrespective of the method of procurement (government-funded or otherwise or its size.

  8. Empirical Model Building Data, Models, and Reality

    CERN Document Server

    Thompson, James R

    2011-01-01

    Praise for the First Edition "This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." - Short Book Reviews This new edition features developments and real-world examples that showcase essential empirical modeling techniques Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these m

  9. Modeling pollutant penetration across building envelopes

    Energy Technology Data Exchange (ETDEWEB)

    Liu, De-Ling; Nazaroff, William W.

    2001-04-01

    As air infiltrates through unintentional openings in building envelopes, pollutants may interact with adjacent surfaces. Such interactions can alter human exposure to air pollutants of outdoor origin. We present modeling explorations of the proportion of particles and reactive gases (e.g., ozone) that penetrate building envelopes as air enters through cracks and wall cavities. Calculations were performed for idealized rectangular cracks, assuming regular geometry, smooth inner crack surface and steady airflow. Particles of 0.1-1.0 {micro}m diameter are predicted to have the highest penetration efficiency, nearly unity for crack heights of 0.25 mm or larger, assuming a pressure difference of 4 Pa or greater and a flow path length of 3 cm or less. Supermicron and ultrafine particles are significantly removed by means of gravitational settling and Brownian diffusion, respectively. In addition to crack geometry, ozone penetration depends on its reactivity with crack surfaces, as parameterized by the reaction probability. For reaction probabilities less than {approx}10{sup -5}, penetration is complete for cracks heights greater than 1 mm. However, penetration through mm scale cracks is small if the reaction probability is {approx}10{sup -4} or greater. For wall cavities, fiberglass insulation is an efficient particle filter, but particles would penetrate efficiently through uninsulated wall cavities or through insulated cavities with significant airflow bypass. The ozone reaction probability on fiberglass fibers was measured to be 10{sup -7} for fibers previously exposed to high ozone levels and 6 x 10{sup -6} for unexposed fibers. Over this range, ozone penetration through fiberglass insulation would vary from >90% to {approx}10-40%. Thus, under many conditions penetration is high; however, there are realistic circumstances in which building envelopes can provide substantial pollutant removal. Not enough is yet known about the detailed nature of pollutant penetration

  10. Building Information Modeling Comprehensive Overview

    Directory of Open Access Journals (Sweden)

    Sergey Kalinichuk

    2015-07-01

    Full Text Available The article is addressed to provide a comprehensive review on recently accelerated development of the Information Technology within project market such as industrial, engineering, procurement and construction. Author’s aim is to cover the last decades of the growth of the Information and Communication Technology in construction industry in particular Building Information Modeling and testifies that the problem of a choice of the effective project realization method not only has not lost its urgency, but has also transformed into one of the major condition of the intensive technology development. All of it has created a great impulse on shortening the project duration and has led to the development of various schedule compression techniques what becomes a focus of modern construction.

  11. Generating navigation models from existing building data

    NARCIS (Netherlands)

    Liu, L.; Zlatanova, S.

    2013-01-01

    Research on indoor navigation models mainly focuses on geometric and logical models .The models are enriched with specific semantic information which supports localisation, navigation and guidance. Geometric models provide information about the structural (physical) distribution of spaces in a build

  12. Strategy for predicting railway-induced vibrations in buildings

    DEFF Research Database (Denmark)

    Persson, Peter; Persson, Kent; Andersen, Lars Vabbersgaard;

    2016-01-01

    for predicting vibrations in nearby buildings in an early stage of the building process. The strategy is based on that there is a fairly good knowledge of the properties of the ground and that some on-site vibration measurements are made. By combining these with finite-element analysis, the vibration level......Urban densification is a way of accommodating population growth. Land adjacent to railways is used for constructing residences and other buildings, and new tramway systems are planned. Under these circumstances, nearby buildings will be exposed to vibrations and noise that may become a nuisance...... for the residents. It is necessary, even at an early stage of planning, to assess the extent of the vibrations and state requirements for the building in order to avoid costly changes at later stages. Ground vibration induced by railway traffic is studied in the paper. The aim is to develop a strategy...

  13. Application of GLBP Algorithm in the Prediction of Building Energy Consumption

    Directory of Open Access Journals (Sweden)

    Dinghao Lv

    2015-06-01

    Full Text Available Using BP neural network in past to predict the energy consumption of the building resulted in some shortcomings. Aiming at these shortages, a new algorithm which combined genetic algorithm with Levenberg-Marquardt algorithm (LM algorithm was proposed. The proposed algorithm was used to improve the neural network and predict the energy consumption of buildings. First, genetic algorithm was used to optimize the weight and threshold of Artificial Neural Network (ANN. Levenberg-Marquardt algorithm was adopted to optimize the neural network training. Then the predicting model was set up in terms of the main effecting factors of the energy consumption. Furthermore, a public building power consumption data for one month is collected by establishing a monitoring platform to train and test the model. Eventually, the simulation result proved that the proposed model was qualified to predict short-term energy consumption accurately and efficiently.

  14. Impacts of building information modeling on facility maintenance management

    Energy Technology Data Exchange (ETDEWEB)

    Ahamed, Shafee; Neelamkavil, Joseph; Canas, Roberto [Centre for Computer-assisted Construction Technologies, National Research Council of Canada, London, Ontario (Canada)

    2010-07-01

    Building information modeling (BIM) is a digital representation of the physical and functional properties of a building; it has been used by construction professionals for a long time and stakeholders are now using it in different aspects of the building lifecycle. This paper intends to present how BIM impacts the construction industry and how it can be used for facility maintenance management. The maintenance and operations of buildings are in most cases still managed through the use of drawings and spreadsheets although life cycle costs of a building are significantly higher than initial investment costs; thus, the use of BIM could help in achieving a higher efficiency and so important benefits. This study is part of an ongoing research project, the nD modeling project, which aims at predicting building energy consumption with better accuracy.

  15. 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.

  16. Numerical Prediction of Buoyant Air Flow in Livestock Buildings

    DEFF Research Database (Denmark)

    Svidt, Kjeld

    not include the effect of room geometry, obstacles or heat sources. This paper describes the use of Computational Fluid Dynamics to predict air flow patterns and temperature distribution in a ventilated space. Good agreement is found when results of numerical predictions are compared with experimental data.......In modern livestock buildings air distribution and air quality are important parameters to animal welfare and to the health of full-tithe employees in animal production. Traditional methods for calculating air distribution in farm buildings are mainly based on formulas for air jets which do...

  17. BIM. Building Information Model. Special issue; BIM. Building Information Model. Themanummer

    Energy Technology Data Exchange (ETDEWEB)

    Van Gelder, A.L.A. [Arta and Consultancy, Lage Zwaluwe (Netherlands); Van den Eijnden, P.A.A. [Stichting Marktwerking Installatietechniek, Zoetermeer (Netherlands); Veerman, J.; Mackaij, J.; Borst, E. [Royal Haskoning DHV, Nijmegen (Netherlands); Kruijsse, P.M.D. [Wolter en Dros, Amersfoort (Netherlands); Buma, W. [Merlijn Media, Waddinxveen (Netherlands); Bomhof, F.; Willems, P.H.; Boehms, M. [TNO, Delft (Netherlands); Hofman, M.; Verkerk, M. [ISSO, Rotterdam (Netherlands); Bodeving, M. [VIAC Installatie Adviseurs, Houten (Netherlands); Van Ravenswaaij, J.; Van Hoven, H. [BAM Techniek, Bunnik (Netherlands); Boeije, I.; Schalk, E. [Stabiplan, Bodegraven (Netherlands)

    2012-11-15

    A series of 14 articles illustrates the various aspects of the Building Information Model (BIM). The essence of BIM is to capture information about the building process and the building product. [Dutch] In 14 artikelen worden diverse aspecten m.b.t. het Building Information Model (BIM) belicht. De essentie van BIM is het vastleggen van informatie over het bouwproces en het bouwproduct.

  18. A simplified dynamic model for existing buildings using CTF and thermal network models

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Xinhua; Wang, Shengwei [Department of Building Services Engineering, The Hong Kong Polytechnic University (China)

    2008-09-15

    An alternative simplified building model is developed to describe existing building system aiming at providing performance benchmark for performance evaluation and diagnosis at building level and performance prediction for air-conditioning system optimal control. This model combines detailed physical models of building envelopes and a thermal network model of building internal mass. The detailed physical models are the CTF (Conduction Transfer Function) models of building envelopes based on the easily available detailed physical properties of exterior walls and roof. The thermal network model is the 2R2C model, and its parameters are estimated and optimized using genetic algorithm with short-term monitored operation data. The parameter optimization of the simplified building internal mass model (2R2C) and the simplified dynamic building model (i.e., CTF+2R2C model) are validated in a high-rising commercial office building under various weather conditions. This CTF+2R2C model is an alternative modeling approach for simulating the overall building dynamic thermal performance when CTF model is chosen to model the building envelope. (author)

  19. Building Energy Modeling: A Data-Driven Approach

    Science.gov (United States)

    Cui, Can

    off-line model is applied based on system identification and Kalman filtering methods. The developed data-driven modeling framework is validated on various genres of buildings, and the experimental results demonstrate desired performance on building energy forecasting in terms of accuracy and computational efficiency. The framework could be easily implemented into building energy model predictive control (MPC), demand response (DR) analysis and real-time operation decision support systems.

  20. Automatic Building Information Model Query Generation

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Yufei; Yu, Nan; Ming, Jiang; Lee, Sanghoon; DeGraw, Jason; Yen, John; Messner, John I.; Wu, Dinghao

    2015-12-01

    Energy efficient building design and construction calls for extensive collaboration between different subfields of the Architecture, Engineering and Construction (AEC) community. Performing building design and construction engineering raises challenges on data integration and software interoperability. Using Building Information Modeling (BIM) data hub to host and integrate building models is a promising solution to address those challenges, which can ease building design information management. However, the partial model query mechanism of current BIM data hub collaboration model has several limitations, which prevents designers and engineers to take advantage of BIM. To address this problem, we propose a general and effective approach to generate query code based on a Model View Definition (MVD). This approach is demonstrated through a software prototype called QueryGenerator. By demonstrating a case study using multi-zone air flow analysis, we show how our approach and tool can help domain experts to use BIM to drive building design with less labour and lower overhead cost.

  1. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

  2. 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.

  3. Predictive Solar-Integrated Commercial Building Load Control

    Energy Technology Data Exchange (ETDEWEB)

    Glasgow, Nathan [EdgePower Inc., Aspen, CO (United States)

    2017-01-31

    This report is the final technical report for the Department of Energy SunShot award number EE0007180 to EdgePower Inc., for the project entitled “Predictive Solar-Integrated Commercial Building Load Control.” The goal of this project was to successfully prove that the integration of solar forecasting and building load control can reduce demand charge costs for commercial building owners with solar PV. This proof of concept Tier 0 project demonstrated its value through a pilot project at a commercial building. This final report contains a summary of the work completed through he duration of the project. Clean Power Research was a sub-recipient on the award.

  4. Building Information Modelling in Denmark and Iceland

    DEFF Research Database (Denmark)

    Jensen, Per Anker; Jóhannesson, Elvar Ingi

    2013-01-01

    Purpose – The purpose of this paper is to explore the implementation of building information modelling (BIM) in the Nordic countries of Europe with particular focus on the Danish building industry with the aim of making use of its experience for the Icelandic building industry. Design....../methodology/aptroach – The research is based on two separate analyses. In the first part, the deployment of information and communication technology (ICT) in the Icelandic building industry is investigated and compared with the other Nordic countries. In the second part the experience in Denmark from implementing and working...... for making standards and guidelines related to BIM. Public building clients are also encouraged to consider initiating projects based on making simple building models of existing buildings in order to introduce the BIM technology to the industry. Icelandic companies are recommended to start implementing BIM...

  5. 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-.

  6. Characterizing Indoor Airflow and Pollutant Transport using Simulation Modeling for Prototypical Buildings. I. Office Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Sohn, M.D.; Daisey, J.M.; Feustel, H.E.

    1999-06-01

    This paper describes the first efforts at developing a set of prototypical buildings defined to capture the key features affecting airflow and pollutant transport in buildings. These buildings will be used to model airflow and pollutant transport for emergency response scenarios when limited site-specific information is available and immediate decisions must be made, and to better understand key features of buildings controlling occupant exposures to indoor pollutant sources. This paper presents an example of this approach for a prototypical intermediate-sized, open style, commercial building. Interzonal transport due to a short-term source release, e.g., accidental chemical spill, in the bottom and the upper floors is predicted and corresponding HVAC system operation effects and potential responses are considered. Three-hour average exposure estimates are used to compare effects of source location and HVAC operation.

  7. A Heat Dynamic Model for Intelligent Heating of Buildings

    DEFF Research Database (Denmark)

    Thavlov, Anders; Bindner, Henrik W.

    2015-01-01

    This article presents a heat dynamic model for prediction of the indoor temperature in an office building. The model has been used in several flexible load applications, where the indoor temperature is allowed to vary around a given reference to provide power system services by shifting the heati...

  8. Modelling diversity in building occupant behaviour: a novel statistical approach

    DEFF Research Database (Denmark)

    Haldi, Frédéric; Calì, Davide; Andersen, Rune Korsholm

    2016-01-01

    We propose an advanced modelling framework to predict the scope and effects of behavioural diversity regarding building occupant actions on window openings, shading devices and lighting. We develop a statistical approach based on generalised linear mixed models to account for the longitudinal nat...

  9. Common Exercises in Whole Building HAM Modelling

    DEFF Research Database (Denmark)

    Rode, Carsten; Woloszyn, Monika

    2009-01-01

    Subtask 1 of the IEA ECBCS Annex 41 (IEA 2007) project had the purpose to advance development in modelling of integral Heat, Air and Moisture (HAM) transfer processes that take place in “whole buildings”. Such modelling considers all relevant elements of buildings: The indoor air, building envelo...

  10. Common Exercises in Whole Building HAM Modelling

    DEFF Research Database (Denmark)

    Rode, Carsten; Woloszyn, Monika

    2008-01-01

    Subtask 1 of the IEA Annex 41 project had the purpose to advance the development in modelling the integral heat, air and moisture transfer processes that take place in “whole buildings”. Such modelling comprises all relevant elements of buildings: The indoor air, the building envelope, the inside...

  11. Whole-building Hygrothermal Simulation Model

    DEFF Research Database (Denmark)

    Rode, Carsten; Grau, Karl

    2003-01-01

    An existing integrated simulation tool for dynamic thermal simulation of building was extended with a transient model for moisture release and uptake in building materials. Validation of the new model was begun with comparison against measurements in an outdoor test cell furnished with single mat...

  12. A Seminar in Mathematical Model-Building.

    Science.gov (United States)

    Smith, David A.

    1979-01-01

    A course in mathematical model-building is described. Suggested modeling projects include: urban problems, biology and ecology, economics, psychology, games and gaming, cosmology, medicine, history, computer science, energy, and music. (MK)

  13. Prediction of Noise Transmission in Lightweight Building Structures

    DEFF Research Database (Denmark)

    Dickow, Kristoffer Ahrens

    tool to predict the flanking transmission of air-borne and structure borne sound already at the design stage. However, lightweight building structures typically do not meet the requirements for ideal SEA subsystems and, therefore, applying the EN 12354 standard to lightweight building structures may...... papers are carried out as parametric studies in the commercial FE package ABAQUS. Finally, an experimental part, that focuses on the uncertainty and variation in wooden junctions, is included. Ten nominally identical plate/beam T-junctions are tested using experimental modal analysis, and the results...

  14. 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...

  15. 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...

  16. Model for Refurbishment of Heritage Buildings

    DEFF Research Database (Denmark)

    Rasmussen, Torben Valdbjørn

    2014-01-01

    A model intended for the selection of feasible refurbishment measures for heritage buildings was developed. The model showed how to choose, evaluate and implement measures that create synergy between the interests in preserving heritage values and creating cost efficient refurbishment that complies...... with the requirements for the use of the building. The model focuses on the cooperation and dialogue between authorities and owners, who refurbish heritage buildings. The developed model was used for the refurbishment of the listed complex, Fæstningens Materialgård. Fæstningens Materialgård is a case study where...

  17. 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....

  18. An Occupant Behavior Model for Building Energy Efficiency and Safety

    Science.gov (United States)

    Pan, L. L.; Chen, T.; Jia, Q. S.; Yuan, R. X.; Wang, H. T.; Ding, R.

    2010-05-01

    An occupant behavior model is suggested to improve building energy efficiency and safety. This paper provides a generic outline of the model, which includes occupancy behavior abstraction, model framework and primary structure, input and output, computer simulation results as well as summary and outlook. Using information technology, now it's possible to collect large amount of information of occupancy. Yet this can only provide partial and historical information, so it's important to develop a model to have full view of the researched building as well as prediction. We used the infrared monitoring system which is set at the front door of the Low Energy Demo Building (LEDB) at Tsinghua University in China, to provide the time variation of the total number of occupants in the LEDB building. This information is used as input data for the model. While the RFID system is set on the 1st floor, which provides the time variation of the occupants' localization in each region. The collected data are used to validate the model. The simulation results show that this presented model provides a feasible framework to simulate occupants' behavior and predict the time variation of the number of occupants in the building. Further development and application of the model is also discussed.

  19. Translating Building Information Modeling to Building Energy Modeling Using Model View Definition

    Directory of Open Access Journals (Sweden)

    WoonSeong Jeong

    2014-01-01

    Full Text Available This paper presents a new approach to translate between Building Information Modeling (BIM and Building Energy Modeling (BEM that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1 the BIM-based Modelica models generated from Revit2Modelica and (2 BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1 enables BIM models to be translated into ModelicaBEM models, (2 enables system interface development based on the MVD for thermal simulation, and (3 facilitates the reuse of original BIM data into building energy simulation without an import/export process.

  20. Translating building information modeling to building energy modeling using model view definition.

    Science.gov (United States)

    Jeong, WoonSeong; Kim, Jong Bum; Clayton, Mark J; Haberl, Jeff S; Yan, Wei

    2014-01-01

    This paper presents a new approach to translate between Building Information Modeling (BIM) and Building Energy Modeling (BEM) that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM) has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD) consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM) and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica) development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1) the BIM-based Modelica models generated from Revit2Modelica and (2) BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1) enables BIM models to be translated into ModelicaBEM models, (2) enables system interface development based on the MVD for thermal simulation, and (3) facilitates the reuse of original BIM data into building energy simulation without an import/export process.

  1. 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.

  2. Non-commutative standard model: model building

    CERN Document Server

    Chaichian, Masud; Presnajder, P

    2003-01-01

    A non-commutative version of the usual electro-weak theory is constructed. We discuss how to overcome the two major problems: (1) although we can have non-commutative U(n) (which we denote by U sub * (n)) gauge theory we cannot have non-commutative SU(n) and (2) the charges in non-commutative QED are quantized to just 0,+-1. We show how the latter problem with charge quantization, as well as with the gauge group, can be resolved by taking the U sub * (3) x U sub * (2) x U sub * (1) gauge group and reducing the extra U(1) factors in an appropriate way. Then we proceed with building the non-commutative version of the standard model by specifying the proper representations for the entire particle content of the theory, the gauge bosons, the fermions and Higgs. We also present the full action for the non-commutative standard model (NCSM). In addition, among several peculiar features of our model, we address the inherentCP violation and new neutrino interactions. (orig.)

  3. Modeling of electromigration salt removal methods in building materials

    DEFF Research Database (Denmark)

    Johannesson, Björn; Ottosen, Lisbeth M.

    2008-01-01

    A model is established for the prediction of the effect of salt removal of building materials using electromigration. Salt-induced decay of building materials, such as masonry and sandstone, is a serious threat to our cultural heritage. Electromigration of salts from building materials, sensitive...... for salt attack of various kinds, is one potential method to preserve old building envelopes. By establishing a model for ionic multi-species diffusion, which also accounts for external applied electrical fields, it is proposed that an important complement to the experimental tests and that verification...... can be obtained. One important issue is to be able to optimizing the salt removing electromagration method in the field by first studying it theoretically. Another benefit is that models can give some answers concerning the effect of the inner surfaces of the material on the diffusion mechanisms...

  4. Structured building model reduction toward parallel simulation

    Energy Technology Data Exchange (ETDEWEB)

    Dobbs, Justin R. [Cornell University; Hencey, Brondon M. [Cornell University

    2013-08-26

    Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations. Parallel computing aims to improve simulation times without loss of accuracy but is poorly utilized by contemporary simulators and is inherently limited by inter-processor communication. This paper bridges these disparate techniques to implement efficient parallel building thermal simulation. We begin with a survey of three structured reduction approaches that compares their performance to a leading unstructured method. We then use structured model reduction to find thermal clusters in the building energy model and allocate processing resources. Experimental results demonstrate faster simulation and low error without any interprocessor communication.

  5. Prediction of thermal sensation in non-air-conditioned buildings in warm climates

    DEFF Research Database (Denmark)

    Fanger, Povl Ole; Toftum, Jørn

    2002-01-01

    The PMV model agrees well with high-quality field studies in buildings with HVAC systems, situated in cold, temperate and warm climates, studied during both summer and winter. In non-air-conditioned buildings in warm climates, occupants may sense the warmth as being less severe than the PMV...... predicts. The main reason is low expectations, but a metabolic rate that is estimated too high can also contribute to explaining the difference. An extension of the PMV model that includes an expectancy factor is introduced for use in non-air-conditioned buildings in warm climates. The extended PMV model...... agrees well with quality field studies in non-air-conditioned buildings of three continents....

  6. Comparison of Building Energy Modeling Programs: Building Loads

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Dandan [Tsinghua Univ., Beijing (China); Hong, Tianzhen [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yan, Da [Tsinghua Univ., Beijing (China); Wang, Chuang [Tsinghua Univ., Beijing (China)

    2012-06-01

    This technical report presented the methodologies, processes, and results of comparing three Building Energy Modeling Programs (BEMPs) for load calculations: EnergyPlus, DeST and DOE-2.1E. This joint effort, between Lawrence Berkeley National Laboratory, USA and Tsinghua University, China, was part of research projects under the US-China Clean Energy Research Center on Building Energy Efficiency (CERC-BEE). Energy Foundation, an industrial partner of CERC-BEE, was the co-sponsor of this study work. It is widely known that large discrepancies in simulation results can exist between different BEMPs. The result is a lack of confidence in building simulation amongst many users and stakeholders. In the fields of building energy code development and energy labeling programs where building simulation plays a key role, there are also confusing and misleading claims that some BEMPs are better than others. In order to address these problems, it is essential to identify and understand differences between widely-used BEMPs, and the impact of these differences on load simulation results, by detailed comparisons of these BEMPs from source code to results. The primary goal of this work was to research methods and processes that would allow a thorough scientific comparison of the BEMPs. The secondary goal was to provide a list of strengths and weaknesses for each BEMP, based on in-depth understandings of their modeling capabilities, mathematical algorithms, advantages and limitations. This is to guide the use of BEMPs in the design and retrofit of buildings, especially to support China’s building energy standard development and energy labeling program. The research findings could also serve as a good reference to improve the modeling capabilities and applications of the three BEMPs. The methodologies, processes, and analyses employed in the comparison work could also be used to compare other programs. The load calculation method of each program was analyzed and compared to

  7. Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

    Science.gov (United States)

    Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

    2010-09-01

    The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the

  8. 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.

  9. Team learning: building shared mental models

    NARCIS (Netherlands)

    Van den Bossche, Piet; Gijselaers, Wim; Segers, Mien; Woltjers, Geert; Kirschner, Paul A.

    2011-01-01

    Van den Bossche, P., Gijselaers, W., Segers, M., Woltjer, G., & Kirschner, P. A. (2011). Team learning: Building shared mental models. Instructional Science, 39, 283-301. doi:10.1007/s11251-010-9128-3.

  10. Experimental and Numerical Analysis of Wind Driven Natural Ventilation in a Building Scale Model

    DEFF Research Database (Denmark)

    Heiselberg, Per Kvols; True, Jan Per Jensen; Sandberg, Mats;

    2004-01-01

    Airflow through openings in a cross ventilated building scale model was investigated in a wind tunnel and by numerical predictions. Predictions for a wind direction perpendicular to the building showed an airflow pattern consisting of streamlines entering the room, that originated from approximat......Airflow through openings in a cross ventilated building scale model was investigated in a wind tunnel and by numerical predictions. Predictions for a wind direction perpendicular to the building showed an airflow pattern consisting of streamlines entering the room, that originated from...

  11. Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

    Energy Technology Data Exchange (ETDEWEB)

    Gregor P. Henze; Moncef Krarti

    2005-09-30

    Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very

  12. 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...

  13. 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...

  14. Building energy modeling for green architecture and intelligent dashboard applications

    Science.gov (United States)

    DeBlois, Justin

    Buildings are responsible for 40% of the carbon emissions in the United States. Energy efficiency in this sector is key to reducing overall greenhouse gas emissions. This work studied the passive technique called the roof solar chimney for reducing the cooling load in homes architecturally. Three models of the chimney were created: a zonal building energy model, computational fluid dynamics model, and numerical analytic model. The study estimated the error introduced to the building energy model (BEM) through key assumptions, and then used a sensitivity analysis to examine the impact on the model outputs. The conclusion was that the error in the building energy model is small enough to use it for building simulation reliably. Further studies simulated the roof solar chimney in a whole building, integrated into one side of the roof. Comparisons were made between high and low efficiency constructions, and three ventilation strategies. The results showed that in four US climates, the roof solar chimney results in significant cooling load energy savings of up to 90%. After developing this new method for the small scale representation of a passive architecture technique in BEM, the study expanded the scope to address a fundamental issue in modeling - the implementation of the uncertainty from and improvement of occupant behavior. This is believed to be one of the weakest links in both accurate modeling and proper, energy efficient building operation. A calibrated model of the Mascaro Center for Sustainable Innovation's LEED Gold, 3,400 m2 building was created. Then algorithms were developed for integration to the building's dashboard application that show the occupant the energy savings for a variety of behaviors in real time. An approach using neural networks to act on real-time building automation system data was found to be the most accurate and efficient way to predict the current energy savings for each scenario. A stochastic study examined the impact of the

  15. Intelligent Monitoring System on Prediction of Building Damage Index using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Reni Suryanita

    2012-03-01

    Full Text Available An earthquake potentially destroys a tall building. The building damage can be indexed by FEMA into three categories namely Immediate Occupancy (IO, Life Safety (LS, and Collapse Prevention (CP. To determine the damage index, the building model has been simulated into structure analysis software. Acceleration data has been analyzed using non linear method in structure analysis program. The earthquake load is time history at surface, PGA=0105g. This work proposes an intelligent monitoring system utilizing Artificial Neural Network to predict the building damage index. The system also provides an alert system and notification to inform the status of the damage. Data learning is trained on ANN utilizing feed forward and back propagation algorithm. The alert system is designed to be able to activate the alarm sound, view the alert bar or text, and send notification via email to the security or management. The system is tested using sample data represented in three conditions involving IO, LS, and CP. The results show that the proposed intelligent monitoring system could provide prediction of up to 92% rate of accuracy and activate the alert. Implementation of the system in building monitoring would allow for rapid, intelligent and accurate prediction of the building damage index due to earthquake.

  16. Integrating Building Information Modeling and Green Building Certification: The BIM-LEED Application Model Development

    Science.gov (United States)

    Wu, Wei

    2010-01-01

    Building information modeling (BIM) and green building are currently two major trends in the architecture, engineering and construction (AEC) industry. This research recognizes the market demand for better solutions to achieve green building certification such as LEED in the United States. It proposes a new strategy based on the integration of BIM…

  17. Integrating Building Information Modeling and Green Building Certification: The BIM-LEED Application Model Development

    Science.gov (United States)

    Wu, Wei

    2010-01-01

    Building information modeling (BIM) and green building are currently two major trends in the architecture, engineering and construction (AEC) industry. This research recognizes the market demand for better solutions to achieve green building certification such as LEED in the United States. It proposes a new strategy based on the integration of BIM…

  18. Building footprint extraction from digital surface models using neural networks

    Science.gov (United States)

    Davydova, Ksenia; Cui, Shiyong; Reinartz, Peter

    2016-10-01

    Two-dimensional building footprints are a basis for many applications: from cartography to three-dimensional building models generation. Although, many methodologies have been proposed for building footprint extraction, this topic remains an open research area. Neural networks are able to model the complex relationships between the multivariate input vector and the target vector. Based on these abilities we propose a methodology using neural networks and Markov Random Fields (MRF) for automatic building footprint extraction from normalized Digital Surface Model (nDSM) and satellite images within urban areas. The proposed approach has mainly two steps. In the first step, the unary terms are learned for the MRF energy function by a four-layer neural network. The neural network is learned on a large set of patches consisting of both nDSM and Normalized Difference Vegetation Index (NDVI). Then prediction is performed to calculate the unary terms that are used in the MRF. In the second step, the energy function is minimized using a maxflow algorithm, which leads to a binary building mask. The building extraction results are compared with available ground truth. The comparison illustrates the efficiency of the proposed algorithm which can extract approximately 80% of buildings from nDSM with high accuracy.

  19. Assessment of energy utilization and leakages in buildings with building information model energy

    Directory of Open Access Journals (Sweden)

    Egwunatum I. Samuel

    2017-03-01

    Full Text Available Given the ability of building information models (BIM to serve as a multidisciplinary data repository, this study attempts to explore and exploit the sustainability value of BIM in delivering buildings that require less energy for operations, emit less carbon dioxide, and provide conducive living environments for occupants. This objective was attained by a critical and extensive literature review that covers the following: (1 building energy consumption, (2 building energy performance and analysis, and (3 BIM and energy assessment. Literature cited in this paper shows that linking an energy analysis tool with a BIM model has helped project design teams to predict and create optimized energy consumption by conducting building energy performance analysis utilizing key performance indicators on average thermal transmitters, resulting heat demand, lighting power, solar heat gains, and ventilation heat losses. An in-depth analysis was conducted on a completed BIM integrated construction project utilizing the Arboleda Project in the Dominican Republic to validate the aforementioned findings. Results show that the BIM-based energy analysis helped the design team attain the world׳s first positive energy building. This study concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results, and deliver energy-efficient buildings. This study further recommends that the adoption of level 2 BIM and BIM integration in energy optimization analysis must be demanded by building regulatory agencies for all projects regardless of procurement method (i.e., government funded or otherwise or size.

  20. Building dynamic spatial environmental models

    NARCIS (Netherlands)

    Karssenberg, D.J.

    2003-01-01

    An environmental model is a representation or imitation of complex natural phenomena that can be discerned by human cognitive processes. This thesis deals with the type of environmental models referred to as dynamic spatial environmental models. The word ‘spatial’ refers to the geographic domain whi

  1. 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

  2. Economic aspects and models for building codes

    DEFF Research Database (Denmark)

    Bonke, Jens; Pedersen, Dan Ove; Johnsen, Kjeld

    It is the purpose of this bulletin to present an economic model for estimating the consequence of new or changed building codes. The object is to allow comparative analysis in order to improve the basis for decisions in this field. The model is applied in a case study.......It is the purpose of this bulletin to present an economic model for estimating the consequence of new or changed building codes. The object is to allow comparative analysis in order to improve the basis for decisions in this field. The model is applied in a case study....

  3. Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

    Science.gov (United States)

    Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

  4. Brookhaven buildings energy conservation optimization model

    Energy Technology Data Exchange (ETDEWEB)

    Carhart, S C; Mulherkar, S S; Sanborn, Y

    1978-01-01

    The Brookhaven Buildings Energy Conservation Optimization Model is a linear programming representation of energy use in buildings. Starting with engineering and economic data on cost and performance of energy technologies used in buildings, including both conversion devices (such as heat pumps) and structural improvements, the model constructs alternative flows for energy through the technologies to meet demands for space heating, air conditioning, thermal applications, and electric lighting and appliances. Alternative paths have different costs and efficiencies. Within constraints such as total demand for energy services, retirement of existing buildings, seasonal operation of certain devices, and others, the model calculates an optimal configuration of energy technologies in buildings. The penetration of the various basic technologies within this configuration is specified in considerable detail, covering new and retrofit markets for nine building types in four regions. Each market may choose from several appropriate conversion devices and four levels each of new and retrofit structural improvement. The principal applications for which the model was designed described briefly.

  5. Modelling the probability of building fires

    Directory of Open Access Journals (Sweden)

    Vojtěch Barták

    2014-12-01

    Full Text Available Systematic spatial risk analysis plays a crucial role in preventing emergencies.In the Czech Republic, risk mapping is currently based on the risk accumulationprinciple, area vulnerability, and preparedness levels of Integrated Rescue Systemcomponents. Expert estimates are used to determine risk levels for individualhazard types, while statistical modelling based on data from actual incidents andtheir possible causes is not used. Our model study, conducted in cooperation withthe Fire Rescue Service of the Czech Republic as a model within the Liberec andHradec Králové regions, presents an analytical procedure leading to the creation ofbuilding fire probability maps based on recent incidents in the studied areas andon building parameters. In order to estimate the probability of building fires, aprediction model based on logistic regression was used. Probability of fire calculatedby means of model parameters and attributes of specific buildings can subsequentlybe visualized in probability maps.

  6. Model building techniques for analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Walther, Howard P.; McDaniel, Karen Lynn; Keener, Donald; Cordova, Theresa Elena; Henry, Ronald C.; Brooks, Sean; Martin, Wilbur D.

    2009-09-01

    The practice of mechanical engineering for product development has evolved into a complex activity that requires a team of specialists for success. Sandia National Laboratories (SNL) has product engineers, mechanical designers, design engineers, manufacturing engineers, mechanical analysts and experimentalists, qualification engineers, and others that contribute through product realization teams to develop new mechanical hardware. The goal of SNL's Design Group is to change product development by enabling design teams to collaborate within a virtual model-based environment whereby analysis is used to guide design decisions. Computer-aided design (CAD) models using PTC's Pro/ENGINEER software tools are heavily relied upon in the product definition stage of parts and assemblies at SNL. The three-dimensional CAD solid model acts as the design solid model that is filled with all of the detailed design definition needed to manufacture the parts. Analysis is an important part of the product development process. The CAD design solid model (DSM) is the foundation for the creation of the analysis solid model (ASM). Creating an ASM from the DSM currently is a time-consuming effort; the turnaround time for results of a design needs to be decreased to have an impact on the overall product development. This effort can be decreased immensely through simple Pro/ENGINEER modeling techniques that summarize to the method features are created in a part model. This document contains recommended modeling techniques that increase the efficiency of the creation of the ASM from the DSM.

  7. Building a multilevel modeling network for lipid processing systems

    DEFF Research Database (Denmark)

    Mustaffa, Azizul Azri; Díaz Tovar, Carlos Axel; Hukkerikar, Amol

    2011-01-01

    data collected from existing process plants, and application of validated models in design and analysis of unit operations; iv) the information and models developed are used as building blocks in the development of methods and tools for computer-aided synthesis and design of process flowsheets (CAFD......The aim of this work is to present the development of a computer aided multilevel modeling network for the systematic design and analysis of processes employing lipid technologies. This is achieved by decomposing the problem into four levels of modeling: i) pure component property modeling...... and a lipid-database of collected experimental data from industry and generated data from validated predictive property models, as well as modeling tools for fast adoption-analysis of property prediction models; ii) modeling of phase behavior of relevant lipid mixtures using the UNIFAC-CI model, development...

  8. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Díaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Mukkerikar, Amol

    2011-01-01

    in design and analysis of unit operations; iv) the information and models developed are used as building blocks in the development of methods and tools for computer-aided synthesis and design of process flowsheets (CAFD). The applicability of this methodology is highlighted in each level of modeling through......The aim of this work is to present the development of a computer aided multilevel modeling network for the systematic design and analysis of processes employing lipid technologies. This is achieved by decomposing the problem into four levels of modeling: i) pure component property modeling...... and a lipid-database of collected experimental data from industry and generated data from validated predictive property models, as well as modeling tools for fast adoption-analysis of property prediction models; ii) modeling of phase behavior of relevant lipid mixtures using the UNIFACCI model, development...

  9. Building models for keratin disorders.

    Science.gov (United States)

    Koster, Maranke I

    2012-05-01

    Palmoplantar keratoderma is a hallmark of pachyonychia congenita (PC) and focal non-epidermolytic palmoplantar keratoderma (FNEPPK). By generating keratin 16 (Krt16)-deficient mice, Lessard and Coulombe, as described in this issue, have generated a mouse model to replicate these palmoplantar lesions. Studies using this model may provide novel insights into the molecular mechanisms responsible for the formation of palmoplantar lesions in PC and FNEPPK patients.

  10. Network Model Building (Process Mapping)

    OpenAIRE

    Blau, Gary; Yih, Yuehwern

    2004-01-01

    12 slides Provider Notes:See Project Planning Video (Windows Media) Posted at the bottom are Gary Blau's slides. Before watching, please note that "process mapping" and "modeling" are mentioned in the video and notes. Here they are meant to refer to the NSCORT "project plan"

  11. Impacts of Model Building Energy Codes

    Energy Technology Data Exchange (ETDEWEB)

    Athalye, Rahul A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sivaraman, Deepak [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elliott, Douglas B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Bing [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bartlett, Rosemarie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-10-31

    The U.S. Department of Energy (DOE) Building Energy Codes Program (BECP) periodically evaluates national and state-level impacts associated with energy codes in residential and commercial buildings. Pacific Northwest National Laboratory (PNNL), funded by DOE, conducted an assessment of the prospective impacts of national model building energy codes from 2010 through 2040. A previous PNNL study evaluated the impact of the Building Energy Codes Program; this study looked more broadly at overall code impacts. This report describes the methodology used for the assessment and presents the impacts in terms of energy savings, consumer cost savings, and reduced CO2 emissions at the state level and at aggregated levels. This analysis does not represent all potential savings from energy codes in the U.S. because it excludes several states which have codes which are fundamentally different from the national model energy codes or which do not have state-wide codes. Energy codes follow a three-phase cycle that starts with the development of a new model code, proceeds with the adoption of the new code by states and local jurisdictions, and finishes when buildings comply with the code. The development of new model code editions creates the potential for increased energy savings. After a new model code is adopted, potential savings are realized in the field when new buildings (or additions and alterations) are constructed to comply with the new code. Delayed adoption of a model code and incomplete compliance with the code’s requirements erode potential savings. The contributions of all three phases are crucial to the overall impact of codes, and are considered in this assessment.

  12. Building predictive models of soil particle-size distribution Construção de modelos preditivos da distribuição do tamanho de partículas do solo

    Directory of Open Access Journals (Sweden)

    Alessandro Samuel-Rosa

    2013-04-01

    Full Text Available Is it possible to build predictive models (PMs of soil particle-size distribution (psd in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index. The PMs explained more than half of the data variance. This performance is similar to (or even better than that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd of soils in regions of complex geology.É possível construir modelos preditivos (MPs da distribuição do tamanho de partículas do solo (DTP em uma região que possua geologia complexa e uma superfície geomórfica jovem e instável? O principal objetivo deste trabalho foi responder a essa questão. Um conjunto de 339 amostras de solo de uma pequena bacia hidrográfica de encosta do sul do Brasil foi usado para construir MPs da DTP na camada superficial do solo. Modelos de regressão linear múltiplos foram construídos com atributos de terreno (elevação, declividade, área de captação, índice de convergência, índice de umidade topográfica. Os MPs explicaram mais da metade da variância dos dados. Esse desempenho é semelhante (se não melhor ao da abordagem tradicional de mapeamento de solos. Para algumas frações de tamanho, o desempenho dos MPs pode chegar a 70 %. As maiores incertezas ocorrem nas áreas de maior

  13. Modeling the Temperature Effect of Orientations in Residential Buildings

    Directory of Open Access Journals (Sweden)

    Sabahat Arif

    2012-07-01

    Full Text Available Indoor thermal comfort in a building has been an important issue for the environmental sustainability. It is an accepted fact that their designs and planning consume a lot of energy in the modern architecture of 20th and 21st centuries. An appropriate orientation of a building can provide thermally comfortable indoor temperatures which otherwise can consume extra energy to condition these spaces through all the seasons. This experimental study investigates the potential effect of this solar passive design strategy on indoor temperatures and a simple model is presented for predicting indoor temperatures based upon the ambient temperatures.

  14. Heterotic model building: 16 special manifolds

    Energy Technology Data Exchange (ETDEWEB)

    He, Yang-Hui [Department of Mathematics, City University,London, EC1V 0HB (United Kingdom); School of Physics, NanKai University,Tianjin, 300071 (China); Merton College, University of Oxford,Oxford OX14JD (United Kingdom); Lee, Seung-Joo [School of Physics, Korea Institute for Advanced Study,Seoul 130-722 (Korea, Republic of); Lukas, Andre; Sun, Chuang [Rudolf Peierls Centre for Theoretical Physics, University of Oxford,1 Keble Road, Oxford OX1 3NP (United Kingdom)

    2014-06-12

    We study heterotic model building on 16 specific Calabi-Yau manifolds constructed as hypersurfaces in toric four-folds. These 16 manifolds are the only ones among the more than half a billion manifolds in the Kreuzer-Skarke list with a non-trivial first fundamental group. We classify the line bundle models on these manifolds, both for SU(5) and SO(10) GUTs, which lead to consistent supersymmetric string vacua and have three chiral families. A total of about 29000 models is found, most of them corresponding to SO(10) GUTs. These models constitute a starting point for detailed heterotic model building on Calabi-Yau manifolds in the Kreuzer-Skarke list. The data for these models can be downloaded http://www-thphys.physics.ox.ac.uk/projects/CalabiYau/toricdata/index.html.

  15. U.S. Department of Energy Commercial Reference Building Models of the National Building Stock

    Energy Technology Data Exchange (ETDEWEB)

    Deru, M.; Field, K.; Studer, D.; Benne, K.; Griffith, B.; Torcellini, P.; Liu, B.; Halverson, M.; Winiarski, D.; Rosenberg, M.; Yazdanian, M.; Huang, J.; Crawley, D.

    2011-02-01

    The U.S. Department of Energy (DOE) Building Technologies Program has set the aggressive goal of producing marketable net-zero energy buildings by 2025. This goal will require collaboration between the DOE laboratories and the building industry. We developed standard or reference energy models for the most common commercial buildings to serve as starting points for energy efficiency research. These models represent fairly realistic buildings and typical construction practices. Fifteen commercial building types and one multifamily residential building were determined by consensus between DOE, the National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory, and represent approximately two-thirds of the commercial building stock.

  16. Numerical prediction of energy consumption in buildings with controlled interior temperature

    Energy Technology Data Exchange (ETDEWEB)

    Jarošová, P.; Št’astník, S. [Brno University of Technology, Faculty of Civil Engineering, 602 00 Brno, Veveří 95, Czech Republic, e-mail jarosova.p@fce.vutbr.cz, stastnik.s@fce.vutbr.cz (Czech Republic)

    2015-03-10

    New European directives bring strong requirement to the energy consumption of building objects, supporting the renewable energy sources. Whereas in the case of family and similar houses this can lead up to absurd consequences, for building objects with controlled interior temperature the optimization of energy demand is really needed. The paper demonstrates the system approach to the modelling of thermal insulation and accumulation abilities of such objetcs, incorporating the significant influence of additional physical processes, as surface heat radiation and moisture-driven deterioration of insulation layers. An illustrative example shows the numerical prediction of energy consumption of a freezing plant in one Central European climatic year.

  17. Computational prediction and control of energy consumption for heating in building structures

    Science.gov (United States)

    Jarošová, Petra; Vala, Jiří

    2017-07-01

    The significance of reasonable prediction and control of energy consumption in building structures follows from the natural requirements of the development of new materials, structures and technologies, as well as from the formal ones from European directives. This paper presents the method based on the generalized multiplicative Fourier decomposition, applied to a model of a building as certain thermal system. The design of the computational algorithm highlights the important contribution of solar radiation, as well as the design and control of the heating equipments. One illustrative numerical example shows the results of the practical implementation of this algorithm in the MATLAB environment.

  18. 构建急性高原病易感者预测模型的方法学研究%Methodological research on building prediction model of susceptible population of acute mountain sickness

    Institute of Scientific and Technical Information of China (English)

    郑然; 周世伟

    2005-01-01

    OBJECTIVE: There are some people in population susceptible to acute mountain sickness. Therefore, it is important to analyse, assess and integrate certain research results to build prediction system and mathematics model in order to predict those susceptible people when army goes to tableland.DATA SOURCES: Computer was used to search databases such as Medline, PubMed and PML to find articles regarding prediction of people susceptible to acute mountain sickness from January 1970 to December 2002 with the search words "acute mountain sickness, susceptible population,prediction" . The language was limited to English. At the same time, Chinese Journal Full-text Database, Chinainfo and CBMdisc were searched to find articles from January 1970 to August 2004 by the Chinese language of "acute mountain sickness, susceptible population and prediction". The research targets are susceptible people to acute mountain sickness. At last,trace-back method was used to supplement some literature and monographs.DATA SELECTION: After systematically analyzed and concluded the literature information and screened researches without conducting experiment, full text of the rest literature was searched and used as selective criteria if it could be used as prediction indicator of susceptible people to acute mountain sickness.DATA EXTRACTION: Totally there were 19 prediction indicators generalized. After conducting systemic analysis, Delphi method and analytic hierarchy process(AHP) to the indicators, 13 were selected while the other 6 were excluded.DATA SYNTHESIS: The indicators were classified according to nervous-humoral regulation ability, oxygen capture ability of respiratory system,anti-anoxia ability of central nervous system, mental health and health service ability. Based on these, system analysis, Delphi method and AHP method were used to screen prediction indicators, establish indictor system, confirm the weighted indicators and weighted indicator system as well as standardize the

  19. Mobile Modelling for Crowdsourcing Building Interior Data

    Science.gov (United States)

    Rosser, J.; Morley, J.; Jackson, M.

    2012-06-01

    Indoor spatial data forms an important foundation to many ubiquitous computing applications. It gives context to users operating location-based applications, provides an important source of documentation of buildings and can be of value to computer systems where an understanding of environment is required. Unlike external geographic spaces, no centralised body or agency is charged with collecting or maintaining such information. Widespread deployment of mobile devices provides a potential tool that would allow rapid model capture and update by a building's users. Here we introduce some of the issues involved in volunteering building interior data and outline a simple mobile tool for capture of indoor models. The nature of indoor data is inherently private; however in-depth analysis of this issue and legal considerations are not discussed in detail here.

  20. Building A Simulation Model For The Prediction Of Temperature Distribution In Pulsed Laser Spot Welding Of Dissimilar Low Carbon Steel 1020 To Aluminum Alloy 6061

    Science.gov (United States)

    Yousef, Adel K. M.; Taha, Ziad. A.; Shehab, Abeer A.

    2011-01-01

    This paper describes the development of a computer model used to analyze the heat flow during pulsed Nd: YAG laser spot welding of dissimilar metal; low carbon steel (1020) to aluminum alloy (6061). The model is built using ANSYS FLUENT 3.6 software where almost all the environments simulated to be similar to the experimental environments. A simulation analysis was implemented based on conduction heat transfer out of the key hole where no melting occurs. The effect of laser power and pulse duration was studied. Three peak powers 1, 1.66 and 2.5 kW were varied during pulsed laser spot welding (keeping the energy constant), also the effect of two pulse durations 4 and 8 ms (with constant peak power), on the transient temperature distribution and weld pool dimension were predicated using the present simulation. It was found that the present simulation model can give an indication for choosing the suitable laser parameters (i.e. pulse durations, peak power and interaction time required) during pulsed laser spot welding of dissimilar metals.

  1. 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

  2. Functional Testing Protocols for Commercial Building Efficiency Baseline Modeling Software

    Energy Technology Data Exchange (ETDEWEB)

    Jump, David; Price, Phillip N.; Granderson, Jessica; Sohn, Michael

    2013-09-06

    This document describes procedures for testing and validating proprietary baseline energy modeling software accuracy in predicting energy use over the period of interest, such as a month or a year. The procedures are designed according to the methodology used for public domain baselining software in another LBNL report that was (like the present report) prepared for Pacific Gas and Electric Company: ?Commercial Building Energy Baseline Modeling Software: Performance Metrics and Method Testing with Open Source Models and Implications for Proprietary Software Testing Protocols? (referred to here as the ?Model Analysis Report?). The test procedure focuses on the quality of the software?s predictions rather than on the specific algorithms used to predict energy use. In this way the software vendor is not required to divulge or share proprietary information about how their software works, while enabling stakeholders to assess its performance.

  3. Sustainability Product Properties in Building Information Models

    Science.gov (United States)

    2012-09-01

    washers, dryers , etc. are indispensable in a passive house. Certification is through a third-party building certifier that has been ac- credited by the...Anchor Trenwyth Model Old World Tumbled - 4X8x16 Standard CMU - 8X8X16 Verastone Plus recycled filled and polished ground face masonry units

  4. Modelling of settlement induced building damage

    NARCIS (Netherlands)

    Giardina, G.

    2013-01-01

    This thesis focuses on the modelling of settlement induced damage to masonry buildings. In densely populated areas, the need for new space is nowadays producing a rapid increment of underground excavations. Due to the construction of new metro lines, tunnelling activity in urban areas is growing.

  5. Techniques for building timing-predictable embedded systems

    CERN Document Server

    Guan, Nan

    2016-01-01

    This book describes state-of-the-art techniques for designing real-time computer systems. The author shows how to estimate precisely the effect of cache architecture on the execution time of a program, how to dispatch workload on multicore processors to optimize resources, while meeting deadline constraints, and how to use closed-form mathematical approaches to characterize highly variable workloads and their interaction in a networked environment. Readers will learn how to deal with unpredictable timing behaviors of computer systems on different levels of system granularity and abstraction. Introduces promising techniques for dealing with challenges associated with deploying real-time systems on multicore platforms; Provides a complete picture of building timing-predictable computer systems, at the program level, component level and system level; Leverages different levels of abstraction to deal with the complexity of the analysis.

  6. 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...

  7. Economic Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat...

  8. Indoor Air Quality Building Education and Assessment Model Forms

    Science.gov (United States)

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  9. Indoor Air Quality Building Education and Assessment Model

    Science.gov (United States)

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  10. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei

    2015-07-26

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.

  11. 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.)

  12. 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...

  13. Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

    Energy Technology Data Exchange (ETDEWEB)

    Gregor P. Henze; Moncef Krarti

    2005-09-30

    Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very

  14. Challenges in microbial ecology: Building predictive understanding of community function and dynamics

    DEFF Research Database (Denmark)

    Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

    2016-01-01

    The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...

  15. Building Detection Using Aerial Images and Digital Surface Models

    Science.gov (United States)

    Mu, J.; Cui, S.; Reinartz, P.

    2017-05-01

    In this paper a method for building detection in aerial images based on variational inference of logistic regression is proposed. It consists of three steps. In order to characterize the appearances of buildings in aerial images, an effective bag-of-Words (BoW) method is applied for feature extraction in the first step. In the second step, a classifier of logistic regression is learned using these local features. The logistic regression can be trained using different methods. In this paper we adopt a fully Bayesian treatment for learning the classifier, which has a number of obvious advantages over other learning methods. Due to the presence of hyper prior in the probabilistic model of logistic regression, approximate inference methods have to be applied for prediction. In order to speed up the inference, a variational inference method based on mean field instead of stochastic approximation such as Markov Chain Monte Carlo is applied. After the prediction, a probabilistic map is obtained. In the third step, a fully connected conditional random field model is formulated and the probabilistic map is used as the data term in the model. A mean field inference is utilized in order to obtain a binary building mask. A benchmark data set consisting of aerial images and digital surfaced model (DSM) released by ISPRS for 2D semantic labeling is used for performance evaluation. The results demonstrate the effectiveness of the proposed method.

  16. Building America Case Study: Predicting Envelope Leakage in Attached Dwellings (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2014-12-01

    'The cost for blower testing is high, because it is labor intensive, and it may disrupt occupants in multiple units. This high cost and disruption deters program participants, and dissuades them from pursuing energy improvements that would trigger air leakage testing, such as improvements to the building envelope.' This statement found in a 2012 report by Heschong Mahone Group emphasizes the importance of reducing the cost and complexity of blower testing in multifamily buildings. Energy efficiency opportunities are being bypassed. The cost of single blower testing is on the order of $300. The cost for guarded blower door testing, the more appropriate test for assessing energy savings opportunities, could easily be six times that and that's only if you have the equipment and simultaneous access to multiple apartments. Thus, the proper test is simply not performed. The objective of the 2013 research project was to develop the model for predicting fully guarded test results (FGT), using unguarded test data and specific building features of apartment units. The model developed has a coefficient of determination R2 value of 0.53 with a root mean square error (RMSE) of 0.13. Both statistical metrics indicate that the model is relatively strong. When tested against data that was not included in the development of the model, prediction accuracy was within 19%, which is reasonable given that seasonal differences in blower door measurements can vary by as much as 25%.

  17. Scripted Building Energy Modeling and Analysis: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Hale, E.; Macumber, D.; Benne, K.; Goldwasser, D.

    2012-08-01

    Building energy modeling and analysis is currently a time-intensive, error-prone, and nonreproducible process. This paper describes the scripting platform of the OpenStudio tool suite (http://openstudio.nrel.gov) and demonstrates its use in several contexts. Two classes of scripts are described and demonstrated: measures and free-form scripts. Measures are small, single-purpose scripts that conform to a predefined interface. Because measures are fairly simple, they can be written or modified by inexperienced programmers.

  18. Building Information Modelling for Smart Built Environments

    Directory of Open Access Journals (Sweden)

    Jianchao Zhang

    2015-01-01

    Full Text Available Building information modelling (BIM provides architectural 3D visualization and a standardized way to share and exchange building information. Recently, there has been an increasing interest in using BIM, not only for design and construction, but also the post-construction management of the built facility. With the emergence of smart built environment (SBE technology, which embeds most spaces with smart objects to enhance the building’s efficiency, security and comfort of its occupants, there is a need to understand and address the challenges BIM faces in the design, construction and management of future smart buildings. In this paper, we investigate how BIM can contribute to the development of SBE. Since BIM is designed to host information of the building throughout its life cycle, our investigation has covered phases from architecture design to facility management. Firstly, we extend BIM for the design phase to provide material/device profiling and the information exchange interface for various smart objects. Next, we propose a three-layer verification framework to assist BIM users in identifying possible defects in their SBE design. For the post-construction phase, we have designed a facility management tool to provide advanced energy management of smart grid-connected SBEs, where smart objects, as well as distributed energy resources (DERs are deployed.

  19. Mind the Gap:Predicted vs.Actual Performance of Green Buildings%Mind the Gap:Predicted vs. Actual Performance of Green Buildings

    Institute of Scientific and Technical Information of China (English)

    Brett Pollard

    2012-01-01

    This paper reviews the major North American and Australian sustainability rating tools to determine how they measure building energy performance. It then reviews the major building energy simulation software packages.The paper then details some of the literature surrounding predicted vs. actual energy performance in green buildings,and concludes with an argument for a more performance-orientated ratings regime.

  20. 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...

  1. 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...

  2. Building information models for astronomy projects

    Science.gov (United States)

    Ariño, Javier; Murga, Gaizka; Campo, Ramón; Eletxigerra, Iñigo; Ampuero, Pedro

    2012-09-01

    A Building Information Model is a digital representation of physical and functional characteristics of a building. BIMs represent the geometrical characteristics of the Building, but also properties like bills of quantities, definition of COTS components, status of material in the different stages of the project, project economic data, etc. The BIM methodology, which is well established in the Architecture Engineering and Construction (AEC) domain for conventional buildings, has been brought one step forward in its application for Astronomical/Scientific facilities. In these facilities steel/concrete structures have high dynamic and seismic requirements, M&E installations are complex and there is a large amount of special equipment and mechanisms involved as a fundamental part of the facility. The detail design definition is typically implemented by different design teams in specialized design software packages. In order to allow the coordinated work of different engineering teams, the overall model, and its associated engineering database, is progressively integrated using a coordination and roaming software which can be used before starting construction phase for checking interferences, planning the construction sequence, studying maintenance operation, reporting to the project office, etc. This integrated design & construction approach will allow to efficiently plan construction sequence (4D). This is a powerful tool to study and analyze in detail alternative construction sequences and ideally coordinate the work of different construction teams. In addition engineering, construction and operational database can be linked to the virtual model (6D), what gives to the end users a invaluable tool for the lifecycle management, as all the facility information can be easily accessed, added or replaced. This paper presents the BIM methodology as implemented by IDOM with the E-ELT and ATST Enclosures as application examples.

  3. 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.

  4. 3D modeling of buildings outstanding sites

    CERN Document Server

    Héno, Rapha?le

    2014-01-01

    Conventional topographic databases, obtained by capture on aerial or spatial images provide a simplified 3D modeling of our urban environment, answering the needs of numerous applications (development, risk prevention, mobility management, etc.). However, when we have to represent and analyze more complex sites (monuments, civil engineering works, archeological sites, etc.), these models no longer suffice and other acquisition and processing means have to be implemented. This book focuses on the study of adapted lifting means for "notable buildings". The methods tackled in this book cover las

  5. 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...

  6. Variable cluster analysis method for building neural network model

    Institute of Scientific and Technical Information of China (English)

    王海东; 刘元东

    2004-01-01

    To address the problems that input variables should be reduced as much as possible and explain output variables fully in building neural network model of complicated system, a variable selection method based on cluster analysis was investigated. Similarity coefficient which describes the mutual relation of variables was defined. The methods of the highest contribution rate, part replacing whole and variable replacement are put forwarded and deduced by information theory. The software of the neural network based on cluster analysis, which can provide many kinds of methods for defining variable similarity coefficient, clustering system variable and evaluating variable cluster, was developed and applied to build neural network forecast model of cement clinker quality. The results show that all the network scale, training time and prediction accuracy are perfect. The practical application demonstrates that the method of selecting variables for neural network is feasible and effective.

  7. Modelling of heat and moisture transfer in buildings - I. Model program

    Energy Technology Data Exchange (ETDEWEB)

    Lu, X. [Laboratory of Structural Engineering and Building Physics, Department of Civil and Environmental Engineering, Helsinki University of Technology, Hut (Finland)

    2002-07-01

    The overall objective of this work is to develop an accurate model for predicting heat and moisture transfer in buildings including building envelopes and indoor air. The model is based on the fundamental thermodynamic relations. Darcy's law, Fick's law and Fourier's law are used in describing the transfer equations. The resultant nonlinear system of partial differential equations is discretized in space by the finite element method. The time marching scheme, Crank-Nicolson scheme, is used to advance the solution in time. The final numerical solution provides transient temperature and moisture distributions in building envelopes as well as temperature and moisture content for building's indoor air subject to outdoor weather conditions described as temperature, relative humidity, solar radiation and wind speed. A series measurements were conducted in order to investigate the model performance. The simulated values were compared against the actual measured values. A good agreement was obtained. (author)

  8. Prediction Models of Free-Field Vibrations from Railway Traffic

    DEFF Research Database (Denmark)

    Malmborg, Jens; Persson, Kent; Persson, Peter

    2017-01-01

    and railways close to where people work and live. Annoyance from traffic-induced vibrations and noise is expected to be a growing issue. To predict the level of vibration and noise in buildings caused by railway and road traffic, calculation models are needed. In the present paper, a simplified prediction...

  9. Mind the Gap:Predicted vs.Actual Performance of Green Buildings

    Institute of Scientific and Technical Information of China (English)

    Brett Pollard

    2012-01-01

    This paper reviews the major North American and Australian sustainability rating tools to determine how they measure building energy performance.It then reviews the major building energy simulation software packages.The paper then details some of the literature surrounding predicted vs.actual energy performance in green buildings,and concludes with an argument for a more performance-orientated ratings regime.

  10. Methodology for Modeling Building Energy Performance across the Commercial Sector

    Energy Technology Data Exchange (ETDEWEB)

    Griffith, B.; Long, N.; Torcellini, P.; Judkoff, R.; Crawley, D.; Ryan, J.

    2008-03-01

    This report uses EnergyPlus simulations of each building in the 2003 Commercial Buildings Energy Consumption Survey (CBECS) to document and demonstrate bottom-up methods of modeling the entire U.S. commercial buildings sector (EIA 2006). The ability to use a whole-building simulation tool to model the entire sector is of interest because the energy models enable us to answer subsequent 'what-if' questions that involve technologies and practices related to energy. This report documents how the whole-building models were generated from the building characteristics in 2003 CBECS and compares the simulation results to the survey data for energy use.

  11. Automatic Generation of 3D Building Models with Multiple Roofs

    Institute of Scientific and Technical Information of China (English)

    Kenichi Sugihara; Yoshitugu Hayashi

    2008-01-01

    Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

  12. Possible User-Dependent CFD Predictions of Transitional Flow in Building Ventilation

    DEFF Research Database (Denmark)

    Peng, Lei; Nielsen, Peter Vilhelm; Wang, Xiaoxue;

    2016-01-01

    among different teams. It indicates that the combined effects of a lack of general turbulence model, and possible errors in multiple decisions based on users’ experience may have caused the observed significant difference. Prediction of transitional flows, as often observed in building ventilation......A modified backward-facing step flow with a large expansion ratio of five (5) was modelled by 19 teams without benchmark solutions or experimental data for validation in an ISHVAC-COBEE July 2015 Tianjin Workshop, entitled as “to predict low turbulent flow”. Different computational fluid dynamics...... (CFD) codes/software, turbulence models, boundary conditions, numerical schemes and convergent criteria were adopted based on the own CFD experience of each participating team. The largest coefficient of variation is larger than 50% and the largest relative maximum difference of penetration length...

  13. Seismic Response Prediction of Buildings with Base Isolation Using Advanced Soft Computing Approaches

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2017-01-01

    Full Text Available Modeling response of structures under seismic loads is an important factor in Civil Engineering as it crucially affects the design and management of structures, especially for the high-risk areas. In this study, novel applications of advanced soft computing techniques are utilized for predicting the behavior of centrically braced frame (CBF buildings with lead-rubber bearing (LRB isolation system under ground motion effects. These techniques include least square support vector machine (LSSVM, wavelet neural networks (WNN, and adaptive neurofuzzy inference system (ANFIS along with wavelet denoising. The simulation of a 2D frame model and eight ground motions are considered in this study to evaluate the prediction models. The comparison results indicate that the least square support vector machine is superior to other techniques in estimating the behavior of smart structures.

  14. Verification of stochastic behavioural models of occupants' interactions with windows in residential buildings

    DEFF Research Database (Denmark)

    Fabi, Valentina; Andersen, Rune Korsholm; Corgnati, Stefano

    2015-01-01

    Realistic characterisation of occupants' window opening behaviour is crucial for reliable prediction of building performance by means of building energy performance simulations. Window opening behaviour has been investigated by several researchers, leading to a variety of logistic regression models....... Initially three models from literature were investigated by comparison of predicted probabilities and the actual measured state of the windows. Data from one of the papers was reanalysed to create new models, based on measurements from single dwellings. These models were used to predict window transition...

  15. Thermal and airflow prediction in buildings by associating models with different levels of details within an object-oriented simulation environment; Prediction des performances thermo-aerauliques des batiments par association de modeles de differents niveaux de finesse au sein d'un environnement oriente objet

    Energy Technology Data Exchange (ETDEWEB)

    Mora, L.

    2003-09-01

    The design of innovative HVAC systems, as well as the evaluation of the comfort of occupants requires a detailed estimation of airflows and heat transfers within building zones. Zonal and CFD methods can in principal provide such details, but in practice they are difficult to apply to study a whole building over long periods of time. In this study, we propose a new simulation platform based on the object oriented simulation environment SPARK to treat most of building zones using the nodal approach. This modeling method considers each zone as a fully and instantaneously well mixed volume. In this case, each zone can be characterized by a unique computational node where temperature, pressure and concentration are determined. Then, some specific rooms are studied with more details. In order to see the impact of these details on the entire building model, we propose different coupling methods depending on models associations between the nodal approach, and zonal or CFD room models. After a brief presentation of the different modeling methods used in this study, we attempt to demonstrate the interest to use one method instead of another depending on the room characteristics or the modeler's objectives. We then present the developed platform in which we solve both nodal and zonal models, and we couple detailed room models with the first method. Finally, a few applications demonstrate some capabilities of the developed platform to not only adjust the level of detail for each room model, but also propose new ways of research. In fact, the last application shows a new coupling method between zonal and CFD methods. In this approach, the first method acquires the airflow structure from results obtained using a CFD model in the room. Consequently, the developed platform has numerous applications, to study the dynamics of heat and mass transfers in buildings as well as in their immediate surroundings. (author)

  16. Strategy for predicting railway-induced vibrations in buildings

    DEFF Research Database (Denmark)

    Persson, Peter; Persson, Kent; Andersen, Lars Vabbersgaard

    2016-01-01

    Urban densification is a way of accommodating population growth. Land adjacent to railways is used for constructing residences and other buildings, and new tramway systems are planned. Under these circumstances, nearby buildings will be exposed to vibrations and noise that may become a nuisance...

  17. Predictive performance simulations for a sustainable lecture building complex

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2012-06-01

    Full Text Available and office building complex for the East London campus of the University of Fort Hare. The design of the building is both unique and complex, combining wind-driven technologies (an aerofoil) and solar-driven technologies (a Trombe wall) to drive a...

  18. Iterative build OMIT maps: Map improvement by iterative model-building and refinement without model bias

    Energy Technology Data Exchange (ETDEWEB)

    Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA; Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720, USA; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, England; Terwilliger, Thomas; Terwilliger, T.C.; Grosse-Kunstleve, Ralf Wilhelm; Afonine, P.V.; Moriarty, N.W.; Zwart, P.H.; Hung, L.-W.; Read, R.J.; Adams, P.D.

    2008-02-12

    A procedure for carrying out iterative model-building, density modification and refinement is presented in which the density in an OMIT region is essentially unbiased by an atomic model. Density from a set of overlapping OMIT regions can be combined to create a composite 'Iterative-Build' OMIT map that is everywhere unbiased by an atomic model but also everywhere benefiting from the model-based information present elsewhere in the unit cell. The procedure may have applications in the validation of specific features in atomic models as well as in overall model validation. The procedure is demonstrated with a molecular replacement structure and with an experimentally-phased structure, and a variation on the method is demonstrated by removing model bias from a structure from the Protein Data Bank.

  19. 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...

  20. A focus on building information modelling.

    Science.gov (United States)

    Ryan, Alison

    2014-03-01

    With the Government Construction Strategy requiring a strengthening of the public sector's capability to implement Building Information Modelling (BIM) protocols, the goal being that all central government departments will be adopting, as a minimum, collaborative Level 2 BIM by 2016, Alison Ryan, of consulting engineers, DSSR, explains the principles behind BIM, its history and evolution, and some of the considerable benefits it can offer. These include lowering capital project costs through enhanced co-ordination, cutting carbon emissions, and the ability to manage facilities more efficiently.

  1. Le soluzioni Building Information Modeling di Bentley

    Directory of Open Access Journals (Sweden)

    Fulvio Bernardini

    2007-04-01

    Full Text Available La questione dell’interoperabilità dei dati negli ultimi anni è stata continuamente dibattuta dai professionisti dei vari settori. L’edilizia col suo ciclo di vita non hanno fatto eccezione e da quando il concetto di Building Information Modeling (BIM ha fatto il suo ingresso nel mondo dell’architettura, dell’ingegneria e delle costruzioni (AEC, le fasi inerenti il processo del buildingnon sono più state considerate separatamente. Bentley Systems, da sempre attiva nel settore delle infrastrutture, propone un’ampia gamma di soluzioni studiate proprio per coprire questo bisogno.

  2. Combining logistic regression and neural networks to create predictive models.

    OpenAIRE

    Spackman, K. A.

    1992-01-01

    Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building wit...

  3. Implementation of Models for Building Envelope Air Flow Fields in a Whole Building Hygrothermal Simulation Tool

    DEFF Research Database (Denmark)

    Sørensen, Karl Grau; Rode, Carsten

    2009-01-01

    Simulation tools are becoming available which predict the heat and moisture conditions in the indoor environment as well as in the envelope of buildings, and thus it has become possible to consider the important interaction between the different components of buildings and the different physical ...

  4. Modelling seasonality in Australian building approvals

    Directory of Open Access Journals (Sweden)

    Harry M Karamujic

    2012-02-01

    Full Text Available The paper examines the impact of seasonal influences on Australian housing approvals, represented by the State of Victoria[1] building approvals for new houses (BANHs. The prime objective of BANHs is to provide timely estimates of future residential building work. Due to the relevance of the residential property sector to the property sector as whole, BANHs are viewed by economic analysts and commentators as a leading indicator of property sector investment and as such the general level of economic activity and employment. The generic objective of the study is to enhance the practice of modelling housing variables. In particular, the study seeks to cast some additional light on modelling the seasonal behaviour of BANHs by: (i establishing the presence, or otherwise, of seasonality in Victorian BANHs; (ii if present, ascertaining is it deterministic or stochastic; (iii determining out of sample forecasting capabilities of the considered modelling specifications; and (iv speculating on possible interpretation of the results. To do so the study utilises a structural time series model of Harwey (1989. The modelling results confirm that the modelling specification allowing for stochastic trend and deterministic seasonality performs best in terms of diagnostic tests and goodness of fit measures. This is corroborated with the analysis of out of sample forecasting capabilities of the considered modelling specifications, which showed that the models with deterministic seasonal specification exhibit superior forecasting capabilities. The paper also demonstrates that if time series are characterized by either stochastic trend or seasonality, the conventional modelling approach[2] is bound to be mis-specified i.e. would not be able to identify statistically significant seasonality in time series.According to the selected modeling specification, factors corresponding to June, April, December and November are found to be significant at five per cent level

  5. Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.;

    2016-01-01

    The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...... problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...

  6. Building a Democratic Model of Science Teaching

    Directory of Open Access Journals (Sweden)

    Suhadi Ibnu

    2016-02-01

    Full Text Available Earlier in the last century, learning in science, as was learning in other disciplines, was developed according to the philosophy of behaviorism. This did not serve the purposes of learning in science properly, as the students were forced to absorb information transferred from the main and the only source of learning, the teacher. Towards the end of the century a significant shift from behaviorism to constructivism philosophy took place. The shift promoted the development of more democratic models of learning in science which provided greater opportunities to the students to act as real scientist, chattering for the building of knowledge and scientific skills. Considering the characteristics of science and the characteristics of the students as active learners, the shift towards democratic models of learning is unavoidable and is merely a matter of time

  7. Building information modelling (BIM: now and beyond

    Directory of Open Access Journals (Sweden)

    Salman Azhar

    2012-12-01

    Full Text Available Building Information Modeling (BIM, also called n-D Modeling or Virtual Prototyping Technology, is a revolutionary development that is quickly reshaping the Architecture-Engineering-Construction (AEC industry. BIM is both a technology and a process. The technology component of BIM helps project stakeholders to visualize what is to be built in a simulated environment to identify any potential design, construction or operational issues. The process component enables close collaboration and encourages integration of the roles of all stakeholders on a project. The paper presents an overview of BIM with focus on its core concepts, applications in the project life cycle and benefits for project stakeholders with the help of case studies. The paper also elaborates risks and barriers to BIM implementation and future trends.

  8. Building information modelling (BIM: now and beyond

    Directory of Open Access Journals (Sweden)

    Salman Azhar

    2015-10-01

    Full Text Available Building Information Modeling (BIM, also called n-D Modeling or Virtual Prototyping Technology, is a revolutionary development that is quickly reshaping the Architecture-Engineering-Construction (AEC industry. BIM is both a technology and a process. The technology component of BIM helps project stakeholders to visualize what is to be built in a simulated environment to identify any potential design, construction or operational issues. The process component enables close collaboration and encourages integration of the roles of all stakeholders on a project. The paper presents an overview of BIM with focus on its core concepts, applications in the project life cycle and benefits for project stakeholders with the help of case studies. The paper also elaborates risks and barriers to BIM implementation and future trends.

  9. A Team Building Model for Software Engineering Courses Term Projects

    Science.gov (United States)

    Sahin, Yasar Guneri

    2011-01-01

    This paper proposes a new model for team building, which enables teachers to build coherent teams rapidly and fairly for the term projects of software engineering courses. Moreover, the model can also be used to build teams for any type of project, if the team member candidates are students, or if they are inexperienced on a certain subject. The…

  10. A Team Building Model for Software Engineering Courses Term Projects

    Science.gov (United States)

    Sahin, Yasar Guneri

    2011-01-01

    This paper proposes a new model for team building, which enables teachers to build coherent teams rapidly and fairly for the term projects of software engineering courses. Moreover, the model can also be used to build teams for any type of project, if the team member candidates are students, or if they are inexperienced on a certain subject. The…

  11. 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.

  12. Energy modeling of two office buildings with data center for green building design

    Energy Technology Data Exchange (ETDEWEB)

    Pan, Yiqun; Yin, Rongxin; Huang, Zhizhong [Institute of Building Performance and Technology, Sino-German College of Applied Sciences, Tongji University, Shanghai 200092 (China)

    2008-07-01

    Energy simulation models are developed with EnergyPlus for two office buildings in a R and D center in Shanghai, China to evaluate the energy cost savings of green building design options compared with the baseline building. As a R and D center of an international IT corporation, there are data centers in the two buildings, which make them different from typical office buildings. The data centers house high energy consuming IT equipments and need 24 h air-conditioning every day all year round. In order to achieve energy cost savings, multiple energy efficiency strategies are employed for design proposed building, encompassing high performance building envelope, lighting system, and HVAC system. Through energy modeling, the design proposed options are compared to an ASHRAE 90.1-2004 compliant budget model to highlight energy cost savings versus ''standard practice'' and show the potential LEED trademark Credit EA1 - Optimize Energy Performance. Meanwhile, they are also compared to China Code model to figure out the energy cost savings versus the most popular practice conforming to China Public Building Energy Saving Design Standard. The whole building energy simulation results show that the yearly energy cost saving of the proposed design will be approximately 27% from China Code building and 21% from ASHRAE budget building, which can achieve 4 points for LEED credit due to energy performance optimization. (author)

  13. 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.

  14. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol

    of these unit operations with respect to performance parameters such as minimum total cost, product yield improvement, operability etc., and process intensification for the retrofit of existing biofuel plants. In the fourth level the information and models developed are used as building blocks...... in the upcoming years major challenges in terms of design and development of better products and more sustainable processes. Although the oleo chemical industry is mature and based on well established processes, the complex systems that lipid compounds form, the lack of accurate predictive models...... for their physical properties and unit operation models for their processing have limited computeraided methods and tools for process synthesis, modeling and simulation to be widely used for design, analysis, and optimization of these processes. In consequence, the aim of this work is to present the development...

  15. Building information modeling based on intelligent parametric technology

    Institute of Scientific and Technical Information of China (English)

    ZENG Xudong; TAN Jie

    2007-01-01

    In order to push the information organization process of the building industry,promote sustainable architectural design and enhance the competitiveness of China's building industry,the author studies building information modeling (BIM) based on intelligent parametric modeling technology.Building information modeling is a new technology in the field of computer aided architectural design,which contains not only geometric data,but also the great amount of engineering data throughout the lifecycle of a building.The author also compares BIM technology with two-dimensional CAD technology,and demonstrates the advantages and characteristics of intelligent parametric modeling technology.Building information modeling,which is based on intelligent parametric modeling technology,will certainly replace traditional computer aided architectural design and become the new driving force to push forward China's building industry in this information age.

  16. LFRic: Building a new Unified Model

    Science.gov (United States)

    Melvin, Thomas; Mullerworth, Steve; Ford, Rupert; Maynard, Chris; Hobson, Mike

    2017-04-01

    The LFRic project, named for Lewis Fry Richardson, aims to develop a replacement for the Met Office Unified Model in order to meet the challenges which will be presented by the next generation of exascale supercomputers. This project, a collaboration between the Met Office, STFC Daresbury and the University of Manchester, builds on the earlier GungHo project to redesign the dynamical core, in partnership with NERC. The new atmospheric model aims to retain the performance of the current ENDGame dynamical core and associated subgrid physics, while also enabling a far greater scalability and flexibility to accommodate future supercomputer architectures. Design of the model revolves around a principle of a 'separation of concerns', whereby the natural science aspects of the code can be developed without worrying about the underlying architecture, while machine dependent optimisations can be carried out at a high level. These principles are put into practice through the development of an autogenerated Parallel Systems software layer (known as the PSy layer) using a domain-specific compiler called PSyclone. The prototype model includes a re-write of the dynamical core using a mixed finite element method, in which different function spaces are used to represent the various fields. It is able to run in parallel with MPI and OpenMP and has been tested on over 200,000 cores. In this talk an overview of the both the natural science and computational science implementations of the model will be presented.

  17. Building energy use prediction and system identification using recurrent neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Kreider, J.F.; Curtiss, P.; Dodier, R.; Krarti, M. [Univ. of Colorado, Boulder, CO (United States); Claridge, D.E.; Haberl, J.S. [Texas A and M Univ., College Station, TX (United States). Dept. of Mechanical Engineering

    1995-08-01

    Following several successful applications of feedforward neural networks (NNs) to the building energy prediction problem a more difficult problem has been addressed recently: namely, the prediction of building energy consumption well into the future without knowledge of immediately past energy consumption. This paper will report results on a recent study of six months of hourly data recorded at the Zachry Engineering Center (ZEC) in College Station, TX. Also reported are results on finding the R and C values for buildings from networks trained on building data.

  18. Prediction of final settlements of buildings constructed on expansive soils

    Directory of Open Access Journals (Sweden)

    María-de-la-Luz Pérez-Rea

    2015-06-01

    Full Text Available Because the action of the swelling pressure, the settlements caused by the transmitted load from the structure on expansive soils, and the settlements calculated by classic theories of soils mechanics are different. This swelling pressure acts in opposite direction to the weight of the building. In this paper, the authors propose the use of a volumetric strain coefficient by settlements exp, in a soil-structure interaction algorithm taking into account the expansive soil behavior in the reduction of the settlement magnitude when a building is placed above soil. It’s necessary to know the initial properties of the expansive unsaturated soil and the load building conditions. A laboratory process is described for determining the aexpcoefficient.

  19. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

    Science.gov (United States)

    Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

    2016-07-01

    Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

  20. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

    Directory of Open Access Journals (Sweden)

    Young-Jin Cha

    2016-07-01

    Full Text Available Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA, was characterized and modeled as a simplified lumped-mass beam model (SLMM, using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA. Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

  1. Building Information Modeling in engineering teaching

    DEFF Research Database (Denmark)

    Andersson, Niclas; Andersson, Pernille Hammar

    2010-01-01

    The application of Information and Communication Technology (ICT) in construction supports business as well as project processes by providing integrated systems for communication, administration, quantity takeoff, time scheduling, cost estimating, progress control among other things. The rapid...... technological development of ICT systems and the increased application of ICT in industry significantly influence the management and organisation of construction projects, and consequently, ICT has implications for the education of engineers and the preparation of students for their future professional careers...... in this case is represented by adopting Building Information Modelling, BIM, for construction management purposes. Course evaluations, a questionnaire and discussions with students confirm a genuinely positive attitude towards the role-play simulation and interaction with industry professionals. The students...

  2. A Model for Air Flow in Ventilated Cavities Implemented in a Tool for Whole-Building Hygrothermal Analysis

    DEFF Research Database (Denmark)

    Grau, Karl; Rode, Carsten

    2006-01-01

    A model for calculating air flows in ventilated cavities has been implemented in the whole-building hygrothermal simulation tool BSim. The tool is able to predict indoor humidity conditions using a transient model for the moisture conditions in the building envelope.......A model for calculating air flows in ventilated cavities has been implemented in the whole-building hygrothermal simulation tool BSim. The tool is able to predict indoor humidity conditions using a transient model for the moisture conditions in the building envelope....

  3. How promotions work : SCAN*PRO-based evolutionary model building

    NARCIS (Netherlands)

    van Heerde, H.J.; Leeflang, P.S.H.; Wittink, D.R.

    2002-01-01

    We provide a rationale for evolutionary model building. The basic idea is that to enhance user acceptance it is important that one begins with a relatively simple model. Simplicity is desired so that managers understand models. As a manager uses the model and builds up experience with this decision

  4. Geometry model construction in infrared image theory simulation of buildings

    Institute of Scientific and Technical Information of China (English)

    谢鸣; 李玉秀; 徐辉; 谈和平

    2004-01-01

    Geometric model construction is the basis of infrared image theory simulation. Taking the construction of the geometric model of one building in Harbin as an example, this paper analyzes the theoretical groundings of simplification and principles of geometric model construction of buildings. It then discusses some particular treatment methods in calculating the radiation transfer coefficient in geometric model construction using the Monte Carlo Method.

  5. Structure Building Predicts Grades in College Psychology and Biology

    Science.gov (United States)

    Arnold, Kathleen M.; Daniel, David B.; Jensen, Jamie L.; McDaniel, Mark A.; Marsh, Elizabeth J.

    2016-01-01

    Knowing what skills underlie college success can allow students, teachers, and universities to identify and to help at-risk students. One skill that may underlie success across a variety of subject areas is structure building, the ability to create mental representations of narratives (Gernsbacher, Varner, & Faust, 1990). We tested if…

  6. Structure Building Predicts Grades in College Psychology and Biology

    Science.gov (United States)

    Arnold, Kathleen M.; Daniel, David B.; Jensen, Jamie L.; McDaniel, Mark A.; Marsh, Elizabeth J.

    2016-01-01

    Knowing what skills underlie college success can allow students, teachers, and universities to identify and to help at-risk students. One skill that may underlie success across a variety of subject areas is structure building, the ability to create mental representations of narratives (Gernsbacher, Varner, & Faust, 1990). We tested if…

  7. Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant

    Institute of Scientific and Technical Information of China (English)

    CHEN Yue-hua; CAO Guang-yi; ZHU Xin-jian

    2007-01-01

    This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.

  8. A geodynamic model of Andean mountain building

    Science.gov (United States)

    Schellart, Wouter P.

    2017-04-01

    The Andes mountain range in South America is the longest in the world and is unique in that it has formed at a subduction zone and not at a continent-continent collision zone. The mountain range has formed due to overriding plate shortening since the Late Cretaceous, and its origin and the driving mechanism(s) responsible for its formation remain a topic of intense debate. Here I present a buoyancy-driven geodynamic model of South American-style subduction, mantle flow and overriding plate deformation, illustrating how subduction-induced mantle flow drives overriding plate deformation. The model reproduces several first-order characteristics of the Andes, including major crustal thickening (up to double the initial crustal thickness) and hundreds of km of east-west shortening in the Central Andes, as well as a slab geometry that is comparable to that of the Nazca slab below the Central Andes. Ultimately, the geodynamic model shows that subduction-induced mantle flow is responsible for Andean-style mountain building.

  9. Building groundwater modeling capacity in Mongolia

    Science.gov (United States)

    Valder, Joshua F.; Carter, Janet M.; Anderson, Mark T.; Davis, Kyle W.; Haynes, Michelle A.; Dorjsuren Dechinlhundev,

    2016-06-16

    Ulaanbaatar, the capital city of Mongolia (fig. 1), is dependent on groundwater for its municipal and industrial water supply. The population of Mongolia is about 3 million people, with about one-half the population residing in or near Ulaanbaatar (World Population Review, 2016). Groundwater is drawn from a network of shallow wells in an alluvial aquifer along the Tuul River. Evidence indicates that current water use may not be sustainable from existing water sources, especially when factoring the projected water demand from a rapidly growing urban population (Ministry of Environment and Green Development, 2013). In response, the Government of Mongolia Ministry of Environment, Green Development, and Tourism (MEGDT) and the Freshwater Institute, Mongolia, requested technical assistance on groundwater modeling through the U.S. Army Corps of Engineers (USACE) to the U.S. Geological Survey (USGS). Scientists from the USGS and USACE provided two workshops in 2015 to Mongolian hydrology experts on basic principles of groundwater modeling using the USGS groundwater modeling program MODFLOW-2005 (Harbaugh, 2005). The purpose of the workshops was to bring together representatives from the Government of Mongolia, local universities, technical experts, and other key stakeholders to build in-country capacity in hydrogeology and groundwater modeling.A preliminary steady-state groundwater-flow model was developed as part of the workshops to demonstrate groundwater modeling techniques to simulate groundwater conditions in alluvial deposits along the Tuul River in the vicinity of Ulaanbaatar. ModelMuse (Winston, 2009) was used as the graphical user interface for MODFLOW for training purposes during the workshops. Basic and advanced groundwater modeling concepts included in the workshops were groundwater principles; estimating hydraulic properties; developing model grids, data sets, and MODFLOW input files; and viewing and evaluating MODFLOW output files. A key to success was

  10. Prediction of Building Floorplans Using Logical and Stochastic Reasoning Based on Sparse Observations

    Science.gov (United States)

    Loch-Dehbi, S.; Dehbi, Y.; Gröger, G.; Plümer, L.

    2016-10-01

    This paper introduces a novel method for the automatic derivation of building floorplans and indoor models. Our approach is based on a logical and stochastic reasoning using sparse observations such as building room areas. No further sensor observations like 3D point clouds are needed. Our method benefits from an extensive prior knowledge of functional dependencies and probability density functions of shape and location parameters of rooms depending on their functional use. The determination of posterior beliefs is performed using Bayesian Networks. Stochastic reasoning is complex since the problem is characterized by a mixture of discrete and continuous parameters that are in turn correlated by non-linear constraints. To cope with this kind of complexity, the proposed reasoner combines statistical methods with constraint propagation. It generates a limited number of hypotheses in a model-based top-down approach. It predicts floorplans based on a-priori localised windows. The use of Gaussian mixture models, constraint solvers and stochastic models helps to cope with the a-priori infinite space of the possible floorplan instantiations.

  11. Prediction using patient comparison vs. modeling: a case study for mortality prediction.

    Science.gov (United States)

    Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter

    2016-08-01

    Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.

  12. Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

    Science.gov (United States)

    Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

  13. Application of neural networks for the prediction of energy use in supermarket buildings

    Energy Technology Data Exchange (ETDEWEB)

    Suh, T.J.; Tassou, S.A.; Datta, D. [Brunel Univ., Uxbridge (United Kingdom); Marriott, D. [Safeway Stores 6 Millington, Middx (United Kingdom)

    1996-12-31

    This paper discusses the application of neural networks to predict energy consumption in commercial buildings. To date, many researchers have demonstrated that neural networks can be more reliable energy predictors than the traditional statistical approaches and can also form the basis for predictive controllers of HVAC equipment. This paper shows the preliminary results of research work at Brunel University for predicting the variation of electricity consumption in a supermarket building based on a neural network. A comparison of the prediction performance of the neural network and a traditional regression approach is presented.

  14. A View on Future Building System Modeling and Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Wetter, Michael

    2011-04-01

    This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described by coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).

  15. Compressive sensing as a paradigm for building physics models

    Science.gov (United States)

    Nelson, Lance J.; Hart, Gus L. W.; Zhou, Fei; Ozoliņš, Vidvuds

    2013-01-01

    The widely accepted intuition that the important properties of solids are determined by a few key variables underpins many methods in physics. Though this reductionist paradigm is applicable in many physical problems, its utility can be limited because the intuition for identifying the key variables often does not exist or is difficult to develop. Machine learning algorithms (genetic programming, neural networks, Bayesian methods, etc.) attempt to eliminate the a priori need for such intuition but often do so with increased computational burden and human time. A recently developed technique in the field of signal processing, compressive sensing (CS), provides a simple, general, and efficient way of finding the key descriptive variables. CS is a powerful paradigm for model building; we show that its models are more physical and predict more accurately than current state-of-the-art approaches and can be constructed at a fraction of the computational cost and user effort.

  16. Understanding obsolescence: a conceptual model for buildings

    NARCIS (Netherlands)

    Thomsen, A.; Van der Flier, K.

    2011-01-01

    What is obsolescence? Numerous older buildings have been demolished due to being labelled as obsolete. There is a general understanding that buildings, similar to machinery and durable consumer goods, should be demolished and replaced when they become obsolete. The truth of this assertion is examine

  17. Understanding obsolescence: a conceptual model for buildings

    NARCIS (Netherlands)

    Thomsen, A.; Van der Flier, K.

    2011-01-01

    What is obsolescence? Numerous older buildings have been demolished due to being labelled as obsolete. There is a general understanding that buildings, similar to machinery and durable consumer goods, should be demolished and replaced when they become obsolete. The truth of this assertion is

  18. Iterative model-building, structure refinement, and density modification with the PHENIX AutoBuild Wizard

    Energy Technology Data Exchange (ETDEWEB)

    Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA; Lawrence Berkeley National Laboratory, One Cyclotron Road, Building 64R0121, Berkeley, CA 94720, USA; Department of Haematology, University of Cambridge, Cambridge CB2 0XY, England; Terwilliger, Thomas; Terwilliger, T.C.; Grosse-Kunstleve, Ralf Wilhelm; Afonine, P.V.; Moriarty, N.W.; Zwart, P.H.; Hung, L.-W.; Read, R.J.; Adams, P.D.

    2007-04-29

    The PHENIX AutoBuild Wizard is a highly automated tool for iterative model-building, structure refinement and density modification using RESOLVE or TEXTAL model-building, RESOLVE statistical density modification, and phenix.refine structure refinement. Recent advances in the AutoBuild Wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model completion algorithms, and automated solvent molecule picking. Model completion algorithms in the AutoBuild Wizard include loop-building, crossovers between chains in different models of a structure, and side-chain optimization. The AutoBuild Wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 {angstrom} to 3.2 {angstrom}, resulting in a mean R-factor of 0.24 and a mean free R factor of 0.29. The R-factor of the final model is dependent on the quality of the starting electron density, and relatively independent of resolution.

  19. Vibration Response of Multi Storey Building Using Finite Element Modelling

    Science.gov (United States)

    Chik, T. N. T.; Zakaria, M. F.; Remali, M. A.; Yusoff, N. A.

    2016-07-01

    Interaction between building, type of foundation and the geotechnical parameter of ground may trigger a significant effect on the building. In general, stiffer foundations resulted in higher natural frequencies of the building-soil system and higher input frequencies are often associated with other ground. Usually, vibrations transmitted to the buildings by ground borne are often noticeable and can be felt. It might affect the building and become worse if the vibration level is not controlled. UTHM building is prone to the ground borne vibration due to closed distance from the main road, and the construction activities adjacent to the buildings. This paper investigates the natural frequency and vibration mode of multi storey office building with the presence of foundation system and comparison between both systems. Finite element modelling (FEM) package software of LUSAS is used to perform the vibration analysis of the building. The building is modelled based on the original plan with the foundation system on the structure model. The FEM results indicated that the structure which modelled with rigid base have high natural frequency compare to the structure with foundation system. These maybe due to soil structure interaction and also the damping of the system which related to the amount of energy dissipated through the foundation soil. Thus, this paper suggested that modelling with soil is necessary to demonstrate the soil influence towards vibration response to the structure.

  20. Modeling thermally active building components using space mapping

    DEFF Research Database (Denmark)

    Pedersen, Frank; Weitzmann, Peter; Svendsen, Svend

    2005-01-01

    In order to efficiently implement thermally active building components in new buildings, it is necessary to evaluate the thermal interaction between them and other building components. Applying parameter investigation or numerical optimization methods to a differential-algebraic (DAE) model....... This paper describes the principle of the space mapping technique, and introduces a simple space mapping technique. The technique is applied to a lumped parameter model of a thermo active component, which provides a model of the thermal performance of the component as a function of two design parameters...... of a building provides a systematic way of estimating efficient building designs. However, using detailed numerical calculations of the components in the building is a time consuming process, which may become prohibitive if the DAE model is to be used for parameter variation or optimization. Unfortunately...

  1. Statistical models describing the energy signature of buildings

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Thavlov, Anders

    2010-01-01

    Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i.......e. the heat dynamics of the building, have been developed. The models can be used to obtain rather detailed knowledge of the energy performance of the building and to optimize the control of the energy consumption for heating, which will be vital in conditions with increasing fluctuation of the energy supply...... or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as UA...

  2. Complementarity of Historic Building Information Modelling and Geographic Information Systems

    Science.gov (United States)

    Yang, X.; Koehl, M.; Grussenmeyer, P.; Macher, H.

    2016-06-01

    In this paper, we discuss the potential of integrating both semantically rich models from Building Information Modelling (BIM) and Geographical Information Systems (GIS) to build the detailed 3D historic model. BIM contributes to the creation of a digital representation having all physical and functional building characteristics in several dimensions, as e.g. XYZ (3D), time and non-architectural information that are necessary for construction and management of buildings. GIS has potential in handling and managing spatial data especially exploring spatial relationships and is widely used in urban modelling. However, when considering heritage modelling, the specificity of irregular historical components makes it problematic to create the enriched model according to its complex architectural elements obtained from point clouds. Therefore, some open issues limiting the historic building 3D modelling will be discussed in this paper: how to deal with the complex elements composing historic buildings in BIM and GIS environment, how to build the enriched historic model, and why to construct different levels of details? By solving these problems, conceptualization, documentation and analysis of enriched Historic Building Information Modelling are developed and compared to traditional 3D models aimed primarily for visualization.

  3. Environmental sustainability modeling with exergy methodology for building life cycle

    Institute of Scientific and Technical Information of China (English)

    刘猛; 姚润明

    2009-01-01

    As an important human activity,the building industry has created comfortable space for living and work,and at the same time brought considerable pollution and huge consumption of energy and recourses. From 1990s after the first building environmental assessment model-BREEAM was released in the UK,a number of assessment models were formulated as analytical and practical in methodology respectively. This paper aims to introduce a generic model of exergy assessment on environmental impact of building life cycle,taking into consideration of previous models and focusing on natural environment as well as building life cycle,and three environmental impacts will be analyzed,namely energy embodied exergy,resource chemical exergy and abatement exergy on energy consumption,resource consumption and pollutant discharge respectively. The model of exergy assessment on environmental impact of building life cycle thus formulated contains two sub-models,one from the aspect of building energy utilization,and the other from building materials use. Combining theories by ecologists such as Odum,building environmental sustainability modeling with exergy methodology is put forward with the index of exergy footprint of building environmental impacts.

  4. Building Energy Model Development for Retrofit Homes

    Energy Technology Data Exchange (ETDEWEB)

    Chasar, David; McIlvaine, Janet; Blanchard, Jeremy; Widder, Sarah H.; Baechler, Michael C.

    2012-09-30

    Based on previous research conducted by Pacific Northwest National Laboratory and Florida Solar Energy Center providing technical assistance to implement 22 deep energy retrofits across the nation, 6 homes were selected in Florida and Texas for detailed post-retrofit energy modeling to assess realized energy savings (Chandra et al, 2012). However, assessing realized savings can be difficult for some homes where pre-retrofit occupancy and energy performance are unknown. Initially, savings had been estimated using a HERS Index comparison for these homes. However, this does not account for confounding factors such as occupancy and weather. This research addresses a method to more reliably assess energy savings achieved in deep energy retrofits for which pre-retrofit utility bills or occupancy information in not available. A metered home, Riverdale, was selected as a test case for development of a modeling procedure to account occupancy and weather factors, potentially creating more accurate estimates of energy savings. This “true up” procedure was developed using Energy Gauge USA software and post-retrofit homeowner information and utility bills. The 12 step process adjusts the post-retrofit modeling results to correlate with post-retrofit utility bills and known occupancy information. The “trued” post retrofit model is then used to estimate pre-retrofit energy consumption by changing the building efficiency characteristics to reflect the pre-retrofit condition, but keeping all weather and occupancy-related factors the same. This creates a pre-retrofit model that is more comparable to the post-retrofit energy use profile and can improve energy savings estimates. For this test case, a home for which pre- and post- retrofit utility bills were available was selected for comparison and assessment of the accuracy of the “true up” procedure. Based on the current method, this procedure is quite time intensive. However, streamlined processing spreadsheets or

  5. Predicting the Texas Windstorm Insurance Association claim payout of commercial buildings from Hurricane Ike

    Directory of Open Access Journals (Sweden)

    J. M. Kim

    2013-08-01

    Full Text Available Following growing public awareness of the danger from hurricanes and tremendous demands for analysis of loss, many researchers have conducted studies to develop hurricane damage analysis methods. Although researchers have identified the significant indicators, there currently is no comprehensive research for identifying the relationship among the vulnerabilities, natural disasters, and economic losses associated with individual buildings. To address this lack of research, this study will identify vulnerabilities and hurricane indicators, develop metrics to measure the influence of economic losses from hurricanes, and visualize the spatial distribution of vulnerability to evaluate overall hurricane damage. This paper has utilized the Geographic Information System to facilitate collecting and managing data, and has combined vulnerability factors to assess the financial losses suffered by Texas coastal counties. A multiple linear regression method has been applied to develop hurricane economic damage predicting models. To reflect the pecuniary loss, insured loss payment was used as the dependent variable to predict the actual financial damage. Geographical vulnerability indicators, built environment vulnerability indicators, and hurricane indicators were all used as independent variables. Accordingly, the models and findings may possibly provide vital references for government agencies, emergency planners, and insurance companies hoping to predict hurricane damage.

  6. Issues of Application of Machine Learning Models for Virtual and Real-Life Buildings

    Directory of Open Access Journals (Sweden)

    Young Min Kim

    2016-06-01

    Full Text Available The current Building Energy Performance Simulation (BEPS tools are based on first principles. For the correct use of BEPS tools, simulationists should have an in-depth understanding of building physics, numerical methods, control logics of building systems, etc. However, it takes significant time and effort to develop a first principles-based simulation model for existing buildings—mainly due to the laborious process of data gathering, uncertain inputs, model calibration, etc. Rather than resorting to an expert’s effort, a data-driven approach (so-called “inverse” approach has received growing attention for the simulation of existing buildings. This paper reports a cross-comparison of three popular machine learning models (Artificial Neural Network (ANN, Support Vector Machine (SVM, and Gaussian Process (GP for predicting a chiller’s energy consumption in a virtual and a real-life building. The predictions based on the three models are sufficiently accurate compared to the virtual and real measurements. This paper addresses the following issues for the successful development of machine learning models: reproducibility, selection of inputs, training period, outlying data obtained from the building energy management system (BEMS, and validation of the models. From the result of this comparative study, it was found that SVM has a disadvantage in computation time compared to ANN and GP. GP is the most sensitive to a training period among the three models.

  7. Building

    OpenAIRE

    Seavy, Ryan

    2014-01-01

    Building for concrete is temporary. The building of wood and steel stands against the concrete to give form and then gives way, leaving a trace of its existence behind. Concrete is not a building material. One does not build with concrete. One builds for concrete. MARCH

  8. Building a generalized distributed system model

    Science.gov (United States)

    Mukkamala, R.

    1992-01-01

    The key elements in the second year (1991-92) of our project are: (1) implementation of the distributed system prototype; (2) successful passing of the candidacy examination and a PhD proposal acceptance by the funded student; (3) design of storage efficient schemes for replicated distributed systems; and (4) modeling of gracefully degrading reliable computing systems. In the third year of the project (1992-93), we propose to: (1) complete the testing of the prototype; (2) enhance the functionality of the modules by enabling the experimentation with more complex protocols; (3) use the prototype to verify the theoretically predicted performance of locking protocols, etc.; and (4) work on issues related to real-time distributed systems. This should result in efficient protocols for these systems.

  9. 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.

  10. Toward Building a New Seismic Hazard Model for Mainland China

    Science.gov (United States)

    Rong, Y.; Xu, X.; Chen, G.; Cheng, J.; Magistrale, H.; Shen, Z.

    2015-12-01

    At present, the only publicly available seismic hazard model for mainland China was generated by Global Seismic Hazard Assessment Program in 1999. We are building a new seismic hazard model by integrating historical earthquake catalogs, geological faults, geodetic GPS data, and geology maps. To build the model, we construct an Mw-based homogeneous historical earthquake catalog spanning from 780 B.C. to present, create fault models from active fault data using the methodology recommended by Global Earthquake Model (GEM), and derive a strain rate map based on the most complete GPS measurements and a new strain derivation algorithm. We divide China and the surrounding regions into about 20 large seismic source zones based on seismotectonics. For each zone, we use the tapered Gutenberg-Richter (TGR) relationship to model the seismicity rates. We estimate the TGR a- and b-values from the historical earthquake data, and constrain corner magnitude using the seismic moment rate derived from the strain rate. From the TGR distributions, 10,000 to 100,000 years of synthetic earthquakes are simulated. Then, we distribute small and medium earthquakes according to locations and magnitudes of historical earthquakes. Some large earthquakes are distributed on active faults based on characteristics of the faults, including slip rate, fault length and width, and paleoseismic data, and the rest to the background based on the distributions of historical earthquakes and strain rate. We evaluate available ground motion prediction equations (GMPE) by comparison to observed ground motions. To apply appropriate GMPEs, we divide the region into active and stable tectonics. The seismic hazard will be calculated using the OpenQuake software developed by GEM. To account for site amplifications, we construct a site condition map based on geology maps. The resulting new seismic hazard map can be used for seismic risk analysis and management, and business and land-use planning.

  11. Modelling energy demand in the buildings sector within the EU

    Energy Technology Data Exchange (ETDEWEB)

    O Broin, Eoin

    2012-11-01

    fuel mixes are applied in three scenarios. The rates for expansion of floor area and increases in living standards are the same for all the scenarios. The model outputs predict that if energy efficiency remains at the current level, then expansion of the building floor area and other increases in living standards would increase final energy demand in the EU by almost 70 % by 2050. The other two scenarios reveal the levels of improvements in efficiency that are needed to maintain energy demand at current rates or reduce it by 20 %. The results of the modelling provide a conceptual framework for the development of fiscal and regulatory policy decisions in relation to energy prices and various categories of energy efficiency measures, with the overall objective of meeting future demand for energy services of the building sector within the EU in a sustainable manner.

  12. Rhode Island Model Evaluation & Support System: Building Administrator. Edition III

    Science.gov (United States)

    Rhode Island Department of Education, 2015

    2015-01-01

    Rhode Island educators believe that implementing a fair, accurate, and meaningful educator evaluation and support system will help improve teaching, learning, and school leadership. The primary purpose of the Rhode Island Model Building Administrator Evaluation and Support System (Rhode Island Model) is to help all building administrators improve.…

  13. DEVELOPING PARAMETRIC BUILDING MODELS – THE GANDIS USE CASE

    Directory of Open Access Journals (Sweden)

    W. Thaller

    2012-09-01

    Full Text Available In the course of a project related to green building design, we have created a group of eight parametric building models that can be manipulated interactively with respect to dimensions, number of floors, and a few other parameters. We report on the commonalities and differences between the models and the abstractions that we were able to identify.

  14. Working group report: Flavor physics and model building

    Indian Academy of Sciences (India)

    M K Parida; Nita Sinha; B Adhikary; B Allanach; A Alok; K S Babu; B Brahmachari; D Choudhury; E J Chun; P K Das; A Ghosal; D Hitlin; W S Hou; S Kumar; H N Li; E Ma; S K Majee; G Majumdar; B Mishra; G Mohanty; S Nandi; H Pas; M K Parida; S D Rindani; J P Saha; N Sahu; Y Sakai; S Sen; C Sharma; C D Sharma; S Shalgar; N N Singh; S Uma Sankar; N Sinha; R Sinha; F Simonetto; R Srikanth; R Vaidya

    2006-11-01

    This is the report of flavor physics and model building working group at WHEPP-9. While activities in flavor physics have been mainly focused on -physics, those in model building have been primarily devoted to neutrino physics. We present summary of working group discussions carried out during the workshop in the above fields, and also briefly review the progress made in some projects subsequently

  15. Predicting wind-induced vibrations of high-rise buildings using unsteady CFD and modal analysis

    KAUST Repository

    Zhang, Yue

    2015-01-01

    This paper investigates the wind-induced vibration of the CAARC standard tall building model, via unsteady Computational Fluid Dynamics (CFD) and a structural modal analysis. In this numerical procedure, the natural unsteady wind in the atmospheric boundary layer is modeled with an artificial inflow turbulence generation method. Then, the turbulent flow is simulated by the second mode of a Zonal Detached-Eddy Simulation, and a conservative quadrature-projection scheme is adopted to transfer unsteady loads from fluid to structural nodes. The aerodynamic damping that represents the fluid-structure interaction mechanism is determined by empirical functions extracted from wind tunnel experiments. Eventually, the flow solutions and the structural responses in terms of mean and root mean square quantities are compared with experimental measurements, over a wide range of reduced velocities. The significance of turbulent inflow conditions and aeroelastic effects is highlighted. The current methodology provides predictions of good accuracy and can be considered as a preliminary design tool to evaluate the unsteady wind effects on tall buildings.

  16. Novel transformation-based response prediction of shear building using interval neural network

    Indian Academy of Sciences (India)

    S Chakraverty; Deepti Moyi Sahoo

    2017-04-01

    Present paper uses powerful technique of interval neural network (INN) to simulate and estimate structural response of multi-storey shear buildings subject to earthquake motion. The INN is first trained for a real earthquake data, viz., the ground acceleration as input and the numerically generated responses of different floors of multi-storey buildings as output. Till date, no model exists to handle positive and negative data in the INN. As such here, the bipolar data in [−1, 1] are converted first to unipolar form, i.e., to [0, 1] by means of a novel transformation for the first time to handle the above training patterns in normalized form. Once the training is done, again the unipolar data areconverted back to its bipolar form by using the inverse transformation. The trained INN architecture is then used to simulate and test the structural response of different floors for various intensity earthquake data and it is found that the predicted responses given by INN model are good for practical purposes.

  17. Method for modelling space conditioning aggregated daily load curves: Application to a university building

    Energy Technology Data Exchange (ETDEWEB)

    Escriva-Escriva, Guillermo; Alvarez-Bel, Carlos; Valencia-Salazar, Ivan [Institute for Energy Engineering, Universidad Politecnica de Valencia, Camino de Vera, s/n, edificio 8E, escalera F, 2a planta, 46022 Valencia (Spain)

    2010-08-15

    Physically based load modelling methodologies have been widely developed and used because of their ability to predict the energy load dynamic response. Most building energy programs predict energy consumption and energy system performance through a whole building energy simulation as well as a global analysis of building thermal processes and heating, ventilation and air-conditioning (HVAC) system performance. A different approach is presented in this paper by introducing a new method for modelling the daily load profile of a group of air-conditioning systems. This method is based on the simulation of a single HVAC system, a set of end-use electrical measurements, and a detailed walk-through and energy audit. The basic methodology allows deducing the aggregated load of a group of space conditioning devices by the addition of the daily simulation of each individual physical system. As an application, the space conditioning daily demand curve of a university building is studied and results are presented. (author)

  18. A new methodology for building energy benchmarking: An approach based on clustering concept and statistical models

    Science.gov (United States)

    Gao, Xuefeng

    Though many building energy benchmarking programs have been developed during the past decades, they hold certain limitations. The major concern is that they may cause misleading benchmarking due to not fully considering the impacts of the multiple features of buildings on energy performance. The existing methods classify buildings according to only one of many features of buildings -- the use type, which may result in a comparison between two buildings that are tremendously different in other features and not properly comparable as a result. This research aims to tackle this challenge by proposing a new methodology based on the clustering concept and statistical analysis. The clustering concept, which reflects on machine learning algorithms, classifies buildings based on a multi-dimensional domain of building features, rather than the single dimension of use type. Buildings with the greatest similarity of features that influence energy performance are classified into the same cluster, and benchmarked according to the centroid reference of the cluster. Statistical analysis is applied to find the most influential features impacting building energy performance, as well as provide prediction models for the new design energy consumption. The proposed methodology as applicable to both existing building benchmarking and new design benchmarking was discussed in this dissertation. The former contains four steps: feature selection, clustering algorithm adaptation, results validation, and interpretation. The latter consists of three parts: data observation, inverse modeling, and forward modeling. The experimentation and validation were carried out for both perspectives. It was shown that the proposed methodology could account for the total building energy performance and was able to provide a more comprehensive approach to benchmarking. In addition, the multi-dimensional clustering concept enables energy benchmarking among different types of buildings, and inspires a new

  19. Empirical data validation for model building

    Science.gov (United States)

    Kazarian, Aram

    2008-03-01

    Optical Proximity Correction (OPC) has become an integral and critical part of process development for advanced technologies with challenging k I requirements. OPC solutions in turn require stable, predictive models to be built that can project the behavior of all structures. These structures must comprehend all geometries that can occur in the layout in order to define the optimal corrections by feature, and thus enable a manufacturing process with acceptable margin. The model is built upon two main component blocks. First, is knowledge of the process conditions which includes the optical parameters (e.g. illumination source, wavelength, lens characteristics, etc) as well as mask definition, resist parameters and process film stack information. Second, is the empirical critical dimension (CD) data collected using this process on specific test features the results of which are used to fit and validate the model and to project resist contours for all allowable feature layouts. The quality of the model therefore is highly dependent on the integrity of the process data collected for this purpose. Since the test pattern suite generally extends to below the resolution limit that the process can support with adequate latitude, the CD measurements collected can often be quite noisy with marginal signal-to-noise ratios. In order for the model to be reliable and a best representation of the process behavior, it is necessary to scrutinize empirical data to ensure that it is not dominated by measurement noise or flyer/outlier points. The primary approach for generating a clean, smooth and dependable empirical data set should be a replicated measurement sampling that can help to statistically reduce measurement noise by averaging. However, it can often be impractical to collect the amount of data needed to ensure a clean data set by this method. An alternate approach is studied in this paper to further smooth the measured data by means of curve fitting to identify remaining

  20. 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

  1. The optimal solution prediction for genetic and distribution building algorithms with binary representation

    Science.gov (United States)

    Sopov, E.; Semenkina, O.

    2015-01-01

    Genetic and distribution building algorithms with binary representation are analyzed. A property of convergence to the optimal solution is discussed. A novel convergence prediction method is proposed and investigated. The method is based on analysis of gene value probabilities distribution dynamics, thus it can predict gene values of the optimal solution to which the algorithm converges. The results of investigations for the optimal prediction algorithm performance are presented.

  2. Reducing the operational energy demand in buildings using building information modeling tools and sustainability approaches

    Directory of Open Access Journals (Sweden)

    Mojtaba Valinejad Shoubi

    2015-03-01

    Full Text Available A sustainable building is constructed of materials that could decrease environmental impacts, such as energy usage, during the lifecycle of the building. Building Information Modeling (BIM has been identified as an effective tool for building performance analysis virtually in the design stage. The main aims of this study were to assess various combinations of materials using BIM and identify alternative, sustainable solutions to reduce operational energy consumption. The amount of energy consumed by a double story bungalow house in Johor, Malaysia, and assessments of alternative material configurations to determine the best energy performance were evaluated by using Revit Architecture 2012 and Autodesk Ecotect Analysis software to show which of the materials helped in reducing the operational energy use of the building to the greatest extent throughout its annual life cycle. At the end, some alternative, sustainable designs in terms of energy savings have been suggested.

  3. Armagh Observatory - Historic Building Information Modelling for Virtual Learning in Building Conservation

    Science.gov (United States)

    Murphy, M.; Chenaux, A.; Keenaghan, G.; GIbson, V..; Butler, J.; Pybusr, C.

    2017-08-01

    In this paper the recording and design for a Virtual Reality Immersive Model of Armagh Observatory is presented, which will replicate the historic buildings and landscape with distant meridian markers and position of its principal historic instruments within a model of the night sky showing the position of bright stars. The virtual reality model can be used for educational purposes allowing the instruments within the historic building model to be manipulated within 3D space to demonstrate how the position measurements of stars were made in the 18th century. A description is given of current student and researchers activities concerning on-site recording and surveying and the virtual modelling of the buildings and landscape. This is followed by a design for a Virtual Reality Immersive Model of Armagh Observatory use game engine and virtual learning platforms and concepts.

  4. DEVELOPING VERIFICATION SYSTEMS FOR BUILDING INFORMATION MODELS OF HERITAGE BUILDINGS WITH HETEROGENEOUS DATASETS

    Directory of Open Access Journals (Sweden)

    L. Chow

    2017-08-01

    Full Text Available The digitization and abstraction of existing buildings into building information models requires the translation of heterogeneous datasets that may include CAD, technical reports, historic texts, archival drawings, terrestrial laser scanning, and photogrammetry into model elements. In this paper, we discuss a project undertaken by the Carleton Immersive Media Studio (CIMS that explored the synthesis of heterogeneous datasets for the development of a building information model (BIM for one of Canada’s most significant heritage assets – the Centre Block of the Parliament Hill National Historic Site. The scope of the project included the development of an as-found model of the century-old, six-story building in anticipation of specific model uses for an extensive rehabilitation program. The as-found Centre Block model was developed in Revit using primarily point cloud data from terrestrial laser scanning. The data was captured by CIMS in partnership with Heritage Conservation Services (HCS, Public Services and Procurement Canada (PSPC, using a Leica C10 and P40 (exterior and large interior spaces and a Faro Focus (small to mid-sized interior spaces. Secondary sources such as archival drawings, photographs, and technical reports were referenced in cases where point cloud data was not available. As a result of working with heterogeneous data sets, a verification system was introduced in order to communicate to model users/viewers the source of information for each building element within the model.

  5. Recurrent neural networks for building energy use prediction and system identification -- A progress report

    Energy Technology Data Exchange (ETDEWEB)

    Kreider, J.F.; Curtiss, P.; Dodier, R.; Krarti, M. [Univ. of Colorado, Boulder, CO (United States); Claridge, D.E.; Haberl, J.S. [Texas A and M Univ., College Station, TX (United States). Dept. of Mechanical Engineering

    1995-11-01

    Following several successful applications of feedforward neural networks (NNs) to the building energy prediction problem a more difficult problem has been addressed recently: namely, the prediction of building energy consumption well into the future without knowledge of immediately past energy consumption. This paper reports results of a recent study of six months of hourly data recorded at the Zachry Engineering Center (ZEC) in College Station, Texas. An early study demonstrated the success of NNs used as predictors for hourly consumption of electricity, chilled water and hot water for the ZEC. Relatively simple networks with less than a dozen inputs were able to predict these three hourly, whole building energy end uses to within errors of 5--10% RMS, the difference depending on the specifics of energy type and time of year. These predictions were made for selected future months given network training data of between one and three past months. Inputs to these networks included measured energy consumption for one or two immediately past hours. Such data are available, for example, if one is trying to conduct hourly diagnostics on heating, ventilating and air conditioning (HVAC) systems in commercial buildings. The success of this study prompted a second study of a more difficult problem. In this case, the goal was to predict energy consumption into the future without knowledge of consumption of the various energies for the immediate past. Such a prediction is of value when estimating what a building, retrofitted with energy conservation features, would have consumed had it not been retrofitted. This prediction can be compared to actual consumption to estimate the savings, if any, that accrue due to the installation of the energy conservation subsystems or components. Because one is predicting for several months, not for one hour, into the future, the problem is more difficult. Results presented show that recurrent NNs can be used for this prediction task.

  6. Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents

    Energy Technology Data Exchange (ETDEWEB)

    Sanyal, Jibonananda [ORNL; New, Joshua Ryan [ORNL; Edwards, Richard [ORNL; Parker, Lynne Edwards [ORNL

    2014-01-01

    Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the Autotune research which employs machine learning algorithms to generate agents for the different kinds of standard reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.

  7. Procedure to predict the storey where plastic drift dominates in two-storey building under strong ground motion

    DEFF Research Database (Denmark)

    Hibino, Y.; Ichinose, T.; Costa, J.L.D.

    2009-01-01

    A procedure is presented to predict the storey where plastic drift dominates in two-storey buildings under strong ground motion. The procedure utilizes the yield strength and the mass of each storey as well as the peak ground acceleration. The procedure is based on two different assumptions: (1....... The efficiency of the procedure is verified by dynamic response analyses using elasto-plastic model....

  8. Energy Savings Modeling of Standard Commercial Building Re-tuning Measures: Large Office Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Fernandez, Nicholas; Katipamula, Srinivas; Wang, Weimin; Huang, Yunzhi; Liu, Guopeng

    2012-06-01

    Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS's capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This report investigates the energy savings potential of several common HVAC system retuning measures on a typical large office building prototype model, using the Department of Energy's building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated - each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All of these measures and combinations were simulated in 16 cities representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy

  9. NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

    Science.gov (United States)

    Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.

    2013-01-01

    A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

  10. 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.

  11. Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity.

    Science.gov (United States)

    Ng, Kenney; Sun, Jimeng; Hu, Jianying; Wang, Fei

    2015-01-01

    Personalized predictive models are customized for an individual patient and trained using information from similar patients. Compared to global models trained on all patients, they have the potential to produce more accurate risk scores and capture more relevant risk factors for individual patients. This paper presents an approach for building personalized predictive models and generating personalized risk factor profiles. A locally supervised metric learning (LSML) similarity measure is trained for diabetes onset and used to find clinically similar patients. Personalized risk profiles are created by analyzing the parameters of the trained personalized logistic regression models. A 15,000 patient data set, derived from electronic health records, is used to evaluate the approach. The predictive results show that the personalized models can outperform the global model. Cluster analysis of the risk profiles show groups of patients with similar risk factors, differences in the top risk factors for different groups of patients and differences between the individual and global risk factors.

  12. Integrating Building Information Modeling and Augmented Reality to Improve Investigation of Historical Buildings

    Directory of Open Access Journals (Sweden)

    Francesco Chionna

    2015-12-01

    Full Text Available This paper describes an experimental system to support investigation of historical buildings using Building Information Modeling (BIM and Augmented Reality (AR. The system requires the use of an off-line software to build the BIM representation and defines a method to integrate diagnostic data into BIM. The system offers access to such information during site investigation using AR glasses supported by marker and marker-less technologies. The main innovation is the possibility to contextualize through AR not only existing BIM properties but also results from non-invasive tools. User evaluations show how the use of the system may enhance the perception of engineers during the investigation process.

  13. Whole-Building Hygrothermal Modeling in IEA Annex 41

    DEFF Research Database (Denmark)

    Rode, Carsten; Woloszyn, Monika

    2007-01-01

    . The IEA Annex 41 project runs from 2004–2007, coming to conclusion just before the Thermal Performance of the Exterior Envelopes of Whole Buildings X conference. The Annex 41 project and its Subtask 1 do not aim to produce one state-of-the-art hygrothermal simulation model for whole buildings, but rather...

  14. Making Connections to the "Real World": A Model Building Lesson

    Science.gov (United States)

    Horibe, Shusaku; Underwood, Bret

    2009-01-01

    Classroom activities that include the process of model building, in which students build simplified physical representations of a system, have the potential to help students make meaningful connections between physics and the real world. We describe a lesson designed with this intent for an introductory college classroom that engages students in…

  15. Modelling Technology for Building Fire Scene with Virtual Geographic Environment

    Science.gov (United States)

    Song, Y.; Zhao, L.; Wei, M.; Zhang, H.; Liu, W.

    2017-09-01

    Building fire is a risky activity that can lead to disaster and massive destruction. The management and disposal of building fire has always attracted much interest from researchers. Integrated Virtual Geographic Environment (VGE) is a good choice for building fire safety management and emergency decisions, in which a more real and rich fire process can be computed and obtained dynamically, and the results of fire simulations and analyses can be much more accurate as well. To modelling building fire scene with VGE, the application requirements and modelling objective of building fire scene were analysed in this paper. Then, the four core elements of modelling building fire scene (the building space environment, the fire event, the indoor Fire Extinguishing System (FES) and the indoor crowd) were implemented, and the relationship between the elements was discussed also. Finally, with the theory and framework of VGE, the technology of building fire scene system with VGE was designed within the data environment, the model environment, the expression environment, and the collaborative environment as well. The functions and key techniques in each environment are also analysed, which may provide a reference for further development and other research on VGE.

  16. Modelling the heat dynamics of a residential building unit: Application to Norwegian buildings

    Directory of Open Access Journals (Sweden)

    D.W.U. Perera

    2014-01-01

    Full Text Available The paper refers to the development of a continuous time mathematical heating model for a building unit based on the first principles. The model is described in terms of the state space variables, and a lumped parameter approach is used to represent the room air temperature and air density using mass and energy balances. The one-dimensional heat equation in cartesian coordinates and spherical coordinates is discretized in order to describe the thermic characteristics of the layers of the building framework and furniture respectively. The developed model is implemented in a MATLAB environment, and mainly a theoretical approach is used to validate it for a residential building unit. Model is also validated using experimental data for a limited period. Short term simulations are used to test the energy efficiency of the building unit with regard to factors such as the operation of heat sources, ventilation, occupancy patterns of people, weather conditions, features of the building structure and heat recovery. The results are consistent and are obtained considerably fast, implying that the model can be used further in modelling the heating dynamics of complex architectural designs and in control applications.

  17. Prediction of Noise Transmission in Lightweight Building Structures

    DEFF Research Database (Denmark)

    Dickow, Kristoffer Ahrens

    groups, where one group shows pass band/stop band behavior, while the other has a nearly uniform distribution of modes. The suggested approach for SEA adaptation is to consider a ribbed plate as two SEA subsystems: One that contains modes related to waves traveling in the direction orthogonal to the ribs......, while the other subsystem contains modes related to waves traveling parallel to the rib stiffeners. The investigations utilize Monte Carlo simulations to examine the behavior of nominally identical plates. Next, two papers that utilize the Finite-Element Method, focusing on aspects of modeling ribbed...... full three-dimensional, solid continuum finite-elements. When using structural elements such as beams and shells, couplings may be modeled as either line or point coupling. However, when utilizing full three-dimensional, solid finite-elements, the scenario is not that simple. The investigations of both...

  18. Extension of the PMV model to non-air-conditioned building in warm climates

    DEFF Research Database (Denmark)

    Fanger, Povl Ole; Toftum, Jørn

    2002-01-01

    The PMV model agrees well with high-quality field studies in buildings with HVAC systems, situated in cold, temperate and warm climates, studied during both summer and winter. In non-air-conditioned buildings in warm climates, occupants may sense the warmth as being less severe than the PMV...... predicts. The main reason is low expectations, but a metabolic rate that is estimated too high can also contribute to explaining the difference. An extension of the PMV model that includes an expectancy factor is introduced for use in non-air-conditioned buildings in warm climates. The extended PMV model...... agrees well with quality field studies in non-air-conditioned buildings of three continents....

  19. Building Component Library: An Online Repository to Facilitate Building Energy Model Creation; Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Fleming, K.; Long, N.; Swindler, A.

    2012-05-01

    This paper describes the Building Component Library (BCL), the U.S. Department of Energy's (DOE) online repository of building components that can be directly used to create energy models. This comprehensive, searchable library consists of components and measures as well as the metadata which describes them. The library is also designed to allow contributors to easily add new components, providing a continuously growing, standardized list of components for users to draw upon.

  20. 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.

  1. D Topological Indoor Building Modeling Integrated with Open Street Map

    Science.gov (United States)

    Jamali, A.; Rahman, A. Abdul; Boguslawski, P.

    2016-09-01

    Considering various fields of applications for building surveying and various demands, geometry representation of a building is the most crucial aspect of a building survey. The interiors of the buildings need to be described along with the relative locations of the rooms, corridors, doors and exits in many kinds of emergency response, such as fire, bombs, smoke, and pollution. Topological representation is a challenging task within the Geography Information Science (GIS) environment, as the data structures required to express these relationships are particularly difficult to develop. Even within the Computer Aided Design (CAD) community, the structures for expressing the relationships between adjacent building parts are complex and often incomplete. In this paper, an integration of 3D topological indoor building modeling in Dual Half Edge (DHE) data structure and outdoor navigation network from Open Street Map (OSM) is presented.

  2. The Dutch sustainable building policy: A model for developing countries?

    Energy Technology Data Exchange (ETDEWEB)

    Melchert, Luciana [Faculty of Architecture and Urbanism, University of Sao Paulo, Rua do Lago, 876, CEP 05508.900, Sao Paulo SP (Brazil)

    2007-02-15

    This article explores the institutionalization of environmental policies in the Dutch building sector and the applicability of the current model to developing countries. First, it analyzes the transition of sustainable building practices in the Netherlands from the 1970s until today, exploring how these were originally embedded in a discourse on 'de-modernization', which attempted to improve the environmental performance of building stocks by means of self-sufficient technologies, whereas nowadays they adopt a framework of 'ecological modernization', with integrative approaches seeking to improve the environmental performance of building stocks through more efficient-rather than self-sufficient-technologies. The study subsequently shows how the current Dutch sustainable building framework has thereby managed to achieve a pragmatic and widely accepted rationale, which can serve to orient the ecological restructuring of building stocks in developing countries. (author)

  3. Guidelines for Using Building Information Modeling for Energy Analysis of Buildings

    Directory of Open Access Journals (Sweden)

    Thomas Reeves

    2015-12-01

    Full Text Available Building energy modeling (BEM, a subset of building information modeling (BIM, integrates energy analysis into the design, construction, and operation and maintenance of buildings. As there are various existing BEM tools available, there is a need to evaluate the utility of these tools in various phases of the building lifecycle. The goal of this research was to develop guidelines for evaluation and selection of BEM tools to be used in particular building lifecycle phases. The objectives of this research were to: (1 Evaluate existing BEM tools; (2 Illustrate the application of the three BEM tools; (3 Re-evaluate the three BEM tools; and (4 Develop guidelines for evaluation, selection and application of BEM tools in the design, construction and operation/maintenance phases of buildings. Twelve BEM tools were initially evaluated using four criteria: interoperability, usability, available inputs, and available outputs. Each of the top three BEM tools selected based on this initial evaluation was used in a case study to simulate and evaluate energy usage, daylighting performance, and natural ventilation for two academic buildings (LEED-certified and non-LEED-certified. The results of the case study were used to re-evaluate the three BEM tools using the initial criteria with addition of the two new criteria (speed and accuracy, and to develop guidelines for evaluating and selecting BEM tools to analyze building energy performance. The major contribution of this research is the development of these guidelines that can help potential BEM users to identify the most appropriate BEM tool for application in particular building lifecycle phases.

  4. Transient Analysis and Performance Prediction of Nocturnal Radiative Cooling of a Building in Owerri, Nigeria

    Directory of Open Access Journals (Sweden)

    K.N. Nwaigwe

    2012-08-01

    Full Text Available A study aimed at a Transient analysis and performance prediction of passive cooling of a building using long wave nocturnal radiation in Owerri, Nigeria are presented. The system modeled consists of the room of a building with a radiator panel attached to its roof, water storage tank located inside the room, pump to circulate water through the radiator panel at night and through a heat exchanger in the room during the day. The mathematical model is based on the thermal radiation properties of the local atmosphere, the heat exchange equations of the radiator panel with the sky during the night and the equations incorporating the relevant heat transfers within the space to be cooled during the day. The resulting equations were transformed into explicit finite difference forms for easy implementation on a personal computer in MATLAB language. This numerical model permits the evaluation of the rate of heat removal from the water storage tank through the radiator panel surface area, Qwt,out, temperature depression between the ambient and room temperatures (Tamb-Trm and total heat gained by water in the storage tank from the space to be cooled through the action of the convector during the day, Qwt,in. The resulting rate of heat removal from the radiator gave a value of 57.6 W/m2, temperature depression was predicted to within 1-1.5ºC and the rate of heat gain by the storage water was 60 W/m2. A sensitivity analysis of the system parameters to ±25% of the base case input values was carried out and the results given as a percentage variation of the above system performance parameters showed consistency to the base case results. An optimal scheme for the modeled 3.0×3.0×2.5 m3 room showed a radiator area of 18.2 m2, a convector area of 28.62 m2 and a tank volume of 1.57 m3. These results show that passive nocturnal cooling technique is a promising solution to the cooling needs for preservation of food and other agricultural produce. It is also

  5. Structural Simulations and Conservation Analysis -Historic Building Information Model (HBIM

    Directory of Open Access Journals (Sweden)

    C. Dore

    2015-02-01

    Full Text Available In this paper the current findings to date of the Historic Building Information Model (HBIM of the Four Courts in Dublin are presented. The Historic Building Information Model (HBIM forms the basis for both structural and conservation analysis to measure the impact of war damage which still impacts on the building. The laser scan survey was carried out in the summer of 2014 of the internal and external structure. After registration and processing of the laser scan survey, the HBIM was created of the damaged section of the building and is presented as two separate workflows in this paper. The first is the model created from historic data, the second a procedural and segmented model developed from laser scan survey of the war damaged drum and dome. From both models structural damage and decay simulations will be developed for documentation and conservation analysis.

  6. Generating navigation models from existing building data

    NARCIS (Netherlands)

    Liu, L.; Zlatanova, S.

    2013-01-01

    Research on indoor navigation models mainly focuses on geometric and logical models .The models are enriched with specific semantic information which supports localisation, navigation and guidance. Geometric models provide information about the structural (physical) distribution of spaces in a

  7. Using connectome-based predictive modeling to predict individual behavior from brain connectivity.

    Science.gov (United States)

    Shen, Xilin; Finn, Emily S; Scheinost, Dustin; Rosenberg, Monica D; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

    2017-03-01

    Neuroimaging is a fast-developing research area in which anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale data sets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: (i) feature selection, (ii) feature summarization, (iii) model building, and (iv) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a considerable amount of the variance in these measures. It has been demonstrated that the CPM protocol performs as well as or better than many of the existing approaches in brain-behavior prediction. As CPM focuses on linear modeling and a purely data-driven approach, neuroscientists with limited or no experience in machine learning or optimization will find it easy to implement these protocols. Depending on the volume of data to be processed, the protocol can take 10-100 min for model building, 1-48 h for permutation testing, and 10-20 min for visualization of results.

  8. Online Model Learning of Buildings Using Stochastic Hybrid Systems Based on Gaussian Processes

    Directory of Open Access Journals (Sweden)

    Hamzah Abdel-Aziz

    2017-01-01

    Full Text Available Dynamical models are essential for model-based control methodologies which allow smart buildings to operate autonomously in an energy and cost efficient manner. However, buildings have complex thermal dynamics which are affected externally by the environment and internally by thermal loads such as equipment and occupancy. Moreover, the physical parameters of buildings may change over time as the buildings age or due to changes in the buildings’ configuration or structure. In this paper, we introduce an online model learning methodology to identify a nonparametric dynamical model for buildings when the thermal load is latent (i.e., the thermal load cannot be measured. The proposed model is based on stochastic hybrid systems, where the discrete state describes the level of the thermal load and the continuous dynamics represented by Gaussian processes describe the thermal dynamics of the air temperature. We demonstrate the evaluation of the proposed model using two-zone and five-zone buildings. The data for both experiments are generated using the EnergyPlus software. Experimental results show that the proposed model estimates the thermal load level correctly and predicts the thermal behavior with good performance.

  9. Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System

    Directory of Open Access Journals (Sweden)

    Lei He

    2016-01-01

    Full Text Available MPC has the ability to optimize the system operation parameters for energy conservation. Recently, it has been used in HVAC systems for saving energy, but there are very few applications in radiant cooling systems. To implement MPC in buildings with radiant terminals, the predictions of cooling load and thermal environment are indispensable. In this paper, a simplified thermal model is proposed for predicting cooling load and thermal environment in buildings with radiant floor. In this thermal model, the black-box model is introduced to derive the incident solar radiation, while the genetic algorithm is utilized to identify the parameters of the thermal model. In order to further validate this simplified thermal model, simulated results from TRNSYS are compared with those from this model and the deviation is evaluated based on coefficient of variation of root mean square (CV. The results show that the simplified model can predict the operative temperature with a CV lower than 1% and predict cooling loads with a CV lower than 10%. For the purpose of supervisory control in HVAC systems, this simplified RC thermal model has an acceptable accuracy and can be used for further MPC in buildings with radiation terminals.

  10. Jeddah Historical Building Information Modelling "JHBIM" - Object Library

    Science.gov (United States)

    Baik, A.; Alitany, A.; Boehm, J.; Robson, S.

    2014-05-01

    The theory of using Building Information Modelling "BIM" has been used in several Heritage places in the worldwide, in the case of conserving, documenting, managing, and creating full engineering drawings and information. However, one of the most serious issues that facing many experts in order to use the Historical Building Information Modelling "HBIM", is creating the complicated architectural elements of these Historical buildings. In fact, many of these outstanding architectural elements have been designed and created in the site to fit the exact location. Similarly, this issue has been faced the experts in Old Jeddah in order to use the BIM method for Old Jeddah historical Building. Moreover, The Saudi Arabian City has a long history as it contains large number of historic houses and buildings that were built since the 16th century. Furthermore, the BIM model of the historical building in Old Jeddah always take a lot of time, due to the unique of Hijazi architectural elements and no such elements library, which have been took a lot of time to be modelled. This paper will focus on building the Hijazi architectural elements library based on laser scanner and image survey data. This solution will reduce the time to complete the HBIM model and offering in depth and rich digital architectural elements library to be used in any heritage projects in Al-Balad district, Jeddah City.

  11. Scaling predictive modeling in drug development with cloud computing.

    Science.gov (United States)

    Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

    2015-01-26

    Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

  12. Jeddah Historical Building Information Modeling "JHBIM" Old Jeddah - Saudi Arabia

    Science.gov (United States)

    Baik, A.; Boehm, J.; Robson, S.

    2013-07-01

    The historic city of Jeddah faces serious issues in the conservation, documentation and recording of its valuable building stock. Terrestrial Laser Scanning and Architectural Photogrammetry have already been used in many Heritage sites in the world. The integration of heritage recording and Building Information Modelling (BIM) has been introduced as HBIM and is now a method to document and manage these buildings. In the last decade many traditional surveying methods were used to record the buildings in Old Jeddah. However, these methods take a long time, can sometimes provide unreliable information and often lack completeness. This paper will look at another approach for heritage recording by using the Jeddah Historical Building Information Modelling (JHBIM).

  13. Features of Functioning the Integrated Building Thermal Model

    Directory of Open Access Journals (Sweden)

    Morozov Maxim N.

    2017-01-01

    Full Text Available A model of the building heating system, consisting of energy source, a distributed automatic control system, elements of individual heating unit and heating system is designed. Application Simulink of mathematical package Matlab is selected as a platform for the model. There are the specialized application Simscape libraries in aggregate with a wide range of Matlab mathematical tools allow to apply the “acausal” modeling concept. Implementation the “physical” representation of the object model gave improving the accuracy of the models. Principle of operation and features of the functioning of the thermal model is described. The investigations of building cooling dynamics were carried out.

  14. Modelling the heat dynamics of buildings using stochastic

    DEFF Research Database (Denmark)

    Andersen, Klaus Kaae; Madsen, Henrik

    2000-01-01

    This paper describes the continuous time modelling of the heat dynamics of a building. The considered building is a residential like test house divided into two test rooms with a water based central heating. Each test room is divided into thermal zones in order to describe both short and long term...... variations. Besides modelling the heat transfer between thermal zones, attention is put on modelling the heat input from radiators and solar radiation. The applied modelling procedure is based on collected building performance data and statistical methods. The statistical methods are used in parameter...... estimation and model validation, while physical knowledge is used in forming the model structure. The suggested lumped parameter model is thus based on thermodynamics and formulated as a system of stochastic differential equations. Due to the continuous time formulation the parameters of the model...

  15. Artificial intelligence support for scientific model-building

    Science.gov (United States)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  16. 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...

  17. Communicate and collaborate by using building information modeling

    DEFF Research Database (Denmark)

    Mondrup, Thomas Fænø; Karlshøj, Jan; Vestergaard, Flemming

    Building Information Modeling (BIM) represents a new approach within the Architecture, Engineering, and Construction (AEC) industry, one that encourages collaboration and engagement of all stakeholders on a project. This study discusses the potential of adopting BIM as a communication...

  18. A procedure for Building Product Models

    DEFF Research Database (Denmark)

    Hvam, Lars

    1999-01-01

    , easily adaptable concepts and methods from data modeling (object oriented analysis) and domain modeling (product modeling). The concepts are general and can be used for modeling all types of specifications in the different phases in the product life cycle. The modeling techniques presented have been...

  19. Prediction error, ketamine and psychosis: An updated model.

    Science.gov (United States)

    Corlett, Philip R; Honey, Garry D; Fletcher, Paul C

    2016-11-01

    In 2007, we proposed an explanation of delusion formation as aberrant prediction error-driven associative learning. Further, we argued that the NMDA receptor antagonist ketamine provided a good model for this process. Subsequently, we validated the model in patients with psychosis, relating aberrant prediction error signals to delusion severity. During the ensuing period, we have developed these ideas, drawing on the simple principle that brains build a model of the world and refine it by minimising prediction errors, as well as using it to guide perceptual inferences. While previously we focused on the prediction error signal per se, an updated view takes into account its precision, as well as the precision of prior expectations. With this expanded perspective, we see several possible routes to psychotic symptoms - which may explain the heterogeneity of psychotic illness, as well as the fact that other drugs, with different pharmacological actions, can produce psychotomimetic effects. In this article, we review the basic principles of this model and highlight specific ways in which prediction errors can be perturbed, in particular considering the reliability and uncertainty of predictions. The expanded model explains hallucinations as perturbations of the uncertainty mediated balance between expectation and prediction error. Here, expectations dominate and create perceptions by suppressing or ignoring actual inputs. Negative symptoms may arise due to poor reliability of predictions in service of action. By mapping from biology to belief and perception, the account proffers new explanations of psychosis. However, challenges remain. We attempt to address some of these concerns and suggest future directions, incorporating other symptoms into the model, building towards better understanding of psychosis. © The Author(s) 2016.

  20. BIM-enabled Conceptual Modelling and Representation of Building Circulation

    Directory of Open Access Journals (Sweden)

    Jin Kook Lee

    2014-08-01

    Full Text Available This paper describes how a building information modelling (BIM-based approach for building circulation enables us to change the process of building design in terms of its computational representation and processes, focusing on the conceptual modelling and representation of circulation within buildings. BIM has been designed for use by several BIM authoring tools, in particular with the widely known interoperable industry foundation classes (IFCs, which follow an object-oriented data modelling methodology. Advances in BIM authoring tools, using space objects and their relations defined in an IFC’s schema, have made it possible to model, visualize and analyse circulation within buildings prior to their construction. Agent-based circulation has long been an interdisciplinary topic of research across several areas, including design computing, computer science, architectural morphology, human behaviour and environmental psychology. Such conventional approaches to building circulation are centred on navigational knowledge about built environments, and represent specific circulation paths and regulations. This paper, however, places emphasis on the use of ‘space objects’ in BIM-enabled design processes rather than on circulation agents, the latter of which are not defined in the IFCs’ schemas. By introducing and reviewing some associated research and projects, this paper also surveys how such a circulation representation is applicable to the analysis of building circulation-related rules.

  1. Rapid Texture Mapping from Image Sequences for Building Geometry Model

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zuxun; WU Jun; ZHANG Jianqing

    2003-01-01

    An effective approach,mapping the texture for building model based on the digital photogrammetric theory, is proposed. The easily-acquired image sequences from digital video camera on helicopter are used astexture resource, and the correspon-dence between the space edge in building geometry model and its line feature in image sequences is determined semiautomatically. The experimental results in production of three-dimensional data for car navigation show us an attractive future both in efficiency and effect.

  2. Building 3D models with modo 701

    CERN Document Server

    García, Juan Jiménez

    2013-01-01

    The book will focus on creating a sample application throughout the book, building gradually from chapter to chapter.If you are new to the 3D world, this is the key to getting started with a modern software in the modern visualization industry. Only minimal previous knowledge is needed.If you have some previous knowledge about 3D content creation, you will find useful tricks that will differentiate the learning experience from a typical user manual from this, a practical guide concerning the most common problems and situations and how to solve them.

  3. 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

  4. Development of hazard-compatible building fragility and vulnerability models

    Science.gov (United States)

    Karaca, E.; Luco, N.

    2008-01-01

    We present a methodology for transforming the structural and non-structural fragility functions in HAZUS into a format that is compatible with conventional seismic hazard analysis information. The methodology makes use of the building capacity (or pushover) curves and related building parameters provided in HAZUS. Instead of the capacity spectrum method applied in HAZUS, building response is estimated by inelastic response history analysis of corresponding single-degree-of-freedom systems under a large number of earthquake records. Statistics of the building response are used with the damage state definitions from HAZUS to derive fragility models conditioned on spectral acceleration values. Using the developed fragility models for structural and nonstructural building components, with corresponding damage state loss ratios from HAZUS, we also derive building vulnerability models relating spectral acceleration to repair costs. Whereas in HAZUS the structural and nonstructural damage states are treated as if they are independent, our vulnerability models are derived assuming "complete" nonstructural damage whenever the structural damage state is complete. We show the effects of considering this dependence on the final vulnerability models. The use of spectral acceleration (at selected vibration periods) as the ground motion intensity parameter, coupled with the careful treatment of uncertainty, makes the new fragility and vulnerability models compatible with conventional seismic hazard curves and hence useful for extensions to probabilistic damage and loss assessment.

  5. Uncertainties in predicting structure-borne sound power input into buildings.

    Science.gov (United States)

    Gibbs, B M

    2013-05-01

    There has been a steady development of methods of measurement and prediction of structure-borne noise in buildings, particularly over the last two decades. In proposing and evaluating these methods, a major consideration has been the likely trade-off between accuracy and simplicity. Structure-borne sound transmission is a more complicated process than airborne sound transmission, but practitioners seek methods of prediction for the former, which are as straightforward as for the latter. In this paper a description is given of a study of multi-contact sources in buildings. The study concentrates on measurement and calculation procedures for sources and calculation procedures for receiver structures, particularly lightweight building elements. Although the study is not exhaustive, the findings point to the limitations of simplified methods, specifically the uncertainties likely as a result of reducing the data sets and computational effort, and the discrepancies resulting from simplifying assumptions.

  6. Modelling of Building Interiors with Mobile Phone Sensor Data

    Directory of Open Access Journals (Sweden)

    Julian Rosser

    2015-06-01

    Full Text Available Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specification.

  7. Danish and Brazilian Modeling of Whole-Building Hygrothermal Performance

    DEFF Research Database (Denmark)

    Rode, Carsten; Mendes, Nathan; Grau, Karl

    2006-01-01

    computational analysis of the hygrothermal performance of whole buildings. Such developments have led to new hygrothermal models for whole buildings. The paper gives examples of two such recent developments and will illustrate some calculation results that can be obtained. Finally the paper will mention some......The humidity of rooms and moisture conditions of materials in the enclosure of buildings depend much on each other because of the moisture exchange that takes place over the interior surfaces. These moisture influences also depend strongly on the thermal conditions of indoor spaces and enclosure...... the humidity low and thus reduce the risk of moisture damage in the building enclosure. In either case the indoor humidity has a direct or indirect impact on the energy performance of the HVAC system of a building. To analyze this situation, one could benefit from some recent developments in integrated...

  8. Modeling thermally active building components using space mapping

    DEFF Research Database (Denmark)

    Pedersen, Frank; Weitzmann, Peter; Svendsen, Svend

    2005-01-01

    simplified models of the components do not always provide useful solutions, since they are not always able to reproduce the correct thermal behavior. The space mapping technique transforms a simplified, but computationally inexpensive model, in order to align it with a detailed model or measurements....... This paper describes the principle of the space mapping technique, and introduces a simple space mapping technique. The technique is applied to a lumped parameter model of a thermo active component, which provides a model of the thermal performance of the component as a function of two design parameters......In order to efficiently implement thermally active building components in new buildings, it is necessary to evaluate the thermal interaction between them and other building components. Applying parameter investigation or numerical optimization methods to a differential-algebraic (DAE) model...

  9. Building models for marketing decisions : past, present and future

    NARCIS (Netherlands)

    Leeflang, P.S.H.; Wittink, Dick R.

    2000-01-01

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models t

  10. Building models for marketing decisions : Past, present and future

    NARCIS (Netherlands)

    Leeflang, PSH; Wittink, DR

    2000-01-01

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models t

  11. Estimating Fallout Building Attributes from Architectural Features and Global Earthquake Model (GEM) Building Descriptions

    Energy Technology Data Exchange (ETDEWEB)

    Dillon, Michael B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kane, Staci R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-03-01

    A nuclear explosion has the potential to injure or kill tens to hundreds of thousands (or more) of people through exposure to fallout (external gamma) radiation. Existing buildings can protect their occupants (reducing fallout radiation exposures) by placing material and distance between fallout particles and individuals indoors. Prior efforts have determined an initial set of building attributes suitable to reasonably assess a given building’s protection against fallout radiation. The current work provides methods to determine the quantitative values for these attributes from (a) common architectural features and data and (b) buildings described using the Global Earthquake Model (GEM) taxonomy. These methods will be used to improve estimates of fallout protection for operational US Department of Defense (DoD) and US Department of Energy (DOE) consequence assessment models.

  12. An Empirical Validation of Building Simulation Software for Modelling of Double-Skin Facade (DSF)

    DEFF Research Database (Denmark)

    Larsen, Olena Kalyanova; Heiselberg, Per; Felsmann, Clemens

    2009-01-01

    buildings, but their accuracy might be limited in cases with DSFs because of the complexity of the heat and mass transfer processes within the DSF. To address this problem, an empirical validation of building models with DSF, performed with various building simulation tools (ESP-r, IDA ICE 3.0, VA114...... of DSF: 1. Thermal buffer mode (closed DSF cavity) and 2. External air curtain mode (naturally ventilated DSF cavity with the top and bottom openings open to outdoors). By carrying out the empirical tests, it was concluded that all models experience difficulties in predictions during the peak solar loads....... None of the models was consistent enough when comparing simulation results with experimental data for the ventilated cavity. However, some models showed reasonable agreement with the experimental results for the thermal buffer mode....

  13. Risk Classification Model for Design and Build Projects

    Directory of Open Access Journals (Sweden)

    O. E. Ogunsanmi

    2011-07-01

    Full Text Available The purpose of this paper is to investigate if the various risk sources in Design and Build projects can be classified into three risk groups of cost, time and quality using the discriminant analysis technique. Literature search was undertaken to review issues of risk sources, classification of the identified risks into a risk structure, management of risks and effects of risks all on Design and Build projects as well as concepts of discriminant analysis as a statistical technique. This literature review was undertaken through the use of internet, published papers, journal articles and other published reports on risks in Design and Build projects. A research questionnaire was further designed to collect research information. This research study is a survey research that utilized cross-sectional design to capture the primary data. The data for the survey was collected in Nigeria. In all 40 questionnaires were sent to various respondents that included Architects, Engineers, Quantity Surveyors and Builders who had used Design and Build procurement method for their recently completed projects. Responses from these retrieved questionnaires that measured the impact of risks on Design and Build were analyzed using the discriminant analysis technique through the use of SPSS software package to build two discriminant models for classifying risks into cost, time and quality risk groups. Results of the study indicate that time overrun and poor quality are the two factors that discriminate between cost, time and quality related risk groups. These two discriminant functions explain the variation between the risk groups. All the discriminating variables of cost overrun, time overrun and poor quality demonstrate some relationships with the two discriminant functions. The two discriminant models built can classify risks in Design and Build projects into risk groups of cost, time and quality. These classifications models have 72% success rate of classification

  14. 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,...

  15. Building a Structural Model: Parameterization and Structurality

    Directory of Open Access Journals (Sweden)

    Michel Mouchart

    2016-04-01

    Full Text Available A specific concept of structural model is used as a background for discussing the structurality of its parameterization. Conditions for a structural model to be also causal are examined. Difficulties and pitfalls arising from the parameterization are analyzed. In particular, pitfalls when considering alternative parameterizations of a same model are shown to have lead to ungrounded conclusions in the literature. Discussions of observationally equivalent models related to different economic mechanisms are used to make clear the connection between an economically meaningful parameterization and an economically meaningful decomposition of a complex model. The design of economic policy is used for drawing some practical implications of the proposed analysis.

  16. Building fire zone model with symbolic mathematics

    Institute of Scientific and Technical Information of China (English)

    武红梅; 郜冶; 周允基

    2009-01-01

    To apply the fire modelling for the fire engineer with symbolic mathematics,the key equations of a zone model were demonstrated. There were thirteen variables with nine constraints,so only four ordinary differential equations (ODEs) were required to solve. A typical fire modelling with two-room structure was studied. Accordingly,the source terms included in the ODEs were simplified and modelled,and the fourth Runge-Kutta method was used to solve the ordinary differential equations (ODEs) with symbolic mathematics. Then a zone model could be used with symbolic mathematics. It is proposed that symbolic mathematics is possible for use by fire engineer.

  17. Research on Dynamic Model's Building of Active Magnetic Suspension Systems

    Institute of Scientific and Technical Information of China (English)

    SHI Jian; YAN Guo-zheng; LI Li-chuan; WANG Kun-dong

    2006-01-01

    An experimental method is introduced in this paper to build the dynamics of AMSS (the active magnetic suspension system), which doesn't depend on system's physical parameters. The rotor can be reliably suspended under the unit feedback control system designed with the primary dynamic model obtained. Online identification in frequency domain is processed to give the precise model. Comparisons show that the experimental method is much closer to the precise model than the theoretic method based on magnetic circuit law. So this experimental method is a good choice to build the primary dynamic model of AMSS.

  18. Duct thermal performance models for large commercial buildings

    Energy Technology Data Exchange (ETDEWEB)

    Wray, Craig P.

    2003-10-01

    Despite the potential for significant energy savings by reducing duct leakage or other thermal losses from duct systems in large commercial buildings, California Title 24 has no provisions to credit energy-efficient duct systems in these buildings. A substantial reason is the lack of readily available simulation tools to demonstrate the energy-saving benefits associated with efficient duct systems in large commercial buildings. The overall goal of the Efficient Distribution Systems (EDS) project within the PIER High Performance Commercial Building Systems Program is to bridge the gaps in current duct thermal performance modeling capabilities, and to expand our understanding of duct thermal performance in California large commercial buildings. As steps toward this goal, our strategy in the EDS project involves two parts: (1) developing a whole-building energy simulation approach for analyzing duct thermal performance in large commercial buildings, and (2) using the tool to identify the energy impacts of duct leakage in California large commercial buildings, in support of future recommendations to address duct performance in the Title 24 Energy Efficiency Standards for Nonresidential Buildings. The specific technical objectives for the EDS project were to: (1) Identify a near-term whole-building energy simulation approach that can be used in the impacts analysis task of this project (see Objective 3), with little or no modification. A secondary objective is to recommend how to proceed with long-term development of an improved compliance tool for Title 24 that addresses duct thermal performance. (2) Develop an Alternative Calculation Method (ACM) change proposal to include a new metric for thermal distribution system efficiency in the reporting requirements for the 2005 Title 24 Standards. The metric will facilitate future comparisons of different system types using a common ''yardstick''. (3) Using the selected near-term simulation approach

  19. 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.

  20. Structural observability analysis and EKF based parameter estimation of building heating models

    Directory of Open Access Journals (Sweden)

    D.W.U. Perera

    2016-07-01

    Full Text Available Research for enhanced energy-efficient buildings has been given much recognition in the recent years owing to their high energy consumptions. Increasing energy needs can be precisely controlled by practicing advanced controllers for building Heating, Ventilation, and Air-Conditioning (HVAC systems. Advanced controllers require a mathematical building heating model to operate, and these models need to be accurate and computationally efficient. One main concern associated with such models is the accurate estimation of the unknown model parameters. This paper presents the feasibility of implementing a simplified building heating model and the computation of physical parameters using an off-line approach. Structural observability analysis is conducted using graph-theoretic techniques to analyze the observability of the developed system model. Then Extended Kalman Filter (EKF algorithm is utilized for parameter estimates using the real measurements of a single-zone building. The simulation-based results confirm that even with a simple model, the EKF follows the state variables accurately. The predicted parameters vary depending on the inputs and disturbances.

  1. Modelling, design, and optimization of net-zero energy buildings

    CERN Document Server

    Athienitis, Andreas

    2015-01-01

    Building energy design is currently going through a period of major changes. One key factor of this is the adoption of net-zero energy as a long term goal for new buildings in most developed countries. To achieve this goal a lot of research is needed to accumulate knowledge and to utilize it in practical applications. In this book, accomplished international experts present advanced modeling techniques as well as in-depth case studies in order to aid designers in optimally using simulation tools for net-zero energy building design. The strategies and technologies discussed in this book are, ho

  2. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  3. Building a better model of cancer

    Directory of Open Access Journals (Sweden)

    DeGregori James

    2006-10-01

    Full Text Available Abstract The 2006 Cold Spring Harbor Laboratory meeting on the Mechanisms and Models of Cancer was held August 16–20. The meeting featured several hundred presentations of many short talks (mostly selected from the abstracts and posters, with the airing of a number of exciting new discoveries. We will focus this meeting review on models of cancer (primarily mouse models, highlighting recent advances in new mouse models that better recapitulate sporadic tumorigenesis, demonstrations of tumor addiction to tumor suppressor inactivation, new insight into senescence as a tumor barrier, improved understanding of the evolutionary paths of cancer development, and environmental/immunological influences on cancer.

  4. A procedure for building product models

    DEFF Research Database (Denmark)

    Hvam, Lars; Riis, Jesper; Malis, Martin

    2001-01-01

    with product models. The next phase includes an analysis of the product assortment, and the set up of a so-called product master. Finally the product model is designed and implemented using object oriented modelling. The procedure is developed in order to ensure that the product models constructed are fit...... for the business processes they support, and properly structured and documented, in order to facilitate that the systems can be maintained continually and further developed. The research has been carried out at the Centre for Industrialisation of Engineering, Department of Manufacturing Engineering, Technical...

  5. CFD simulation of pollutant dispersion around isolated buildings: on the role of convective and turbulent mass fluxes in the prediction accuracy.

    Science.gov (United States)

    Gousseau, P; Blocken, B; van Heijst, G J F

    2011-10-30

    Computational Fluid Dynamics (CFD) is increasingly used to predict wind flow and pollutant dispersion around buildings. The two most frequently used approaches are solving the Reynolds-averaged Navier-Stokes (RANS) equations and Large-Eddy Simulation (LES). In the present study, we compare the convective and turbulent mass fluxes predicted by these two approaches for two configurations of isolated buildings with distinctive features. We use this analysis to clarify the role of these two components of mass transport on the prediction accuracy of RANS and LES in terms of mean concentration. It is shown that the proper simulation of the convective fluxes is essential to predict an accurate concentration field. In addition, appropriate parameterization of the turbulent fluxes is needed with RANS models, while only the subgrid-scale effects are modeled with LES. Therefore, when the source is located outside of recirculation regions (case 1), both RANS and LES can provide accurate results. When the influence of the building is higher (case 2), RANS models predict erroneous convective fluxes and are largely outperformed by LES in terms of prediction accuracy of mean concentration. These conclusions suggest that the choice of the appropriate turbulence model depends on the configuration of the dispersion problem under study. It is also shown that for both cases LES predicts a counter-gradient mechanism of the streamwise turbulent mass transport, which is not reproduced by the gradient-diffusion hypothesis that is generally used with RANS models.

  6. Team learning: building shared mental models

    NARCIS (Netherlands)

    Bossche, van den P.; Gijselaers, W.; Segers, M.; Woltjer, G.B.; Kirschner, P.

    2011-01-01

    To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning

  7. Team Learning: Building Shared Mental Models

    Science.gov (United States)

    Van den Bossche, Piet; Gijselaers, Wim; Segers, Mien; Woltjer, Geert; Kirschner, Paul

    2011-01-01

    To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning behaviors and team effectiveness. Analyses were…

  8. Building Mathematical Models Of Solid Objects

    Science.gov (United States)

    Randall, Donald P.; Jones, Kennie H.; Von Ofenheim, William H.; Gates, Raymond L.; Matthews, Christine G.

    1989-01-01

    Solid Modeling Program (SMP) version 2.0 provides capability to model complex solid objects mathematically through aggregation of geometric primitives (parts). System provides designer with basic set of primitive parts and capability to define new primitives. Six primitives included in present version: boxes, cones, spheres, paraboloids, tori, and trusses. Written in VAX/VMS FORTRAN 77.

  9. Team learning: building shared mental models

    NARCIS (Netherlands)

    Bossche, van den P.; Gijselaers, W.; Segers, M.; Woltjer, G.B.; Kirschner, P.

    2011-01-01

    To gain insight in the social processes that underlie knowledge sharing in teams, this article questions which team learning behaviors lead to the construction of a shared mental model. Additionally, it explores how the development of shared mental models mediates the relation between team learning

  10. RF building block modelling : optimization and synthesis

    NARCIS (Netherlands)

    Cheng, Wei

    2012-01-01

    For circuit designers it is desirable to have relatively simple RF circuit models that do give decent estimation accuracy and provide sufficient understanding of circuits. Chapter 2 in this thesis shows a general weak nonlinearity model that meets these demands. Using a method that is related to har

  11. Building a Database for a Quantitative Model

    Science.gov (United States)

    Kahn, C. Joseph; Kleinhammer, Roger

    2014-01-01

    A database can greatly benefit a quantitative analysis. The defining characteristic of a quantitative risk, or reliability, model is the use of failure estimate data. Models can easily contain a thousand Basic Events, relying on hundreds of individual data sources. Obviously, entering so much data by hand will eventually lead to errors. Not so obviously entering data this way does not aid linking the Basic Events to the data sources. The best way to organize large amounts of data on a computer is with a database. But a model does not require a large, enterprise-level database with dedicated developers and administrators. A database built in Excel can be quite sufficient. A simple spreadsheet database can link every Basic Event to the individual data source selected for them. This database can also contain the manipulations appropriate for how the data is used in the model. These manipulations include stressing factors based on use and maintenance cycles, dormancy, unique failure modes, the modeling of multiple items as a single "Super component" Basic Event, and Bayesian Updating based on flight and testing experience. A simple, unique metadata field in both the model and database provides a link from any Basic Event in the model to its data source and all relevant calculations. The credibility for the entire model often rests on the credibility and traceability of the data.

  12. RF building block modeling: optimization and synthesis

    NARCIS (Netherlands)

    Cheng, W.

    2012-01-01

    For circuit designers it is desirable to have relatively simple RF circuit models that do give decent estimation accuracy and provide sufficient understanding of circuits. Chapter 2 in this thesis shows a general weak nonlinearity model that meets these demands. Using a method that is related to

  13. Model building with non-compact cosets

    Science.gov (United States)

    Croon, Djuna Lize

    2016-11-01

    We explore Goldstone boson potentials in non-compact cosets of the form SO (n , 1) / SO (n). We employ a geometric approach to find the scalar potential, and focus on the conditions under which it is compact in the large field limit. We show that such a potential is found for a specific misalignment of the vacuum. This result has applications in different contexts, such as in Composite Higgs scenarios and theories for the Early Universe. We work out an example of inflation based on a non-compact coset which makes predictions which are consistent with the current observational data.

  14. Building Water Models, A Different Approach

    CERN Document Server

    Izadi, Saeed; Onufriev, Alexey V

    2014-01-01

    Simplified, classical models of water are an integral part of atomistic molecular simulations, especially in biology and chemistry where hydration effects are critical. Yet, despite several decades of effort, these models are still far from perfect. Presented here is an alternative approach to constructing point charge water models - currently, the most commonly used type. In contrast to the conventional approach, we do not impose any geometry constraints on the model other than symmetry. Instead, we optimize the distribution of point charges to best describe the "electrostatics" of the water molecule, which is key to many unusual properties of liquid water. The search for the optimal charge distribution is performed in 2D parameter space of key lowest multipole moments of the model, to find best fit to a small set of bulk water properties at room temperature. A virtually exhaustive search is enabled via analytical equations that relate the charge distribution to the multipole moments. The resulting "optimal"...

  15. 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....

  16. An Application of Non-Linear Autoregressive Neural Networks to Predict Energy Consumption in Public Buildings

    Directory of Open Access Journals (Sweden)

    Luis Gonzaga Baca Ruiz

    2016-08-01

    Full Text Available This paper addresses the problem of energy consumption prediction using neural networks over a set of public buildings. Since energy consumption in the public sector comprises a substantial share of overall consumption, the prediction of such consumption represents a decisive issue in the achievement of energy savings. In our experiments, we use the data provided by an energy consumption monitoring system in a compound of faculties and research centers at the University of Granada, and provide a methodology to predict future energy consumption using nonlinear autoregressive (NAR and the nonlinear autoregressive neural network with exogenous inputs (NARX, respectively. Results reveal that NAR and NARX neural networks are both suitable for performing energy consumption prediction, but also that exogenous data may help to improve the accuracy of predictions.

  17. Economic Model Predictive Control for Spray Drying Plants

    DEFF Research Database (Denmark)

    Petersen, Lars Norbert

    and a complexity reduced control model is used for state estimation and prediction in the controllers. These models facilitate development and comparison of control strategies. We develop two MPC strategies; a linear tracking MPC with a Real-Time Optimization layer (MPC with RTO) and an Economic Nonlinear MPC (E...... and sticky powder is avoided from building up on the dryer walls; 3) Demonstrate the industrial application of an MPC strategy to a full-scale industrial four-stage spray dryer. The main scientific contributions can be summarized to: - Modeling of a four-stage spray dryer. We develop new first...

  18. Integration of inaccurate data into model building and uncertainty assessment

    Energy Technology Data Exchange (ETDEWEB)

    Coleou, Thierry

    1998-12-31

    Model building can be seen as integrating numerous measurements and mapping through data points considered as exact. As the exact data set is usually sparse, using additional non-exact data improves the modelling and reduces the uncertainties. Several examples of non-exact data are discussed and a methodology to honor them in a single pass, along with the exact data is presented. This automatic procedure is valid for both ``base case`` model building and stochastic simulations for uncertainty analysis. 5 refs., 3 figs.

  19. Modelling energy demand in the Norwegian building stock

    Energy Technology Data Exchange (ETDEWEB)

    Sartori, Igor

    2008-07-15

    Energy demand in the building stock in Norway represents about 40% of the final energy consumption, of which 22% goes to the residential sector and 18% to the service sector. In Norway there is a strong dependency on electricity for heating purposes, with electricity covering about 80% of the energy demand in buildings. The building sector can play an important role in the achievement of a more sustainable energy system. The work performed in the articles presented in this thesis investigates various aspects related to the energy demand in the building sector, both in singular cases and in the stock as a whole. The work performed in the first part of this thesis on development and survey of case studies provided background knowledge that was then used in the second part, on modelling the entire stock. In the first part, a literature survey of case studies showed that, in a life cycle perspective, the energy used in the operating phase of buildings is the single most important factor. Design of low-energy buildings is then beneficial and should be pursued, even though it implies a somewhat higher embodied energy. A case study was performed on a school building. First, a methodology using a Monte Carlo method in the calibration process was explored. Then, the calibrated model of the school was used to investigate measures for the achievement of high energy efficiency standard through renovation work. In the second part, a model was developed to study the energy demand in a scenario analysis. The results showed the robustness of policies that included conservation measures against the conflicting effects of the other policies. Adopting conservation measures on a large scale showed the potential to reduce both electricity and total energy demand from present day levels while the building stock keeps growing. The results also highlighted the inertia to change of the building stock, due to low activity levels compared to the stock size. It also became clear that a deeper

  20. Active Shapes for Automatic 3D Modeling of Buildings

    NARCIS (Netherlands)

    Sirmacek, B.; Lindenbergh, R.C.

    2015-01-01

    Recent technological developments help us to acquire high quality 3D measurements of our urban environment. However, these measurements, which come as point clouds or Digital Surface Models (DSM), do not directly give 3D geometrical models of buildings. In addition to that, they are not suitable for

  1. Proposed Methodology for Generation of Building Information Model with Laserscanning

    Institute of Scientific and Technical Information of China (English)

    Shutao Li; J(o)rg lsele; Georg Bretthauer

    2008-01-01

    For refurbishment and state review of an existing old building,a new model reflecting the current state is often required especially when the original plans are no longer accessible.Laser scanners are used more and more as surveying instruments for various applications because of their high-precision scanning abilities.For buildings,the most notable and widely accepted product data model is the IFC product data model.It is designed to cover the whole lifecycle and supported by various software vendors and enables applications to efficiently share and exchange project information.The models obtained with the laser scan-ner,normally sets of points ("point cloud"),have to be transferred to an IFC compatible building information model to serve the needs of different planning states.This paper presents an approach designed by the German Research Center in Karlsmhe (Forschungszentrum Kadsmhe) to create an IFC compatible building information model from laser range images.The methodology through the entire process from data acquisi tion to the IFC compatible product model was proposed in this paper.In addition,IFC-Models with different level of detail (LoDs) were introduced and discussed within the work.

  2. 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

  3. 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.

  4. Modelling heat and moisture transfer in buildings. Applications to indoor thermal and moisture control

    Energy Technology Data Exchange (ETDEWEB)

    Lu Xiaoshu

    2002-07-01

    The objective of this thesis is to firstly develop a mathematical model for predicting heat and moisture transfer in buildings exposed to outdoor climatic conditions presented as temperature, relative humidity, solar radiation and wind velocity. Secondly, the heat and moisture transfer model is used to theoretically study the possibilities of controlling indoor thermal and moisture levels into an allowable range by means of heating indoor air and ventilating outdoor air. Starting from an extensive literature, it is indicated that less attention has been devoted to the topic that is similar to this thesis work. The reviewed literature has been classified into different categories in a consistent and systematic way. In modelling heat and moisture transfer in a building, the building structure is split into two components: building indoor air and building envelopes, most of which are porous media. The heat and moisture transfer equations are based on the fundamental thermodynamic relations. Darcy's law, Fick's law and Fourier's law are used in describing the transfer equations. The resultant nonlinear system of partial differential equations is discretised by using the finite element method or the finite difference method. The time marching scheme, Crank-Nicolson scheme, is adopted to advance the solution in time. The final solution provides transient distributions of thermal, moisture content and gaseous pressure for the envelopes as well as the transient thermal and moisture content for indoor air. The model program, named as HMTB, is validated with the real test houses. HMTB has a highly flexibility: It has been used to simulate the multiphase drying process of a porous medium. It has been adopted to predict transient thermal and moisture contents for buildings, transient indoor moisture generation rates and condensation potential on the wall surfaces. In studying the applications of indoor thermal and moisture control, HMTB has been applied to

  5. A Pathway Idea in Model Building

    Science.gov (United States)

    Mathai, A. M.; Haubold, H. J.

    2014-01-01

    The pathway idea is a way of going from one family of functions to another family of functions and yet another family of functions through a parameter in the mode l so that a switching mechanism is introduced into the model through a parameter. The advantage of the idea is that the model can cover the ideal or stable situation in a physical situation as well as cover the unstable neighborhoods or move from unstable neighborhoods to the stable situation. The basic idea is illustrated for the real scalar case here and its connections to topics in astrophysics and non-extens ive statistical mechanics, namely superstatistics and Tsallis statistics, Mittag-Leffler models, hypergeometric functions and generalized special functions such as the H-function etc are pointed out. The pathway idea is available for the real and complex rectangular matrix variate cases but only the real scalar case is illustrated here.

  6. Building probabilistic graphical models with Python

    CERN Document Server

    Karkera, Kiran R

    2014-01-01

    This is a short, practical guide that allows data scientists to understand the concepts of Graphical models and enables them to try them out using small Python code snippets, without being too mathematically complicated. If you are a data scientist who knows about machine learning and want to enhance your knowledge of graphical models, such as Bayes network, in order to use them to solve real-world problems using Python libraries, this book is for you. This book is intended for those who have some Python and machine learning experience, or are exploring the machine learning field.

  7. Impact of the U.S. National Building Information Model Standard (NBIMS) on Building Energy Performance Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Bazjanac, Vladimir

    2007-08-01

    The U.S. National Institute for Building Sciences (NIBS) started the development of the National Building Information Model Standard (NBIMS). Its goal is to define standard sets of data required to describe any given building in necessary detail so that any given AECO industry discipline application can find needed data at any point in the building lifecycle. This will include all data that are used in or are pertinent to building energy performance simulation and analysis. This paper describes the background that lead to the development of NBIMS, its goals and development methodology, its Part 1 (Version 1.0), and its probable impact on building energy performance simulation and analysis.

  8. BUILDING A SUSTAINABLE REGION ECONOMIC DEVELOPMENT MODEL

    Directory of Open Access Journals (Sweden)

    Pshunetlev A. A.

    2014-09-01

    Full Text Available The article contains basic assumptions of the region sustainable economic development model, which can be used to gain new knowledge about economic processes, contribute to the stability of the regional development, as well as serve as an educational tool in the study of relevant disciplines

  9. Scope of Building Information Modeling (BIM in India

    Directory of Open Access Journals (Sweden)

    Mahua Mukherjee

    2009-01-01

    Full Text Available The design communication is gradually being changed from 2D based to integrated 3D digital interface. Building InformationModeling (BIM is a model-based design concept, in which buildings will be built virtually before they get built outin the field, where data models organized for complete integration of all relevant factors in the building lifecycle whichalso manages the information exchange between the AEC (Architects, Engineers, Contractors professionals, to strengthenthe interaction between the design team. BIM is a shared knowledge about the information for decisions making during itslifecycle. There’s still much to be learned about the opportunities and implications of this tool.This paper deals with the status check of BIM application in India, to do that a survey has been designed to check the acceptanceof BIM till date, while this application is widely accepted throughout the industry in many countries for managingproject information with capabilities for cost control and facilities management.

  10. Evaluation of Sabine's formula on the prediction and control of reverberant noise in a modern LEED Platinum certified research building

    Science.gov (United States)

    Quinn-Vawter, Christopher

    The Powerhouse Energy Campus is a LEED Platinum certified research building located in Fort Collins, Colorado and is part of Colorado State University. Completed in 2014, the renovated interior of the Powerhouse consists largely of open floor plans with minimal closed rooms to allow the building's heating and cooling system to function. The open floor plan and use of interior building materials with hard surfaces created problematic noise levels for the office occupants as noise from laboratory spaces or offices could be heard throughout the building. This project provided a unique opportunity to evaluate the method available to most industrial hygienists to measure and predict reverberant noise: Sabine's Formula and the impulse noise method of reverberation measurement. Reverberation times (RT60) in five interior spaces ranging from 76 m3 to 5400 m3 were modeled using a Sabine's Formula model. The RT60 predictions were then compared to the reverberation times measured in each location, and reverberant noise treatments were designed for two rooms using the same models. The RT 60 times were taken again after the installation of the recommended treatments for two rooms. This allowed for the evaluation of both the modeling capabilities of Sabine's Formula and the practical industrial hygiene application of the equation to select effective acoustic treatments to control reverberant noise. The model performed well in room volumes 620 m3 and below, and would have likely performed better in the large volume rooms if they did not have such complex, open acoustic environments. The model was still slightly underestimating reverberation times at 620 m3 indicating that it would perform well in larger volume spaces, though this study was not able to identify the room volume at which Sabine's Formula begins to overestimate reverberation times. The RT60 time reductions in both the first floor classroom and the second floor conference room indicated that the reverberant noise

  11. Exploitation of Semantic Building Model in Indoor Navigation Systems

    Science.gov (United States)

    Anjomshoaa, A.; Shayeganfar, F.; Tjoa, A. Min

    2009-04-01

    There are many types of indoor and outdoor navigation tools and methodologies available. A majority of these solutions are based on Global Positioning Systems (GPS) and instant video and image processing. These approaches are ideal for open world environments where very few information about the target location is available, but for large scale building environments such as hospitals, governmental offices, etc the end-user will need more detailed information about the surrounding context which is especially important in case of people with special needs. This paper presents a smart indoor navigation solution that is based on Semantic Web technologies and Building Information Model (BIM). The proposed solution is also aligned with Google Android's concepts to enlighten the realization of results. Keywords: IAI IFCXML, Building Information Model, Indoor Navigation, Semantic Web, Google Android, People with Special Needs 1 Introduction Built environment is a central factor in our daily life and a big portion of human life is spent inside buildings. Traditionally the buildings are documented using building maps and plans by utilization of IT tools such as computer-aided design (CAD) applications. Documenting the maps in an electronic way is already pervasive but CAD drawings do not suffice the requirements regarding effective building models that can be shared with other building-related applications such as indoor navigation systems. The navigation in built environment is not a new issue, however with the advances in emerging technologies like GPS, mobile and networked environments, and Semantic Web new solutions have been suggested to enrich the traditional building maps and convert them to smart information resources that can be reused in other applications and improve the interpretability with building inhabitants and building visitors. Other important issues that should be addressed in building navigation scenarios are location tagging and end-user communication

  12. Development of Interpretable Predictive Models for BPH and Prostate Cancer

    Science.gov (United States)

    Bermejo, Pablo; Vivo, Alicia; Tárraga, Pedro J; Rodríguez-Montes, JA

    2015-01-01

    BACKGROUND Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH. METHODS An observational study was performed on 150 patients with PSA ≥3 ng/mL and age >50 years. We built a decision tree and a logistic regression model, validated with the leave-one-out methodology, in order to predict PC or BPH, or reject both. RESULTS Statistical dependence with PC and BPH was found for prostate volume (P-value < 0.001), PSA (P-value < 0.001), international prostate symptom score (IPSS; P-value < 0.001), digital rectal examination (DRE; P-value < 0.001), age (P-value < 0.002), antecedents (P-value < 0.006), and meat consumption (P-value < 0.08). The two predictive models that were constructed selected a subset of these, namely, volume, PSA, DRE, and IPSS, obtaining an area under the ROC curve (AUC) between 72% and 80% for both PC and BPH prediction. CONCLUSION PSA and volume together help to build predictive models that accurately distinguish among PC, BPH, and patients without any of these pathologies. Our decision tree and logistic regression models outperform the AUC obtained in the compared studies. Using these models as decision support, the number of unnecessary biopsies might be significantly reduced. PMID:25780348

  13. Building Qualitative Models of Thermodynamic Processes

    Science.gov (United States)

    2007-01-01

    two containers 61 53 Envisionment for simple flow with thermal properties 62 54 Envisionment for simple flow without thermal properties 63 55 A...pump and a path connecting two containers 64 56 Scenario input for a pump and a return path between two containers . . 64 57 Envisionment for the...Specifically, the domain model is written in the language of QPE[8], an envisioner for Qualitative Process theory . We assume a reading knowledge of QP theory

  14. Maxent modelling for predicting the potential distribution of Thai Palms

    DEFF Research Database (Denmark)

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

    2011-01-01

    Increasingly species distribution models are being used to address questions related to ecology, biogeography and species conservation on global and regional scales. We used the maximum entropy approach implemented in the MAXENT programme to build a habitat suitability model for Thai palms based...... on presence data. The aim was to identify potential hot spot areas, assess the determinants of palm distribution ranges, and provide a firmer knowledge base for future conservation actions. We focused on a relatively small number of climatic, environmental and spatial variables in order to avoid...... overprediction of species distribution ranges. The models with the best predictive power were found by calculating the area under the curve (AUC) of receiver-operating characteristic (ROC). Here, we provide examples of contrasting predicted species distribution ranges as well as a map of modeled palm diversity...

  15. CORAL: building up the model for bioconcentration factor and defining it's applicability domain.

    Science.gov (United States)

    Toropov, A A; Toropova, A P; Lombardo, A; Roncaglioni, A; Benfenati, E; Gini, G

    2011-04-01

    CORAL (CORrelation And Logic) software can be used to build up the quantitative structure--property/activity relationships (QSPR/QSAR) with optimal descriptors calculated with the simplified molecular input line entry system (SMILES). We used CORAL to evaluate the applicability domain of the QSAR models, taking a model of bioconcentration factor (logBCF) as example. This model's based on a large training set of more than 1000 chemicals. To improve the model is predictivity and reliability on new compounds, we introduced a new function, which uses the Delta(obs) = logBCF(expr)--logBCF(calc) of the predictions on the chemicals in the training set. With this approach, outliers are eliminated from the phase of training. This proved useful and increased the model's predictivity. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

  16. A Unified Building Model for 3D Urban GIS

    Directory of Open Access Journals (Sweden)

    Ihab Hijazi

    2012-07-01

    Full Text Available Several tasks in urban and architectural design are today undertaken in a geospatial context. Building Information Models (BIM and geospatial technologies offer 3D data models that provide information about buildings and the surrounding environment. The Industry Foundation Classes (IFC and CityGML are today the two most prominent semantic models for representation of BIM and geospatial models respectively. CityGML has emerged as a standard for modeling city models while IFC has been developed as a reference model for building objects and sites. Current CAD and geospatial software provide tools that allow the conversion of information from one format to the other. These tools are however fairly limited in their capabilities, often resulting in data and information losses in the transformations. This paper describes a new approach for data integration based on a unified building model (UBM which encapsulates both the CityGML and IFC models, thus avoiding translations between the models and loss of information. To build the UBM, all classes and related concepts were initially collected from both models, overlapping concepts were merged, new objects were created to ensure the capturing of both indoor and outdoor objects, and finally, spatial relationships between the objects were redefined. Unified Modeling Language (UML notations were used for representing its objects and relationships between them. There are two use-case scenarios, both set in a hospital: “evacuation” and “allocating spaces for patient wards” were developed to validate and test the proposed UBM data model. Based on these two scenarios, four validation queries were defined in order to validate the appropriateness of the proposed unified building model. It has been validated, through the case scenarios and four queries, that the UBM being developed is able to integrate CityGML data as well as IFC data in an apparently seamless way. Constraints and enrichment functions are

  17. Validation of models of users' window opening behaviour in residential buildings

    DEFF Research Database (Denmark)

    Corgnati, Stefano P.; Andersen, Rune Korsholm; Fabi, Valentina

    2013-01-01

    The characterisation of window opening behaviour is crucial for suitable prediction of building performance (energy consumption, indoor environmental quality, etc.) by means of simulations. In this paper, data from a measurement campaign was used to validate three models of window opening behaviour....... Data from the measurement campaign was used as input in the models to calculate the probability of opening and closing windows. Afterwards, the validation was carried out by comparing the predicted probabilities with the actual measured state of the windows in the dwellings....

  18. 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...

  19. XLISP-Stat Tools for Building Generalised Estimating Equation Models

    Directory of Open Access Journals (Sweden)

    Thomas Lumley

    1996-12-01

    Full Text Available This paper describes a set of Lisp-Stat tools for building Generalised Estimating Equation models to analyse longitudinal or clustered measurements. The user interface is based on the built-in regression and generalised linear model prototypes, with the addition of object-based error functions, correlation structures and model formula tools. Residual and deletion diagnostic plots are available on the cluster and observation level and use the dynamic graphics capabilities of Lisp-Stat.

  20. Model-building codes for membrane proteins.

    Energy Technology Data Exchange (ETDEWEB)

    Shirley, David Noyes; Hunt, Thomas W.; Brown, W. Michael; Schoeniger, Joseph S. (Sandia National Laboratories, Livermore, CA); Slepoy, Alexander; Sale, Kenneth L. (Sandia National Laboratories, Livermore, CA); Young, Malin M. (Sandia National Laboratories, Livermore, CA); Faulon, Jean-Loup Michel; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA)

    2005-01-01

    We have developed a novel approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only a sparse set of distance constraints, such as those derived from MS3-D, dipolar-EPR and FRET experiments. Algorithms have been written for searching the conformational space of membrane protein folds matching the set of distance constraints, which provides initial structures for local conformational searches. Local conformation search is achieved by optimizing these candidates against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. This results in refined helical bundles to which the interhelical loops and amino acid side-chains are added. Using a set of only 27 distance constraints extracted from the literature, our methods successfully recover the structure of dark-adapted rhodopsin to within 3.2 {angstrom} of the crystal structure.

  1. Energy Consumption and Indoor Environment Predicted by a Combination of Computational Fluid Dynamics and Building Energy Performance Simulation

    DEFF Research Database (Denmark)

    Nielsen, Peter Vilhelm

    2003-01-01

    An interconnection between a building energy performance simulation program and a Computational Fluid Dynamics program (CFD) for room air distribution is introduced for improvement of the predictions of both the energy consumption and the indoor environment.The article describes a calculation...... of the energy consumption in a large building where the building energy simulation program is modified by CFD predictions of the flow between three zones that are connected by pressure and buoyancy-driven air flow through open areas. The two programs are interconnected in an iterative procedure. The article...... shows also an evaluation of the air quality in the main area of the buildings based on CFD predictions. It is demonstrated that an interconnection between a CFD program and a building energy performance simulation program will improve both the energy consumption data and the prediction of thermal...

  2. SIMPLIFIED BUILDING MODELS EXTRACTION FROM ULTRA-LIGHT UAV IMAGERY

    Directory of Open Access Journals (Sweden)

    O. Küng

    2012-09-01

    Full Text Available Generating detailed simplified building models such as the ones present on Google Earth is often a difficult and lengthy manual task, requiring advanced CAD software and a combination of ground imagery, LIDAR data and blueprints. Nowadays, UAVs such as the AscTec Falcon 8 have reached the maturity to offer an affordable, fast and easy way to capture large amounts of oblique images covering all parts of a building. In this paper we present a state-of-the-art photogrammetry and visual reconstruction pipeline provided by Pix4D applied to medium resolution imagery acquired by such UAVs. The key element of simplified building models extraction is the seamless integration of the outputs of such a pipeline for a final manual refinement step in order to minimize the amount of manual work.

  3. Integrated Urban System and Energy Consumption Model: Residential Buildings

    Directory of Open Access Journals (Sweden)

    Rocco Papa

    2014-05-01

    Full Text Available This paper describes a segment of research conducted within the project PON 04a2_E Smart Energy Master for the energetic government of the territory conducted by the Department of Civil, Architectural and Environment Engineering, University of Naples "Federico II".  In particular, this article is part of the study carried out for the definition of the comprehension/interpretation model that correlates buildings, city’s activities and users’ behaviour in order to promote energy savings. In detail, this segment of the research wants to define the residential variables to be used in the model. For this purpose a knowledge framework at international level has been defined, to estimate the energy requirements of residential buildings and the identification of a set of parameters, whose variation has a significant influence on the energy consumption of residential buildings.

  4. Combined Grammar for the Modeling of Building Interiors

    Science.gov (United States)

    Becker, S.; Peter, M.; Fritsch, D.; Philipp, D.; Baier, P.; Dibak, C.

    2013-11-01

    As spatial grammars have proven successful and efficient to deliver LOD3 models, the next challenge is their extension to indoor applications, leading to LOD4 models. Therefore, a combined indoor grammar for the automatic generation of indoor models from erroneous and incomplete observation data is presented. In building interiors where inaccurate observation data is available, the grammar can be used to make the reconstruction process robust, and verify the reconstructed geometries. In unobserved building interiors, the grammar can generate hypotheses about possible indoor geometries matching the style of the rest of the building. The grammar combines concepts from L-systems and split grammars. It is designed in such way that it can be derived from observation data fully automatically. Thus, manual predefinitions of the grammar rules usually required to tune the grammar to a specific building style, become obsolete. The potential benefit of using our grammar as support for indoor modeling is evaluated based on an example where the grammar has been applied to automatically generate an indoor model from erroneous and incomplete traces gathered by foot-mounted MEMS/IMU positioning systems.

  5. Predicting Solar Cycle 25 using Surface Flux Transport Model

    Science.gov (United States)

    Imada, Shinsuke; Iijima, Haruhisa; Hotta, Hideyuki; Shiota, Daiko; Kusano, Kanya

    2017-08-01

    It is thought that the longer-term variations of the solar activity may affect the Earth’s climate. Therefore, predicting the next solar cycle is crucial for the forecast of the “solar-terrestrial environment”. To build prediction schemes for the next solar cycle is a key for the long-term space weather study. Recently, the relationship between polar magnetic field at the solar minimum and next solar activity is intensively discussed. Because we can determine the polar magnetic field at the solar minimum roughly 3 years before the next solar maximum, we may discuss the next solar cycle 3years before. Further, the longer term (~5 years) prediction might be achieved by estimating the polar magnetic field with the Surface Flux Transport (SFT) model. Now, we are developing a prediction scheme by SFT model as a part of the PSTEP (Project for Solar-Terrestrial Environment Prediction) and adapting to the Cycle 25 prediction. The predicted polar field strength of Cycle 24/25 minimum is several tens of percent smaller than Cycle 23/24 minimum. The result suggests that the amplitude of Cycle 25 is weaker than the current cycle. We also try to obtain the meridional flow, differential rotation, and turbulent diffusivity from recent modern observations (Hinode and Solar Dynamics Observatory). These parameters will be used in the SFT models to predict the polar magnetic fields strength at the solar minimum. In this presentation, we will explain the outline of our strategy to predict the next solar cycle and discuss the initial results for Cycle 25 prediction.

  6. NOAA ESRI Grid - seafloor hardbottom occurrence predictions model in New York offshore planning area from Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents hard bottom occurrence predictions from a spatial model developed for the New York offshore spatial planning area. This model builds upon the...

  7. Automatically updating predictive modeling workflows support decision-making in drug design.

    Science.gov (United States)

    Muegge, Ingo; Bentzien, Jörg; Mukherjee, Prasenjit; Hughes, Robert O

    2016-09-01

    Using predictive models for early decision-making in drug discovery has become standard practice. We suggest that model building needs to be automated with minimum input and low technical maintenance requirements. Models perform best when tailored to answering specific compound optimization related questions. If qualitative answers are required, 2-bin classification models are preferred. Integrating predictive modeling results with structural information stimulates better decision making. For in silico models supporting rapid structure-activity relationship cycles the performance deteriorates within weeks. Frequent automated updates of predictive models ensure best predictions. Consensus between multiple modeling approaches increases the prediction confidence. Combining qualified and nonqualified data optimally uses all available information. Dose predictions provide a holistic alternative to multiple individual property predictions for reaching complex decisions.

  8. Fundamental mass transfer modeling of emission of volatile organic compounds from building materials

    Science.gov (United States)

    Bodalal, Awad Saad

    In this study, a mass transfer theory based model is presented for characterizing the VOC emissions from building materials. A 3-D diffusion model is developed to describe the emissions of volatile organic compounds (VOCs) from individual sources. Then the formulation is extended to include the emissions from composite sources (system comprising an assemblage of individual sources). The key parameters for the model (The diffusion coefficient of the VOC in the source material D, and the equilibrium partition coefficient k e) were determined independently (model parameters are determined without the use of chamber emission data). This procedure eliminated to a large extent the need for emission testing using environmental chambers, which is costly, time consuming, and may be subject to confounding sink effects. An experimental method is developed and implemented to measure directly the internal diffusion (D) and partition coefficients ( ke). The use of the method is illustrated for three types of VOC's: (i) Aliphatic Hydrocarbons, (ii) Aromatic Hydrocarbons and ( iii) Aldehydes, through typical dry building materials (carpet, plywood, particleboard, vinyl floor tile, gypsum board, sub-floor tile and OSB). Then correlations for predicting D and ke based solely on commonly available properties such as molecular weight and vapour pressure were proposed for each product and type of VOC. These correlations can be used to estimate the D and ke when direct measurement data are not available, and thus facilitate the prediction of VOC emissions from the building materials using mass transfer theory. The VOC emissions from a sub-floor material (made of the recycled automobile tires), and a particleboard are measured and predicted. Finally, a mathematical model to predict the diffusion coefficient through complex sources (floor adhesive) as a function of time was developed. Then this model (for diffusion coefficient in complex sources) was used to predict the emission rate from

  9. Energy Prediction versus Energy Performance of Green Buildings in Malaysia. Comparison of Predicted and Operational Measurement of GBI Certified Green Office in Kuala Lumpur

    Directory of Open Access Journals (Sweden)

    Zaid Suzaini M

    2016-01-01

    Full Text Available Forward from the sustainability agenda of Brundtland in 1987 and the increasing demand for energy efficient buildings, the building industry has taken steps in meeting the challenge of reducing its environmental impact. Initiatives such as ‘green’ or ‘sustainable’ design have been at the forefront of architecture, while green assessment tools have been used to predict the energy performance of building during its operational phase. However, there is still a significant hap between predicted or simulated energy measurements compared to actual operational energy consumption, or is more commonly referred as the ‘performance gap’. This paper tries to bridge this gap by comparing measured operational energy consumption of a Green Building Index (GBI certified office building in Kuala Lumpur, with its predicted energy rating qualification.

  10. Semi-Automatic Modelling of Building FAÇADES with Shape Grammars Using Historic Building Information Modelling

    Science.gov (United States)

    Dore, C.; Murphy, M.

    2013-02-01

    This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.

  11. Overcoming Microsoft Excel's Weaknesses for Crop Model Building and Simulations

    Science.gov (United States)

    Sung, Christopher Teh Boon

    2011-01-01

    Using spreadsheets such as Microsoft Excel for building crop models and running simulations can be beneficial. Excel is easy to use, powerful, and versatile, and it requires the least proficiency in computer programming compared to other programming platforms. Excel, however, has several weaknesses: it does not directly support loops for iterative…

  12. Getting Started and Working with Building Information Modeling

    Science.gov (United States)

    Smith, Dana K.

    2009-01-01

    This article will assume that one has heard of Building Information Modeling or BIM but has not developed a strategy as to how to get the most out of it. The National BIM Standard (NBIMS) has defined BIM as a digital representation of physical and functional characteristics of a facility. As such, it serves as a shared knowledge resource for…

  13. Building information modeling (BIM) approach to the GMT Project

    Science.gov (United States)

    Teran, Jose; Sheehan, Michael; Neff, Daniel H.; Adriaanse, David; Grigel, Eric; Farahani, Arash

    2014-07-01

    The Giant Magellan Telescope (GMT), one of several next generation Extremely Large Telescopes (ELTs), is a 25.4 meter diameter altitude over azimuth design set to be built at the summit of Cerro Campánas at the Las Campánas Observatory in Chile. The paper describes the use of Building Information Modeling (BIM) for the GMT project.

  14. Aligning building information model tools and construction management methods

    NARCIS (Netherlands)

    Hartmann, Timo; van Meerveld, H.J.; Vossebeld, N.; Adriaanse, Adriaan Maria

    2012-01-01

    Few empirical studies exist that can explain how different Building Information Model (BIM) based tool implementation strategies work in practical contexts. To help overcoming this gap, this paper describes the implementation of two BIM based tools, the first, to support the activities at an estimat

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Modeling climate change impact in hospitality sector, using building resources consumption signature

    Science.gov (United States)

    Pinto, Armando; Bernardino, Mariana; Silva Santos, António; Pimpão Silva, Álvaro; Espírito Santo, Fátima

    2016-04-01

    Hotels are one of building types that consumes more energy and water per person and are vulnerable to climate change because in the occurrence of extreme events (heat waves, water stress) same failures could compromise the hotel services (comfort) and increase energy cost or compromise the landscape and amenities due to water use restrictions. Climate impact assessments and the development of adaptation strategies require the knowledge about critical climatic variables and also the behaviour of building. To study the risk and vulnerability of buildings and hotels to climate change regarding resources consumption (energy and water), previous studies used building energy modelling simulation (BEMS) tools to study the variation in energy and water consumption. In general, the climate change impact in building is evaluated studying the energy and water demand of the building for future climate scenarios. But, hotels are complex buildings, quite different from each other and assumption done in simplified BEMS aren't calibrated and usually neglect some important hotel features leading to projected estimates that do not usually match hotel sector understanding and practice. Taking account all uncertainties, the use of building signature (statistical method) could be helpful to assess, in a more clear way, the impact of Climate Change in the hospitality sector and using a broad sample. Statistical analysis of the global energy consumption obtained from bills shows that the energy consumption may be predicted within 90% confidence interval only with the outdoor temperature. In this article a simplified methodology is presented and applied to identify the climate change impact in hospitality sector using the building energy and water signature. This methodology is applied to sixteen hotels (nine in Lisbon and seven in Algarve) with four and five stars rating. The results show that is expect an increase in water and electricity consumption (manly due to the increase in

  8. 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…

  9. On a computational model of building thermal dynamic response

    Science.gov (United States)

    Jarošová, Petra; Vala, Jiří

    2016-07-01

    Development and exploitation of advanced materials, structures and technologies in civil engineering, both for buildings with carefully controlled interior temperature and for common residential houses, together with new European and national directives and technical standards, stimulate the development of rather complex and robust, but sufficiently simple and inexpensive computational tools, supporting their design and optimization of energy consumption. This paper demonstrates the possibility of consideration of such seemingly contradictory requirements, using the simplified non-stationary thermal model of a building, motivated by the analogy with the analysis of electric circuits; certain semi-analytical forms of solutions come from the method of lines.

  10. 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)

  11. Analogue Behavioral Modeling of Switched-Current Building Block Circuits

    Institute of Scientific and Technical Information of China (English)

    ZENG Xuan; WANG Wei; SHI Jianlei; TANG Pushan; D.ZHOU

    2001-01-01

    This paper proposes a behavioral modeling technique for the second-generation switched-current building block circuits. The proposed models are capable of capturing the non-ideal behavior of switched-current circuits, which includes the charge injection effects and device mismatch effects. As a result, system performance degradations due to the building block imperfections can be detected at the early design stage by fast behavioral simulations. To evaluate the accuracy of the proposed models, we developed a time-domain behavioral simulator. Experimental results have shown that compared with SPICE, the behavioral modeling error is less than 2.15%, while behavioral simulation speed up is 4 orders in time-domain.

  12. Enhancements to ASHRAE Standard 90.1 Prototype Building Models

    Energy Technology Data Exchange (ETDEWEB)

    Goel, Supriya; Athalye, Rahul A.; Wang, Weimin; Zhang, Jian; Rosenberg, Michael I.; Xie, YuLong; Hart, Philip R.; Mendon, Vrushali V.

    2014-04-16

    This report focuses on enhancements to prototype building models used to determine the energy impact of various versions of ANSI/ASHRAE/IES Standard 90.1. Since the last publication of the prototype building models, PNNL has made numerous enhancements to the original prototype models compliant with the 2004, 2007, and 2010 editions of Standard 90.1. Those enhancements are described here and were made for several reasons: (1) to change or improve prototype design assumptions; (2) to improve the simulation accuracy; (3) to improve the simulation infrastructure; and (4) to add additional detail to the models needed to capture certain energy impacts from Standard 90.1 improvements. These enhancements impact simulated prototype energy use, and consequently impact the savings estimated from edition to edition of Standard 90.1.

  13. Pressure integration technique for predicting wind-induced response in high-rise buildings

    Directory of Open Access Journals (Sweden)

    Aly Mousaad Aly

    2013-12-01

    Full Text Available This paper presents a procedure for response prediction in high-rise buildings under wind loads. The procedure is illustrated in an application example of a tall building exposed to both cross-wind and along-wind loads. The responses of the building in the lateral directions combined with torsion are estimated simultaneously. Results show good agreement with recent design standards; however, the proposed procedure has the advantages of accounting for complex mode shapes, non-uniform mass distribution, and interference effects from the surrounding. In addition, the technique allows for the contribution of higher modes. For accurate estimation of the acceleration response, it is important to consider not only the first two lateral vibrational modes, but also higher modes. Ignoring the contribution of higher modes may lead to underestimation of the acceleration response; on the other hand, it could result in overestimation of the displacement response. Furthermore, the procedure presented in this study can help decision makers, involved in a tall building design/retrofit to choose among innovative solutions like aerodynamic mitigation, structural member size adjustment, damping enhancement, and/or materials change, with an objective to improve the resiliency and the serviceability under extreme wind actions.

  14. Building the ensemble flood prediction system by using numerical weather prediction data: Case study in Kinu river basin, Japan

    Science.gov (United States)

    Ishitsuka, Y.; Yoshimura, K.

    2016-12-01

    Floods have a potential to be a major source of economic or human damage caused by natural disasters. Flood prediction systems were developed all over the world and to treat the uncertainty of the prediction ensemble simulation is commonly adopted. In this study, ensemble flood prediction system using global scale land surface and hydrodynamic model was developed. The system requests surface atmospheric forcing and Land Surface Model, MATSIRO, calculates runoff. Those generated runoff is inputted to hydrodynamic model CaMa-Flood to calculate discharge and flood inundation. CaMa-Flood can simulate flood area and its fraction by introducing floodplain connected to river channel. Forecast leadtime was set 39hours according to forcing data. For the case study, the flood occurred at Kinu river basin, Japan in 2015 was hindcasted. In a 1761 km² Kinu river basin, 3-days accumulated average rainfall was 384mm and over 4000 people was left in the inundated area. Available ensemble numerical weather prediction data at that time was inputted to the system in a resolution of 0.05 degrees and 1hour time step. As a result, the system predicted the flood occurrence by 45% and 84% at 23 and 11 hours before the water level exceeded the evacuation threshold, respectively. Those prediction lead time may provide the chance for early preparation for the floods such as levee reinforcement or evacuation. Adding to the discharge, flood area predictability was also analyzed. Although those models were applied for Japan region, this system can be applied easily to other region or even global scale. The areal flood prediction in meso to global scale would be useful for detecting hot zones or vulnerable areas over each region.

  15. 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.

  16. 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.

  17. Links Related to the Indoor Air Quality Building Education and Assessment Model

    Science.gov (United States)

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  18. Bibliography for the Indoor Air Quality Building Education and Assessment Model

    Science.gov (United States)

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  19. Product Modelling for Building Design: Annotated Bibliography (2nd Edition)

    DEFF Research Database (Denmark)

    Galle, Per

    1999-01-01

    This bibliography concerns research publications from 1976 to 1994-5, on product modelling in computer aided architectural design and computer aided engineering design of buildings and their surroundings. For each item of literature, full bibliographic information is given whenever available...... of literature is offered on machine interpretation of drawings, which may be relevant in the context of information exchange among different product models. Although the bibliography is fairly comprehensive as far as it goes, no completeness of coverage is claimed....

  20. Scenario-building considerations for financial planning models

    Energy Technology Data Exchange (ETDEWEB)

    Murray, S.; Carino, D.

    1994-12-31

    The construction of scenarios is an essential model-building step in stochastic programming. When a discrete sample of scenarios is chosen to represent a continuity of potential outcomes, scenario choice can impact both solution speed and quality. For financial planning models, techniques are discussed that ensure a scenario set matches moments of the continuous distribution and improvements in solution speed and quality are investigated.

  1. Product Modelling for Building Design: Annotated Bibliography (2nd Edition)

    DEFF Research Database (Denmark)

    Galle, Per

    1999-01-01

    This bibliography concerns research publications from 1976 to 1994-5, on product modelling in computer aided architectural design and computer aided engineering design of buildings and their surroundings. For each item of literature, full bibliographic information is given whenever available...... of literature is offered on machine interpretation of drawings, which may be relevant in the context of information exchange among different product models. Although the bibliography is fairly comprehensive as far as it goes, no completeness of coverage is claimed....

  2. First Prismatic Building Model Reconstruction from Tomosar Point Clouds

    Science.gov (United States)

    Sun, Y.; Shahzad, M.; Zhu, X.

    2016-06-01

    This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR) point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007) and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce) the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center) in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

  3. 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.

  4. Evaluation of Sub-Zonal Airflow Models for the Prediction of Local Interior Boundary Conditions

    DEFF Research Database (Denmark)

    Steskens, Paul W. M. H.; Janssen, Hans; Rode, Carsten

    2013-01-01

    and applicability of the sub-zonal airflow model to predict the local indoor environmental conditions, as well as the local surface transfer coefficients near building components. Two test cases were analyzed for, respectively, natural and forced convection in a room. The simulation results predicted from the sub...

  5. Regulatory odour model development: Survey of modelling tools and datasets with focus on building effects

    DEFF Research Database (Denmark)

    Olesen, H. R.; Løfstrøm, P.; Berkowicz, R.;

    dispersion models for estimating local concentration levels in general. However, the report focuses on some particular issues, which are relevant for subsequent work on odour due to animal production. An issue of primary concern is the effect that buildings (stables) have on flow and dispersion. The handling...... of building effects is a complicated problem, and a major part of the report is devoted to the treatment of building effects in dispersion models...

  6. 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.

  7. 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.

  8. Vhrs Stereo Images for 3d Modelling of Buildings

    Science.gov (United States)

    Bujakiewicz, A.; Holc, M.

    2012-07-01

    The paper presents the project which was carried out in the Photogrammetric Laboratory of Warsaw University of Technology. The experiment is concerned with the extraction of 3D vector data for buildings creation from 3D photogrammetric model based on the Ikonos stereo images. The model was reconstructed with photogrammetric workstation - Summit Evolution combined with ArcGIS 3D platform. Accuracy of 3D model was significantly improved by use for orientation of pair of satellite images the stereo measured tie points distributed uniformly around the model area in addition to 5 control points. The RMS for model reconstructed on base of the RPC coefficients only were 16,6 m, 2,7 m and 47,4 m, for X, Y and Z coordinates, respectively. By addition of 5 control points the RMS were improved to 0,7 m, 0,7 m 1,0 m, where the best results were achieved when RMS were estimated from deviations in 17 check points (with 5 control points)and amounted to 0,4 m, 0,5 m and 0,6 m, for X, Y, and Z respectively. The extracted 3D vector data for buildings were integrated with 2D data of the ground footprints and afterwards they were used for 3D modelling of buildings in Google SketchUp software. The final results were compared with the reference data obtained from other sources. It was found that the shape of buildings (in concern to the number of details) had been reconstructed on level of LoD1, when the accuracy of these models corresponded to the level of LoD2.

  9. VHRS STEREO IMAGES FOR 3D MODELLING OF BUILDINGS

    Directory of Open Access Journals (Sweden)

    A. Bujakiewicz

    2012-07-01

    Full Text Available The paper presents the project which was carried out in the Photogrammetric Laboratory of Warsaw University of Technology. The experiment is concerned with the extraction of 3D vector data for buildings creation from 3D photogrammetric model based on the Ikonos stereo images. The model was reconstructed with photogrammetric workstation – Summit Evolution combined with ArcGIS 3D platform. Accuracy of 3D model was significantly improved by use for orientation of pair of satellite images the stereo measured tie points distributed uniformly around the model area in addition to 5 control points. The RMS for model reconstructed on base of the RPC coefficients only were 16,6 m, 2,7 m and 47,4 m, for X, Y and Z coordinates, respectively. By addition of 5 control points the RMS were improved to 0,7 m, 0,7 m 1,0 m, where the best results were achieved when RMS were estimated from deviations in 17 check points (with 5 control pointsand amounted to 0,4 m, 0,5 m and 0,6 m, for X, Y, and Z respectively. The extracted 3D vector data for buildings were integrated with 2D data of the ground footprints and afterwards they were used for 3D modelling of buildings in Google SketchUp software. The final results were compared with the reference data obtained from other sources. It was found that the shape of buildings (in concern to the number of details had been reconstructed on level of LoD1, when the accuracy of these models corresponded to the level of LoD2.

  10. Application of the Software as a Service Model to the Control of Complex Building Systems

    Energy Technology Data Exchange (ETDEWEB)

    Stadler, Michael; Donadee, Jon; Marnay, Chris; Lai, Judy; Mendes, Goncalo; Appen, Jan von; M& #233; gel, Oliver; Bhattacharya, Prajesh; DeForest, Nicholas; Lai, Judy

    2011-03-18

    In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building. The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.

  11. Application of the Software as a Service Model to the Control of Complex Building Systems

    Energy Technology Data Exchange (ETDEWEB)

    Stadler, Michael; Donadee, Jonathan; Marnay, Chris; Mendes, Goncalo; Appen, Jan von; Megel, Oliver; Bhattacharya, Prajesh; DeForest, Nicholas; Lai, Judy

    2011-03-17

    In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building. The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.

  12. Model-Driven Engineering Support for Building C# Applications

    Science.gov (United States)

    Derezińska, Anna; Ołtarzewski, Przemysław

    Realization of Model-Driven Engineering (MDE) vision of software development requires a comprehensive and user-friendly tool support. This paper presents a UML-based approach for building trustful C# applications. UML models are refined using profiles for assigning class model elements to C# concepts and to elements of implementation project. Stereotyped elements are verified on life and during model to code transformation in order to prevent creation of an incorrect code. The Transform OCL Fragments into C# system (T.O.F.I.C.) was created as a feature of the Eclipse environment. The system extends the IBM Rational Software Architect tool.

  13. 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...

  14. 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.

  15. Internet of Things building blocks and business models

    CERN Document Server

    Hussain, Fatima

    2017-01-01

    This book describes the building blocks and introductory business models for Internet of Things (IoT). The author provide an overview of the entire IoT architecture and constituent layers, followed by detail description of each block . Various inter-connecting technologies and sensors are discussed in context of IoT networks. In addition to this, concepts of Big Data and Fog Computing are presented and characterized as per data generated by versatile IoT applications . Smart parking system and context aware services are presented as an hybrid model of cloud and Fog Afterwards, various IoT applications and respective business models are discussed. Finally, author summarizes the IoT building blocks and identify research issues in each, and suggest potential research projects worthy of pursuing. .

  16. Predicting the future completing models of observed complex systems

    CERN Document Server

    Abarbanel, Henry

    2013-01-01

    Predicting the Future: Completing Models of Observed Complex Systems provides a general framework for the discussion of model building and validation across a broad spectrum of disciplines. This is accomplished through the development of an exact path integral for use in transferring information from observations to a model of the observed system. Through many illustrative examples drawn from models in neuroscience, fluid dynamics, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is investigated. Using highly instructive examples, the problems of data assimilation and the means to treat them are clearly illustrated. This book will be useful for students and practitioners of physics, neuroscience, regulatory networks, meteorology and climate science, network dynamics, fluid dynamics, and o...

  17. Mesoscale Wind Predictions for Wave Model Evaluation

    Science.gov (United States)

    2016-06-07

    N0001400WX20041(B) http://www.nrlmry.navy.mil LONG TERM GOALS The long-term goal is to demonstrate the significance and importance of high...ocean waves by an appropriate wave model. OBJECTIVES The main objectives of this project are to: 1. Build the infrastructure to generate the...temperature for all COAMPS grids at the resolution of each of these grids. These analyses are important for the proper 2 specification of the lower

  18. Thermal monitoring and indoor temperature predictions in a passive solar building in an arid environment

    Energy Technology Data Exchange (ETDEWEB)

    Krueger, Eduardo [Programa de Pos-Graduacao em Tecnologia, Departamento de Construcao Civil, Universidade Tecnologica Federal do Parana, Av. Sete de Setembro, 3165-Curitiba 80230-901 (Brazil); Givoni, Baruch [Department of Architecture, School of Arts and Architecture, UCLA, Los Angeles, CA (United States); Ben Gurion University (Israel)

    2008-11-15

    In this paper, results of a long-term temperature monitoring in a passive solar house, located at the Sede-Boqer Campus of the Ben-Gurion University, in the Negev region of Israel are presented. Local latitude is 30.8 N and the elevation is approximately 480 m above sea level. The climate of the region is characterized by strong daily and seasonal thermal fluctuations, dry air and clear skies with intense solar radiation. The monitored building consists of a two storey, passive solar house and belongs to a student dormitory complex located at the Sede-Boqer Campus. Formulae were developed, based on part of the whole monitoring period, representing the measured daily indoor maximum, average and minimum temperatures. The formulae were then validated against measurements taken independently in different time periods. In managing the building, the main objective in the winter was to bring up the indoor temperature by direct and indirect solar gains while in the summer it was to keep the temperature down. Therefore, analysis of the data and development of predictive formulas of the indoor temperatures were done separately for the winter and for the summer. Measured data of each season were then divided into two sub-periods, the first one used to generate formulas based on measured data (generation) and the second for testing the predictability of the formulas by independent data (validation). In general, a fairly good agreement was verified between onsite measurements and results of the formulae, with regard to daily indoor maximum, average and minimum temperatures. The issue of using outdoor temperatures measured in the adjacent street canyon instead of those registered at the local meteorological site for evaluating the building's cooling demand is also addressed in the paper. The developed formulae were here used for estimating the building's thermal and energy performance in summer, taking into account: (1) solely climatic data from the meteorological

  19. 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

  20. Nonlinear turbulence models for predicting strong curvature effects

    Institute of Scientific and Technical Information of China (English)

    XU Jing-lei; MA Hui-yang; HUANG Yu-ning

    2008-01-01

    Prediction of the characteristics of turbulent flows with strong streamline curvature, such as flows in turbomachines, curved channel flows, flows around airfoils and buildings, is of great importance in engineering applicatious and poses a very practical challenge for turbulence modeling. In this paper, we analyze qualitatively the curvature effects on the structure of turbulence and conduct numerical simulations of a turbulent U- duct flow with a number of turbulence models in order to assess their overall performance. The models evaluated in this work are some typical linear eddy viscosity turbulence models, nonlinear eddy viscosity turbulence models (NLEVM) (quadratic and cubic), a quadratic explicit algebraic stress model (EASM) and a Reynolds stress model (RSM) developed based on the second-moment closure. Our numerical results show that a cubic NLEVM that performs considerably well in other benchmark turbulent flows, such as the Craft, Launder and Suga model and the Huang and Ma model, is able to capture the major features of the highly curved turbulent U-duct flow, including the damping of turbulence near the convex wall, the enhancement of turbulence near the concave wall, and the subsequent turbulent flow separation. The predictions of the cubic models are quite close to that of the RSM, in relatively good agreement with the experimental data, which suggests that these inodels may be employed to simulate the turbulent curved flows in engineering applications.

  1. An evaluation of prior influence on the predictive ability of Bayesian model averaging.

    Science.gov (United States)

    St-Louis, Véronique; Clayton, Murray K; Pidgeon, Anna M; Radeloff, Volker C

    2012-03-01

    Model averaging is gaining popularity among ecologists for making inference and predictions. Methods for combining models include Bayesian model averaging (BMA) and Akaike's Information Criterion (AIC) model averaging. BMA can be implemented with different prior model weights, including the Kullback-Leibler prior associated with AIC model averaging, but it is unclear how the prior model weight affects model results in a predictive context. Here, we implemented BMA using the Bayesian Information Criterion (BIC) approximation to Bayes factors for building predictive models of bird abundance and occurrence in the Chihuahuan Desert of New Mexico. We examined how model predictive ability differed across four prior model weights, and how averaged coefficient estimates, standard errors and coefficients' posterior probabilities varied for 16 bird species. We also compared the predictive ability of BMA models to a best single-model approach. Overall, Occam's prior of parsimony provided the best predictive models. In general, the Kullback-Leibler prior, however, favored complex models of lower predictive ability. BMA performed better than a best single-model approach independently of the prior model weight for 6 out of 16 species. For 6 other species, the choice of the prior model weight affected whether BMA was better than the best single-model approach. Our results demonstrate that parsimonious priors may be favorable over priors that favor complexity for making predictions. The approach we present has direct applications in ecology for better predicting patterns of species' abundance and occurrence.

  2. Building enterprise reuse program--A model-based approach

    Institute of Scientific and Technical Information of China (English)

    梅宏; 杨芙清

    2002-01-01

    Reuse is viewed as a realistically effective approach to solving software crisis. For an organization that wants to build a reuse program, technical and non-technical issues must be considered in parallel. In this paper, a model-based approach to building systematic reuse program is presented. Component-based reuse is currently a dominant approach to software reuse. In this approach, building the right reusable component model is the first important step. In order to achieve systematic reuse, a set of component models should be built from different perspectives. Each of these models will give a specific view of the components so as to satisfy different needs of different persons involved in the enterprise reuse program. There already exist some component models for reuse from technical perspectives. But less attention is paid to the reusable components from a non-technical view, especially from the view of process and management. In our approach, a reusable component model--FLP model for reusable component--is introduced. This model describes components from three dimensions (Form, Level, and Presentation) and views components and their relationships from the perspective of process and management. It determines the sphere of reusable components, the time points of reusing components in the development process, and the needed means to present components in terms of the abstraction level, logic granularity and presentation media. Being the basis on which the management and technical decisions are made, our model will be used as the kernel model to initialize and normalize a systematic enterprise reuse program.

  3. Predicting the Impact of Rock Blasting on Building Structures at Awunakrom in the Ahanta West District of Ghana

    Directory of Open Access Journals (Sweden)

    K.J. Bansah

    2014-07-01

    Full Text Available Blasting is an important process after drilling is completed in hard rock mining. It involves placing explosives in drill holes and detonating them to cause explosion. The energy released during this process fragments the rocks into sizes for desired end use. The detonation of these explosives may produce undesirable effects such as ground vibration which is capable of causing damage to building structures. It is therefore, necessary to conduct blast impact studies to determine potential impact of blast induced ground vibration prior to mining and establish remediation techniques. Blast impact study was conducted at Awunakrom in the Ahanta West District of Ghana. Building structures within the study area were mapped and characterized. A blast impact prediction model was also generated. Blast induced vibrations that may propagate from the Father Brown pit of Golden Star Wassa Limited using various instantaneous charges were determined. It was found that bench blasting at the Father Brown pit has a potential of causing damage to building structures within the Awunakrom community if the maximum instantaneous charge adopted at the southernmost periphery of the pit exceeds 30 kg. It was therefore, recommended that all bench blast conducted at the southern periphery of the Father Brown pit should adopt a maximum instantaneous charge of 30 kg to avert any potential blast damage. However, variable instantaneous charges of more than 30 kg can be adopted as the blast location moves towards the northern periphery.

  4. Building 235-F Goldsim Fate And Transport Model

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, G. A.; Phifer, M. A.

    2012-09-14

    Savannah River National Laboratory (SRNL) personnel, at the request of Area Completion Projects (ACP), evaluated In-Situ Disposal (ISD) alternatives that are under consideration for deactivation and decommissioning (D&D) of Building 235-F and the Building 294-2F Sand Filter. SRNL personnel developed and used a GoldSim fate and transport model, which is consistent with Musall 2012, to evaluate relative to groundwater protection, ISD alternatives that involve either source removal and/or the grouting of portions or all of 235-F. This evaluation was conducted through the development and use of a Building 235-F GoldSim fate and transport model. The model simulates contaminant release from four 235-F process areas and the 294-2F Sand Filter. In addition, it simulates the fate and transport through the vadose zone, the Upper Three Runs (UTR) aquifer, and the Upper Three Runs (UTR) creek. The model is designed as a stochastic model, and as such it can provide both deterministic and stochastic (probabilistic) results. The results show that the median radium activity concentrations exceed the 5 ?Ci/L radium MCL at the edge of the building for all ISD alternatives after 10,000 years, except those with a sufficient amount of inventory removed. A very interesting result was that grouting was shown to basically have minimal effect on the radium activity concentration. During the first 1,000 years grouting may have some small positive benefit relative to radium, however after that it may have a slightly deleterious effect. The Pb-210 results, relative to its 0.06 ?Ci/L PRG, are essentially identical to the radium results, but the Pb-210 results exhibit a lesser degree of exceedance. In summary, some level of inventory removal will be required to ensure that groundwater standards are met.

  5. 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

  6. Building blocks for automated elucidation of metabolites: Machine learning methods for NMR prediction

    Science.gov (United States)

    Kuhn, Stefan; Egert, Björn; Neumann, Steffen; Steinbeck, Christoph

    2008-01-01

    Background Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE) of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. Results A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. Conclusion NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites. PMID:18817546

  7. Building blocks for automated elucidation of metabolites: Machine learning methods for NMR prediction

    Directory of Open Access Journals (Sweden)

    Neumann Steffen

    2008-09-01

    Full Text Available Abstract Background Current efforts in Metabolomics, such as the Human Metabolome Project, collect structures of biological metabolites as well as data for their characterisation, such as spectra for identification of substances and measurements of their concentration. Still, only a fraction of existing metabolites and their spectral fingerprints are known. Computer-Assisted Structure Elucidation (CASE of biological metabolites will be an important tool to leverage this lack of knowledge. Indispensable for CASE are modules to predict spectra for hypothetical structures. This paper evaluates different statistical and machine learning methods to perform predictions of proton NMR spectra based on data from our open database NMRShiftDB. Results A mean absolute error of 0.18 ppm was achieved for the prediction of proton NMR shifts ranging from 0 to 11 ppm. Random forest, J48 decision tree and support vector machines achieved similar overall errors. HOSE codes being a notably simple method achieved a comparatively good result of 0.17 ppm mean absolute error. Conclusion NMR prediction methods applied in the course of this work delivered precise predictions which can serve as a building block for Computer-Assisted Structure Elucidation for biological metabolites.

  8. CHEERUP: A General Software-Environment for Building, Using and Administering Predictive Monitoring Portals

    Directory of Open Access Journals (Sweden)

    MUSSI, S.

    2011-11-01

    Full Text Available The intended meaning of the term predictive monitoring used in the paper is the following. A population of subjects (living beings, machines, works of art, etc. is monitored by a domain expert with regard to the possible occurrence of an undesired/desired event E. More precisely, an expert periodically (e.g. every two years, every week, etc. depending on the specific application examines the single subjects and, for each of them, enters examination outcomes in a database where statistical data are automatically processed in order to produce probabilistic inferences about the occurrence in the future of E for the subject under examination (individualized prediction. This allows the expert to take suitable measures in advance in order to prevent/favour the occurrence of E for the subject. Such an approach to predictive monitoring requires that the expert who monitors subjects has at his/her disposal a suitable software system provided with database and algorithms for both properly managing monitoring-processes and producing probabilistic predictions. The paper presents CHEERUP : a prototype product, usable via Internet, that consists in a general software-environment for building, using and administering specific predictive monitoring software-systems (in the paper called portals.

  9. 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...

  10. Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.

    Science.gov (United States)

    Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep

    2009-08-31

    Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future

  11. Building a Decision Support System for Inpatient Admission Prediction With the Manchester Triage System and Administrative Check-in Variables.

    Science.gov (United States)

    Zlotnik, Alexander; Alfaro, Miguel Cuchí; Pérez, María Carmen Pérez; Gallardo-Antolín, Ascensión; Martínez, Juan Manuel Montero

    2016-05-01

    The usage of decision support tools in emergency departments, based on predictive models, capable of estimating the probability of admission for patients in the emergency department may give nursing staff the possibility of allocating resources in advance. We present a methodology for developing and building one such system for a large specialized care hospital using a logistic regression and an artificial neural network model using nine routinely collected variables available right at the end of the triage process.A database of 255.668 triaged nonobstetric emergency department presentations from the Ramon y Cajal University Hospital of Madrid, from January 2011 to December 2012, was used to develop and test the models, with 66% of the data used for derivation and 34% for validation, with an ordered nonrandom partition. On the validation dataset areas under the receiver operating characteristic curve were 0.8568 (95% confidence interval, 0.8508-0.8583) for the logistic regression model and 0.8575 (95% confidence interval, 0.8540-0. 8610) for the artificial neural network model. χ Values for Hosmer-Lemeshow fixed "deciles of risk" were 65.32 for the logistic regression model and 17.28 for the artificial neural network model. A nomogram was generated upon the logistic regression model and an automated software decision support system with a Web interface was built based on the artificial neural network model.

  12. Toward a General Research Process for Using Dubin's Theory Building Model

    Science.gov (United States)

    Holton, Elwood F.; Lowe, Janis S.

    2007-01-01

    Dubin developed a widely used methodology for theory building, which describes the components of the theory building process. Unfortunately, he does not define a research process for implementing his theory building model. This article proposes a seven-step general research process for implementing Dubin's theory building model. An example of a…

  13. Toward a General Research Process for Using Dubin's Theory Building Model

    Science.gov (United States)

    Holton, Elwood F.; Lowe, Janis S.

    2007-01-01

    Dubin developed a widely used methodology for theory building, which describes the components of the theory building process. Unfortunately, he does not define a research process for implementing his theory building model. This article proposes a seven-step general research process for implementing Dubin's theory building model. An example of a…

  14. Combining a Detailed Building Energy Model with a Physically-Based Urban Canopy Model

    Science.gov (United States)

    Bueno, Bruno; Norford, Leslie; Pigeon, Grégoire; Britter, Rex

    2011-09-01

    A scheme that couples a detailed building energy model, EnergyPlus, and an urban canopy model, the Town Energy Balance (TEB), is presented. Both models are well accepted and evaluated within their individual scientific communities. The coupled scheme proposes a more realistic representation of buildings and heating, ventilation and air-conditioning (HVAC) systems, which allows a broader analysis of the two-way interactions between the energy performance of buildings and the urban climate around the buildings. The scheme can be used to evaluate the building energy models that are being developed within the urban climate community. In this study, the coupled scheme is evaluated using measurements conducted over the dense urban centre of Toulouse, France. The comparison includes electricity and natural gas energy consumption of buildings, building façade temperatures, and urban canyon air temperatures. The coupled scheme is then used to analyze the effect of different building and HVAC system configurations on building energy consumption, waste heat released from HVAC systems, and outdoor air temperatures for the case study of Toulouse. Three different energy efficiency strategies are analyzed: shading devices, economizers, and heat recovery.

  15. Towards The Long-Term Preservation of Building Information Models

    DEFF Research Database (Denmark)

    Beetz, Jacob; Dietze, Stefan; Berndt, René

    2013-01-01

    primarily been on textual and audio-visual media types. With the recent paradigm shift in architecture and construction from analog 2D plans and scale models to digital 3D information models of buildings, long-term preservation efforts must turn their attention to this new type of data. Currently......Long-term preservation of information about artifacts of the built environment is crucial to provide the ability to retrofit legacy buildings, to preserve cultural heritage, to ensure security precautions, to enable knowledge-reuse of design and engineering solutions and to guarantee the legal...... liabilities of all stakeholders (e.g. designer, engineers). Efforts for the digital preservation of information have come a long way and a number of mature methods, frameworks, guidelines and software systems are at the disposal of librarians and archivists. However, the focus of these developments has...

  16. Lidar-equipped uav for building information modelling

    Science.gov (United States)

    Roca, D.; Armesto, J.; Lagüela, S.; Díaz-Vilariño, L.

    2014-06-01

    The trend to minimize electronic devices in the last decades accounts for Unmanned Airborne Vehicles (UAVs) as well as for sensor technologies and imaging devices, resulting in a strong revolution in the surveying and mapping industries. However, only within the last few years the LIDAR sensor technology has achieved sufficiently reduction in terms of size and weight to be considered for UAV platforms. This paper presents an innovative solution to capture point cloud data from a Lidar-equipped UAV and further perform the 3D modelling of the whole envelope of buildings in BIM format. A mini-UAV platform is used (weigh less than 5 kg and up to 1.5 kg of sensor payload), and data from two different acquisition methodologies is processed and compared with the aim at finding the optimal configuration for the generation of 3D models of buildings for energy studies

  17. Building Information Modeling for Managing Design and Construction

    DEFF Research Database (Denmark)

    Berard, Ole Bengt

    outcome of construction work. Even though contractors regularly encounter design information problems, these issues are accepted as a condition of doing business and better design information has yet to be defined. Building information modeling has the inherent promise of improving the quality of design...... information by suggesting technologies and methods that are supposed to improve design information. However, building information modeling provides no means to assess these improvements of design information. This research introduces design information quality as an equivalent to information quality...... of five points, ranging from traditional to most innovative practice. However, since technology and practice changes rapidly, the definition of each score has to be adjusted regularly. Finally, the framework is applied to a construction project in order to evaluate its practical application. The framework...

  18. State reduced order models for the modelling of the thermal behavior of buildings

    Energy Technology Data Exchange (ETDEWEB)

    Menezo, Christophe; Bouia, Hassan; Roux, Jean-Jacques; Depecker, Patrick [Institute National de Sciences Appliquees de Lyon, Villeurbanne Cedex, (France). Centre de Thermique de Lyon (CETHIL). Equipe Thermique du Batiment]. E-mail: menezo@insa-cethil-etb.insa-lyon.fr; bouia@insa-cethil-etb.insa-lyon.fr; roux@insa-cethil-etb.insa-lyon.fr; depecker@insa-cethil-etb.insa-lyon.fr

    2000-07-01

    This work is devoted to the field of building physics and related to the reduction of heat conduction models. The aim is to enlarge the model libraries of heat and mass transfer codes through limiting the considerable dimensions reached by the numerical systems during the modelling process of a multizone building. We show that the balanced realization technique, specifically adapted to the coupling of reduced order models with the other thermal phenomena, turns out to be very efficient. (author)

  19. 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.

  20. 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...

  1. PEB: thermal oriented architectural modeling for building energy efficiency regulations

    OpenAIRE

    Leclercq, Pierre; Juchmes, Roland; Delfosse, Vincent; Safin, Stéphane; Dawans, Arnaud; Dawans, Adrien

    2011-01-01

    As part of the overhauling of the building energy efficiency regulations (following European directive 2002/91/CE), the Wallonia and Brussels-Capital Region commissioned the LUCID to develop an optional 3D graphic encoding module to be integrated with the core energy efficiency computation engine developed by Altran Europe. Our contribution consisted mostly in analyzing the target users’ needs and representations (ergonomics, UI, interactions) and implementing a bespoke 3D CAD modeler dedicat...

  2. A model of backdraft phenomenon in building fires

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In order to further investigate the physical mechanism of the backdraft phenomenon in building fires, a simplified math ematical model is established based on energy balance equation, and its catastrophe mechanism is analyzed based on catastrophe theory, and the relationship between system control variables and fire conditions is studied. It is indicated that the backdraft phenomenon is a kind of typical catastrophe behavior, and of the common characteristics of catastrophe.

  3. 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)

  4. Model code for energy conservation in new building construction

    Energy Technology Data Exchange (ETDEWEB)

    None

    1977-12-01

    In response to the recognized lack of existing consensus standards directed to the conservation of energy in building design and operation, the preparation and publication of such a standard was accomplished with the issuance of ASHRAE Standard 90-75 ''Energy Conservation in New Building Design,'' by the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., in 1975. This standard addressed itself to recommended practices for energy conservation, using both depletable and non-depletable sources. A model code for energy conservation in building construction has been developed, setting forth the minimum regulations found necessary to mandate such conservation. The code addresses itself to the administration, design criteria, systems elements, controls, service water heating and electrical distribution and use, both for depletable and non-depletable energy sources. The technical provisions of the document are based on ASHRAE 90-75 and it is intended for use by state and local building officials in the implementation of a statewide energy conservation program.

  5. Simulation and Big Data Challenges in Tuning Building Energy Models

    Energy Technology Data Exchange (ETDEWEB)

    Sanyal, Jibonananda [ORNL; New, Joshua Ryan [ORNL

    2013-01-01

    EnergyPlus is the flagship building energy simulation software used to model whole building energy consumption for residential and commercial establishments. A typical input to the program often has hundreds, sometimes thousands of parameters which are typically tweaked by a buildings expert to get it right . This process can sometimes take months. Autotune is an ongoing research effort employing machine learning techniques to automate the tuning of the input parameters for an EnergyPlus input description of a building. Even with automation, the computational challenge faced to run the tuning simulation ensemble is daunting and requires the use of supercomputers to make it tractable in time. In this proposal, we describe the scope of the problem, the technical challenges faced and overcome, the machine learning techniques developed and employed, and the software infrastructure developed/in development when taking the EnergyPlus engine, which was primarily designed to run on desktops, and scaling it to run on shared memory supercomputers (Nautilus) and distributed memory supercomputers (Frost and Titan). The parametric simulations produce data in the order of tens to a couple of hundred terabytes.We describe the approaches employed to streamline and reduce bottlenecks in the workflow for this data, which is subsequently being made available for the tuning effort as well as made available publicly for open-science.

  6. A Predictive Model for Wind Farms Using Dynamic Mode Decomposition

    Science.gov (United States)

    Thomas, Vaughan; Meneveau, Charles; Gayme, Dennice

    2016-11-01

    In this work we extend traditional dynamic mode decomposition (DMD) to develop a linear predictive model for the time evolution of the velocity field for a multiple-turbine wind farm. Traditional DMD identifies a set of DMD modes which can be used to produce a linear system that approximates the dynamics of the original system. Typically, these DMD modes consist of those that both grow and decay, but in order to develop a predictive model we need a system that evolves along a manifold that neither grows nor decays. Here we modify the DMD calculation to build such a model. We then apply this method to three dimensional large eddy simulations (LES) of a multi-turbine wind farm. Our predictive wind farm model is initialized with a small time series of data independent of the original data used to create the system. When initialized in this manner our DMD based model can reproduce the subsequent time evolution of the velocity field over ten inter-turbine convective timescales with a gradual falloff in performance. This work is supported by the National Science Foundation (Grants ECCS-1230788 and OISE-1243482, the WINDINSPIRE project).

  7. Building disc structure and galaxy properties through angular momentum: The DARK SAGE semi-analytic model

    CERN Document Server

    Stevens, Adam R H; Mutch, Simon J

    2016-01-01

    We present the new semi-analytic model of galaxy evolution, DARK SAGE, a heavily modified version of the publicly available SAGE code. The model is designed for detailed evolution of galactic discs. We evolve discs in a series of annuli with fixed specific angular momentum, which allows us to make predictions for the radial and angular-momentum structure of galaxies. Most physical processes, including all channels of star formation and associated feedback, are performed in these annuli. We present the surface density profiles of our model spiral galaxies, both as a function of radius and specific angular momentum, and find the discs naturally build a pseduobulge-like component. Our main results are focussed on predictions relating to the integrated mass--specific angular momentum relation of stellar discs. The model produces a distinct sequence between these properties in remarkable agreement with recent observational literature. We investigate the impact Toomre disc instabilities have on shaping this sequenc...

  8. 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.

  9. Comparison of cross-validation and bootstrap aggregating for building a seasonal streamflow forecast model

    Science.gov (United States)

    Schick, Simon; Rössler, Ole; Weingartner, Rolf

    2016-10-01

    Based on a hindcast experiment for the period 1982-2013 in 66 sub-catchments of the Swiss Rhine, the present study compares two approaches of building a regression model for seasonal streamflow forecasting. The first approach selects a single "best guess" model, which is tested by leave-one-out cross-validation. The second approach implements the idea of bootstrap aggregating, where bootstrap replicates are employed to select several models, and out-of-bag predictions provide model testing. The target value is mean streamflow for durations of 30, 60 and 90 days, starting with the 1st and 16th day of every month. Compared to the best guess model, bootstrap aggregating reduces the mean squared error of the streamflow forecast by seven percent on average. Thus, if resampling is anyway part of the model building procedure, bootstrap aggregating seems to be a useful strategy in statistical seasonal streamflow forecasting. Since the improved accuracy comes at the cost of a less interpretable model, the approach might be best suited for pure prediction tasks, e.g. as in operational applications.

  10. Modeling of fire smoke movement in multizone garments building using two open source platforms

    Science.gov (United States)

    Khandoker, Md. Arifur Rahman; Galib, Musanna; Islam, Adnan; Rahman, Md. Ashiqur

    2017-06-01

    Casualty of garment factory workers from factory fire in Bangladesh is a recurring tragedy. Smoke, which is more fatal than fire itself, often propagates through different pathways from lower to upper floors during building fire. Among the toxic gases produced from a building fire, carbon monoxide (CO) can be deadly, even in small amounts. This paper models the propagation and transportation of fire induced smoke (CO) that resulted from the burning of synthetic polyester fibers using two open source platforms, CONTAM and Fire Dynamics Simulator (FDS). Smoke migration in a generic multistoried garment factory building in Bangladesh is modeled using CONTAM where each floor is compartmentalized by different zones. The elevator and stairway shafts are modeled by phantom zones to simulate contaminant (CO) transport from one floor to upper floors. FDS analysis involves burning of two different stacks of polyester jacket of six feet height and with a maximum heat release rate per unit area of 1500kw/m2 over a storage area 50m2 and 150m2, respectively. The resulting CO generation and removal rates from FDS are used in CONTAM to predict fire-borne CO propagation in different zones of the garment building. Findings of the study exhibit that the contaminant flow rate is a strong function of the position of building geometry, location of initiation of fire, amount of burnt material, presence of AHU and contaminant generation and removal rate of CO from the source location etc. The transport of fire-smoke in the building Hallways, stairways and lifts are also investigated in detail to examine the safe egress of the occupants in case of fire.

  11. Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

    Energy Technology Data Exchange (ETDEWEB)

    Liao, James C. [Univ. of California, Los Angeles, CA (United States)

    2016-10-01

    Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

  12. 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.

  13. 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.

  14. Numerical Investigation of a Moisture Evaporation Model in Building Materials

    CERN Document Server

    Amirkhanov, I V; Pavlish, M; Puzynina, T P; Puzynin, I V; Sarhadov, I

    2005-01-01

    The properties of a model of moisture evaporation in a porous building material of a rectangular form proposed in [1] are investigated. Algorithms of solving a nonlinear diffusion equation with initial and boundary conditions simulating the dynamic distribution of moisture concentration, calculation of coefficients of a polynomial describing transport of moisture with usage of experimental measurement of moisture concentration in a sample are developed and investigated. Research on the properties of the model is carried out depending on the degree of the polynomial, a set of its coefficients, and the quantity of the used experimental data.

  15. The Proposal of Model for Building Cooperation Management in Company

    Directory of Open Access Journals (Sweden)

    Josef Vodák

    2015-12-01

    Full Text Available The goal of the article is to use detailed literature analysis and findings of an empirical research, and to propose model for building cooperation management in a company. The article brings a valuable tool to company managers in a form of a complex and detailed model to achieve successful implementation of cooperation management in a company. The article thus provides a tool for company managers for managing their cooperation projects and activities. Use of this tool is meant to help minimize occurrence of conflict situations and to support smooth progress of cooperation activities.

  16. The Prediction Model of Dam Uplift Pressure Based on Random Forest

    Science.gov (United States)

    Li, Xing; Su, Huaizhi; Hu, Jiang

    2017-09-01

    The prediction of the dam uplift pressure is of great significance in the dam safety monitoring. Based on the comprehensive consideration of various factors, 18 parameters are selected as the main factors affecting the prediction of uplift pressure, use the actual monitoring data of uplift pressure as the evaluation factors for the prediction model, based on the random forest algorithm and support vector machine to build the dam uplift pressure prediction model to predict the uplift pressure of the dam, and the predict performance of the two models were compared and analyzed. At the same time, based on the established random forest prediction model, the significance of each factor is analyzed, and the importance of each factor of the prediction model is calculated by the importance function. Results showed that: (1) RF prediction model can quickly and accurately predict the uplift pressure value according to the influence factors, the average prediction accuracy is above 96%, compared with the support vector machine (SVM) model, random forest model has better robustness, better prediction precision and faster convergence speed, and the random forest model is more robust to missing data and unbalanced data. (2) The effect of water level on uplift pressure is the largest, and the influence of rainfall on the uplift pressure is the smallest compared with other factors.

  17. An Iterative Algorithm to Build Chinese Language Models

    CERN Document Server

    Luo, X; Luo, Xiaoqiang; Roukos, Salim

    1996-01-01

    We present an iterative procedure to build a Chinese language model (LM). We segment Chinese text into words based on a word-based Chinese language model. However, the construction of a Chinese LM itself requires word boundaries. To get out of the chicken-and-egg problem, we propose an iterative procedure that alternates two operations: segmenting text into words and building an LM. Starting with an initial segmented corpus and an LM based upon it, we use a Viterbi-liek algorithm to segment another set of data. Then, we build an LM based on the second set and use the resulting LM to segment again the first corpus. The alternating procedure provides a self-organized way for the segmenter to detect automatically unseen words and correct segmentation errors. Our preliminary experiment shows that the alternating procedure not only improves the accuracy of our segmentation, but discovers unseen words surprisingly well. The resulting word-based LM has a perplexity of 188 for a general Chinese corpus.

  18. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    DEFF Research Database (Denmark)

    Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna;

    2014-01-01

    Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful...... applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min...... on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together....

  19. Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

    KAUST Repository

    Marcatili, Paolo

    2014-11-06

    © 2014 Nature America, Inc. All rights reserved. Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (~10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

  20. Natural selection at work: an accelerated evolutionary computing approach to predictive model selection

    Directory of Open Access Journals (Sweden)

    Olcay Akman

    2010-07-01

    Full Text Available We implement genetic algorithm based predictive model building as an alternative to the traditional stepwise regression. We then employ the Information Complexity Measure (ICOMP as a measure of model fitness instead of the commonly used measure of R-square. Furthermore, we propose some modifications to the genetic algorithm to increase the overall efficiency.

  1. Metadata and their impact on processes in Building Information Modeling

    Directory of Open Access Journals (Sweden)

    Vladimir Nyvlt

    2014-04-01

    Full Text Available Building Information Modeling (BIM itself contains huge potential, how to increase effectiveness of every project in its all life cycle. It means from initial investment plan through project and building-up activities to long-term usage and property maintenance and finally demolition. Knowledge Management or better say Knowledge Sharing covers two sets of tools, managerial and technological. Manager`s needs are real expectations and desires of final users in terms of how could they benefit from managing long-term projects, covering whole life cycle in terms of sparing investment money and other resources. Technology employed can help BIM processes to support and deliver these benefits to users. How to use this technology for data and metadata collection, storage and sharing, which processes may these new technologies deploy. We will touch how to cover optimized processes proposal for better and smooth support of knowledge sharing within project time-scale, and covering all its life cycle.

  2. 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.

  3. 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.

  4. Map algebra and model algebra for integrated model building

    NARCIS (Netherlands)

    Schmitz, O.; Karssenberg, D.J.; Jong, K. de; Kok, J.-L. de; Jong, S.M. de

    2013-01-01

    Computer models are important tools for the assessment of environmental systems. A seamless workflow of construction and coupling of model components is essential for environmental scientists. However, currently available software packages are often tailored either to the construction of model compo

  5. Procedural Modeling for Rapid-Prototyping of Multiple Building Phases

    Science.gov (United States)

    Saldana, M.; Johanson, C.

    2013-02-01

    RomeLab is a multidisciplinary working group at UCLA that uses the city of Rome as a laboratory for the exploration of research approaches and dissemination practices centered on the intersection of space and time in antiquity. In this paper we present a multiplatform workflow for the rapid-prototyping of historical cityscapes through the use of geographic information systems, procedural modeling, and interactive game development. Our workflow begins by aggregating archaeological data in a GIS database. Next, 3D building models are generated from the ArcMap shapefiles in Esri CityEngine using procedural modeling techniques. A GIS-based terrain model is also adjusted in CityEngine to fit the building elevations. Finally, the terrain and city models are combined in Unity, a game engine which we used to produce web-based interactive environments which are linked to the GIS data using keyhole markup language (KML). The goal of our workflow is to demonstrate that knowledge generated within a first-person virtual world experience can inform the evaluation of data derived from textual and archaeological sources, and vice versa.

  6. 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.

  7. 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.

  8. 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.

  9. Building a better fragment library for de novo protein structure prediction.

    Directory of Open Access Journals (Sweden)

    Saulo H P de Oliveira

    Full Text Available Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10. We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. "Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources".

  10. 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.

  11. 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

  12. 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...

  13. 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.

  14. 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...

  15. Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU

    Directory of Open Access Journals (Sweden)

    Kennedy Curtis E

    2011-10-01

    Full Text Available Abstract Background Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. Methods We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Results Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1 selecting candidate variables; 2 specifying measurement parameters; 3 defining data format; 4 defining time window duration and resolution; 5 calculating latent variables for candidate variables not directly measured; 6 calculating time series features as latent variables; 7 creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8

  16. 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

  17. 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...

  18. 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

  19. 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.

  20. 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…