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...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  2. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  3. 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 ...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption.......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...

  4. Building and Verifying a Predictive Model of Interruption Resumption

    Science.gov (United States)

    2012-03-01

    the gardener to remember those plants (and whether they need to be removed), and so will not commit resources to remember that information . The overall...camera), the storyteller needed help much less often. This result suggests that when there is no one to help them remember the last thing they said...INV ITED P A P E R Building and Verifying a Predictive Model of Interruption Resumption Help from a robot, to allow a human storyteller to continue

  5. Multiscale modelling for better hygrothermal prediction of porous building materials

    Directory of Open Access Journals (Sweden)

    Belarbi Rafik

    2018-01-01

    Full Text Available The aim of this work is to understand the influence of the microstructuralgeometric parameters of porous building materials on the mechanisms of coupled heat, air and moisture transfers, in order to predict behavior of the building to control and improve it in its durability. For this a multi-scale approach is implemented. It consists of mastering the dominant physical phenomena and their interactions on the microscopic scale. Followed by a dual-scale modelling, microscopic-macroscopic, of coupled heat, air and moisture transfers that takes into account the intrinsic properties and microstructural topology of the material using X-ray tomography combined with the correlation of 3D images were undertaken. In fact, the hygromorphicbehavior under hydric solicitations was considered. In this context, a model of coupled heat, air and moisture transfer in porous building materials was developed using the periodic homogenization technique. These informations were subsequently implemented in a dynamic computation simulation that model the hygrothermalbehaviourof material at the scale of the envelopes and indoor air quality of building. Results reveals that is essential to consider the local behaviors of materials, but also to be able to measure and quantify the evolution of its properties on a macroscopic scale from the youngest age of the material. In addition, comparisons between experimental and numerical temperature and relative humidity profilesin multilayers wall and in building envelopes were undertaken. Good agreements were observed.

  6. Early experiences building a software quality prediction model

    Science.gov (United States)

    Agresti, W. W.; Evanco, W. M.; Smith, M. C.

    1990-01-01

    Early experiences building a software quality prediction model are discussed. The overall research objective is to establish a capability to project a software system's quality from an analysis of its design. The technical approach is to build multivariate models for estimating reliability and maintainability. Data from 21 Ada subsystems were analyzed to test hypotheses about various design structures leading to failure-prone or unmaintainable systems. Current design variables highlight the interconnectivity and visibility of compilation units. Other model variables provide for the effects of reusability and software changes. Reported results are preliminary because additional project data is being obtained and new hypotheses are being developed and tested. Current multivariate regression models are encouraging, explaining 60 to 80 percent of the variation in error density of the subsystems.

  7. 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.

  8. 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

    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 ...

  9. 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.

  10. 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.

  11. IBM SPSS modeler essentials effective techniques for building powerful data mining and predictive analytics solutions

    CERN Document Server

    McCormick, Keith; Wei, Bowen

    2017-01-01

    IBM SPSS Modeler allows quick, efficient predictive analytics and insight building from your data, and is a popularly used data mining tool. This book will guide you through the data mining process, and presents relevant statistical methods which are used to build predictive models and conduct other analytic tasks using IBM SPSS Modeler. From ...

  12. Key Questions in Building Defect Prediction Models in Practice

    Science.gov (United States)

    Ramler, Rudolf; Wolfmaier, Klaus; Stauder, Erwin; Kossak, Felix; Natschläger, Thomas

    The information about which modules of a future version of a software system are defect-prone is a valuable planning aid for quality managers and testers. Defect prediction promises to indicate these defect-prone modules. However, constructing effective defect prediction models in an industrial setting involves a number of key questions. In this paper we discuss ten key questions identified in context of establishing defect prediction in a large software development project. Seven consecutive versions of the software system have been used to construct and validate defect prediction models for system test planning. Furthermore, the paper presents initial empirical results from the studied project and, by this means, contributes answers to the identified questions.

  13. 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…

  14. A kind of prediction from superstring model building

    CERN Document Server

    Muñoz, C

    2001-01-01

    Assuming that the Standard Model of Particle Physics arises from the $E_8\\times E_8$ Heterotic String Theory, we try to solve the discrepancy between the unification scale predicted by this theory ($\\approx g_{GUT}\\times 5.27\\cdot 10^{17}$ GeV) and the value deduced from LEP experiments ($\\approx 2\\cdot 10^{16}$ GeV). A crucial ingredient in our solution is the presence at low energies of three generations of supersymmetric Higgses and vector-like colour triplets. As a by-product our analysis gives rise to a strategy which might be useful in order to construct realistic models.

  15. 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

  16. 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.

  17. 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

    with the building controls (windows, thermostats, solar shading etc.). During the last decade, studies about stochastic models of occupants' behaviour in relation to control of the indoor environment have been published. Often the overall aim of these models is to enable more reliable predictions of building...... 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....... However, comparisons of the average stochastic predictions with the measured temperatures, relative humidity and CO2 concentrations revealed that the models did not predict the actual indoor environmental conditions well....

  18. 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...

  19. Actual building energy use patterns and their implications for predictive modeling

    International Nuclear Information System (INIS)

    Heidarinejad, Mohammad; Cedeño-Laurent, Jose G.; Wentz, Joshua R.; Rekstad, Nicholas M.; Spengler, John D.; Srebric, Jelena

    2017-01-01

    Highlights: • Developed three building categories based on energy use patterns of campus buildings. • Evaluated implication of temporal energy data granularity on predictive modeling. • Demonstrated importance of monitoring daily chilled water consumption. • Identified interval electricity data as an indicator of building operation schedules. • Demonstrated a calibration process for energy modeling of a campus building. - Abstract: The main goal of this study is to understand the patterns in which commercial buildings consume energy, rather than evaluating building energy use based on aggregate utility bills typically linked to building principal tenant activity or occupancy type. The energy consumption patterns define buildings as externally-load, internally-load, or mixed-load dominated buildings. Penn State and Harvard campuses serve as case studies for this particular research project. The buildings in these two campuses use steam, chilled water, and electricity as energy commodities and maintain databases of different resolutions to include minute, hourly, daily, and monthly data instances depending on the commodity and available data acquisition system. The results of this study show monthly steam consumption directly correlates to outdoor environmental conditions for 88% of the studied buildings, while chilled water consumption has negligible correlation to the outdoor environmental conditions. Thus, in terms of monthly chilled water consumption, 86% of buildings are internally-load and mixed-load dominated, respectively. Chilled water consumption is better suited for the daily analyses compared to the monthly and hourly analyses. While the influence of building operation schedules affects the analyses at the hourly level, the monthly chilled water consumptions are not good indicators of the building energy consumption patterns. Electricity consumption at the monthly (or seasonal) level can support the building energy simulation tools for the

  20. A diffusivity model for predicting VOC diffusion in porous building materials based on fractal theory

    International Nuclear Information System (INIS)

    Liu, Yanfeng; Zhou, Xiaojun; Wang, Dengjia; Song, Cong; Liu, Jiaping

    2015-01-01

    Highlights: • Fractal theory is introduced into the prediction of VOC diffusion coefficient. • MSFC model of the diffusion coefficient is developed for porous building materials. • The MSFC model contains detailed pore structure parameters. • The accuracy of the MSFC model is verified by independent experiments. - Abstract: Most building materials are porous media, and the internal diffusion coefficients of such materials have an important influences on the emission characteristics of volatile organic compounds (VOCs). The pore structure of porous building materials has a significant impact on the diffusion coefficient. However, the complex structural characteristics bring great difficulties to the model development. The existing prediction models of the diffusion coefficient are flawed and need to be improved. Using scanning electron microscope (SEM) observations and mercury intrusion porosimetry (MIP) tests of typical porous building materials, this study developed a new diffusivity model: the multistage series-connection fractal capillary-bundle (MSFC) model. The model considers the variable-diameter capillaries formed by macropores connected in series as the main mass transfer paths, and the diameter distribution of the capillary bundles obeys a fractal power law in the cross section. In addition, the tortuosity of the macrocapillary segments with different diameters is obtained by the fractal theory. Mesopores serve as the connections between the macrocapillary segments rather than as the main mass transfer paths. The theoretical results obtained using the MSFC model yielded a highly accurate prediction of the diffusion coefficients and were in a good agreement with the VOC concentration measurements in the environmental test chamber.

  1. 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 ...

  2. A Prediction Mechanism of Energy Consumption in Residential Buildings Using Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Israr Ullah

    2018-02-01

    Full Text Available Internet of Things (IoT is considered as one of the future disruptive technologies, which has the potential to bring positive change in human lifestyle and uplift living standards. Many IoT-based applications have been designed in various fields, e.g., security, health, education, manufacturing, transportation, etc. IoT has transformed conventional homes into Smart homes. By attaching small IoT devices to various appliances, we cannot only monitor but also control indoor environment as per user demand. Intelligent IoT devices can also be used for optimal energy utilization by operating the associated equipment only when it is needed. In this paper, we have proposed a Hidden Markov Model based algorithm to predict energy consumption in Korean residential buildings using data collected through smart meters. We have used energy consumption data collected from four multi-storied buildings located in Seoul, South Korea for model validation and results analysis. Proposed model prediction results are compared with three well-known prediction algorithms i.e., Support Vector Machine (SVM, Artificial Neural Network (ANN and Classification and Regression Trees (CART. Comparative analysis shows that our proposed model achieves 2.96 % better than ANN results in terms of root mean square error metric, 6.09 % better than SVM and 9.03 % better than CART results. To further establish and validate prediction results of our proposed model, we have performed temporal granularity analysis. For this purpose, we have evaluated our proposed model for hourly, daily and weekly data aggregation. Prediction accuracy in terms of root mean square error metric for hourly, daily and weekly data is 2.62, 1.54 and 0.46, respectively. This shows that our model prediction accuracy improves for coarse grain data. Higher prediction accuracy gives us confidence to further explore its application in building control systems for achieving better energy efficiency.

  3. 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.

  4. 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....../s, the expectancy factors for the extended PMV model and the extended SET model were from 0.770 to 0.974 and from 1.330 to 1.363, and the adaptive coefficients for the adaptive PMV model and the adaptive SET model were from 0.029 to 0.167 and from-0.213 to-0.195. In addition, the difference in thermal sensation...... 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...

  5. 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.

  6. A diffusivity model for predicting VOC diffusion in porous building materials based on fractal theory.

    Science.gov (United States)

    Liu, Yanfeng; Zhou, Xiaojun; Wang, Dengjia; Song, Cong; Liu, Jiaping

    2015-12-15

    Most building materials are porous media, and the internal diffusion coefficients of such materials have an important influences on the emission characteristics of volatile organic compounds (VOCs). The pore structure of porous building materials has a significant impact on the diffusion coefficient. However, the complex structural characteristics bring great difficulties to the model development. The existing prediction models of the diffusion coefficient are flawed and need to be improved. Using scanning electron microscope (SEM) observations and mercury intrusion porosimetry (MIP) tests of typical porous building materials, this study developed a new diffusivity model: the multistage series-connection fractal capillary-bundle (MSFC) model. The model considers the variable-diameter capillaries formed by macropores connected in series as the main mass transfer paths, and the diameter distribution of the capillary bundles obeys a fractal power law in the cross section. In addition, the tortuosity of the macrocapillary segments with different diameters is obtained by the fractal theory. Mesopores serve as the connections between the macrocapillary segments rather than as the main mass transfer paths. The theoretical results obtained using the MSFC model yielded a highly accurate prediction of the diffusion coefficients and were in a good agreement with the VOC concentration measurements in the environmental test chamber. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

    Directory of Open Access Journals (Sweden)

    Chengdong Li

    2018-01-01

    Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

  8. Development of Building Thermal Load and Discomfort Degree Hour Prediction Models Using Data Mining Approaches

    Directory of Open Access Journals (Sweden)

    Yaolin Lin

    2018-06-01

    Full Text Available Thermal load and indoor comfort level are two important building performance indicators, rapid predictions of which can help significantly reduce the computation time during design optimization. In this paper, a three-step approach is used to develop and evaluate prediction models. Firstly, the Latin Hypercube Sampling Method (LHSM is used to generate a representative 19-dimensional design database and DesignBuilder is then used to obtain the thermal load and discomfort degree hours through simulation. Secondly, samples from the database are used to develop and validate seven prediction models, using data mining approaches including multilinear regression (MLR, chi-square automatic interaction detector (CHAID, exhaustive CHAID (ECHAID, back-propagation neural network (BPNN, radial basis function network (RBFN, classification and regression trees (CART, and support vector machines (SVM. It is found that the MLR and BPNN models outperform the others in the prediction of thermal load with average absolute error of less than 1.19%, and the BPNN model is the best at predicting discomfort degree hour with 0.62% average absolute error. Finally, two hybrid models—MLR (MLR + BPNN and MLR-BPNN—are developed. The MLR-BPNN models are found to be the best prediction models, with average absolute error of 0.82% in thermal load and 0.59% in discomfort degree hour.

  9. A neuro-fuzzy model for prediction of the indoor temperature in typical Australian residential buildings

    Energy Technology Data Exchange (ETDEWEB)

    Alasha' ary, Haitham; Moghtaderi, Behdad; Page, Adrian; Sugo, Heber [Priority Research Centre for Energy, Chemical Engineering, School of Engineering, Faculty of Engineering and Built Environment, the University of Newcastle, Callaghan, Newcastle, NSW 2308 (Australia)

    2009-07-15

    The Masonry Research Group at The University of Newcastle, Australia has embarked on an extensive research program to study the thermal performance of common walling systems in Australian residential buildings by studying the thermal behaviour of four representative purpose-built thermal test buildings (referred to as 'test modules' or simply 'modules' hereafter). The modules are situated on the university campus and are constructed from brick veneer (BV), cavity brick (CB) and lightweight (LW) constructions. The program of study has both experimental and analytical strands, including the use of a neuro-fuzzy approach to predict the thermal behaviour. The latter approach employs an experimental adaptive neuro-fuzzy inference system (ANFIS) which is used in this study to predict the room (indoor) temperatures of the modules under a range of climatic conditions pertinent to Newcastle (NSW, Australia). The study shows that this neuro-fuzzy model is capable of accurately predicting the room temperature of such buildings; thus providing a potential computationally efficient and inexpensive predictive tool for the more effective thermal design of housing. (author)

  10. Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

    Science.gov (United States)

    Koehler, Sarah Muraoka

    suited for nonlinear optimization problems. The parallel computation of the algorithm exploits iterative linear algebra methods for the main linear algebra computations in the algorithm. We show that the splitting of the algorithm is flexible and can thus be applied to various distributed platform configurations. The two proposed algorithms are applied to two main energy and transportation control problems. The first application is energy efficient building control. Buildings represent 40% of energy consumption in the United States. Thus, it is significant to improve the energy efficiency of buildings. The goal is to minimize energy consumption subject to the physics of the building (e.g. heat transfer laws), the constraints of the actuators as well as the desired operating constraints (thermal comfort of the occupants), and heat load on the system. In this thesis, we describe the control systems of forced air building systems in practice. We discuss the "Trim and Respond" algorithm which is a distributed control algorithm that is used in practice, and show that it performs similarly to a one-step explicit DMPC algorithm. Then, we apply the novel distributed primal-dual active-set method and provide extensive numerical results for the building MPC problem. The second main application is the control of ramp metering signals to optimize traffic flow through a freeway system. This application is particularly important since urban congestion has more than doubled in the past few decades. The ramp metering problem is to maximize freeway throughput subject to freeway dynamics (derived from mass conservation), actuation constraints, freeway capacity constraints, and predicted traffic demand. In this thesis, we develop a hybrid model predictive controller for ramp metering that is guaranteed to be persistently feasible and stable. This contrasts to previous work on MPC for ramp metering where such guarantees are absent. We apply a smoothing method to the hybrid model predictive

  11. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression.

    Science.gov (United States)

    Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris

    2016-09-01

    similar performances reaching AUC values 0.783 and 0.779 for traditional Lasso and Tree-Lasso, respectfully. However, information loss of Lasso models is 0.35 bits higher compared to Tree-Lasso model. We propose a method for building predictive models applicable for the detection of readmission risk based on Electronic Health records. Integration of domain knowledge (in the form of ICD-9-CM taxonomy) and a data-driven, sparse predictive algorithm (Tree-Lasso Logistic Regression) resulted in an increase of interpretability of the resulting model. The models are interpreted for the readmission prediction problem in general pediatric population in California, as well as several important subpopulations, and the interpretations of models comply with existing medical understanding of pediatric readmission. Finally, quantitative assessment of the interpretability of the models is given, that is beyond simple counts of selected low-level features. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. 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...... and electricity price. Simulation studies demonstrate the capabilities of the proposed model and algorithm. Compared to traditional operation of heat pumps with constant electricity prices, the optimized operating strategy saves 25-33% of the electricity cost....

  13. Model building

    International Nuclear Information System (INIS)

    Frampton, Paul H.

    1998-01-01

    In this talk I begin with some general discussion of model building in particle theory, emphasizing the need for motivation and testability. Three illustrative examples are then described. The first is the Left-Right model which provides an explanation for the chirality of quarks and leptons. The second is the 331-model which offers a first step to understanding the three generations of quarks and leptons. Third and last is the SU(15) model which can accommodate the light leptoquarks possibly seen at HERA

  14. Model building

    International Nuclear Information System (INIS)

    Frampton, P.H.

    1998-01-01

    In this talk I begin with some general discussion of model building in particle theory, emphasizing the need for motivation and testability. Three illustrative examples are then described. The first is the Left-Right model which provides an explanation for the chirality of quarks and leptons. The second is the 331-model which offers a first step to understanding the three generations of quarks and leptons. Third and last is the SU(15) model which can accommodate the light leptoquarks possibly seen at HERA. copyright 1998 American Institute of Physics

  15. 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......When there is a high penetration of renewables in the energy system, it requires proactive control of large numbers of distributed demand response resources to maintain the system’s reliability and improve its operational economics. This paper presents the Economic Model Predictive Control (EMPC...

  16. Towards building a neural network model for predicting pile static load test curves

    Directory of Open Access Journals (Sweden)

    Alzo’ubi A. K.

    2018-01-01

    Full Text Available In the United Arab Emirates, Continuous Flight Auger piles are the most widely used type of deep foundation. To test the pile behaviour, the Static Load Test is routinely conducted in the field by increasing the dead load while monitoring the displacement. Although the test is reliable, it is expensive to conduct. This test is usually conducted in the UAE to verify the pile capacity and displacement as the load increase and decreases in two cycles. In this paper we will utilize the Artificial Neural Network approach to build a model that can predict a complete Static Load Pile test. We will show that by integrating the pile configuration, soil properties, and ground water table in one artificial neural network model, the Static Load Test can be predicted with confidence. We believe that based on this approach, the model is able to predict the entire pile load test from start to end. The suggested approach is an excellent tool to reduce the cost associated with such expensive tests or to predict pile’s performance ahead of the actual test.

  17. 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.

  18. 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.

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

    Science.gov (United States)

    Challoner, Avril; Pilla, Francesco; Gill, Laurence

    2015-12-01

    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.

  20. 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.

  1. A model to predict radon exhalation from walls to indoor air based on the exhalation from building material samples

    International Nuclear Information System (INIS)

    Sahoo, B.K.; Sapra, B.K.; Gaware, J.J.; Kanse, S.D.; Mayya, Y.S.

    2011-01-01

    In recognition of the fact that building materials are an important source of indoor radon, second only to soil, surface radon exhalation fluxes have been extensively measured from the samples of these materials. Based on this flux data, several researchers have attempted to predict the inhalation dose attributable to radon emitted from walls and ceilings made up of these materials. However, an important aspect not considered in this methodology is the enhancement of the radon flux from the wall or the ceiling constructed using the same building material. This enhancement occurs mainly because of the change in the radon diffusion process from the former to the latter configuration. To predict the true radon flux from the wall based on the flux data of building material samples, we now propose a semi-empirical model involving radon diffusion length and the physical dimensions of the samples as well as wall thickness as other input parameters. This model has been established by statistically fitting the ratio of the solution to radon diffusion equations for the cases of three-dimensional cuboidal shaped building materials (such as brick, concrete block) and one dimensional wall system to a simple mathematical function. The model predictions have been validated against the measurements made at a new construction site. This model provides an alternative tool (substitute to conventional 1-D model) to estimate radon flux from a wall without relying on 226 Ra content, radon emanation factor and bulk density of the samples. Moreover, it may be very useful in the context of developing building codes for radon regulation in new buildings. - Research highlights: → A model is proposed to predict radon flux from wall using flux of building material. → It is established based on the diffusion mechanism in building material and wall. → Study showed a large difference in radon flux from building material and wall. → Model has been validated against the measurements made at

  2. 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.

  3. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    DEFF Research Database (Denmark)

    Rong, Li; Nielsen, Peter Vilhelm; Bjerg, Bjarne Schmidt

    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......, simulating domain etc. This information is particularly important for the readers to evaluate the quality of the CFD simulation results....

  5. Building Predictive Human Performance Models of Skill Acquisition in a Data Entry Task

    National Research Council Canada - National Science Library

    Fu, Wai-Tat; Gonzalez, Cleotilde; Healy, Alice F; Kole, James A; Bourne, Jr., Lyle E

    2006-01-01

    .... Since data entry is a central component in most human-machine interaction, a predictive model of performance will provide useful information that informs interface design and effectiveness of training...

  6. Potential Energy Flexibility for a Hot-Water Based Heating System in Smart Buildings Via Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Ahmed, Awadelrahman M. A.; Zong, Yi; Mihet-Popa, Lucian

    2017-01-01

    This paper studies the potential of shifting the heating energy consumption in a residential building to low price periods based on varying electricity price signals suing Economic Model Predictive Control strategy. The investigated heating system consists of a heat pump incorporated with a hot...... water tank as active thermal energy storage, where two optimization problems are integrated together to optimize both the heat pump electricity consumption and the building heating consumption. A sensitivity analysis for the system flexibility is examined. The results revealed that the proposed...

  7. Building Customer Churn Prediction Models in Fitness Industry with Machine Learning Methods

    OpenAIRE

    Shan, Min

    2017-01-01

    With the rapid growth of digital systems, churn management has become a major focus within customer relationship management in many industries. Ample research has been conducted for churn prediction in different industries with various machine learning methods. This thesis aims to combine feature selection and supervised machine learning methods for defining models of churn prediction and apply them on fitness industry. Forward selection is chosen as feature selection methods. Support Vector ...

  8. Model building and new particles

    International Nuclear Information System (INIS)

    Frampton, P.H.

    1992-01-01

    After an outline of the Standard Model, indications of new physics beyond it are discussed. The nature of model building is illustrated by three examples which predict, respectively, new particles called the axigluon, sarks and the aspon. (author). 11 refs

  9. 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...

  10. Development of a prediction model for the cost saving potentials in implementing the building energy efficiency rating certification

    International Nuclear Information System (INIS)

    Jeong, Jaewook; Hong, Taehoon; Ji, Changyoon; Kim, Jimin; Lee, Minhyun; Jeong, Kwangbok; Koo, Choongwan

    2017-01-01

    Highlights: • This study evaluates the building energy efficiency rating (BEER) certification. • Prediction model was developed for cost saving potentials by the BEER certification. • Prediction model was developed using LCC analysis, ROV, and Monte Carlo simulation. • Cost saving potential was predicted to be 2.78–3.77% of the construction cost. • Cost saving potential can be used for estimating the investment value of BEER. - Abstract: Building energy efficiency rating (BEER) certification is an energy performance certificates (EPCs) in South Korea. It is critical to examine the cost saving potentials of the BEER-certification in advance. This study aimed to develop a prediction model for the cost saving potentials in implementing the BEER-certification, in which the cost saving potentials included the energy cost savings of the BEER-certification and the relevant CO_2 emissions reduction as well as the additional construction cost for the BEER-certification. The prediction model was developed by using data mining, life cycle cost analysis, real option valuation, and Monte Carlo simulation. The database were established with 437 multi-family housing complexes (MFHCs), including 116 BEER-certified MFHCs and 321 non-certified MFHCs. The case study was conducted to validate the developed prediction model using 321 non-certified MFHCs, which considered 20-year life cycle. As a result, compared to the additional construction cost, the average cost saving potentials of the 1st-BEER-certified MFHCs in Groups 1, 2, and 3 were predicted to be 3.77%, 2.78%, and 2.87%, respectively. The cost saving potentials can be used as a guideline for the additional construction cost of the BEER-certification in the early design phase.

  11. 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...... settings to meet an optimization objective such as minimum cost and minimum reference temperature error. It demonstrates that this MPC strategy can realize load shifting, and maximize the PV self-consumption in the residential sector. With this demand side control study, it is expected that MPC strategy...

  12. Building a 3D geomechanical model of a gas field for geohazard prediction

    NARCIS (Netherlands)

    Orlic, B.; Eijs, R. van; Zijl, W.; Wees, J.D. van

    2002-01-01

    Land subsidence, triggered earthquakes and wellbore instabilities are some examples of geohazards caused by or related to the production of subsurface natural resources and storage of energy residues in the deep subsurface. The main objective of geomechanical modelling is to effectively predict

  13. Predicting 30-Day Readmissions in an Asian Population: Building a Predictive Model by Incorporating Markers of Hospitalization Severity.

    Directory of Open Access Journals (Sweden)

    Lian Leng Low

    Full Text Available To reduce readmissions, it may be cost-effective to consider risk stratification, with targeting intervention programs to patients at high risk of readmissions. In this study, we aimed to derive and validate a prediction model including several novel markers of hospitalization severity, and compare the model with the LACE index (Length of stay, Acuity of admission, Charlson comorbidity index, Emergency department visits in past 6 months, an established risk stratification tool.This was a retrospective cohort study of all patients ≥ 21 years of age, who were admitted to a tertiary hospital in Singapore from January 1, 2013 through May 31, 2015. Data were extracted from the hospital's electronic health records. The outcome was defined as unplanned readmissions within 30 days of discharge from the index hospitalization. Candidate predictive variables were broadly grouped into five categories: Patient demographics, social determinants of health, past healthcare utilization, medical comorbidities, and markers of hospitalization severity. Multivariable logistic regression was used to predict the outcome, and receiver operating characteristic analysis was performed to compare our model with the LACE index.74,102 cases were enrolled for analysis. Of these, 11,492 patient cases (15.5% were readmitted within 30 days of discharge. A total of fifteen predictive variables were strongly associated with the risk of 30-day readmissions, including number of emergency department visits in the past 6 months, Charlson Comorbidity Index, markers of hospitalization severity such as 'requiring inpatient dialysis during index admission, and 'treatment with intravenous furosemide 40 milligrams or more' during index admission. Our predictive model outperformed the LACE index by achieving larger area under the curve values: 0.78 (95% confidence interval [CI]: 0.77-0.79 versus 0.70 (95% CI: 0.69-0.71.Several factors are important for the risk of 30-day readmissions

  14. Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

    Science.gov (United States)

    Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

    2017-10-01

    To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-valuemodel is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP

  15. 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)

  16. 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. © The

  17. 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...

  18. 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.

  19. Building Models to Predict Hint-or-Attempt Actions of Students

    Science.gov (United States)

    Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil

    2015-01-01

    A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…

  20. 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

  1. 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

    2009-10-01

    Full Text Available 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.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.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 found to result in maximally predictive models are

  2. Prediction models in building acoustics : introduction to the special session at Forum Acusticum 1999 in Berlin

    NARCIS (Netherlands)

    Gerretsen, E.; Nightingale, T.R.T.

    1999-01-01

    There is strong interest in being able to predict the apparent sound insulation in completed constructions so that the suitability of the construction details and materials may be assessed at the design stage. Methods do exist that provide estimates of the apparent sound insulation. An example of

  3. A Novel Distributed Economic Model Predictive Control Approach for Building Air-Conditioning Systems in Microgrids

    Directory of Open Access Journals (Sweden)

    Xinan Zhang

    2018-04-01

    Full Text Available With the penetration of grid-connected renewable energy generation, microgrids are facing stability and power quality problems caused by renewable intermittency. To alleviate such problems, demand side management (DSM of responsive loads, such as building air-conditioning system (BACS, has been proposed and studied. In recent years, numerous control approaches have been published for proper management of single BACS. The majority of these approaches focus on either the control of BACS for attenuating power fluctuations in the grid or the operating cost minimization on behalf of the residents. These two control objectives are paramount for BACS control in microgrids and can be conflicting. As such, they should be considered together in control design. As individual buildings may have different owners/residents, it is natural to control different BACSs in an autonomous and self-interested manner to minimize the operational costs for the owners/residents. Unfortunately, such “selfish” operation can result in abrupt and large power fluctuations at the point of common coupling (PCC of the microgrid due to lack of coordination. Consequently, the original objective of mitigating power fluctuations generated by renewable intermittency cannot be achieved. To minimize the operating costs of individual BACSs and simultaneously ensure desirable overall power flow at PCC, this paper proposes a novel distributed control framework based on the dissipativity theory. The proposed method achieves the objective of renewable intermittency mitigation through proper coordination of distributed BACS controllers and is scalable and computationally efficient. Simulation studies are carried out to illustrate the efficacy of the proposed control framework.

  4. Contribution of mesoscopic modeling for flows prediction in cracked concrete buildings in condition of severe accident

    International Nuclear Information System (INIS)

    Nguyen, T.D.

    2010-01-01

    This Ph.D. thesis aims at characterising and modeling the mechanical behavior of concrete at the mesoscopic scale. The more general scope of this study is the development of mesoscopic model for concrete; this model is to represent the concrete as a heterogeneous medium, taking into account the difference between aggregate and cement paste respecting the grading curve, the model parameters describe the mechanical and thermal behavior of cement paste and aggregates. We are interested in understanding the concrete behaviour, considered one structure. A program of random granular structure valid in 2D and 3D has been developed. This program is interfaced with the Finite Element code CAST3M in order to compute the numerical simulations. A method for numerical representation of the inclusions of concrete was also developed and validated by projection of the geometry on the shape functions, thus eliminating the problems of meshing that made the representation of all aggregates skeleton almost impossible, particularly in 3D. Firstly, the model is studied in two-dimensional and three-dimensional in order to optimize the geometrical model of the inner structure of concrete in terms of the meshing strategy and the smallest size of the aggregate to be taken into account. The results of the 2D and 3D model are analyzed and compared in the case of uniaxial tension and uniaxial compression. The model used is an isotropic unilateral damage model from Fichant [Fichant et al., 1999]. The model allows to simulate both the macroscopic behavior but also with the local studies of the distribution of crack and crack opening. The model shows interesting results on the transition from diffuse to localized damage and is able to reproduce dilatancy in compression. Finally, the mesoscopic model is applied to three simulations: the calculation of the permeability of cracked concrete; the simulation of the hydration of concrete at early age and finally the scale effect illustrated by bending

  5. 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...

  6. SUSY GUT Model Building

    International Nuclear Information System (INIS)

    Raby, Stuart

    2008-01-01

    In this talk I discuss the evolution of SUSY GUT model building as I see it. Starting with 4 dimensional model building, I then consider orbifold GUTs in 5 dimensions and finally orbifold GUTs embedded into the E 8 xE 8 heterotic string.

  7. An Empirical Model Building Criterion Based on Prediction with Applications in Parametric Cost Estimation.

    Science.gov (United States)

    1980-08-01

    varia- ble is denoted by 7, the total sum of squares of deviations from that mean is defined by n - SSTO - (-Y) (2.6) iul and the regression sum of...squares by SSR - SSTO - SSE (2.7) II 14 A selection criterion is a rule according to which a certain model out of the 2p possible models is labeled "best...dis- cussed next. 1. The R2 Criterion The coefficient of determination is defined by R2 . 1 - SSE/ SSTO . (2.8) It is clear that R is the proportion of

  8. 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

  9. 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.)

  10. Mould growth prediction by computational simulation on historic buildings

    OpenAIRE

    Krus, M.; Kilian, R.; Sedlbauer, K.

    2007-01-01

    Historical buildings are often renovated with a high expenditure of time and money without investigating and considering the causes of the damages. In many cases historic buildings can only be maintained by changing their usage. This change of use may influence the interior climate enormously. To assess the effect on the risk of mould growth on building parts or historic monuments a predictive model has been developed recently, describing the hygrothermal behaviour of the spore. It allows for...

  11. Building and validation of a prognostic model for predicting extracorporeal circuit clotting in patients with continuous renal replacement therapy.

    Science.gov (United States)

    Fu, Xia; Liang, Xinling; Song, Li; Huang, Huigen; Wang, Jing; Chen, Yuanhan; Zhang, Li; Quan, Zilin; Shi, Wei

    2014-04-01

    To develop a predictive model for circuit clotting in patients with continuous renal replacement therapy (CRRT). A total of 425 cases were selected. 302 cases were used to develop a predictive model of extracorporeal circuit life span during CRRT without citrate anticoagulation in 24 h, and 123 cases were used to validate the model. The prediction formula was developed using multivariate Cox proportional-hazards regression analysis, from which a risk score was assigned. The mean survival time of the circuit was 15.0 ± 1.3 h, and the rate of circuit clotting was 66.6 % during 24 h of CRRT. Five significant variables were assigned a predicting score according to the regression coefficient: insufficient blood flow, no anticoagulation, hematocrit ≥0.37, lactic acid of arterial blood gas analysis ≤3 mmol/L and APTT R (2) = 0.232; P = 0.301). A risk score that includes the five above-mentioned variables can be used to predict the likelihood of extracorporeal circuit clotting in patients undergoing CRRT.

  12. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

  13. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  14. Solar energy in buildings solved by building information modeling

    Science.gov (United States)

    Chudikova, B.; Faltejsek, M.

    2018-03-01

    Building lead us to use renewable energy sources for all types of buildings. The use of solar energy is the alternatives that can be applied in a good ratio of space, price, and resultant benefits. Building Information Modelling is a modern and effective way of dealing with buildings with regard to all aspects of the life cycle. The basis is careful planning and simulation in the pre-investment phase, where it is possible to determine the effective result and influence the lifetime of the building and the cost of its operation. By simulating, analysing and insert a building model into its future environment where climate conditions and surrounding buildings play a role, it is possible to predict the usability of the solar energy and establish an ideal model. Solar systems also very affect the internal layout of buildings. Pre-investment phase analysis, with a view to future aspects, will ensure that the resulting building will be both low-energy and environmentally friendly.

  15. 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...

  16. 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.

  17. 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...

  18. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  19. Preliminary Empirical Models for Predicting Shrinkage, Part Geometry and Metallurgical Aspects of Ti-6Al-4V Shaped Metal Deposition Builds

    Science.gov (United States)

    Escobar-Palafox, Gustavo; Gault, Rosemary; Ridgway, Keith

    2011-12-01

    Shaped Metal Deposition (SMD) is an additive manufacturing process which creates parts layer by layer by weld depositions. In this work, empirical models that predict part geometry (wall thickness and outer diameter) and some metallurgical aspects (i.e. surface texture, portion of finer Widmanstätten microstructure) for the SMD process were developed. The models are based on an orthogonal fractional factorial design of experiments with four factors at two levels. The factors considered were energy level (a relationship between heat source power and the rate of raw material input.), step size, programmed diameter and travel speed. The models were validated using previous builds; the prediction error for part geometry was under 11%. Several relationships between the factors and responses were identified. Current had a significant effect on wall thickness; thickness increases with increasing current. Programmed diameter had a significant effect on percentage of shrinkage; this decreased with increasing component size. Surface finish decreased with decreasing step size and current.

  20. Preliminary Empirical Models for Predicting Shrinkage, Part Geometry and Metallurgical Aspects of Ti-6Al-4V Shaped Metal Deposition Builds

    International Nuclear Information System (INIS)

    Escobar-Palafox, Gustavo; Gault, Rosemary; Ridgway, Keith

    2011-01-01

    Shaped Metal Deposition (SMD) is an additive manufacturing process which creates parts layer by layer by weld depositions. In this work, empirical models that predict part geometry (wall thickness and outer diameter) and some metallurgical aspects (i.e. surface texture, portion of finer Widmanstätten microstructure) for the SMD process were developed. The models are based on an orthogonal fractional factorial design of experiments with four factors at two levels. The factors considered were energy level (a relationship between heat source power and the rate of raw material input.), step size, programmed diameter and travel speed. The models were validated using previous builds; the prediction error for part geometry was under 11%. Several relationships between the factors and responses were identified. Current had a significant effect on wall thickness; thickness increases with increasing current. Programmed diameter had a significant effect on percentage of shrinkage; this decreased with increasing component size. Surface finish decreased with decreasing step size and current.

  1. Open string model building

    International Nuclear Information System (INIS)

    Ishibashi, Nobuyuki; Onogi, Tetsuya

    1989-01-01

    Consistency conditions of open string theories, which can be a powerful tool in open string model building, are proposed. By making use of these conditions and assuming a simple prescription for the Chan-Paton factors, open string theories in several backgrounds are studied. We show that 1. there exist a large number of consistent bosonic open string theories on Z 2 orbifolds, 2. SO(32) type I superstring is the unique consistent model among fermionic string theories on the ten-dimensional flat Minkowski space, and 3. with our prescription for the Chan-Paton factors, there exist no consistent open superstring theories on (six-dimensional Minkowski space-time) x (Z 2 orbifold). (orig.)

  2. Prediction of failure modes for concrete nuclear-containment buildings

    International Nuclear Information System (INIS)

    Butler, T.A.

    1982-01-01

    The failure modes and associated failure pressures for two common generic types of PWR containments are predicted. One building type is a lightly reinforced, posttensioned structure represented by the Zion nuclear reactor containment. The other is the normally reinforced Indian Point containment. Two-dimensional models of the buildings developed using the finite element method are used to predict the failure modes and failure pressures. Predicted failure modes for both containments involve loss of structural integrity at the intersection of the cylindrical sidewall with the base slab

  3. Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes.

    Science.gov (United States)

    Zhao, Lue Ping; Carlsson, Annelie; Larsson, Helena Elding; Forsander, Gun; Ivarsson, Sten A; Kockum, Ingrid; Ludvigsson, Johnny; Marcus, Claude; Persson, Martina; Samuelsson, Ulf; Örtqvist, Eva; Pyo, Chul-Woo; Bolouri, Hamid; Zhao, Michael; Nelson, Wyatt C; Geraghty, Daniel E; Lernmark, Åke

    2017-11-01

    It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies. Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D. In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10 -92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime. Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations. Copyright © 2017 John Wiley & Sons, Ltd.

  4. 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....... Finally, it is discussed how to adjust the model for practical purposes, and a scheme for actual service life for selected building components important for analysis of sustainability is linked. The schemes are now being implemented as basis for sustainability certification of new buildings in Denmark....

  5. Analysis of Various Inflow Turbulence Generation Methods in Large Eddy Simulation Approach for Prediction of Pollutant Dispersion around Model Buildings

    Directory of Open Access Journals (Sweden)

    F. Bazdidi Tehrani

    2017-02-01

    of windward wall of the second building. Among the various inflow turbulence generation methods, the vortex method is the most precise method and no-inlet perturbation method is the least precise method.

  6. Flavored model building

    International Nuclear Information System (INIS)

    Hagedorn, C.

    2008-01-01

    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 4 , the dihedral group D 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, √((m d )/(m s ))= vertical stroke V us vertical stroke and √((m d )/(m s ))= vertical stroke (V td )/(V 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 n and D' 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 θ C , i.e. vertical stroke V us(cd) vertical stroke cos((3π)/(7)), as well as maximal atmospheric mixing, θ 23 =(π)/(4), and vanishing θ 13 in the lepton sector. (orig.)

  7. 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.)

  8. 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.

  9. A model predictive framework of Ground Source Heat Pump coupled with Aquifer Thermal Energy Storage System in heating and cooling equipment of a building

    NARCIS (Netherlands)

    Rostampour Samarin, V.; Bloemendal, J.M.; Keviczky, T.

    2017-01-01

    This paper presents a complete model of a building heating and cooling equipment and a ground source heat pump (GSHP) coupled with an aquifer thermal energy storage (ATES) system. This model contains detailed
    mathematical representations of building thermal dynamics, ATES system dynamics, heat

  10. 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...

  11. Humidity build-up in electronic enclosures exposed to different geographical locations by RC modelling and reliability prediction

    DEFF Research Database (Denmark)

    Conseil-Gudla, H.; Staliulionis, Z.; Mohanty, S.

    2018-01-01

    according to this steady state (25 °C and 60% RH) have been calculated for the different climates, and the protection offered by the enclosures has been estimated under different casing materials and resistor-capacitor (RC) simulation. This method offers a way to predict the average value of failure rate...

  12. RCrane: semi-automated RNA model building.

    Science.gov (United States)

    Keating, Kevin S; Pyle, Anna Marie

    2012-08-01

    RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems.

  13. RCrane: semi-automated RNA model building

    International Nuclear Information System (INIS)

    Keating, Kevin S.; Pyle, Anna Marie

    2012-01-01

    RCrane is a new tool for the partially automated building of RNA crystallographic models into electron-density maps of low or intermediate resolution. This tool helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems

  14. Darwinian Model Building

    NARCIS (Netherlands)

    Kester, Do; Bontekoe, Romke; MohammadDjafari, A; Bercher, JF; Bessiere, P

    2010-01-01

    We present a way to generate heuristic mathematical models based on the Darwinian principles of variation and selection in a pool of individuals over many generations. Each individual has a genotype (the hereditary properties) and a phenotype (the expression of these properties in the environment).

  15. Darwinian Model Building

    International Nuclear Information System (INIS)

    Kester, Do; Bontekoe, Romke

    2011-01-01

    We present a way to generate heuristic mathematical models based on the Darwinian principles of variation and selection in a pool of individuals over many generations. Each individual has a genotype (the hereditary properties) and a phenotype (the expression of these properties in the environment). Variation is achieved by cross-over and mutation operations on the genotype which consists in the present case of a single chromosome. The genotypes 'live' in the environment of the data. Nested Sampling is used to optimize the free parameters of the models given the data, thus giving rise to the phenotypes. Selection is based on the phenotypes.The evidences which naturally follow from the Nested Sampling Algorithm are used in a second level of Nested Sampling to find increasingly better models.The data in this paper originate from the Leiden Cytology and Pathology Laboratory (LCPL), which screens pap smears for cervical cancer. We have data for 1750 women who on average underwent 5 tests each. The data on individual women are treated as a small time series. We will try to estimate the next value of the prime cancer indicator from previous tests of the same woman.

  16. 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

  17. Prediction of residential building energy consumption: A neural network approach

    International Nuclear Information System (INIS)

    Biswas, M.A. Rafe; Robinson, Melvin D.; Fumo, Nelson

    2016-01-01

    Some of the challenges to predict energy utilization has gained recognition in the residential sector due to the significant energy consumption in recent decades. However, the modeling of residential building energy consumption is still underdeveloped for optimal and robust solutions while this research area has become of greater relevance with significant advances in computation and simulation. Such advances include the advent of artificial intelligence research in statistical model development. Artificial neural network has emerged as a key method to address the issue of nonlinearity of building energy data and the robust calculation of large and dynamic data. The development and validation of such models on one of the TxAIRE Research houses has been demonstrated in this paper. The TxAIRE houses have been designed to serve as realistic test facilities for demonstrating new technologies. The input variables used from the house data include number of days, outdoor temperature and solar radiation while the output variables are house and heat pump energy consumption. The models based on Levenberg-Marquardt and OWO-Newton algorithms had promising results of coefficients of determination within 0.87–0.91, which is comparable to prior literature. Further work will be explored to develop a robust model for residential building application. - Highlights: • A TxAIRE research house energy consumption data was collected in model development. • Neural network models developed using Levenberg–Marquardt or OWO-Newton algorithms. • Model results match well with data and statistically consistent with literature.

  18. Thermal Models for Intelligent Heating of Buildings

    DEFF Research Database (Denmark)

    Thavlov, Anders; Bindner, Henrik W.

    2012-01-01

    the comfort of residents, proper prediction models for indoor temperature have to be developed. This paper presents a model for prediction of indoor temperature and power consumption from electrical space heating in an office building, using stochastic differential equations. The heat dynamic model is build......The Danish government has set the ambitious goal that the share of the total Danish electricity consumption, covered by wind energy, should be increased to 50% by year 2020. This asks for radical changes in how we utilize and transmit electricity in the future power grid. To fully utilize the high...... share of renewable power generation, which is in general intermittent and non-controllable, the consumption side has to be much more flexible than today. To achieve such flexibility, methods for moving power consumption in time, within the hourly timescale, have to be developed. One approach currently...

  19. Models for map building and navigation

    International Nuclear Information System (INIS)

    Penna, M.A.; Jian Wu

    1993-01-01

    In this paper the authors present several models for solving map building and navigation problems. These models are motivated by biological processes, and presented in the context of artificial neural networks. Since the nodes, weights, and threshold functions of the models all have physical meanings, they can easily predict network topologies and avoid traditional trial-and-error training. On one hand, this makes their models useful in constructing solutions to engineering problems (problems such as those that occur in robotics, for example). On the other hand, this might also contribute to the ability of their models to explain some biological processes, few of which are completely understood at this time

  20. Modeling the building blocks of biodiversity.

    Directory of Open Access Journals (Sweden)

    Lucas N Joppa

    Full Text Available BACKGROUND: Networks of single interaction types, such as plant-pollinator mutualisms, are biodiversity's "building blocks". Yet, the structure of mutualistic and antagonistic networks differs, leaving no unified modeling framework across biodiversity's component pieces. METHODS/PRINCIPAL FINDINGS: We use a one-dimensional "niche model" to predict antagonistic and mutualistic species interactions, finding that accuracy decreases with the size of the network. We show that properties of the modeled network structure closely approximate empirical properties even where individual interactions are poorly predicted. Further, some aspects of the structure of the niche space were consistently different between network classes. CONCLUSIONS/SIGNIFICANCE: These novel results reveal fundamental differences between the ability to predict ecologically important features of the overall structure of a network and the ability to predict pair-wise species interactions.

  1. Alternatives to quintessence model building

    International Nuclear Information System (INIS)

    Avelino, P.P.; Beca, L.M.G.; Pinto, P.; Carvalho, J.P.M. de; Martins, C.J.A.P.

    2003-01-01

    We discuss the issue of toy model building for the dark energy component of the universe. Specifically, we consider two generic toy models recently proposed as alternatives to quintessence models, respectively known as Cardassian expansion and the Chaplygin gas. We show that the former is entirely equivalent to a class of quintessence models. We determine the observational constraints on the latter, coming from recent supernovae results and from the shape of the matter power spectrum. As expected, these restrict the model to a behavior that closely matches that of a standard cosmological constant Λ

  2. 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...

  3. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  4. A study of the importance of occupancy to building cooling load in prediction by intelligent approach

    International Nuclear Information System (INIS)

    Kwok, Simon S.K.; Lee, Eric W.M.

    2011-01-01

    Research highlights: → The building occupancy affecting the cooling load prediction is studied. → PENN model is adopted in this study for predicting the building cooling load. → Statistical approach is adopted to result a less prejudice prediction performance. → Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of simulation results

  5. A study of the importance of occupancy to building cooling load in prediction by intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Kwok, Simon S.K. [Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Lee, Eric W.M., E-mail: ericlee@cityu.edu.h [Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong)

    2011-07-15

    Research highlights: {yields} The building occupancy affecting the cooling load prediction is studied. {yields} PENN model is adopted in this study for predicting the building cooling load. {yields} Statistical approach is adopted to result a less prejudice prediction performance. {yields} Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of

  6. Analysis of a Residential Building Energy Consumption Demand Model

    Directory of Open Access Journals (Sweden)

    Meng Liu

    2011-03-01

    Full Text Available In order to estimate the energy consumption demand of residential buildings, this paper first discusses the status and shortcomings of current domestic energy consumption models. Then it proposes and develops a residential building energy consumption demand model based on a back propagation (BP neural network model. After that, taking residential buildings in Chongqing (P.R. China as an example, 16 energy consumption indicators are introduced as characteristics of the residential buildings in Chongqing. The index system of the BP neutral network prediction model is established and the multi-factorial BP neural network prediction model of Chongqing residential building energy consumption is developed using the Cshap language, based on the SQL server 2005 platform. The results obtained by applying the model in Chongqing are in good agreement with actual ones. In addition, the model provides corresponding approximate data by taking into account the potential energy structure adjustments and relevant energy policy regulations.

  7. Predictive Models and Computational Toxicology (II IBAMTOX)

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  8. Quantification of Uncertainty in Predicting Building Energy Consumption

    DEFF Research Database (Denmark)

    Brohus, Henrik; Frier, Christian; Heiselberg, Per

    2012-01-01

    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...... 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...

  9. 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 heating...... of the building in time. This way the thermal mass of the building can be used to absorb energy from renewable energy source when available and postpone heating in periods with lack of renewable energy generation. The model is used in a model predictive controller to ensure the residential comfort over a given...

  10. 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.

  11. Model calibration for building energy efficiency simulation

    International Nuclear Information System (INIS)

    Mustafaraj, Giorgio; Marini, Dashamir; Costa, Andrea; Keane, Marcus

    2014-01-01

    Highlights: • Developing a 3D model relating to building architecture, occupancy and HVAC operation. • Two calibration stages developed, final model providing accurate results. • Using an onsite weather station for generating the weather data file in EnergyPlus. • Predicting thermal behaviour of underfloor heating, heat pump and natural ventilation. • Monthly energy saving opportunities related to heat pump of 20–27% was identified. - Abstract: This research work deals with an Environmental Research Institute (ERI) building where an underfloor heating system and natural ventilation are the main systems used to maintain comfort condition throughout 80% of the building areas. Firstly, this work involved developing a 3D model relating to building architecture, occupancy and HVAC operation. Secondly, the calibration methodology, which consists of two levels, was then applied in order to insure accuracy and reduce the likelihood of errors. To further improve the accuracy of calibration a historical weather data file related to year 2011, was created from the on-site local weather station of ERI building. After applying the second level of calibration process, the values of Mean bias Error (MBE) and Cumulative Variation of Root Mean Squared Error (CV(RMSE)) on hourly based analysis for heat pump electricity consumption varied within the following ranges: (MBE) hourly from −5.6% to 7.5% and CV(RMSE) hourly from 7.3% to 25.1%. Finally, the building was simulated with EnergyPlus to identify further possibilities of energy savings supplied by a water to water heat pump to underfloor heating system. It found that electricity consumption savings from the heat pump can vary between 20% and 27% on monthly bases

  12. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  13. Integration of design applications with building models

    DEFF Research Database (Denmark)

    Eastman, C. M.; Jeng, T. S.; Chowdbury, R.

    1997-01-01

    This paper reviews various issues in the integration of applications with a building model... (Truncated.)......This paper reviews various issues in the integration of applications with a building model... (Truncated.)...

  14. 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.

  15. 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.

  16. Energy modelling and capacity building

    International Nuclear Information System (INIS)

    2005-01-01

    The Planning and Economic Studies Section of the IAEA's Department of Nuclear Energy is focusing on building analytical capacity in MS for energy-environmental-economic assessments and for the elaboration of sustainable energy strategies. It offers a variety of analytical models specifically designed for use in developing countries for (i) evaluating alternative energy strategies; (ii) assessing environmental, economic and financial impacts of energy options; (iii) assessing infrastructure needs; (iv) evaluating regional development possibilities and energy trade; (v) assessing the role of nuclear power in addressing priority issues (climate change, energy security, etc.). These models can be used for analysing energy or electricity systems, and to assess possible implications of different energy, environmental or financial policies that affect the energy sector and energy systems. The models vary in complexity and data requirements, and so can be adapted to the available data, statistics and analytical needs of different countries. These models are constantly updated to reflect changes in the real world and in the concerns that drive energy system choices. They can provide thoughtfully informed choices for policy makers over a broader range of circumstances and interests. For example, they can readily reflect the workings of competitive energy and electricity markets, and cover such topics as external costs. The IAEA further offers training in the use of these models and -just as important- in the interpretation and critical evaluation of results. Training of national teams to develop national competence over the full spectrum of models, is a high priority. The IAEA maintains a broad spectrum of databanks relevant to energy, economic and environmental analysis in MS, and make these data available to analysts in MS for use in their own analytical work. The Reference Technology Data Base (RTDB) and the Reference Data Series (RDS-1) are the major vehicles by which we

  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. 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

  19. Systematic model building with flavor symmetries

    International Nuclear Information System (INIS)

    Plentinger, Florian

    2009-01-01

    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 μ → eγ, τ → μγ, and τ → eγ 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 to search for phenomenological

  20. 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

  1. 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.

  2. 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.

  3. Damage Level Prediction of Reinforced Concrete Building Based on Earthquake Time History Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Suryanita Reni

    2017-01-01

    Full Text Available The strong motion earthquake could cause the building damage in case of the building not considered in the earthquake design of the building. The study aims to predict the damage-level of building due to earthquake using Artificial Neural Networks method. The building model is a reinforced concrete building with ten floors and height between floors is 3.6 m. The model building received a load of the earthquake based on nine earthquake time history records. Each time history scaled to 0,5g, 0,75g, and 1,0g. The Artificial Neural Networks are designed in 4 architectural models using the MATLAB program. Model 1 used the displacement, velocity, and acceleration as input and Model 2 used the displacement only as the input. Model 3 used the velocity as input, and Model 4 used the acceleration just as input. The output of the Neural Networks is the damage level of the building with the category of Safe (1, Immediate Occupancy (2, Life Safety (3 or in a condition of Collapse Prevention (4. According to the results, Neural Network models have the prediction rate of the damage level between 85%-95%. Therefore, one of the solutions for analyzing the structural responses and the damage level promptly and efficiently when the earthquake occurred is by using Artificial Neural Network

  4. 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.

  5. Predictive control techniques for energy and indoor environmental quality management in buildings

    Energy Technology Data Exchange (ETDEWEB)

    Kolokotsa, D. [Technological Educational Institute of Crete, Department of Natural Resources and Environment, 3, Romanou str., 73133, Hania, Crete (Greece); Pouliezos, A. [Technical University of Crete, Department of Production Engineering and Management, University Campus, Kounoupidiana, 73100 Hania (Greece); Stavrakakis, G.; Lazos, C. [Technical University of Crete, Department of Electronics and Computer Engineering, University Campus, Kounoupidiana, 73100 Hania (Greece)

    2009-09-15

    The aim of the present paper is to present a model-based predictive controller, combined with a Building Energy Management System (BEMS). The overall system predicts the indoor environmental conditions of a specific building and selects the most appropriate actions so as to reach the set points and contribute to the indoor environmental quality by minimizing energy costs. The controller is tested using a BEMS installation in Hania, Crete, Greece. (author)

  6. Predicting energy performance of a net-zero energy building: A statistical approach

    International Nuclear Information System (INIS)

    Kneifel, Joshua; Webb, David

    2016-01-01

    Highlights: • A regression model is applied to actual energy data from a net-zero energy building. • The model is validated through a rigorous statistical analysis. • Comparisons are made between model predictions and those of a physics-based model. • The model is a viable baseline for evaluating future models from the energy data. - Abstract: 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

  7. 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.

  8. 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.

  9. Machine Learning Approaches Toward Building Predictive Models for Small Molecule Modulators of miRNA and Its Utility in Virtual Screening of Molecular Databases.

    Science.gov (United States)

    Periwal, Vinita; Scaria, Vinod

    2017-01-01

    The ubiquitous role of microRNAs (miRNAs) in a number of pathological processes has suggested that they could act as potential drug targets. RNA-binding small molecules offer an attractive means for modulating miRNA function. The availability of bioassay data sets for a variety of biological assays and molecules in public domain provides a new opportunity toward utilizing them to create models and further utilize them for in silico virtual screening approaches to prioritize or assign potential functions for small molecules. Here, we describe a computational strategy based on machine learning for creation of predictive models from high-throughput biological screens for virtual screening of small molecules with the potential to inhibit microRNAs. Such models could be potentially used for computational prioritization of small molecules before performing high-throughput biological assay.

  10. 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.

  11. 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

    . The retrieved heat excess can be stored in the water tank. For this purpose the charging and the discharging water loops has been designed. We present the non-linear model of the above described system and a non-linear model predictive supervisory controller that according to the received price signal......, occupancy information and ambient temperature minimizes the operation cost of the whole system and distributes set points to local controllers of supermarkets subsystems. We find that when reliable information about the high price period is available, it is profitable to use the refrigeration system...... to generate heat during the low price period, store it and use it to substitute the conventional heater during the high price period....

  12. 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...

  13. The Use of Modelling for Theory Building in Qualitative Analysis

    Science.gov (United States)

    Briggs, Ann R. J.

    2007-01-01

    The purpose of this article is to exemplify and enhance the place of modelling as a qualitative process in educational research. Modelling is widely used in quantitative research as a tool for analysis, theory building and prediction. Statistical data lend themselves to graphical representation of values, interrelationships and operational…

  14. 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.

  15. Modeling of shear wall buildings

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, A K [North Carolina State Univ., Raleigh (USA). Dept. of Civil Engineering

    1984-05-01

    Many nuclear power plant buildings, for example, the auxiliary building, have reinforced concrete shear walls as the primary lateral load resisting system. Typically, these walls have low height to length ratio, often less than unity. Such walls exhibit marked shear lag phenomenon which would affect their bending stiffness and the overall stress distribution in the building. The deformation and the stress distribution in walls have been studied which is applicable to both the short and the tall buildings. The behavior of the wall is divided into two parts: the symmetric flange action and the antisymmetry web action. The latter has two parts: the web shear and the web bending. Appropriate stiffness equations have been derived for all the three actions. These actions can be synthesized to solve any nonlinear cross-section. Two specific problems, that of lateral and torsional loadings of a rectangular box, have been studied. It is found that in short buildings shear lag plays a very important role. Any beam type formulation which either ignores shear lag or includes it in an idealized form is likely to lead to erroneous results. On the other hand a rigidity type approach with some modifications to the standard procedures would yield nearly accurate answers.

  16. A new, accurate predictive model for incident hypertension

    DEFF Research Database (Denmark)

    Völzke, Henry; Fung, Glenn; Ittermann, Till

    2013-01-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.......Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....

  17. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

  18. Effect of length of measurement period on accuracy of predicted annual heating energy consumption of buildings

    International Nuclear Information System (INIS)

    Cho, Sung-Hwan; Kim, Won-Tae; Tae, Choon-Soeb; Zaheeruddin, M.

    2004-01-01

    This study examined the temperature dependent regression models of energy consumption as a function of the length of the measurement period. The methodology applied was to construct linear regression models of daily energy consumption from 1 day to 3 months data sets and compare the annual heating energy consumption predicted by these models with actual annual heating energy consumption. A commercial building in Daejon was selected, and the energy consumption was measured over a heating season. The results from the investigation show that the predicted energy consumption based on 1 day of measurements to build the regression model could lead to errors of 100% or more. The prediction error decreased to 30% when 1 week of data was used to build the regression model. Likewise, the regression model based on 3 months of measured data predicted the annual energy consumption within 6% of the measured energy consumption. These analyses show that the length of the measurement period has a significant impact on the accuracy of the predicted annual energy consumption of buildings

  19. 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....

  20. 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.)

  1. 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.

  2. 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.

  3. 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.

  4. A review of building information modelling

    Science.gov (United States)

    Wang, Wen; Han, Rui

    2018-05-01

    Building Information Modelling (BIM) is widely seen as a catalyst for innovation and productivity. It is becoming standard for new construction and is the most significant technology changing how we design, build, use and manage the building. It is a dominant technological trend in the software industry and although the theoretical groundwork was laid in the previous century, it is a popular topic in academic research. BIM is discussed in this study, which results can provide better and more comprehensive choices for building owners, designers, and developers in future.

  5. 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.

  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. A numerical simulation strategy on occupant evacuation behaviors and casualty prediction in a building during earthquakes

    Science.gov (United States)

    Li, Shuang; Yu, Xiaohui; Zhang, Yanjuan; Zhai, Changhai

    2018-01-01

    Casualty prediction in a building during earthquakes benefits to implement the economic loss estimation in the performance-based earthquake engineering methodology. Although after-earthquake observations reveal that the evacuation has effects on the quantity of occupant casualties during earthquakes, few current studies consider occupant movements in the building in casualty prediction procedures. To bridge this knowledge gap, a numerical simulation method using refined cellular automata model is presented, which can describe various occupant dynamic behaviors and building dimensions. The simulation on the occupant evacuation is verified by a recorded evacuation process from a school classroom in real-life 2013 Ya'an earthquake in China. The occupant casualties in the building under earthquakes are evaluated by coupling the building collapse process simulation by finite element method, the occupant evacuation simulation, and the casualty occurrence criteria with time and space synchronization. A case study of casualty prediction in a building during an earthquake is provided to demonstrate the effect of occupant movements on casualty prediction.

  8. On the prediction of building damage from ground motion

    Energy Technology Data Exchange (ETDEWEB)

    Blume, John A [John A. Blume and Associates Research Division, San Francisco, CA (United States)

    1970-05-15

    In the planning of a nuclear event it is essential to consider the effects of the expected ground motion on all exposed buildings and other structures. There are various steps and procedures in this process which generally increase in scope and refinement as the preparations advance. Initial, rough estimates, based upon rules-of-thumb and preliminary predictions of ground motion and structural response, may be adequate to show general feasibility of the project. Subsequent work is done in both the field and analysis phases, to estimate the total structure exposure, to isolate special hazards, and to make damage cost estimates. Finally, specific analyses are made of special buildings or structures to identify safety problems and to make recommendations for safety measures during the proposed event. Because the ground motion and the structural response both involve many random variables and therefore some uncertainties in prediction, the probabilistic aspects must be considered, both on a broad statistical basis and for specific safety considerations. Decisions must be made as to the acceptability or non-acceptability of the risks and any indicated procedures before and during the event to reduce or to eliminate the risks. The paper discusses various techniques involved in these operations including the Spectral Matrix Method of damage prediction, the Threshold Evaluation Scale for specific building analysis, and the inelastic and probabilistic aspects of the problem. (author)

  9. On the prediction of building damage from ground motion

    International Nuclear Information System (INIS)

    Blume, John A.

    1970-01-01

    In the planning of a nuclear event it is essential to consider the effects of the expected ground motion on all exposed buildings and other structures. There are various steps and procedures in this process which generally increase in scope and refinement as the preparations advance. Initial, rough estimates, based upon rules-of-thumb and preliminary predictions of ground motion and structural response, may be adequate to show general feasibility of the project. Subsequent work is done in both the field and analysis phases, to estimate the total structure exposure, to isolate special hazards, and to make damage cost estimates. Finally, specific analyses are made of special buildings or structures to identify safety problems and to make recommendations for safety measures during the proposed event. Because the ground motion and the structural response both involve many random variables and therefore some uncertainties in prediction, the probabilistic aspects must be considered, both on a broad statistical basis and for specific safety considerations. Decisions must be made as to the acceptability or non-acceptability of the risks and any indicated procedures before and during the event to reduce or to eliminate the risks. The paper discusses various techniques involved in these operations including the Spectral Matrix Method of damage prediction, the Threshold Evaluation Scale for specific building analysis, and the inelastic and probabilistic aspects of the problem. (author)

  10. A Learning Framework for Control-Oriented Modeling of Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.; Vishnu, Abhinav; Vrabie, Draguna L.

    2018-01-18

    Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.

  11. Application of artificial neural network to predict the optimal start time for heating system in building

    International Nuclear Information System (INIS)

    Yang, In-Ho; Yeo, Myoung-Souk; Kim, Kwang-Woo

    2003-01-01

    The artificial neural network (ANN) approach is a generic technique for mapping non-linear relationships between inputs and outputs without knowing the details of these relationships. This paper presents an application of the ANN in a building control system. The objective of this study is to develop an optimized ANN model to determine the optimal start time for a heating system in a building. For this, programs for predicting the room air temperature and the learning of the ANN model based on back propagation learning were developed, and learning data for various building conditions were collected through program simulation for predicting the room air temperature using systems of experimental design. Then, the optimized ANN model was presented through learning of the ANN, and its performance to determine the optimal start time was evaluated

  12. 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....

  13. 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

  14. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    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...

  15. 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…

  16. Modeling of heat and mass transfer in lateritic building envelopes

    International Nuclear Information System (INIS)

    Meukam, Pierre

    2004-10-01

    The aim of the present work is to investigate the behavior of building envelopes made of local lateritic soil bricks subjected to different climatic conditions. The analysis is developed for the prediction of the temperature, relative humidity and water content behavior within the walls. The building envelopes studied in this work consist of lateritic soil bricks with incorporation of natural pozzolan or sawdust in order to obtain small thermal conductivity and low-density materials, and limit the heat transfer between the atmospheric climate and the inside environment. In order to describe coupled heat and moisture transfer in wet porous materials, the coupled equations were solved by the introduction of diffusion coefficients. A numerical model HMtrans, developed for prediction of beat and moisture transfer in multi-layered building components, was used to simulate the temperature, water content and relative humidity profiles within the building envelopes. The results allow the prediction of the duration of the exposed building walls to the local weather conditions. They show that for any of three climatic conditions considered, relative humidity and water content do not exceed 87% and 5% respectively. There is therefore minimum possibility of water condensation in the materials studied. The durability of building envelopes made of lateritic soil bricks with incorporation of natural pozzolan or sawdust is not strongly affected by the climatic conditions in tropical and equatorial regions. (author)

  17. RANDOM FUNCTIONS AND INTERVAL METHOD FOR PREDICTING THE RESIDUAL RESOURCE OF BUILDING STRUCTURES

    Directory of Open Access Journals (Sweden)

    Shmelev Gennadiy Dmitrievich

    2017-11-01

    Full Text Available Subject: possibility of using random functions and interval prediction method for estimating the residual life of building structures in the currently used buildings. Research objectives: coordination of ranges of values to develop predictions and random functions that characterize the processes being predicted. Materials and methods: when performing this research, the method of random functions and the method of interval prediction were used. Results: in the course of this work, the basic properties of random functions, including the properties of families of random functions, are studied. The coordination of time-varying impacts and loads on building structures is considered from the viewpoint of their influence on structures and representation of the structures’ behavior in the form of random functions. Several models of random functions are proposed for predicting individual parameters of structures. For each of the proposed models, its scope of application is defined. The article notes that the considered approach of forecasting has been used many times at various sites. In addition, the available results allowed the authors to develop a methodology for assessing the technical condition and residual life of building structures for the currently used facilities. Conclusions: we studied the possibility of using random functions and processes for the purposes of forecasting the residual service lives of structures in buildings and engineering constructions. We considered the possibility of using an interval forecasting approach to estimate changes in defining parameters of building structures and their technical condition. A comprehensive technique for forecasting the residual life of building structures using the interval approach is proposed.

  18. 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

  19. Building Information Modelling in Denmark and Iceland

    DEFF Research Database (Denmark)

    Jensen, Per Anker; Jóhannesson, Elvar Ingi

    2013-01-01

    with BIM is studied. Based on findings from both parts, ideas and recommendations are put forward for the Icelandic building industry about feasible ways of implementing BIM. Findings – Among the results are that the use of BIM is very limited in the Icelandic companies compared to the other Nordic...... 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...... countries. Research limitations/implications – The research is limited to the Nordic countries in Europe, but many recommendations could be relevant to other countries. Practical implications – It is recommended to the Icelandic building authorities to get into cooperation with their Nordic counterparts...

  20. 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....

  1. Build Your Own Payment Model.

    Science.gov (United States)

    Berlin, Joey

    2017-07-01

    Physicians participating in MACRA have a unique opportunity to create and submit their own alternative payment models to the government and take command of their own future payments. At least one Texas physician is taking a crack at developing his own model.

  2. 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.

  3. Minimalism in Inflation Model Building

    CERN Document Server

    Dvali, Gia; Dvali, Gia; Riotto, Antonio

    1998-01-01

    In this paper we demand that a successfull inflationary scenario should follow from a model entirely motivated by particle physics considerations. We show that such a connection is indeed possible within the framework of concrete supersymmetric Grand Unified Theories where the doublet-triplet splitting problem is naturally solved. The Fayet-Iliopoulos D-term of a gauge $U(1)_{\\xi}$ symmetry, which plays a crucial role in the solution of the doublet-triplet splitting problem, simultaneously provides a built-in inflationary slope protected from dangerous supergravity corrections.

  4. Minimalism in inflation model building

    Science.gov (United States)

    Dvali, Gia; Riotto, Antonio

    1998-01-01

    In this paper we demand that a successful inflationary scenario should follow from a model entirely motivated by particle physics considerations. We show that such a connection is indeed possible within the framework of concrete supersymmetric Grand Unified Theories where the doublet-triplet splitting problem is naturally solved. The Fayet-Iliopoulos D-term of a gauge U(1)ξ symmetry, which plays a crucial role in the solution of the doublet-triplet splitting problem, simultaneously provides a built-in inflationary slope protected from dangerous supergravity corrections.

  5. 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.

  6. Model for Refurbishment of Heritage Buildings

    DEFF Research Database (Denmark)

    Rasmussen, Torben Valdbjørn

    2014-01-01

    the Heritage Agency, the Danish Working Environment Authority and the owner as a team cooperated in identifying feasible refurbishments. In this case, the focus centered on restoring and identifying potential energy savings and deciding on energy upgrading measures for the listed complex. The refurbished...... 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...

  7. Heterotic model building: 16 special manifolds

    International Nuclear Information System (INIS)

    He, Yang-Hui; Lee, Seung-Joo; Lukas, Andre; Sun, Chuang

    2014-01-01

    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.

  8. 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

  9. Understanding the origin of radon indoors: Building a predictive capability

    International Nuclear Information System (INIS)

    Sextro, R.G.

    1985-12-01

    Indoor radon concentrations one to two orders of magnitude higher than the US average of ∼60 Bq m -3 (∼1.5 pCi L -1 ) are not uncommon, and concentrations greater than 4000 Bq m -3 have been observed in houses in areas with no known artificially-enhanced radon sources. In general, source categories for indoor radon are well known: soil, domestic water, building materials, outdoor air, and natural gas. Soil is thought to be a major source of indoor radon, either through molecular diffusion (usually a minor component) or convective flow of soil gas. While soil gas flow into residences has been demonstrated, no detailed understanding of the important factors affecting the source strength of radon from soil has yet emerged. Preliminary work in this area has identified a number of likely issues, including the concentration of radium in the soil, the emanating fraction, soil type, soil moisture content, and other factors that would influence soil permeability and soil gas transport. Because a significant number of dwellings are expected to have indoor radon concentrations above guideline levels, a predictive capability is needed that would help identify geographical areas having the potential for high indoor concentrations. This paper reviews the preliminary work that has been done to identify important soil and building characteristics that influence the migration of radon and outlines the areas of further research necessary for development of a predictive method. 32 refs., 4 figs

  10. 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.

  11. Modeling of Dynamic Responses in Building Insulation

    Directory of Open Access Journals (Sweden)

    Anna Antonyová

    2015-10-01

    Full Text Available In this research a measurement systemwas developedfor monitoring humidity and temperature in the cavity between the wall and the insulating material in the building envelope. This new technology does not disturb the insulating material during testing. The measurement system can also be applied to insulation fixed ten or twenty years earlier and sufficiently reveals the quality of the insulation. A mathematical model is proposed to characterize the dynamic responses in the cavity between the wall and the building insulation as influenced by weather conditions.These dynamic responses are manifested as a delay of both humidity and temperature changes in the cavity when compared with the changes in the ambient surrounding of the building. The process is then modeled through numerical methods and statistical analysis of the experimental data obtained using the new system of measurement.

  12. 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

    International Nuclear Information System (INIS)

    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.

  13. Prediction of hydrogen distribution in the reactor building in CANDU6 plant

    International Nuclear Information System (INIS)

    Jin, Y.; Song, Y.

    2008-01-01

    The CANDU plants have a lot of zircaloy. The fuel cladding, calandria tubes and pressure tubes are made of zircaloy. The zircaloy can be oxidized and hydrogen is generated during severe accident progression. The detonation or deflagration to detonation transition (DDT) due to hydrogen combustion may occur if the local hydrogen concentration or global hydrogen concentration exceeds certain value. The detonation may result in the rupture of the reactor building. The inside of the reactor building of CANDU plants is complex. So prediction of hydrogen distribution in the reactor building is important. This prediction is made using ISAAC code and GOTHIC code. ISAAC code partitioned the reactor building in to 7 compartments. GOTHIC code modeled the CANDU6 reactor building using 12 nodes. The hydrogen concentrations in the various compartments in the reactor building are compared. GOTHIC code slightly underpredicts hydrogen concentration in the F/M rooms than ISAAC code, but trend is same. The hydrogen concentration in the boiler room and the moderator room shows almost same as for both codes. (author)

  14. PREDICTED PERCENTAGE DISSATISFIED (PPD) MODEL ...

    African Journals Online (AJOL)

    HOD

    their low power requirements, are relatively cheap and are environment friendly. ... PREDICTED PERCENTAGE DISSATISFIED MODEL EVALUATION OF EVAPORATIVE COOLING ... The performance of direct evaporative coolers is a.

  15. models for predicting compressive strength and water absorption

    African Journals Online (AJOL)

    user

    presents a mathematical model for predicting the compressive strength and water absorption of laterite-quarry dust cement block using ... building and construction of new infrastructure and .... In (6), R is a vector containing the real ratios of the.

  16. 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......The application of product modeling in manufacturing companies raises the important question of how to model product knowledge in a comprehensible and efficient way. An important challenge is to qualify engineers to model and specify IT-systems (product models) to support their specification...... activities. A basic assumption is that engineers have to take the responsability for building product models to be used in their domain. To do that they must be able to carry out the modeling task on their own without any need for support from computer science experts. This paper presents a set of simple...

  17. 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.

  18. Aspects of superstring model-building

    International Nuclear Information System (INIS)

    Ellis, J.

    1989-01-01

    Several approaches to model-building with strings are discussed, including Calabi-Yau manifolds and fermionic formulations of strings directly in four dimensions. Ideas about supersymmetry breaking are reviewed. Flipped SU(5)xU(1) is touted as the theory of everything below the Planck scale (perhaps). (author). 64 refs, 7 figs

  19. 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.

  20. 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.

  1. 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.

  2. Improved model for solar heating of buildings

    OpenAIRE

    Lie, Bernt

    2015-01-01

    A considerable future increase in the global energy use is expected, and the effects of energy conversion on the climate are already observed. Future energy conversion should thus be based on resources that have negligible climate effects; solar energy is perhaps the most important of such resources. The presented work builds on a previous complete model for solar heating of a house; here the aim to introduce ventilation heat recovery and improve on the hot water storage model. Ventilation he...

  3. 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.

  4. Predicted carbonation of existing concrete building based on the Indonesian tropical micro-climate

    Science.gov (United States)

    Hilmy, M.; Prabowo, H.

    2018-03-01

    This paper is aimed to predict the carbonation progress based on the previous mathematical model. It shortly explains the nature of carbonation including the processes and effects. Environmental humidity and temperature of the existing concrete building are measured and compared to data from local Meteorological, Climatological, and Geophysical Agency. The data gained are expressed in the form of annual hygrothermal values which will use as the input parameter in carbonation model. The physical properties of the observed building such as its location, dimensions, and structural material used are quantified. These data then utilized as an important input parameter for carbonation coefficients. The relationships between relative humidity and the rate of carbonation established. The results can provide a basis for repair and maintenance of existing concrete buildings and the sake of service life analysis of them.

  5. Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks

    International Nuclear Information System (INIS)

    Li Qiong; Meng Qinglin; Cai Jiejin; Yoshino, Hiroshi; Mochida, Akashi

    2009-01-01

    This study presents four modeling techniques for the prediction of hourly cooling load in the building. In addition to the traditional back propagation neural network (BPNN), the radial basis function neural network (RBFNN), general regression neural network (GRNN) and support vector machine (SVM) are considered. All the prediction models have been applied to an office building in Guangzhou, China. Evaluation of the prediction accuracy of the four models is based on the root mean square error (RMSE) and mean relative error (MRE). The simulation results demonstrate that the four discussed models can be effective for building cooling load prediction. The SVM and GRNN methods can achieve better accuracy and generalization than the BPNN and RBFNN methods

  6. 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.

  7. Stochastic approaches to inflation model building

    International Nuclear Information System (INIS)

    Ramirez, Erandy; Liddle, Andrew R.

    2005-01-01

    While inflation gives an appealing explanation of observed cosmological data, there are a wide range of different inflation models, providing differing predictions for the initial perturbations. Typically models are motivated either by fundamental physics considerations or by simplicity. An alternative is to generate large numbers of models via a random generation process, such as the flow equations approach. The flow equations approach is known to predict a definite structure to the observational predictions. In this paper, we first demonstrate a more efficient implementation of the flow equations exploiting an analytic solution found by Liddle (2003). We then consider alternative stochastic methods of generating large numbers of inflation models, with the aim of testing whether the structures generated by the flow equations are robust. We find that while typically there remains some concentration of points in the observable plane under the different methods, there is significant variation in the predictions amongst the methods considered

  8. 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.

  9. 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.

  10. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  11. Support vector machine in prediction of building energy demand using pseudo dynamic approach

    NARCIS (Netherlands)

    Paudel, S.; Nguyen, H.P.; Kling, W.L.; Elmitri, Mohamed; Lacarriere, B.; Corre, le O.

    2015-01-01

    Building’s energy consumption prediction is a major concern in the recent years and many efforts have been achieved in order to improve the energy management of buildings. In particular, the prediction of energy consumption in building is essential for the energy operator to build an optimal

  12. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  13. Predicting the hurricane damage ratio of commercial buildings by claim payout from Hurricane Ike

    OpenAIRE

    J. M. Kim; P. K. Woods; Y. J. Park; T. H. Kim; J. S. Choi; K. Son

    2013-01-01

    The increasing occurrence of natural disaster events and related damages have led to a growing demand for models that predict financial loss. Although considerable research has studied the financial losses related to natural disaster events, and has found significant predictors, there has not yet been a comprehensive study that addresses the relationship among the vulnerabilities, natural disasters, and economic losses of the individual buildings. This study...

  14. Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

    Czech Academy of Sciences Publication Activity Database

    Pčolka, M.; Žáčeková, E.; Robinett, R.; Čelikovský, Sergej; Šebek, M.

    2016-01-01

    Roč. 53, č. 1 (2016), s. 124-138 ISSN 0967-0661 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Model predictive control * Identification for control * Building climatecontrol Subject RIV: BC - Control Systems Theory Impact factor: 2.602, year: 2016 http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf

  15. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... signal based on a process model, coping with constraints on inputs and ... paper, we will present an introduction to the theory and application of MPC with Matlab codes ... section 5 presents the simulation results and section 6.

  16. Progress in D-brane model building

    International Nuclear Information System (INIS)

    Marchesano, F.

    2007-01-01

    The state of the art in D-brane model building is briefly reviewed, focusing on recent achievements in the construction of D=4 N=1 type II string vacua with semi-realistic gauge sectors. Such progress relies on a better understanding of the spectrum of BPS D-branes, the effective field theory obtained from them and the explicit construction of vacua. We first consider D-branes in standard Calabi-Yau compactifications, and then the more involved case of compactifications with fluxes. We discuss how the non-trivial interplay between D-branes and fluxes modifies the previous model-building rules, as well as provides new possibilities to connect string theory to particle physics. (Abstract Copyright [2007], Wiley Periodicals, Inc.)

  17. BUILDING DETECTION USING AERIAL IMAGES AND DIGITAL SURFACE MODELS

    Directory of Open Access Journals (Sweden)

    J. Mu

    2017-05-01

    Full Text Available 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.

  18. 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

  19. 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...... is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved....

  20. 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.

  1. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria

    2017-01-01

    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  2. Boxes of Model Building and Visualization.

    Science.gov (United States)

    Turk, Dušan

    2017-01-01

    Macromolecular crystallography and electron microscopy (single-particle and in situ tomography) are merging into a single approach used by the two coalescing scientific communities. The merger is a consequence of technical developments that enabled determination of atomic structures of macromolecules by electron microscopy. Technological progress in experimental methods of macromolecular structure determination, computer hardware, and software changed and continues to change the nature of model building and visualization of molecular structures. However, the increase in automation and availability of structure validation are reducing interactive manual model building to fiddling with details. On the other hand, interactive modeling tools increasingly rely on search and complex energy calculation procedures, which make manually driven changes in geometry increasingly powerful and at the same time less demanding. Thus, the need for accurate manual positioning of a model is decreasing. The user's push only needs to be sufficient to bring the model within the increasing convergence radius of the computing tools. It seems that we can now better than ever determine an average single structure. The tools work better, requirements for engagement of human brain are lowered, and the frontier of intellectual and scientific challenges has moved on. The quest for resolution of new challenges requires out-of-the-box thinking. A few issues such as model bias and correctness of structure, ongoing developments in parameters defining geometric restraints, limitations of the ideal average single structure, and limitations of Bragg spot data are discussed here, together with the challenges that lie ahead.

  3. 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.

  4. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  5. 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

  6. A procedure for building product models

    DEFF Research Database (Denmark)

    Hvam, Lars; Riis, Jesper; Malis, Martin

    2001-01-01

    This article presents a procedure for building product models to support the specification processes dealing with sales, design of product variants and production preparation. The procedure includes, as the first phase, an analysis and redesign of the business processes, which are to be supported...... 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...

  7. Modeling of HVAC operational faults in building performance simulation

    International Nuclear Information System (INIS)

    Zhang, Rongpeng; Hong, Tianzhen

    2017-01-01

    Highlights: •Discuss significance of capturing operational faults in existing buildings. •Develop a novel feature in EnergyPlus to model operational faults of HVAC systems. •Compare three approaches to faults modeling using EnergyPlus. •A case study demonstrates the use of the fault-modeling feature. •Future developments of new faults are discussed. -- Abstract: Operational faults are common in the heating, ventilating, and air conditioning (HVAC) systems of existing buildings, leading to a decrease in energy efficiency and occupant comfort. Various fault detection and diagnostic methods have been developed to identify and analyze HVAC operational faults at the component or subsystem level. However, current methods lack a holistic approach to predicting the overall impacts of faults at the building level—an approach that adequately addresses the coupling between various operational components, the synchronized effect between simultaneous faults, and the dynamic nature of fault severity. This study introduces the novel development of a fault-modeling feature in EnergyPlus which fills in the knowledge gap left by previous studies. This paper presents the design and implementation of the new feature in EnergyPlus and discusses in detail the fault-modeling challenges faced. The new fault-modeling feature enables EnergyPlus to quantify the impacts of faults on building energy use and occupant comfort, thus supporting the decision making of timely fault corrections. Including actual building operational faults in energy models also improves the accuracy of the baseline model, which is critical in the measurement and verification of retrofit or commissioning projects. As an example, EnergyPlus version 8.6 was used to investigate the impacts of a number of typical operational faults in an office building across several U.S. climate zones. The results demonstrate that the faults have significant impacts on building energy performance as well as on occupant

  8. Predictive Modeling in Race Walking

    Directory of Open Access Journals (Sweden)

    Krzysztof Wiktorowicz

    2015-01-01

    Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

  9. Occupant behavior in building energy simulation: towards a fit-for-purpose modeling strategy

    NARCIS (Netherlands)

    Gaetani, I.; Hoes, P.; Hensen, J.L.M.

    2016-01-01

    Occupant behavior is nowadays acknowledged as a main source of discrepancy between predicted and actual building performance; therefore, researchers attempt to model occupants' presence and adaptive actions more realistically. Literature shows a proliferation of increasingly complex, data-based

  10. Public health component in building information modeling

    Science.gov (United States)

    Trufanov, A. I.; Rossodivita, A.; Tikhomirov, A. A.; Berestneva, O. G.; Marukhina, O. V.

    2018-05-01

    A building information modelling (BIM) conception has established itself as an effective and practical approach to plan, design, construct, and manage buildings and infrastructure. Analysis of the governance literature has shown that the BIM-developed tools do not take fully into account the growing demands from ecology and health fields. In this connection, it is possible to offer an optimal way of adapting such tools to the necessary consideration of the sanitary and hygienic specifications of materials used in construction industry. It is proposed to do it through the introduction of assessments that meet the requirements of national sanitary standards. This approach was demonstrated in the case study of Revit® program.

  11. A Probabilistic Model for Exteriors of Residential Buildings

    KAUST Repository

    Fan, Lubin

    2016-07-29

    We propose a new framework to model the exterior of residential buildings. The main goal of our work is to design a model that can be learned from data that is observable from the outside of a building and that can be trained with widely available data such as aerial images and street-view images. First, we propose a parametric model to describe the exterior of a building (with a varying number of parameters) and propose a set of attributes as a building representation with fixed dimensionality. Second, we propose a hierarchical graphical model with hidden variables to encode the relationships between building attributes and learn both the structure and parameters of the model from the database. Third, we propose optimization algorithms to generate three-dimensional models based on building attributes sampled from the graphical model. Finally, we demonstrate our framework by synthesizing new building models and completing partially observed building models from photographs.

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

    International Nuclear Information System (INIS)

    Terwilliger, Thomas C.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Moriarty, Nigel W.; Adams, Paul D.; Read, Randy J.; Zwart, Peter H.; Hung, Li-Wei

    2008-01-01

    An OMIT procedure is presented that has the benefits of iterative model building density modification and refinement yet is essentially unbiased by the atomic model that is built. 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

  13. Working group report: Flavor physics and model building

    Indian Academy of Sciences (India)

    cO Indian Academy of Sciences. Vol. ... This is the report of flavor physics and model building working group at ... those in model building have been primarily devoted to neutrino physics. ..... [12] Andrei Gritsan, ICHEP 2004, Beijing, China.

  14. Airflow and radon transport modeling in four large buildings

    International Nuclear Information System (INIS)

    Fan, J.B.; Persily, A.K.

    1995-01-01

    Computer simulations of multizone airflow and contaminant transport were performed in four large buildings using the program CONTAM88. This paper describes the physical characteristics of the buildings and their idealizations as multizone building airflow systems. These buildings include a twelve-story multifamily residential building, a five-story mechanically ventilated office building with an atrium, a seven-story mechanically ventilated office building with an underground parking garage, and a one-story school building. The air change rates and interzonal airflows of these buildings are predicted for a range of wind speeds, indoor-outdoor temperature differences, and percentages of outdoor air intake in the supply air Simulations of radon transport were also performed in the buildings to investigate the effects of indoor-outdoor temperature difference and wind speed on indoor radon concentrations

  15. 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.

  16. Towards evaluation and prediction of building sustainability using life cycle behaviour simulation

    Directory of Open Access Journals (Sweden)

    Marzouk Mohamed

    2017-01-01

    Full Text Available Nowadays researchers and practitioners are oriented towards questioning how effective are the different building life cycle activities contribution to preserving the environment and fulfilling the need for equilibrium. Terminologies such as Building sustainability and Green Buildings have long been adopted yet the evaluation of such has been driven through the use of rating systems. LEED of the United States, BREEAM of the United Kingdom, and Pearl of the United Arab Emirates are namely good examples of these rating systems. This paper introduces a new approach for evaluation of building life cycle sustainability through simulation of activities interaction and studying its behaviour. The effort focuses on comprehending impact and effect of suitability related activities over the whole building life cycle or period of time. The methodology includes gathering a pool of parameters through benchmarking of five selected rating systems, analytical factorization for the gathered parameters is used to elect the most influencing parameters. Followed by simulation modelling using System dynamics to capture the interaction of the considered parameters. The resulting behaviour obtained from simulation is studied and used in designing a tool for prediction of sustainability.

  17. 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.

  18. Directions for model building from asymptotic safety

    Science.gov (United States)

    Bond, Andrew D.; Hiller, Gudrun; Kowalska, Kamila; Litim, Daniel F.

    2017-08-01

    Building on recent advances in the understanding of gauge-Yukawa theories we explore possibilities to UV-complete the Standard Model in an asymptotically safe manner. Minimal extensions are based on a large flavor sector of additional fermions coupled to a scalar singlet matrix field. We find that asymptotic safety requires fermions in higher representations of SU(3) C × SU(2) L . Possible signatures at colliders are worked out and include R-hadron searches, diboson signatures and the evolution of the strong and weak coupling constants.

  19. 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)

  20. Predictive performance simulations for a sustainable lecture building complex

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2012-06-01

    Full Text Available the site and building are not ideally oriented regarding the prevailing wind directions that generally follow the coast. From the perspective of the design team, the commitment to use a building information management (BIM) system at inception needed a... far more integrated approach to design development. Engineers typically wait for the architects to design the whole building, and then only drill down to final calculated structural design configurations and sizes. With BIM, these activities should...

  1. Development of predictive control strategies for building climate control

    OpenAIRE

    NAGPAL, HIMANSHU

    2018-01-01

    APPROVED The rapid growth in energy usage and CO2 emissions has become a critical issue for the whole world. It is noteworthy that buildings are a major contributor to global primary energy consumption. Among building services, use of energy in heating-ventilation-air-conditioning (HVAC) system is particularly significant (about 50\\% of the total building energy consumption). Therefore, the development and implementation of effective control strategies to optimize the operation of HVAC sys...

  2. 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.

  3. Validating computational predictions of night-time ventilation in Stanford's Y2E2 building

    Science.gov (United States)

    Chen, Chen; Lamberti, Giacomo; Gorle, Catherine

    2017-11-01

    Natural ventilation can significantly reduce building energy consumption, but robust design is a challenging task. We previously presented predictions of natural ventilation performance in Stanford's Y2E2 building using two models with different levels of fidelity, embedded in an uncertainty quantification framework to identify the dominant uncertain parameters and predict quantified confidence intervals. The results showed a slightly high cooling rate for the volume-averaged temperature, and the initial thermal mass temperature and window discharge coefficients were found to have an important influence on the results. To further investigate the potential role of these parameters on the observed discrepancies, the current study is performing additional measurements in the Y2E2 building. Wall temperatures are recorded throughout the nightflush using thermocouples; flow rates through windows are measured using hotwires; and spatial variability in the air temperature is explored. The measured wall temperatures are found the be within the range of our model assumptions, and the measured velocities agree reasonably well with our CFD predications. Considerable local variations in the indoor air temperature have been recorded, largely explaining the discrepancies in our earlier validation study. Future work will therefore focus on a local validation of the CFD results with the measurements. Center for Integrated Facility Engineering (CIFE).

  4. 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...

  5. 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

  6. 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.

  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. The prediction of engineering cost for green buildings based on information entropy

    Science.gov (United States)

    Liang, Guoqiang; Huang, Jinglian

    2018-03-01

    Green building is the developing trend in the world building industry. Additionally, construction costs are an essential consideration in building constructions. Therefore, it is necessary to investigate the problems of cost prediction in green building. On the basis of analyzing the cost of green building, this paper proposes the forecasting method of actual cost in green building based on information entropy and provides the forecasting working procedure. Using the probability density obtained from statistical data, such as labor costs, material costs, machinery costs, administration costs, profits, risk costs a unit project quotation and etc., situations can be predicted which lead to cost variations between budgeted cost and actual cost in constructions, through estimating the information entropy of budgeted cost and actual cost. The research results of this article have a practical significance in cost control of green building. Additionally, the method proposed in this article can be generalized and applied to a variety of other aspects in building management.

  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. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

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

    2011-01-01

    of a computer aided multilevel modeling network consisting a collection of new and adopted models, methods and tools for the systematic design and analysis of processes employing lipid technology. This is achieved by decomposing the problem into four levels of modeling: 1. pure component properties; 2. mixtures...... and phase behavior; 3. unit operations; and 4. process synthesis and design. The methods and tools in each level include: For the first level, a lipid‐database of collected experimental data from the open literature, confidential data from industry and generated data from validated predictive property...... 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...

  11. 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.

  12. Near-Source Modeling Updates: Building Downwash & Near-Road

    Science.gov (United States)

    The presentation describes recent research efforts in near-source model development focusing on building downwash and near-road barriers. The building downwash section summarizes a recent wind tunnel study, ongoing computational fluid dynamics simulations and efforts to improve ...

  13. Rapidly locating sources and predicting contaminant dispersion in buildings

    International Nuclear Information System (INIS)

    Sohn, Michael D.; Reynolds, Pamela; Gadgil, Ashok J.; Sextro, Richard G.

    2002-01-01

    Contaminant releases in or near a building can lead to significant human exposures unless prompt response measures are taken. However, selecting the proper response depends in part on knowing the source locations, the amounts released, and the dispersion characteristics of the pollutants. We present an approach that estimates this information in real time. It uses Bayesian statistics to interpret measurements from sensors placed in the building yielding best estimates and uncertainties for the release conditions, including the operating state of the building. Because the method is fast, it continuously updates the estimates as measurements stream in from the sensors. We show preliminary results for characterizing a gas release in a three-floor, multi-room building at the Dugway Proving Grounds, Utah, USA

  14. Novel transformation-based response prediction of shear building ...

    Indian Academy of Sciences (India)

    c Indian Academy of Sciences ... structural response of multi-storey shear buildings subject to earthquake motion. The INN is first ... China has been presented by Xie et al. (2011). ... research works have been done using INN in other fields.

  15. Encoding Dissimilarity Data for Statistical Model Building.

    Science.gov (United States)

    Wahba, Grace

    2010-12-01

    We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A "newbie" algorithm is provided for embedding new objects into this space. This allows the dissimilarity information to be incorporated into a Smoothing Spline ANOVA penalized likelihood model, a Support Vector Machine, or any model that will admit Reproducing Kernel Hilbert Space components, for nonparametric regression, supervised learning, or semi-supervised learning. Future work and open questions are discussed. The papers are: F. Lu, S. Keles, S. Wright and G. Wahba 2005. A framework for kernel regularization with application to protein clustering. Proceedings of the National Academy of Sciences 102, 12332-1233.G. Corrada Bravo, G. Wahba, K. Lee, B. Klein, R. Klein and S. Iyengar 2009. Examining the relative influence of familial, genetic and environmental covariate information in flexible risk models. Proceedings of the National Academy of Sciences 106, 8128-8133F. Lu, Y. Lin and G. Wahba. Robust manifold unfolding with kernel regularization. TR 1008, Department of Statistics, University of Wisconsin-Madison.

  16. Impact of whole-building hygrothermal modelling on the assessment of indoor climate in a library building

    Energy Technology Data Exchange (ETDEWEB)

    Steeman, M.; Janssens, A. [Ghent University, Department of Architecture and Urban Planning, Jozef Plateaustraat 22, B-9000 Gent (Belgium); De Paepe, M. [Ghent University, Department of Flow, Heat and Combustion Mechanics, Sint-Pietersnieuwstraat 41, B-9000 Gent (Belgium)

    2010-07-15

    This paper focuses on the importance of accurately modelling the hygrothermal interaction between the building and its hygroscopic content for the assessment of the indoor climate. Libraries contain a large amount of stored books which require a stable relative humidity to guarantee their preservation. On the other hand, visitors and staff must be comfortable with the indoor climate. The indoor climate of a new library building is evaluated by means of measurements and simulations. Complaints of the staff are confirmed by measured data during the winter and summer of 2007-2008. For the evaluation of the indoor climate, a building simulation model is used in which the porous books are either described by a HAM model or by a simplified isothermal model. Calculations demonstrate that the HAM model predicts a more stable indoor climate regarding both temperature and relative humidity variations in comparison to the estimations by the simplified model. This is attributed to the ability of the HAM model to account for the effect of temperature variations on moisture storage. Moreover, by applying the HAM model, a good agreement with the measured indoor climate is found. As expected, a larger exposed book surface ameliorates the indoor climate because a more stable indoor relative humidity is obtained. Finally, the building simulation model is used to improve the indoor climate with respect to the preservation of valuable books. Results demonstrate that more stringent interventions on the air handling unit are expected when a simplified approach is used to model the hygroscopic books. (author)

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

    OpenAIRE

    Lee, Jin Kook; Kim, Mi Jeong

    2014-01-01

    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 modelli...

  18. 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 and ...... and hereby shift the heat pump power consumption to periods with both low electricity prices and a high fraction of green energy in the grid.......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...

  19. Dispersion model for airborne radioactive particulates inside a process building

    International Nuclear Information System (INIS)

    Perkins, W.C.; Stoddard, D.H.

    1984-02-01

    An empirical model, predicting the spread of airborne radioactive particles after they are released inside a building, has been developed. The basis for this model is a composite of data for dispersion of airborne activity recorded during 12 case incidents. These incidents occurred at the Savannah River Plant (SRP) during approximately 90 plant-years of experience with the chemical and metallurgical processing of purified neptunium and plutonium. The model illustrates that the multiple-air-zone concept, used in the designs of many nuclear facilities, can be an efficient safety feature to limit the spread of airborne activity from a release. This study also provides some insight into an apparently anomalous behavior of airborne particulates, namely, their migration against the prevailing flow of ventilation air. 2 references, 12 figures, 4 tables

  20. Flexible building stock modelling with array-programming

    DEFF Research Database (Denmark)

    Brøgger, Morten; Wittchen, Kim Bjarne

    2017-01-01

    Many building stock models employ archetype-buildings in order to capture the essential characteristics of a diverse building stock. However, these models often require multiple archetypes, which make them inflexible. This paper proposes an array-programming based model, which calculates the heat...... tend to overestimate potential energy-savings, if we do not consider these discrepancies. The proposed model makes it possible to compute and visualize potential energy-savings in a flexible and transparent way....

  1. Weather Correlations to Calculate Infiltration Rates for U. S. Commercial Building Energy Models.

    Science.gov (United States)

    Ng, Lisa C; Quiles, Nelson Ojeda; Dols, W Stuart; Emmerich, Steven J

    2018-01-01

    As building envelope performance improves, a greater percentage of building energy loss will occur through envelope leakage. Although the energy impacts of infiltration on building energy use can be significant, current energy simulation software have limited ability to accurately account for envelope infiltration and the impacts of improved airtightness. This paper extends previous work by the National Institute of Standards and Technology that developed a set of EnergyPlus inputs for modeling infiltration in several commercial reference buildings using Chicago weather. The current work includes cities in seven additional climate zones and uses the updated versions of the prototype commercial building types developed by the Pacific Northwest National Laboratory for the U. S. Department of Energy. Comparisons were made between the predicted infiltration rates using three representations of the commercial building types: PNNL EnergyPlus models, CONTAM models, and EnergyPlus models using the infiltration inputs developed in this paper. The newly developed infiltration inputs in EnergyPlus yielded average annual increases of 3 % and 8 % in the HVAC electrical and gas use, respectively, over the original infiltration inputs in the PNNL EnergyPlus models. When analyzing the benefits of building envelope airtightening, greater HVAC energy savings were predicted using the newly developed infiltration inputs in EnergyPlus compared with using the original infiltration inputs. These results indicate that the effects of infiltration on HVAC energy use can be significant and that infiltration can and should be better accounted for in whole-building energy models.

  2. 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

  3. 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.

  4. 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.

  5. 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

    2016-01-01

    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. PMID:27376303

  6. Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard

    International Nuclear Information System (INIS)

    Terwilliger, Thomas C.; Grosse-Kunstleve, Ralf W.; Afonine, Pavel V.; Moriarty, Nigel W.; Zwart, Peter H.; Hung, Li-Wei; Read, Randy J.; Adams, Paul D.

    2008-01-01

    The highly automated PHENIX AutoBuild wizard is described. The procedure can be applied equally well to phases derived from isomorphous/anomalous and molecular-replacement methods. The PHENIX AutoBuild wizard is a highly automated tool for iterative model building, structure refinement and density modification using RESOLVE 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 to 3.2 Å, 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 is relatively independent of resolution

  7. A legacy building model for holistic nursing.

    Science.gov (United States)

    Lange, Bernadette; Zahourek, Rothlyn P; Mariano, Carla

    2014-06-01

    This pilot project was an effort to record the historical roots, development, and legacy of holistic nursing through the visionary spirit of four older American Holistic Nurses Association (AHNA) members. The aim was twofold: (a) to capture the holistic nursing career experiences of elder AHNA members and (b) to begin to create a Legacy Building Model for Holistic Nursing. The narratives will help initiate an ongoing, systematic method for the collection of historical data and serve as a perpetual archive of knowledge and inspiration for present and future holistic nurses. An aesthetic inquiry approach was used to conduct in-depth interviews with four older AHNA members who have made significant contributions to holistic nursing. The narratives provide a rich description of their personal and professional evolution as holistic nurses. The narratives are presented in an aesthetic format of the art forms of snapshot, pastiche, and collage rather than traditional presentations of research findings. A synopsis of the narratives is a dialogue between the three authors and provides insight for how a Legacy Model can guide our future. Considerations for practice, education, and research are discussed based on the words of wisdom from the four older holistic nurses.

  8. 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…

  9. PV (photovoltaics) performance evaluation and simulation-based energy yield prediction for tropical buildings

    International Nuclear Information System (INIS)

    Saber, Esmail M.; Lee, Siew Eang; Manthapuri, Sumanth; Yi, Wang; Deb, Chirag

    2014-01-01

    Air pollution and climate change increased the importance of renewable energy resources like solar energy in the last decades. Rack-mounted PhotoVoltaics (PV) and Building Integrated PhotoVoltaics (BIPV) are the most common photovoltaic systems which convert incident solar radiation on façade or surrounding area to electricity. In this paper the performance of different solar cell types is evaluated for the tropical weather of Singapore. As a case study, on-site measured data of PV systems implemented in a zero energy building in Singapore, is analyzed. Different types of PV systems (silicon wafer and thin film) have been installed on rooftop, façade, car park shelter, railing and etc. The impact of different solar cell generations, arrays environmental conditions (no shading, dappled shading, full shading), orientation (South, North, East or West facing) and inclination (between PV module and horizontal direction) is investigated on performance of modules. In the second stage of research, the whole PV systems in the case study are simulated in EnergyPlus energy simulation software with several PV performance models including Simple, Equivalent one-diode and Sandia. The predicted results by different models are compared with measured data and the validated model is used to provide simulation-based energy yield predictions for wide ranges of scenarios. It has been concluded that orientation of low-slope rooftop PV has negligible impact on annual energy yield but in case of PV external sunshade, east façade and panel slope of 30–40° are the most suitable location and inclination. - Highlights: • Characteristics of PV systems in tropics are analyzed in depth. • The ambiguity toward amorphous panel energy yield in tropics is discussed. • Equivalent-one diode and Sandia models can fairly predict the energy yield. • A general guideline is provided to estimate the energy yield of PV systems in tropics

  10. Modeling arson - An exercise in qualitative model building

    Science.gov (United States)

    Heineke, J. M.

    1975-01-01

    A detailed example is given of the role of von Neumann and Morgenstern's 1944 'expected utility theorem' (in the theory of games and economic behavior) in qualitative model building. Specifically, an arsonist's decision as to the amount of time to allocate to arson and related activities is modeled, and the responsiveness of this time allocation to changes in various policy parameters is examined. Both the activity modeled and the method of presentation are intended to provide an introduction to the scope and power of the expected utility theorem in modeling situations of 'choice under uncertainty'. The robustness of such a model is shown to vary inversely with the number of preference restrictions used in the analysis. The fewer the restrictions, the wider is the class of agents to which the model is applicable, and accordingly more confidence is put in the derived results. A methodological discussion on modeling human behavior is included.

  11. Multidisciplinary Energy Assessment of Tertiary Buildings: Automated Geomatic Inspection, Building Information Modeling Reconstruction and Building Performance Simulation

    Directory of Open Access Journals (Sweden)

    Faustino Patiño-Cambeiro

    2017-07-01

    Full Text Available There is an urgent need for energy efficiency in buildings within the European framework, considering its environmental implications, and Europe’s energy dependence. Furthermore, the need for enhancing and increasing productivity in the building industry turns new technologies and building energy performance simulation environments into extremely interesting solutions towards rigorous analysis and decision making in renovation within acceptable risk levels. The present work describes a multidisciplinary approach for the estimation of the energy performance of an educational building. The research involved data acquisition with advanced geomatic tools, the development of an optimized building information model, and energy assessment in Building Performance Simulation (BPS software. Interoperability issues were observed in the different steps of the process. The inspection and diagnostic phases were conducted in a timely, accurate manner thanks to automated data acquisition and subsequent analysis using Building Information Modeling based tools (BIM-based tools. Energy simulation was performed using Design Builder, and the results obtained were compared with those yielded by the official software tool established by Spanish regulations for energy certification. The discrepancies between the results of both programs have proven that the official software program is conservative in this sense. This may cause the depreciation of the assessed buildings.

  12. MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

    Science.gov (United States)

    Son, S. W.; Lim, Y.; Kim, D.

    2017-12-01

    The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

  13. Investigation Into Informational Compatibility Of Building Information Modelling And Building Performance Analysis Software Solutions

    OpenAIRE

    Hyun, S.; Marjanovic-Halburd, L.; Raslan, R.

    2015-01-01

    There are significant opportunities for Building Information Modelling (BIM) to address issues related to sustainable and energy efficient building design. While the potential benefits associated with the integration of BIM and BPA (Building Performance Analysis) have been recognised, its specifications and formats remain in their early infancy and often fail to live up to the promise of seamless interoperability at various stages of design process. This paper conducts a case study to investi...

  14. Prediction of moisture migration and pore pressure build-up in concrete at high temperatures

    International Nuclear Information System (INIS)

    Ichikawa, Y.; England, G.L.

    2004-01-01

    Prediction of moisture migration and pore pressure build-up in non-uniformly heated concrete is important for safe operation of concrete containment vessels in nuclear power reactors and for assessing the behaviour of fire-exposed concrete structures. (1) Changes in moisture content distribution in a concrete containment vessel during long-term operation should be investigated, since the durability and radiation shielding ability of concrete are strongly influenced by its moisture content. (2) The pressure build-up in a concrete containment vessel in a postulated accident should be evaluated in order to determine whether a venting system is necessary between liner and concrete to relieve the pore pressure. (3) When concrete is subjected to rapid heating during a fire, the concrete can suffer from spalling due to pressure build-up in the concrete pores. This paper presents a mathematical and computational model for predicting changes in temperature, moisture content and pore pressure in concrete at elevated temperatures. A pair of differential equations for one-dimensional heat and moisture transfer in concrete are derived from the conservation of energy and mass, and take into account the temperature-dependent release of gel water and chemically bound water due to dehydration. These equations are numerically solved by the finite difference method. In the numerical analysis, the pressure, density and dynamic viscosity of water in the concrete pores are calculated explicitly from a set of formulated equations. The numerical analysis results are compared with two different sets of experimental data: (a) long-term (531 days) moisture migration test under a steady-state temperature of 200 deg. C, and (b) short-term (114 min) pressure build-up test under transient heating. These experiments were performed to investigate the moisture migration and pressure build-up in the concrete wall of a reactor containment vessel at high temperatures. The former experiment simulated

  15. 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).

  16. 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.

  17. 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

    cavity such as behind the exterior cladding of a building envelope, 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 constructionplane. The paper presents the models and how they have...

  18. COMPLEMENTARITY OF HISTORIC BUILDING INFORMATION MODELLING AND GEOGRAPHIC INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    X. Yang

    2016-06-01

    Full Text Available 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.

  19. 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...... 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......-values, time constants of the building, and other parameters related to the heat dynamics. A method for selecting the most appropriate model for a given building is outlined and finally a perspective of the applications is given. Aknowledgements to the Danish Energy Saving Trust and the Interreg IV ``Vind i...

  20. System Dynamics as Model-Based Theory Building

    OpenAIRE

    Schwaninger, Markus; Grösser, Stefan N.

    2008-01-01

    This paper introduces model-based theory building as a feature of system dynamics (SD) with large potential. It presents a systemic approach to actualizing that potential, thereby opening up a new perspective on theory building in the social sciences. The question addressed is if and how SD enables the construction of high-quality theories. This contribution is based on field experiment type projects which have been focused on model-based theory building, specifically the construction of a mi...

  1. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  2. The theoretical modelling of aerosol behaviour within containment buildings

    International Nuclear Information System (INIS)

    Dunbar, I.H.

    1988-01-01

    The modelling of the deposition of aerosol particles within the containment building plays an important part in determining the effectiveness of the building in reducing releases of activity following accidents. This paper describes attempts to ensure the accuracy of computer codes which model aerosol behaviour, with special reference to the code AEROSIM-M. Code intercomparisons have been used to test the reliability of the coding and the accuracy of the numerical methods. Those codes which assume that the particle size distribution is always lognormal give significantly different results from those which do not make this assumption but instead discretise the range of particle sizes. When the same physical assumptions are made, the predictions of different discrete codes are in reasonable agreement. In comparisons between an earlier version of AEROSIM and sodium fire experiments, the code achieved good agreement on the overall time-scale of deposition. An extensive set of tests of AEROSIM-M against experiments relevant to LWR conditions is underway. (author)

  3. Building entity models through observation and learning

    Science.gov (United States)

    Garcia, Richard; Kania, Robert; Fields, MaryAnne; Barnes, Laura

    2011-05-01

    To support the missions and tasks of mixed robotic/human teams, future robotic systems will need to adapt to the dynamic behavior of both teammates and opponents. One of the basic elements of this adaptation is the ability to exploit both long and short-term temporal data. This adaptation allows robotic systems to predict/anticipate, as well as influence, future behavior for both opponents and teammates and will afford the system the ability to adjust its own behavior in order to optimize its ability to achieve the mission goals. This work is a preliminary step in the effort to develop online entity behavior models through a combination of learning techniques and observations. As knowledge is extracted from the system through sensor and temporal feedback, agents within the multi-agent system attempt to develop and exploit a basic movement model of an opponent. For the purpose of this work, extraction and exploitation is performed through the use of a discretized two-dimensional game. The game consists of a predetermined number of sentries attempting to keep an unknown intruder agent from penetrating their territory. The sentries utilize temporal data coupled with past opponent observations to hypothesize the probable locations of the opponent and thus optimize their guarding locations.

  4. Consensus models to predict endocrine disruption for all ...

    Science.gov (United States)

    Humans are potentially exposed to tens of thousands of man-made chemicals in the environment. It is well known that some environmental chemicals mimic natural hormones and thus have the potential to be endocrine disruptors. Most of these environmental chemicals have never been tested for their ability to disrupt the endocrine system, in particular, their ability to interact with the estrogen receptor. EPA needs tools to prioritize thousands of chemicals, for instance in the Endocrine Disruptor Screening Program (EDSP). Collaborative Estrogen Receptor Activity Prediction Project (CERAPP) was intended to be a demonstration of the use of predictive computational models on HTS data including ToxCast and Tox21 assays to prioritize a large chemical universe of 32464 unique structures for one specific molecular target – the estrogen receptor. CERAPP combined multiple computational models for prediction of estrogen receptor activity, and used the predicted results to build a unique consensus model. Models were developed in collaboration between 17 groups in the U.S. and Europe and applied to predict the common set of chemicals. Structure-based techniques such as docking and several QSAR modeling approaches were employed, mostly using a common training set of 1677 compounds provided by U.S. EPA, to build a total of 42 classification models and 8 regression models for binding, agonist and antagonist activity. All predictions were evaluated on ToxCast data and on an exte

  5. 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.

  6. A Probabilistic Model for Exteriors of Residential Buildings

    KAUST Repository

    Fan, Lubin; Wonka, Peter

    2016-01-01

    We propose a new framework to model the exterior of residential buildings. The main goal of our work is to design a model that can be learned from data that is observable from the outside of a building and that can be trained with widely available

  7. 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.

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

    Science.gov (United States)

    Kim, J. M.; Woods, P. K.; Park, Y. J.; Son, K.

    2013-08-01

    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.

  9. Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network

    NARCIS (Netherlands)

    Paudel, S.; Elmtiri, M.; Kling, W.L.; Corre, le O.; Lacarriere, B.

    2014-01-01

    This paper presents the building heating demand prediction model with occupancy profile and operational heating power level characteristics in short time horizon (a couple of days) using artificial neural network. In addition, novel pseudo dynamic transitional model is introduced, which consider

  10. Mathematical models for indoor radon prediction

    International Nuclear Information System (INIS)

    Malanca, A.; Pessina, V.; Dallara, G.

    1995-01-01

    It is known that the indoor radon (Rn) concentration can be predicted by means of mathematical models. The simplest model relies on two variables only: the Rn source strength and the air exchange rate. In the Lawrence Berkeley Laboratory (LBL) model several environmental parameters are combined into a complex equation; besides, a correlation between the ventilation rate and the Rn entry rate from the soil is admitted. The measurements were carried out using activated carbon canisters. Seventy-five measurements of Rn concentrations were made inside two rooms placed on the second floor of a building block. One of the rooms had a single-glazed window whereas the other room had a double pane window. During three different experimental protocols, the mean Rn concentration was always higher into the room with a double-glazed window. That behavior can be accounted for by the simplest model. A further set of 450 Rn measurements was collected inside a ground-floor room with a grounding well in it. This trend maybe accounted for by the LBL model

  11. 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.

  12. 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

  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...... the modeling, free scientific contributions have been invited from specific fields that need the most attention in order to better accomplish the integral building simulations. This paper will give an overview of the advances in whole-building hygrothermal simulation that have been accomplished and presented...

  14. Collaborative data analytics for smart buildings: opportunities and models

    DEFF Research Database (Denmark)

    Lazarova-Molnar, Sanja; Mohamed, Nader

    2018-01-01

    of collaborative data analytics for smart buildings, its benefits, as well as presently possible models of carrying it out. Furthermore, we present a framework for collaborative fault detection and diagnosis as a case of collaborative data analytics for smart buildings. We also provide a preliminary analysis...... of the energy efficiency benefit of such collaborative framework for smart buildings. The result shows that significant energy savings can be achieved for smart buildings using collaborative data analytics.......Smart buildings equipped with state-of-the-art sensors and meters are becoming more common. Large quantities of data are being collected by these devices. For a single building to benefit from its own collected data, it will need to wait for a long time to collect sufficient data to build accurate...

  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. Dispersion model for airborne particulates inside a building

    International Nuclear Information System (INIS)

    Perkins, W.C.; Stoddard, D.H.

    1985-01-01

    An empirical model has been developed for the spread of airborne radioactive particles after they are released inside a building. The model has been useful in performing safety analyses of actinide materials facilities at the Savannah River Plant (SRP). These facilities employ the multiple-air-zone concept; that is, ventilation air flows from rooms or areas of least radioactive material hazard, through zones of increasing hazard, to a treatment system. A composite of the data for dispersion of airborne activity during 12 actual case incidents at SRP forms the basis for this model. These incidents occurred during approximately 90 plant-years of experience at SRP with the chemical and metallurgical processing of purified neptunium and plutonium after their recovery from irradiated uranium. The model gives ratios of the airborne activity concentrations in rooms and corridors near the site of the release. The multiple-air-zone concept has been applied to many designs of nuclear facilities as a safety feature to limit the spread of airborne activity from a release. The model illustrates the limitations of this concept: it predicts an apparently anomalous behavior of airborne particulates; namely, a small migration against the flow of the ventilation air

  17. Data driven propulsion system weight prediction model

    Science.gov (United States)

    Gerth, Richard J.

    1994-10-01

    The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.

  18. Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

    Science.gov (United States)

    Song, Chen; Zhong-Cheng, Wu; Hong, Lv

    2018-03-01

    Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

  19. ARMAGH OBSERVATORY – HISTORIC BUILDING INFORMATION MODELLING FOR VIRTUAL LEARNING IN BUILDING CONSERVATION

    Directory of Open Access Journals (Sweden)

    M. Murphy

    2017-08-01

    Full Text Available 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.

  20. 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.

  1. 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...

  2. 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.

  3. Developing Verification Systems for Building Information Models of Heritage Buildings with Heterogeneous Datasets

    Science.gov (United States)

    Chow, L.; Fai, S.

    2017-08-01

    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.

  4. Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach

    International Nuclear Information System (INIS)

    Lü, Xiaoshu; Lu, Tao; Kibert, Charles J.; Viljanen, Martti

    2015-01-01

    Highlights: • This paper presents a new modeling method to forecast energy demands. • The model is based on physical–statistical approach to improving forecast accuracy. • A new method is proposed to address the heterogeneity challenge. • Comparison with measurements shows accurate forecasts of the model. • The first physical–statistical/heterogeneous building energy modeling approach is proposed and validated. - Abstract: Energy consumption forecasting is a critical and necessary input to planning and controlling energy usage in the building sector which accounts for 40% of the world’s energy use and the world’s greatest fraction of greenhouse gas emissions. However, due to the diversity and complexity of buildings as well as the random nature of weather conditions, energy consumption and loads are stochastic and difficult to predict. This paper presents a new methodology for energy demand forecasting that addresses the heterogeneity challenges in energy modeling of buildings. The new method is based on a physical–statistical approach designed to account for building heterogeneity to improve forecast accuracy. The physical model provides a theoretical input to characterize the underlying physical mechanism of energy flows. Then stochastic parameters are introduced into the physical model and the statistical time series model is formulated to reflect model uncertainties and individual heterogeneity in buildings. A new method of model generalization based on a convex hull technique is further derived to parameterize the individual-level model parameters for consistent model coefficients while maintaining satisfactory modeling accuracy for heterogeneous buildings. The proposed method and its validation are presented in detail for four different sports buildings with field measurements. The results show that the proposed methodology and model can provide a considerable improvement in forecasting accuracy

  5. 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.

  6. Lost opportunities: Modeling commercial building energy code adoption in the United States

    International Nuclear Information System (INIS)

    Nelson, Hal T.

    2012-01-01

    This paper models the adoption of commercial building energy codes in the US between 1977 and 2006. Energy code adoption typically results in an increase in aggregate social welfare by cost effectively reducing energy expenditures. Using a Cox proportional hazards model, I test if relative state funding, a new, objective, multivariate regression-derived measure of government capacity, as well as a vector of control variables commonly used in comparative state research, predict commercial building energy code adoption. The research shows little political influence over historical commercial building energy code adoption in the sample. Colder climates and higher electricity prices also do not predict more frequent code adoptions. I do find evidence of high government capacity states being 60 percent more likely than low capacity states to adopt commercial building energy codes in the following year. Wealthier states are also more likely to adopt commercial codes. Policy recommendations to increase building code adoption include increasing access to low cost capital for the private sector and providing noncompetitive block grants to the states from the federal government. - Highlights: ► Model the adoption of commercial building energy codes from 1977–2006 in the US. ► Little political influence over historical building energy code adoption. ► High capacity states are over 60 percent more likely than low capacity states to adopt codes. ► Wealthier states are more likely to adopt commercial codes. ► Access to capital and technical assistance is critical to increase code adoption.

  7. Building Energy Modeling and Control Methods for Optimization and Renewables Integration

    Science.gov (United States)

    Burger, Eric M.

    This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled

  8. Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

    Science.gov (United States)

    Lee, Jia-Ying Joey; Miller, James Alastair; Basu, Sreetama; Kee, Ting-Zhen Vanessa; Loo, Lit-Hsin

    2018-06-01

    Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity. This approach is called "High-throughput In vitro Phenotypic Profiling for Toxicity Prediction" (HIPPTox). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks and/or activation of the DNA-damage response (DDR) pathway. Therefore, HIPPTox helps us to uncover these common modes-of-action of pulmonotoxic chemicals. HIPPTox may also be applied to other cell types or models, and accelerate the development of predictive in vitro assays for other cell-type- or organ-specific toxicities.

  9. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  10. Modelling inspection policies for building maintenance.

    Science.gov (United States)

    Christer, A H

    1982-08-01

    A method of assessing the potential of an inspection maintenance policy as opposed to an existing breakdown maintenance policy for a building complex is developed. The method is based upon information likely to be available and specific subjective assessments which could be made available. Estimates of the expected number of defects identified at an inspection and the consequential cost saving are presented as functions of the inspection frequency.

  11. 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.

  12. 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.

  13. Hygrothermal modelling of flooding events within historic buildings

    NARCIS (Netherlands)

    Huijbregts, Z.; Schellen, H.L.; Schijndel, van A.W.M.; Blades, N.

    2014-01-01

    Flooding events pose a high risk to valuable monumental buildings and their interiors. Due to higher river discharges and sea level rise, flooding events may occur more often in future. Hygrothermal building simulation models can be applied to investigate the impact of a flooding event on the

  14. Hygrothermal modelling of flooding events within historic buildings

    NARCIS (Netherlands)

    Huijbregts, Z.; Schijndel, van A.W.M.; Schellen, H.L.; Blades, N.; Mahdavi, A.; Mertens, B.

    2013-01-01

    Flooding events pose a high risk to valuable monumental buildings and their interiors. Due to higher river discharges and sea level rise, flooding events may occur more often in future. Hygrothermal building simulation models can be applied to investigate the impact of a flooding event on the

  15. 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.

  16. A prediction model for assessing residential radon concentration in Switzerland

    International Nuclear Information System (INIS)

    Hauri, Dimitri D.; Huss, Anke; Zimmermann, Frank; Kuehni, Claudia E.; Röösli, Martin

    2012-01-01

    Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th–90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40–111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69–215 Bq/m³) in the medium category, and 219 Bq/m³ (108–427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be

  17. 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)

  18. 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.

  19. 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....

  20. Energy policy for integrating the building environmental performance model of an air conditioned building in a subtropical climate

    International Nuclear Information System (INIS)

    Mui, K.W.

    2006-01-01

    For an air conditioned building, the major electricity consumption is by the heating, and air conditioning (HVAC) system. As energy saving strategies may be in conflict with the criteria of indoor air quality and thermal comfort, a concept of the building environmental performance model (BEPM) has been developed to optimize energy consumption in HVAC systems without any deterioration of the indoor air quality and thermal comfort. The BEPM is divided into two main modules: the adaptive comfort temperature (ACT) module and the new demand control ventilation (nDCV) module. This study aims to enhance and prompt the conventional operation of the air side systems by incorporating temperature reset with the adaptive comfort temperature control and the new demand control ventilation system in high rise buildings in Hong Kong. A new example weather year (1991) was established as a reference to compute the energy use of HVAC systems in buildings in order to obtain more representative data for predicting annual energy consumption. A survey of 165 Hong Kong office buildings was conducted and it provided valuable information on the existing HVAC design values in different grades of private commercial buildings in Hong Kong. It was found that the actual measured values of indoor temperature were lower than the design ones. Furthermore, with the new example weather year and the integration of the BEPM into Grade A private office buildings in Hong Kong, the total energy saving of the air conditioning systems was calculated (i.e. a saving of HK$122 million in electrical consumption per year) while the thermal comfort for the occupants was also maintained

  1. 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.

  2. Numerical model for stack gas diffusion in terrain with buildings. Variations in air flow and gas concentration with additional building near stack

    International Nuclear Information System (INIS)

    Sada, Koichi; Michioka, Takenobu; Ichikawa, Yoichi; Komiyama, Sumito; Numata, Kunio

    2009-01-01

    A numerical simulation method for predicting atmospheric flow and stack gas diffusion using a calculation domain of several km around a stack under complex terrain conditions containing buildings has been developed. The turbulence closure technique using a modified k-ε-type model without a hydrostatic approximation was used for flow calculation, and some of the calculation grids near the ground were treated as buildings using a terrain-following coordinate system. Stack gas diffusion was predicted using the Lagrangian particle model, that is, the stack gas was represented by trajectories of released particles. The developed numerical model was applied to a virtual terrain and building conditions in this study prior to the applications of a numerical model for real terrain and building conditions. The height of the additional building (H a ), located about 200 m leeward from the stack, was varied (i.e., H a =0, 20, 30 and 50 m), and its effects on airflow and the concentration of stack gas at a released height of 75 m were calculated. Furthermore, effective stack height, which was used in the safety analysis of atmospheric diffusion for nuclear facilities in Japan, was evaluated from the calculated ground-level concentration of stack gas. The cavity region behind the additional building was calculated, and turbulence near the cavity was observed to decrease when the additional building was present. According to these flow variations with the additional building, tracer gas tended to diffuse to the ground surface rapidly with the additional building at the leeward position of the cavity, and the ground-level stack gas concentration along the plume axis also increased with the height of the additional building. However, the variations in effective stack height with the height of the additional building were relatively small and ranged within several m in this study. (author)

  3. 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....

  4. Development of an atmospheric diffusion numerical model for a nuclear facility. Numerical calculation method incorporating building effects

    International Nuclear Information System (INIS)

    Sada, Koichi; Michioka, Takenobu; Ichikawa, Yoichi

    2002-01-01

    Because effluent gas is sometimes released from low positions, viz., near the ground surface and around buildings, the effects caused by buildings within the site area are not negligible for gas diffusion predictions. For these reasons, the effects caused by buildings for gas diffusion are considered under the terrain following calculation coordinate system in this report. Numerical calculation meshes on the ground surface are treated as the building with the adaptation of wall function techniques of turbulent quantities in the flow calculations using a turbulence closure model. The reflection conditions of released particles on building surfaces are taken into consideration in the diffusion calculation using the Lagrangian particle model. Obtained flow and diffusion calculation results are compared with those of wind tunnel experiments around the building. It was apparent that features observed in a wind tunnel, viz., the formation of cavity regions behind the building and the gas diffusion to the ground surface behind the building, are also obtained by numerical calculation. (author)

  5. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  6. Improving the accuracy of energy baseline models for commercial buildings with occupancy data

    International Nuclear Information System (INIS)

    Liang, Xin; Hong, Tianzhen; Shen, Geoffrey Qiping

    2016-01-01

    Highlights: • We evaluated several baseline models predicting energy use in buildings. • Including occupancy data improved accuracy of baseline model prediction. • Occupancy is highly correlated with energy use in buildings. • This simple approach can be used in decision makings of energy retrofit projects. - Abstract: More than 80% of energy is consumed during operation phase of a building’s life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. The results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M&V and facilitate investment strategies of energy efficiency retrofit.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  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. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  13. 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.

  14. Integration of Models of Building Interiors with Cadastral Data

    OpenAIRE

    Gotlib Dariusz; Karabin Marcin

    2017-01-01

    Demands for applications which use models of building interiors is growing and highly diversified. Those models are applied at the stage of designing and construction of a building, in applications which support real estate management, in navigation and marketing systems and, finally, in crisis management and security systems. They are created on the basis of different data: architectural and construction plans, both, in the analogue form, as well as CAD files, BIM data files, by means of las...

  15. 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.

  16. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

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

    Science.gov (United States)

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

    2015-01-01

    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. 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. Statistical dependence with PC and BPH was found for prostate volume (P-value BPH prediction. 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.

  18. 'Semi-realistic'F-term inflation model building in supergravity

    International Nuclear Information System (INIS)

    Kain, Ben

    2008-01-01

    We describe methods for building 'semi-realistic' models of F-term inflation. By semi-realistic we mean that they are built in, and obey the requirements of, 'semi-realistic' particle physics models. The particle physics models are taken to be effective supergravity theories derived from orbifold compactifications of string theory, and their requirements are taken to be modular invariance, absence of mass terms and stabilization of moduli. We review the particle physics models, their requirements and tools and methods for building inflation models

  19. A deep auto-encoder model for gene expression prediction.

    Science.gov (United States)

    Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

    2017-11-17

    Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

  20. Modeling volatile organic compounds sorption on dry building materials using double-exponential model

    International Nuclear Information System (INIS)

    Deng, Baoqing; Ge, Di; Li, Jiajia; Guo, Yuan; Kim, Chang Nyung

    2013-01-01

    A double-exponential surface sink model for VOCs sorption on building materials is presented. Here, the diffusion of VOCs in the material is neglected and the material is viewed as a surface sink. The VOCs concentration in the air adjacent to the material surface is introduced and assumed to always maintain equilibrium with the material-phase concentration. It is assumed that the sorption can be described by mass transfer between the room air and the air adjacent to the material surface. The mass transfer coefficient is evaluated from the empirical correlation, and the equilibrium constant can be obtained by linear fitting to the experimental data. The present model is validated through experiments in small and large test chambers. The predicted results accord well with the experimental data in both the adsorption stage and desorption stage. The model avoids the ambiguity of model constants found in other surface sink models and is easy to scale up

  1. Prediction models for successful external cephalic version: a systematic review.

    Science.gov (United States)

    Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein

    2015-12-01

    To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.

  2. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  3. Predictive user modeling with actionable attributes

    NARCIS (Netherlands)

    Zliobaite, I.; Pechenizkiy, M.

    2013-01-01

    Different machine learning techniques have been proposed and used for modeling individual and group user needs, interests and preferences. In the traditional predictive modeling instances are described by observable variables, called attributes. The goal is to learn a model for predicting the target

  4. Verification and improvement of a predictive model for radionuclide migration

    International Nuclear Information System (INIS)

    Miller, C.W.; Benson, L.V.; Carnahan, C.L.

    1982-01-01

    Prediction of the rates of migration of contaminant chemical species in groundwater flowing through toxic waste repositories is essential to the assessment of a repository's capability of meeting standards for release rates. A large number of chemical transport models, of varying degrees of complexity, have been devised for the purpose of providing this predictive capability. In general, the transport of dissolved chemical species through a water-saturated porous medium is influenced by convection, diffusion/dispersion, sorption, formation of complexes in the aqueous phase, and chemical precipitation. The reliability of predictions made with the models which omit certain of these processes is difficult to assess. A numerical model, CHEMTRN, has been developed to determine which chemical processes govern radionuclide migration. CHEMTRN builds on a model called MCCTM developed previously by Lichtner and Benson

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

    KAUST Repository

    Zhang, Yue; Habashi, Wagdi G (Ed); Khurram, Rooh Ul Amin

    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

  6. Four-dimensional strings: Phenomenology and model building

    International Nuclear Information System (INIS)

    Quiros, M.

    1989-01-01

    In these lectures we will review some of the last developments in string theories leading to the construction of realistic four-dimensional string models. Special attention will be paid to world-sheet and space-time supersymmetry, modular invariance and model building for supersymmetric and (tachyon-free) nonsupersymmetric ten and four-dimensional models. (orig.)

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

    NARCIS (Netherlands)

    Leeflang, PSH; Wittink, DR

    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

  8. Building aggregate timber supply models from individual harvest choice

    Science.gov (United States)

    Maksym Polyakov; David N. Wear; Robert Huggett

    2009-01-01

    Timber supply has traditionally been modelled using aggregate data. In this paper, we build aggregate supply models for four roundwood products for the US state of North Carolina from a stand-level harvest choice model applied to detailed forest inventory. The simulated elasticities of pulpwood supply are much lower than reported by previous studies. Cross price...

  9. 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, which...

  10. 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.

  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. 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. 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

  14. Building analytical three-field cosmological models

    Energy Technology Data Exchange (ETDEWEB)

    Santos, J.R.L. [Universidade de Federal de Campina Grande, Unidade Academica de Fisica, Campina Grande, PB (Brazil); Moraes, P.H.R.S. [ITA-Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP (Brazil); Ferreira, D.A. [Universidade de Federal de Campina Grande, Unidade Academica de Fisica, Campina Grande, PB (Brazil); Universidade Federal da Paraiba, Departamento de Fisica, Joao Pessoa, PB (Brazil); Neta, D.C.V. [Universidade de Federal de Campina Grande, Unidade Academica de Fisica, Campina Grande, PB (Brazil); Universidade Estadual da Paraiba, Departamento de Fisica, Campina Grande, PB (Brazil)

    2018-02-15

    A difficult task to deal with is the analytical treatment of models composed of three real scalar fields, as their equations of motion are in general coupled and hard to integrate. In order to overcome this problem we introduce a methodology to construct three-field models based on the so-called ''extension method''. The fundamental idea of the procedure is to combine three one-field systems in a non-trivial way, to construct an effective three scalar field model. An interesting scenario where the method can be implemented is with inflationary models, where the Einstein-Hilbert Lagrangian is coupled with the scalar field Lagrangian. We exemplify how a new model constructed from our method can lead to non-trivial behaviors for cosmological parameters. (orig.)

  15. Robust Building Energy Load Forecasting Using Physically-Based Kernel Models

    Directory of Open Access Journals (Sweden)

    Anand Krishnan Prakash

    2018-04-01

    Full Text Available Robust and accurate building energy load forecasting is important for helping building managers and utilities to plan, budget, and strategize energy resources in advance. With recent prevalent adoption of smart-meters in buildings, a significant amount of building energy consumption data became available. Many studies have developed physics-based white box models and data-driven black box models to predict building energy consumption; however, they require extensive prior knowledge about building system, need a large set of training data, or lack robustness to different forecasting scenarios. In this paper, we introduce a new building energy forecasting method based on Gaussian Process Regression (GPR that incorporates physical insights about load data characteristics to improve accuracy while reducing training requirements. The GPR is a non-parametric regression method that models the data as a joint Gaussian distribution with mean and covariance functions and forecast using the Bayesian updating. We model the covariance function of the GPR to reflect the data patterns in different forecasting horizon scenarios, as prior knowledge. Our method takes advantage of the modeling flexibility and computational efficiency of the GPR while benefiting from the physical insights to further improve the training efficiency and accuracy. We evaluate our method with three field datasets from two university campuses (Carnegie Mellon University and Stanford University for both short- and long-term load forecasting. The results show that our method performs more accurately, especially when the training dataset is small, compared to other state-of-the-art forecasting models (up to 2.95 times smaller prediction error.

  16. Robust predictions of the interacting boson model

    International Nuclear Information System (INIS)

    Casten, R.F.; Koeln Univ.

    1994-01-01

    While most recognized for its symmetries and algebraic structure, the IBA model has other less-well-known but equally intrinsic properties which give unavoidable, parameter-free predictions. These predictions concern central aspects of low-energy nuclear collective structure. This paper outlines these ''robust'' predictions and compares them with the data

  17. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    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 is a r...

  18. Building functional networks of spiking model neurons.

    Science.gov (United States)

    Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

    2016-03-01

    Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

  19. Guidelines for Reproducibly Building and Simulating Systems Biology Models.

    Science.gov (United States)

    Medley, J Kyle; Goldberg, Arthur P; Karr, Jonathan R

    2016-10-01

    Reproducibility is the cornerstone of the scientific method. However, currently, many systems biology models cannot easily be reproduced. This paper presents methods that address this problem. We analyzed the recent Mycoplasma genitalium whole-cell (WC) model to determine the requirements for reproducible modeling. We determined that reproducible modeling requires both repeatable model building and repeatable simulation. New standards and simulation software tools are needed to enhance and verify the reproducibility of modeling. New standards are needed to explicitly document every data source and assumption, and new deterministic parallel simulation tools are needed to quickly simulate large, complex models. We anticipate that these new standards and software will enable researchers to reproducibly build and simulate more complex models, including WC models.

  20. Building a generalized distributed system model

    Science.gov (United States)

    Mukkamala, R.

    1993-01-01

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

  1. Introduction of Building Information Modeling (BIM) Technologies in Construction

    Science.gov (United States)

    Milyutina, M. A.

    2018-05-01

    The issues of introduction of building information modeling (BIM) in construction industry are considered in this work. The advantages of this approach and perspectives of the transition to new design technologies, construction process management, and operation in the near future are stated. The importance of development of pilot projects that should identify the ways and means of verification of the regulatory and technical base, as well as economic indicators in the transition to Building Information Technologies in the construction, is noted.

  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. 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.

  4. A Toolkit for Building Hybrid, Multi-Resolution PMESII Models

    National Research Council Canada - National Science Library

    Bachman, John A; Harper, Karen A

    2007-01-01

    ...) models in support of a Commander's Predictive Environment (CPE) was developed. This development environment is based upon Charles River Analytic's Graphical Agent Development Environment (GRADE...

  5. String consistency for unified model building

    International Nuclear Information System (INIS)

    Chaudhuri, S.; Chung, S.W.; Hockney, G.; Lykken, J.

    1995-01-01

    We explore the use of real fermionization as a test case for understanding how specific features of phenomenological interest in the low-energy effective superpotential are realized in exact solutions to heterotic superstring theory. We present pedagogic examples of models which realize SO(10) as a level two current algebra on the world-sheet, and discuss in general how higher level current algebras can be realized in the tensor product of simple constituent conformal field theories. We describe formal developments necessary to compute couplings in models built using real fermionization. This allows us to isolate cases of spin structures where the standard prescription for real fermionization may break down. (orig.)

  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. Hybrid Building Performance Simulation Models for Industrial Energy Efficiency Applications

    Directory of Open Access Journals (Sweden)

    Peter Smolek

    2018-06-01

    Full Text Available In the challenge of achieving environmental sustainability, industrial production plants, as large contributors to the overall energy demand of a country, are prime candidates for applying energy efficiency measures. A modelling approach using cubes is used to decompose a production facility into manageable modules. All aspects of the facility are considered, classified into the building, energy system, production and logistics. This approach leads to specific challenges for building performance simulations since all parts of the facility are highly interconnected. To meet this challenge, models for the building, thermal zones, energy converters and energy grids are presented and the interfaces to the production and logistics equipment are illustrated. The advantages and limitations of the chosen approach are discussed. In an example implementation, the feasibility of the approach and models is shown. Different scenarios are simulated to highlight the models and the results are compared.

  8. Extracting falsifiable predictions from sloppy models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

    2007-12-01

    Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

  9. The prediction of epidemics through mathematical modeling.

    Science.gov (United States)

    Schaus, Catherine

    2014-01-01

    Mathematical models may be resorted to in an endeavor to predict the development of epidemics. The SIR model is one of the applications. Still too approximate, the use of statistics awaits more data in order to come closer to reality.

  10. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  11. 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.

  12. Building Information Model: advantages, tools and adoption efficiency

    Science.gov (United States)

    Abakumov, R. G.; Naumov, A. E.

    2018-03-01

    The paper expands definition and essence of Building Information Modeling. It describes content and effects from application of Information Modeling at different stages of a real property item. Analysis of long-term and short-term advantages is given. The authors included an analytical review of Revit software package in comparison with Autodesk with respect to: features, advantages and disadvantages, cost and pay cutoff. A prognostic calculation is given for efficiency of adoption of the Building Information Modeling technology, with examples of its successful adoption in Russia and worldwide.

  13. Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

    Science.gov (United States)

    Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

    2017-12-01

    Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model

  14. A model for the sustainable selection of building envelope assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Huedo, Patricia, E-mail: huedo@uji.es [Universitat Jaume I (Spain); Mulet, Elena, E-mail: emulet@uji.es [Universitat Jaume I (Spain); López-Mesa, Belinda, E-mail: belinda@unizar.es [Universidad de Zaragoza (Spain)

    2016-02-15

    The aim of this article is to define an evaluation model for the environmental impacts of building envelopes to support planners in the early phases of materials selection. The model is intended to estimate environmental impacts for different combinations of building envelope assemblies based on scientifically recognised sustainability indicators. These indicators will increase the amount of information that existing catalogues show to support planners in the selection of building assemblies. To define the model, first the environmental indicators were selected based on the specific aims of the intended sustainability assessment. Then, a simplified LCA methodology was developed to estimate the impacts applicable to three types of dwellings considering different envelope assemblies, building orientations and climate zones. This methodology takes into account the manufacturing, installation, maintenance and use phases of the building. Finally, the model was validated and a matrix in Excel was created as implementation of the model. - Highlights: • Method to assess the envelope impacts based on a simplified LCA • To be used at an earlier phase than the existing methods in a simple way. • It assigns a score by means of known sustainability indicators. • It estimates data about the embodied and operating environmental impacts. • It compares the investment costs with the costs of the consumed energy.

  15. A model for the sustainable selection of building envelope assemblies

    International Nuclear Information System (INIS)

    Huedo, Patricia; Mulet, Elena; López-Mesa, Belinda

    2016-01-01

    The aim of this article is to define an evaluation model for the environmental impacts of building envelopes to support planners in the early phases of materials selection. The model is intended to estimate environmental impacts for different combinations of building envelope assemblies based on scientifically recognised sustainability indicators. These indicators will increase the amount of information that existing catalogues show to support planners in the selection of building assemblies. To define the model, first the environmental indicators were selected based on the specific aims of the intended sustainability assessment. Then, a simplified LCA methodology was developed to estimate the impacts applicable to three types of dwellings considering different envelope assemblies, building orientations and climate zones. This methodology takes into account the manufacturing, installation, maintenance and use phases of the building. Finally, the model was validated and a matrix in Excel was created as implementation of the model. - Highlights: • Method to assess the envelope impacts based on a simplified LCA • To be used at an earlier phase than the existing methods in a simple way. • It assigns a score by means of known sustainability indicators. • It estimates data about the embodied and operating environmental impacts. • It compares the investment costs with the costs of the consumed energy.

  16. 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

  17. 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

  18. Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock

    Directory of Open Access Journals (Sweden)

    Anna Kipping

    2017-12-01

    Full Text Available Sound estimates of future heat and electricity demand with high temporal and spatial resolution are needed for energy system planning, grid design, and evaluating demand-side management options and polices on regional and national levels. In this study, smart meter data on electricity consumption in buildings are combined with cross-sectional building information to model hourly electricity consumption within the household and service sectors on a regional basis in Norway. The same modeling approach is applied to model aggregate hourly district heat consumption in three different consumer groups located in Oslo. A comparison of modeled and metered hourly energy consumption shows that hourly variations and aggregate consumption per county and year are reproduced well by the models. However, for some smaller regions, modeled annual electricity consumption is over- or underestimated by more than 20%. Our results indicate that the presented method is useful for modeling the current and future hourly energy consumption of a regional building stock, but that larger and more detailed training datasets are required to improve the models, and more detailed building stock statistics on regional level are needed to generate useful estimates on aggregate regional energy consumption.

  19. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  20. Building metaphors and extending models of grief.

    Science.gov (United States)

    VandeCreek, L

    1985-01-01

    Persons in grief turn to metaphors as they seek to understand and express their experience. Metaphors illustrated in this article include "grief is a whirlwind," "grief is the Great Depression all over again" and "grief is gray, cloudy and rainy weather." Hospice personnel can enhance their bereavement efforts by identifying and cultivating the expression of personal metaphors from patients and families. Two metaphors have gained wide cultural acceptance and lie behind contemporary scientific explorations of grief. These are "grief is recovery from illness" (Bowlby and Parkes) and "death is the last stage of growth and grief is the adjustment reaction to this growth" (Kubler-Ross). These models have developed linear perspectives of grief but have neglected to study the fluctuating intensity of symptoms. Adopting Worden's four-part typology of grief, the author illustrates how the pie graph can be used to display this important aspect of the grief experience, thus enhancing these models.

  1. Sustainability Product Properties in Building Information Models

    Science.gov (United States)

    2012-09-01

    preferred car- pool parking spots, preferred low-emitting/fuel-efficient vehicle parking spots, bike racks and telecommuting as options to promote good...most part, these have not been in a computable form. Fallon then stressed the importance of a common conceptual framework, using the IFC model...organizations would be formed with the help of Mr. Kalin. He stressed the goal of the project was to create templates that would be free to use

  2. Group theory for unified model building

    International Nuclear Information System (INIS)

    Slansky, R.

    1981-01-01

    The results gathered here on simple Lie algebras have been selected with attention to the needs of unified model builders who study Yang-Mills theories based on simple, local-symmetry groups that contain as a subgroup the SUsup(w) 2 x Usup(w) 1 x SUsup(c) 3 symmetry of the standard theory of electromagnetic, weak, and strong interactions. The major topics include, after a brief review of the standard model and its unification into a simple group, the use of Dynkin diagrams to analyze the structure of the group generators and to keep track of the weights (quantum numbers) of the representation vectors; an analysis of the subgroup structure of simple groups, including explicit coordinatizations of the projections in weight space; lists of representations, tensor products and branching rules for a number of simple groups; and other details about groups and their representations that are often helpful for surveying unified models, including vector-coupling coefficient calculations. Tabulations of representations, tensor products, and branching rules for E 6 , SO 10 , SU 6 , F 4 , SO 9 , SO 5 , SO 8 , SO 7 , SU 4 , E 7 , E 8 , SU 8 , SO 14 , SO 18 , SO 22 , and for completeness, SU 3 are included. (These tables may have other applications.) Group-theoretical techniques for analyzing symmetry breaking are described in detail and many examples are reviewed, including explicit parameterizations of mass matrices. (orig.)

  3. Experimental and analytical studies of a deeply embedded reactor building model considering soil-building interaction. Pt. 1

    International Nuclear Information System (INIS)

    Tanaka, H.; Ohta, T.; Uchiyama, S.

    1979-01-01

    The purpose of this paper is to describe the dynamic characteristics of a deeply embedded reactor building model derived from experimental and analytical studies which considers soil-building interaction behaviour. The model building is made of reinforced concrete. It has two stories above ground level and a basement, resting on sandy gravel layer at a depth of 3 meters. The backfill around the building was made to ground level. The model building is simplified and reduced to about one-fifteenth (1/15) of the prototype. It has bearing wall system for the basement and the first story, and frame system for the second. (orig.)

  4. 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.

  5. BIM, GIS and semantic models of cultural heritage buildings

    Directory of Open Access Journals (Sweden)

    Pavel Tobiáš

    2016-12-01

    Full Text Available Even though there has been a great development of using building information models in the AEC (Architecture/Engineering/Construction sector recently, creation of models of existing buildings is still not very usual. The cultural heritage documentation is still, in most cases, kept in the form of 2D drawings while these drawings mostly contain only geometry without semantics, attributes or definitions of relationships and hierarchies between particular building elements. All these additional information would, however, be very providential for the tasks of cultural heritage preservation, i.e. for the facility management of heritage buildings or for reconstruction planning and it would be suitable to manage all geometric and non-geometric information in a single 3D information model. This paper is based on the existing literature and focuses on the historic building information modelling to provide information about the current state of the art. First, a summary of available software tools is introduced while not only the BIM tools but also the related GIS software is considered. This is followed by a review of existing efforts worldwide and an evaluation of the facts found.

  6. Rain water runoff from porous building facades : implementation and application of a first-order runoff model coupled to a HAM model

    NARCIS (Netherlands)

    Brande, T. van den; Blocken, B.J.E.; Roels, S.

    2013-01-01

    Wind-driven rain (WDR) is one of the most important moisture sources for a building facade. Therefore, a reliable prediction of WDR loads is a prerequisite to assess the durability of building facade components. However, current state of the art Heat-Air-Moisture (HAM) models that are used to assess

  7. Incorporating uncertainty in predictive species distribution modelling.

    Science.gov (United States)

    Beale, Colin M; Lennon, Jack J

    2012-01-19

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

  8. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  9. Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

    Science.gov (United States)

    Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

    2018-02-01

    To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

  10. 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

  11. Validation of Occupants’ Behaviour Models for Indoor Quality Parameter and Energy Consumption Prediction

    DEFF Research Database (Denmark)

    Fabi, Valentina; Sugliano, Martina; Andersen, Rune Korsholm

    2015-01-01

    Occupants’ behaviour related to building control system plays a significant role to achieve thermal comfort and air quality in naturally-ventilated buildings. Generally, the published models of occupant's behavior are not validated, meaning that the predictive power has not yet been tested. For t...

  12. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  13. Time dependent patient no-show predictive modelling development.

    Science.gov (United States)

    Huang, Yu-Li; Hanauer, David A

    2016-05-09

    Purpose - The purpose of this paper is to develop evident-based predictive no-show models considering patients' each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach - A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings - The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications - The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value - This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients' show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows.

  14. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

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

  15. 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

  16. Current State of the Art Historic Building Information Modelling

    Science.gov (United States)

    Dore, C.; Murphy, M.

    2017-08-01

    In an extensive review of existing literature a number of observations were made in relation to the current approaches for recording and modelling existing buildings and environments: Data collection and pre-processing techniques are becoming increasingly automated to allow for near real-time data capture and fast processing of this data for later modelling applications. Current BIM software is almost completely focused on new buildings and has very limited tools and pre-defined libraries for modelling existing and historic buildings. The development of reusable parametric library objects for existing and historic buildings supports modelling with high levels of detail while decreasing the modelling time. Mapping these parametric objects to survey data, however, is still a time-consuming task that requires further research. Promising developments have been made towards automatic object recognition and feature extraction from point clouds for as-built BIM. However, results are currently limited to simple and planar features. Further work is required for automatic accurate and reliable reconstruction of complex geometries from point cloud data. Procedural modelling can provide an automated solution for generating 3D geometries but lacks the detail and accuracy required for most as-built applications in AEC and heritage fields.

  17. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  18. Models for describing the thermal characteristics of building components

    DEFF Research Database (Denmark)

    Jimenez, M.J.; Madsen, Henrik

    2008-01-01

    , for example. For the analysis of these tests, dynamic analysis models and methods are required. However, a wide variety of models and methods exists, and the problem of choosing the most appropriate approach for each particular case is a non-trivial and interdisciplinary task. Knowledge of a large family....... The characteristics of each type of model are highlighted. Some available software tools for each of the methods described will be mentioned. A case study also demonstrating the difference between linear and nonlinear models is considered....... of these approaches may therefore be very useful for selecting a suitable approach for each particular case. This paper presents an overview of models that can be applied for modelling the thermal characteristics of buildings and building components using data from outdoor testing. The choice of approach depends...

  19. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  20. Seismic simulation analysis of nuclear reactor building by soil-building interaction model

    International Nuclear Information System (INIS)

    Muto, K.; Kobayashi, T.; Motohashi, S.; Kusano, N.; Mizuno, N.; Sugiyama, N.

    1981-01-01

    Seismic simulation analysis were performed for evaluating soil-structure interaction effects by an analytical approach using a 'Lattice Model' developed by the authors. The purpose of this paper is to check the adequacy of this procedure for analyzing soil-structure interaction by means of comparing computed results with recorded ones. The 'Lattice Model' approach employs a lumped mass interactive model, in which not only the structure but also the underlying and/or surrounding soil are modeled as descretized elements. The analytical model used for this study extends about 310 m in the horizontal direction and about 103 m in depth. The reactor building is modeled as three shearing-bending sticks (outer wall, inner wall and shield wall) and the underlying and surrounding soil are divided into four shearing sticks (column directly beneath the reactor building, adjacent, near and distant columns). A corresponding input base motion for the 'Lattice Model' was determined by a deconvolution analysis using a recorded motion at elevation -18.5 m in the free-field. The results of this simulation analysis were shown to be in reasonably good agreement with the recorded ones in the forms of the distribution of ground motions and structural responses, acceleration time histories and related response spectra. These results showed that the 'Lattice Model' approach was an appropriate one to estimate the soil-structure interaction effects. (orig./HP)

  1. A model for the build-up of disordered material in ion bombarded Si

    International Nuclear Information System (INIS)

    Nelson, R.S.

    1977-01-01

    A new model based on experimental observation is developed for the build-up of disordered material in ion bombarded silicon. The model assumes that disordered zones are created in a background of migrating point defects, these zones then act as neutral sinks for such defects which interact with the zones and cause recrystallization. A simple steady state rate theory is developed to describe the build-up of disordered material with ion dose as a function of temperature. In general the theory predicts two distinct behaviour patterns depending on the temperature and the ion mass, namely a linear build-up with dose to complete disorder for heavy bombarding ions and a build-up to saturation at a relatively low level for light ions such as protons. However, in some special circumstances a transition region is predicted where the build-up of disorder approximately follows a (dose)sup(1/2) relationship before reverting to a linear behaviour at high dose. (author)

  2. Comparison of Predictive Modeling Methods of Aircraft Landing Speed

    Science.gov (United States)

    Diallo, Ousmane H.

    2012-01-01

    Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

  3. Hierarchical modeling of indoor radon concentration: how much do geology and building factors matter?

    International Nuclear Information System (INIS)

    Borgoni, Riccardo; De Francesco, Davide; De Bartolo, Daniela; Tzavidis, Nikos

    2014-01-01

    Radon is a natural gas known to be the main contributor to natural background radiation exposure and only second to smoking as major leading cause of lung cancer. The main concern is in indoor environments where the gas tends to accumulate and can reach high concentrations. The primary contributor of this gas into the building is from the soil although architectonic characteristics, such as building materials, can largely affect concentration values. Understanding the factors affecting the concentration in dwellings and workplaces is important both in prevention, when the construction of a new building is being planned, and in mitigation when the amount of Radon detected inside a building is too high. In this paper we investigate how several factors, such as geologic typologies of the soil and a range of building characteristics, impact on indoor concentration focusing, in particular, on how concentration changes as a function of the floor level. Adopting a mixed effects model to account for the hierarchical nature of the data, we also quantify the extent to which such measurable factors manage to explain the variability of indoor radon concentration. - Highlights: • It is assessed how the variability of indoor radon concentration depends on buildings and lithologies. • The lithological component has been found less relevant than the building one. • Radon-prone lithologies have been identified. • The effect of the floor where the room is located has been estimated. • Indoor radon concentration have been predicted for different dwelling typologies

  4. Modelling the distribution of 222Rn concentration in a multi level, general purpose building

    International Nuclear Information System (INIS)

    Toro, Laszlo; Noditi, Mihaela; Gheorghe, Raluca; Gheorghe, Dan

    2008-01-01

    The importance of 222 Rn (radon) in the indoor air related to the exposure form natural sources is relatively well documented. About 30% of the individual effective dose from natural sources is coming from the inhalation of 222 Rn and his short lived daughters. In unfavorable conditions given by the soil porosity and the existence of upward air movement in the soil there is a possibility to have unusually high radon concentration in houses even on soil with 'normal' 226 Ra content. Some construction solutions (high indoor spaces) should generate a significant indoor-outdoor negative pressure differences and consequently upward air currents (stack effect) which will facilitate the entrance of radon in the building. This effect will multiply the possibility of migration of radon in the building. The difficulty of the prediction of radon migration in the soil-building system increase the importance of the mathematical modelling of the behavior of radon-soil emission, infiltration and migration in the building - in areas with high radon potential. For one level simple buildings there are several models in the literature but the information regarding the multilevel building models are relatively scarce. Two different approaches used to describe the behavior of the radon gas in large (mainly high) buildings have been analyzed: Direct approach: computational fluid dynamics, solving the transport equations for the whole building (the domain of the solution of the transport and flow equations is delimited by the building envelope - the external walls); the openings (internal and external) and ventilation are defined by the boundary conditions. This approach is quite complex, the equations are solved (numerically) for highly inhomogeneous medium but is based on the fundamental processes governing the transport. In the same time it gives the possibility to obtain a concentration pattern in every part of the building. Multi-zone approach treating the building as interconnected

  5. Predictive modelling using neuroimaging data in the presence of confounds.

    Science.gov (United States)

    Rao, Anil; Monteiro, Joao M; Mourao-Miranda, Janaina

    2017-04-15

    including the confound as a predictor gives models that are less accurate than the baseline model. We do find, however, that different methods appear to focus their predictions on specific subsets of the population-of-interest, and that predictive accuracy is greater when there is no confounding present. We conclude with a discussion comparing the advantages and disadvantages of each approach, and the implications of our evaluation for building predictive models that can be used in clinical practice. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  6. A general model of confidence building: analysis and implications

    International Nuclear Information System (INIS)

    Kilgour, D.M.

    1998-01-01

    For more than two decades, security approaches in Europe have included confidence building. Many have argued that Confidence-Building Measures (CBMS) played an essential role in the enormous transformations that took place there. Thus, it is hardly,surprising that CBMs have been proposed as measures to reduce tensions and transform security relationships elsewhere in the world. The move toward wider application of CBMs has strengthened recently, as conventional military, diplomatic, and humanitarian approaches seem to have failed to address problems associated with peace-building and peace support operations. There is, however, a serious problem. We don't really know why, or even how, CBMs work. Consequently, we have no reliable way to design CBMs that would be appropriate in substance, form, and timing for regions culturally, geographically, and militarily different from Europe. Lacking a solid understanding of confidence building, we are handicapped in our efforts to extend its successes to the domain of peace building and peace support. To paraphrase Macintosh, if we don't know how CBMs succeeded in the past, then we are unlikely to be good at maintaining, improving, or extending them. The specific aim of this project is to step into this gap, using the methods of game theory to clarify some aspects of the underlying logic of confidence building. Formal decision models will be shown to contribute new and valuable insights that will assist in the design of CBMs to contribute to new problems and in new arenas. (author)

  7. 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.

  8. Management Model for efficient quality control in new buildings

    Directory of Open Access Journals (Sweden)

    C. E. Rodríguez-Jiménez

    2017-09-01

    Full Text Available The management of the quality control of each building process is usually set up in Spain from different levels of demand. This work tries to obtain a model of reference, to compare the quality control of the building process of a specific product (building, and to be able to evaluate its warranty level. In the quest of this purpose, we take credit of specialized sources and 153 real cases of Quality Control were carefully revised using a multi-judgment method. Applying different techniques to get a specific valuation (impartial of the input parameters through Delphi’s method (17 experts query, whose matrix treatment with the Fuzzy-QFD tool condenses numerical references through a weighted distribution of the selected functions and their corresponding conditioning factors. The model thus obtained (M153 is useful in order to have a quality control reference to meet the expectations of the quality.

  9. IMPROVING TRADITIONAL BUILDING REPAIR CONSTRUCTION QUALITY USING HISTORIC BUILDING INFORMATION MODELING CONCEPT

    Directory of Open Access Journals (Sweden)

    T. C. Wu

    2013-07-01

    Full Text Available In addition to the repair construction project following the repair principles contemplated by heritage experts, the construction process should be recorded and measured at any time for monitoring to ensure the quality of repair. The conventional construction record methods mostly depend on the localized shooting of 2D digital images coupled with text and table for illustration to achieve the purpose of monitoring. Such methods cannot fully and comprehensively record the 3D spatial relationships in the real world. Therefore, the construction records of traditional buildings are very important but cannot function due to technical limitations. This study applied the 3D laser scanning technology to establish a 3D point cloud model for the repair construction of historical buildings. It also broke down the detailed components of the 3D point cloud model by using the concept of the historic building information modeling, and established the 3D models of various components and their attribute data in the 3DGIS platform database. In the construction process, according to the time of completion of each stage as developed on the construction project, this study conducted the 3D laser scanning and database establishment for each stage, also applied 3DGIS spatial information and attribute information comparison and analysis to propose the analysis of differences in completion of various stages for improving the traditional building repair construction quality. This method helps to improve the quality of repair construction work of tangible cultural assets of the world. The established 3DGIS platform can be used as a power tool for subsequent management and maintenance.

  10. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

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

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... 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...

  11. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

  12. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    OpenAIRE

    David Ebert

    2006-01-01

    One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

  13. Fingerprint verification prediction model in hand dermatitis.

    Science.gov (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

    2015-07-01

    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  14. Large urban fire environment: trends and model city predictions

    International Nuclear Information System (INIS)

    Larson, D.A.; Small, R.D.

    1983-01-01

    The urban fire environment that would result from a megaton-yield nuclear weapon burst is considered. The dependence of temperatures and velocities on fire size, burning intensity, turbulence, and radiation is explored, and specific calculations for three model urban areas are presented. In all cases, high velocity fire winds are predicted. The model-city results show the influence of building density and urban sprawl on the fire environment. Additional calculations consider large-area fires with the burning intensity reduced in a blast-damaged urban center

  15. Multi-model analysis in hydrological prediction

    Science.gov (United States)

    Lanthier, M.; Arsenault, R.; Brissette, F.

    2017-12-01

    Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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...... 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...

  8. Multiple regression models for energy use in air-conditioned office buildings in different climates

    International Nuclear Information System (INIS)

    Lam, Joseph C.; Wan, Kevin K.W.; Liu Dalong; Tsang, C.L.

    2010-01-01

    An attempt was made to develop multiple regression models for office buildings in the five major climates in China - severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R 2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89-97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered.

  9. 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.

  10. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  11. Innovative model of business process reengineering at machine building enterprises

    Science.gov (United States)

    Nekrasov, R. Yu; Tempel, Yu A.; Tempel, O. A.

    2017-10-01

    The paper provides consideration of business process reengineering viewed as amanagerial innovation accepted by present day machine building enterprises, as well as waysto improve its procedure. A developed innovative model of reengineering measures isdescribed and is based on the process approach and other principles of company management.

  12. 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

  13. Profiles in Leadership: Enhancing Learning through Model and Theory Building.

    Science.gov (United States)

    Mello, Jeffrey A.

    2003-01-01

    A class assignment was designed to present factors affecting leadership dynamics, allow practice in model and theory building, and examine leadership from multicultural perspectives. Students developed a profile of a fictional or real leader and analyzed qualities, motivations, context, and effectiveness in written and oral presentations.…

  14. Building extraction for 3D city modelling using airborne laser ...

    African Journals Online (AJOL)

    Light detection and ranging (LiDAR) technology has become a standard tool for three-dimensional mapping because it offers fast rate of data acquisition with unprecedented level of accuracy. This study presents an approach to accurately extract and model building in three-dimensional space from airborne laser scanning ...

  15. Building and Sustaining Digital Collections: Models for Libraries and Museums.

    Science.gov (United States)

    Council on Library and Information Resources, Washington, DC.

    In February 2001, the Council on Library and Information Resources (CLIR) and the National Initiative for a Networked Cultural Heritage (NINCH) convened a meeting to discuss how museums and libraries are building digital collections and what business models are available to sustain them. A group of museum and library senior executives met with…

  16. Building a 3-D Appearance Model of the Human Face

    DEFF Research Database (Denmark)

    Sjöstrand, Karl; Larsen, Rasmus; Lading, Brian

    2003-01-01

    This paper describes a method for building an appearance model from three-dimensional data of human faces. The data consists of 3-D vertices, polygons and a texture map. The method uses a set of nine manually placed landmarks to automatically form a dense correspondence of thousands of points...

  17. Building on Tinto's model of engagement and persistence ...

    African Journals Online (AJOL)

    Building on Tinto's model of engagement and persistence: Experiences from the Umthombo Youth Development Foundation Scholarship Scheme. A Ross. Abstract. Background. Major inequalities in staffing levels at rural and urban hospitals contribute to poorer health outcomes in rural areas. Local and international ...

  18. 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…

  19. FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    U. S. Panday

    2012-09-01

    Full Text Available In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of – 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for

  20. Spent fuel: prediction model development

    International Nuclear Information System (INIS)

    Almassy, M.Y.; Bosi, D.M.; Cantley, D.A.

    1979-07-01

    The need for spent fuel disposal performance modeling stems from a requirement to assess the risks involved with deep geologic disposal of spent fuel, and to support licensing and public acceptance of spent fuel repositories. Through the balanced program of analysis, diagnostic testing, and disposal demonstration tests, highlighted in this presentation, the goal of defining risks and of quantifying fuel performance during long-term disposal can be attained

  1. Navy Recruit Attrition Prediction Modeling

    Science.gov (United States)

    2014-09-01

    have high correlation with attrition, such as age, job characteristics, command climate, marital status, behavior issues prior to recruitment, and the...the additive model. glm(formula = Outcome ~ Age + Gender + Marital + AFQTCat + Pay + Ed + Dep, family = binomial, data = ltraining) Deviance ...0.1 ‘ ‘ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance : 105441 on 85221 degrees of freedom Residual deviance

  2. 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

  3. Predicting and Modeling RNA Architecture

    Science.gov (United States)

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  4. Finding furfural hydrogenation catalysts via predictive modelling

    NARCIS (Netherlands)

    Strassberger, Z.; Mooijman, M.; Ruijter, E.; Alberts, A.H.; Maldonado, A.G.; Orru, R.V.A.; Rothenberg, G.

    2010-01-01

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes

  5. FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL ...

    African Journals Online (AJOL)

    FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL STRESSES IN ... the transverse residual stress in the x-direction (σx) had a maximum value of 375MPa ... the finite element method are in fair agreement with the experimental results.

  6. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico; Kryshtafovych, Andriy; Tramontano, Anna

    2009-01-01

    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

  7. Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

    Science.gov (United States)

    Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

    2013-10-01

    Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  8. Construction Worker Fatigue Prediction Model Based on System Dynamic

    Directory of Open Access Journals (Sweden)

    Wahyu Adi Tri Joko

    2017-01-01

    Full Text Available Construction accident can be caused by internal and external factors such as worker fatigue and unsafe project environment. Tight schedule of construction project forcing construction worker to work overtime in long period. This situation leads to worker fatigue. This paper proposes a model to predict construction worker fatigue based on system dynamic (SD. System dynamic is used to represent correlation among internal and external factors and to simulate level of worker fatigue. To validate the model, 93 construction workers whom worked in a high rise building construction projects, were used as case study. The result shows that excessive workload, working elevation and age, are the main factors lead to construction worker fatigue. Simulation result also shows that these factors can increase worker fatigue level to 21.2% times compared to normal condition. Beside predicting worker fatigue level this model can also be used as early warning system to prevent construction worker accident

  9. 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.

  10. Damping in building structures during earthquakes: test data and modeling

    International Nuclear Information System (INIS)

    Coats, D.W. Jr.

    1982-01-01

    A review and evaluation of the state-of-the-art of damping in building structures during earthquakes is presented. The primary emphasis is in the following areas: 1) the evaluation of commonly used mathematical techniques for incorporating damping effects in both simple and complex systems; 2) a compilation and interpretation of damping test data; and 3) an evaluation of structure testing methods, building instrumentation practices, and an investigation of rigid-body rotation effects on damping values from test data. A literature review provided the basis for evaluating mathematical techiques used to incorporate earthquake induced damping effects in simple and complex systems. A discussion on the effectiveness of damping, as a function of excitation type, is also included. Test data, from a wide range of sources, has been compiled and interpreted for buidings, nuclear power plant structures, piping, equipment, and isolated structural elements. Test methods used to determine damping and frequency parameters are discussed. In particular, the advantages and disadvantages associated with the normal mode and transfer function approaches are evaluated. Additionally, the effect of rigid-body rotations on damping values deduced from strong-motion building response records is investigated. A discussion of identification techniques typically used to determine building parameters (frequency and damping) from strong motion records is included. Finally, an analytical demonstration problem is presented to quantify the potential error in predicting fixed-base structural frequency and damping values from strong motion records, when rigid-body rotations are not properly accounted for

  11. Protocol to Manage Heritage-Building Interventions Using Heritage Building Information Modelling (HBIM

    Directory of Open Access Journals (Sweden)

    Isabel Jordan-Palomar

    2018-03-01

    Full Text Available The workflow in historic architecture projects presents problems related to the lack of clarity of processes, dispersion of information and the use of outdated tools. Different heritage organisations have showed interest in innovative methods to resolve those problems and improve cultural tourism for sustainable economic development. Building Information Modelling (BIM has emerged as a suitable computerised system for improving heritage management. Its application to historic buildings is named Historic BIM (HBIM. HBIM literature highlights the need for further research in terms of the overall processes of heritage projects, its practical implementation and a need for better cultural documentation. This work uses Design Science Research to develop a protocol to improve the workflow in heritage interdisciplinary projects. Research techniques used include documentary analysis, semi-structured interviews and focus groups. HBIM is proposed as a virtual model that will hold heritage data and will articulate processes. As a result, a simple and visual HBIM protocol was developed and applied in a real case study. The protocol was named BIMlegacy and it is divided into eight phases: building registration, determine intervention options, develop design for intervention, planning the physical intervention, physical intervention, handover, maintenance and culture dissemination. It contemplates all the stakeholders involved.

  12. Building Information Modeling (BIM) for Indoor Environmental Performance Analysis

    DEFF Research Database (Denmark)

    The report is a part of a research assignment carried out by students in the 5ETCS course “Project Byggeri – [entitled as: Building Information Modeling (BIM) – Modeling & Analysis]”, during the 3rd semester of master degree in Civil and Architectural Engineering, Department of Engineering, Aarhus...... University. This includes seven papers describing BIM for Sustainability, concentrating specifically on individual topics regarding to Indoor Environment Performance Analysis....

  13. 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....

  14. Mental models accurately predict emotion transitions.

    Science.gov (United States)

    Thornton, Mark A; Tamir, Diana I

    2017-06-06

    Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

  15. Mental models accurately predict emotion transitions

    Science.gov (United States)

    Thornton, Mark A.; Tamir, Diana I.

    2017-01-01

    Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

  16. 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...

  17. FIRST PRISMATIC BUILDING MODEL RECONSTRUCTION FROM TOMOSAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    Y. Sun

    2016-06-01

    Full Text Available 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.

  18. Modeling Manpower and Equipment Productivity in Tall Building Construction Projects

    Science.gov (United States)

    Mudumbai Krishnaswamy, Parthasarathy; Rajiah, Murugasan; Vasan, Ramya

    2017-12-01

    Tall building construction projects involve two critical resources of manpower and equipment. Their usage, however, widely varies due to several factors affecting their productivity. Currently, no systematic study for estimating and increasing their productivity is available. What is prevalent is the use of empirical data, experience of similar projects and assumptions. As tall building projects are here to stay and increase, to meet the emerging demands in ever shrinking urban spaces, it is imperative to explore ways and means of scientific productivity models for basic construction activities: concrete, reinforcement, formwork, block work and plastering for the input of specific resources in a mixed environment of manpower and equipment usage. Data pertaining to 72 tall building projects in India were collected and analyzed. Then, suitable productivity estimation models were developed using multiple linear regression analysis and validated using independent field data. It is hoped that the models developed in the study will be useful for quantity surveyors, cost engineers and project managers to estimate productivity of resources in tall building projects.

  19. Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

    Science.gov (United States)

    Su, X.

    2017-12-01

    A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

  20. 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...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  1. Model predictive Controller for Mobile Robot

    OpenAIRE

    Alireza Rezaee

    2017-01-01

    This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

  2. METHODS OF SELECTING THE EFFECTIVE MODELS OF BUILDINGS REPROFILING PROJECTS

    Directory of Open Access Journals (Sweden)

    Александр Иванович МЕНЕЙЛЮК

    2016-02-01

    Full Text Available The article highlights the important task of project management in reprofiling of buildings. It is expedient to pay attention to selecting effective engineering solutions to reduce the duration and cost reduction at the project management in the construction industry. This article presents a methodology for the selection of efficient organizational and technical solutions for the reconstruction of buildings reprofiling. The method is based on a compilation of project variants in the program Microsoft Project and experimental statistical analysis using the program COMPEX. The introduction of this technique in the realigning of buildings allows choosing efficient models of projects, depending on the given constraints. Also, this technique can be used for various construction projects.

  3. 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.

  4. 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

  5. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  6. Fine modeling of energy exchanges between buildings and urban atmosphere

    International Nuclear Information System (INIS)

    Daviau-Pellegrin, Noelie

    2016-01-01

    This thesis work is about the effect of buildings on the urban atmosphere and more precisely the energetic exchanges that take place between these two systems. In order to model more finely the thermal effects of buildings on the atmospheric flows in simulations run under the CFD software Code-Saturne, we proceed to couple this tool with the building model BuildSysPro. This library is run under Dymola and can generate matrices describing the building thermal properties that can be used outside this software. In order to carry out the coupling, we use these matrices in a code that allows the building thermal calculations and the CFD to exchange their results. After a review about the physical phenomena and the existing models, we explain the interactions between the atmosphere and the urban elements, especially buildings. The latter can impact the air flows dynamically, as they act as obstacles, and thermally, through their surface temperatures. At first, we analyse the data obtained from the measurement campaign EM2PAU that we use in order to validate the coupled model. EM2PAU was carried out in Nantes in 2011 and represents a canyon street with two rows of four containers. Its distinctive feature lies in the simultaneous measurements of the air and wall temperatures as well as the wind speeds with anemometers located on a 10 m-high mast for the reference wind and on six locations in the canyon. This aims for studying the thermal influence of buildings on the air flows. Then the numerical simulations of the air flows in EM2PAU is carried out with different methods that allow us to calculate or impose the surface temperature we use for each of the container walls. The first method consists in imposing their temperatures from the measurements. For each wall, we set the temperature to the surface temperature that was measured during the EM2PAU campaign. The second method involves imposing the outdoor air temperature that was measured at a given time to all the

  7. 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.

  8. NEW UPPER AND LOWER BOUNDS LINE OF SIGHT PATH LOSS MODELS FOR MOBILE PROPAGATION IN BUILDINGS

    Directory of Open Access Journals (Sweden)

    Supachai Phaiboon

    2017-11-01

    Full Text Available This paper proposes a method to predict line-of-sight (LOS path loss in buildings. We performed measurements in two different type of buildings at a frequency of 1.8 GHz and propose new upper and lower bounds path loss models which depend on max and min values of sample path loss data. This makes our models limit path loss within the boundary lines. The models include time-variant effects such as people moving and cars in parking areas with their influence on wave propagation that is very high.  The results have shown that the proposed models will be useful for the system and cell design of indoor wireless communication systems.

  9. 7 CFR Exhibit E to Subpart A of... - Voluntary National Model Building Codes

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 12 2010-01-01 2010-01-01 false Voluntary National Model Building Codes E Exhibit E... National Model Building Codes The following documents address the health and safety aspects of buildings and related structures and are voluntary national model building codes as defined in § 1924.4(h)(2) of...

  10. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  11. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  12. 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. .

  13. 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.

  14. 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.

  15. Integration of Models of Building Interiors with Cadastral Data

    Science.gov (United States)

    Gotlib, Dariusz; Karabin, Marcin

    2017-12-01

    Demands for applications which use models of building interiors is growing and highly diversified. Those models are applied at the stage of designing and construction of a building, in applications which support real estate management, in navigation and marketing systems and, finally, in crisis management and security systems. They are created on the basis of different data: architectural and construction plans, both, in the analogue form, as well as CAD files, BIM data files, by means of laser scanning (TLS) and conventional surveys. In this context the issue of searching solutions which would integrate the existing models and lead to elimination of data redundancy is becoming more important. The authors analysed the possible input- of cadastral data (legal extent of premises) at the stage of the creation and updating different models of building's interiors. The paper focuses on one issue - the way of describing the geometry of premises basing on the most popular source data, i.e. architectural and construction plans. However, the described rules may be considered as universal and also may be applied in practice concerned may be used during the process of creation and updating indoor models based on BIM dataset or laser scanning clouds

  16. 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.

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

    DEFF Research Database (Denmark)

    Mondrup, Thomas Fænø

    methodologies. Thesis studies showed that BIM approaches have the potential to improve AEC/FM communication and collaboration. BIM is by its nature multidisciplinary, bringing AEC/FM project participants together and creating constant communication. However, BIM adoption can lead to technical challenges......, 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......, for example, getting BIM-compatible tools to communicate properly. Furthermore, BIM adoption requires organizational change, that is changes in AEC/FM work practices and interpersonal dynamics. Consequently, to ensure that the adoption of BIM is successful, it is recommended that common IT regulations...

  18. Finding Furfural Hydrogenation Catalysts via Predictive Modelling.

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-09-10

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (k(H):k(D)=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R(2)=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.

  19. 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...

  20. Uncertainty analysis of pollutant build-up modelling based on a Bayesian weighted least squares approach

    International Nuclear Information System (INIS)

    Haddad, Khaled; Egodawatta, Prasanna; Rahman, Ataur; Goonetilleke, Ashantha

    2013-01-01

    Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality datasets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares regression and Bayesian weighted least squares regression for the estimation of uncertainty associated with pollutant build-up prediction using limited datasets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling. - Highlights: ► Water quality data spans short time scales leading to significant model uncertainty. ► Assessment of uncertainty essential for informed decision making in water

  1. Active buildings: modelling physical activity and movement in office buildings. An observational study protocol.

    Science.gov (United States)

    Smith, Lee; Ucci, Marcella; Marmot, Alexi; Spinney, Richard; Laskowski, Marek; Sawyer, Alexia; Konstantatou, Marina; Hamer, Mark; Ambler, Gareth; Wardle, Jane; Fisher, Abigail

    2013-11-12

    Health benefits of regular participation in physical activity are well documented but population levels are low. Office layout, and in particular the number and location of office building destinations (eg, print and meeting rooms), may influence both walking time and characteristics of sitting time. No research to date has focused on the role that the layout of the indoor office environment plays in facilitating or inhibiting step counts and characteristics of sitting time. The primary aim of this study was to investigate associations between office layout and physical activity, as well as sitting time using objective measures. Active buildings is a unique collaboration between public health, built environment and computer science researchers. The study involves objective monitoring complemented by a larger questionnaire arm. UK office buildings will be selected based on a variety of features, including office floor area and number of occupants. Questionnaires will include items on standard demographics, well-being, physical activity behaviour and putative socioecological correlates of workplace physical activity. Based on survey responses, approximately 30 participants will be recruited from each building into the objective monitoring arm. Participants will wear accelerometers (to monitor physical activity and sitting inside and outside the office) and a novel tracking device will be placed in the office (to record participant location) for five consecutive days. Data will be analysed using regression analyses, as well as novel agent-based modelling techniques. The results of this study will be disseminated through peer-reviewed publications and scientific presentations. Ethical approval was obtained through the University College London Research Ethics Committee (Reference number 4400/001).

  2. 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

  3. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  4. Model-based and model-free “plug-and-play” building energy efficient control

    International Nuclear Information System (INIS)

    Baldi, Simone; Michailidis, Iakovos; Ravanis, Christos; Kosmatopoulos, Elias B.

    2015-01-01

    Highlights: • “Plug-and-play” Building Optimization and Control (BOC) driven by building data. • Ability to handle the large-scale and complex nature of the BOC problem. • Adaptation to learn the optimal BOC policy when no building model is available. • Comparisons with rule-based and advanced BOC strategies. • Simulation and real-life experiments in a ten-office building. - Abstract: Considerable research efforts in Building Optimization and Control (BOC) have been directed toward the development of “plug-and-play” BOC systems that can achieve energy efficiency without compromising thermal comfort and without the need of qualified personnel engaged in a tedious and time-consuming manual fine-tuning phase. In this paper, we report on how a recently introduced Parametrized Cognitive Adaptive Optimization – abbreviated as PCAO – can be used toward the design of both model-based and model-free “plug-and-play” BOC systems, with minimum human effort required to accomplish the design. In the model-based case, PCAO assesses the performance of its control strategy via a simulation model of the building dynamics; in the model-free case, PCAO optimizes its control strategy without relying on any model of the building dynamics. Extensive simulation and real-life experiments performed on a 10-office building demonstrate the effectiveness of the PCAO–BOC system in providing significant energy efficiency and improved thermal comfort. The mechanisms embedded within PCAO render it capable of automatically and quickly learning an efficient BOC strategy either in the presence of complex nonlinear simulation models of the building dynamics (model-based) or when no model for the building dynamics is available (model-free). Comparative studies with alternative state-of-the-art BOC systems show the effectiveness of the PCAO–BOC solution

  5. Comparative Study of Bancruptcy Prediction Models

    Directory of Open Access Journals (Sweden)

    Isye Arieshanti

    2013-09-01

    Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

  6. 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

  7. An expandable software model for collaborative decision making during the whole building life cycle

    International Nuclear Information System (INIS)

    Papamichael, K.; Pal, V.; Bourassa, N.; Loffeld, J.; Capeluto, G.

    2000-01-01

    Decisions throughout the life cycle of a building, from design through construction and commissioning to operation and demolition, require the involvement of multiple interested parties (e.g., architects, engineers, owners, occupants and facility managers). The performance of alternative designs and courses of action must be assessed with respect to multiple performance criteria, such as comfort, aesthetics, energy, cost and environmental impact. Several stand-alone computer tools are currently available that address specific performance issues during various stages of a building's life cycle. Some of these tools support collaboration by providing means for synchronous and asynchronous communications, performance simulations, and monitoring of a variety of performance parameters involved in decisions about a building during building operation. However, these tools are not linked in any way, so significant work is required to maintain and distribute information to all parties. In this paper we describe a software model that provides the data management and process control required for collaborative decision making throughout a building's life cycle. The requirements for the model are delineated addressing data and process needs for decision making at different stages of a building's life cycle. The software model meets these requirements and allows addition of any number of processes and support databases over time. What makes the model infinitely expandable is that it is a very generic conceptualization (or abstraction) of processes as relations among data. The software model supports multiple concurrent users, and facilitates discussion and debate leading to decision making. The software allows users to define rules and functions for automating tasks and alerting all participants to issues that need attention. It supports management of simulated as well as real data and continuously generates information useful for improving performance prediction and

  8. 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.

  9. Building 235-F Goldsim Fate And Transport Model

    International Nuclear Information System (INIS)

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

    2012-01-01

    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 and 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 ρCi/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 ρCi/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

  10. Air Dispersion Modeling for Building 3026C/D Demolition

    Energy Technology Data Exchange (ETDEWEB)

    Ward, Richard C [ORNL; Sjoreen, Andrea L [ORNL; Eckerman, Keith F [ORNL

    2010-06-01

    This report presents estimates of dispersion coefficients and effective dose for potential air dispersion scenarios of uncontrolled releases from Oak Ridge National Laboratory (ORNL) buildings 3026C, 3026D, and 3140 prior to or during the demolition of the 3026 Complex. The Environmental Protection Agency (EPA) AERMOD system1-6 was used to compute these estimates. AERMOD stands for AERMIC Model, where AERMIC is the American Meteorological Society-EPA Regulatory Model Improvement Committee. Five source locations (three in building 3026D and one each in building 3026C and the filter house 3140) and associated source characteristics were determined with the customer. In addition, the area of study was determined and building footprints and intake locations of air-handling systems were obtained. In addition to the air intakes, receptor sites consisting of ground level locations on four polar grids (50 m, 100 m, 200 m, and 500 m) and two intersecting lines of points (50 m separation), corresponding to sidewalks along Central Avenue and Fifth Street. Three years of meteorological data (2006 2008) were used each consisting of three datasets: 1) National Weather Service data; 2) upper air data for the Knoxville-Oak Ridge area; and 3) local weather data from Tower C (10 m, 30 m and 100 m) on the ORNL reservation. Annual average air concentration, highest 1 h average and highest 3 h average air concentrations were computed using AERMOD for the five source locations for the three years of meteorological data. The highest 1 h average air concentrations were converted to dispersion coefficients to characterize the atmospheric dispersion as the customer was interested in the most significant response and the highest 1 h average data reflects the best time-averaged values available from the AERMOD code. Results are presented in tabular and graphical form. The results for dose were obtained using radionuclide activities for each of the buildings provided by the customer.7

  11. eTOXlab, an open source modeling framework for implementing predictive models in production environments.

    Science.gov (United States)

    Carrió, Pau; López, Oriol; Sanz, Ferran; Pastor, Manuel

    2015-01-01

    Computational models based in Quantitative-Structure Activity Relationship (QSAR) methodologies are widely used tools for predicting the biological properties of new compounds. In many instances, such models are used as a routine in the industry (e.g. food, cosmetic or pharmaceutical industry) for the early assessment of the biological properties of new compounds. However, most of the tools currently available for developing QSAR models are not well suited for supporting the whole QSAR model life cycle in production environments. We have developed eTOXlab; an open source modeling framework designed to be used at the core of a self-contained virtual machine that can be easily deployed in production environments, providing predictions as web services. eTOXlab consists on a collection of object-oriented Python modules with methods mapping common tasks of standard modeling workflows. This framework allows building and validating QSAR models as well as predicting the properties of new compounds using either a command line interface or a graphic user interface (GUI). Simple models can be easily generated by setting a few parameters, while more complex models can be implemented by overriding pieces of the original source code. eTOXlab benefits from the object-oriented capabilities of Python for providing high flexibility: any model implemented using eTOXlab inherits the features implemented in the parent model, like common tools and services or the automatic exposure of the models as prediction web services. The particular eTOXlab architecture as a self-contained, portable prediction engine allows building models with confidential information within corporate facilities, which can be safely exported and used for prediction without disclosing the structures of the training series. The software presented here provides full support to the specific needs of users that want to develop, use and maintain predictive models in corporate environments. The technologies used by e

  12. Heterotic SO(32) model building in four dimensions

    International Nuclear Information System (INIS)

    Choi, K.S.; Groot Nibbelink, S.; Minnesota Univ., Minneapolis, MN; Trapletti, M.

    2004-10-01

    Four dimensional heterotic SO(32) orbifold models are classified systematically with model building applications in mind. We obtain all Z 3 , Z 7 and Z 2N models based on vectorial gauge shifts. The resulting gauge groups are reminiscent of those of type-I model building, as they always take the form SO(2n 0 ) x U(n 1 ) x.. x U(n N-1 ) x SO(2n N ). The complete twisted spectrum is determined simultaneously for all orbifold models in a parametric way depending on n 0 ,.., n N , rather than on a model by model basis. This reveals interesting patterns in the twisted states: They are always built out of vectors and anti-symmetric tensors of the U(n) groups, and either vectors or spinors of the SO(2n) groups. Our results may shed additional light on the S-duality between heterotic and type-I strings in four dimensions. As a spin-off we obtain an SO(10) GUT model with four generations from the Z 4 orbifold. (orig.)

  13. 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.

  14. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

  15. FINDING CUBOID-BASED BUILDING MODELS IN POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    W. Nguatem

    2012-07-01

    Full Text Available In this paper, we present an automatic approach for the derivation of 3D building models of level-of-detail 1 (LOD 1 from point clouds obtained from (dense image matching or, for comparison only, from LIDAR. Our approach makes use of the predominance of vertical structures and orthogonal intersections in architectural scenes. After robustly determining the scene's vertical direction based on the 3D points we use it as constraint for a RANSAC-based search for vertical planes in the point cloud. The planes are further analyzed to segment reliable outlines for rectangular surface within these planes, which are connected to construct cuboid-based building models. We demonstrate that our approach is robust and effective over a range of real-world input data sets with varying point density, amount of noise, and outliers.

  16. 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)

  17. 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)

  18. 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

  19. 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.

  20. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2011-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  1. A new, accurate predictive model for incident hypertension.

    Science.gov (United States)

    Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K

    2013-11-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures. The primary study population consisted of 1605 normotensive individuals aged 20-79 years with 5-year follow-up from the population-based study, that is the Study of Health in Pomerania (SHIP). The initial set was randomly split into a training and a testing set. We used a probabilistic graphical model applying a Bayesian network to create a predictive model for incident hypertension and compared the predictive performance with the established Framingham risk score for hypertension. Finally, the model was validated in 2887 participants from INTER99, a Danish community-based intervention study. In the training set of SHIP data, the Bayesian network used a small subset of relevant baseline features including age, mean arterial pressure, rs16998073, serum glucose and urinary albumin concentrations. Furthermore, we detected relevant interactions between age and serum glucose as well as between rs16998073 and urinary albumin concentrations [area under the receiver operating characteristic (AUC 0.76)]. The model was confirmed in the SHIP validation set (AUC 0.78) and externally replicated in INTER99 (AUC 0.77). Compared to the established Framingham risk score for hypertension, the predictive performance of the new model was similar in the SHIP validation set and moderately better in INTER99. Data mining procedures identified a predictive model for incident hypertension, which included innovative and easy-to-measure variables. The findings promise great applicability in screening settings and clinical practice.

  2. BUILDING NEW BUSINESS MODELS FOR SUSTAINABLE GROWTH AND DEVELOPMENT

    OpenAIRE

    Taco C. R. van Someren; Shuhua van Someren-Wang

    2011-01-01

    Considered are issues of methodology and methods, as well as ideology of strategic innovation. Using the tools of this approach is offered as mechanisms to develop and build business models for sustainable socio-economic economic growth and development of different regions. The connection between key problems of sustainable development and management policy of different economic entities is studied. The consultancy company Ynnovate’s experience in addressing these issues in the EU and China i...

  3. BUILDING INFORMATION MODELS FOR MONITORING AND SIMULATION DATA IN HERITAGE BUILDINGS

    Directory of Open Access Journals (Sweden)

    D. P. Pocobelli

    2018-05-01

    Full Text Available This paper analyses the use of BIM in heritage buildings, assessing the state-of-the-art and finding paths for further development. Specifically, this work is part of a broader project, which final aim is to support stakeholders through BIM. Given that humidity is one of the major causes of weathering, being able to detect, depict and forecast it, is a key task. A BIM model of a heritage building – enhanced with the integration of a weathering forecasting model – will be able to give detailed information on possible degradation patterns, and when they will happen. This information can be effectively used to plan both ordinary and extraordinary maintenance. The Jewel Tower in London, our case study, is digitised using combined laser scanning and photogrammetry, and a virtual model is produced. The point cloud derived from combined laser scanning & photogrammetry is traced out in with Autodesk Revit, where the main volumetry (gross walls and floors is created with parametric objects. Surface characterisation of the façade is given through renderings. Specifically, new rendering materials have been created for this purpose, based on rectified photos of the Tower. The model is then integrated with moisture data, organised in spreadsheets and linked to it via parametric objects representing the points where measurements had been previously taken. The spatial distribution of moisture is then depicted using Dynamo. This simple exercise demonstrates the potential Dynamo has for condition reporting, and future work will concentrate on the creation of a complex forecasting model to be linked through it.

  4. Model building strategy for logistic regression: purposeful selection.

    Science.gov (United States)

    Zhang, Zhongheng

    2016-03-01

    Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

  5. Building and testing models with extended Higgs sectors

    Science.gov (United States)

    Ivanov, Igor P.

    2017-07-01

    Models with non-minimal Higgs sectors represent a mainstream direction in theoretical exploration of physics opportunities beyond the Standard Model. Extended scalar sectors help alleviate difficulties of the Standard Model and lead to a rich spectrum of characteristic collider signatures and astroparticle consequences. In this review, we introduce the reader to the world of extended Higgs sectors. Not pretending to exhaustively cover the entire body of literature, we walk through a selection of the most popular examples: the two- and multi-Higgs-doublet models, as well as singlet and triplet extensions. We will show how one typically builds models with extended Higgs sectors, describe the main goals and the challenges which arise on the way, and mention some methods to overcome them. We will also describe how such models can be tested, what are the key observables one focuses on, and illustrate the general strategy with a subjective selection of results.

  6. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  7. Guidelines for developing efficient thermal conduction and storage models within building energy simulations

    International Nuclear Information System (INIS)

    Hillary, Jason; Walsh, Ed; Shah, Amip; Zhou, Rongliang; Walsh, Pat

    2017-01-01

    Improving building energy efficiency is of paramount importance due to the large proportion of energy consumed by thermal operations. Consequently, simulating a building's environment has gained popularity for assessing thermal comfort and design. The extended timeframes and large physical scales involved necessitate compact modelling approaches. The accuracy of such simulations is of chief concern, yet there is little guidance offered on achieving accurate solutions whilst mitigating prohibitive computational costs. Therefore, the present study addresses this deficit by providing clear guidance on discretisation levels required for achieving accurate but computationally inexpensive models. This is achieved by comparing numerical models of varying discretisation levels to benchmark analytical solutions with prediction accuracy assessed and reported in terms of governing dimensionless parameters, Biot and Fourier numbers, to ensure generality of findings. Furthermore, spatial and temporal discretisation errors are separated and assessed independently. Contour plots are presented to intuitively determine the optimal discretisation levels and time-steps required to achieve accurate thermal response predictions. Simulations derived from these contour plots were tested against various building conditions with excellent agreement observed throughout. Additionally, various scenarios are highlighted where the classical single lumped capacitance model can be applied for Biot numbers much greater than 0.1 without reducing accuracy. - Highlights: • Addressing the problems of inadequate discretisation within building energy models. • Accuracy of numerical models assessed against analytical solutions. • Fourier and Biot numbers used to provide generality of results for any material. • Contour plots offer intuitive way to interpret results for manual discretisation. • Results show proposed technique promising for automation of discretisation process.

  8. 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…

  9. 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. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. 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.

  11. Alcator C-Mod predictive modeling

    International Nuclear Information System (INIS)

    Pankin, Alexei; Bateman, Glenn; Kritz, Arnold; Greenwald, Martin; Snipes, Joseph; Fredian, Thomas

    2001-01-01

    Predictive simulations for the Alcator C-mod tokamak [I. Hutchinson et al., Phys. Plasmas 1, 1511 (1994)] are carried out using the BALDUR integrated modeling code [C. E. Singer et al., Comput. Phys. Commun. 49, 275 (1988)]. The results are obtained for temperature and density profiles using the Multi-Mode transport model [G. Bateman et al., Phys. Plasmas 5, 1793 (1998)] as well as the mixed-Bohm/gyro-Bohm transport model [M. Erba et al., Plasma Phys. Controlled Fusion 39, 261 (1997)]. The simulated discharges are characterized by very high plasma density in both low and high modes of confinement. The predicted profiles for each of the transport models match the experimental data about equally well in spite of the fact that the two models have different dimensionless scalings. Average relative rms deviations are less than 8% for the electron density profiles and 16% for the electron and ion temperature profiles

  12. Building a three-dimensional model of CYP2C9 inhibition using the Autocorrelator: an autonomous model generator.

    Science.gov (United States)

    Lardy, Matthew A; Lebrun, Laurie; Bullard, Drew; Kissinger, Charles; Gobbi, Alberto

    2012-05-25

    In modern day drug discovery campaigns, computational chemists have to be concerned not only about improving the potency of molecules but also reducing any off-target ADMET activity. There are a plethora of antitargets that computational chemists may have to consider. Fortunately many antitargets have crystal structures deposited in the PDB. These structures are immediately useful to our Autocorrelator: an automated model generator that optimizes variables for building computational models. This paper describes the use of the Autocorrelator to construct high quality docking models for cytochrome P450 2C9 (CYP2C9) from two publicly available crystal structures. Both models result in strong correlation coefficients (R² > 0.66) between the predicted and experimental determined log(IC₅₀) values. Results from the two models overlap well with each other, converging on the same scoring function, deprotonated charge state, and predicted the binding orientation for our collection of molecules.

  13. Building Modelling Methodologies for Virtual District Heating and Cooling Networks

    Energy Technology Data Exchange (ETDEWEB)

    Saurav, Kumar; Choudhury, Anamitra R.; Chandan, Vikas; Lingman, Peter; Linder, Nicklas

    2017-10-26

    District heating and cooling systems (DHC) are a proven energy solution that has been deployed for many years in a growing number of urban areas worldwide. They comprise a variety of technologies that seek to develop synergies between the production and supply of heat, cooling, domestic hot water and electricity. Although the benefits of DHC systems are significant and have been widely acclaimed, yet the full potential of modern DHC systems remains largely untapped. There are several opportunities for development of energy efficient DHC systems, which will enable the effective exploitation of alternative renewable resources, waste heat recovery, etc., in order to increase the overall efficiency and facilitate the transition towards the next generation of DHC systems. This motivated the need for modelling these complex systems. Large-scale modelling of DHC-networks is challenging, as it has several components interacting with each other. In this paper we present two building methodologies to model the consumer buildings. These models will be further integrated with network model and the control system layer to create a virtual test bed for the entire DHC system. The model is validated using data collected from a real life DHC system located at Lulea, a city on the coast of northern Sweden. The test bed will be then used for simulating various test cases such as peak energy reduction, overall demand reduction etc.

  14. Toward Accessing Spatial Structure from Building Information Models

    Science.gov (United States)

    Schultz, C.; Bhatt, M.

    2011-08-01

    Data about building designs and layouts is becoming increasingly more readily available. In the near future, service personal (such as maintenance staff or emergency rescue workers) arriving at a building site will have immediate real-time access to enormous amounts of data relating to structural properties, utilities, materials, temperature, and so on. The critical problem for users is the taxing and error prone task of interpreting such a large body of facts in order to extract salient information. This is necessary for comprehending a situation and deciding on a plan of action, and is a particularly serious issue in time-critical and safety-critical activities such as firefighting. Current unifying building models such as the Industry Foundation Classes (IFC), while being comprehensive, do not directly provide data structures that focus on spatial reasoning and spatial modalities that are required for high-level analytical tasks. The aim of the research presented in this paper is to provide computational tools for higher level querying and reasoning that shift the cognitive burden of dealing with enormous amounts of data away from the user. The user can then spend more energy and time in planning and decision making in order to accomplish the tasks at hand. We present an overview of our framework that provides users with an enhanced model of "built-up space". In order to test our approach using realistic design data (in terms of both scale and the nature of the building models) we describe how our system interfaces with IFC, and we conduct timing experiments to determine the practicality of our approach. We discuss general computational approaches for deriving higher-level spatial modalities by focusing on the example of route graphs. Finally, we present a firefighting scenario with alternative route graphs to motivate the application of our framework.

  15. Model building in the free-fermionic formulation of superstrings

    International Nuclear Information System (INIS)

    Dreiner, H.K.

    1989-01-01

    In this thesis the author presents results in the free fermionic formulation of string theory in four space-time dimensions as presented by I. Antoniadis and C. Bachas. First he discusses how to build N = 1 space-time supersymmetric models. He also uses the low-energy requirements of N = 1 space-time supersymmetry as well as chiral space-time fermions to show that the spectrum does not contain any massless scalar fields which transform under the adjoint representation of the gauge group. He also discusses the consequences of these results for model building efforts. In Chapter 1 and 2 he introduces the concepts of string theory as well as the notation which he will be using throughout the following chapters. In Chapter 3 he reviews the free fermionic formulation of string theory as presented by [AB] including the rules for model building. He first classifies all the possible single boundary conditions for the free fermionic fields in the theory and then classifies the cases for which two or more distinct boundary conditions are compatible. In Chapter 4 he uses the rules from Chapter 3 to construct several toy models, which show what possible gauge groups can arise in the theory and how they can be constructed. In Chapter 5 he uses the classification of the boundary conditions for the fermionic fields to classify all the models with N = 4 spacetime supersymmetry. He then discusses the different possibilities to obtain models with N = 2, 1, and 0 spacetime supersymmetry. He shows that the requirement of N = 1 spacetime supersymmetry severely restricts the allowed constructions of the world-sheet supercharge. In Chapter 6 he proves, using the requirement of N = 1 space-time supersymmetry, that the spectrum does not contain any massless scalar fields transforming as the adjoint representation of the gauge group

  16. Building information modeling in the architectural design phases

    DEFF Research Database (Denmark)

    Hermund, Anders

    2009-01-01

    The overall economical benefits of Building Information Modeling are generally comprehensible, but are there other problems with the implementation of BIM as a formulized system in a field that ultimately is dependant on a creative input? Is optimization and economic benefit really contributing...... with an architectural quality? In Denmark the implementation of the digital working methods related to BIM has been introduced by government law in 2007. Will the important role of the architect as designer change in accordance with these new methods, and does the idea of one big integrated model represent a paradox...... in relation to designing? The BIM mindset requires changes on many levels....

  17. Modeling of electromigration salt removal methods in building materials

    DEFF Research Database (Denmark)

    Johannesson, Björn; Ottosen, Lisbeth M.

    2008-01-01

    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...... with its ionic mobility properties. It is, further, assumed that Gauss’s law can be used to calculate the internal electrical field induced by the diffusion it self. In this manner the external electrical field applied can be modeled, simply, by assigning proper boundary conditions for the equation...

  18. Prediction models and control algorithms for predictive applications of setback temperature in cooling systems

    International Nuclear Information System (INIS)

    Moon, Jin Woo; Yoon, Younju; Jeon, Young-Hoon; Kim, Sooyoung

    2017-01-01

    Highlights: • Initial ANN model was developed for predicting the time to the setback temperature. • Initial model was optimized for producing accurate output. • Optimized model proved its prediction accuracy. • ANN-based algorithms were developed and tested their performance. • ANN-based algorithms presented superior thermal comfort or energy efficiency. - Abstract: In this study, a temperature control algorithm was developed to apply a setback temperature predictively for the cooling system of a residential building during occupied periods by residents. An artificial neural network (ANN) model was developed to determine the required time for increasing the current indoor temperature to the setback temperature. This study involved three phases: development of the initial ANN-based prediction model, optimization and testing of the initial model, and development and testing of three control algorithms. The development and performance testing of the model and algorithm were conducted using TRNSYS and MATLAB. Through the development and optimization process, the final ANN model employed indoor temperature and the temperature difference between the current and target setback temperature as two input neurons. The optimal number of hidden layers, number of neurons, learning rate, and moment were determined to be 4, 9, 0.6, and 0.9, respectively. The tangent–sigmoid and pure-linear transfer function was used in the hidden and output neurons, respectively. The ANN model used 100 training data sets with sliding-window method for data management. Levenberg-Marquart training method was employed for model training. The optimized model had a prediction accuracy of 0.9097 root mean square errors when compared with the simulated results. Employing the ANN model, ANN-based algorithms maintained indoor temperatures better within target ranges. Compared to the conventional algorithm, the ANN-based algorithms reduced the duration of time, in which the indoor temperature

  19. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    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.

  20. Software Tools For Building Decision-support Models For Flood Emergency Situations

    Science.gov (United States)

    Garrote, L.; Molina, M.; Ruiz, J. M.; Mosquera, J. C.

    The SAIDA decision-support system was developed by the Spanish Ministry of the Environment to provide assistance to decision-makers during flood situations. SAIDA has been tentatively implemented in two test basins: Jucar and Guadalhorce, and the Ministry is currently planning to have it implemented in all major Spanish basins in a few years' time. During the development cycle of SAIDA, the need for providing as- sistance to end-users in model definition and calibration was clearly identified. System developers usually emphasise abstraction and generality with the goal of providing a versatile software environment. End users, on the other hand, require concretion and specificity to adapt the general model to their local basins. As decision-support models become more complex, the gap between model developers and users gets wider: Who takes care of model definition, calibration and validation?. Initially, model developers perform these tasks, but the scope is usually limited to a few small test basins. Before the model enters operational stage, end users must get involved in model construction and calibration, in order to gain confidence in the model recommendations. However, getting the users involved in these activities is a difficult task. The goal of this re- search is to develop representation techniques for simulation and management models in order to define, develop and validate a mechanism, supported by a software envi- ronment, oriented to provide assistance to the end-user in building decision models for the prediction and management of river floods in real time. The system is based on three main building blocks: A library of simulators of the physical system, an editor to assist the user in building simulation models, and a machine learning method to calibrate decision models based on the simulation models provided by the user.