<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaodong Xu</style></author><author><style face="normal" font="default" size="100%">Yifan Wu</style></author><author><style face="normal" font="default" size="100%">Wei Wang</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Ning Xu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China</style></title><secondary-title><style face="normal" font="default" size="100%">Building Simulation</style></secondary-title><short-title><style face="normal" font="default" size="100%">Build. Simul.</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://link.springer.com/10.1007/s12273-019-0510-zhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/article/10.1007/s12273-019-0510-z/fulltext.html</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">411 - 424</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Urbanization has led to changes in urban morphology and climate, while urban open space has become an important ecological factor for evaluating the performance of urban development. This study presents an optimization approach using computational performance simulation. With a genetic algorithm using the Grasshopper tool, this study analyzed the layout and configuration of urban open space and its impact on the urban micro-climate under summer and winter conditions. The outdoor mean Universal Thermal Climate Index (UTCI) was applied as the performance indicator for evaluating the quality of the urban micro-climate. Two cases—one testbed and one real urban block in Nanjing, China—were used to validate the computer-aided simulation process. The optimization results in the testbed showed UTCI values varied from 36.5 to 37.3 °C in summer and from −4.9 to −1.9 °C in winter. In the case of the real urban block, optimization results show, for summer, although the average UTCI value increased by 0.6 °C, the average air velocity increased by 0.2 m/s; while in winter, the average UTCI value increased by 1.7 °C and the average air velocity decreased by 0.2 m/s. These results demonstrate that the proposed computer-aided optimization process can improve the thermal comfort conditions of open space in urban blocks. Finally, this study discusses strategies and guidelines for the layout design of urban open space to improve urban environment comfort.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Blum</style></author><author><style face="normal" font="default" size="100%">K. Arendt</style></author><author><style face="normal" font="default" size="100%">Lisa Rivalin</style></author><author><style face="normal" font="default" size="100%">Mary Ann Piette</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">C.T. Veje</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Energy</style></secondary-title><short-title><style face="normal" font="default" size="100%">Applied Energy</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">hvac</style></keyword><keyword><style  face="normal" font="default" size="100%">Model predictive control</style></keyword><keyword><style  face="normal" font="default" size="100%">System identification</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://linkinghub.elsevier.com/retrieve/pii/S0306261918318099https://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/plain</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">236</style></volume><pages><style face="normal" font="default" size="100%">410 - 425</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to the significant effort required to configure and calibrate the model used in the MPC controller. While many studies have focused on methods to expedite model configuration and improve model accuracy, few have studied the impact a wide range of factors have on the accuracy of the resulting model. In addition, few have continued on to analyze these factors&#039; impact on MPC controller performance in terms of final operating costs. Therefore, this study first identifies the practical factors affecting model setup, specifically focusing on the thermal envelope. The seven that are identified are building design, model structure, model order, data set, data quality, identification algorithm and initial guesses, and software tool-chain. Then, through a large number of trials, it analyzes each factor&#039;s influence on model accuracy, focusing on grey-box models for a single zone building envelope. Finally, this study implements a subset of the models identified with these factor variations in heating, ventilating, and air conditioning MPC controllers, and tests them in simulation of a representative case that aims to optimally cool a single-zone building with time-varying electricity prices. It is found that a difference of up to 20% in cooling cost for the cases studied can occur between the best performing model and the worst performing model. The primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zhe Wang</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Mary Ann Piette</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Predicting plug loads with occupant count data through a deep learning approach</style></title><secondary-title><style face="normal" font="default" size="100%">Energy</style></secondary-title><short-title><style face="normal" font="default" size="100%">Energy</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">deep learning</style></keyword><keyword><style  face="normal" font="default" size="100%">Long short term memory network</style></keyword><keyword><style  face="normal" font="default" size="100%">Occupant count</style></keyword><keyword><style  face="normal" font="default" size="100%">Plug loads</style></keyword><keyword><style  face="normal" font="default" size="100%">prediction</style></keyword><keyword><style  face="normal" font="default" size="100%">Predictive control</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://linkinghub.elsevier.com/retrieve/pii/S0360544219310205</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">181</style></volume><pages><style face="normal" font="default" size="100%">29 - 42</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Predictive control has gained increasing attention for its ability to reduce energy consumption and improve occupant comfort in buildings. The plug loads prediction is a key component for the predictive building controls, as plug loads is a major source of internal heat gains in buildings. This study proposed a novel method to apply the Long-Short-Term-Memory (LSTM) Network, a special form of Recurrent Neural Network, to predict plug loads. The occupant count and the time have been confirmed to drive the plug load profile and thus selected as the features for the plug load prediction. The LSTM network was trained and tested with ground truth occupant count data collected from a real office building in Berkeley, California. Results from the LSTM network markedly improve the prediction accuracy compared with traditional linear regression methods and the classical Artificial Neural Network. 95% of 1-h predictions from LSTM network are within ±1 kW of the actual plug loads, given the average plug loads during the office hour is 8.6 kW. The CV(RMSE) of the predicted plug load is 11% for the next hour, and 20% for the next 8 h. Lastly, we compared four prediction approaches with the office building we monitored: LSTM vs. ARIMA, with occupant counts vs. without occupant counts. It was found, the prediction error of the LSTM approach is around 4% less than the ARIMA approach. Using occupant counts as an exogenous input could further reduce the prediction error by 5%–6%. The findings of this paper could shed light on the plug load prediction for building control optimizations such as model-predictive control.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Blum</style></author><author><style face="normal" font="default" size="100%">Filip Jorissen</style></author><author><style face="normal" font="default" size="100%">Sen Huang</style></author><author><style face="normal" font="default" size="100%">Yan Chen</style></author><author><style face="normal" font="default" size="100%">Javier Arroyo</style></author><author><style face="normal" font="default" size="100%">Kyle Benne</style></author><author><style face="normal" font="default" size="100%">Yanfei Li</style></author><author><style face="normal" font="default" size="100%">Valentin Gavan</style></author><author><style face="normal" font="default" size="100%">Lisa Rivalin</style></author><author><style face="normal" font="default" size="100%">Lieve Helsen</style></author><author><style face="normal" font="default" size="100%">Draguna Vrabie</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Marina Sofos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">IBPSA Building Simulation 2019</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">building simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Model predictive control</style></keyword><keyword><style  face="normal" font="default" size="100%">software development</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><pub-location><style face="normal" font="default" size="100%">Rome, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiaodong Xu</style></author><author><style face="normal" font="default" size="100%">Fenlan Luo</style></author><author><style face="normal" font="default" size="100%">Wei Wang</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Xiuzhang Fu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance-Based Evaluation of Courtyard Design in China’s Cold-Winter Hot-Summer Climate Regions</style></title><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title><short-title><style face="normal" font="default" size="100%">Sustainability</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">aspect ratio</style></keyword><keyword><style  face="normal" font="default" size="100%">courtyard design</style></keyword><keyword><style  face="normal" font="default" size="100%">ecological buffer area</style></keyword><keyword><style  face="normal" font="default" size="100%">ecological effect</style></keyword><keyword><style  face="normal" font="default" size="100%">layout</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2071-1050/10/11/3950http://www.mdpi.com/2071-1050/10/11/3950/pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">3950</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Evaluates the performance of the traditional courtyard design of the Jiangnan Museum, located in Jiangsu Province. In the evaluation, the spatial layout of courtyards is adjusted, the aspect ratio is changed, and an ecological buffer space is created. To model and evaluate the performance of the courtyard design, this study applied the Computational fluid dynamics (CFD) software, Parabolic Hyperbolic Or Elliptic Numerical Integration Code Series (PHOENICS), for wind environment simulation, and the EnergyPlus-based software, DesignBuilder, for energy simulation. Results show that a good combination of courtyard layout and aspect ratio can improve the use of natural ventilation by increasing free cooling during hot summers and reducing cold wind in winters. The results also show that ecological buffer areas of a courtyard can reduce cooling loads in summer by approximately 19.6% and heating loads in winter by approximately 22.3%. The study provides insights into the optimal design of a courtyard to maximize its benefit in regulating the microclimate during both winter and summer.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xuan Luo</style></author><author><style face="normal" font="default" size="100%">Khee Poh Lam</style></author><author><style face="normal" font="default" size="100%">Yixing Chen</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance Evaluation of an Agent-based Occupancy Simulation Model</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">model performance evaluation</style></keyword><keyword><style  face="normal" font="default" size="100%">occupancy pattern</style></keyword><keyword><style  face="normal" font="default" size="100%">Occupancy simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">occupant behavior</style></keyword><keyword><style  face="normal" font="default" size="100%">occupant presence and movement</style></keyword><keyword><style  face="normal" font="default" size="100%">verification</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2017</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">115</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peng Xue</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Bing Dong</style></author><author><style face="normal" font="default" size="100%">Cheuk Ming Mak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Preliminary Investigation of Water Usage Behavior in Single-Family Homes</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">daily water use</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Analytics</style></keyword><keyword><style  face="normal" font="default" size="100%">occupant behavior</style></keyword><keyword><style  face="normal" font="default" size="100%">residential water consumption</style></keyword><keyword><style  face="normal" font="default" size="100%">Water usage behavior</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU &lt;em&gt;per household&lt;/em&gt; and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU &lt;em&gt;per capita.&lt;/em&gt; Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs.&lt;/p&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kaiyu Sun</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Sarah C. Taylor-Lange</style></author><author><style face="normal" font="default" size="100%">Mary Ann Piette</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A pattern-based automated approach to building energy model calibration</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Building model calibration is critical in bringing simulated energy use closer to the actual consumption. This paper presents a novel, automated model calibration approach that uses logic linking parameter tuning with bias pattern recognition to overcome some of the disadvantages associated with traditional calibration processes. The pattern-based process contains four key steps: (1) running the original precalibrated energy model to obtain monthly simulated electricity and gas use; (2) establishing a pattern bias, either Universal or Seasonal Bias, by comparing load shape patterns of simulated and actual monthly energy use; (3) using programmed logic to select which parameter to tune first based on bias pattern, weather and input parameter interactions; and (4) automatically tuning the calibration parameters and checking the progress using pattern-fit criteria. The automated calibration algorithm was implemented in the Commercial Building Energy Saver, a web-based building energy retrofit analysis toolkit. The proof of success of the methodology was demonstrated using a case study of an office building located in San Francisco. The case study inputs included the monthly electricity bill, monthly gas bill, original building model and weather data with outputs resulting in a calibrated model that more closely matched that of the actual building energy use profile. The novelty of the developed calibration methodology lies in linking parameter tuning with the underlying logic associated with bias pattern identification. Although there are some limitations to this approach, the pattern-based automated calibration methodology can be universally adopted as an alternative to manual or hierarchical calibration approaches.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-1004495</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Mingsheng Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prevention of Compressor Short Cycling in Direct-Expansion (DX) Rooftop Units, Part 1: Theoretical Analysis and Simulation</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><volume><style face="normal" font="default" size="100%">117</style></volume><pages><style face="normal" font="default" size="100%">666-676</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Mingsheng Liu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prevention of Compressor Short Cycling in Direct-Expansion (DX) Rooftop Units— Part 2: Field Investigation</style></title><secondary-title><style face="normal" font="default" size="100%">ASHRAE Transactions</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><volume><style face="normal" font="default" size="100%">117</style></volume><pages><style face="normal" font="default" size="100%">677-685</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Paul Mara</style></author><author><style face="normal" font="default" size="100%">Declan O&#039;Sullivan</style></author><author><style face="normal" font="default" size="100%">Rob Brennan</style></author><author><style face="normal" font="default" size="100%">Marcus Keane</style></author><author><style face="normal" font="default" size="100%">Kris McGlinn</style></author><author><style face="normal" font="default" size="100%">James O&#039;Donnell</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pervasive Knowledge-Based Networking for Maintenance Inspection in Smart Buildings</style></title><secondary-title><style face="normal" font="default" size="100%">MUCS 2009: 6th IEEE International Workshop on Managing Ubiquitous Communications and Services</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><pub-location><style face="normal" font="default" size="100%">Barcelona, Spain</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pierre Hollmuller</style></author><author><style face="normal" font="default" size="100%">Joyce Carlo</style></author><author><style face="normal" font="default" size="100%">Martin Ordenes</style></author><author><style face="normal" font="default" size="100%">Fernando Westphal</style></author><author><style face="normal" font="default" size="100%">Roberto Lamberts</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Potential of Buried Pipes Systems and Derived Techniques for Passive Cooling of Buildings in Brazilian Climates</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. Building Simulation 2007</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Beijing, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jaya Mukhopadhyay</style></author><author><style face="normal" font="default" size="100%">Jeff S. Haberl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance of High-Performance Glazing in IECC Compliant Building Simulation Model (DOE-2)</style></title><secondary-title><style face="normal" font="default" size="100%">SimBuild 2006</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Cambridge, MA, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Elijah Polak</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Precision control for generalized pattern search algorithms with adaptive precision function evaluations</style></title><secondary-title><style face="normal" font="default" size="100%">SIAM Journal on Optimization</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">650-669 </style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to include a subprocedure that adaptively controls the precision of the approximating cost functions. The numerical approximations to the cost function need not define a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. We show by numerical experiments that such an approach leads to substantial time savings in minimizing computationally expensive functions.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Etienne Wurtz</style></author><author><style face="normal" font="default" size="100%">Chadi Maalouf</style></author><author><style face="normal" font="default" size="100%">Laurent Mora</style></author><author><style face="normal" font="default" size="100%">Francis Allard</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Parametric Analysis of a Solar Desiccant Cooling System using the SimSPARK Environment</style></title><secondary-title><style face="normal" font="default" size="100%">IBPSA Building Simulation 2005</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2005</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Montreal, Canada</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peng Xu</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Mary Ann Piette</style></author><author><style face="normal" font="default" size="100%">James E. Braun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Peak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building</style></title><secondary-title><style face="normal" font="default" size="100%">2004 ACEEE Summer Study on Energy Efficiency in Buildings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">demand shifting (pre-cooling)</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2004</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Pacific Grove, CA</style></pub-location><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft&lt;sup&gt;2&lt;/sup&gt; office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1 - 2.3 W/ft&lt;sup&gt;2&lt;/sup&gt;) during normal peak hours from 2 - 5 pm, without causing any thermal comfort complaints. The effects on the demand from 2 - 5 pm of the inclusion of pre-cooling prior to occupancy are unclear.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-55800</style></custom2></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brent T. Griffith</style></author><author><style face="normal" font="default" size="100%">Peter G. Ellis</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Photovoltaic and Solar Thermal Modeling with the EnergyPlus Calculation Engine</style></title><secondary-title><style face="normal" font="default" size="100%">World Renewable Energy Congress VIII and Expo</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2004</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Denver, Colorado, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Yi Jiang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of building thermal performance under random conditions</style></title><secondary-title><style face="normal" font="default" size="100%">TSINGHUA-HVAC-&#039;95</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1995</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1995</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Beijing, China</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gene Clark</style></author><author><style face="normal" font="default" size="100%">Fred M. Loxsom</style></author><author><style face="normal" font="default" size="100%">Earl S. Doderer</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Performance of Roofpond Cooled Residences in U.S. Climate</style></title><secondary-title><style face="normal" font="default" size="100%">Passive Solar Journal</style></secondary-title><short-title><style face="normal" font="default" size="100%">Passive Sol. J.</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">1987</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/1987</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">265-292</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The thermal advantages of a roofpond as an element of a residential cooling system are described. The authors conducted heat transfer experiments at two roofpond residences (RPRs) at Trinity University; the authors used data from these experiments to validate RPR simulations. Results of measurements of vertical and horizontal temperature differences within roofponds are discussed. Horizontal heat transfer within one water bag was effective. Thermal resistance at the outer surface of a water bag with a deflated glazing can be significant. Simulation shows that an RPR can provide comfort without supplemental sensible cooling during almost all hours of a typical summer in any U.S climate. Ceiling fans are important in most climates. In the most demanding climates, the residence and the pond insulating panels must have high R-value. A map is included that provides RPR design guidance. The simulations indicate that dehumidification will be required to control mold, mildew, and ceiling condensation in an RPR in most climates; energy and power displacement by an RPR is sensitive to the humidity control required and the efficiency of the dehumidifier used.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><section><style face="normal" font="default" size="100%">265</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Polarization Parameters of 183 Extragalactic Radio Sources</style></title><secondary-title><style face="normal" font="default" size="100%">Monthly Notices of the Royal Astronomical Society</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1975</style></year></dates><volume><style face="normal" font="default" size="100%">173</style></volume><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Robin G. Conway</style></author><author><style face="normal" font="default" size="100%">David Stannard</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Polarization of Radio Sources at 31 CM</style></title><secondary-title><style face="normal" font="default" size="100%">Monthly Notices of the Royal Astronomical Society</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Astronomical Catalogs</style></keyword><keyword><style  face="normal" font="default" size="100%">extragalactic radio sources</style></keyword><keyword><style  face="normal" font="default" size="100%">faraday effect</style></keyword><keyword><style  face="normal" font="default" size="100%">interferometry</style></keyword><keyword><style  face="normal" font="default" size="100%">microwave emission</style></keyword><keyword><style  face="normal" font="default" size="100%">polarized electromagnetic radiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Quasars</style></keyword><keyword><style  face="normal" font="default" size="100%">radiant flux density</style></keyword><keyword><style  face="normal" font="default" size="100%">radio astronomy</style></keyword><keyword><style  face="normal" font="default" size="100%">statistical analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">tables (data)</style></keyword><keyword><style  face="normal" font="default" size="100%">very high frequencies</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1974</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/1974</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">169</style></volume><pages><style face="normal" font="default" size="100%">117-131</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Measurements of the linear polarization of extragalactic radio sources have been made over a range of wavelengths in order to study both the properties of the sources themselves and the Faraday rotation along the line of sight to the observer. As part of a continuing program of such measurements the flux densities and integrated polarizations of 226 sources (including 134 quasars) were observed at 966 MHz (lambda 31 cm), to complement previous measurements at lambda 49 and lambda 74 cm (Conway et al. 1972). These results have been combined with others at shorter wavelengths in a discussion of the polarization properties of quasars (Conway et al. 1974). All the sources have angular sizes of 1 arcmin or less&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">117</style></section></record></records></xml>