<?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%">Felix Bunning</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Marcus Fuchs</style></author><author><style face="normal" font="default" size="100%">Dirk Muller</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bidirectional low temperature district energy systems with agent-based control: Performance comparison and operation optimization</style></title><secondary-title><style face="normal" font="default" size="100%">Applied Energy</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><volume><style face="normal" font="default" size="100%">209</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><custom2><style face="normal" font="default" size="100%">2001090</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%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Jared Langevin</style></author><author><style face="normal" font="default" size="100%">Kaiyu Sun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building Simulation: Ten Challenges</style></title><secondary-title><style face="normal" font="default" size="100%">Building Simulation</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building energy use</style></keyword><keyword><style  face="normal" font="default" size="100%">building life cycle</style></keyword><keyword><style  face="normal" font="default" size="100%">building performance simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">energy efficiency</style></keyword><keyword><style  face="normal" font="default" size="100%">energy modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">zero-net-energy buildings</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Buildings consume more than one-third of the world’s primary energy. Reducing energy use and greenhouse-gas emissions in the buildings sector through energy conservation and efficiency improvements constitutes a key strategy for achieving global energy and environmental goals. Building performance simulation has been increasingly used as a tool for designing, operating and retrofitting buildings to save energy and utility costs. However, opportunities remain for researchers, software developers, practitioners and policymakers to maximize the value of building performance simulation in the design and operation of low energy buildings and communities that leverage interdisciplinary approaches to integrate humans, buildings, and the power grid at a large scale. This paper presents ten challenges that highlight some of the most important issues in building performance simulation, covering the full building life cycle and a wide range of modeling scales. The formulation and discussion of each challenge aims to provide insights into the state-of-the-art and future research opportunities for each topic, and to inspire new questions from young researchers in this field.&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%">Ruoxi Jia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Buildings.Occupants: a Modelica package for modelling occupant behaviour in buildings</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Building Performance Simulation</style></secondary-title><short-title><style face="normal" font="default" size="100%">Journal of Building Performance Simulation</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">modelica</style></keyword><keyword><style  face="normal" font="default" size="100%">Modelica Buildings Library</style></keyword><keyword><style  face="normal" font="default" size="100%">Modelica Occupants Package</style></keyword><keyword><style  face="normal" font="default" size="100%">Occupant Behaviour</style></keyword><keyword><style  face="normal" font="default" size="100%">Occupant behaviour modelling</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%">11/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.tandfonline.com/doi/full/10.1080/19401493.2018.1543352https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.1543352</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">1 - 12</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Energy-related occupant behaviour is crucial to design and operation of energy and control systems in buildings. Occupant behaviours are often oversimplified as static schedules or settings in building performance simulation ignoring their stochastic nature. The continuous and dynamic interaction between occupants and building systems motivates their simultaneous simulation in an efficient manner. In the past, simultaneous simulation has relied on co-simulation approaches or customized source code changes to building simulation programmes. This paper presents Buildings. Occupants, an open-source package implemented in Modelica, for the simulation of occupant behaviours of lighting, windows, blinds, heating and air conditioning systems in office and residential buildings. Examples were presented to illustrate how the models in the Occupants package are capable to simulate stochastic occupant behaviours. The major contribution of this work is to introduce the equation-based modelling approach to simulate occupant behaviours in buildings and to develop an open-source Occupants package in the Modelica language&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%">Xin Zhou</style></author><author><style face="normal" font="default" size="100%">Da Yan</style></author><author><style face="normal" font="default" size="100%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Dandan Zhu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building energy modeling programs comparison Research on HVAC systems simulation part</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Building energy modeling programs</style></keyword><keyword><style  face="normal" font="default" size="100%">comparison tests</style></keyword><keyword><style  face="normal" font="default" size="100%">HVAC system simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">theory analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Building energy simulation programs are effective tools for the evaluation of building energy saving and optimization of design. The fact that large discrepancies exist in simulated results when different BEMPs are used to model the same building has caused wide concern. Urgent research is needed to identify the main elements that contribute towards the simulation results. This technical report summarizes methodologies, processes, and the main assumptions of three building energy modeling programs (BEMPs) for HVAC calculations: EnergyPlus, DeST, and DOE-2.1E, and test cases are designed to analyze the calculation process in detail. This will help users to get a better understanding of BEMPs and the research methodology of building simulation. This will also help build a foundation for building energy code development and energy labeling programs.&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%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Wei Feng</style></author><author><style face="normal" font="default" size="100%">Alison Lu</style></author><author><style face="normal" font="default" size="100%">Jianjun Xia</style></author><author><style face="normal" font="default" size="100%">Le Yang</style></author><author><style face="normal" font="default" size="100%">Qi Shen</style></author><author><style face="normal" font="default" size="100%">Piljae Im</style></author><author><style face="normal" font="default" size="100%">Mahabir Bhandari</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building Energy Monitoring and Analysis</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2013</style></date></pub-dates></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;U.S. and China are the world&#039;s top two economics. Together they consumed one-third of the world&#039;s primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services.&lt;/p&gt;&lt;p&gt;Buildings in the US and China consumed about 40% and 25% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change.&lt;/p&gt;&lt;p&gt;This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.&lt;/p&gt;&lt;p&gt;Key research findings were summarized as follows:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Identified the need for a standard data model and platform to collect, process, analyze, and exchange building performance data due to different definitions of energy use and boundary, difficulty in exchanging data, and lack of current standards.&lt;/li&gt;&lt;li&gt;Compared energy monitoring systems to identify gaps, including iSagy, Pulse Energy, SkySpark, sMap, EPP, ION, and Metasys.&lt;/li&gt;&lt;li&gt;Contributed to develop a standard data model to represent energy use in buildings (ISO standard 12655 and a Chinese national standard)&lt;/li&gt;&lt;li&gt;Determined that buildings in the United States and China are very different in design, operation, maintenance, occupant behavior: U.S. buildings have more stringent comfort standards regarding temperature, ventilation, lighting, and hot-water use and therefore higher internal loads and operating hours, and China buildings having higher lighting energy use, seasonal HVAC operation, more operators, more use of natural ventilation, less outdoor ventilation air, and wider range of comfort temperature.&lt;/li&gt;&lt;li&gt;Completed data collection for six office buildings, one in UC Merced campus, one in Sacramento, one in Berkeley, one in George Tech campus, and two in Beijing.&lt;/li&gt;&lt;li&gt;Compiled a source book of 10 selected buildings in the United States and China with detailed descriptions of the buildings, data points, and monitoring systems, and containing energy analysis of each building and an energy benchmarking among all buildings.&lt;/li&gt;&lt;li&gt;Recognized limited availability of quality data, particularly with long periods of time-interval data, and general lack of value for good data and large datasets.&lt;/li&gt;&lt;li&gt;Compiled a building energy database, with detailed energy end use at 1-hour or 15-minute time interval, of six office buildings — four in the U.S. and two in China. The database is available to the public and is a valuable resource for building research.&lt;/li&gt;&lt;li&gt;Developed methods and used them in data analysis of building performance for the five buildings with adequate data, including energy benchmarking, profiling (daily, weekly, monthly), and diagnostics.&lt;/li&gt;&lt;li&gt;Recommended energy efficiency measures for building retrofit in both countries. U.S. buildings show more potential savings by reducing operation time, reducing plug-loads, expanding comfort temperature range, and turning off lights or equipment when not in use; while Chinese buildings can save energy by increasing lighting system efficiency, and improving envelope insulation and HVAC equipment efficiency.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;The research outputs from the project can help better understand energy performance of buildings, improve building operations to reduce energy waste and increase efficiency, identify retrofit opportunities for existing buildings, and provide guideline to improve the design of new buildings. The standardized energy monitoring and analysis platform as well as the collected real building data can also be used for other CERC projects that need building energy measurements, and be further linked to building energy benchmarking and rating/labeling systems.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-6640E</style></custom2></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%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">Thierry Stephane Nouidui</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Zhengwei Li</style></author><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BacNet and Analog/Digital Interfaces of the Building Controls Virtual Testbed</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2011</style></date></pub-dates></dates><abstract><style face="normal" font="default" size="100%">&lt;p&gt;This paper gives an overview of recent developments in the Building Controls Virtual Test Bed (BCVTB), a framework for co-simulation and hardware-in-the-loop.&lt;/p&gt;&lt;p&gt;First, a general overview of the BCVTB is presented. Second, we describe the BACnet interface, a link which has been implemented to couple BACnet devices to the BCVTB. We present a case study where the interface was used to couple a whole building simulation program to a building control system to assess in real-time the performance of a real building. Third, we present the ADInterfaceMCC, an analog/digital interface that allows a USB-based analog/digital converter to be linked to the BCVTB. In a case study, we show how the link was used to couple the analog/digital converter to a building simulation model for local loop control.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-5446E</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%">Thierry Stephane Nouidui</style></author><author><style face="normal" font="default" size="100%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Zhengwei Li</style></author><author><style face="normal" font="default" size="100%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</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%">BACnet and Analog/Digital Interfaces of the Building Controls Virtual Test Bed</style></title><secondary-title><style face="normal" font="default" size="100%">Proc. of the 12th IBPSA Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2011</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Sydney, Australia</style></pub-location><pages><style face="normal" font="default" size="100%">p. 294-301</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><custom2><style face="normal" font="default" size="100%">LBNL-5446E</style></custom2></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%">Marcus Keane</style></author><author><style face="normal" font="default" size="100%">Andrea Costa</style></author><author><style face="normal" font="default" size="100%">James O&#039;Donnell</style></author><author><style face="normal" font="default" size="100%">Karsten Menzel</style></author><author><style face="normal" font="default" size="100%">Dirk, Alan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BuildWise Final Report</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Technical Report</style></work-type></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%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Brian E. Coffey</style></author><author><style face="normal" font="default" size="100%">Scott Williams</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Benchmarking and Equipment and Controls Assessment for a ‘Big Box’ Retail Chain</style></title><secondary-title><style face="normal" font="default" size="100%">ACEEE Summer Study on Energy Efficiency in Buildings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Asilomar, California, USA</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;The paper describes work to enable improved energy performance of existing and new retail stores belonging to a national chain and thereby also identify measures and tools that would improve the performance of ‘big box&#039; stores generally. A detailed energy simulation model of a standard store design was developed and used to:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;demonstrate the benefits of benchmarking the energy performance of retail stores of relatively standard design using baselines derived from simulation,&lt;/li&gt;&lt;li&gt;identify cost-effective improvements in the efficiency of components to be incorporated in the next design cycle,&lt;/li&gt;&lt;li&gt;use simulation to identify potential control strategy improvements that could be adopted in all stores, improving operational efficiency.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;The core enabling task of the project was to develop an energy model of the current standard design using the EnergyPlus simulation program. For the purpose of verification of the model against actual utility bills, the model was reconfigured to represent twelve existing stores (seven relatively new stores and five older stores) in different US climates and simulations were performed using weather data obtained from the National Weather Service. The results of this exercise, which showed generally good agreement between predicted and measured total energy use, suggest that dynamic benchmarking based on energy simulation would be an effective tool for identifying operational problems that affect whole building energy use. The models of the seven newer stores were then configured with manufacturers&#039; performance data for the equipment specified in the current design and used to assess the energy and cost benefits of increasing the efficiency of selected HVAC, lighting and envelope components. The greatest potential for cost-effective energy savings appears to be a substantial increase in the efficiency of the blowers in the roof top units and improvements in the efficiency of the lighting. The energy benefits of economizers on the roof-top units were analyzed and found to be very sensitive to the operation of the exhaust fans used to control building pressurization.&lt;/p&gt;</style></abstract></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%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Peng Xu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Building Controls Virtual Test Bed – a Simulation Environment for Developing and Testing Control Algorithms, Strategies and Systems</style></title><secondary-title><style face="normal" font="default" size="100%">Building Simulation ’07</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">controls</style></keyword><keyword><style  face="normal" font="default" size="100%">development system</style></keyword><keyword><style  face="normal" font="default" size="100%">hardware-in-the-loop</style></keyword><keyword><style  face="normal" font="default" size="100%">testing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ibpsa.org/proceedings/BS2007/p748_final.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Bejing, China</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;The paper describes the design of a Building Controls Virtual Test Bed (BCVTB), a simulation environment for the development of control algorithms and strategies for the major energy systems in buildings, HVAC, lighting, active facades and on-site generation. The BCVTB is based on the whole building energy simulation program EnergyPlus and includes both the pure simulation and the hardware-in-the-loop methods of implementing the controls. For convenience and scalability, the design of the hardware-in-the-loop interface for supervisory controls uses BACnet rather than the analog interface used for local loop control. The paper concludes with a case study of the use of a prototype implementation of the BCVTB to precommission the building control system for the naturally-ventilated San Francisco Federal Building. A number of problems were found with the control program, demonstrating the value of the precommissioning and the effectiveness of the technique.&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%">Ravi S. Prasher</style></author><author><style face="normal" font="default" size="100%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">Patrick E. Phelan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Brownian Motion Based Convective- Conductive Model for the Effective Thermal Conductivity of Nanofluids</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Heat Transfer</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%">128</style></volume><pages><style face="normal" font="default" size="100%">588-595</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">588</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%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Elijah Polak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building design optimization using a convergent pattern search algorithm with adaptive precision simulations</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">37</style></volume><pages><style face="normal" font="default" size="100%">603-612</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We propose a simulation–precision control algorithm that can be used with a family of derivative free optimization algorithms to solve optimization problems in which the cost function is defined through the solutions of a coupled system of differential algebraic equations (DAEs). Our optimization algorithms use coarse precision approximations to the solutions of the DAE system in the early iterations and progressively increase the precision as the optimization approaches a solution. Such schemes often yield a significant reduction in computation time. We assume that the cost function is smooth but that it can only be approximated numerically by approximating cost functions that are discontinuous in the design parameters. We show that this situation is typical for many building energy optimization problems.We present a new building energy and daylighting simulation program, which constructs approximations to the cost function that converge uniformly on bounded sets to a smooth function as precision is increased.We prove that for our simulation program, our optimization algorithms construct sequences of iterates with stationary accumulation points. We present numerical experiments in which we minimize the annual energy consumption of an office building for lighting, cooling and heating. In these examples, our precision control algorithm reduces the computation time up to a factor of four.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom2><style face="normal" font="default" size="100%">LBNL-57341</style></custom2></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%">Elmer Morrissey</style></author><author><style face="normal" font="default" size="100%">Marcus Keane</style></author><author><style face="normal" font="default" size="100%">James O&#039;Donnell</style></author><author><style face="normal" font="default" size="100%">John F. McCarthy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building Effectiveness Communication Ratios for Improved Building Life Cycle Management</style></title><secondary-title><style face="normal" font="default" size="100%">IBPSA Building Simulation Conference 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%">Montréal, Canada</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;Many existing building energy performance assessment frameworks, quantifying and categorising buildings post occupancy, offer limited feedback on design decisions. An environment providing decision makers with pertinent information to assess the consequences of each design decision in a timely, cost effective and practical manner is required to promote viable low-energy solutions from the outset. This paper outlines a performance-based strategy utilising building effectiveness communication ratios stored in Building Information Models (BIM). Decision makers will be capable of rating the building&#039;s energy performance throughout its natural life cycle without imposing adverse penalties on facilities located in dissimilar climatic zones subjected to stringent building codes and regulations. With this advancement in building energy assessment in place, a progressive improvement in energy efficiency for the building stock is a feasible and realistic target.&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%">Xiufeng Pang</style></author><author><style face="normal" font="default" size="100%">Zheng, B</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%">Building Pressure Control in VAV System with Relief Air Fan</style></title><secondary-title><style face="normal" font="default" size="100%">the 5th International Conference of Enhanced Building Operations</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%">2005</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Pittsburgh, PA</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%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BuildOpt - A new building energy simulation program that is built on smooth models</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">1085-1092</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has a unique once continuously differentiable solution. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with Generalized Pattern Search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today&#039;s building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt&#039;s approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><section><style face="normal" font="default" size="100%">1085</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%">Prajesh Bhattacharya</style></author><author><style face="normal" font="default" size="100%">Saha, S.K.</style></author><author><style face="normal" font="default" size="100%">Ajay K. Yadav</style></author><author><style face="normal" font="default" size="100%">Patrick E. Phelan</style></author><author><style face="normal" font="default" size="100%">Ravi S. Prasher</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Brownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Applied Physics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">complex fluids</style></keyword><keyword><style  face="normal" font="default" size="100%">Disperse systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Thermal conduction in nonmetallic liquids</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%">06/2004</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">95</style></volume><pages><style face="normal" font="default" size="100%">6492–6494</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Normally, nanofluids have higher thermal conductivities than their base fluids. Therefore, it is of interest to predict the effective thermal conductivity of such a nanofluid under different conditions, especially since only limited experimental data are available. We have developed a technique to compute the effective thermal conductivity of a nanofluid using Brownian dynamics simulation, which has the advantage of being computationally less expensive than molecular dynamics, and have coupled that with the equilibrium Green-Kubo method. By comparing the results of our calculation with the available experimental data, we show that our technique predicts the thermal conductivity of nanofluids to a good level of accuracy.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><section><style face="normal" font="default" size="100%">6492</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%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Elijah Polak</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building Design Optimization Using a Convergent Pattern Search Algorithm with Adaptive Precision Simulations</style></title><secondary-title><style face="normal" font="default" size="100%">Energy and Buildings</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><volume><style face="normal" font="default" size="100%">37</style></volume><pages><style face="normal" font="default" size="100%">603-612</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">603</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%">Vladimir Bazjanac</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building energy performance simulation as part of interoperable software environments</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><number><style face="normal" font="default" size="100%">8</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">879-883</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><call-num><style face="normal" font="default" size="100%">LBNL/PUB-905</style></call-num><custom1><style face="normal" font="default" size="100%">&lt;p&gt;Simulation Research Group&lt;/p&gt;</style></custom1><custom2><style face="normal" font="default" size="100%">LBNL/PUB-905</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%">Vladimir Bazjanac</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building Energy Performance Simulation as Part of Interoperable Software Environments</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</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%">2004</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">879-883</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">879</style></section></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%">James O&#039;Donnell</style></author><author><style face="normal" font="default" size="100%">Elmer Morrissey</style></author><author><style face="normal" font="default" size="100%">Marcus Keane</style></author><author><style face="normal" font="default" size="100%">Vladimir Bazjanac</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BuildingPI: A Future Tool for Building Life Cycle Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">SimBuild 2004 1st International Conference of IBPSA-USA</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%">08/2004</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Boulder, Colorado, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><custom2><style face="normal" font="default" size="100%">LBNL-56071</style></custom2></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%">Michael Wetter</style></author><author><style face="normal" font="default" size="100%">Elijah Polak</style></author><author><style face="normal" font="default" size="100%">Van P. Carey</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BuildOpt 1.0.1 validation</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><custom2><style face="normal" font="default" size="100%">LBNL-54658</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%">Michael Wetter</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">BuildOpt - A new building energy simulation program that is built on smooth models</style></title><secondary-title><style face="normal" font="default" size="100%">Building and Environment</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%">08/2005</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">40</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has unique solution that is once continuously differentiable in the building design parameters. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with generalized pattern search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today&#039;s building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt&#039;s approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom2><style face="normal" font="default" size="100%">LBNL-54657</style></custom2><section><style face="normal" font="default" size="100%">1085-1092</style></section></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%">Tuomas Laine</style></author><author><style face="normal" font="default" size="100%">Risto Kosonen</style></author><author><style face="normal" font="default" size="100%">Kim Hagström</style></author><author><style face="normal" font="default" size="100%">Panu Mustakallio</style></author><author><style face="normal" font="default" size="100%">De-Wei Yin</style></author><author><style face="normal" font="default" size="100%">Philip Haves</style></author><author><style face="normal" font="default" size="100%">Qingyan Chen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Better IAQ Through Integrating Design Tools For The HVAC Industry</style></title><secondary-title><style face="normal" font="default" size="100%">Healthy Buildings 2000</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2000</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Espoo, Finland</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;There is currently no effective combination of interoperable design tools to cover all critical aspects of the HVAC design process. Existing design tools are separately available, but require expertise and operating time that is beyond the scope of a normal design project. For example, energy analysis and computational fluid dynamics (CFD) tools are not used in practical design, leading to poor indoor air quality and/or unnecessary energy consumption in buildings.&lt;/p&gt;&lt;p&gt;A prototype integrated software tool for demonstration, process mapping and proof-of-concept purposes was developed under a new international, Finland/USA jointly funded development project BildIT. Individual design tools were simplified and adapted to specific applications and also integrated so that they can be used in a timely and effective manner by the designer. The core of the prototype linked together an architectural CAD system, a 3D space model, a CFD program and a building energy simulation program and it utilises real product data from manufacturer&#039;s software. Also the complex building design, construction, maintenance and retrofit processes were mapped to get a template for the structure of the integrated design tool.&lt;/p&gt;</style></abstract><custom2><style face="normal" font="default" size="100%">LBNL-48456</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%">Tianzhen Hong</style></author><author><style face="normal" font="default" size="100%">Siaw K. Chou</style></author><author><style face="normal" font="default" size="100%">T.Y. Bong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building simulation: an overview of development and information sources</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%">building simulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2000</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2000</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">347-361</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We review the state-of-the-art on the development and application of computer-aided building simulation by addressing some crucial questions in the field. Although the answers are not intended to be comprehensive, they are sufficiently varied to provide an overview ranging from the historical and technical development to choosing a suitable simulation program and performing building simulation. Popular icons of major interested agencies and simulation tools and key information sources are highlighted. Future trends in the design and operation of energy-efficient ‘green&#039; buildings are briefly described.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><work-type><style face="normal" font="default" size="100%">Review Article</style></work-type><section><style face="normal" font="default" size="100%">347</style></section></record></records></xml>