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At least 685 records · Page 38

Exploring Building Retrofit Strategies Using AutoBEM Under Future Weather Scenarios

This study evaluates the long-term effectiveness of energy conservation measures (ECMs) on building energy consumption using AutoBEM, a scalable modeling framework driven by the high-resolution Model America dataset. We simulated 18,951 buildings in Flagstaff, Arizona under four climate scenarios using Future Typical Meteorological Year (fTMY) weather files for six time periods spanning from 1980 to 2099. Six ECMs were analyzed across electricity and gas usage, including HVAC fuel-switching, insulation upgrades, and infiltration control. While some measures, such as reducing space infiltration by percentage, showed minimal or even negative impact on total energy savings at the aggregate level, they proved highly effective for specific building types. Conversely, HVAC electrification offers high gas reduction but shifts demand to electricity, highlighting critical trade-offs under different climate trajectories. Building-type-specific analysis under SSP5-RCP8.5 (2080–2099) revealed significant variation in ECM performance, underscoring the need for targeted retrofit strategies. This study demonstrates the power of combining fTMY projections with large-scale simulations to inform data-driven retrofit planning.

Chowdhury, Shovan [ORNL]↗

Geochemical Reaction Mechanism Discovery from Molecular Simulation

Methods to explore reactions using computer simulation are becoming increasingly quantitative, versatile, and robust. In this review, a rationale for how molecular simulation can help build better geochemical kinetics models is first given. We summarize some common methods that geochemists use to simulate reaction mechanisms, specifically classical molecular dynamics and quantum chemical methods and discuss their strengths and weaknesses. Useful tools such as umbrella sampling and metadynamics that enable one to explore reactions are discussed. Several case studies wherein geochemists have used these tools to understand reaction mechanisms are presented, including water exchange and sorption on aqueous species and mineral surfaces, surface charging, crystal growth and dissolution, and electron transfer. The impact that molecular simulation has had on our understanding of geochemical reactivity are highlighted in each case. In the future, it is anticipated that molecular simulation of geochemical reaction mechanisms will become more commonplace as a tool to validate and interpret experimental data, and provide a check on the plausibility of geochemical kinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

OpenFAST [SWR-08-12]

OpenFAST is a wind turbine simulation tool which builds on NREL's FAST v8 software. NREL's FAST.Farm software extends the capability of OpenFAST to simulate multi-turbine wind farms. They were created with the goal of being community models developed and used by research laboratories, academia, and industry. They are managed by a dedicated team at the National Renewable Energy Laboratory (NREL). Our objective is to ensure that OpenFAST and FAST.Farm are sustainable software that are well tested and well documented. If you'd like to contribute, see the Developer Documentation and any open GitHub issues with the Help Wanted tag.

Jonkman, Jason↗

ComStock/COVID-19: U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies

ComStock is a DOE platform, with NREL as the lead developer, that models the U.S. commercial building stock using OpenStudio/EnergyPlus to perform physics-based building energy modeling simulations. The ASHRAE Epidemic Taskforce (ASHRAE-ETF) has released several COVID-19 mitigation strategies for commercial buildings. ComStock was used to analyze the impact of four strategies on the existing commercial building stock. These strategies are upgrading to MERV-13 filters, disabling demand control ventilation (DCV), increasing minimum outdoor air to 100%, and HVAC flushing mode operation. Results show the impact of each measure on energy consumption, electric consumption, gas consumption and peak electric.

30 DIRECT ENERGY CONVERSION↗

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for the solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗

Modeling and analysis of heat emissions from buildings to ambient air

Heat emissions from buildings is a significant source of anthropogenic heat influencing the urban microclimate; however, they are usually oversimplified in urban climate and microclimate modeling. This study developed a bottom-up physics-based approach to calculate heat emissions from buildings to the ambient air and implemented the approach in EnergyPlus. In this work, a simple result verification was conducted by comparing the EnergyPlus simulated results against the spreadsheet calculations. Simulations covering 16 commercial building types, four climates, and two energy efficiency levels were conducted to understand and evaluate the building heat emissions and their temporal patterns as well as three major components: (1) building envelope (convective heat transfer to ambient air), (2) zones (air exfiltration and exhaust air), and (3) HVAC systems (relief air and heat rejection from condensers or cooling towers). The main findings are: (1) heat emissions are usually higher than the site energy use (about 2.5 times), and their dynamics should be considered; (2) building characteristics and their energy systems lead to differences in heat emission contributions from the three components, and their dynamics, for example, in the warehouse models, the envelope component accounts for 90.4%, while it is 12.7% for the large office models; (3) for most building typologies, the climate has a strong impact on heat emissions, for example, buildings with dominant heat emissions from the zone exhaust air and/or the HVAC reject heat, a general decrease in heat emissions in hotter climates is observed, while envelope-dominated buildings show the opposite; and (4) building technologies that reduce energy use in buildings may perform differently in reducing heat emissions. The developed heat emissions calculation method can be adopted in EnergyPlus and most other building energy modeling programs. It can provide dynamic building heat emissions as an input to urban climate computational fluid dynamics (CFD) models at a higher spatial and temporal resolution than is currently available, to improve the simulation accuracy of the urban microclimate and capture the urban heat island effect and urban overheating.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Resolving discrepancies in bang-time predictions for indirect-drive ICF experiments on the NIF: Insights from the Build-A-Hohlraum campaign

This study investigated discrepancies between measured and simulated x-ray drive in Indirect-Drive Inertial Confinement Fusion (ID-ICF) hohlraums at the National Ignition Facility. Despite advances in radiation-hydrodynamic simulations, a consistent “drive deficit” remains. Experimentally measured ID-ICF capsule bang-times are systematically 400–700 ps later than simulations predict. The Build-A-Hohlraum (BAH) campaign explored potential causes for this discrepancy by systematically varying hohlraum features, including laser entrance hole (LEH) windows, capsules, and gas fills. Overall, the agreement between simulated and experimental x-ray drive was found to be largely unaffected by these changes. The data allow us to exclude some hypotheses put forward to potentially explain the discrepancy. Errors in the local thermodynamic equilibrium (LTE) atomic modeling, errors in the modeling of LEH closure, and errors due to a lack of plasma species mix physics in simulations are shown to be inconsistent with our measurements. Instead, the data support the hypothesis that errors in NLTE emission modeling are a significant contributor to the discrepancy. X-ray emission in the 2–4 keV range is found to be approximately 30% lower than in simulations. This is accompanied by higher than predicted electron temperatures in the gold bubble region, pointing to errors in non-LTE modeling. Introducing an opacity multiplier of 0.87 on energy groups above 1.8 keV improves agreement with experimental data, reducing the bang-time discrepancy from 300 to 100 ps. These results underscore the need for refined NLTE opacity models to enhance the predictive power of hohlraum simulations.

Band emission↗

Transactive Control of Commercial Buildings for Demand Response

Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Several case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Regional Analysis of Building Distributed Energy Costs and CO2 Abatement: A U.S. - China Comparison

The following paper conducts a regional analysis of the U.S. and Chinese buildings? potential for adopting Distributed Energy Resources (DER). The expected economics of DER in 2020-2025 is modeled for a commercial and a multi-family residential building in different climate zones. The optimal building energy economic performance is calculated using the Distributed Energy Resources Customer Adoption Model (DER CAM) which minimizes building energy costs for a typical reference year of operation. Several DER such as combined heat and power (CHP) units, photovoltaics, and battery storage are considered. The results indicate DER have economic and environmental competitiveness potential, especially for commercial buildings in hot and cold climates of both countries. In the U.S., the average expected energy cost savings in commercial buildings from DER CAM?s suggested investments is 17percent, while in Chinese buildings is 12percent. The electricity tariffs structure and prices along with the cost of natural gas, represent important factors in determining adoption of DER, more so than climate. High energy pricing spark spreads lead to increased economic attractiveness of DER. The average emissions reduction in commercial buildings is 19percent in the U.S. as a result of significant investments in PV, whereas in China, it is 20percent and driven by investments in CHP. Keywords: Building Modeling and Simulation, Distributed Energy Resources (DER), Energy Efficiency, Combined Heat and Power (CHP), CO2 emissions 1. Introduction The transition from a centralized and fossil-based energy paradigm towards the decentralization of energy supply and distribution has been a major subject of research over the past two decades. Various concerns have brought the traditional model into question; namely its environmental footprint, its structural inflexibility and inefficiency, and more recently, its inability to maintain acceptable reliability of supply. Under such a troubled setting, distributed energy resources (DER) comprising of small, modular, electrical renewable or fossil-based electricity generation units placed at or near the point of energy consumption, has gained much attention as a viable alternative or addition to the current energy system. In 2010, China consumed about 30percent of its primary energy in the buildings sector, leading the country to pay great attention to DER development and its applications in buildings. During the 11th Five Year Plan (FYP), China has implemented 371 renewable energy building demonstration projects, and 210 photovoltaics (PV) building integration projects. At the end of the 12th FYP, China is targeting renewable energy to provide 10percent of total building energy, and to save 30 metric tons of CO2 equivalents (mtce) of energy with building integrated renewables. China is also planning to implement one thousand natural gas-based distributed cogeneration demonstration projects with energy utilization rates over 70percent in the 12th FYP. All these policy targets require significant DER systems development for building applications. China?s fast urbanization makes building energy efficiency a crucial economic issue; however, only limited studies have been done that examine how to design and select suitable building energy technologies in its different regions. In the U.S., buildings consumed 40percent of the total primary energy in 2010 [1] and it is estimated that about 14 billion m2 of floor space of the existing building stock will be remodeled over the next 30 years. Most building?s renovation work has been on building envelope, lighting and HVAC systems. Although interest has emerged, less attention is being paid to DER for buildings. This context has created opportunities for research, development and progressive deployment of DER, due to its potential to combine the production of power and heat (CHP) near the point of consumption and delivering multiple benefits to customers, such as cost

25 ENERGY STORAGE↗

Moisture Transfer in Commercial Buildings Due to Air Leakage: A New Feature in the Online Airtightness Savings Calculator

Air leakage through the building envelopes is responsible for a large amount of energy use. The US Department of Energy Windows and Building Envelope Research and Development Roadmap for Emerging Technologies states that, in 2010, air infiltration was responsible for 20% of primary energy consumption attributable to the fenestration and building envelopes of commercial buildings. Despite this fact, improving airtightness is not always recognized by commercial building owners, as they have been slow in acknowledging and diminishing the detrimental effects of air leakage on energy use, comfort, indoor air quality, and building material durability.The design and construction industry would benefit from a credible, easy-to-use tool that estimates potential energy and financial savings in a standardized manner so designers and contractors can give building owners compelling reasons to invest in reducing air leakage. In 2016–2017, Oak Ridge National Laboratory, the National Institute of Standards and Technology, the Air Barrier Association of America, and the US-China Clean Energy Research Center for Building Energy Efficiency collaborated to develop an online calculator. This user-friendly calculator is free to the public and uses the simulation results of the whole building energy simulation tool EnergyPlus and the airflow simulation tool CONTAM. In 2018–2019, the calculator was expanded to add moisture transfer calculations given that air leakage through the building envelope can have a significant impact on moisture transfer and associated impacts. Four more commercial building types were also added to the existing database of three building types as part of this update. This paper describes the procedure used to calculate moisture transfer due to air leakage and provides examples that demonstrate the moisture transfer for each of the seven commercial building types that are currently part of the calculator.

Shrestha, Som↗

Modeling urban building energy use: A review of modeling approaches and procedures

With rapid urbanization and economic development, the world has been experiencing an unprecedented increase in energy consumption and greenhouse gas (GHG) emissions. While reducing energy consumption and GHG emissions is a common interest shared by major developed and developing countries, actions to enable these global reductions are generally implemented at the city scale. This is because baseline information from individual cities plays an important role in identifying economical options for improving building energy efficiency and reducing GHG emissions. Numerous approaches have been proposed for modeling urban building energy use in the past decades. This paper aims to provide an up-to-date review of the broad categories of energy models for urban buildings and describes the basic workflow of physics-based, bottom-up models and their applications in simulating urban-scale building energy use. Because there are significant differences across models with varied potential for application, strengths and weaknesses of the reviewed models are also presented. This is followed by a discussion of challenging issues associated with model preparation and calibration.

Bottom-up approaches↗

A Data-Driven Approach to Nation-Scale Building Energy Modeling

In 2019, 125 million U.S. residential and commercial buildings consumed $412 billion in energy bills. These buildings currently consume 40% of the nation's primary energy, 73% of electricity, 80% of energy during peak electric grid use, and responsible for 39% of greenhouse gas emissions [14]. Urban-scale building energy modeling has grown significantly in the past decade, allowing individual campuses or communities of buildings to be modeled, simulated, and cost-effective solutions for intelligent management to be identified and implemented. While traditionally limited to individual counties and usually less than 2,000 buildings, the Automatic Building Energy Modeling (AutoBEM) soft-ware suite has been developed to process unconventional, nation-scale data sources to generate unique OpenStudio and EnergyPlus models of each building. Through the use of High Performance Computing (HPC) resources, every U.S. building has been simulated. This paper showcases the data layout, node partitioning, algorithmic approaches, and analytic results that were used to create, share, and analyze 124.4 million U.S. building models.

Berres, Andy↗

An efficient numerical model for predicting residual stress and strain in parts manufactured by laser powder bed fusion

Abstract Computational modeling of additively manufactured structures plays an increasingly important role in product design and optimization. For laser powder bed fusion processes, the accurate modeling of stress and distortion requires large amount of computational cost due to very localized heat input and evolving complex geometries. The current study takes advantage of a graphics processing unit accelerated explicit finite element analysis code and approximated heat conduction analysis to predict the macroscopic thermo-mechanical behavior in laser selective melting. Adjacent layers and tracks were lumped to reduce the number of time steps and elements in the finite element model. The effects of track and layer grouping on prediction accuracy and solution efficiency are investigated to provide a guidance for a cost-effective simulation. Thin-wall builds from Inconel alloy 625 (IN625) powders were simulated by applying the developed modeling approach to get the detailed residual stress and distortion at a computational speed 50 times higher than conventional approach. Under repeated heating and cooling cycles, a high tensile stress was produced near surfaces of a build due to a larger shrinkage on surface than that in central area. It is also shown that horizontal stresses concentrate near the root and top layers of the IN625 build. The predicted residual elastic strain distribution was validated by the experimental measurement using x-ray synchrotron diffraction.

36 MATERIALS SCIENCE↗

Variability of near-fault seismic risk to reinforced concrete buildings based on high-resolution physics-based ground motion simulations

Broadband physics-based simulated earthquake ground motions are utilized to characterize the regional-scale seismic risk to modern reinforced concrete (RC) structures. A highly dense dataset of ground motions covering a 100-km urn:x-wiley:00988847:media:eqe3413:eqe3413-math-0001 40-km domain was generated using kinematic fault rupture models with varying rupture characteristics to represent shallow crustal earthquakes and resolved up to frequencies of 5 Hz. Over 40,000 nonlinear response history simulations of short- and mid-rise RC special moment frame buildings were conducted using simulation models that are capable of representing nonlinear behavior and component deterioration effects. The spatial variability of structural risk within a single earthquake scenario and between different rupture scenarios is examined, and the regions of strongest directivity effects and highest structural demands are identified. The structural demands may vary by factor of up to 8.0 at very short distances from the fault, and the large dispersion in the demands decreases significantly beyond a distance of 15 km. The interstory drift and member rotation demands are substantially impacted by important features of the geological structure and the characteristics of the rupture scenarios, particularly the presence of localized high-slip regions. The frequency characteristics of the structures are found to play an important role in determining the effects of near-fault ground motions on the structural response and expected damage. The results of this study suggest that the simulated ground motions, particularly those generated using the hybrid rupture approach, may offer reasonable structural risk estimates for low-frequency structures and conservative estimates for high-frequency structures.

58 GEOSCIENCES↗

Orbiter/External Tank Mate 3-D Solid Modeling

This research and development project presents an overview of the work completed while attending a summer 2004 American Society of Engineering Education/National Aeronautics and Space Administration (ASEE/NASA) Faculty Fellowship. This fellowship was completed at the Kennedy Space Center, Florida. The scope of the project was to complete parts, assemblies, and drawings that could be used by Ground Support Equipment (GSE) personnel to simulate situations and scenarios commonplace to the space shuttle Orbiter/External Tank (ET) Mate (50004). This mate takes place in the Vehicle Assembly Building (VAB). These simulations could then be used by NASA engineers as decision-making tools. During the summer of 2004, parts were created that defined the Orbiter/ET structural interfaces. Emphasis was placed upon assemblies that included the Orbiter/ET forward attachment (EO-1), aft left thrust strut (EO-2), aft right tripod support structure (EO-3), and crossbeam and aft feedline/umbilical supports. These assemblies are used to attach the Orbiter to the ET. The Orbiter/ET Mate assembly was then used to compare and analyze clearance distances using different Orbiter hang angles. It was found that a 30-minute arc angle change in Orbiter hang angle affected distance at the bipod strut to Orbiter yoke fitting 8.11 inches. A 3-D solid model library was established as a result of this project. This library contains parts, assemblies, and drawings translated into several formats. This library contains a collection of the following files: sti for sterolithography, stp for neutral file work, shrinkwrap for compression. tiff for photoshop work, jpeg for Internet use, and prt and asm for Pro/Engineer use. This library was made available to NASA engineers so that they could access its contents to make angle, load, and clearance analysis studies. These decision-making tools may be used by Pro/Engineer users and non-users.

Godfrey, G. S.↗

An intelligent simulation training system

The Department of Industrial Engineering at the University of Central Florida, Embry-Riddle Aeronautical University and General Electric (SCSD) have been funded by the State of Florida to build an Intelligent Simulation Training System. The objective was and is to make the system generic except for the domain expertise. Researchers accomplished this objective in their prototype. The system is modularized and therefore it is easy to make any corrections, expansions or adaptations. The funding by the state of Florida has exceeded $3 million over the past three years and through the 1990 fiscal year. UCF has expended in excess of 15 work years on the project. The project effort has been broken into three major tasks. General Electric provides the simulation. Embry-Riddle Aeronautical University provides the domain expertise. The University of Central Florida has constructed the generic part of the system which is comprised of several modules that perform the tutoring, evaluation, communication, status, etc. The generic parts of the Intelligent Simulation Training Systems (ISTS) are described.

Biegel, John E.↗

Using Residential and Office Building Archetypes for Energy Efficiency Building Solutions in an Urban Scale: A China Case Study

Building energy consumption accounts for 36% of the overall energy end use worldwide and is growing rapidly as developing countries continue to urbanize. Understanding the energy use at urban scale will lay the foundation for identification of energy efficiency opportunities to be deployed at speed. China has almost half of global new constructions and plays an important role in building suitability. However, an open source national building energy consumption database is not available in China. To provide data support for building energy consumptions, this paper used a simulation method to develop an urban building energy consumption database for a pilot city in Wuhan, China. First, residential, small, and large office building archetype energy models were created in EnergyPlus to represent typical building energy consumption in Wuhan. The baseline reference model simulation results were further validated using survey data from the literature. Second, stochastic simulations were conducted to consider different design parameters and occupants’ energy usage intensity scenarios, such as thermal properties of the building envelope, lighting power density, equipment power density, HVAC (heating, ventilation and air conditioning) schedule, etc. A building energy consumption database was generated for typical building archetypes. Third, data-driven regression analysis was conducted to support quick building energy consumption prediction using key high- level building information inputs. Finally, a web-based urban energy platform and an interface were developed to support further third-party application development. The research is expected to provide fast energy efficiency building design solutions for urban planning, new constructions as well as building retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗