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DOE OSTI2021

Sensitivity Analysis of Occupant Preferences on Energy Usage in Residential Buildings: Preprint

Residential buildings, accounting for 37% of the total electricity consumption in the United States, are suitable for demand-side management (DSM) programs to support effective and economical operation of the power system. A home energy management system (HEMS) enables residential buildings to participate in such programs. It is important to account for occupant preferences in HEMS to ensure occupant satisfaction while participating in DSM programs. For example, people who prefer a higher thermal comfort level are likely to consume more energy. In this study, we used foresee™, a HEMS developed by the National Renewable Energy Lab (NREL), to perform a sensitivity analysis of occupant preferences with the following objectives: minimize utility cost, minimize carbon footprint, and maximize thermal comfort. To incorporate the preferences into the HEMS, the SMARTER method was used to derive a set of weighting factors for each objective. We performed week-long building energy simulations using a model of a home in Fort Collins, Colorado, where there is mandatory time-of-use electricity rate structure. The foreseeTM HEMS was used to control the home with six different sets of occupant preferences. The study shows that occupant preferences can have a significant impact and is important to consider when modeling residential buildings. Results show that the HEMS could achieve energy reduction ranging from 3% to 21%, cost savings ranging from 5% to 24%, and carbon emission reduction ranging from 3% to 21%, while maintaining a low thermal discomfort level ranging from 0.78 K-hour to 6.47 K-hour in a one-week period during winter. These outcomes quantify the impact of varying occupant preferences and will be useful for controlling the electrical grid and developing HEMS solutions.

carbon footprint↗

DOE OSTI2016

Building America Case Study: Impact of Slab-Foundation Heat Transfer on Space-Conditioning Energy Use in Florida, Cocoa, Florida

Heat transfer to slab foundations has remained an area of building science with poor understanding over the last three decades of energy efficiency research. This is somewhat surprising since the area of floors in single family homes is generally equal to wall, or windows or attics which have been extensively evaluated. Research that has been done has focused in the impact of slab on grade foundations and insulation schemes on heat losses associated with heating in predominantly heating dominated climates. Slab on grade construction is very popular in cooling-dominated southern states where it accounts for 77 percent of new home floors according to U.S. Census data in 2014. There is a widespread conception that tile flooring, as opposed to carpet, makes for a cooler home interior in warm climates. Empirical research is needed as building energy simulations such as DOE-2 and EnergyPlus rely on simplified models to evaluate these influences. BA-PIRC performed experiments over an entire year from 2014-2015 in FSEC's Flexible Residential Test Facilities (FRTF) intended to assess for the first time 1) slab on grade influence in a cooling dominated climate, and 2) how the difference in a carpeted vs. uncarpeted building might influence heating and cooling. Two identical side by side residential buildings were evaluated, the East with pad and carpet and the west with a bare slab floor. A highly detailed grid of temperature measurements were taken on the slab surface at various locations as well as at depths of 1, 2.5, 5, 10 and 20 feet.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Building America Case Study: Impact of Slab-Foundation Heat Transfer on Space-Conditioning Energy Use in Florida, Cocoa, Florida

BAPIRC↗

DOE OSTI2017

MOOSE Framework Speed and Memory Optimizations

The Multiphysics Object Oriented Simulation Environment (MOOSE) framework has been developed to solve a variety of complex simulations ranging from groundwater flows to full reactor simulations. MOOSE excels at solving fully-implicit, fully-coupled, highly nonlinear models using the Jacobian Free Newton-Krylov (JFNK) method relying on years of expertise in several dependent packages including PETSc, libMesh, Hypre and many others. The modular design of MOOSE enables the rapid development of new physics models that can be coupled with relative ease within the framework for building up simulations of different levels of complexity. With the ongoing adoption of MOOSE to new application areas along with streamlining of existing simulations, the priorities must be adjusted to include code optimizations. This includes both execution speed and the memory footprint of MOOSE-based simulations. These two categories can be further broken down into ''micro-optimizations'' or source code optimizations and algorithmic optimizations where source code is restructured to accomplish the same tasks through a more efficient means. However, before any code optimizations can occur, one must have robust way of measuring these critical simulation properties to identify the best candidates for optimizations along with having a way to identify the effectiveness of proposed optimizations to the framework. This report discusses the preliminary work towards the implementation of a robust execution baseline of the framework and derivative applications under a variety of different simulations. In addition, several potential optimization target areas in both the MOOSE framework and dependent libraries have been identified. An implementation strategy and potential benefits are discussed.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1986

RT_BUILD: An expert programmer for implementing and simulating Ada real-time control software

The RT BUILD is an expert control system programmer that creates real-time Ada code from block-diagram descriptions of control systems. Since RT BUILD embodies substantial knowledge about the implementation of real-time control systems, it can perform many, if not most of the functions normally performed by human real-time programmers. Though much basic research was done in automatic programming, RT BUILD appears to be the first application of this research to an important problem in flight control system development. In particular, RT BUILD was designed to directly increase productivity and reliability for control implementations of large complex systems.

Lehman, Larry L.↗

DOE OSTI2026

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

COMPASO : A new halo finder for competitive assignment to spherical overdensities

We describe a new method (compaso) for identifying groups of particles in cosmological N-body simulations. compaso builds upon existing spherical overdensity (SO) algorithms by taking into consideration the tidal radius around a smaller halo before competitively assigning halo membership to the particles. In this way, the compaso finder allows for more effective deblending of haloes in close proximity as well as the formation of new haloes on the outskirts of larger ones. This halo-finding algorithm is used in the abacussummit suite of N-body simulations, designed to meet the cosmological simulation requirements of the Dark Energy Spectroscopic Instrument (DESI) survey. compaso is developed as a highly efficient on-the-fly group finder, which is crucial for enabling good load-balancing between the GPU and CPU and the creation of high-resolution merger trees. In this paper, we describe the halo-finding procedure and its particular implementation in abacus, accompanying it with a qualitative analysis of the finder. We test the robustness of the compaso catalogues before and after applying the cleaning method described in an accompanying paper and demonstrate its effectiveness by comparing it with other validation techniques. We then visualize the haloes and their density profiles, finding that they are well fit by the NFW formalism. Finally, we compare other properties such as radius–mass relationships and two-point correlation functions with that of another widely used halo finder, rockstar.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗

DOE OSTI2020

Residential Natural Gas Demand Response Potential during Extreme Cold Events in Electricity-Gas Coupled Energy Systems

In regions where natural gas is used for both power generation and heating buildings, extreme cold weather events can place the electrical system under enormous stress and challenge the ability to meet residential heating and electric demands. Residential demand response has long been used in the power sector to curtail summer electric load, but these types of programs in general have not seen adoption in the natural gas sector during winter months. Natural gas demand response (NG-DR) has garnered interest given recent extreme cold weather events in the United States; however, the magnitude of savings and potential impacts—to occupants and energy markets—are not well understood. We present a case-study analysis of the technical potential for residential natural gas demand response in the northeast United States that utilizes diverse whole-building energy simulations and high-performance computing. Our results show that NG-DR applied to residential heating systems during extreme cold-weather conditions could reduce natural gas demand by 1–29% based on conservative and aggressive strategies, respectively. This indicates a potential to improve the resilience of gas and electric systems during stressful events, which we examine by estimating the impact on energy costs and electricity generation from natural gas. We also explore relationships between hourly indoor temperatures, demand response, and building envelope efficiency.

03 NATURAL GAS↗

DOE OSTI2018

Automatic Building Energy Model Creation (AutoBEM) for Urban-Scale Energy Modeling and Assessment of Value Propositions for Electric Utilities

Residential and commercial buildings in the United States consume 73% of all electricity generated. Demand charges (i.e. “peak usage”) can account for 30-70% of a utility bill and continue to grow even as energy prices are decreasing, due largely in part to adoption of intermittent renewables and less efficient, more costly generation assets which must be brought online during peak demand. In order to quantitatively assess business value and either enhance existing or propose new programs for utilities, the ability to detect, generate, and simulate a building energy model has been applied to a 1,385 km2 utility district involving over 160,000 buildings in a smart grid backed by a fiber optic network. The organization operating the electrical distribution and fiber optic networks has prioritized and guided the creation of a virtual utility in order to assess a prioritized list of potential revenue streams and determine the most cost-effective programs for their organization and their rate-payers. We provide an overview of the technical capabilities developed for generally-applicable urban-scale building energy modeling to any geographical area and the utility-defined use cases being assessed.

New, Joshua↗

NASA NTRS2019

A Composite Damage Tolerance Simulation Technique to Augment the Building Block Approach

Aerospace structures comprised of composite materials are traditionally certified empirically via the Building Block Approach (BBA). While this approach has been performed successfully in the past, it is expensive and time consuming. One means to improve the overall efficiency of composite structural certification is to reduce the cost of the BAA by eliminating the need for some tests by incorporating damage analysis tools. For an analysis to replace a given test, the tool must first be validated using other similar test data. The subject of this paper is a description of an analysis technique for simulating compression after damage strength of a solid laminate. The analysis technique is one that is practical for use in an applied engineering context due to efforts to minimize necessary computational resources and complexity of the model.

McElroy, Mark↗

DOE OSTI2014

Energy Evaluation of a New Construction Pilot Community: Fresno, California

A new construction pilot community was constructed by builder-partner Wathen-Castanos Hybrid Homes (WCHH) based on a single occupied test house that was designed to achieve greater than 30% energy savings with respect to the House Simulation Protocols (Hendron, Robert; Engebrecht, Cheryn (2010). Building America House Simulation Protocols. Golden, CO: National Renewable Energy Laboratory). Builders face several key problems when implementing a whole-house systems integrated measures package (SIMP) from a single test house into multiple houses. Although a technical solution already may have been evaluated and validated in an individual test house, the potential exists for constructability failures at the community scale. This report addresses factors of implementation and scalability at the community scale and proposes methodologies by which community-scale energy evaluations can be performed based on results at the occupied test house level. Research focused on the builder and trade implementation of a SIMP and the actual utility usage in the houses at the community scale of production. Five occupants participated in this community-scale research by providing utility bills and information on occupancy and miscellaneous gas and electric appliance use for their houses. IBACOS used these utility data and background information to analyze the actual energy performance of the houses. Verification with measured data is an important component in predictive energy modeling. The actual utility bill readings were compared to projected energy consumption using BEopt with actual weather and thermostat set points for normalization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗

NASA NTRS2019

A Composite Damage Tolerance Simulation Technique to Augment the Building Block Approach

Aerospace structures comprised of composite materials are traditionally certified empirically via the Building Block Approach (BBA). While this approach has been performed successfully in the past, it is expensive and time-consuming. One means to improve the overall efficiency of composite structural certification is to reduce the cost of the BBA by eliminating the need for some tests by incorporating damage analysis tools. For an analysis to replace a given test, the tool must first be validated using other similar test data. The subject of this paper is a description of an efficient analysis technique for simulating compression after damage strength of a solid laminate. The analysis technique is one that is practical for use in an applied engineering context due to efforts to minimize necessary computational resources and complexity of the model.

McElroy, Mack↗

DOE OSTI2015

Assessment of the Potential to Achieve very Low Energy Use in Public Buildings in China with Advanced Window and Shading Systems

As rapid growth in the construction industry continues to occur in China, the increased demand for a higher standard living is driving significant growth in energy use and demand across the country. Building codes and standards have been implemented to head off this trend, tightening prescriptive requirements for fenestration component measures using methods similar to the U.S. model energy code American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1. The objective of this study is to (a) provide an overview of applicable code requirements and current efforts within China to enable characterization and comparison of window and shading products, and (b) quantify the load reduction and energy savings potential of several key advanced window and shading systems, given the divergent views on how space conditioning requirements will be met in the future. System-level heating and cooling loads and energy use performance were evaluated for a code-compliant large office building using the EnergyPlus building energy simulation program. Commercially-available, highly-insulating, low-emittance windows were found to produce 24%–66% lower perimeter zone HVAC electricity use compared to the mandated energy-efficiency standard in force (GB 50189-2005) in cold climates like Beijing. Low-e windows with operable exterior shading produced up to 30%–80% reductions in perimeter zone HVAC electricity use in Beijing and 18%–38% reductions in Shanghai compared to the standard. The economic context of China is unique since the cost of labor and materials for the building industry is so low. Broad deployment of these commercially available technologies with the proper supporting infrastructure for design, specification, and verification in the field would enable significant reductions in energy use and greenhouse gas emissions in the near term.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Multizonal modeling of SARS-CoV-2 aerosol dispersion in a virtual office building

The dispersion of indoor airborne contaminants across different zones within a mechanically ventilated building is a complex phenomenon driven by multiple factors. In this study, we modeled the indoor dispersion of airborne SARS-CoV-2 aerosols within a US Department of Energy detailed medium office prototype building using CONTAM software. The aim of this study is to improve our understanding about how different parts of a building can experience varying concentrations of the airborne viruses under different circumstances of release and mitigation strategies. Results indicate that unventilated stairwells can have significantly higher concentrations of airborne viruses. The mitigation strategies of morning and evening flushing of conditioned zones were not found to be very effective. Instead, a constant high percentage of outdoor air in the supply mix, and the use of masks, portable HEPA air cleaners, MERV 13 or higher HVAC air filters, and ultraviolet germicidal irradiation disinfection were effective strategies to prevent airborne viral contamination in the majority of the simulated office building.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

A Forward Time Stepping Heat Conduction Model for Spot Melt Additive Manufacturing

Solidification dynamics are crucial for determining microstructure development in additively manufactured parts. Multiphysics models based on finite element or finite volume methods may help gain insight for complicated phenomena such as fluid flow, keyholing, and porosity but are too computationally expensive to use for simulating actual builds. Recent analytic and semi-analytic solutions for moving heat sources in a semi-infinite three-dimensional space provide a way to accurately estimate the solidification conditions for entire builds. The downside to these methods is that, unlike finite element or finite volume methods, they cannot use the temperature distribution of the previous timesteps to march the solution forward in time. This paper provides the mathematical formulation and implementation of a forward time stepping (FTS) approach to an existing semi-analytic solution. The speed and accuracy of the two methods are then compared for various scan patterns. The result is that, for spot melts, the forward time-stepping model provides improvements in both speed and accuracy. This is especially true for longer simulations, where the simulation can be orders of magnitude faster. Finally, the longest simulation analyzed in this paper was roughly 30× faster when using the forward time-stepping model versus the straightforward implementation of the semi-analytic solution.

36 MATERIALS SCIENCE↗