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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14

Community Geothermal: Soil Conductivity, Borehole Design, Energy Models, and Load Data for a Residential System Development - Hinesburg, VT

This dataset contains materials from the Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES) project, which evaluated the techno-economic feasibility of a community geothermal system for a residential development in Hinesburg, VT. The dataset includes detailed soil conductivity test reports, energy models, borehole design reports, hourly energy loads for heating, cooling, and hot water, and design layouts. EnergyPlus was used to model building energy loads, and Modelica software was applied for geothermal loop sizing based on these loads and soil conductivity results. Python scripts for network design further refined the models. Key files include PDF reports on borehole design (with projections for 1-year, 15-year, and 30-year systems), soil conductivity test results, EnergyPlus modeling outputs, and 2D/3D design drawings in PDF, DWG, and DXF formats. Python notebooks for network design and OnePipe model files are also provided, with Modelica required for viewing certain files. Outputs and modeling data are in various formats including CSV, JPG, HTML, and IDF, with units and data clearly labeled to support understanding of system design and performance for the proposed geothermal solution.

15 GEOTHERMAL ENERGY↗

A dataset of cyber-induced mechanical faults on buildings with network and buildings data

We have collected data of cyber-induced mechanical faults on buildings using a simulation platform. A DOE reference building model was used for running the simulation under a Rogue device attack and collected the network data as well as the physical buildings data to better understand the impacts of cyber attacks on the building and help identify the source of the mechanical fault with the network data. Alfalfa is the tool used for simulating the DOE reference buildings and acts as an interface to the model for querying the status and providing input externally. The Building Automation System (BAS) is the centralized controller providing control commands to other BACnet devices on the network based on the building status received from Alfalfa. The BACnet devices like damper will listen for the control commands from BAS on the BACnet network and implement it. The attacker is the malicious actor on the network creating disruptions by placing cyber-attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Solar+Storage for Household Back-up Power: Implications of building efficiency, load flexibility, and electrification for backup during long-duration power interruptions [Slides]

The study analyzes the evolving role of solar+storage for home backup power during long-duration power interruptions. In particular, it evaluates how required storage sizing is impacted as homes become more efficient, flexible, and electrified. The study relies on NREL’s ResStock building modeling platform to create statistically representative distributions of the existing building stock in ten locations across the United States. It then shows how the amount battery storage required for backup power rises or falls as a series of building envelope efficiency, load flexibility, and electrification measures are applied across the building stock in each region. The study also includes sensitivities to show how backup power requirements are impacted by the timing and duration of power interruptions, and explores variation in backup power requirements across the building stock within each study location. The results demonstrate the value of pairing solar+storage with efficiency upgrades, smart home controls, and (in mild winter climates) efficient heat pump retrofits. That value comes in the form of reducing the amount of storage required and/or extending the range of interruption conditions over which a given system can provide backup power (i.e., more extreme weather and/or longer interruptions). Heat pumps in cold-weather climates can pose a challenge for solar+storage backup power, given the amount of storage required, though are a vast improvement over electric-resistance heating. Retaining existing fossil-based heating systems for occasional use during power interruptions, as either the primary or supplementary source of heat, can mitigate this challenge. Other forms of building electrification (e.g., cooking and water heating) generally have marginal impacts on backup battery sizing, given their relatively small energy demand.

14 SOLAR ENERGY↗

A Semi-Detailed Pyrolytic Gas-Phase Kinetic Model for the Volatiles of Polyethylene Thermal Degradation

This work presents a semi-detailed kinetic model to address the pyrolytic gas-phase reactivity of volatiles formed during thermal degradation of polyethylene (PE). The model builds on a validated multi-step condensed-phase model and employs validated lumping approaches. Short-chain compounds are modelled with high detail, while long-chain ones are described by surrogate species representative of diesel-cuts (NC16H32) and waxes (NC30H60). The reactivity of short chains is described through the comprehensive CRECK kinetic model, updated to align C5-C7 olefins based on recent literature experimental data. Due to the lack of experimental data for longer olefins, their reactivity is modeled by analogy to the shorter ones, ensuring an asymptotic behavior with increasing carbon numbers. The semi-detailed model is validated through experimental data on PE pyrolysis, assuming an instantaneous mixing of the inert inlet flow with released volatiles, followed by a segregated plug-flow behavior. Validation across different reactor setups confirms the model’s capability to predict detailed product distributions. Despite minor discrepancies, the proposed model effectively captures experimental trends. Further work will address modelling the reactivity in oxygen-containing environments.

kinetics↗

Wakes from arrays of buildings

Experiments were carried out in a small wind tunnel in which atmospheric flow around buildings was simulated. Arrays of one, two, three, and four model buildings were tested, and wake profiles of velocity and turbulence were measured. The data indicate the effect of the buildings on the wind environment encountered by aircraft during landing or takeoff operations. It was possible to use the results to locate the boundaries of the air regions affected by the obstacles and to recommend preferred arrangements of buildings to maximize light safety.

Logan, E., Jr.↗

Wakes from arrays of buildings

Experiments were carried out in a small wind tunnel in which atmospheric flow around buildings was simulated. Arrays of one, two, three, and four model buildings were tested, and wake profiles of velocity and turbulence were measured. The data indicate the effect of the buildings on the wind environment encountered by aircraft during landing or takeoff operations. It was possible to use the results to locate the boundaries of the air regions affected by the obstacles and to recommend preferred arrangement of buildings to maximize light safety. Previously announced in STAR as N83-14430

Logan, E., Jr.↗

Open Innovation for a NASA Architecture Library

NASA’s Center of Excellence for Collaborative Innovation (CoECI) uses open innovation, or “crowdsourcing”, to access the global public to find ideas, concepts, designs, or solutions that meet a previously unmet need possibly resulting in significant advances in performance. The Center of Excellence for Collaborative Innovation was launched at the request of the White House Office of Science and Technology Policy. This is both a non-traditional method of innovation and a non-traditional method of outreach to the public to involve them in space technologies and programs. It has been used often for software development and new hardware technology. In this case we applied it to innovate with systems engineering tools for creating space architectures. The challenge was sponsored by NASA Engineering and Safety Center Systems Engineering Technical Fellow as part of a program for NASA’s adoption of MBSE. It was a trial to see if there would be as much participation or quality submissions with this more specialized topic and skill. The challenge sought space architecture representations and decompositions to create a library of modeled parts in a system modeling language (SysML). Mission architects mostly start from scratch to build model elements representing the functional and physical architecture of a system in SysML. There are a few beginning libraries, but these are also local to a program or group. A common library will save system engineers a large amount of time, will allow project stakeholders to recognize common graphics and quickly understand the architecture options. The challenge was promoted internationally, especially through professional organizations and universities with a systems engineering focus. It was open for 4 months, purposefully over the winter holiday break time to allow participants extra time outside of work or school. The challenge was designed so that expertise in space hardware was not necessary but getting to play with models of space architecture could provide motivation to participate. We did not receive as many entries as other broader outreach challenges, but the ones we received were extremely thorough and high quality. Solutions came from individuals and teams, students and professional consultants from the United States and Europe. We learned a few lessons about how to engage with the public and what characteristics of a problem result in good crowdsourcing results. The outreach challenge produced several useful ideas and modeled space elements, and the group will be engaging the winners to learn more about their new approaches.

innovation↗

A Semi-Detailed Pyrolytic Gas-Phase Kinetic Model for the Volatiles of Polyethylene Thermal Degradation

This work presents a semi-detailed kinetic model to address the pyrolytic gas-phase reactivity of volatiles formed during thermal degradation of polyethylene (PE). The model builds on a validated multi-step condensed-phase model and employs validated lumping approaches. Short-chain compounds are modelled with high detail, while long-chain ones are described by surrogate species representative of diesel-cuts (NC16H32) and waxes (NC30H60). The reactivity of short chains is described through the comprehensive CRECK kinetic model, updated to align C5-C7 olefins based on recent literature experimental data. Due to the lack of experimental data for longer olefins, their reactivity is modeled by analogy to the shorter ones, ensuring an asymptotic behavior with increasing carbon numbers. The semi-detailed model is validated through experimental data on PE pyrolysis, assuming an instantaneous mixing of the inert inlet flow with released volatiles, followed by a segregated plug-flow behavior. Validation across different reactor setups confirms the model’s capability to predict detailed product distributions. Despite minor discrepancies, the proposed model effectively captures experimental trends. Further work will address modelling the reactivity in oxygen-containing environments.

kinetics↗

Applications of Artificial Neural Networks in Structural Engineering with Emphasis on Continuum Models

The use of continuum models for the analysis of discrete built-up complex aerospace structures is an attractive idea especially at the conceptual and preliminary design stages. But the diversity of available continuum models and hard-to-use qualities of these models have prevented them from finding wide applications. In this regard, Artificial Neural Networks (ANN or NN) may have a great potential as these networks are universal approximators that can realize any continuous mapping, and can provide general mechanisms for building models from data whose input-output relationship can be highly nonlinear. The ultimate aim of the present work is to be able to build high fidelity continuum models for complex aerospace structures using the ANN. As a first step, the concepts and features of ANN are familiarized through the MATLAB NN Toolbox by simulating some representative mapping examples, including some problems in structural engineering. Then some further aspects and lessons learned about the NN training are discussed, including the performances of Feed-Forward and Radial Basis Function NN when dealing with noise-polluted data and the technique of cross-validation. Finally, as an example of using NN in continuum models, a lattice structure with repeating cells is represented by a continuum beam whose properties are provided by neural networks.

Kapania, Rakesh K.↗

Aggregation and data driven identification of building thermal dynamic model and unmeasured disturbance

An aggregate model is a single-zone equivalent of a multi-zone building, and is useful for many purposes, including model based control of large heating, ventilation and air conditioning (HVAC) equipment. This paper deals with the problem of simultaneously identifying an aggregate thermal dynamic model and unknown disturbances from input–output data of multi-zone buildings. The unknown disturbance is a key challenge since it is not measurable but non-negligible. In this paper, we first present a principled method to aggregate a multi-zone building model into a single zone model, and show the aggregation is not as trivial as it has been assumed in the prior art. We then provide a method to identify the parameters of the model and the unknown disturbance for this aggregate (single-zone) model. Finally, we test our proposed identification algorithm to data collected from a multi-zone building testbed in Oak Ridge National Laboratory. A key insight provided by the aggregation method allows us to recognize under what conditions the estimation of the disturbance signal will be necessarily poor and uncertain, even in the case of a specially designed test in which the disturbances affecting each zone are known (as the case of our experimental testbed). This insight is used to provide a heuristic that can be used to assess when the identification results are likely to have high or low accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A high-fidelity building performance simulation test bed for the development and evaluation of advanced controls

We present an open-source building performance simulation test bed, the Advanced Controls Test Bed (ACTB), that interfaces high-fidelity Spawn of EnergyPlus building models, with advanced controllers implemented in Python. Additionally, the ACTB leverages the Building Optimization Testing and Alfalfa platforms for managing simulations, providing an external clock, a representational state transfer (REST) application programming interface (API), and key performance indicators for evaluating the effectiveness of control strategies. The REST API allows the development of external controllers programmed in languages such as Python, which provides flexibility and a rich choice of scientific libraries for designing control sequences. We present three test cases based on the U.S. Department of Energy's Reference Small Office Building to demonstrate the ACTB's capabilities: (a) rule-based controls compliant with ASHRAE Guideline 36 control sequences; (b) an economic model predictive control implemented using do-mpc; and (c) a deep Q-network reinforcement learning agent implemented using OpenAI Gym.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integration of Electric Vehicle Charging Loads in Residential Building Stock Energy Modeling

The rapid adoption of electric vehicles (EVs) has resulted in significant new household electric loads that have the potential to change how energy costs are incurred by homeowners and the landscape of utility operations and energy infrastructure. Whereas adoption patterns and magnitudes of residential building and EV charging loads are influenced by distinct factors, the loads themselves are tightly coupled with the behavior of the individual occupants and EV owners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Resolving the ($\mathscr{g}$-2)$_μ$ discrepancy with $\mathcal{F}$–SU(5) intersecting D-branes

A discrepancy between the measured anomalous magnetic moment of the muon (g - 2) μ and computed Standard Model value now stands at a combined 4.2σ following experiments at Brookhaven National Lab (BNL) and the Fermi National Accelerator Laboratory (FNAL). A solution to the disagreement is uncovered in flipped SU(5) with additional TeV-Scale vector-like 10 +$\bar{10}$ multiplets and charged singlet derived from local F-Theory, collectively referred to as $\mathcal {F}$-SU(5). Here we engage general No-Scale supersymmetry (SUSY) breaking in $\mathcal {F}$-SU(5) D-brane model building to alleviate the (g-2)μ. tension between the Standard Model and observations. A robust Δa μ (SUSY) is realized via mixing of M 5 and M 1X at the secondary SU(5) x U(1) X unification scale in $\mathcal {F}$-SU(5) emanating from SU(5) breaking and U(1) X flux effects. Calculations unveil Δa μ (SUSY) = 19.0-22.3 x 10 -10 for gluino masses of M($\tilde{g}$ = 2.25-2.56 TeV nd higgsino dark matter, aptly residing within the BNL+FNAL 1σ mean. This (g – 2)μ favorable region of the model space also generates the correct light Higgs boson mass and branching ratios of companion rare decay processes, and is further consistent with all LHC Run 2 constraints. Finally, we also examine the heavy SUSY Higgs boson in light of recent LHC searches for an extended Higgs sector.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analysis of strategies to meet ASHRAE S241 infectious aerosol control targets by space type and region using EnergyPlus™ simulations

Professional organizations, such as ASHRAE, have recently proposed new voluntary standards for controlling infectious aerosols. Specifically, ASHRAE Standard 241 (S241) defines equivalent clean air targets for a range of space types that can be met through combinations of mitigation measures. This paper seeks to inform the selection of measures by space type and climate zone through building simulations that quantify the impacts of increased outdoor air ventilation; increasing filtration and/or adding germicidal ultraviolet (GUV) in the central heating, ventilation, and air-conditioning (HVAC) systems; or using portable air cleaners (PACs), upper room GUV, or whole room GUV approaches to increase equivalent clean air delivery. The measures are assessed individually and in practical combinations for their ability to meet S241 in four space types (offices, classrooms, dining areas, and healthcare waiting rooms) using prototype buildings modeled using EnergyPlus. The mitigation measures are compared holistically against baseline building operations using metrics for equivalent clean air, energy, and comfort. The results in this study show that single measures can meet S241 for offices with minimal impacts on energy and comfort, while either upper room GUV systems or combinations of measures such as MERV 13 HVAC filtration with PACs are needed to meet S241 for classrooms. The dining area and healthcare waiting room targets cannot be met in this study when assuming design occupancy and MS2 as the challenge agent, even when combining multiple measures together. This paper provides valuable considerations when designing measures to meet S241 for a range of spaces and scenarios.

GUV↗

Automating Traffic Microsimulation from SYNCHRO UTDF to SUMO

Modern transportation research relies on seamlessly integrating traffic signal data with robust network representation and simulation tools. This study presents utdf2gmns, an open-source Python tool that automates conversion of the Universal Traffic Data Format, including network representation, signalized intersections, and turning volumes into the General Modeling Network Specification (GMNS) Standard. The resulting GMNS-compliant network can be converted for microsimulation in SUMO. By automatically extracting intersection control parameters and aligning them with GMNS conventions, utdf2gmns minimizes manual preprocessing and data loss. utdf2gmns also integrates with the Sigma-X engine to extract and visualize key traffic control metrics, such as phasing diagrams, turning volumes, volume-tocapacity ratios, and control delays. This streamlined workflow enables efficient scenario testing, accurate model building, and consistent data management. Validated through case studies, utdf2gmns reliably models complex urban corridors, promoting reproducibility and standardization. Documentation is available on GitHub and PyPI, supporting easy integration and community engagement.

Luo, Roy [ORNL] (ORCID:0009000312909983)↗

dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]

The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated. All Authors and Contributors are alphabetized in the Developers section with Authors of Code listed first, followed by Contributors and do not reflect equal contributions.

Sigrin, Benjamin↗

dGen™ (Distributed Generation Market Demand Model) [SWR-17-09]

The Distributed Generation Market Demand (dGen™) model is a geospatially rich, bottom-up, market-penetration model that simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the continental United States through 2050. The National Renewable Energy Laboratory (NREL) developed dGen to analyze the key factors that will affect future market demand for distributed solar, wind, storage, and other DER technologies in the United States within a single modeling platform. The dGen model builds on, extends, and provides significant advances over NREL’s SolarDS model (Denholm et al. 2009), which is now deprecated.

Preus, Robert↗

Bim-to-fea Conversion Program

The purpose of this program is to enable interoperability between BIM-based architectural design software (i.e., Revit, ArchiCAD, AVEVA E3D) to structural analysis software (i.e., SAP2000). The program takes in BIM building model data via the IFC file format, automatically transforms the architectural coordination entities (structural beams, columns, slabs, walls) to structural analysis entities (i.e., finite element space frames and shells), automatically adjusts the connectivity of the structural analysis entities, and finally exports the structural analysis entities as a structural analysis model contained within a new IFC file. For example, a 3D building in Revit can be exported to an IFC file, run through this BIM-to-FEA program, then the exported IFC can be inputted into SAP2000.

Crowder, Nicholas [Idaho National Laboratory (INL)↗