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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 721 records · Page 40

Thermal Performance of Aged and Weathered Spray-On Foam Insulation (SOFI) Materials Under Cryogenic Vacuum Conditions (Cryostat-4)

The NASA Cryogenics Test Laboratory at Kennedy Space Center conducted long-term testing of SOFI materials under actual-use cryogenic conditions with Cryostat-4. The materials included in the testing were NCFI 24-124 (acreage foam), BX-265 (close-out foam, including intertank flange and bipod areas), and a potential alternate material, NCFI 27-68, (acreage foam with the flame retardant removed). Specimens of these materials were placed at two locations: a site that simulated aging (the Vehicle Assembly Building [VAB]) and a site that simulated weathering (the Atmospheric Exposure Test Site [beach site]). After aging/weathering intervals of 3, 6, and 12 months, the samples were retrieved and tested for their thermal performance under cryogenic vacuum conditions with test apparatus Cryostat-4.

Source record↗

Cryogenic Moisture Analysis of Spray-On Foam Insulation (SOFI)

The NASA Cryogenics Test Laboratory at Kennedy Space Center conducted long-term testing of SOFI materials under actual-use cryogenic conditions. The lab tested NCFI 24-124 (acreage foam), BX-265 (close-out foam, including intertank flange and bipod areas), and a potential alternate material, NCFI 27-68 (acreage foam with the flame retardant removed). Specimens of all three materials were placed at a site that simulated aging (the Vehicle Assembly Building [VAB]) and a site that simulated weathering (Atmospheric Exposure Test Site [beach site]). After aging/ weathering intervals of 3, 6, and 12 months, the samples were retrieved and tested for their ability to absorb moisture under conditions similar to those experienced by the Space Shuttle External Tank (ET) during the loading of cryogenic propellants.

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Accuracy of a Crude Approach to Urban Multi-Scale Building Energy Models Compared to 15-min Electricity Use

ASHRAE has recently named a TC4.7 subcommittee on Multi-Scale Energy Modeling and there have been many technical developments focused on urban-scale energy modeling with the goal of creating building energy models for all buildings in a city to facilitate simulation-informed energy optimization for the built environment. These efforts often rely on non-scalable, local sources of information (e.g. county’s tax assessor’s database) to create more accurate models of those buildings. In partnership with the local utility, a year’s worth of real-world 15-minute electrical use data from 178,377 premise buildings has been assessed. This smart meter data is statistically analyzed and compared to corresponding simulation data for 97 different building prototypes in order to better assess simulation accuracy for various utility-defined use cases. To our knowledge, this is the first time real world and simulated building energy use data have been compared at this scale.

Garrison, Eric↗

Validation and moisture content sensitivity analysis of cross-laminated timber wall assemblies in EnergyPlus

Cross-laminated timber buildings are becoming more common in North America, with many numerical studies showing potential energy savings. However, no studies have validated any EnergyPlus heat transfer algorithms or quantified their accuracy in simulating CLT in building envelopes. This study empirically validates the heat flux predictions for each of EnergyPlus's heat transfer algorithms (Conduction Transfer Functions (CTF), Effective Moisture Penetration Depth (EMPD), Conduction Finite Difference (CondFD), and Heat and Moisture Transfer (HAMT)) for two different CLT ply thicknesses with both summer and winter boundary conditions measured in controlled lab experiments. It also evaluates the model sensitivity of heat flux and heating and cooling loads to moisture content. The 1D validation shows that the HAMT model is the most accurate among all algorithms. All EnergyPlus's heat flux predictions are accurate independent of CLT plate thickness for summer conditions. However, the three constant property algorithms (CTF, EMPD, and CondFD) underpredict heat flux throughout the whole day during winter conditions. The 1D sensitivity analysis indicates that elevated moisture content can increase peak heat fluxes through the material by up to 20 %. Finally, the whole building model sensitivity analysis shows increased heating load and slight cooling load variation due to increased moisture content when using constant property models. The analysis shows significantly lower peak thermal demand (7 % lower heating and 6 % lower cooling) and monthly thermal load (8 % less cooling and 6 % less heating) predictions when using HAMT vs a constant property model.

42 ENGINEERING↗

Simulating "Mars on Earth"

By now, everyone who's heard of the Haughton-Mars Project knows that we travel to Devon Island to learn how people will live and work on Mars. But how do we learn about Mars operations from what happens in the Arctic? We must document our experience--traverses, life in the hab, instrument deployment, communications, and so on. Then we must analyze and formally model what happens. In short, while most scientists are studying the crater, other scientists must be studying the expedition itself. That's what I have done in the past four field seasons. I study field science, both as it naturally occurs at Haughton (unconstrained by a "Mars Sam") and as a constrained experiment using the Flashline Mars Arctic Research Station. During the second week of July 2001, I lived and worked in the hab as part of the Phase 2 crew of six. Besides participating in all activities, I took many photographs and time lapse video. The result of my work will be a computer simulation of how we lived and worked in the hab. It won't be a model of particular people or even my own phase per se, but a pastiche that demonstrates (a proof of concept) that we have appropriate tools for simulating the layout of the hab and daily routines followed by the group and individual scientists. Activities-how people spend their time-are the focus of my observations for building such a simulation model.

Clancey, William J.↗

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis

Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.

14 SOLAR ENERGY↗

A Simulation Resource Team for Innovative Fusion Concepts

This project created a shared simulation resource for innovative fusion concepts at the University of Rochester, built around the FLASH, TriForce, OSIRIS, and OSHUN codes. Many promising fusion approaches are too complex to evaluate by experiment alone yet building a custom simulation capability from scratch for each new concept is expensive and slow. The BETHE Simulation Resource Team addressed this problem by developing and validating a flexible set of numerical tools, which were then applied across three major concept areas: plasma-jet-driven magneto-inertial fusion, staged Z pinches, and field-reversed configurations. The team assisted three concept teams and carried out independent analyses of all three concepts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LIQUIDARMOR CM Flashing and Sealant, High Impact Technology Demonstration

Air leakage is responsible for about 1.1 quads of energy or 6% of the total energy used by commercial buildings in the US. Consequently, infiltration and exfiltration are among the largest envelope-related contributors to the heating, ventilation, and air conditioning loads in commercial buildings. New air sealing technologies have recently emerged that aim to improve the performance of air barrier systems by simplifying their installation procedure. LIQUIDARMORTM CM Flashing and Sealant is an example of these new advanced material technologies. This technology is a spray-applied sealant and liquid flashing and can span gaps that are up to ¼ in. wide without a supporting material. ORNL verified the performance of LIQUIDARMORTM CM with field tests and energy simulations from a building in which LIQUIDARMORTM CM was one of components of the air barrier system. The Homeland Security Training Center (HTC) at the College of DuPage in Glen Ellyn, IL, served as the demonstration site. Blower door test results show the average air leakage rate in the demonstration site to be 0.15 cfm/ft2 at 1.57 psf, or 63% lower than the 0.4 cfm at 1.57 psf specified in the 2015 International Energy Conservation Code (IECC). According to simulation results, HTC lowered its annual heating and cooling cost by about $3,000 or 9% compared to a similar building that lacked an air barrier system. This demonstration project serves as an example of the level of building envelope airtightness that can be achieved by using air barrier materials that are properly installed, and illustrates the energy and financial savings that such an airtight envelope could attain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

In-Depth Modeling and Simulation Analysis of Artemis Missions Using the Impact Probabilistic Risk Assessment Tool

BACKGROUND The Artemis campaign is a Moon exploration program with a series of six planned missions, five of which will be crewed. These five crewed missions will contain a single mission segment (space flight), or multiple mission segments involving space flight (Orion), lunar landing (LTV) and/or space habitat (Gateway). Each crewed segment faces the risk of unique medical conditions, necessitating medical sets/kits tailored to those specificities. To support and enable a data-driven and evidence-based decision-making process through out a mission’s life cycle, a software tool called IMPACT was developed. Using probabilistic risk assessment (PRA) methodologies, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a novel tool built for analyzing the possibility of encountering complex medical risks during space flight, and for identifying the medical resources and capabilities needed to treat those potential at-risk medical conditions. IMPACT achieves this by performing hundreds of thousands of Monte Carlo simulations of missions to build aggregate pictures of medical risk. During an extended simulation modeling phase, IMPACT generated analytical results for medical risks, and the medical resources and capabilities to address those risks, for every segment of every crewed Artemis mission. This presentation will highlight the reliability, consistency and validity of IMPACT’s computational modeling techniques and will showcase the library of analytical outcomes generated for the Artemis missions. OVERVIEW During the early stages of IMPACT’s design, architecture and technical requirements collection, “scenarios” (use cases) - achievement goals required for acceptance testing, were identified by stakeholders. IMPACT successfully completed the scenario testing requirements and undertook an extensive operational run phase utilizing a wide range of input combinations with a goal of delivering a cohesive, trustworthy, reliable, vast, and diverse body of evidence. The intent of these modeling runs was to validate consistency in output, ensure solidity of executable operations and to streamline processes by identifying areas requiring efficiency improvements. Using the many missions of Artemis, IMPACT ran variations of operational runs to assess the output for acceptable, as well as unusual characteristics. This rigorous long-term “shakedown” analysis was implemented to help build a collective body of evidence to aid in securing a high level of confidence, reliability, and validity in the output, whether from the applicational components of IMPACT, or the entirety of the operational process. ANTICIPATED ANALYSIS AND CONCLUSION This presentation will discuss the various categories of input criteria; the comparisons in the application of these input criteria to various Artemis missions; the preparation and collection of the body of evidence, and reliability of the computational modeling techniques. This paper serves as an initial analytical overview of IMPACT’s probabilistic risk assessment (PRA) medical risk outputs covering Artemis missions and is not intended to be deemed the official medical response for the Artemis campaign.

Crew Composition↗

Adaptive smart simulator for characterization and MPPT construction of PV array

Partial shading conditions are among the most important problems in large photovoltaic array. Many works of literature are interested in modeling, control and optimization of photovoltaic conversion of solar energy under partial shading conditions, The aim of this study is to build a software simulator similar to hard simulator and to produce a shading pattern of the proposed photovoltaic array in order to use the delivered information to obtain an optimal configuration of the PV array and construct MPPT algorithm. Graphical user interfaces (Matlab GUI) are built using a developed script, this tool is easy to use, simple, and has a rapid of responsiveness, the simulator supports large array simulations that can be interfaced with MPPT and power electronic converters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Full Core TREAT Kinetics Demonstration Using Rattlesnake/BISON Coupling Within MAMMOTH

This report summarizes key aspects of research in evaluation of modeling needs for TREAT transient simulation. Using a measured TREAT critical measurement and a transient for a small, experimentally simplified core, Rattlesnake and MAMMOTH simulations are performed building from simple infinite media to a full core model. Cross sections processing methods are evaluated, various homogenization approaches are assessed and the neutronic behavior of the core studied to determine key modeling aspects. The simulation of the minimum critical core with the diffusion solver shows very good agreement with the reference Monte Carlo simulation and the experiment. The full core transient simulation with thermal feedback shows a significantly lower power peak compared to the documented experimental measurement, which is not unexpected in the early stages of model development.

97 MATHEMATICS AND COMPUTING↗

Thermo-chemical Fluid Flow Simulation in Hot-Dip Galvanizing: The Evaluation of Dross Build-Up Formation

This paper presents a new computational framework to investigate the driving force for the formation of intermetallic dross particles in the zinc bath and dross build-up on the bath hardware. This is a major problem in continuous hot-dip galvanizing lines. The Computational Fluid Dynamics (CFD) model calculates the turbulent thermo-chemical flow conditions within the liquid melt. A detailed modeling of the steel strip–liquid interface enhances this approach, by means of a conjugated heat transfer calculation and a spatially resolved, temperature- and concentration-dependent iron dissolution and aluminum uptake. The heart of the computational framework is a thermodynamic model, which assesses the driving force for the formation or dissolution of dross particles in the bath and dross build-up on stationary and rotating equipment. The simulation results are validated with temperature and species depth profile measurements. The applicability of the CFD model is shown by investigating the locally resolved aluminum uptake and iron dissolution at the steel-strip surface, and the multi-physics conditions in the region near the roll. The novel approach of evaluating the thermodynamic driving force enables the assessment of the formation of dross build-up at the roll surface.

36 MATERIALS SCIENCE↗

Fast Transverse Beam Instability Caused by Electron Cloud Trapped in Combined Function Magnets

Electron cloud instabilities affect the performance of many circular high-intensity particle accelerators. They usually have a fast growth rate and might lead to an increase of the transverse emittance and beam loss. A peculiar example of such an instability is observed in the Fermilab Recycler proton storage ring. Although this instability might pose a challenge for future intensity upgrades, its nature had not been completely understood. The phenomena has been studied experimentally by comparing the dynamics of stable and unstable beam, numerically by simulating the build-up of the electron cloud and its interaction with the beam, and analytically by constructing a model of an electron cloud driven instability with the electrons trapped in combined function dipoles. Stabilization of the beam by a clearing bunch reveals that the instability is caused by the electron cloud, trapped in beam optics magnets. Measurements of microwave propagation confirm the presence of the cloud in the combined function dipoles. Numerical simulations show that up to 10$^{-2}$ of the particles can be trapped by their magnetic field. Since the process of electron cloud build-up is exponential, once trapped this amount of electrons significantly increases the density of the cloud on the next revolution. In a combined function dipole this multi-turn accumulation allows the electron cloud reaching final intensities orders of magnitude greater than in a pure dipole. The estimated fast instability growth rate of about 30 revolutions and low mode frequency of 0.4 MHz are consistent with experimental observations and agree with the simulations. The created instability model allows investigating the beam stability for the future intensity upgrades.

43 PARTICLE ACCELERATORS↗

How will United States commercial building energy use be impacted by IPCC climate scenarios?

Climate change and anthropogenically-forced shift of weather in the future will impact energy use and resilience of both the built environment and the electric grid. The aim of this analysis is to understand how future climate scenarios will impact electricity and natural gas use of commercial buildings in the United States. Here, this study analyzes this impact for 2030, 2045, and 2100 using Representative Concentration Pathways (RCP) scenarios defined in Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5. The large, gridded simulation of meteorological variables for RCPs 2.6, 4.5, 6.0, and 8.5 are selected and downscaled to make available hourly Future Meteorological Year (FMY) weather files for use and improvement in subsequent studies. High performance computing resources use these FMYs to simulate commercial prototype buildings in every American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) climate zone of the United States (US), and results are scaled to nation-wide energy use using conditioned floor area multipliers. The analysis is conducted without speculating the physical and performance traits of future buildings or the grid characteristics. This analysis quantifies the impact of climate change on source electrical and natural gas usage for commercial buildings in the United States over the next 80 years. If US commercial floorspace remained constant, total energy use by 2100 is predicted between an 1.75% decrease under the greatest emission scenario (8.5) and a 1.76% increase under the lowest emission scenario (2.6). When adjusted for anticipated urban growth by 2100, the predicted range is 65% increase (8.5) and 71% increase (2.6). Under a global temperature rise climate scenario, the warmest US climate zones will see a large increases in electricity use derived from space cooling while the coldest US climate zones will see significant decreases in natural gas use caused by the decrease in heating necessary. While climate change may ultimately require adaptations of the built environment to withstand its effects and because the United States is a country that requires more heating than cooling, from a building energy perspective, climate change (average temperature rise) is a net energy saver for the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fusion RF Modeling Machine Learning (FusionML_RF) v1.0

FusionML_RF consists of multiple codes and trained machine learning (ML) models that perform low-cost output modeling from the Genray-CQL3D. Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. For example, completing a single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time. On the other hand, these ML models achieve ~ms of inference time with high accuracy across the input parameter space. This software collection consists of multiple components. (1) codes that use ML methods and precomputed Genray-CQL3D simulation output to build regression models that enable approximate computations of Genray-CLQ3D outputs from arbitrary but physically meaningful input parameters (surrogate modeling); (2) three trained models created by the team, using a database of 16,000+ GENRAY/CQL3D simulations, to study the performance of ML models for surrogate modeling; (3) codes that load the trained models and simulation data, and then compute mean squared error between the models' predictions and the ground truth of simulation output data. This collection is being made available in conjunction with a scientific publication about the work to promote reusability and provide an artifact of the scientific work.

Bai, Zhe↗

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗

Passive cooling designs to improve heat resilience of homes in underserved and vulnerable communities

Disadvantaged communities face a growing threat to staying safe during heat waves, especially during coincident power outages. This study develops a methodology to evaluate the effectiveness of passive cooling measures (those that operate without power) to improve residential building heat resilience. Building performance is simulated for representative homes and on district scales in two disadvantaged communities in Fresno, California. Eleven passive measures are evaluated using four heat resilience metrics with and without grid power. Results show performance of the mitigation measures varies by building characteristics, surrounding environment, and power scenario. The two most effective measures were installing solar-control window films and adding roof insulation. For pre-1978 single-family homes, these two measures can reduce unmet degree-hours (UDH) indoors by 12% and 11% respectively without grid power, or 28% and 37% with grid power. Their respective UDH reductions at district scale typically range 8% — 20% and 4% — 12% without grid power, or 14% — 44% and 8% — 51% with grid power. Top floors have higher overheating risk than lower floors during extreme heat events with coincident power outages. Natural ventilation can help, reducing UDH by 21% — 26%. The methodology and findings from this study can help cities, communities, and utilities develop effective and targeted strategies to promote greater residential heat resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects

As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.

force field↗