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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

FY2012 Annual Progress Report for Vehicle and Systems Simulation and Testing

Annual progress report that evaluates the technologies and performance characteristics of advanced automotive powertrain components and subsystems in an integrated vehicle systems context. These evaluations address light-, medium-, and heavy-duty vehicle platforms. This work is directed toward evaluating and verifying the targets of the VTO R&D teams and to providing guidance in establishing roadmaps for achievement of these goals.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

FY22 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY22. As an extension of the effort from FY21, this year’s work focuses primarily on the two-phase modeling of the NSTF using RELAP5-3D, particularly with the inclusion of the cavity model. The results from simulations were used to compare against experimental data for benchmarking purposes of the RELAP5 deck. Additionally, RELAP5 was used as a predictive tool to guide planned test operations and identify expected system behaviors. In the first part of this report, details are provided of the cavity omitted model where heat flux is applied directly as a boundary condition to the risers. The general trend predicted by the RELAP5 model matches that from the experimental data when a single-phase natural circulation flow is first established, followed by an oscillatory two-phase period and finally a stable two-phase flow. However, the onset of oscillations is predicted early by the model due to the smaller thermal mixing region in the tank. However, by expanding the simulated thermal mixing region in the tank, the onset of oscillations predicted by the model is able to match that from the experiment. These oscillations where studied in depth and are deduced to be flashing-induced instability. The model was then modified to simulate an accident scenario case where a representative heat load based on the full-scale Framatome’s 625 MW t SC-HTGR was applied directly to the riser channels. The simulated initial and boundary conditions were identical to those performed experimentally, facilitating direct comparisons between the predicted and experimental results. It was determined that the results showed some discrepancies remain, likely due to the overprediction of vapor generation rate by the computer model. In the second part of this report, the cavity model is re-introduced where it is observed that the RELAP5 prediction is now able to capture the major trends of the observed flow commonly observed during two-phase conditions. However, the onset of oscillations is once again predicted early by the model, possibly caused by the underprediction of heat loss from the heater and cavity. This is likely due to the omission of support structures in the cavity that can act as additional pathways for heat to escape to the environment. To overcome the underprediction of heat loss, part of the insulation surrounding the cavity side panels and the back of the heaters are removed to allow heat to escape directly to the environment, which then improves the RELAP5 prediction. Parametric studies are also performed to investigate the effects of heater power, tank inventory level, and tank gas space pressure on flow behaviors, also in direct comparison to conditions tested experimentally. User option-61 in the RELAP5-3D input deck, which changes the heat transfer coefficient correlations used for calculating the vapor generation, is also investigated where it is found that by enabling the option, the overall duration of oscillations is increased and matches that from the experiment better. The RELAP5 model is further benchmarked with a header inlet- throttling case where it is observed that the prediction from the model fails to capture some major features observed in the experiment. By using a modified loss coefficient curve for the valve, the accuracy of the prediction is improved where most of the major features observed in the experiment are predicted by the model. Lastly, the model is benchmarked with an inventory depletion scenario where it is observed that despite the modeling limitation of RELAP5, the prediction shows good agreement with the experimental data where major trends and features are captured by the model. Future work will see continued development of the current RELAP5-3D input deck of the NSTF to both improve the accuracy of the model’s predictive capability and continuing serving the experimental program. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2014

WetLab-2: Tools for Conducting On-Orbit Quantitative Real-Time Gene Expression Analysis on ISS

The objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform capable of conducting gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens sampled or cultured on orbit. The project has selected a Commercial-Off-The-Shelf (COTS) qRT-PCR system, the Cepheid SmartCycler and will fly it in its COTS configuration. The SmartCycler has a number of advantages including modular design (16 independent PCR modules), low power consumption, rapid ramp times and the ability to detect up to four separate fluorescent channels at one time enabling multiplex assays that can be used for normalization and to study multiple genes of interest in each module. The team is currently working with Cepheid to enable the downlink of data from the ISS to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project has adapted commercial technology to design a module that can lyse cells and extract RNA of sufficient quality and quantity for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. The WetLab-2 system is capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. The ability to conduct qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples. The system can be used to validate terrestrial analyses of samples returned from ISS by providing on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experiment parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Researchers will also be able to sample multigenerational changes in organisms. Finally, the system can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-7 in June 2015.

quantitative PCR↗
DOE OSTI2023

The Jupiter High-240 Experiment

The Jupiter High-240 experiment was performed in May of 2019 by researchers from Los Alamos National Laboratory (LANL) at the National Criticality Experiments Research Center (NCERC) in the Device Assembly Facility (DAF) located at the Nevada National Security Site (NNSS). This experiment has previously been mentioned briefly in prior publication related to a collaborative effort with the Japan Atomic Energy Agency (JAEA) to assess lead void coefficients of reactivity in uranium- and plutonium-fueled systems with lead. This series of experiments supports JAEA’s research into the development of an accelerator driven transmutation system for spent nuclear fuel. The Jupiter High-240 experiment built upon the previous Jupiter experiment by incorporating plutonium fuel plates with higher 240 Pu content. Efforts to formally benchmark the original Jupiter experiment have continued for inclusion in the benchmark handbook of the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Whereas there is much similarity between the two Jupiter experiments, there is a desire to also evaluate and benchmark this second experiment to further contribute towards the availability of lead-sensitive benchmarks. The components utilized in these two experiments have also been used to perform other subcritical and Rossi-α measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Benchmarking boron carbide equation of state using computation and experiment

Boron carbide ( B 4 C ) is of both fundamental scientific and practical interest due to its structural complexity and how it changes upon compression, as well as its many industrial uses and potential for use in inertial confinement fusion (ICF) and high-energy density physics experiments. Here, we report the results of a comprehensive computational study of the equation of state (EOS) of B 4 C in the liquid, warm dense matter, and plasma phases. Our calculations are cross-validated by comparisons with Hugoniot measurements up to 61 megabar from planar shock experiments performed at the National Ignition Facility (NIF). Our computational methods include path integral Monte Carlo, activity expansion, as well as all-electron Green's function Korringa-Kohn-Rostoker and molecular dynamics that are both based on density functional theory. We calculate the pressure-internal energy EOS of B 4 C over a broad range of temperatures ( ~ 6 × 10 3 – 5 × 10 8 K) and densities (0.025–50 g / cm 3 ). We assess that the largest discrepancies between theoretical predictions are ≲ 5 % near the compression maximum at 1– 2 × 10 6 K. This is the warm-dense state in which the K shell significantly ionizes and has posed grand challenges to theory and experiment. By comparing with different EOS models, we find a Purgatorio model (LEOS 2122) that agrees with our calculations. The maximum discrepancies in pressure between our first-principles predictions and LEOS 2122 are ~ 18 % and occur at temperatures between 6 × 10 3 – 2 × 10 5 K, which we believe originate from differences in the ion thermal term and the cold curve that are modeled in LEOS 2122 in comparison with our first-principles calculations. To account for potential differences in the ion thermal term, we have developed three new equation-of-state models that are consistent with theoretical calculations and experiment. We apply these new models to 1D hydrodynamic simulations of a polar direct-drive NIF implosion, demonstrating that these new models are now available for future ICF design studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Urban Combined Heat and Power with Integrated Renewables and Energy Storage

This project demonstrated how incorporating a diverse generation and storage portfolio allows an urban district energy system to improve its efficiency by at least 50% and increase its backup power by at least 40% with a return on investment of at least ten years. The improvement was evaluated against the baseline operations for two urban district energy systems (DESs): a synthetic DES and a George Washington University DES. The DES techno-economic framework we developed yields reliability, resilience, and vulnerability indices for urban DESs (including generation and storage) with designation of which technologies improve the security and resiliency metrics by at least 20% compared to the status quo. The indices are benchmarked against baseline scenarios, and cost projections (capital cost and return on investment) to achieve the 20% improvement are reported. The energy management system we developed to conduct these analyses was incorporated into a user-friendly interface that can be used for decision-making by a user with no technical or programming background.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models

Here, we construct a data set of metal–organic framework (MOF) linkers and employ a fine-tuned GPT assistant to propose MOF linker designs by mutating and modifying the existing linker structures. This strategy allows the GPT model to learn the intricate language of chemistry in molecular representations, thereby achieving an enhanced accuracy in generating linker structures compared with its base models. Aiming to highlight the significance of linker design strategies in advancing the discovery of water-harvesting MOFs, we conducted a systematic MOF variant expansion upon state-of-the-art MOF-303 utilizing a multidimensional approach that integrates linker extension with multivariate tuning strategies. We synthesized a series of isoreticular aluminum MOFs, termed Long-Arm MOFs (LAMOF-1 to LAMOF-10), featuring linkers that bear various combinations of heteroatoms in their five-membered ring moiety, replacing pyrazole with either thiophene, furan, or thiazole rings or a combination of two. Beyond their consistent and robust architecture, as demonstrated by permanent porosity and thermal stability, the LAMOF series offers a generalizable synthesis strategy. Importantly, these 10 LAMOFs establish new benchmarks for water uptake (up to 0.64 g g –1 ) and operational humidity ranges (between 13 and 53%), thereby expanding the diversity of water-harvesting MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Path integral Monte Carlo simulations of dense carbon-hydrogen plasmas

Carbon-hydrogen plasmas and hydrocarbon materials are of broad interest to laser shock experimentalists, high energy density physicists, and astrophysicists. Accurate equations of state (EOSs) of hydrocarbons are valuable for various studies from inertial confinement fusion to planetary science. By combining path integral Monte Carlo (PIMC) results at high temperatures and density functional theory molecular dynamics results at lower temperatures, we compute the EOSs for hydrocarbons from simulations performed at 1473 separate (ρ, T)-points distributed over a range of compositions. These methods accurately treat electronic excitation effects with neither adjustable parameter nor experimental input. PIMC is also an accurate simulation method that is capable of treating many-body interaction and nuclear quantum effects at finite temperatures. These methods therefore provide a benchmark-quality EOS that surpasses that of semi-empirical and Thomas-Fermi-based methods in the warm dense matter regime. By comparing our first-principles EOS to the LEOS 5112 model for CH, we validate the specific heat assumptions in this model but suggest that the Grüneisen parameter is too large at low temperatures. Based on our first-principles EOSs, we predict the principal Hugoniot curve of polystyrene to be 2%-5% softer at maximum shock compression than that predicted by orbital-free density functional theory and SESAME 7593. By investigating the atomic structure and chemical bonding of hydrocarbons, we show a drastic decrease in the lifetime of chemical bonds in the pressure interval from 0.4 to 4 megabar. We find the assumption of linear mixing to be valid for describing the EOS and the shock Hugoniot curve of hydrocarbons in the regime of partially ionized atomic liquids. We make predictions of the shock compression of glow-discharge polymers and investigate the effects of oxygen content and C:H ratio on its Hugoniot curve. In conclusion, our full suite of first-principles simulation results may be used to benchmark future theoretical investigations pertaining to hydrocarbon EOSs and should be helpful in guiding the design of future experiments on hydrocarbons in the gigabar regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1982

Surface protection overview

A first-cut integrated environmental attack life prediction methodology for hot section components is addressed. The HOST program is concerned with oxidation and hot corrosion attack of metallic coatings as well as their degradation by interdiffusion with the substrate. The effects of the environment and coatings on creep/fatigue behavior are being addressed through a joint effort with the Fatigue sub-project. An initial effort will attempt to scope the problem of thermal barrier coating life prediction. Verification of models will be carried out through benchmark rig tests including a 4 atm. replaceable blade turbine and a 50 atm. pressurized burner rig.

Levine, S. R.↗
NASA NTRS2005

Cold Flow Plume Entrainment Test Final Report NTF Test Number 2456

As part of the Space Shuttle Return to Flight (RTF) program, Marshall Space Flight Center (MSFC) performed computational fluid dynamics (CFD) analysis to define the velocity flowfields around the Shuttle stack at liftoff. These CFD predicted velocity flowfields were used in debris transport analysis (DTA). High speed flows such as plumes induce or 'entrain' mass from the surrounding environment. Previous work had shown that CFD analysis over-predicts plume induced flows. Therefore, the DTA would tend to 1) predict more debris impacts, and 2) the debris velocity (and kinetic energy) of those impacts would be too high. At a November, 2004 peer-review it was recommended that the Liftoff DTA team quantify the uncertainty in the DTA caused by the CFD's over prediction of plume induced flow. To do so, the Liftoff DTA team needed benchmark quality data for plume induced flow to quantify the CFD accuracy and its effect on the DTA. MSFC's Nozzle Test Facility (NTF) conducted the "Nozzle Induced Flows test, P#2456" to obtain experimental data for plume induced flows for nozzle flow exhausting into q quiescent freestream. Planning for the test began in December, 2004 and the experimental data was obtained in February and March of 2005. The funding for this test was provided by MSFC's Space Shuttle Propulsion Systems Integration and Engineering office.

Ruf, Joseph H.↗
DOE OSTI2025

Analyzing the Impact of Future Weather Data on Energy Consumption in Weatherization Assistant

This study supports the mission of the U.S. Department of Energy’s Weatherization Assistance Program (WAP), which aims to increase the energy efficiency of dwellings and reduce their total residential expenditures. Specifically, we examine how projected future climate conditions may affect residential building energy performance by integrating future weather data into the National Energy Audit Tool (NEAT). Since WAP evaluates the cost-effectiveness of retrofit measures over lifespans of up to 30 years, accounting for evolving climate conditions is increasingly important. To reflect future household energy demands, this study replaces historically based Typical Meteorological Year (TMY3) weather inputs with Future Typical Meteorological Year (fTMY) datasets derived from global climate model (GCM) projections. A simulation-based framework was established to enable NEAT analysis under future weather conditions. This workflow involves converting EPW-format weather files into JSON inputs compatible with NEAT and generating degree-hour metrics needed for load calculations. The fTMY dataset used in this study was developed by Oak Ridge National Laboratory through downscaling of six GCMs under different emission scenarios and covers the period from 2020 to 2100. In contrast, the TMY3 dataset is based on historical weather data from 1961 to 1990. Simulations were conducted for benchmark single-family prototype buildings across ASHRAE climate zones 1–7, which cover all regions of the U.S. except the subarctic Zone 8 in northern Alaska, evaluating both heating and cooling loads under TMY3 and fTMY conditions. Four foundation types were tested, while heating systems were standardized, as NEAT does not differentiate thermal energy load by HVAC system type in its load calculations. Results show that fTMY weather input consistently yield lower heating loads and higher cooling loads across most locations, aligning with expected climate warming trends. Notably, colder regions such as zones 6A, 6B, and 7 experience marked reductions in heating load, while warmer and transitional zones, such as 2A (Lufkin, TX) and 3C (San Francisco, CA), have substantial increases in cooling loads. Although this study does not directly assess the performance of retrofit measures under future climate conditions, it provides a critical foundation for doing so. By quantifying shifts in baseline (i.e., pre-retrofit case) energy loads between historical and future weather files, the study highlights the importance of integrating climate-responsive data into audit tools. These findings will inform future efforts to evaluate the long-term effectiveness and cost-effectiveness of weatherization measures under changing climate conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Thermal Transport by First-Principles Anharmonic Lattice Dynamics

Predictive methodologies for calculating lattice thermal transport and related properties have been recently developed and benchmarked successfully against measurements in a wide range of materials, from bulk to the nanoscale. This chapter presents an overview of the theoretical underpinnings of typical numerical methods for solving the Peierls-Boltzmann equation (PBE) for phonon transport when coupled with density functional theory (DFT). We discuss how these numerical methods may be employed to advance fundamental understanding of thermal transport, particularly as applied to measurements of anharmonic properties (e.g., linewidths, lattice expansion) in materials. In particular, calculations of interatomic force constants, integration methods, and construction of transport properties will be explained in detail with reference to relevant research in the literature. Furthermore, this chapter will provide an overview of applications and methods for calculations of thermal conductivities beyond perfect infinite crystals (including phonon-defect scattering) and of other measured observables, including mean free path accumulation, linewidths, and densities of states from scattering experiments.

Lindsay, Lucas↗
DOE OSTI2018

A new hybrid algorithm combining a new chaos optimization approach with gradient descent for high dimensional optimization problems

Chaos optimization algorithm (COA) is a recently developed method for global optimization based on chaos theory. It has the features of easy implementation, short execution time and robust mechanisms of escaping from local optima compared with the existing stochastic searching algorithm. By integrating the gradient descent method with a new COA approach using new strategies including symmetrization and levelling, a novel hybrid method, called SCGD, is proposed in this paper. The main idea is to combine the good ability of exploitation of the gradient descent with the high ability of exploration of COA. The purpose is to avoid being trapped into local optima and to improve convergence in large space and high-dimension optimization problems. The simulation results based on a set of 50 benchmark functions with diverse properties and different dimensions show the efficiency and the abilities of the proposed method in finding the global optima compared with the existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

When physics-informed data analytics outperforms black-box machine learning: A case study in thickness control for additive manufacturing

Aerosol jet printing (AJP) has emerged as a promising noncontact additive manufacturing method for high-resolution printing for a wide range of material systems. A key challenge limiting the broader adoption of AJP in the material science community is the lack of methods to precisely control thickness. Herein, we develop a model-based design of experiment (MBDoE) framework that integrates physics-informed models, nonlinear regression, and information criteria to postulate, select and calibrate the best model to describe and optimize the AJP manufacturing process. Starting with already available data from system commissioning (e.g., prior single variable sensitivity analysis), four candidate physics-informed models are postulated and trained. MBDoE identifies a single additional optimal experiment to validate these predictive models with quantified uncertainties, which are then used to determine the best experimental conditions to control printed film thickness. As a comparative benchmark, the analysis is repeated using the same dataset with nonparametric Gaussian process regression (GPR) model that does not incorporate physical information. Using MBDoE principles, we find that only five experiments are necessary to calibrate the nonlinear physics-informed parametric model, and with said limited data, this model outperforms the black-box machine learning GPR model. This key result underscores an emerging trend in the data science community: incorporating physical information into predictive models often drastically reduces the data requirements. Leveraging MBDoE further increased the data efficiency. By design, the proposed data science framework is general in nature and can be easily extended to other experimental and additive manufacturing systems beyond AJP.

Aerosol jet printing↗
DOE OSTI2023

Relativistic resolution-of-the-identity with Cholesky integral decomposition

In this study, we present an efficient integral decomposition approach called the restricted-kinetic-balance resolution-of-the-identity (RKB-RI) algorithm, which utilizes a tunable RI method based on the Cholesky integral decomposition for in-core relativistic quantum chemistry calculations. The RKB-RI algorithm incorporates the restricted-kinetic-balance condition and offers a versatile framework for accurate computations. Notably, the Cholesky integral decomposition is employed not only to approximate symmetric large-component electron repulsion integrals but also those involving small-component basis functions. In addition to comprehensive error analysis, we investigate crucial conditions, such as the kinetic balance condition and variational stability, which underlie the applicability of Dirac relativistic electronic structure theory. Here we compare the computational cost of the RKB-RI approach with the full in-core method to assess its efficiency. To evaluate the accuracy and reliability of the RKB-RI method proposed in this work, we employ actinyl oxides as benchmark systems, leveraging their properties for validation purposes. This investigation provides valuable insights into the capabilities and performance of the RKB-RI algorithm and establishes its potential as a powerful tool in the field of relativistic quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at √s = 8 TeV

The performance and strategies used in electron reconstruction and selection at CMS are presented based on data corresponding to an integrated luminosity of 19.7 fb -1 , collected in proton-proton collisions at √s = 8 TeV at the CERN LHC. The paper focuses on prompt isolated electrons with transverse momenta ranging from about 5 to a few 100 GeV. A detailed description is given of the algorithms used to cluster energy in the electromagnetic calorimeter and to reconstruct electron trajectories in the tracker. The electron momentum is estimated by combining the energy measurement in the calorimeter with the momentum measurement in the tracker. Benchmark selection criteria are presented, and their performances assessed using Z, Υ, and J/ψ decays into e + + e - pairs. The spectra of the observables relevant to electron reconstruction and selection as well as their global efficiencies are well reproduced by Monte Carlo simulations. The momentum scale is calibrated with an uncertainty smaller than 0.3%. The momentum resolution for electrons produced in Z boson decays ranges from 1.7 to 4.5%, depending on electron pseudorapidity and energy loss through bremsstrahlung in the detector material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2016

Review of Potential Wind Tunnel Balance Technologies

This manuscript reviews design, manufacture, materials, sensors, and data acquisition technologies that may benefit wind tunnel balances for the aerospace research community. Current state-of-the-art practices are used as the benchmark to consider advancements driven by researcher and facility needs. Additive manufacturing is highlighted as a promising alternative technology to conventional fabrication and has the potential to reduce both the cost and time required to manufacture force balances. Material alternatives to maraging steels are reviewed. Sensor technologies including piezoresistive, piezoelectric, surface acoustic wave, and fiber optic are compared to traditional foil based gages to highlight unique opportunities and shared challenges for implementation in wind tunnel environments. Finally, data acquisition systems that could be integrated into force balances are highlighted as a way to simplify the user experience and improve data quality. In summary, a rank ordering is provided to support strategic investment in exploring the technologies reviewed in this manuscript.

Burns, Devin E.↗
DOE OSTI2017

Application-level regression testing framework using Jenkins

Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integrate with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.

97 MATHEMATICS AND COMPUTING↗