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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

TPS Certification by Analysis: Model-Driven Characterization of Properties and Failure in Woven Thermal Protection Systems

Woven, ablative thermal protection system (TPS) materials provide a robust option for aggressive (re)entries and thus have been baselined for the upcoming Mars Sample Return (MSR) mission's Earth Entry System (EES). The reliability requirements for MSR-EES necessitate understanding of material property variability, which could be significant given the complex structure and anisotropic nature of properties in TPS weaves, as well as the response to potential impact with micrometeoroids or orbital debris during the EES re-entry. The TPS Certification by Analysis effort within the Entry Systems Modeling project seeks to provide computational models and analyses that support the certification against such material-based risks. For the present talk, focus will be given to the characterization of baseline woven TPS material properties and mechanical failure limits, which entails (1) use of computational techniques (e.g., machine learning) to interpret computed tomography images of the weave to generate representative structural models and (2) application of multiscale material modeling approaches to characterize thermomechanical and failure properties.

thermal protection systems↗
NASA NTRSDate not supplied

TPS Certification by Analysis: Model-Driven Characterization of Properties and Failure in Woven Thermal Protection Systems

Woven, ablative thermal protection system (TPS) materials provide a robust option for aggressive (re)entries and thus have been baselined for the upcoming Mars Sample Return (MSR) mission’s Earth Entry System (EES). The reliability requirements for MSR-EES necessitate understanding of material property variability, which could be significant given the complex structure and anisotropic nature of properties in TPS weaves, as well as the response to potential impact with micrometeoroids or orbital debris during the EES re-entry. The TPS Certification by Analysis effort within the Entry Systems Modeling project seeks to provide computational models and analyses that support the certification against such material-based risks. For the present talk, focus will be given to the characterization of baseline woven TPS material properties and mechanical failure limits, which entails (1) use of computational techniques (e.g., machine learning) to interpret computed tomography images of the weave to generate representative structural models and (2) application of multiscale material modeling approaches to characterize thermomechanical and failure properties.

Justin B. Haskins↗
DOE OSTI2021

Validation of the Public Radiation Exposure Calculation for the Incident at the National Institute of Standards and Technology Center for Neutron Research on February 3, 2021

The Department of Energy/National Nuclear Security Administration Consequence Management Program was contacted by the Health Physics Chief of the National Institute of Standards and Technology Center for Neutron Research (NCNR) to review public radiation exposure calculations for an event that occurred on its Gaithersburg, Maryland, campus on February 3, 2021. Subject matter experts from the Nuclear Emergency Support Team (NEST) assets, specifically the Consequence Management Home Team (CMHT) and the National Atmospheric Release Advisory Center (NARAC), were selected to provide support. CMHT used three separate modeling codes to validate the results the scientists at NCNR calculated using the HotSpot model. The analyses were performed using NARAC’s in-house Lagrangian dispersion codes known as LODI and Aeolus, as well as the Turbo FRMAC software from Sandia National Laboratories. The team used parameters provided by the NCNR scientists regarding the site, applicable observable meteorological data, and environmental survey and sampling data to estimate public exposure. Each model estimated public dose at much less than 0.5 mrem. CMHT concurs with the NCNR public radiation exposure calculations which state that members of the public at the 400-meter boundary would have received a radiological dose of less than 0.5 mrem.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Field Validated Utility-Scale Battery Storage Control Models for Quasi-Static Analyses

This paper presents a co-simulation based approach to implement and validate advanced battery storage control modes in OpenDSS that replicate behavior of a utility scale vanadium red-ox flow battery (VRFB). Inverter-interfaced utiliy-scale battery storage systems (BSS) have modes of operation to facilitate multiple grid-support functions. In order to enable accurate understanding of the impacts from grid-support functions modes of operation it is required to develop validated models that replicates behavior of the actual control system. This paper presents the pseudo code for the implemented control schemes including peak shaving and capacity firming control modes. Additionally, this paper also provides insight on convergence sensitivity of the presented algorithms to related parameters. The results obtained from simulation studies will be compared against field operated utility-scale BSS measurements to verify the implemented algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Unlocking expanded flagellin perception through rational receptor engineering

Abstract The surface-localized receptor kinase FLS2 detects the flg22 epitope from bacterial flagella. FLS2 is conserved across land plants, but bacterial pathogens exhibit polymorphic flg22 epitopes. Most FLS2 homologues possess narrow perception ranges, but four with expanded perception have been identified. Using diversity analyses, AlphaFold modelling and amino acid properties, key residues enabling expanded recognition were mapped to FLS2’s concave surface, interacting with the co-receptor and polymorphic flg22 residues. Synthetic biology enabled engineering of expanded recognition from QvFLS2 (Quercus variabilis) into a homologue with canonical perception. A similar approach enabled transfer ofAgrobacteriumperception from FLS2 XL (Vitis riparia) into VrFLS2. Evolutionary analyses across three plant orders showed residues under positive selection aligning with those binding the co-receptor and flg22’s C terminus, suggesting more alleles with expanded perception exist. Our experimental data enabled the identification of specific receptor amino acid properties and AlphaFold3 metrics that facilitate predicting FLS2–flg22 recognition. This study provides a framework for rational receptor engineering to enhance pathogen restriction.

Plant Sciences↗
DOE OSTI2014

Thermophysical properties of BKC 44306 and BKC 44307 PMDI urethane solid and foams

Accurate knowledge of thermophysical properties of urethane foam is considered extremely important for meaningful models and analyses to be developed of scenarios wherein the foam is heated. Its performance at temperature requires a solid understanding of the foam material properties at temperature. Also, foam properties vary with density/porosity. An experimental program to determine the thermal properties of the two foams and their parent solid urethane was developed in order to support development of a predictive model relating density and thermal properties from first principles. Thermal properties (thermal conductivity, diffusivity, and specific heat) of the foam were found to vary with temperatures from 26°C to 90°C. Thermal conductivity generally increases with increasing temperature for a given initial density and ranges from .0433 W/mK at 26°C to .0811 W/mK at 90°C; thermal diffusivity generally decreases with increasing temperature for a given initial density and ranges from .4101 mm 2 /s at 26°C to .1263 mm 2 /s at 90°C; and specific heat generally increases with increasing temperature for a given initial density and ranges from .1078 MJ/m 3 K at 26°C to .6323 MJ/m 3 K at 90°C. Thermal properties of the solid urethane were also found to vary with temperatures from 26°C to 90°C. Average thermal conductivity generally increases with increasing temperature for a given initial density and ranges from 0.126 to 0.131 W/mK at 26°C to 0.153 to 0.157 W/mK at 90°C; average thermal diffusivity generally decreases with increasing temperature for a given initial density and ranges from 0.142 to 0.147 mm 2 /s at 26°C to 0.124 to 0.125 mm 2 /s at 90°C; and average specific heat generally increases with increasing temperature for a given initial density and ranges from 0.889 to 0.899 MJ/m 3 K to 1.229 to 1.274 MJ/m 3 K at 90°C. The density of both foam and solid urethane decreased with increasing temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Determining the Release of Radionuclides from SRS Tank 12H Waste Residual Solids Following Tank Closure

Eight High Level Waste (HLW) tanks used to store radioactive waste slurries have been emptied and closed at the Savannah River Site (SRS). Performance Analyses (PA) modeling of the release of radionuclides from residual waste solids in these tanks into the environment over extended time periods indicated the most likely risk drivers for environmental contamination. Radionuclide leaching studies were desired to provide additional information regarding the residual waste solubility assumptions used in the models. This report serves to provide equilibrium solubility data for several radionuclides identified as risk drivers and adds to the database of solubility values reported in the previous analogous study with Tank 18F solids. Pore water leaching studies were conducted on actual SRS Tank 12H residual waste solids to support Liquid Waste tank closure efforts and closed tank Performance Analyses. Tank 12H was exposed to extensive mechanical cleaning, caustic aluminum dissolution, and oxalic acid chemical cleaning prior to closure. The methodology utilized for leach testing was developed during previous testing. Slurries of tank residual solids and grout-representative solids in simulated grout pore water solutions (based on SRS groundwater compositions) with pH and E h values expected during the aging of the closed waste tank were produced. The soluble concentrations of selected radionuclides were analyzed versus time to confirm equilibrium conditions were achieved. These are the first leach studies conducted on waste tank residuals exposed to these cleaning conditions.

Eh↗
DOE OSTI2011

A COMPRESSED SENSING METHOD WITH ANALYTICAL RESULTS FOR LIDAR FEATURE CLASSIFICATION

We present an innovative way to autonomously classify LiDAR points into bare earth, building, vegetation, and other categories. One desirable product of LiDAR data is the automatic classification of the points in the scene. Our algorithm automatically classifies scene points using Compressed Sensing Methods via Orthogonal Matching Pursuit algorithms utilizing a generalized K-Means clustering algorithm to extract buildings and foliage from a Digital Surface Models (DSM). This technology reduces manual editing while being cost effective for large scale automated global scene modeling. Quantitative analyses are provided using Receiver Operating Characteristics (ROC) curves to show Probability of Detection and False Alarm of buildings vs. vegetation classification. Histograms are shown with sample size metrics. Our inpainting algorithms then fill the voids where buildings and vegetation were removed, utilizing Computational Fluid Dynamics (CFD) techniques and Partial Differential Equations (PDE) to create an accurate Digital Terrain Model (DTM) [6]. Inpainting preserves building height contour consistency and edge sharpness of identified inpainted regions. Qualitative results illustrate other benefits such as Terrain Inpainting s unique ability to minimize or eliminate undesirable terrain data artifacts. Keywords: Compressed Sensing, Sparsity, Data Dictionary, LiDAR, ROC, K-Means, Clustering, K-SVD, Orthogonal Matching Pursuit

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Rayleigh–Taylor unstable flames at higher Reynolds number

ABSTRACT Rayleigh–Taylor (RT) unstable flames are a key component of Type Ia and Iax supernovae explosions, but their complex hydrodynamics is still not well understood. These flames are affected not only by the RT instability, but also by the turbulence it generates. Both processes can increase the flame speed by stretching and wrinkling the flame. This makes it hard to choose a subgrid model for the flame speed in full star Type Ia or Iax simulations. Commonly used subgrid models get around this difficulty by assuming that either the RT instability or turbulence is dominant and sets the flame speed. In previous work, we evaluated the physical assumptions and predictive abilities of these two types of models by analysing a large parameter study of 3D direct numerical simulations of RT unstable flames. Surprisingly, we found that the flame dynamics is dominated by the RT instability and that RT unstable flames are very different from turbulent flames. In particular, RT unstable flames are thinner rather than thicker when turbulence is strong. In addition, none of the turbulent flame speed models adequately predicted the flame speed. We also showed that the RT flame speed model failed when the RT instability was strong, suggesting that geometrical burning effects also influence the flame speed. However, these results depended on simulations with Re ≲ 720. In this paper, we extend the parameter study to higher Reynolds number and show that the basic conclusions of our previous study still hold when the RT-generated turbulence is stronger.

Hicks, E. P.↗
DOE OSTI2023

MODELS FOR ESTIMATING THE AUTOFRETTAGE PRESSURE AND RESIDUAL STRESSES IN WALLS OF TYPE 2 PRESSURE VESSELS

Autofrettage is a manufacturing process used during fabrication of Type 2 pressure vessels designed for usage at high pressures to enhance the fatigue life. The process locks high compressive residual stresses in the vessel’s liner wall that reduce the maximum and the mean stress during service loading. To achieve a consistent residual stress profile across the wall of the vessel, the choice of autofrettage pressure is critical. Several finite element analyses runs were conducted to estimate the correct autofrettage pressure that is a function of the yield strength of the liner material, the wall thickness, and the outside diameter of the liner for a wrap thickness of 17.06 mm (48 wire layers). From the finite element analyses results, models were developed to estimate the correct autofrettage pressure and the residual stress distribution across the liner wall as a function of the yield strength of the liner material, the wall thickness, and the outside diameter of the liner.

08 HYDROGEN↗
DOE OSTI2021

Development of Electro-chemical Battery Model for Plug-and-Play Eco-system Library

Energy storage components are fundamental to the concept of an Integrated Energy System (IES). They serve to store surplus energy during low-demand periods for later release when other IES components (i.e., Secondary Energy Source, Balance of Plant, etc.) would otherwise have to operate flexibly. This provision for storage avoids high-amplitude power ramps in these components thereby limiting thermal and mechanical stresses to their internals and providing for extended service life. This report describes a dynamic model that has been developed for an electrochemical battery. The lithium-ion (Li-ion) cell was selected as representative technology. The battery model was developed in the Dymola simulation environment and meets the requirements of the ecosystem plug-and-play library. The model accurately describes the electric dynamic response of a Li-ion battery for an imposed charging/discharging power profile. The corresponding physical limitations related to over-power scenarios, and the impact of the residual state of charge are accounted for in the model. A literature review of the major degradation processes affecting Li-ion batteries was performed. Given the purposes of the CTD-IES project, the progressive fade of the installed capacity, the reduction of the round-trip efficiency, and the limits on the number of charging/discharging cycles are aspects that need to be taken into account in techno-economic analyses. The modeling of these degradation phenomena becomes crucial when predictions over long time horizons (capacity expansion) are made. For each one of these phenomena, a brief description is given, and some figures to be implemented in the HERON optimization algorithm are presented.

25 ENERGY STORAGE↗
DOE OSTI2016

Applications Using the Advanced Simulation Capability for Environmental Management Tool-set - 16335

The Office of Soil and Groundwater of the U.S. Department of Energy (DOE) Office of Environmental Management (EM) developed the Advanced Simulation Capability for Environmental Management (ASCEM). The ASCEM tool-sets can be used for making informed choices in uncertain and complex environments, where cost-benefits of environmental impacts and human health need to be considered. The deployments and demonstrations show how ASCEM provides a unified framework that facilitates efficient modeling and analyses to address costs and benefits of engineering and remediation decisions: - Evaluation of engineered remediation and monitoring strategies at the Savannah River Site (SRS) F-Area in collaboration with the Office of Soil and Groundwater Remediation, Attenuation-Based Remedies in the Subsurface Applied Field Research Initiative; - Assessment of performance assessment issues and waste tank closure at SRS; - Evaluation of alternative conceptual models for the deep vadose zone at the Hanford Site, supporting waste tank closure. The ASCEM tool-sets enable computationally efficient representations of the complex subsurface systems, including fractured and faulted volcanic and carbonate aquifers, a very deep water table, and multiple contaminant sources. The applications demonstrate that deployment of the ASCEM tool-sets provides an opportunity to reduce conservatisms in modeling assessments and allows detailed investigation of alternative conceptual models. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Analysis of ABCB phosphoglycoproteins (PGPs) and their contribution to monocot biomass, structural stability, and productivity

Efforts to manipulate production of plant secondary cell walls to improve the quality of biofuel feedstocks are currently limited by an inability to regulate the transport of small molecule components out of the cell. Plant ABCB p-glycoproteins are a small family of plasma membrane organic molecule transporters that have become primary targets for this effort, as they can potentially be harnessed to control the export of aromatic compounds and organic acids. However, unlike promiscuous mammalian ABCBs that function in multidrug resistance, all plant ABCB proteins characterized to date exhibit relatively narrow substrate specificity. Although ABCBs exhibit a highly conserved architecture, efforts to modify ABCB activity have been hampered by a lack of structural information largely because an eukaryotic ABCB protein crystal structure has yet to be obtained. Structure/ function analyses have been further impeded by the lack of a common heterologous expression system that can be used to characterize recombinant ABCB proteins, as many cannot be functionally expressed in S. cereviseae or other systems where proteins with analogous function can be readily knocked out. Using experimentally-determined plant ABCB substrate affinities and the crystal structure of the bacterial Sav1866 “half” ABC transporter, we have developed sequence/structure models for ABCBs that provide a testable context for mutational analysis of plant ABCB transporters. We have also developed a flexible heterologous expression system in Schizosaccharomyces pombe in which all endogenous ABC transporters have been knocked out. The effectiveness of this system for transport studies has been demonstrated by the successful functional expression all of the known PIN, AUX/LAX and ABCB auxin transporters. Our central hypothesis is that the domains of the ABCB proteins that we have identified as substrate docking sites and regulators of transport directionality can be altered or swapped to alter the transport characteristics of the proteins. We propose to combine computer modelling, mutational analyses, and complementation of well characterized Arabidopsis abcb4,14,and 19 mutants to elucidate ABCB function. The long term objective of this project is to enhance ABCB transport of cell wall components, to manipulate the direction of ABCB substrate transport, and, ultimately, to produce “designer” ABC transporters that can be used to modify plant feedstock quality.

09 BIOMASS FUELS↗
DOE OSTI2022

Simulating energetic particle losses in JET plasmas with a reverse integration biasing scheme

We report that an integrated energetic particle transport model has been constructed in JET plasmas constrained by experimental fast ion loss measurements. The model incorporates a synthetic fast ion loss detector identical to JET’s thin-foil Faraday cup fast ion loss detector array. The loss model combines analyses from the TRANSP and ORBIT-kick codes with enhanced features for producing the synthetic diagnostic. Extensions to the ORBIT code framework allow a full-orbit representation within the vacuum region that can map particles directly to an installed detector geometry. Since synthetic fast ion loss detectors are plagued by weak loss statistics, a novel reverse integration biasing scheme has been implemented to boost computational efficiency. The model is validated against experimental loss measurements induced by long-lived kink modes and is found to be in good agreement. This confirms the development of a fully integrated transport/loss model which can be quantitatively verified against experiment allowing for future validation and predictive studies. The model is particularly useful for more complicated plasma scenarios that involve multiple fast ion species such as JET’s 2021 DT-campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Dynamic Model Validation of PV Inverters Under Short-Circuit Conditions: Preprint

Photovoltaic (PV) modules have dramatically decreased in price in the past few years, spurring the expansion of photovoltaic deployment. Residential and commercial rooftop installations are connected to the distribution network; large-scale installation PV power plants (PVPs) have benefited from tax incentives and the low cost of PV modules. As the level penetration of PV generation increases, the impact on power system reliability will also be greater. Utility power system planners must consider the role of PV generation in power systems more realistically by representing PV generation in dynamic stability analyses. Dynamic models of PV inverters have been developed in the positive sequence representation. NREL has developed a PV inverter dynamic model in PSCAD/EMTDC. This paper validates the dynamic model with an actual hardware bench test conducted by Southern California Edison's Distributed Energy Resources laboratory. All the fault combinations -- symmetrical and unsymmetrical -- were performed in the laboratory. We compare the simulation results with the bench test results.

14 SOLAR ENERGY↗
DOE OSTI2016

Phosphorus and carrier density of heavily n-type doped germanium

The threshold current density of n-type, tensile-strained Ge lasers strongly depends on the electron density. Although optical net gain analyses indicate that the optimum electron density should be on the order of 1 × 10{sup 20} cm{sup −3} to get the lowest threshold, it is not a simple task to increase the electron density beyond the mid range of 10{sup 19} cm{sup −3}. The present paper analyzes the phenomenon where electron density is not proportional to phosphorus donor density, i.e., “saturation” phenomenon, by applying the so-called amphoteric defect model. The analyses indicate that the saturation phenomenon can be well explained by the charge compensation between the phosphorus donors (P{sup +}) and doubly negative charged Ge vacancies (V{sup 2−}).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗