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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Modeling and Evaluation of Canted Coil Springs as High Temperature Seal Preloading Devices

Future reusable launch vehicles will require advanced structural seals. This includes propulsion seals along edges and hinge lines in hypersonic engines, and control surface seals for movable flaps and elevons on proposed reentry vehicles. Seals must remain in sealing engagement with opposing surfaces, for multiple missions, even though the seal gap may be opening and closing due to thermal and structural loads. To meet this requirement either the seals themselves must be resilient or there must be a resilient structural element behind the seals. Case Western Reserve University is working with NASA s Glenn Research Center to develop more resilient high temperature seal components and preloading devices. Results are presented for a finite element analysis of a canted coil spring that is being considered as a high temperature seal preloading device. This type of spring is a leading candidate due to its ability to provide nearly constant force over a large deflection. The finite element analyses were verified by comparing them to experimental results of canted coil springs of three different stiffnesses, measured at Glenn Research Center. Once validated the parameterized model was combined with a scripting algorithm to assess the effects of key spring design variables (wire diameter, coils per inch, cant amplitude, eccentricity, and spring width) on spring stiffness and maximum Von Mises stress to aid in subsequent design.

Oswald, Jay J.↗
NASA NTRS2006

Design of the ARES Mars Airplane and Mission Architecture

Significant technology advances have enabled planetary aircraft to be considered as viable science platforms. Such systems fill a unique planetary science measurement gap, that of regional-scale, near-surface observation, while providing a fresh perspective for potential discovery. Recent efforts have produced mature mission and flight system concepts, ready for flight project implementation. This paper summarizes the development of a Mars airplane mission architecture that balances science, implementation risk and cost. Airplane mission performance, flight system design and technology maturation are described. The design, analysis and testing completed demonstrates the readiness of this science platform for use in a Mars flight project.

Braun, Robert D.↗
DOE OSTI2020

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗
DOE OSTI2024

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify, and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles, it is known as a directed acyclic graph. A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts can identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS

This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

An Overview of the Patch Integral Method (PIM), a New Heat Transfer Analysis Tool for Hypersonic Wind Tunnel Facilities at NASA Langley

NASA Langley’s hypersonic wind tunnels are heavily leveraged for planetary missions. The data collection method in these tunnels is thermography, and surface temperature measurements of the model surface are collected and reduced to produce surface heating data, as seen in Fig 1. However, during model injection, no temperature data are collected, and thus conventional, integral heat transfer methods cannot be used to solve for surface heating. A method was developed in the 1990’s to reduce this data despite the data gap, known as the step approximation method. The method assumes that the film coefficient behaves as a step function, the model is semi-infinite, and thermal properties are constant. With these simplifying assumptions, a Laplace transform can be performed to result in an equation that takes the initial temperature of the model and a temperature at some point in time to back out the film coefficient at that time. This is the method that is used in the current thermographic data reduction software, IHEAT. While computationally light-weight, the step approximation has several issues associated with it. The time-history of temperature is not accounted for, which is vital as heat transfer is an integral process. Additionally, the required semi-infinite assumption is unnecessary and might be violated during runtime. Thermal variation of material properties can have a sizeable impact on heating results and are not modeled by the method. This method also takes multiple seconds to “collapse” to a steady state, which is undesirable from both a facility and data reduction standpoint. The method is also very sensitive to the “effective time” approximation, an approximation of when heating instantaneously starts (which is a nonphysical simplification), and a small variation in this value can result in an error in heating results.

J. S. Cheatwood↗
DOE OSTI2026

Supporting U.S. National Security Through Cybersecurity Partnerships

At NLR, we're studying energy evolutions and threats to understand the challenges they pose and uncover ways to leverage grid advancements to achieve more secure, defensible, and reliable systems. Our integrated research approach bridges the gap between cyber threats and real-world consequences to deliver actionable solutions that reduce vulnerabilities and help strengthen U.S. national security.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

The Markov gap for geometric reflected entropy

The reflected entropy S R (A : B) of a density matrix ρ AB is a bipartite correlation measure lower-bounded by the quantum mutual information I(A : B). In holographic states satisfying the quantum extremal surface formula, where the reflected entropy is related to the area of the entanglement wedge cross-section, there is often an order-N 2 gap between S R and I. We provide an information-theoretic interpretation of this gap by observing that S R - I is related to the fidelity of a particular Markov recovery problem that is impossible in any state whose entanglement wedge cross-section has a nonempty boundary; for this reason, we call the quantity S R - I the Markov gap. We then prove that for time-symmetric states in pure AdS 3 gravity, the Markov gap is universally lower bounded by log(2)ℓ AdS /2G N times the number of endpoints of the cross-section. We provide evidence that this lower bound continues to hold in the presence of bulk matter, and comment on how it might generalize above three bulk dimensions. Finally, we explore the Markov recovery problem controlling S R - I using fixed area states. This analysis involves deriving a formula for the quantum fidelity — in fact, for all the sandwiched Rényi relative entropies — between fixed area states with one versus two fixed areas, which may be of independent interest. We discuss, throughout the paper, connections to the general theory of multipartite entanglement in holography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Molecular Dynamics Investigation of Nanoscale Hydrophobicity of Polymer Surfaces: What Makes Water Wet?

The wettability of a polymer surface–related to its hydrophobicity or tendency to repel water–can be crucial for determining its utility, such as for a coating or a purification membrane. While wettability is commonly associated with the macroscopic measurement of a contact angle between surface, water, and air, the molecular physics that underlie these macroscopic observations are not fully known, and anticipating relative behavior of different polymers is challenging. To address this gap in molecular-level understanding, we use molecular dynamics simulations to investigate and contrast interactions of water with six chemically distinct polymers: polytetrafluoroethylene, polyethylene, polyvinyl chloride, poly(methyl methacrylate), Nylon 66, and polyvinyl alcohol. We show that several prospective quantitative metrics for hydrophobicity agree well with experimental contact angles. Moreover, the behavior of water in proximity to these polymer surfaces can be distinguished with analysis of interfacial water dynamics, extent of hydrogen bonding, and molecular orientation–even when macroscopic measures of hydrophobicity are similar. The predominant factor dictating wettability is found to be the extent of hydrogen bonding between polymer and water, but the precise manifestation of hydrogen bonding and its impact on surface-water structure varies. In the absence of hydrogen bonding, other molecular interactions and polymer mechanics control hydrophobic ordering. Furthermore, these results provide new insights into how polymer chemistry specifically impacts water-polymer interactions and translates to surface hydrophobicity. Such factors may facilitate the design or processing of polymer surfaces to achieve targeted wetting behavior, and presented analyses can be useful in studying the interfacial physics of other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Real-Time Alignment and Reorientation of Polymer Chains in Liquid Crystal Elastomers

Liquid crystal elastomers (LCEs) exhibit soft elasticity due to the alignment and reorientation of mesogens upon mechanical loading, which provides additional mechanisms to absorb and dissipate energy. This enhanced response makes LCEs potentially transformative materials for biomedical devices, tissue replacements, and protective equipment. However, there is a critical knowledge gap in understanding the highly rate-dependent dissipative behaviors of LCEs due to the lack of real-time characterization techniques that probe the microscale network structure and link it to the mechanical deformation of LCEs. In this work, we employ in situ optical measurements to evaluate the alignment and reorientation degree of mesogens in LCEs. The data are correlated to the quantitative physical analysis using polarized Fourier-transform infrared spectroscopy. The time scale of mesogen alignment is determined at different strain levels and loading rates. The mesogen reorientation kinetics is characterized to establish its relationship with the macroscale tensile strain, and compared to theoretical predictions. Overall, this work provides the first detailed study on the time-dependent evolution of mesogen alignment and reorientation in deformed LCEs. It also provides an effective and more accessible approach for other researchers to investigate the structural-property relationships of different types of polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Efficient charge to spin conversion in iridium oxide thin films

Many 5d transition metal oxides have a unique electronic structure, where the density of states near the Fermi level is dominated by only 5d electrons with strong spin–orbit coupling. IrO 2 , a Dirac nodal line semi-metal, is the simplest of these oxides. The presence of 5d electrons and gap opening of Dirac nodal lines via strong spin–orbit coupling allows for the hybridization of the 5d electrons of the oxide with the itinerant d electrons of a ferromagnet, while simultaneously increasing the intrinsic spin Hall effect. We report large charge-to-spin conversion in thin films of this material using spin-torque ferromagnetic resonance experiments. Finally, by independently performing line shape analysis and linewidth modulation experiments, we conclusively determine the spin Hall angle of optimized IrO 2 films to be ∼8 times larger than that of Pt.

Ferromagnetic materials↗
DOE OSTI2023

ChemoGraph: Interactive Visual Exploration of the Chemical Space

Exploratory analysis of the chemical space is an important task in the field of cheminformatics. For example, in drug discovery research, chemists investigate sets of thousands of chemical compounds in order to identify novel yet structurally similar synthetic compounds to replace natural products. Manually exploring the chemical space inhabited by all possible molecules and chemical compounds is impractical, and therefore presents a challenge. To fill this gap, we present ChemoGraph, a novel visual analytics technique for interactively exploring related chemicals. In ChemoGraph, we formalize a chemical space as a hypergraph and apply novel machine learning models to compute related chemical compounds. It uses a database to find related compounds from a known space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. With a drug discovery usage scenario and initial expert feedback from a case study, we demonstrate the usefulness of ChemoGraph.

chemical space exploration↗
NASA NTRS2007

Unsteady Turbine Blade and Tip Heat Transfer Due to Wake Passing

The geometry and the flow conditions of the first stage turbine blade of GE s E3 engine have been used to obtain the unsteady three-dimensional blade and tip heat transfer. The isothermal wall boundary condition was used. The effect of the upstream wake of the first stage vane was of interest and was simulated by provision of a gust type boundary condition upstream of the blades. A one blade periodic domain was used. The consequence of this choice was explored in a preliminary study which showed little difference in the time mean heat transfer between 1:1 and 2:3 vane/blade domains. The full three-dimensional computations are of the blade having a clearance gap of 2 percent the span. Comparison between the time averaged unsteady and steady heat transfer is provided. It is shown that there is a significant difference between the steady and time mean of unsteady blade heat transfer in localized regions. The differences on the suction side of the blade in the near hub and near tip regions were found to be rather significant. Steady analysis underestimated the blade heat transfer by as much as 20 percent as compared to the time average obtained from the unsteady analysis. As for the blade tip, the steady analysis and the unsteady analysis gave results to within 2 percent.

Ameri, Ali A.↗
DOE OSTI2026

Diagnosing Ghost Bunches with the Upstream Extinction Monitor in the Mu2e Experiment

The Mu2e experiment has a stringent requirement for extinction of the pulsed proton beam, referring to the elimination of particles between proton bunches to a relative level of 10$^-10$, which means a single out-of-time particle in the inter-pulse gaps for every 250 complete proton pulses. As the construction of the Mu2e experiment nears completion, it is crucially important to make an early measurement of the beam extinction in its current condition. Hence the upstream extinction monitor was constructed and operated to probe for problems in the proton pulse structure or a higher than expected incidence rate of out-of-time particles. The analysis in this work comes from data taken in March 2026. The long data run showed a significant presence of out-of-time particles from ghost bunches in the Delivery Ring approximately 388 ns after the centers of the main proton pulses. These are hypothesized to be the result of a combination of a RF frequency mismatch, particle space charge, and machine impedance during the rebunching sequence in the Recycler Ring, which can lead to particles leaking into adjacent buckets, but further studies and simulations are needed to confirm this

Hensley, R. [UC, Davis] (ORCID:0000000216064485)↗
DOE OSTI2024

Bridging the gap: linking Torulaspora delbrueckii genotypes to fermentation phenotypes and wine aroma

Abstract Climate change and consumer preferences are driving innovation in winemaking, with a growing interest in non-Saccharomyces species. Among these, Torulaspora delbrueckii (Td) has gained recognition for its ability to reduce volatile acidity and enhance aromatic complexity in wine. However, knowledge regarding its phenotypic and genomic diversity impacting alcoholic fermentation remains limited. Aiming to elucidate the metabolic differences between Td and Saccharomyces cerevisiae (Sc) and the Td intraspecies diversity, we conducted a comprehensive metabolic characterization of 15 Td strains. This analysis delved beyond standard fermentation parameters (kinetics and major metabolites production) to explore non-conventional aromas and establish genotype-phenotype links. Our findings confirmed that most Td strains produce less acetic acid and more succinate and glycerol than Sc. The overall aromatic profiles of Td strains differed from Sc, exhibiting higher levels of monoterpenes and higher alcohols, while producing less acetate esters, fatty acids, their corresponding ethyl esters, and lactones. Moreover, we identified the absence of genes responsible for specific aroma profiles, such as decreased ethyl esters production, as well as the absence of cell wall genes, which might negatively affect Td performance when compared to Sc. This work highlights the significant diversity within Td and underscores potential links between its genotype and phenotype.

Silva-Sousa, Flávia (ORCID:0000000307383190)↗
DOE OSTI2024

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters

Smart inverters (SIs) have demonstrated their potential to provide grid services for both transmission and distribution systems. One of these grid services, distribution network voltage regulation by SIs, has the potential to improve network voltage regulation through controlling the reactive and active power output of the SIs. Voltage regulation by SIs will be distributed and might be better suited to controlling local conditions to complement traditional voltage-regulating assets, e.g., tap-changing transformers, capacitor banks, and line voltage regulators. There is a gap in the literature on comparing the SI response characteristics when the SIs are controlled by a local controller or external control signals. This paper presents an experimental study to characterize SI reactive power regulation responses to two different control methods: autonomous control and remote dispatch. We found that SI reactive power regulation responses exhibit important differences between these methods in terms of delays and ramp rate. Finally, power-hardware-in-the-loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL test results show that the SI response characteristics for autonomous control and remote dispatch need to be considered when planning for distribution network voltage regulation using SIs.

autonomous control↗
DOE OSTI2023

Thermohydraulic Design Analysis of the Target Assembly in the Material Plasma Exposure Experiment Facility

The Material Plasma Exposure eXperiment (MPEX) project seeks to design a steady-state linear plasma facility at Oak Ridge National Laboratory that will be used to study plasma-material interactions (PMIs) at fusion prototypic levels, supporting the evaluation and development of materials for the next generation of fusion devices. This study is focused on PMI exposure of small-size neutron-irradiated specimens, which are clamped onto an actively cooled component. A thermohydraulic evaluation of a new MPEX target assembly design to assess the appropriate operation during MPEX operation is presented. To further guide the design and assess the structural integrity of the components under expected loads, preliminary thermomechanical stress analyses were also conducted. To ensure good thermal contact between the components, thermal interface materials, such as silver flexible graphite, were used in the assembly. It was found that the maximum target temperatures of 1572, 1463, and 1315 K were obtained for Grafoil thicknesses of 0.61, 0.38, and 0.25 mm, respectively. The distribution of the axial deformation at high heat fluxes showed that there are no gaps between components, indicating good contact at material interfaces. Moreover, the contact pressure between the target and other components indicated that very good contact was established at these interfaces. Furthermore, the stress-strain conditions for the target will be further used to assess the appropriate operation during MPEX experiments and gain insight into materials science phenomena during PMI experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2008

Atmospheric Correction at AERONET Locations: A New Science and Validation Data Set

This paper describes an AERONET-based Surface Reflectance Validation Network (ASRVN) and its dataset of spectral surface bidirectional reflectance and albedo based on MODIS TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50x50 square kilometer subsets of MODIS L1B data from MODAPS and AERONET aerosol and water vapor information. Then it performs an accurate atmospheric correction for about 100 AERONET sites based on accurate radiative transfer theory with high quality control of the input data. The ASRVN processing software consists of L1B data gridding algorithm, a new cloud mask algorithm based on a time series analysis, and an atmospheric correction algorithm. The atmospheric correction is achieved by fitting the MODIS top of atmosphere measurements, accumulated for 16-day interval, with theoretical reflectance parameterized in terms of coefficients of the LSRT BRF model. The ASRVN takes several steps to ensure high quality of results: 1) cloud mask algorithm filters opaque clouds; 2) an aerosol filter has been developed to filter residual semi-transparent and sub-pixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing requirement of consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of seasonal back-up spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixels. The ASRVN products include three parameters of LSRT model (k(sup L), k(sup G), k(sup V)), surface albedo, NBRF (a normalized BRF computed for a standard viewing geometry, VZA=0 deg., SZA=45 deg.), and IBRF (instantaneous, or one angle, BRF value derived from the last day of MODIS measurement for specific viewing geometry) for MODIS 500m bands 1-7. The results are produced daily at resolution of 1 km in gridded format. We also provide cloud mask, quality flag and a browse bitmap image. The new dataset can be used for a wide range of applications including validation analysis and science research.

Wang, Yujie↗