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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 433 records · Page 24

A Comparison of Methods for Assessing Space Suit Joint Ranges of Motion

Through the Advanced Exploration Systems (AES) Program, NASA is attempting to use the vast collection of space suit mobility data from 50 years worth of space suit testing to build predictive analysis tools to aid in early architecture decisions for future missions and exploration programs. However, the design engineers must first understand if and how data generated by different methodologies can be compared directly and used in an essentially interchangeable manner. To address this question, the isolated joint range of motion data from two different test series were compared. Both data sets were generated from participants wearing the Mark III Space Suit Technology Demonstrator (MK-III), Waist Entry I-suit (WEI), and minimal clothing. Additionally the two tests shared a common test subject that allowed for within subject comparisons of the methods that greatly reduced the number of variables in play. The tests varied in their methodologies: the Space Suit Comparative Technologies Evaluation used 2-D photogrammetry to analyze isolated ranges of motion while the Constellation space suit benchmarking and requirements development used 3-D motion capture to evaluate both isolated and functional joint ranges of motion. The isolated data from both test series were compared graphically, as percent differences, and by simple statistical analysis. The results indicated that while the methods generate results that are statistically the same (significance level p= 0.01), the differences are significant enough in the practical sense to make direct comparisons ill advised. The concluding recommendations propose direction for how to bridge the data gaps and address future mobility data collection to allow for backward compatibility.

Aitchison, Lindsay T.↗

Polyolefin plastic waste hydroconversion to fuels, lubricants, and waxes: a comparative study

Hydroconversion technologies have surged to the forefront of deconstructing plastic waste. Recent studies have been performed over several catalysts with varying conditions and plastics that make comparisons difficult. We compile and compare data from the literature by introducing various metrics and perform a simple energy analysis. We draw mechanistic similarities to and differences from the past literature on small alkane hydroconversion and leverage the former to propose standard approaches to tune product selectivity. We exemplify the plastics materials gap and the challenges it creates. Lastly, we discuss the current limitations and suggest future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

6⁢𝐻-perovskite dimer lattice with antiferromagnetic interactions: Ba 3⁢ Zn 1−𝑥⁢ Ca 𝑥 ⁢Ru 2 ⁢O 9

Here, we investigate the magnetic behavior of the 6⁢𝐻-perovskite dimer lattice Ba 3 ⁢Zn 1−𝑥 ⁢Ca 𝑥 ⁢Ru 2 ⁢O 9 using analytical theory, density functional theory, inelastic neutron scattering, and modeling of historical magnetization and neutron-scattering data. A dimer mean-field theory built upon classical Luttinger–Tisza analysis generates a phase diagram revealing a transition from a nonmagnetic singlet to a finite-moment ground state as interdimer couplings increase. A (generalized) linear spin-wave theory captures multiplet mixing, excitation gap closing, and fluctuation-induced moment suppression. Density-functional-theory calculations on selected compounds, together with neutron spectroscopy of dilute Ba 3 ⁢Zn⁢(Ru 1−𝑥 ⁢Sb 𝑥 ) 2 ⁢O 9 , confirm the exchange hierarchy, enabling quantification of previously published experiments within this framework. Our results identify three mechanisms for magnetic moment suppression—quantum fluctuations, ligand hybridization, and nonmagnetic-singlet/magnetic-multiplet mixing.

Pajerowski, Daniel M. [Oak Ridge National Laborato↗

A Modelica Implementation of an Organic Rankine Cycle

Organic Rankine cycle (ORC) systems generate power from low-grade heat sources, such as geothermal sources and industrial waste heat. A key feature is that a working fluid is selected to match the temperature of the source. With the vast pool of candidate working fluids comes the challenge of developing a large number of robust thermodynamic media models. We implemented a subcritical ORC model in Modelica that uses working fluid data records and interpolation schemes in lieu of thermodynamic medium evaluation for energy recovery estimation. This is a component model that can be integrated into a larger energy system model. It does not require detailed thermodynamic, heat transfer, or machine analysis. Our ORC model fills a gap where working fluids are ready to choose or easy to add, and at the same time can be integrated into an energy system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Radiation-induced extrinsic photoconductivity in Li-doped Si.

Investigation of the effects of lithium on radiation-produced complexes having long-time stability by examining the localized energy levels in the forbidden gap which give rise to extrinsic photoconductivity. The levels are found to disappear and in some cases shift with annealing in the 100-450 C temperature range. Due to the complexity of the system and the present lack of adequate theory, no complete analysis of the data obtained could be made.

Fenimore, E.↗

Validity of the two-level model for Viterbi decoder gap-cycle performance

A two-level model has previously been proposed for approximating the performance of a Viterbi decoder which encounters data received with periodically varying signal-to-noise ratio. Such cyclically gapped data is obtained from the Very Large Array (VLA), either operating as a stand-alone system or arrayed with Goldstone. This approximate model predicts that the decoder error rate will vary periodically between two discrete levels with the same period as the gap cycle. It further predicts that the length of the gapped portion of the decoder error cycle for a constraint length K decoder will be about K-1 bits shorter than the actual duration of the gap. The two-level model for Viterbi decoder performance with gapped data is subjected to detailed validation tests. Curves showing the cyclical behavior of the decoder error burst statistics are compared with the simple square-wave cycles predicted by the model. The validity of the model depends on a parameter often considered irrelevant in the analysis of Viterbi decoder performance, the overall scaling of the received signal or the decoder's branch-metrics. Three scaling alternatives are examined: optimum branch-metric scaling and constant branch-metric scaling combined with either constant noise-level scaling or constant signal-level scaling. The simulated decoder error cycle curves roughly verify the accuracy of the two-level model for both the case of optimum branch-metric scaling and the case of constant branch-metric scaling combined with constant noise-level scaling. However, the model is not accurate for the case of constant branch-metric scaling combined with constant signal-level scaling.

Dolinar, S.↗

Open architectures for formal reasoning and deductive technologies for software development

The objective of this project is to develop an open architecture for formal reasoning systems. One goal is to provide a framework with a clear semantic basis for specification and instantiation of generic components; construction of complex systems by interconnecting components; and for making incremental improvements and tailoring to specific applications. Another goal is to develop methods for specifying component interfaces and interactions to facilitate use of existing and newly built systems as 'off the shelf' components, thus helping bridge the gap between producers and consumers of reasoning systems. In this report we summarize results in several areas: our data base of reasoning systems; a theory of binding structures; a theory of components of open systems; a framework for specifying components of open reasoning system; and an analysis of the integration of rewriting and linear arithmetic modules in Boyer-Moore using the above framework.

Mccarthy, John↗

Phase change material-to-refrigerant heat exchangers: Experimental validation and uneven melting analysis

Thermal energy storage (TES) using phase change materials (PCMs) enables load shifting and reduces mismatches between the building's thermal demand and the heat pump (HP) system's thermal capacity. While most TES studies have focused on single-phase heat transfer fluids, PCM-to-refrigerant heat exchangers (PRHX), in which the refrigerant undergoes liquid-vapor phase change, remain largely underexplored. Here, to address this gap, this study systematically investigates a shell-and-tube PRHX operating as the condenser in an HP through experiments and simulations. A two-dimensional enthalpy-based finite-volume PRHX model was developed and validated against experimental data, including refrigerant and PCM temperature profiles, PRHX capacity, and system-level performance. Results show three characteristic stages: Stage I, the condenser temperature rapidly increases with PCM in the solid state absorbing sensible heat; Stage II, stable operation during PCM phase change; and Stage III, performance decline once part of the PCM becomes fully melted. Heat transfer analysis revealed that uneven PCM melting along the condenser length was driven primarily by variations in the refrigerant-side heat transfer coefficient, rather than local approach temperature differences. Further study demonstrated that minimizing refrigerant outlet subcooling led to more uniform PCM melting and extended Stages I and II by up to 89%. This paper provides a validated PRHX model, clarifies the mechanisms of uneven PCM melting, and highlights subcooling control as an effective strategy to improve TES performance in HP systems without requiring secondary loops.

Graphite matrix↗

ISO Guest Observer Data Analysis and LWS Instrument Team Activities

We have designed and fabricated infrared filters for use at wavelengths greater than or equal to 15 microns. Unlike conventional dielectric filters used at the short wavelengths, ours are made from stacked metal grids, spaced at a very small fraction of the performance wavelengths. The individual lattice layers are gold, the spacers are polyimide, and they are assembled using integrated circuit processing techniques; they resemble some metallic photonic band-gap structures. We simulate the filter performance accurately, including the coupling of the propagating, near-field electromagnetic modes, using computer aided design codes. We find no anomalous absorption. The geometrical parameters of the grids are easily altered in practice, allowing for the production of tuned filters with predictable useful transmission characteristics. Although developed for astronomical instrumentation, the filters are broadly applicable in systems across infrared and terahertz bands.

Oliversen, Ronald J.↗

A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.

BIOMASS FUELS↗

Analysis of Fire-Induced Circulations during the FireFlux2 Experiment

Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression.

Benik, Jeremy T.↗

Techno-Economic Analysis of decentralized preprocessing systems for fast pyrolysis biorefineries with blended feedstocks in the southeastern United States

This study evaluated the economic feasibility of fast pyrolysis biorefineries fed with blended pine residues and switchgrass in the Southeastern U.S. with different supply chain design. Previous techno-economic analyses (TEA) have focused on either blended biomass or decentralized preprocessing without investigating the impacts of varied process parameters, technology options, and real-world biomass distribution. This study fills the literature gap by modeling scenarios for different biomass blending ratios, biorefinery and preprocessing site (so-called depot) capacities, and alternative preprocessing technologies. High-resolution, real-world geospatial data were analyzed using Geographic Information Systems to facilitate supply chain design and TEA. For a decentralized system, the minimum fuel selling price (MFSP) of biofuel was 3.92–4.33 per gallon gasoline equivalent (GGE), while the MFSP for the centralized biorefinery at the same capacities ranged between 3.75–4.02/GGE. Implementing a high moisture pelleting process depot rather than a conventional pelleting process lowered the MFSP by 0.03–0.17/GGE. Scenario analysis indicated decreased MFSP with increasing biorefinery capacities but not necessarily with increasing depot size. Medium-size depots (500 OMDT/day) achieved the lowest MFSP. Here, this analysis identified the optimal blending ratios for two preprocessing technologies at varied depot sizes. Counterintuitively, increasing the proportion of higher cost switchgrass reduced the MFSP for large biorefineries (>5000 ODMT/day), but increased the MFSP for small biorefineries (1000–2500 ODMT/day). Although the decentralized systems have a higher MFSP based on current analysis, it has other potential benefits such as mitigated supply chain risks and improved feedstock quality that are difficult to be quantified in this TEA.

09 BIOMASS FUELS↗

Passive and active peer effects in the spatial diffusion of residential solar panels: A case study of the Las Vegas Valley

This research analyzes the role of peer influences on the adoption of residential rooftop solar photovoltaic panels (PV) within the context of the Diffusion of Innovation Theory. PV literature indicates that adopters are influenced by word of mouth (WOM) information exchange with peers, i.e., active peer effects, while other studies suggest that living near households with visible rooftop PV installations influences adoption, i.e., passive peer effects. We bridge the gap in this literature by conducting a mixed methods analysis. We develop and administer a survey to Las Vegas Valley (LVV) residents to identify current and potential PV adopters' perceptions of peer-effects and consumer intention variables. We conduct a spatial analysis of Google's Project Sunroof data to identify LVV neighborhoods in the later stages of the PV diffusion process, i.e., those with the highest PV adoption rates. Key results show that current PV adopters living in early diffusion areas report significantly higher active and passive peer effects compared to adopters in later diffusion areas. Potential adopters in later diffusion areas report higher passive peer effects than those in early diffusion areas. Overall, because LVV has a low PV adoption rate (<3%), short term strategies aimed at increasing PV adoption should emphasize WOM active peer effects. Here, we caution against long-term green marketing strategies focusing solely on peer-effects as the PV market matures.

14 SOLAR ENERGY↗

Portable Distortion Free Large Solid Angle Coverage Detector

Neutron single crystal diffractometers require large solid angle coverage for optimum performance. This can be achieved by tiling flat detectors in a cylindrical or spherical geometry, but results in large gaps in detector coverage and parallax distortion. The detector edges exhibit degraded resolution, distortion, and gamma rejection. Since the detector edge regions are a significant fraction of the detector active area, they must be removed from the experimental data set, requiring extra beam time to collect enough analysis data. A spherical detector with a continuous surface would effectively address this issue while eliminating most boundary ‘dead’ areas. Here we report on the development of a novel hemispherical shaped neutron detector using seamlessly tiled readout modules to form the desired shape. The heart of the detector is a specially developed curved neutron scintillator coupled to high resolution silicon photomultiplier (SiPM) Anger cameras via custom made fiber optic tapers (FOTs). The detector has been assembled and initial tests have been conducted at the High Flux Isotope Reactor (HFIR) beamlines at Oak Ridge National Laboratory (ORNL). Here, in this work, we describe details of the scintillator design, fabrication and characterization, evaluation of individual detector modules, the details of the detector design implementation, and evaluation of the assembled detector at ORNL beamlines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CFD Simulations of the IHF 13-Inch Nozzle Flow: 55-deg Sphere-Cone Model, Manufactured Fences and Gaps

This paper reports computational analyses of testsin a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted using 55-deg sphere-cone models placed in a free jet downstream of the 13-inch diameter conical nozzle in the Ames 60-MW Interaction Heating Facility. Some of the sphere-cone models include surface features such as manufactured fences and gaps intended to simulate effects of differential recession, all of which disturb the flow, producing augmented heating locally and downstream.Test calibration data were obtained using slug and Gardon gage stagnation calorimeters, and a sphere-cone calorimeter model with six Gardon gages and five pressure tabs.The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested, and comparisons with the experimental measurements. These simulations take into account nonuniform total enthalpy and mass flux profiles at the nozzle inlet as well as the expansion waves emanating from the nozzle exit and their effects on the model flowfields.

Arc-jets↗

Machine Learning Applications to Metal-Silicate Equilibria and their Insights into Core Formation

An extensive number of studies have experimentally investigated how elements distribute between metal and silicate phases, to better constrain core-mantle chemical equilibrium. Here, we present a new database compiling all (to our knowledge) experimental data on liquid metal-silicate partitioning from 118 peer-reviewed publications. We applied various machine learning techniques to gain further insights into these partitioning equilibria and their dependencies. We performed a network analysis to investigate the relationship between experiments and partition coefficients, which enables visualizing gaps in the experimental dataset and biases related to varying experimental conditions and analytical setup. In addition, semi-empirical thermodynamic models are commonly used to extrapolate these chemical reactions to the wide range of pressure, temperature and compositional conditions of planetary differentiation. These models are based on linear regressions that assume continuous relationship between partition coefficients and experimental variables. Here, we considered random forest regressions, which are algorithms based on ensembles of decision trees and does not consider continuous effects of each variable. The application of this regression significantly improves the prediction of metal-silicate partitioning for several elements including Ni, Si and Cr. We will show how this new approach improves our understanding of elemental exchange between metal and silicate and their implications for the Earth’s core formation.

siderophile element↗

Tidal Resource Gaps Analysis Technical Report

The tidal resource gaps project was created to address a growing body of evidence that models underpredict tidal current speeds compared to measurements at a number of the top-ranking tidal energy sites. In response, this project compared opportunistic tidal power density measurements from 16 tidal energy hot spot sites with estimates from resource assessment data to identify discrepancies. To improve the accuracy of resource estimates from model data, updated data from eight improved model simulations were obtained. Model improvements included grid refinement, domain coupling, and the use of unstructured or nested grids. New resource estimates were calculated from the updated models, and these data were used to update the tidal hot spots-a list of promising tidal energy sites around the United States.

16 TIDAL AND WAVE POWER↗

A Multiyear Gridded Data Ensemble of Surface Biogenic Carbon Fluxes for North America: Evaluation and Analysis of Results

Accurate and fine-scale estimates of biogenic carbon fluxes are critical for measuring and monitoring the biosphere's responses and feedback to the climate system. Currently available data products from flux towers and model-intercomparison projects struggle to adequately represent spatiotemporal dynamics of surface biogenic carbon fluxes, and to quantify their uncertainties, which also are crucial to atmospheric inversion systems. To address these gaps, we introduce a new perturbed-parameter model ensemble with the CASA model to estimate surface biogenic carbon fluxes at monthly and 3-hourly scales for North America at ~500-m and 5-km resolutions. We first use the Extended Fourier Amplitude Sensitivity Testing to choose the three most sensitive parameters to be perturbed, maximum light use efficiency (E max ), optimal temperature of photosynthesis (T opt ), and temperature response of respiration (Q 10 ). The initial range for each parameter is broadly sampled for the L1 ensemble, but then we pruned E max with site-level primary productivity to derive an L2 ensemble with narrower uncertainty ranges. Ensembles are strongly correlated with site-level results at both monthly and 3-hourly scales, and the spread across L1/L2 ensemble members encompasses the range of AmeriFlux observations. Monthly variability in the L2 ensemble mean is 85% of the observed variability. The L2 ensemble outperforms diverse data products with the highest Taylor skill scores at diurnal to annual scales. Finally, the ensemble's seasonality agrees well with other models for most biome types and in high and middle latitudes, but inconsistencies are found in subtropical and tropical ecoregions and for annual totals over North America.

54 ENVIRONMENTAL SCIENCES↗