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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 OSTI2022

Physics demonstration and verification of MOOSE framework reactor module meshing capabilities

The recently developed Reactor module in the open-source MOOSE framework includes finite element meshing capabilities for analysis of common reactor geometries. Capabilities in the Reactor module have been employed to generate meshes for physics applications including a sodium-cooled fast reactor core analysis using Griffin, a fast reactor assembly thermal deformation analysis using MOOSE Tensor Mechanics, and a heat-pipe cooled microreactor coupled analysis using Griffin, Bison, and Sockeye. The process to build these meshes using MOOSE's meshing capabilities is described. Physics simulation results using MOOSE-based meshes have been verified to match results which leverage external meshing software such as Cubit or Argonne's Mesh Tools. MOOSE's Reactor module provides significant advantages compared to the use of external meshing tools when analyzing Cartesian and hexagonal reactor lattices using MOOSE-based applications: accessibility to the end user, low barrier to entry for new users, speed of mesh generation, volume preservation of meshed fuel pins, and simplification of analysis workflow when using MOOSE applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1981

Estimation and correction of advection effects with single and multiple, conventional and Doppler radars

The laws of fluid motion are invariant under a Gallilean transformation. For a perfect observing system, the data analysis should, therefore, also be invariant under a Gallilean transformation. This invariance is often not preserved in practical observing systems. In this connection, it is often advisable to perform mesoscale analysis in a frame moving with respect to the earth's surface. In the present investigation the velocity of such a frame is referred to as an advection velocity. The investigation is concerned with remaining problems regarding the Gallilean transformation. The establishment of a frame of reference for the achievement of maximum coherence is considered, taking into account the case of given nonsimultaneous observations of scalars or Cartesian vectors. It is found that advection speed can be estimated objectively if a scalar or Cartesian vector can be observed directly and if, in addition, the time and position of each observation is approximately known.

Gal-Chen, T.↗
DOE OSTI2026

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗
NASA NTRS2007

Roller Bearing Health Monitoring Using CPLE Frequency Analysis Method

This paper describes a unique vibration signature analysis technique Coherence Phase Line Enhancer (CPLE) Frequency Analysis - for roller bearing health monitoring. Defects of roller bearing (e.g. wear, foreign debris, crack in bearing supporting structure, etc.) can cause small bearing characteristic frequency shifts due to minor changes in bearing geometry. Such frequency shifts are often too small to detect by the conventional Power Spectral Density (PSD) due to its frequency bandwidth limitation. This Coherent Phase Line Enhancer technology has been evolving over the last few years and has culminated in the introduction of a new and novel frequency spectrum which is fully described in this paper. This CPLE technology uses a "key phasor" or speed probe as a preprocessor for this analysis. With the aid of this key phasor, this CPLE technology can develop a two dimensional frequency spectrum that preserves both amplitude and phase that is not normally obtained using conventional frequency analysis. This two-dimensional frequency transformation results in several newly defined spectral functions; i. e. CPLE-PSD, CPLE-Coherence and the CPLE-Frequency. This paper uses this CPLE frequency analysis to detect subtle, low level bearing related signals in the High Pressure Fuel Pump (HPFP) of the Space Shuttle Main Engine (SSME). For many rotating machinery applications, a key phasor is an essential measurement that is used in the detection of bearing related signatures. There are times however, when a key phasor is not available; i. e. during flight of any of the SSME turbopumps or on the SSME High Pressure Oxygen Turbopump (HPOTP) where no speed probe is present. In this case, the CPLE analysis approach can still be achieved using a novel Pseudo Key Phasor (PKP) technique to reconstruct a 1/Rev PKP signal directly from external vibration measurements. This paper develops this Pseudo Key Phasor technique and applies it to the SSME vibration data.

Jong, Jen-Yi↗
NASA NTRS1997

Shape Optimization by Bayesian-Validated Computer-Simulation Surrogates

A nonparametric-validated, surrogate approach to optimization has been applied to the computational optimization of eddy-promoter heat exchangers and to the experimental optimization of a multielement airfoil. In addition to the baseline surrogate framework, a surrogate-Pareto framework has been applied to the two-criteria, eddy-promoter design problem. The Pareto analysis improves the predictability of the surrogate results, preserves generality, and provides a means to rapidly determine design trade-offs. Significant contributions have been made in the geometric description used for the eddy-promoter inclusions as well as to the surrogate framework itself. A level-set based, geometric description has been developed to define the shape of the eddy-promoter inclusions. The level-set technique allows for topology changes (from single-body,eddy-promoter configurations to two-body configurations) without requiring any additional logic. The continuity of the output responses for input variations that cross the boundary between topologies has been demonstrated. Input-output continuity is required for the straightforward application of surrogate techniques in which simplified, interpolative models are fitted through a construction set of data. The surrogate framework developed previously has been extended in a number of ways. First, the formulation for a general, two-output, two-performance metric problem is presented. Surrogates are constructed and validated for the outputs. The performance metrics can be functions of both outputs, as well as explicitly of the inputs, and serve to characterize the design preferences. By segregating the outputs and the performance metrics, an additional level of flexibility is provided to the designer. The validated outputs can be used in future design studies and the error estimates provided by the output validation step still apply, and require no additional appeals to the expensive analysis. Second, a candidate-based a posteriori error analysis capability has been developed which provides probabilistic error estimates on the true performance for a design randomly selected near the surrogate-predicted optimal design.

Patera, Anthony T.↗
NASA NTRSDate not supplied

Assessing Organic Preservation and the Implications for Potential Biosignatures in the Bastide Member of the Séítah Formation, Jezero Crater

Introduction: Olivine has the highest CO2 trapping potential of ultramafic minerals, due to its rapid rate of dissolution and high percentage of divalent cations/unpolymerized silicate tetrahedra [1]. It generates divalent carbonates from CO2 and sequesters CO2 into the mineral matrix of the target lithology. The co-occurrence of olivine and carbonate within abraded targets from the Bastide Member of the Séítah Formation (Fm) of the Jezero crater floor [2] suggests the carbonation of olivine occurred within the mineral matrix hosted in a subsurface system. Hydrothermal origins for the subsurface system are hypothesized from orbital data [3]. This is supported by the detection of hydration features within the rock as well as the carbonate features are solely detected within the abrasion patch but not the rock’s surface. Organic preservation potential of abrasion patches: We incorporated the SHERLOC/WATSON results acquired from the Dourbes, Garde, and Quartier abrasion patches in the Séítah Fm to investigate the organomineral associations, and determine the biosignature preservation potential of these rocks. Dourbes is dominated by olivine and has minor amounts of carbonate, hydrated Ca-sulfate, and amorphous or microcrystalline silicate. Fluorescence features (330-340 nm) are detected in discrete locales and could be consistent with double ring aromatic organic molecules; yet, these features do not appear to be associated with an identified mineral phase. Dark subhedral to euhedral olivine grains within the Garde abrasion patch often co-occur with carbonate-consistent spectral signatures in all analyzed scans. The availability of Fe2+ is a known influence on olivine dissolution rates [1] and SuperCam estimates of the olivine composition (Forsterite-60 average for Sols 202-234) may thereby provide a constraint on the carbonation extent. Carbonated olivine phenocrysts within the matrix may be due to aqueous alteration, as the carbonation of nodules is consistent with observations in other hydrothermal systems and within Martian meteorites (ALH84001) [4]. In comparison, the Quartier abrasion patch represents an extensively altered endmember within the Bastide Member of the Séítah Fm. It contains a fluorescence doublet at 305/325 nm that coexists with multiple species of Na-sulfate and Mg-sulfate, Mg-carbonates, olivine [5]. Aqueous alteration and implications for habitability: The identification of primary and secondary mineral phases observed in the Bastide Member suggests the release of cations from primary ultramafic minerals through aqueous alteration. Within Garde, the carbonate detected appears to be Mg-rich and likely formed from the in situ alteration of Mg-rich olivine within the region as carbonate has only been detected within the rock via in situ analysis. Carbonates derived from abiotic and biotic reactions preserve biosignatures (i.e. indices of habitability) on Earth. The detected carbonate phase found in association with fluorescent features within the rock matrix may also indicate potential organic compounds preserved in a putative hydrothermal system. Fluorescent features (~330 nm) are unique to Garde and Dourbes, though they are co-located to carbonate signatures solely within Garde, and between the light toned minerals. Identification of these fluorescent features may be consistent with 1-2 ring aromatic compounds. The limit of detection for Raman is multiple orders of magnitude greater than the limit of detection required for fluorescence [6]. Implications for provenance: Hydrothermal systems represent disequilibrium chemical conditions that are hypothesized to have supported the emergence of life and also preserve ancient carbon within precipitated carbonates [7]. Hydrothermal system associated carbonates are capable of preserving biosignatures up to an estimated ~3.77 – 4.28 Gya [8]. Thus, carbonated olivine found within the Séítah Fm may represent a high-potential biosignature preserving environment on Mars. The formation of carbonates by an aqueous alteration process, such as carbonation of olivine is also consistent with hypotheses for carbonate within the greater regional-olivine bearing unit [2,3], which contains Garde, Dourbes, and Quartier. Acknowledgments: This work was carried out at the Jet Propulsion Laboratory, The California Institute of Technology under a contract from NASA. References: [1] Wood et al., (2019) ES&T, 6, 10. [2] Stack, K. et al., (2020) Space Sci Rev, 216, 127. [3] Tarnas, J. et al., (2021) JGR: Planets, 126, 11. [4] Steele et al., (2007) Meteorit. Planet. Sci., 42, 9. [5] Murphy, A.E. et al., (2022) LPSC [6] Bhartia et al., (2021) Space Sci Rev, 217, 58. [7] Luther (2021) GRL, 48, e2021GL094869. [8] Dodd et al., (2017) Nature, 543, 60-64

E L Cardarelli↗
NASA NTRS2011

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗
NASA NTRS1997

Local Analysis of Shock Capturing Using Discontinuous Galerkin Methodology

The compact form of the discontinuous Galerkin method allows for a detailed local analysis of the method in the neighborhood of the shock for a non-linear model problem. Insight gained from the analysis leads to new flux formulas that are stable and that preserve the compactness of the method. Although developed for a model equation, the flux formulas are applicable to systems such as the Euler equations. This article presents the analysis for methods with a degree up to 5. The analysis is accompanied by supporting numerical experiments using Burgers' equation and the Euler equations.

Atkins, H. L.↗
DOE OSTI2022

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Abstract Projection of land use and land‐cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land‐use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well‐defined conservation goals while minimizing impacts to agriculture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Energetic Copolymers From LLM-105 and Aliphatic Isocyanates

Energetic polymers typically feature fuel-rich backbones with pendant oxidizing explosophores, which are used to modify pressure and temperature characteristics in energetic formulations. However, these pendant explosophores generally increase sensitivity and decrease the thermal stability of the polymer in the condensed phase. Direct polymerization of insensitive high explosives (IHEs) bearing polymerizable functionalities, such as amines, provides a synthetic platform for deriving tunable energetic materials. Here, this work demonstrates the first direct polymerization of the IHE 2,6-diamino-3,5-dinitropyrazine-1-oxide (LLM-105) with aliphatic isocyanate comonomers to yield an energetic copolyurea (PUa1) and an energetic copolyurea network (PUa2). 1 H and 13 C nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy (FTIR) confirm copolyurea synthesis. PUa1 exhibited branching reactions commonly found in polyurea syntheses, and these side reactions were suppressed in PUa2 through use of a polyfunctional isocyanate. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) demonstrate the energetic IHE based polyurea preserves the energetic decomposition of the parent monomer LLM-105 in PUa1 (1203 J g −1 ) and PUa2 (687 J g −1 ), albeit with reduced thermal stability with peak decomposition temperatures of 235°C and 233°C, respectively. This work presents a new approach for generating energetic polymers from IHE cores with tunable energetic, thermal, and structural characteristics.

Chemistry↗
DOE OSTI2026

Solvation-guided inhibition of manganese dissolution of lithium- and manganese- rich cathode via cyclic carbonate molecular engineering

Lithium and manganese-rich (LMR) layered oxides represent a leading class of high-energy cathode materials, but their practical realization is fundamentally limited by severe manganese (Mn) dissolution, a process that triggers structural degradation and rapid capacity fade. While mitigation efforts have predominantly focused on interfacial engineering, the intrinsic contribution of bulk electrolyte solvation to this degradation pathway remains largely unexplored, primarily due to the difficulty of deconvolving its effects from concurrent cathode-electrolyte interphase (CEI) formation. Here, we report an experimental design to isolate the role of solvation. We systematically varied the electrolyte solvent solvation power by substituting the strongly coordinating ethylene carbonate (EC) with its weaker coordinating fluorinated derivatives, fluoroethylene carbonate (FEC) and trans-4,5-Difluoro-1,3-dioxolan-2-one (DFEC), while maintaining a consistent interfacial chemistry. Remarkably, the electrolyte formulated with the weakest solvent, DFEC, exhibits superior cycling stability, suppressing Mn dissolution by up to 63% relative to the conventional EC-based system. Post-mortem analysis unequivocally attributes this performance enhancement to the preservation of the LMR cathode's structural integrity, a direct consequence of mitigated Mn dissolution. This work provides conclusive evidence that modulating bulk electrolyte solvation is a potent and direct strategy for stabilizing LMR cathodes, establishing a vital design principle for next-generation battery systems.

25 ENERGY STORAGE↗
DOE OSTI2024

Role of physics in physics-informed machine learning

Physical systems are characterized by inherent symmetries, one of which is encapsulated in the units of their parameters and system states. These symmetries enable a lossless order-reduction, e.g., via dimensional analysis based on the Buckingham theorem. Despite the latter's benefits, machine learning (ML) strategies for the discovery of constitutive laws seldom subject experimental and/or numerical data to dimensional analysis. We demonstrate the potential of dimensional analysis to significantly enhance the interpretability and generalizability of ML-discovered secondary laws. Our numerical experiments with creeping fluid flow past solid ellipsoids show how dimensional analysis enable both deep neural networks and sparse regression reproduce old results, e.g., Stokes law for a sphere, and generate new ones, e.g., an expression for an ellipsoid misaligned with the flow direction. Furthermore, our results suggest the need to incorporate other physics-based symmetries and invariances into ML-based techniques for equation discovery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Taweret: a Python package for Bayesian model mixing

Uncertainty quantification using Bayesian methods is a growing area of research. Bayesian model mixing (BMM) is a recent development which combines the predictions from multiple models such that the fidelity of each model is preserved in the final result. Practical tools and analysis suites that facilitate such methods are therefore needed. Taweret introduces BMM to existing Bayesian uncertainty quantification efforts. Currently, Taweret contains three individual Bayesian model mixing techniques, each pertaining to a different type of problem structure; we encourage the future inclusion of user-developed mixing methods. Taweret’s first use case is in nuclear physics, but the package has been structured such that it should be adaptable to any research engaged in model comparison or model mixing.

Ingles, Kevin↗
NASA NTRS1980

The Lockheed OSO-8 program. Analysis of data from the mapping X-ray heliometer experiment

The final report describes the extent of the analysis effort, and other activities associated with the preservation and documentation of the data set are described. The main scientific results, which are related to the behavior of individual solar activity regions in the energy band 1.5 - 15 keV, are summarized, and a complete bibliography of publications and presentations is given. Copies of key articles are also provided.

Acton, L. W.↗
NASA NTRS1994

A stochastic precipitation disaggregation scheme for GCM applications

In the surface hydrologic parameterization of general circulation models (GCMs), it is commonly assumed that the precipitation processes are homogeneous over a GCM grid square and that the precipitation intensity is uniformly distributed. Based on evidence that the spatial distribution of precipitation within a GCM grid square is crucial for the land surface hydrology parameterization, a few researchers have explored the impacts of assuming that the precipitation is exponentially distributed. This paper explores the suitability of the aforementioned assumptions. First, a statistical analysis is conducted of historical precipitation data for three GCM grids in different regions of the United States. The analysis suggests that neither the uniform nor the exponential distribution assumption may be suitable at the GCM grid scale and, that instead, the spatial variability in precipitation is characterized by statistical patterns that are inhomogeneous. These patterns vary from grid to grid and are induced by the interaction between atmospheric conditions and various land surface characteristics, such as topographical features, surface properties, etc. Within the same grid square, however, the statistical patterns are generally constant from year to year. Based on this analysis, a computationally viable (i.e., usable with GCMs) stochastic precipitation disaggregation scheme that utilizes these stable statistical patterns is proposed. The method was used to generate spatially distributed hourly rainfall for a summer season in the southwestern region of the continental United States. Analysis of the results shows that the methodology preserves the seasonal characteristics of spatial variability in precipitation that is observed in the long-term historical data.

Gao, Xiaogang↗
NASA NTRS1994

Experiment K-7-23: Effect of Spaceflight on Level and Function of Immune Cells: Immunology Studies - Part 1

Two different experiments were carried out in this segment of the immunology protocol for samples received from rats flown on Cosmos 2044. Control groups included vivarium, synchronous and antiorthostatically suspended rats. In the first experiment, rat bone marrow cells were examined in Moscow for their response to recombinant murine colony stimulating factor-granulocyte / monocyte (CSF-GM). In the second experiment, rat spleen and bone marrow cells were stained in Moscow with a variety of antibodies directed against cell surface antigenic markers. These cells were preserved and shipped to the United States for analysis on a flow cytometer. The results of the studies indicated that bone marrow cells from flown and suspended rats showed a decreased response to CSF-GM as compared to bone marrow cells from control rats. Spleen cells from flown rats showed increased percentages of suppressor-cytotoxic-T and helper-T cells amongst the entire cell population. Bone marrow cells showed an increase in the percentage of helper-T cells in the myelogenous population and increased percentages of anti-asialo GM-1 bearing, interleukin-2 receptor bearing, pan-T and helper-T cells in the lymphocytic population. Cell populations from rats suspended antiorthostatically did not follow the same pattern of distribution of leukocytes as cell populations for flown rats. These results are similar, but not identical to, earlier results from Cosmos 1887, and confirm that space flight can have profound effects on immune system components and activities.

Sonnenfeld, G.↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
NASA NTRS2014

State Event Models for the Formal Analysis of Human-Machine Interactions

The work described in this paper was motivated by our experience with applying a framework for formal analysis of human-machine interactions (HMI) to a realistic model of an autopilot. The framework is built around a formally defined conformance relation called "fullcontrol" between an actual system and the mental model according to which the system is operated. Systems are well-designed if they can be described by relatively simple, full-control, mental models for their human operators. For this reason, our framework supports automated generation of minimal full-control mental models for HMI systems, where both the system and the mental models are described as labelled transition systems (LTS). The autopilot that we analysed has been developed in the NASA Ames HMI prototyping tool ADEPT. In this paper, we describe how we extended the models that our HMI analysis framework handles to allow adequate representation of ADEPT models. We then provide a property-preserving reduction from these extended models to LTSs, to enable application of our LTS-based formal analysis algorithms. Finally, we briefly discuss the analyses we were able to perform on the autopilot model with our extended framework.

State-event Models↗