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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
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Advancing Air Mobility: Few-Shot Learning in Airspace Research and Development

The advancement of Air Mobility, particularly in the context of Advanced Air Mobility (AAM) and Urban Air Mobility (UAM), represents a transformative shift in aviation's role in modern society. A comprehensive understanding of requirement consistency is paramount for fostering interoperability, standardization, and cost-effectiveness within airspace systems. This paper introduces a novel approach utilizing a pretrained Sentence Transformers model and few-shot learning to address this crucial aspect task of flagging potentially inconsistent requirements. Few-shot learning supports the development of this future through ensuring the accuracy and consistency of identified requirements with little human oversight. This approach offers a promising solution to the challenges of requirement consistency identification in airspace systems. By harnessing the power of advanced NLP techniques with fine-tuned models, stakeholders can enhance efficiency, accuracy, and scalability; ultimately fostering improved interoperability, standardization, and cost-effectiveness in airspace management.

Natural Language Processing↗
DOE OSTI2025

A standards perspective on genomic data reusability and reproducibility

Genomic and metagenomic sequence data provides an unprecedented ability to re-examine findings, offering a transformative potential for advancing research, developing computational tools, enhancing clinical applications, and fostering scientific collaboration. However, effective and ethical reuse of genomics data is hampered by numerous technical and social challenges. The International Microbiome and Multi’Omics Standards Alliance (IMMSA, https://www.microbialstandards.org/) and the Genomic Standards Consortium (GSC, https://gensc.org) hosted a 5-part seminar series “A Year of Data Reuse” in 2024 to explore challenges and opportunities of data reuse and reproducibility across disparate domains of the genomic sciences. Addressing these challenges will require a multifaceted approach, including common metadata reporting, clear communication, standardized protocols, improved data management infrastructure, ethical guidelines, and collaborative policies that prioritize transparency and accessibility. We offer strategies to enable responsible and technically feasible data reuse, recognition of data reproducibility challenges, and emphasizing the importance of cross-disciplinary efforts in the pursuit of open science and data-driven innovation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Characterization of Triaxial Braided Composite Material Properties for Impact Simulation

The reliability of impact simulations for aircraft components made with triaxial braided carbon fiber composites is currently limited by inadequate material property data and lack of validated material models for analysis. Improvements to standard quasi-static test methods are needed to account for the large unit cell size and localized damage within the unit cell. The deformation and damage of a triaxial braided composite material was examined using standard quasi-static in-plane tension, compression, and shear tests. Some modifications to standard test specimen geometries are suggested, and methods for measuring the local strain at the onset of failure within the braid unit cell are presented. Deformation and damage at higher strain rates is examined using ballistic impact tests on 61- by 61- by 3.2-mm (24- by 24- by 0.125-in.) composite panels. Digital image correlation techniques were used to examine full-field deformation and damage during both quasi-static and impact tests. An impact analysis method is presented that utilizes both local and global deformation and failure information from the quasi-static tests as input for impact simulations. Improvements that are needed in test and analysis methods for better predictive capability are examined.

Roberts, Gary D.↗
NASA NTRS2015

Risk Informed Philosophy: Using What We Fear to Lose to Guide Us to Success

When an organization sets out on a new effort, program, or project, one of the first steps undertaken is to understand the related requirements. Most often, these requirements come in the form of standards, directives, or other organizational processes, and are derived to meet a broad range of efforts, programs, and projects. The net result is that organizations or teams are forced to start with a maximum set of requirements and expend time and energy tailoring the set of requirements down to what is more appropriate for the effort, program, or project at hand. This presentation will present an alternate method for the application of requirements or best practices that is based upon the actual risks to the safety, performance, or success of the effort. This additive route for applying best practices and requirements also encourages an early exploration of the risks, thus yielding a better understanding of where resources should be applied. This presentation also extends this concept of risk-based application of best practices and requirements to the selection of organization-wide improvement or standardization efforts, such as Lean, Six Sigma, and Quality Management Systems.

Darpel, Scott↗
NASA NTRS2016

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Environment↗
NASA NTRS1994

Accelerated panel methods using the fast multipole method

Panel methods are commonly used in computational fluid dynamics for the solution of potential flow problems. The methods are a numerical technique based on the surface distribution of singularity elements. The solution is the process of finding the strength of the singularity elements distributed over the body's surface. This process involves the solution of the matrix problem Pq = p' for a set of unknowns q. The Fast Multipole Method is used to directly compute q without using matrix solvers. The algorithm works in O(N) time for N points, a great improvement over standard matrix solvers. In panel methods, the surface of a body is divided into a series of quadrilateral panels. The methods involve the computation of the influence of all other panels on each individual panel. The influence is based on the surface distribution, though this can be approximated by the area for distant panels. An alternative approximation, though with arbitrary accuracy, is to develop a multipole expansion about the center of the panel to describe the effect of a given panel on distant points in space. The expansion is based on the moments of the panel, thus allow the use of various surface distributions without changing the basic algorithm, just the computation of the various moments. The expansions are then manipulated in a tree walk to develop Taylor series expansions about a point in space which describe the effect of all distant panels on any point within a volume of convergence. The effect of near panels then needs to be computed directly, but the effect of all distant panels can be computed by simply evaluating the resulting expansion. The Fast Multipole Method has been applied to panel methods for the solution of source and doublet distributions. A major feature of the algorithm is that the algorithm does not change to derive the potential and velocity for sources and doublets. The same expansions can be used for both sources and doublets. Since the velocity is related to the potential, and the doublet potential is related to the z-component of the source velocity, all values can be derived from the same expansion by taking a series of partial derivatives. This requires more expansion terms to be kept since terms are lost in the process of taking partial derivatives. Thus to maintain accuracy for the doublet computation, more terms are required than if just evaluating for sources. The resulting Fast Multipole code should then parallelize better than classical panel methods due to the locality of data dependencies found in the Fast Multipole Method. Theoretically the parallelized code should execute in O(log N) time with O(N) processors, though this is not practical. Ongoing work includes implementing the parallel accelerated panel method, including methods to improve the load balancing of the problem by taking advantage of the known geometry of panels, and to encorporate sensitivity analysis into the algorithm.

Leathrum, James F., Jr.↗
NASA NTRS1969

An improved atomic hydrogen frequency and time standard

Use of a large bulb, long-multipole magnet, automatic tuner and aluminum cavity provides an improved hydrogen maser which is accurate over long periods of time and suitable for tracking station environments.

Mc Gunigal, T. E.↗
DOE OSTI2024

CO 2 Uptake and Stability Enhancement in Vinyltrimethoxysilane‐Treated SBA‐15 Solid Amine‐Based Sorbents

Abstract Silica‐supported amine absorbents, including materials produced by tethering aminosilanes or infusion of poly(ethyleneimine), represent a promising class of materials for CO 2 capture applications, including direct air and point source capture. Various silica surface treatments and functionalization strategies are explored to enhance stability and CO 2 uptake in amine‐based solid sorbent systems. Here, the synthesis and characterization of novel vinyltrimethoxysilane‐treated Santa Barbara Amorphous‐15 (SBA‐15) supports and the corresponding enhancement in CO 2 uptake compared to various SBA‐15‐based control supports are presented. The relationship between CO 2 diffusion and amine efficiency in these systems is explored using a previously reported kinetic model. The synthesized materials are characterized with CO 2 and H 2 O isotherms, diffuse reflectance infrared Fourier transform spectroscopy, 1 H T 1 – T 2 relaxation correlation NMR, and rapid thermal cycling experiments. The novel support materials are shown to enable high amine efficiencies, approaching a fourfold improvement over standard SBA‐15‐supported amines, while simultaneously exhibiting excellent stability when cycled rapidly under humid conditions. As the poly(ethyleneimine) loadings are held constant across the various samples, enhancements in CO 2 uptake are attributed to differences in the way the poly(ethyleneimine) interacts with the support surface.

Vallace, Anthony↗
DOE OSTI2025

Pathways for decarbonization of the buildings sector in Ukraine

The paper focuses on Ukraine’s intention to achieve a two-thirds reduction in buildings’ energy consumption for heating and cooling by 2050, concurrently aiming for net zero greenhouse gas emissions and heightened energy security. Here, the study examines the outcomes of retrofitting existing residential, commercial, and public buildings with highly efficient materials, improving construction standards, and transitioning to advanced heating systems. However, Russia’s invasion in 2022 inflicted substantial damage, prompting a shift from retrofit and decarbonization to reconstruction. The Ukrainian government’s Reconstruction Plan emphasizes clean, sustainable, and resilient energy systems. The study employs energy system and integrated assessment models (TIMES-Ukraine and GCAM-Ukraine) to explore scenarios taking into consideration the war, reconstruction, and a net zero CO 2 pathway. Using two models allowed the inter-model comparison. The analysis addresses vital questions on energy resiliency measures and the compounding effects of decarbonization. Findings indicate that Ukraine’s energy goals can be met through strategic retrofitting and economy-wide decarbonization, emphasizing the importance of low-carbon alternatives like district heating with renewable sources. Electrification with renewables and fuel-switching emerges as crucial for achieving building decarbonization. The study offers valuable insights into navigating energy challenges amidst the war and outlines a pathway for Ukraine’s sustainable energy future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Binding of Phosphate Species to Ca 2+ and Mg 2+ in Aqueous Solution

Phosphate derivatives and their interaction with metal cations are involved in many important biological phenomena, so an accurate characterization of the phosphate-metal interaction is necessary to properly understand the role of phosphate-metal contacts in mediating biological function. Herein, we improved the standard 12-6 Lennard-Jones (LJ) potential via the usage of the 12-6-4 LJ model, which incorporates ion-induced dipole interactions. Via parameter scanning, we fine-tuned the 12-6-4 LJ polarizability values to obtain accurate absolute binding free energies for the phosphate anions H 2 PO 4 – , HPO 4 2– , PO 4 3– coordinating with Ca 2+ and Mg 2+ . First, we modified the phosphate 12-6-4 LJ parameters to reproduce the solvation free energies of the series of phosphate anions using the thermodynamic integration (TI) method. Then, using the potential mean force (PMF) method, the polarizability of the metal-phosphate interaction was obtained. We show that the free energy profiles of phosphate ions coordinated to Ca 2+ and Mg 2+ generally show similar trends at longer metal–phosphate distances, while the absolute binding energy values increased with deprotonation. The resulting parameters demonstrate the flexibility of the 12-6-4 LJ-type nonbonded model and its usefulness in accurately describing cation–anion interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Diagnosing the representation of surface and layered soil moisture in Earth system models

Surface soil moisture (mrsos) and vertically integrated soil moisture (mrsol) over the top 10 cm should, by definition, be physically consistent in Earth System Models (ESMs). However, an evaluation of nine CMIP6 models reveals substantial inconsistencies: in some models, mrsos and integrated mrsol agree globally; in others, they align only in specific regions; and in a few, they diverge across all grid cells. These discrepancies arise from a combination of factors, including metadata errors, inconsistent variable definitions, or diagnostic sequencing within the model. We demonstrate how such issues can lead to significant biases, even when both variables are present and seemingly well-defined. As model complexity increases and multi-model comparisons become more common, assumptions about variable equivalence may lead to flawed conclusions. This study highlights the need for routine consistency checks, improved metadata standards, and community-wide practices that ensure reliability of derived variables across ESM outputs, particularly in preparation for CMIP7.

Earth system models↗
DOE OSTI2024

Modelling the impact of host galaxy dust on type Ia supernova distance measurements

Type Ia Supernovae (SNe Ia) are a critical tool in measuring the accelerating expansion of the universe. Recent efforts to improve these standard candles have focused on incorporating the effects of dust on distance measurements with SNe Ia. In this paper, we use the state-of-the-art Dark Energy Survey 5 year sample to evaluate two different families of dust models: empirical extinction models derived from SNe Ia data and physical attenuation models from the spectra of galaxies. In this work, we use realistic simulations of SNe Ia to forward-model different models of dust and compare summary statistics in order to test different assumptions and impacts on SNe Ia data. Among the SNe Ia-derived models, we find that a logistic function of the total-to-selective extinction R V best recreates the correlations between supernova distance measurements and host galaxy properties, though an additional 0.02 mag of grey scatter is needed to fully explain the scatter in SNIa brightness in all cases. These empirically derived extinction distributions are highly incompatible with the physical attenuation models from galactic spectral measurements. From these results, we conclude that SNe Ia must either preferentially select extreme ends of galactic dust distributions, or that the characterization of dust along the SNe Ia line-of-sight is incompatible with that of galactic dust distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Searches for CE ν NS and physics beyond the standard model using Skipper-CCDs at CONNIE

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) aims to detect the coherent scattering ( CE ν NS ) of reactor antineutrinos off silicon nuclei using thick fully depleted high-resistivity silicon CCDs. Two Skipper-CCD sensors with subelectron readout noise capability were installed at the experiment next to the Angra-2 reactor in 2021, making CONNIE the first experiment to employ Skipper-CCDs for reactor neutrino detection. We report on the performance of the Skipper-CCDs, the new data processing, data quality, and event selection for CE ν NS interactions, which enable CONNIE to reach a record low detection threshold of 15 eV. The data were collected over 300 days in 2021–2022 and correspond to exposures of 14.9 g-days with the reactor-on and 3.5 g-days with the reactor-off. The difference between the reactor-on and off event rates shows no excess and yields upper limits for the neutrino interaction rates, comparable with previous CONNIE limits from standard CCDs and higher exposures. Searches for new neutrino interactions beyond the Standard Model improve the previous CONNIE limit on a simplified model with light vector mediators. A first dark matter (DM) search by diurnal modulation by CONNIE obtains the best limits on the DM-electron scattering cross section by a surface-level experiment. These promising results, obtained using a very small-mass sensor, illustrate the potential of Skipper-CCDs to probe rare neutrino interactions and motivate the plans to increase the detector mass in the near future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A Practical Solver for Scalar Data Topological Simplification

This paper presents a practical approach for the optimization of topological simplification, a central pre-processing step for the analysis and visualization of scalar data. Given an input scalar field f and a set of “signal” persistence pairs to maintain, our approaches produces an output field g that is close to f and which optimizes (i) the cancellation of “non-signal” pairs, while (ii) preserving the “signal” pairs. In contrast to pre-existing simplification algorithms, our approach is not restricted to persistence pairs involving extrema and can thus address a larger class of topological features, in particular saddle pairs in three-dimensional scalar data. Our approach leverages recent generic persistence optimization frameworks and extends them with tailored accelerations specific to the problem of topological simplification. Extensive experiments report substantial accelerations over these frameworks, thereby making topological simplification optimization practical for real-life datasets. Our approach enables a direct visualization and analysis of the topologically simplified data, e.g., via isosurfaces of simplified topology (fewer components and handles). We apply our approach to the extraction of prominent filament structures in three-dimensional data. Specifically, we show that our pre-simplification of the data leads to practical improvements over standard topological techniques for removing filament loops. Here, we also show how our approach can be used to repair genus defects in surface processing. Finally, we provide a C++ implementation for reproducibility purposes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Wind Turbine Rotors of the Future: A Research Agenda from the Big Adaptive Rotor Project

This white paper outlines a roadmap to inform future research efforts around the wind turbine rotors of the future. The document is authored by researchers that have been working on the Big Adaptive Rotor (BAR) and related initiatives at the National Renewable Energy Laboratory and Sandia National Laboratories. The Wind Energy Technologies Office of the U.S. Department of Energy has been funding BAR since 2018. The learnings from BAR have been documented in dozens of publications. This new paper identifies unresolved critical challenges in wind turbine rotor technology and structures them in four large topic areas: 1. Predictive and validated numerical tools. 2. Design methods and standards. 3. Improvements in manufacturing. 4. Technological innovations. Although wind turbines have not changed in their core architecture, with the market almost entirely dominated by three-bladed upwind rotors, a vast amount of research has allowed to introduce technological innovations resulting in a reduction in levelized cost of energy that made wind competitive with all traditional sources of electricity. Focusing on the rotor, blades will keep following the trend of mass and stiffness reduction, will adopt segmentation, and will keep growing in length, both land-based and offshore. To support this continuous innovation, this white paper argues that research efforts in rotor technology at the national labs are best directed to the first three topic areas and to low technology-readiness-levels (1-3) innovations, leaving the task of implementing higher-TRL (4-9) technological innovations to industry stakeholders. This research roadmap is also well aligned with the upcoming roadmap defined during the International Energy Agency 109th Topical Expert Meeting on the Grand Challenges of Wind Energy.

17 WIND ENERGY↗
DOE OSTI2025

The Poisson tensor completion non-parametric differential entropy estimator

We introduce the Poisson tensor completion (PTC) estimator, a non-parametric differential entropy estimator. The PTC estimator leverages inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial Poisson process. The Poisson tensor decomposition leads to a completion of the intensity measure over all bins—including those containing few to no samples—and leads to our proposed PTC differential entropy estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values and so can be safely used directly in entropy estimation. Our estimator is the first tensor-based estimator that exploits the underlying spatial Poisson process related to the histogram explicitly when estimating the probability density with low-rank tensor decompositions for the purpose of tensor completion. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

42 ENGINEERING↗
DOE OSTI2025

Safety Hazards of Batteries and Hydrogen Storage Systems in Proximity

This report addresses the safety concerns and mitigations for battery failures and their impact on hydrogen storage systems. Through an analysis of failure modes, this report highlights the risks posed by thermal runaway and chemical emissions caused by batteries. Although rare, battery thermal failure events may prompt the opening of the relief valve on the hydrogen tank. Strategies such as battery management systems, thermal management systems, and multiple thermally activated pressure relief devices can mitigate these risks. Potential simulations and experiments to better quantify the unique risks posed by lithium-ion batteries near tanks are suggested. Improving safety standards will enable integration of batteries and hydrogen storage systems in various energy storage technologies.

08 HYDROGEN↗
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗