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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Myriad World Baseline: Global Geodemographic Estimates

The LandScan Myriad World Baseline (MWB) method produces global, residential (nighttime/home-location) gridded geodemographic estimates based on 5-year age/gender cohorts—at 30-arcsecond (≈1 km) resolution. MWB is designed to fill gaps where detailed, georeferenced survey data (e.g., Demographic and Health Surveys (DHS)) are missing or outdated, and to provide a baseline that can support human security analysis, including consequence assessment, “patterns of life” modeling, and scenario-based population futures. MWB’s workflow spatializes household-level age/gender characteristics from the GLOPOP-S dataset by conflating household and gridded expected relative wealth adapted from Global Gridded Relative Deprivation Index (GRDI), then adjusts them to a target year of interest. Age/gender estimates are then applied to harmonize lowest-administrative-level statistics with LandScan residential counts, yielding final geodemographic estimates. Two validation case studies are presented: Ghana (2021) and Tokyo/Kanagawa, Japan (2020), illustrating spatial variability in demographic cohorts and comparing MWB outputs to official gridded statistics. Results show close overall alignment relative to validation criteria including population pyramids and age-dependency ratios.

Tuccillo, Joe [ORNL] (ORCID:0000000259300943)↗
NASA NTRS2011

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

A rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for a curved orthogrid panel typical of launch vehicle skin structures. Several test article configurations were produced by adding component equipment of differing weights to the flight-like vehicle panel. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was employed to describe the assumed correlation of phased input sound pressures across the energized panel. This application demonstrates the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software modules developed for the RPTF method can be easily adapted for quick replacement of the diffuse acoustic field with other pressure field models; for example a turbulent boundary layer (TBL) model suitable for vehicle ascent. Wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this type of environment. Finally, component vibration environments for design were developed from the measured and predicted responses and compared with those derived from traditional techniques such as Barrett scaling methods for unloaded and component-loaded panels.

Frady, Gregory P.↗
NASA NTRS2016

Meanline Analysis of Turbines with Choked Flow in the Object-Oriented Turbomachinery Analysis Code

The prediction of turbomachinery performance characteristics is an important part of the conceptual aircraft engine design process. During this phase, the designer must examine the effects of a large number of turbomachinery design parameters to determine their impact on overall engine performance and weight. The lack of detailed design information available in this phase necessitates the use of simpler meanline and streamline methods to determine the turbomachinery geometry characteristics and provide performance estimates prior to more detailed CFD (Computational Fluid Dynamics) analyses. While a number of analysis codes have been developed for this purpose, most are written in outdated software languages and may be difficult or impossible to apply to new, unconventional designs. The Object-Oriented Turbomachinery Analysis Code (OTAC) is currently being developed at NASA Glenn Research Center to provide a flexible meanline and streamline analysis capability in a modern object-oriented language. During the development and validation of OTAC, a limitation was identified in the code's ability to analyze and converge turbines as the flow approached choking. This paper describes a series of changes which can be made to typical OTAC turbine meanline models to enable the assessment of choked flow up to limit load conditions. Results produced with this revised model setup are provided in the form of turbine performance maps and are compared to published maps.

Choked Flow↗
NASA NTRS2017

Time Domain Stability Margin Assessment of the NS Space Launch System GN&C Design for Exploration Mission One

The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation.

Clements, Keith↗
NASA NTRS2017

Time Domain Stability Margin Assessment of the NASA Space Launch System GN&C Design for Exploration Mission One

The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation.

Clements, Keith↗
DOE OSTI2024

An RC snubber design method to achieve optimized switching noise‐loss trade‐off of cascode GaN HEMTs

Abstract The cascode gallium nitride high electron mobility transistors (GaN HEMTs) are very vulnerable to self‐sustained turn‐off oscillation due to their cascode configuration. This paper presents a design approach for the RC snubber of cascode GaN HEMTs to achieve the optimized noise‐loss trade‐off. At first, an analytical model is proposed to describe the instability of cascode GaN HEMTs‐based test circuits utilizing RC snubber. Based on the model, an analytical approach is proposed to achieve two optimum RC snubber designs S1 and S2. The design S1 can satisfactorily dampen the oscillation with minimum switching losses. The design S2 achieves maximum effective damping on the oscillation at a minimized cost of additional power losses. In the end, the accuracy of the proposed model is validated by the double‐pulse test and good agreement is obtained.

Xue, Peng↗
DOE OSTI2025

Designing for cooperative grain boundary segregation in multicomponent alloys

Tailoring the nanoscale distribution of chemical species at grain boundaries is a powerful method to dramatically influence the properties of polycrystalline materials. However, classical approaches to the problem have tacitly assumed that only competition is possible between solute species. In this paper, we show that solute elements can cooperate in the way they segregate to grain boundaries: In properly targeted alloys, the different chemical species cooperate to each fill complementary grain boundary sites disfavored by the other. By developing a theoretical “spectral” approach to this problem based on quantum-accurate grain boundary site distributions, we show how grain boundaries can be cooperatively alloyed, whether by depletion or enrichment. We provide machine-learned cosegregation information for over 700 ternary aluminum-based alloys and experimentally validate the concept in one ternary alloy where cosegregation is not expected by prior models but is expected based on the cooperative model.

grain boundaries↗
DOE OSTI2017

Simultaneous Estimation of Electromechanical Modes and Forced Oscillations

Over the past several years, great strides have been made in the effort to monitor the small-signal stability of power systems. These efforts focus on estimating electromechanical modes, which are a property of the system that dictate how generators in different parts of the system exchange energy. Though the algorithms designed for this task are powerful and important for reliable operation of the power system, they are susceptible to severe bias when forced oscillations are present in the system. Forced oscillations are fundamentally different from electromechanical oscillations in that they are the result of a rogue input to the system, rather than a property of the system itself. To address the presence of forced oscillations, the frequently used AutoRegressive Moving Average (ARMA) model is adapted to include sinusoidal inputs, resulting in the AutoRegressive Moving Average plus Sinusoid (ARMA+S) model. From this model, a new Two-Stage Least Squares algorithm is derived to incorporate the forced oscillations, thereby enabling the simultaneous estimation of the electromechanical modes and the amplitude and phase of the forced oscillations. The method is validated using simulated power system data as well as data obtained from the western North American power system (wNAPS) and Eastern Interconnection (EI).

Electromechanical modes↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
NASA NTRS1995

Static stability of the Space Station solar array FASTMast structure

The combined loads test of the 3-Bay FASTMast marks the end of the Lewis Research Center (LeRC) effort to characterize the behavior of the principal Space Station solar array support structure. The primary objective of this test and analysis effort was to develop a method to predict structural stability failure modes under flight-like applied loads. Included at the beginning of this report is a brief historical perspective of the hardware design development and FASTMast structural stability problem evolution. Once an understanding of the solution process has been established, test and analysis details are presented and related to the postulated failure theories. The combined load test series subjected the structure to a combination of transverse, moment, and torsion loads similar to that expected in the service environment. Nonlinear finite element (FE) models were developed and large displacement analyses were performed to support the test effort and failure mode predictions. Details of the test configuration as well as test and analysis results are presented. The results were then critiqued to establish valid and successful support of the failure mode assessments. Finally, study conclusions are drawn and recommendations for safe operation of the FASTMast structure are presented for consideration.

Shaker, John F.↗
NASA NTRS2013

Analysis Methods for Progressive Damage of Composite Structures

This document provides an overview of recent accomplishments and lessons learned in the development of general progressive damage analysis methods for predicting the residual strength and life of composite structures. These developments are described within their State-of-the-Art (SoA) context and the associated technology barriers. The emphasis of the authors is on developing these analysis tools for application at the structural level. Hence, modeling of damage progression is undertaken at the mesoscale, where the plies of a laminate are represented as a homogenous orthotropic continuum. The aim of the present effort is establish the ranges of validity of available models, to identify technology barriers, and to establish the foundations of the future investigation efforts. Such are the necessary steps towards accurate and robust simulations that can replace some of the expensive and time-consuming "building block" tests that are currently required for the design and certification of aerospace structures.

Rose, Cheryl A.↗
DOE OSTI2024

Coal-derived conductive pavement for winter de-icing: prototype, modeling, and simulation

Existing pavement de-icing methods result in high installation and maintenance costs, traffic delays, excessive weariness and corrosion, and negative environmental and safety impacts. To overcome these challenges, this paper presents an innovative pathway to designing and constructing smart self-heating pavements using a low-cost coal-char bearing asphalt material. The conductive asphalt incorporates coal char, i.e., a key byproduct of the coal pyrolysis process, into the Stone Mastic Asphalt (SMA) mixture. This asphalt containing coal-derived solid carbon exhibits highly tailorable electrical conductivity, satisfactory mechanical and thermophysical properties, and superior cost-efficiency as compared to other conductive pavement materials. The de-icing performance was also demonstrated by laboratory experiments on a bench-scale prototype. Furthermore, an efficient thermal network model was developed and validated by experiments to investigate the transient thermal behavior and energy performance of the Ohmic heating pavement system. Furthermore, the whole-year energy simulation case studies were conducted on a bridge pavement with an annual energy use of 24.6–1444.8 kWh/m 2 , showcasing its potential in field applications across cool humid, cold humid, and subarctic/arctic climate zones.

42 ENGINEERING↗
DOE OSTI2025

A fully-integrated lattice Boltzmann method for fluid–structure interaction

Here we present a fully-integrated lattice Boltzmann (LB) method for fluid–structure interaction (FSI) simulations that efficiently models deformable solids in complex suspensions and active systems. Our Eulerian method (LBRMT) couples finite-strain solids to the LB fluid on the same fixed computational grid with the reference map technique (RMT). An integral part of the LBRMT is a new LB boundary condition for moving deformable interfaces across different densities. With this fully Eulerian solid–fluid coupling, the LBRMT is well-suited for parallelization and simulating multi-body contact without remeshing or extra meshes. We validate its accuracy via a benchmark of a deformable solid in a lid-driven cavity, then showcase its versatility through examples of soft solids rotating and settling. The LBRMT achieves a spatial convergence rate between first-order and second-order for FSI simulations and is designed for low to intermediate Reynolds number flows with finite inertia at small Mach numbers. With simulations of complex suspensions mixing, we highlight the potential of the LBRMT for studying collective behavior in soft matter and biofluid dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A model combustor for studying a reacting jet in an oscillating crossflow

This paper discusses a novel model combustion experiment that was built for studying the structure and dynamics of a reacting jet in an unsteady crossflow. A natural-gas-fired dump combustor is used to generate and sustain an acoustically oscillating vitiated flow that serves as the crossflow for transverse jet injection. Unlike most other techniques that are limited in operating pressure or acoustic amplitude, this method of generating an unsteady flow field is demonstrated at a pressure of 10 atm with peak-to-peak oscillation amplitudes approaching 20% of the mean pressure. An optically accessible test section designed for these conditions provides access for advanced laser and optical diagnostic measurements. Detailed measurements provide insight into the complex acoustic-hydrodynamic-combustion coupling processes and offer high-quality, high-resolution validation data for numerical simulations. Careful instrumentation port design considerations for the higher amplitude acoustics are detailed. As a whole, this paper focuses on select representative segments of the experiment operational space that highlight our strategy of providing an oscillatory flowfield. This includes presenting the acoustic operational space such as acoustic amplitudes, frequencies, and mode shapes. Select imaging results are then reported to support our strategies capability to produce high-fidelity measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Novel SOLPS-ITER simulations of X-point target and snowflake divertors

Abstract The design and understanding of alternative divertor configurations may be crucial for achieving acceptable steady-state heat and particle material loads for magnetic confinement fusion reactors. Multiple X-point alternative divertor geometries such as snowflakes and X-point targets have great potential in reducing power loads, but have not yet been simulated widely in codes with kinetic neutrals. This paper discusses recent changes made to the SOLPS-ITER code to allow for the simulation of X-point target and low-field side snowflake divertor geometries. Snowflake simulations using this method are presented, in addition to the first SOLPS-ITER simulation of the X-point target. Analysis of these results show reasonable consistency with the simple modelling and theoretical predictions, supporting the validity of the methodology implemented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Comparison of Single-Phase Convection in Additive Manufactured Versus Traditional Metal Foams

Abstract Metal foams have been often used for thermal management due to their favorable characteristics including high specific surface area (SSA), high thermal conductivity, and low relative density. However, they are accompanied by shortcomings including the significant contact resistances due to attachment method, as well as the need for characterization of foam parameters such as pore diameter and SSA. Additive manufactured (AM) metal foams would eliminate the substrate/foam thermal resistance, decrease the need for pre-usage characterization, and allow for tailoring structures, while also taking advantage of the characteristics of traditionally manufactured foams. A commercial, aluminum foam (nominally 5 pores per inch (PPI), 86.5% porosity) was analyzed using X-ray microcomputed tomography, and a custom-designed metal foam based on the cell diameter and porosity of the commercial sample was subsequently manufactured. Reduced domain computational fluid dynamics/heat transfer (CFD-HT) models were compared against experimental data. Postvalidation, the flow behavior, effect of varying attachment thermal conductivities, and thermal performance were numerically investigated, demonstrating the usefulness of validated pore-scale models, as well as the potential for improved performance using AM metal foams over traditionally manufactured foams.

Engineering↗
DOE OSTI2018

Synthetic Biology Open Language (SBOL) Version 2.2.0

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year’s JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Theoretical study of thermodynamic properties and reaction rates of importance in the high-speed research program

One of the primary goals of NASA's high-speed research program is to determine the feasibility of designing an environmentally safe commercial supersonic transport airplane. The largest environmental concern is focused on the amount of ozone destroying nitrogen oxides (NO(x)) that would be injected into the lower stratosphere during the cruise portion of the flight. The limitations placed on NO(x) emission require more than an order of magnitude reduction over current engine designs. To develop strategies to meet this goal requires first gaining a fundamental understanding of the combustion chemistry. To accurately model the combustor requires a computational fluid dynamics approach that includes both turbulence and chemistry. Since many of the important chemical processes in this regime involve highly reactive radicals, an experimental determination of the required thermodynamic data and rate constants is often very difficult. Unlike experimental approaches, theoretical methods are as applicable to highly reactive species as stable ones. Also our approximation of treating the dynamics classically becomes more accurate with increasing temperature. In this article we review recent progress in generating thermodynamic properties and rate constants that are required to understand NO(x) formation in the combustion process. We also describe our one-dimensional modeling efforts to validate an NH3 combustion reaction mechanism. We have been working in collaboration with researchers at LeRC, to ensure that our theoretical work is focused on the most important thermodynamic quantities and rate constants required in the chemical data base.

Langhoff, Stephen↗