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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Required developments in structural dynamics

The finite element method, modal component synthesis, and the use of fast Fourier transformation were key developments in structural dynamics in the past 15 to 20 years. Current areas requiring additional effort include: (1) the correct calculation of modal shape and natural frequencies for complex structures; (2) the correlation of math models with test data; (3) the establishment of a criteria for "goodness" of the correlation between analysis and test; (4) the selection of the correct displacement functions when using computer programs for modal synthesis; (5) accuracy of response calculations; and (6) the inverse problem of determining the force problem from the response data. Trends identified include the use of distributed computing, greater reliance on analysis, and the possible use of artificial intelligence techniques, or some way of feeding back information, to provide solution guidance to engineers.

Wada, B. K.↗
NASA NTRS1997

Test Verification of the Cassini Spacecraft Dynamic Model

The Cassini spacecraft mission to Saturn will be launched in October 1997, on a Titan IV/Centaur launch vehicle. Cassini is the largest interplanetary spacecraft ever developed. Before launch approval can be obtained, a test verified finite element model of the Cassini spacecraft must be completed and approved by NASA. The correctness of this model is critical to the final verification coupled loads analysis and margin of safety assessments.

Cassini↗
DOE OSTI2025

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2023

Finite Element Model Tuning using Analytical Sensitivity Values

This paper presents an efficient approach for tuning finite element models to match the measured ground vibrationtest and proof test data. Frequencies, mode shapes, total weight, location of the center of gravity, and staticdeformation computed from the finite element model are matched to the measured data. The model tuningprocedure used in this work is based on solving an optimization problem in which the errors for the consideredmetrics, between the finite element prediction and the measured data, are minimized. Analytical sensitivity values ofperformance indices are computed using the NASTRAN-generated sensitivity values together with the in-housecomputer programs, which allow for faster computational time and the use of gradient-based optimizers. The methodis applied to the Aerostructures Test Wing 4 model. The study shows that the military standard and the NASAstandard for comparing analytical and experimental modal data are all satisfied. The final finite element modelcorrelates well with the test data. The flutter speed decreases by 8.91% after model tuning compared with the original Aerostructures Test Wing 4 design.

Chan-gi Pak↗
NASA NTRS1984

Effects of warping and pretwist on torsional vibration of rotating beams

The effect of pretwist and warping on the torsional vibration of short-aspect-ratio rotating beams is examined for application to the modeling of turbofan, turboprop, and compressor blades. The equations of motion and the associated boundary conditions by using both Wagner's hypothesis and Washizu's theory are derived and a few minor limitations of the Wagner's hypothesis, as applied to thick blades, are pointed out and discussed. The equations for several special cases are solved in a closed form. Results are presented indicating the effect of warping, pretwist, and rotation on torsional vibration of beams as aspect ratio is varied. The results show that the structural warping and pretwist terms have a significant effect on torsional frequency and mode shapes of short-aspect-ratio blades whereas the inertial warping terms have negligible effect. Since the torsional frequencies and mode shapes are very important in aeroelastic analyses by using modal methods, the structural warping terms should be included in modeling turbofan, turboprop, compressor, and turbine blades.

Kaza, K. R. V.↗
NASA NTRS1986

Analysis and simulation of the MAST (COFS-1 flight hardware)

In-house analysis work in support of the Control of Flexible Structures (COFS) program is being performed at the NASA Langley Research Center. The work involves evaluation of the proposed design configuration, controller design as well as actuator dynamic modeling, and MAST/actuator dynamic simulation of excitation and damping. A complete finite element model of the MAST has been developed. This finite element model has been incorporated into an optimization procedure which minimizes total mass while maintaining modal coupling. Results show an increase in the total mass due to additional constraints (namely, the diagonal frequency constraint) imposed on the baseline design. A valid actuator dynamic model is presented and a complete test sequence of the proposed flight experiment is demonstrated. The actuator dynamic model is successfully used for damping and the stroke limitations for first mode excitation are demonstrated. Plans are to incorporate additional design variables and constraints into the optimization procedure (such as actuator location) and explore alternative formulations of the objective function. A different actuator dynamic model to include hardware limitations will be investigated.

Horta, Lucas G.↗
NASA NTRS2011

Ares I-X In-Flight Modal Identification

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Bartkowicz, Theodore J.↗
NASA NTRS1988

Initial test results on state estimation on the SCOLE mast

Modal state estimation tests are performed on the SCOLE mast for the fixed Shuttle platform case. Kalman filter state estimation results from a five mode computer model of the SCOLE mast, developed from a finite element analysis, are compared with those state estimates obtained from laboratory tests. Two comparison runs are presented, one an excitation of the first two bending modes, another, an excitation of the first torsional mode of the mast. Results from both runs show poor agreement in modal estimation between the computer model simulations and the laboratory test data. At present, the reason(s) for this poor performance is unknown. Both the laboratory hardware and software and the computer model are being checked for possible sources of errors. Further computer simulations as well as laboratory testing will be performed.

Sparks, D., Jr.↗
NASA NTRS1989

Design of a flexure mount for optics in dynamic and cryogenic environments

The design of a flexure mount for a mirror operating in a cryogenic environment is presented. This structure represents a design effort recently submitted to NASA Ames for the support of the primary mirror of the Space Infrared Telescope Facility (SIRTF). The support structure must passively accommodate the differential thermal contraction between the glass mirror and the aluminium structure of the telescope during cryogenic cooldown. Further, it must support the one meter diameter, 116 kilogram (258 pound) primary mirror during a severe launch to orbit without exceeding the micro-yield of the material anywhere in the flexure mount. Procedures used to establish the maximum allowable radial stiffness of the flexural mount, based on the finite element program NASTRAN and the optical program FRINGE, are discussed. Early design concepts were evaluated using a parametric design program, and the development of that program is presented. Dynamic loading analyses performed with NASTRAN are discussed. Methods of combining modal responses resulting from a displacement response spectrum analysis are discussed, and a combination scheme called MRSS, modified root of sum of squares, is presented. Model combination schemes using MRSS, SRSS, and ABS are compared to the results of the modal frequency response analysis performed with NASTRAN.

Pollard, Lloyd Wayne↗
DOE OSTI2024

Improving BC Mixing State and CCN Activity Representation With Machine Learning in the Community Atmosphere Model Version 6 (CAM6)

Abstract Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non‐BC species and large mass ratio of coating to BC ( R BC , the mass ratio of non‐BC species to BC in BC‐containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle‐resolved simulations to the CAM6 with MAM4 (MAM4‐ML). In MAM4‐ML, we use R BC to partition accumulation mode particles into two new modes, BC‐free particles and BC‐containing particles. We adjust R BC to make the modeled BC mixing state index ( χ mode ) match the one predicted by the ML model ( χ ML ). On a global average, the mass fraction of BC‐containing particles in accumulation mode decreases from 100% (MAM4‐default) to 48% (MAM4‐ML). The globally averaged χ mode decreases from 78% (MAM4‐default) to 63% (MAM4‐ML, 19% reduction) and agrees well with χ ML (66%). The R BC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC‐containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs.

Meteorology & Atmospheric Sciences↗
NASA NTRSDate not supplied

Satellite-Derived Imagery and Transfer Learning: A Novel Technique for Land Cover Classification

Land cover classification is a continuing research topic due to its relevance to land use and land cover changes from impacts such as climate change, agriculture, urbanization, and hazardous weather. Simple access to frequently changing land cover classifications could provide knowledge and decision support to various researchers and agencies across the globe for each of above-mentioned and related influences. This research aims to provide a novel technique for land cover classification of remote sensing imagery; harnessing Artificial Neural Networks and transfer learning (TL). Knowledge sharing techniques within machine learning are typically utilized when training datasets are sparse or transitions between data modalities is required. In this case, two data modalities, multi and hyperspectral data, are considered for knowledge transfer. The large number of continuous spectral bands available from hyperspectral sensors typically provide increased sophisticated land classification capability compared to more traditional multispectral imagery with limited discrete spectral bands. However, large-scale, frequent access to hyperspectral imagery is relatively limited. The proposed classification technique would therefore prove useful in regions in which hyperspectral data are not readily available for classification but multispectral data are. Image segmentation models are trained on each multi and hyperspectral datasets. Knowledge sharing techniques are then applied to each model to understand what knowledge, if any, is gained when moving between the data modalities. The datasets utilized for training and testing a U-Net model include the European Space Agency’s multispectral imager Sentinel-2 and the hyperspectral German Aerospace Center’s Earth Sensing Imaging Spectrometer (DESIS). Initially, only two classes, land and water, are classified for simplicity. However, more complex classes can be added if knowledge sharing is successful. The workflow for image classification through supervised image segmentation with a U-Net model will be discussed along with metrics calculated before and after TL for both Sentinel-2 and DESIS data are applied. Additionally, future steps to advance the sophistication of this technique as well as other applicable methodologies will be explored.

Emily Foshee↗
NASA NTRS1992

Aeroelastic stability analyses of two counter rotating propfan designs for a cruise missile model

Aeroelastic stability analyses were performed to insure structural integrity of two counterrotating propfan blade designs for a NAVY/Air Force/NASA cruise missile model wind tunnel test. This analysis predicted if the propfan designs would be flutter free at the operating conditions of the wind tunnel test. Calculated stability results are presented for the two blade designs with rotational speed and Mach number as the parameters. A aeroelastic analysis code ASTROP2 (Aeroelastic Stability and Response of Propulsion Systems - 2 Dimensional Analysis), developed at LeRC, was used in this project. The aeroelastic analysis is a modal method and uses the combination of a finite element structural model and two dimensional steady and unsteady cascade aerodynamic models. This code was developed to analyze single rotation propfans but was modified and applied to counterrotating propfans for the present work. Modifications were made to transform the geometry and rotation of the aft rotor to the same reference frame as the forward rotor, to input a non-uniform inflow into the rotor being analyzed, and to automatically converge to the least stable aeroelastic mode.

Mahajan, Aparajit J.↗
NASA NTRS2003

Identification of Computational and Experimental Reduced-Order Models

The identification of computational and experimental reduced-order models (ROMs) for the analysis of unsteady aerodynamic responses and for efficient aeroelastic analyses is presented. For the identification of a computational aeroelastic ROM, the CFL3Dv6.0 computational fluid dynamics (CFD) code is used. Flutter results for the AGARD 445.6 Wing and for a Rigid Semispan Model (RSM) computed using CFL3Dv6.0 are presented, including discussion of associated computational costs. Modal impulse responses of the unsteady aerodynamic system are computed using the CFL3Dv6.0 code and transformed into state-space form. The unsteady aerodynamic state-space ROM is then combined with a state-space model of the structure to create an aeroelastic simulation using the MATLAB/SIMULINK environment. The MATLAB/SIMULINK ROM is then used to rapidly compute aeroelastic transients, including flutter. The ROM shows excellent agreement with the aeroelastic analyses computed using the CFL3Dv6.0 code directly. For the identification of experimental unsteady pressure ROMs, results are presented for two configurations: the RSM and a Benchmark Supercritical Wing (BSCW). Both models were used to acquire unsteady pressure data due to pitching oscillations on the Oscillating Turntable (OTT) system at the Transonic Dynamics Tunnel (TDT). A deconvolution scheme involving a step input in pitch and the resultant step response in pressure, for several pressure transducers, is used to identify the unsteady pressure impulse responses. The identified impulse responses are then used to predict the pressure responses due to pitching oscillations at several frequencies. Comparisons with the experimental data are then presented.

Silva, Walter A.↗
NASA NTRS2018

Quantification of Dynamic Model Validation Metrics Using Uncertainty Propagation from Requirements

The Space Launch System, NASA's new large launch vehicle for long range space exploration, is presently in the final design and construction phases, with the first launch scheduled for 2019. A dynamic model of the system has been created and is critical for calculation of interface loads and natural frequencies and mode shapes for guidance, navigation, and control (GNC). Because of the program and schedule constraints, a single modal test of the SLS will be performed while bolted down to the Mobile Launch Pad just before the first launch. A Monte Carlo and optimization scheme will be performed to create thousands of possible models based on given dispersions in model properties and to determine which model best fits the natural frequencies and mode shapes from modal test. However, the question still remains as to whether this model is acceptable for the loads and GNC requirements. An uncertainty propagation and quantification (UP and UQ) technique to develop a quantitative set of validation metrics that is based on the flight requirements has therefore been developed and is discussed in this paper. There has been considerable research on UQ and UP and validation in the literature, but very little on propagating the uncertainties from requirements, so most validation metrics are "rules-of-thumb;" this research seeks to come up with more reason-based metrics. One of the main assumptions used to achieve this task is that the uncertainty in the modeling of the fixed boundary condition is accurate, so therefore that same uncertainty can be used in propagating the fixed-test configuration to the free-free actual configuration. The second main technique applied here is the usage of the limit-state formulation to quantify the final probabilistic parameters and to compare them with the requirements. These techniques are explored with a simple lumped spring-mass system and a simplified SLS model. When completed, it is anticipated that this requirements-based validation metric will provide a quantified confidence and probability of success for the final SLS dynamics model, which will be critical for a successful launch program, and can be applied in the many other industries where an accurate dynamic model is required.

Brown, Andrew M.↗
NASA NTRS1991

Investigation of the aeroelastic stability of the AFW wind-tunnel model using CAP-TSD

The Computational Aeroelasticity Program - Transonic Small Disturbance (CAP-TSD) code, developed at the NASA Langley Research Center, is applied to the Active Flexible Wing (AFW) wind tunnel model for prediction of the model's transonic aeroelastic behavior. A semi-span computational model is used for evaluation of symmetric motions and a full span model is used for evaluation of antisymmetric motions. Static aeroelastic solutions using CAP-TSD are computed. Dynamic (flutter) analyses are then performed as perturbations about the static aeroelastic deformations and presented as flutter boundaries in terms of Mach number and dynamic pressure. Flutter boundaries that take into account modal refinements, vorticity and entropy corrections, antisymmetric motions and sensitivity to the modeling of the wing tip ballast stores are also presented and compared with experimental flutter results.

Silva, Walter A.↗
NASA NTRS1992

Investigation of the aeroelastic stability of the AFW wind-tunnel model using CAP-TSD

The Computational Aeroelasticity Program - Transonic Small Disturbance (CAP-TSD) code is applied to the Active Flexible Wing (AFW) wind tunnel model for prediction of the model's transonic aeroelastic behavior. A semi-span computational model is used for evaluation of symmetric motions and a full span model is used for evaluation of antisymmetric motions. Static aeroelastic solutions using CAP-TSD are computed. Dynamic flutter analyses are then performed as perturbations about the static aeroelastic deformations and presented as flutter boundaries in terms of Mach number and dynamic pressure. Flutter boundaries that take into account modal refinements, vorticity, and entropy corrections, antisymmetric motions and sensitivity to the modeling of the wing tip ballast stores are also presented and compared with experimental flutter results.

Silva, Walter A.↗
NASA NTRS1992

Further investigations of the aeroelastic behavior of the AFW wind-tunnel model using transonic small disturbance theory

The CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code, developed at the NASA Langley Research Center, is applied to the Active Flexible Wing wind-tunnel model for prediction of transonic aeroelastic behavior. A semi-span computational model is used for evaluation of symmetric motions, and a full-span model is used for evaluation of antisymmetric motions. Static aeroelastic solutions using CAP-TSD are computed. Dynamic (flutter) analyses then are performed as perturbations about the static aeroelastic deformations and presented as flutter boundaries in terms of Mach number and dynamic pressure. Flutter boundaries that take into account modal refinements, vorticity and entropy corrections, antisymmetric motions and sensitivity to the modeling of the wing tip ballast stores also are presented and compared with experimental flutter results.

Silva, Walter A.↗