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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗
DOE OSTI2026

Virtual Growth of SRF Materials: A Machine Learning Approach to Predict the Crystalline Structural Ordering in Nb Surface Oxides

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Unlisted, US, IL; Fermilab]↗
NASA NTRS2009

Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning

Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.

data analysis↗
DOE OSTI2022

Putting AlphaFold models to work with phenix.process_predicted_model and ISOLDE

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom–atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
NASA NTRS1993

Experimental validation of optimization-based integrated controls-structures design methodology for flexible space structures

An optimization-based integrated design approach for flexible space structures is experimentally validated using three types of dissipative controllers, including static, dynamic, and LQG dissipative controllers. The nominal phase-0 of the controls structure interaction evolutional model (CEM) structure is redesigned to minimize the average control power required to maintain specified root-mean-square line-of-sight pointing error under persistent disturbances. The redesign structure, phase-1 CEM, was assembled and tested against phase-0 CEM. It is analytically and experimentally demonstrated that integrated controls-structures design is substantially superior to that obtained through the traditional sequential approach. The capability of a software design tool based on an automated design procedure in a unified environment for structural and control designs is demonstrated.

Maghami, Peiman G.↗
NASA NTRS1991

Fast Approximate Analysis Of Modified Antenna Structure

Abbreviated algorithms developed for fast approximate analysis of effects of modifications in supporting structures upon root-mean-square (rms) path-length errors of paraboloidal-dish antennas. Involves combination of methods of structural-modification reanalysis with new extensions of correlation analysis to obtain revised rms path-length error. Full finite-element analysis, usually requires computer of substantial capacity, necessary only to obtain responses of unmodified structure to known external loads and to selected self-equilibrating "indicator" loads. Responses used in shortcut calculations, which, although theoretically "exact", simple enough to be performed on hand-held calculator. Useful in design, design-sensitivity analysis, and parametric studies.

Levy, Roy↗
NASA NTRS1999

Composite Fuselage Technology

Work was conducted over a ten-year period to address the central issue of damage in primary load-bearing aircraft composite structure, specifically fuselage structure. This included the three facets of damage resistance, damage tolerance, and damage arrest. Experimental, analytical, and numerical work was conducted in order to identify and better understand the mechanisms that control the structural behavior of fuselage structures in their response to the three aspects of damage. Furthermore, work was done to develop straightforward design methodologies that can be employed by structural designers in preliminary design stages to make intelligent choices concerning the material, layup, and structural configurations so that a more efficient structure with structural integrity can be designed and built. Considerable progress was made towards achieving these goals via this work. In regard to damage tolerance considerations, the following were identified as important effects: composite layup and associated orthotropy/structural anisotropy, specifics of initial local damage mechanisms, role of longitudinal versus hoop stress, and large deformation and associated geometric nonlinearity. Means were established to account for effects of radius and for the nonlinear response. In particular, nondimensional parameters were identified to characterize the importance of nonlinearity in the response of pressurized cylinders. This led to the establishment of a iso-nonlinear-error plot for reference in structural design. Finally, in the case of damage tolerance, the general approach of the original methodology to predict the failure pressure involving extending basic plate failure data by accounting for the local stress intensification was accomplished for the general case by accounting for the mechanisms noted by utilizing the capability of the STAGS finite element code and numerically calculating the local stress intensification for the particular configuration to be considered. For the issue of damage arrest, placement of and configuration of stiffeners (including stiffener curvature), and magnitude and orientation of principal strains due to local bending were found to be key considerations. Means were established to account for stiffener effectiveness quantitatively based on radius, slit size, stiffener curvature' and relative bending stifffiesses involved. Geometric nonlinearity was also found to play an - 24 - important role here. Furthermore, it was determined that damage propagation is controlled by different mechanisms (hoop stress versus flapping stress and the associated factors involved in each) depending upon the direction of damage propagation. This latter item results in an inability to scale these phenomena in one test due to the different factors involved. Finally, the importance of shell curvature and associated instability in response to transverse loading including impact were found to be important considerations in damage resistance. A technique, involving asymmetric meshing of a finite element mesh, was developed to predict this behavior and showed excellent correlation with experimental results. Further details of these ten years of work are presented herein with references made to the fourteen documents produced during this work where full details can be found. Implications of this work are discussed and recommendations made. Although it is clear that there is more work to be done to fully understand composite fuselage technology and specifically the overall issue of damage in primary load-bearing composite structures, important understanding and capability has been extended via this work.

Lagace, Paul A.↗
DOE OSTI2018

Error fields in the Wendelstein 7-X stellarator

The role of error fields in stellarators is explored in this work through simulations of, and experiments performed on, the Wendelstein 7-X (W7-X) stellarator. Previous experimental results, based on limiter plasmas in W7-X, suggest that error fields are small in the experiment based on limiter plasmas. In this work, we document results from the first divertor campaign on W7-X with a focus on error fields resonant with the edge island divertor structure. Measurements obtained using divertor thermocouples corroborate earlier limiter results that the error fields are small and correctable, requiring only 5% of the total rated current of the trim coil system. The effect of these error fields on magnetic geometry and topology are investigated using the flux surface measurement technique. The resulting divertor thermal load asymmetry is modeled via field line diffusion and compared to experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Abstract. Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models. To quantify the aerosol mixing state, we used the aerosol mixing state indices for submicron aerosol based on the mixing of optically absorbing and non-absorbing species (χo), the mixing of primary carbonaceous and non-primary carbonaceous species (χc), and the mixing of hygroscopic and non-hygroscopic species (χh). To achieve a spatiotemporal comparison, we calculated the mixing state indices using output from the Community Earth System Model with the four-mode version of the Modal Aerosol Module (MAM4) and compared the results with the mixing state indices from a benchmark machine-learned model trained on high-detail particle-resolved simulations from the particle-resolved stochastic aerosol model PartMC-MOSAIC. The two methods yielded very different spatial patterns of the mixing state indices. In some regions, the yearly averaged χ value computed by the MAM4 model differed by up to 70 percentage points from the benchmark values. These errors tended to be zonally structured, with the MAM4 model predicting a more internally mixed aerosol at low latitudes and a more externally mixed aerosol at high latitudes compared to the benchmark. Our study quantifies potential model bias in simulating mixing state in different regions and provides insights into potential improvements to model process representation for a more realistic simulation of aerosols towards better quantification of radiative forcing and aerosol–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The impact of curation errors in the PDBBind Database on machine learning predictions of protein–protein binding affinity

The PDBBind database has been widely utilized for the computational prediction of protein–protein binding affinities. While the accuracy of the PDBBind-curated equilibrium dissociation constants (K D ) has been reported for the protein–ligand subset of the PDBBind database, the curation accuracy has not been reported for the protein–protein subset. Here, we present a detailed manual analysis for the subset of PDBBind records with PubMed Central Open Access primary publications and find that ~19% of these records had K D values that were not supported by their primary publications. The impact of these putative curation errors on the machine learning-based prediction of K D from experimental protein–protein 3D structures was evaluated and correcting the curation errors improved the Pearson correlation coefficient between measured and random forest-predicted log 10 (K D ) values by ~8 percentage points. This finding underscores the importance of dataset accuracy for computational modelling and highlights the need for more stringent curation processes when extracting information from the scientific literature.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

An analysis of the effects of coincident errors on multi-version software

The present study is concerned with the application of a model which provides a basis for analytical investigations of redundant software. The model links certain basic quantities with the experimental process of testing independently designed software components. The model is employed to provide insight into the effects of coincident errors on an N-version software structure in which the structure fails if at least a majority of its components fail. Attention is given to coincident errors, the intensity distribution for coincident errors, the coincident errors model, and a condition for redundancy to improve reliability.

Eckhardt, D. E., Jr.↗
NASA NTRS1979

Configuration management and automatic control of an augmentor wing aircraft with vectored thrust

An advanced structure for automatic flight control logic for powered-lift aircraft operating in terminal areas is under investigation at Ames Research Center. This structure is based on acceleration control; acceleration commands are constructed as the sum of acceleration on the reference trajectory and a corrective feedback acceleration to regulate path tracking errors. The central element of the structure, termed a Trimmap, uses a model of the aircraft aerodynamic and engine forces to calculate the control settings required to generate the acceleration commands. This report describes the design criteria for the Trimmap and derives a Trimmap for Ames experimental augmentor wing jet STOL research aircraft.

Cicolani, L. S.↗
NASA NTRS1984

Optimization of Antenna Structure Design

Optimality criteria design is applied for large antenna structures with multiple constraints on microwave performance. The constraints are on accuracy of the structure: restrictions on the microwave pathlength error, and the antenna pointing error. The examples given show convergence to low-weight feasible designs that satisfy the constraints. Truss-member sizes are automatically selected from tables of commercially available structural shapes, and approximations results from the method of selection are found moderate. The multiple constraint design is shown to be more effective in meeting constraints than the old envelop method. For practical structures, the new design method can be performed within reasonable core size and computation time.

Levy, R.↗
DOE OSTI2022

PM4Stell: A prototype permanent magnet stellarator structure

Permanent magnets provide a possible solution to simplify complicated stellarator coils. Here, a prototype permanent magnet stellarator structure, PM4Stell, has been funded to demonstrate the technical feasibility of using permanent magnets to create the shaping field of a stellarator. Permanent magnets in uniform cubes with three polarization directions will be carefully placed to generate the required magnetic field for a National Compact Stellarator eXperiment-like equilibrium together with planar toroidal field coils. Discrete magnets will be glued together and inserted into a “post-office-box-like” supporting structure. Electromagnetic and structural analyses have been done to validate the design. Error field correction magnets will be used to shim possible error fields. The design efforts of the prototype permanent magnet stellarator structure are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2006

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei (CCN) concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.

Ghan, Stephen J.↗
NASA NTRSDate not supplied

Root Cause Analysis of the Data Refinement Process – Medical Conditions Capability Resource Tables

The medical system for spaceflight thus far has been designed to support missions in low earth orbit (LEO). Crew capabilities are limited and heavily dependent on the team of medical support staff at Mission Control Center (MCC) to guide diagnosis and management. However, missions to the Moon and Mars will suffer from several constraints that will make this ground support focused approach to care ineffective. In order to update and modify medical system design, NASA has relied on Probabilistic Risk Assessment (PRA) modeling to mitigate medical risk through trade space analysis. Specifically, capability resource tables (CRT’s) were developed to create a dataset of resources required to manage a list of accepted medical conditions significant in exploration spaceflight. With 120 conditions, this dataset contained hundreds of capabilities and thousands of resources with tens of thousands of cells of data. Initially these tables were built in excel for high throughput during development, but ultimately had to be transferred, managed, and modified into the Evidence Library database for modeling purposes. The process of collating and reviewing the Evidence Library revealed numerous errors in the dataset that had to be corrected through iterative changes. Several error types emerged during this process and can be broken into specific classifications defined as “input”, “transcription”, “structural”, “branching”, and “information”. In reviewing these error types through the root cause analysis (RCA) approach, we were able to identify the contributors to these errors which included single data review points, changing product end goals, limited software selection, time constraints and several others. By reviewing and evaluating the underlying causes we can provide possible system improvements that can be implemented for current and future data management in PRA model inputs.

A. Anderson↗