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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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NASA NTRS1975

EMGAN: A computer program for time and frequency domain reduction of electromyographic data

An experiment in electromyography utilizing surface electrode techniques was developed for the Apollo-Soyuz test project. This report describes the computer program, EMGAN, which was written to provide first order data reduction for the experiment. EMG signals are produced by the membrane depolarization of muscle fibers during a muscle contraction. Surface electrodes detect a spatially summated signal from a large number of muscle fibers commonly called an interference pattern. An interference pattern is usually so complex that analysis through signal morphology is extremely difficult if not impossible. It has become common to process EMG interference patterns in the frequency domain. Muscle fatigue and certain myopathic conditions are recognized through changes in muscle frequency spectra.

Hursta, W. N.↗

NASA NTRS2024

A Convexification-Based Outer-Approximation Method for Convex and Nonconvex MINLP

The advancement of domain reduction techniques has significantly enhanced the performance of solvers in mathematical programming. This paper delves into the impact of integrating convexification and domain reduction techniques within the Outer-Approximation method. We propose a refined convexification-based Outer-Approximation method alongside a Branch-and-Bound method for both convex and nonconvex Mixed-Integer Nonlinear Programming problems. These methods have been developed and incorporated into the open-source Mixed-Integer Nonlinear Decomposition Toolbox for Pyomo-MindtPy. Comprehensive benchmark tests were conducted, validating the effectiveness and reliability of our proposed algorithms. These tests highlight the improvements achieved by incorporating convexification and domain reduction techniques into the Outer-Approximation and Branch-and-Bound methods.

Optimization↗

DOE OSTI2025

Seismic response of vertical dry storage casks under three-dimensional earthquake motions

Ensuring the long-term seismic safety of dry storage casks (DSCs) is becoming increasingly critical as these systems evolve from temporary to de facto permanent repositories for spent nuclear fuels. Traditional seismic soil–structure interaction (SSI) assessment methods use one-dimensional deconvolution or simplified boundary conditions to model incident waves. Although computationally appealing, simplifying assumptions may alter the seismic risk by neglecting the full complexity of three-dimensional (3D) wave propagation effects. To address this challenge, this paper introduces a novel high-fidelity computational framework that leverages the Domain Reduction Method (DRM) with perfectly matched layers (PML) to accurately transfer complex, 3D seismic wavefields from regional-scale fault-rupture simulations into local-scale finite element models of DSCs. Using broadband, physics-based ground motions from a generic M w 7.0 strike-slip event, both single-cask and multi-cask configurations were investigated under near- and far-field conditions. Emphasis is placed on capturing complex SSI, spatial variability in the ground motion, and nonlinear phenomena such as cask rocking and sliding. Numerical results demonstrate that near-field conditions, where forward directivity and fling-step effects dominate, lead to significantly higher DSC rocking and sliding. Far-field cases, by contrast, generally exhibit modest responses. Incorporating SSI tends to amplify or alter DSC response spectra and introduce response variability, which underscores the need for site-specific evaluations and robust modeling approaches to ensure the seismic integrity of DSCs in interim spent fuel storage installations.

Das, Tonmoy↗

DOE OSTI2025

Boundary Corrections for Kernel Approximation to Differential Operators

The kernel-based approach to operator approximation for partial differential equations has been shown to be unconditionally stable for linear PDEs and numerically exhibit unconditional stability for non-linear PDEs. These methods have the same computational cost as an explicit finite difference scheme but can exhibit order reduction at boundaries. In previous work on periodic domains, order reduction was addressed, yielding high-order accuracy. The issue addressed in this work is the elimination of order reduction of the kernel-based approach for a more general set of boundary conditions. Further, we consider the case of both first and second order operators. To demonstrate the theory, we provide not only the mathematical proofs but also experimental results by applying various boundary conditions to different types of equations. The results agree with the theory, demonstrating a systematic path to high order for kernel-based methods on bounded domains.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Modelling chaotic vibrations using NASTRAN

Due to the unavailability and, later, prohibitive cost of the computational power required, many phenomena in nonlinear dynamic systems have in the past been addressed in terms of linear systems. Linear systems respond to periodic inputs with periodic outputs, and may be characterized in the time domain or in the frequency domain as convenient. Reduction to the frequency domain is frequently desireable to reduce the amount of computation required for solution. Nonlinear systems are only soluble in the time domain, and may exhibit a time history which is extremely sensitive to initial conditions. Such systems are termed chaotic. Dynamic buckling, aeroelasticity, fatigue analysis, control systems and electromechanical actuators are among the areas where chaotic vibrations have been observed. Direct transient analysis over a long time period presents a ready means of simulating the behavior of self-excited or externally excited nonlinear systems for a range of experimental parameters, either to characterize chaotic behavior for development of load spectra, or to define its envelope and preclude its occurrence.

Sheerer, T. J.↗

NASA NTRS1988

Modal model reduction or model reduction of large space structures in frequency domain

Large space structures are characterized by a large number of modes, grouped frequencies, and small inherent damping. Model reduction techniques in time domain may not be effective due to small damping. The model truncation method is generally used. This method can not solve the problem of grouped frequencies, and will lose all the information about the higher order modes. A new method developed in this paper, which tries to minimize the error of interested transfer functions, makes use of all the information of the original system, and achieves improvement not only from a smaller error of transfer functions but also from better frequency distribution.

Mifang, Ruan↗

DOE OSTI2025

Denoising Seismograms in the Time Domain Using a Deep Learning Model

Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.

P-waves↗

NASA NTRS1994

Non-Reflecting Regions for Finite Difference Methods in Modeling of Elastic Wave Propagation in Plates

Solution of the wave equation using techniques such as finite difference or finite element methods can model elastic wave propagation in solids. This requires mapping the physical geometry into a computational domain whose size is governed by the size of the physical domain of interest and by the required resolution. This computational domain, in turn, dictates the computer memory requirements as well as the calculation time. Quite often, the physical region of interest is only a part of the whole physical body, and does not necessarily include all the physical boundaries. Reduction of the calculation domain requires positioning an artificial boundary or region where a physical boundary does not exist. It is important however that such a boundary, or region, will not affect the internal domain, i.e., it should not cause reflections that propagate back into the material. This paper concentrates on the issue of constructing such a boundary region.

Kishoni, Doron↗

NASA NTRSDate not supplied

Zircon (U-Th)/He Impact Crater Thermochronometry and the Effects of Shock Microstructures on Helium Diffusion Kinetics

Accurate and precise age determination of impact cratering events remains challenging and often contentious; less than half of all known craters are regarded as accurately and precisely dated. Zircon (U-Th)/He (ZHe) dating of impactites can be employed to date medium to large impact structures as ZHe ages can be fully reset in minutes at T >1000°C, a plausible scenario in the central melt pool. In contrast, complete resetting of ZHe at 200-300°C, encountered near the crater margins or due to post-impact hydrothermal overprinting, may take >103-6 years. To test the reliability of ZHe impact dating, we have quantified the effects of shock-induced microstructures on helium diffusion kinetics in well-characterized variably shocked zircon. We investigated samples from two impact structures, the Chicxulub multi-ring crater and Ries complex crater, to compare diffusion kinetics from structures with different size, age, and hydrothermal system longevity. Shock microstructures were characterized by backscattered-electron imaging prior to determining the He diffusion kinetics by prograde and retrograde fractional-release experiments via light-bulb furnace with incremental step-heating (10°C) from 300°C to 600°C. Next, we examine the internal interconnectivity and sizes of the diffusion domains by EBSD. While we found that zircon with few shock microstructures exhibited no marked deviation from helium diffusion kinetics of undamaged zircon, zircon grains with planar microstructures and granular textures are characterized by a dramatic decrease in helium retentivity due to the reduction in the effective domain size and the introduction of interconnected fast diffusion pathways. A subset of grains were ZHe dated and showed that less deformed grains yielded a weighted mean age within error of the accepted impact ages, while the grains with planar microstructures or granular textures gave systematically younger ages. These new diffusion data and ZHe ages demonstrate that highly shocked grains are unsuitable for ZHe impact crater dating. Therefore, detailed characterization of impact-induced microstructures is critical for determining accurate ZHe impact ages and offers the possibility of investigating post-impact hydrothermal circulation.

Zircon↗

DOE OSTI2024

Efficient Dimension Reduction of Complex Three-dimensional CO2 Saturation using Deep Learning Models

In the domain of deep learning (DL), dimension reduction is crucial for enhancing training efficiency and mitigating overfitting, particularly when managing complex data such as three-dimensional (3D) saturation data. The 3D saturation data in the context of geological carbon storage (GCS) presents unique challenges due to its inherent sparsity and the abrupt transitions at plume boundaries, known as shock fronts. To address the challenges, we proposed a novel DL framework that integrates dimension reduction with advanced 3D reconstruction techniques. Our model leveraged latent variables derived from 2D average saturation data, offering a robust and efficient solution tailored to the intricate dynamics of 3D saturation fields. The proposed framework can extract the critical features of the high-dimensional data while reducing the variable numbers, which is more tractable for DL models and enhances the model robustness and accuracy. Therefore, it provides a novel approach for modeling and analyses in complex geological scenarios, which finds great potential applications in environmental monitoring and energy storage.

Wang, Hongsheng↗

NASA NTRSDate not supplied

Zircon (U-Th)/He Impact Crater Thermochronometry and the Effects of Shock Microstructures on Helium Diffusion Kinetics

Absolute age determination of impact cratering events remains difficult and often controversial; a challenge that has resulted in < 50% of known impact craters regarded as accurately and precisely dated. Besides conventional 40Ar/39Ar and U-Pb methods, zircon (U-Th)/He (ZHe) dating of impactites has been applied to large- to medium-sized impact structures. ZHe dates can be fully reset in minutes at 1000°C, which is commonly reached in central sections of the melt sheet, whereas resetting of ZHe at <300°C, which might be encountered near the crater margins or persist in post-impact hydrothermal systems, may take >103-6 years. There is a critical need to quantify the effects of shock-induced microstructures and impact metamorphism on helium diffusion kinetics in well-characterized, variably shocked zircon to further establish the reliability of (U-Th)/He for dating impacts. For this purpose, we investigated suevite and impact melt samples from two impact structures, the Chicxulub multi-ring basin and the Ries complex crater, which enables us to compare zircon helium diffusion kinetics from impact structures with differing sizes, ages, and hydrothermal system longevities. Shock microstructures were characterized by backscattered-electron (BSE) imaging prior to diffusion step-heating fractional release experiments using light-bulb furnace with prograde and retrograde incremental 10°C steps from 250°C to 600°C. Afterward, we characterize the diffusion domain sizes and their interconnectivity within the shocked zircon grains using electron backscatter diffraction (EBSD). We find that zircon with few shock microstructures exhibit no significant deviation from helium diffusion kinetics of undamaged zircon. In contrast, zircon grains with planar deformation features (PDFs) and granular textures classified by BSE and EBSD are characterized by a dramatic decrease in helium retentivity, similar to radiation damaged grains, due to a reduction in the effective domain size and the introduction of interconnected fast diffusion pathways created by shock microstructures. A subset of grains were dated by ZHe after the external morphology of the grains was determined by BSE imaging. The euhedral grains yielded a weighted mean age within the uncertainty of the accepted impact ages, whereas the grains with PDFs or granular textures exhibited younger ages. Thus, these diffusion experiments and ZHe dates suggest that the dramatic decrease in domain size likely renders shocked grains more susceptible to impact-induced hydrothermal resetting and subsequent overprinting. Hence, characterization of shock microstructures is critical for determining accurate impact ages using ZHe methods especially when applied to previously unconstrained craters. The thermochronometer also offers the opportunity to determine the magnitude and duration of post-impact hydrothermal circulation.

zircon↗

NASA NTRS2016

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗

NASA NTRSDate not supplied

Zircon (U-TH)/He Impact Crater Thermochronometry and the Effects of Shock Microstructures on Helium Diffusion Kinetics

Accurate age determinations of hyper-velocity impact and cratering events remains difficult and often controversial, while less than half of all known impact craters are regarded as accurately and precisely dated. Besides 40Ar/39Ar and U-Pb methods, zircon (U-Th)/He dating of impactites is a burgeoning technique to date large- to medium-sized impact structures. Zircon (U-Th)/He ages can be fully reset in minutes at 1000°C, T commonly reached in and directly adjacent to impact melt domains, whereas complete resetting of zircon (U-Th)/He at <300°C, which might be encountered near the crater margins or persist in post-impact hydrothermal systems, may take >103-4 years. However, there is a critical need to test the reliability of (U-Th)/He impact dating in shock deformed zircon, and to quantify helium diffusion kinetics in well-characterized grains with a broad spectrum of shock-induced defect substructures. For this purpose, we investigated samples from two impact structures, the 66 Ma Chicxulub multi-ring basin and the 15 Ma Ries complex crater, to compare zircon diffusion kinetics from impact structures with varying parameters, including size, age, and hydrothermal system longevity. Shock microstructures were characterized by backscattered-electron (BSE) imaging prior to determination of diffusion step-heating fractional release experiments using light-bulb furnace with prograde and retrograde incrementally 10°C steps from 300°C to 600°C. We find that zircon with low-level shock microstructures exhibit no significant deviation from helium diffusion kinetics of undamaged zircon. In contrast, zircon grains with planar deformation features and granular textures classified by SEM are characterized by a dramatic decrease in helium retentivity, similar to radiation damage, due to the reduction in the effective domain size and the introduction of fast diffusion pathways. This likely renders shocked grains more susceptible to impact-induced hydrothermal resetting. Hence, characterization of impact microstructure is critical for determining accurate impact ages, but also offers the opportunity to determine the magnitude and duration of post-impact hydrothermal circulation.

Catherine Ross↗

DOE OSTI2024

Effects of residual oxygen on superconducting niobium films

The integration of niobium (Nb) into emerging superconducting circuits can enhance their performance and function. However, growth of high purity Nb can be challenging due to its high reactivity with oxygen. Here, in this study, we examine the role of residual oxygen inside the growth chamber in transforming the structural, chemical, and superconducting properties of Nb films. We demonstrate that an increase in unintentional oxygen impurities lowers the superconducting critical temperature of Nb. This evolution coincides with the reduction of Nb crystal domains, which are separated by highly disordered oxygen-rich regions. Moreover, chemical analysis reveals the formation of niobium monoxide within the film during growth. These findings provide a comprehensive picture of how residual oxygen in the growth chamber can affect the properties of the Nb films. This study contributes to the materials science and engineering knowledge of superconducting Nb growth.

36 MATERIALS SCIENCE↗

NASA NTRS1981

Practical gust load alleviation and flutter suppression control laws based on a LQG methodology

A modified linear quadratic Gaussian (LQG) synthesis procedure has been used to design low-order robust multiloop controllers for a flexible airplane. The introduction of properly constructed fictitious Gauss-Markov processes in the control loops allowed meeting classical frequency-domain stability criteria using the direct synthesis procedures of modern time-domain control theory. Model reduction was used to simplify the control laws to the point where they could be easily implemented on onboard flight computers. These control laws provided excellent gust load and flutter mode control with good stability margins and compared very favorably to other control laws synthesized by the classical root-locus technique.

Gangsaas, D.↗

NASA NTRS1993

A zonal CFD method for three-dimensional wing simulations

The primary objective of this work is to demonstrate the feasibility of a 3D potential/viscous flow coupling procedure for reducing computational effort while maintaining solution accuracy. The closed-loop, overlapped, velocity-coupling concept has been developed in a new code, ZAP3D, that couples a potential flow panel code with a Navier-Stokes method. The current ZAP3D calculation for an aspect ratio 5 wing with an outer domain radius of about 1.2 chords represents a speed-up in CPU time over the ARC3D large domain calculation by about a factor of 2.5. This improvement is achieved for less than a 0.5 percent deviation in C(L), 10 counts change in C(D), and 0.0015 variation in C(My). Additional reductions in the required computational domain for ZAP3D are expected as the method is further developed and refined.

Summa, J. M.↗

NASA NTRS1982

The role of modern control theory in the design of controls for aircraft turbine engines

The development, applications, and current research in modern control theory (MCT) are reviewed, noting the importance for fuel-efficient operation of turbines with variable inlet guide vanes, compressor stators, and exhaust nozzle area. The evolution of multivariable propulsion control design is examined, noting a basis in a matrix formulation of the differential equations defining the process, leading to state space formulations. Reports and papers which appeared from 1970-1982 which dealt with problems in MCT applications to turbine engine control design are outlined, including works on linear quadratic regulator methods, frequency domain methods, identification, estimation, and model reduction, detection, isolation, and accommodation, and state space control, adaptive control, and optimization approaches. Finally, NASA programs in frequency domain design, sensor failure detection, computer-aided control design, and plant modeling are explored

Zeller, J.↗

DOE OSTI2024

Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization

ABSTRACT Urban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.

Talebpour, Mahdad↗