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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Welding Defect Classification from Simulated Ultrasonic Signals

Nondestructive testing is widely used to detect and to size up discontinuities embedded in a material. Among the several ultrasonic techniques, time of flight diffraction (TOFD) combines high speed inspection, high sizing reliability and low rate of incorrect results. However, the classification of defects through ultrasound signals acquired by the TOFD technique depends heavily on the knowledge and experience of the operator and thus, this classification is still frequently questioned. Besides, this task requires long processing time due to the large amount of data to be analyzed. Nevertheless, computational tools for pattern recognition can be employed to analyze a high amount of data with large efficiency. In the present work, simulation of ultrasound propagation in two-dimensional media containing, each one, different kinds of modeled discontinuities which mimic defects in welded joints were performed. Clustering (k-means) and classification (principal component analysis and k-nearest neighbors) algorithms were employed to associate each simulated ultrasound signal with its corresponding modeled defects. The results for each method were analyzed, discussed and compared. The results are very promising.

42 ENGINEERING↗
DOE OSTI2021

Enzymes and Models. In: XAFS Techniques for Catalysts, Nanomaterials, and Surfaces

Many important redox-active metalloenzymes consist of 3d transition metals in their active sites. They catalyze multi-electron reactions in aqueous solution, under ambient temperature and pressure. To understand the functionality of the catalytic sites of these enzymes, X-ray spectroscopy methods provide important information of the electronic structure of the metal of interest and its local structural information, as well as their changes during the catalysis. Studying model compounds, that mimic enzyme catalytic site structures or their functional mimics, is as critical as studying enzymes themselves, in order to interpret X-ray spectroscopic data. In this chapter, various X-ray spectroscopic methods that are useful for structural and electronic structural studies of enzymes and model compounds are described.

Yachandra, VK↗
NASA NTRS1994

Metabolic Cages for a Space Flight Model in the Rat

A variety of space flight models are available to mimic the physiologic changes seen in the rat during weightlessness. The model reported by Wronski and Morey-Holton has been widely used by many investigators, in musculoskeletal physiologic studies especially, resulting in accumulation of an extensive database that enables scientists to mimic space flight effects in the 1-g environment of Earth. However, information on nutrition or gastrointestinal and renal function in this space flight model is limited by the difficulty in acquiring uncontaminated metabolic specimens for analysis. In the Holton system, a traction tape harness is applied to the tail, and the rat's hindquarters are elevated by attaching the harness to a pulley system. Weight-bearing hind limbs are unloaded, and there is a headward fluid shift. The tail-suspended rats are able to move freely about their cages on their forelimbs and tolerate this procedure with minimal signs of stress. The cage used in Holton's model is basically a clear acrylic box set on a plastic grid floor with the pulley and tail harness system attached to the open top of the cage. Food is available from a square food cup recessed into a corner of the floor. In this system, urine, feces, and spilled food fall through the grid floor onto absorbent paper beneath the cage and cannot be separated and recovered quantitatively for analysis in metabolic balance studies. Commercially available metabolic cages are generally cylindrical and have been used with a centrally located suspension apparatus in other space flight models. The large living area, three times as large as most metabolic cages, and the free range of motion unique to Holton's model, essential for musculoskeletal investigations, were sacrificed. Holton's cages can accommodate animals ranging in weight from 70 to 600 g. Although an alternative construction of Holton's cage has been reported, it does not permit collection of separate urine and fecal samples. We describe the modifications to Holton's food delivery system, cage base, and the addition of a separator system for the collection of urine and fecal samples for metabolic and nutrition studies in the tail suspension model.

Harper, Jennifer S.↗
DOE OSTI2022

Development of lean, efficient, and fast physics-framed deep-learning-based proxy models for subsurface carbon storage

In this work, we present deep-learning-based surrogate models for CCUS developed with four different algorithms and a physics-framed two-phase flow problem involving displacement of water by CO 2 . The deep-learning models were trained using 3D datasets describing the pressure plume, CO 2 saturation plume, and water extraction rate generated by numerical simulation. The hyperparameters defining the architecture of the neural networks were optimized to determine the slimmest network size and training parameters that give the most efficient performance at the least training cost. To develop a robust model that closely mimics the governing physical laws, the discretized form of the two-phase fluid transport equation was used to formulate the supervised deep-learning task. The algorithms investigated in this study predicted the data to above 95% accuracy, with the multi-layer perceptron model demonstrating the best performance by balancing training speed, prediction time, and prediction accuracy with lean network capacity. Furthermore, the surrogate models simultaneously predict reservoir pressure and CO 2 saturation in every grid block, including the surface well extraction rate and bottomhole pressure, at all simulation times for a given static model realization in just a few seconds on a standard desktop computer. A key outcome of this study is that limits can be placed on network design parameters to avoid over designing neural networks, with associated efficiencies in training and prediction times. This is very useful because large volumes of data may be generated in CCUS projects and over-design of neural network architectures imposes penalties that are antithetical to the goal of near-real time forecasting.

58 GEOSCIENCES↗
DOE OSTI2015

From photoelectron detachment spectra of BrHBr{sup −}, BrDBr{sup −} and IHI{sup −}, IDI{sup −} to vibrational bonding of BrMuBr and IMuI

Photoelectron detachment XLX{sup −}(00{sup 0}0) + hν → XLX(vib) + e{sup −} + KER (X = Br or I, L = H or D) at sufficiently low temperatures photoionizes linear dihalogen anions XLX{sup −} in the vibrational ground state (v{sub 1}v{sub 2}{sup l}v{sub 3} = 00{sup 0}0) and prepares the neutral radicals XLX(vib) in vibrational states (vib). At the same time, part of the photon energy (hν) is converted into kinetic energy release (KER) of the electron [R. B. Metz, S. E. Bradforth, and D. M. Neumark, Adv. Chem. Phys. 81, 1 (1992)]. The process may be described approximately in terms of a Franck-Condon type transfer of the vibrational wavefunction representing XLX{sup −}(00{sup 0}0) from the domain close to the minimum of its potential energy surface (PES) to the domain close to the linear transition state of the PES of the neutral XLX. As a consequence, prominent peaks of the photoelectron detachment spectra (pds) correlate with the vibrational energies E{sub XLX,vib} of states XLX(vib) which are centered at linear transition state. The corresponding vibrational quantum numbers may be labeled vib = (v{sub 1}v{sub 2}{sup l}v{sub 3}) = (00{sup 0}v{sub 3}). Accordingly, the related most prominent peaks in the pds are labeled v{sub 3}. We construct a model PES which mimics the “true” PES in the domain of transition state such that it supports vibrational states with energies E{sub XLX,pds,00{sup 0}v{sub 3}} close to the peaks of the pds labeled v{sub 3} = 0, 2, and 4. Subsequently, the same model PES is also used to calculate approximate values of the energies E{sub XMuX,00{sup 0}0} of the isotopomers XMuX(00{sup 0}0). For the heavy isotopomers XHX and XDX, it turns out that all energies E{sub XLX,00{sup 0}v{sub 3}} are above the threshold for dissociation, which means that all heavy XLX(00{sup 0}v{sub 3}) with wavefunctions centered at the transition state are unstable resonances with finite lifetimes. Turning the table, bound states of the heavy XLX are van der Waals (vdW) bonded. In contrast, the energies E{sub XMuX,00{sup 0}0} of the light isotopomers XMuX(00{sup 0}0) are below the threshold for dissociation, with wavefunctions centered at the transition state. This means that XMuX(00{sup 0}0) are vibrationally bonded. This implies a fundamental change of the nature of chemical bonding, from vdW bonding of the heavy XHX, XDX to vibrational bonding of XMuX. For BrMuBr, the present results derived from experimental pds of BrHBr{sup −} and BrDBr{sup −} confirm the recent discovery of vibrational bonding based on quantum chemical ab initio calculations [D. G. Fleming, J. Manz, K. Sato, and T. Takayanagi, Angew. Chem., Int. Ed. 53, 13706 (2014)]. The extension from BrLBr to ILI means the discovery of a new example of vibrational bonding. These empirical results for the vibrational bonding of IMuI, derived from the photoelectron spectra of IHI{sup −} and IDI{sup −}, are supported by ab initio simulations of the spectra and of the wavefunction representing vibrational bonding of IMuI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Rationally designed carbohydrate-occluded epitopes elicit HIV-1 Env-specific antibodies

An array of carbohydrates masks the HIV-1 surface protein Env, contributing to the evasion of humoral immunity. In most HIV-1 isolates ‘glycan holes’ occur due to natural sequence variation, potentially revealing the underlying protein surface to the immune system. Here we computationally design epitopes that mimic such surface features (carbohydrate-occluded neutralization epitopes or CONE) of Env through ‘epitope transplantation’, in which the target region is presented on a carrier protein scaffold with preserved structural properties. Scaffolds displaying the four CONEs are examined for structure and immunogenicity. Crystal structures of two designed proteins reflect the computational models and accurately mimic the native conformations of CONEs. The sera from rabbits immunized with several CONE immunogens display Env binding activity. Our method determines essential structural elements for targets of protective antibodies. The ability to design immunogens with high mimicry to viral proteins also makes possible the exploration of new templates for vaccine development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A review of NEST models for liquid xenon and an exhaustive comparison with other approaches

This paper discusses the microphysical simulation of interactions in liquid xenon, the active detector medium in many leading rare-event searches for new physics, and describes experimental observables useful for understanding detector performance. The scintillation and ionization yield distributions for signal and background are presented using the Noble Element Simulation Technique (NEST), a toolkit based on experimental data and simple empirical formulas, which mimic previous microphysics modeling but are guided by data. The NEST models for light and charge production as a function of the particle type, energy, and electric field are reviewed, along with models for energy resolution and final pulse areas. NEST is compared with other models or sets of models and validated against real data, with several specific examples drawn from XENON, ZEPLIN, LUX, LZ, PandaX, and table-top experiments used for calibrations.

WIMPs↗
NASA NTRS1979

An angular momentum approximation for molecular collisions in the presence of intense laser radiation

An approximation to a previously presented rigorous description of molecular (atom-atom) collisions occurring in the presence of intense radiation is investigated. This rigorous description explicitly considers the angular momentum transferred between the molecule and the radiation field in the absorption or emission of a photon, but involves a complicated system of close-coupled equations which must be solved independently for each projection M of the initial, total molecular angular momentum. (This is a direct consequence of the lack of rotational invariance in the molecule-field problem). These equations are solved for a model system which mimics the collision of a halogen with a rare gas atom. Empirical observations made in the course of performing these calculations lead to the development of an approximation which avoids the repeated calculations for each initial M. This orientational average approximation greatly reduces the effort required to describe the system, and for the model calculation, yields accurate results for field intensities as high as 10 GW/sq cm.

Devries, P. L.↗
DOE OSTI2022

Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow

We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Equation of State and Energy Loss of Hot and Dense Quark-Gluon matter from Holographic Black Holes

By using gravity/gauge correspondence, we construct a holographic model, constrained to mimic the lattice QCD equation of state at zero density, to investigate the temperature and baryon chemical potential dependence of the equation of state. We also obtained the energy loss of light and heavy partons within the hot and dense plasma represented by the heavy quark drag force, Langevin diffusion coefficients and jet quenching parameter at the critical point and across the first-order transition line predicted by the model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1990

Basic Mechanisms of Solar Variability

In order to simulate the behavior of a changing Sun in a realistic way, researchers have used a perturbation analysis (the results are summarized in Endal et al. 1985). In this approach, they use a standard solar model and then vary several of the model parameters to mimic the sudden or gradual change of some physical property within the Sun. The evolution following the perturbation is followed in a physically self-consistent way, that is, hydrostatic and thermal processes occur in their normal timescales. This treatment has allowed us to determine the sensitivity of the various global parameters to physical processes affecting the solar interior, and it has guided us in defining the least complex global solar model which can address the question of climatically significant variability. Not surprisingly, magnetic fields play the crucial role. The current status of the model, what researchers have already learned from it, and the future prospects are discussed.

Sofia, Sabatino↗
NASA NTRSDate not supplied

Comparison of Multivariate Time Series Prediction Techniques for Emulating Noah-LSM Soil Moisture Outputs

Land surface models are crucial tools for many earth science applications including numerical weather prediction, water resource and crop monitoring, and climatological analysis. Given a set of atmospheric forcings, seasonal data, and static parameters, models like Noah-LSM solve for land surface quantities including skin temperature, sensible heat flux, and soil moisture. While these calculations are theoretically robust, they are often computationally expensive. Since artificial neural networks (ANNs) are universal function approximators, they can learn to emulate the output of a deterministic numerical model given a time series of input forcings, with the learned ANN having substantially shorter execution time. The ANN could efficiently parameterize other models, generate ensembles, and provide first-guess inputs for retrievals. As such, with the goal of developing a model that efficiently mimics the output of Noah-LSM given NLDAS2 forcings on a region covering much of the central US, we examine and compare several neural network architectures for the multi-horizon multivariate time series forecasting problem. Recent literature includes a diverse set of approaches including autoregressive architectures like LSTM and GRU, parametric and non-parametric statistical predictors (ForecastNet and MQRNN), self-attention (LSTM-attention-LSTM), and temporal convovlution (DeepTCN). We implement several of these models for the Noah-LSM prediction task, highlighting the features and challenges for each and providing practical insight on the training process.

Mitchell Dodson↗
DOE OSTI2013

Three-dimensional culture of sebaceous gland cells revealing the role of prostaglandin E{sub 2}-induced activation of canonical Wnt signaling

Highlights: •Three-dimensional culture generates “semi-vivo” sebaceous glands. •Xenograft model failed to mimic the biology of sebaceous glands in vivo. •Proinflammatory cytokine PGE{sub 2} enhances Wnt signal activity in the organoids. •PGE{sub 2} influences on the mitochondrial and lipid metabolism in the organoids. •Considering 3R agenda, “semi-vivo” sebaceous glands are useful for research. -- Abstract: Background: Prostaglandin E{sub 2} (PGE{sub 2}) is a proinflammatory mediator and activates the canonical Wnt–β-catenin signaling pathway in hematopoietic stem cells. The SZ95 cell line was established from human sebaceous gland cells and is studied as a model system for these cells. Given that 2D culture of SZ95 cells does not recapitulate the organization of sebaceous glands in situ, we developed a 3D culture system for these cells and examined the effects of PGE{sub 2} on cell morphology and function. Results: SZ95 cells maintained in 3D culture formed organoids that mimicked the organization of sebaceous glands in situ, including the establishment of a basement membrane. Organoids exposed to PGE{sub 2} were larger and adopted a more complex organization compared with control organoids. PGE{sub 2} activated the canonical Wnt signaling pathway as well as increased cell viability and proliferation, mitochondrial metabolism, and lipid synthesis in the organoids. Conclusions: Culture of SZ95 cells in 3D culture system recapitulates the structure and susceptibility to PGE{sub 2} of sebaceous glands in situ and should prove useful for studies of the response of these glands to inflammation and other environmental stressors. Our results also implicate PGE{sub 2}-induced activation of canonical Wnt signaling pathway in regulation of the morphology,proliferation, and function of “semi-vivo” sebaceous glands.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

HIGH-LOW FIDELITY THERMAL HYDRAULIC COUPLING USING AI/MACHINE LEARNING ALGORITHMS

The primary goal of the US Department of Energy (DOE) office of Nuclear Energy Integrated Energy Systems (IES) program is to develop the tools and framework for coupling multi-scale and multi-physical thermal and electrical energy usage and storage systems. High- and low-fidelity (high–low) coupling is a key feature of multi-scale, multi-component systems and has been an important focus of research in the nuclear energy community for the past two decades. An essential feature of demonstrating the capability to couple high-fidelity and low-fidelity systems for real-time applications are surrogate/reduced order models (ROM). For the purposes of this study, surrogate models are essentially Blackbox models, typically developed using supervised Machine learning (ML) algorithms. The surrogate models can be used to mimic the response of high-fidelity models to represent large historical datasets and coupled with more general low-fidelity system models distributed as Functional Mock-up Interface (FMI) or Functional Mock-up Units (FMU) modules. The example is demonstrated with Spallation Neutron Source (SNS) First Target Station flow loop data. The flow loop is a liquid mercury loop with a pump, piping, heat exchange, and internal heat generation in the target window. This work elucidates some of the potential benefits and future needs of developing tools for high–low system coupling of energy systems.

Williams, Wesley↗
DOE OSTI2018

Python Performance Prediction Package for the PGET instrument: User Guide

The Performance Prediction Package (PPP) is a software suite for generating radiation transport results, or leveraging existing transport results, to produce synthetic emission tomography measurements of spent nuclear fuel assemblies. Such synthetic data can be used to mimic specific measurements, and to systematically investigate detection capabilities. Possible uses for the tool include: • Instrument design • Predictive evaluation of observables prior to an inspection visit • Post-measurement assessment of measured data • Evaluation of unusual cases – closed containers with anomalous objects • Sensitivity studies for planning inspections • Sensitivity studies for diversion scenarios • Evaluation of analysis methods A scenario is defined with an assembly type, burnup, and cooling time; as well as assembly rotation angle and position relative to the PGET instrument. Pin-to-pin activity variations or a burnup gradient may be present, but in an inspection scenario these are unlikely to be specified. The measurement will specify a measurement time and a particular detector for detector response, and an optional empirical correction can further adjust the model to better mimic the measurement. The goal is to detect missing pins, or burnup anomalies consistent with a pin substituted with a fresh pin after partial burnup.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1992

Measurement of pressure ridges in SAR images of sea ice - Preliminary results on scattering theory

Sea ice ridges and keels (hummocks and bummocks) are important in sea ice research for both scientific and practical reasons. A long-term objective is to make quantitative measurements of sea ice ridges using synthetic aperture radar (SAR) images. The preliminary results of a scattering model for sea ice ridge are reported. The approach is through the ridge height variance spectrum Psi(K), where K is the spatial wavenumber, and the two-scale scattering model. The height spectrum model is constructed to mimic height statistics observed with an airborne optical laser. The spectrum model is used to drive a two-scale scattering model. Model results for ridges observed at C- and X-band yield normalized radar cross sections that are 10 to 15 dB larger than the observed cross sections of multiyear ice over the range of angles of incidence from 10 to 70 deg.

Vesecky, J. F.↗
DOE OSTI2022

Selenite and Selenate Sequestration during Coprecipitation with Barite: Insights from Mineralization Processes of Adsorption, Nucleation, and Growth

Coprecipitation of selenium oxyanions with barite is a facile way to sequester Se in the environments. However, the chemical composition of Se-barite coprecipitates usually deviates from that predicted from thermodynamic calculations. This discrepancy was resolved by considering variations in nucleation and growth rates controlled by ion–mineral interactions, solubility, and interfacial energy. For homogeneous precipitation, ~10% of sulfate, higher than thermodynamic predictions (<0.3%), was substituted by Se(IV) or Se(VI) oxyanion, which was attributed to adsorption-induced entrapment during crystal growth. For heterogeneous precipitation, thiol- and carboxylic-based organic films, utilized as model interfaces to mimic the natural organic-abundant environments, further enhanced the sequestration of Se(VI) oxyanions (up to 41–92%) with barite. Such enhancement was kinetically driven by increased nucleation rates of selenate-rich barite having a lower interfacial energy than pure barite. In contrast, only small amounts of Se(IV) oxyanions (~1%) were detected in heterogeneous coprecipitates mainly due to a lower saturation index of BaSeO 3 and deprotonation degree of Se(IV) oxyanion at pH 5.6. Finally, these roles of nanoscale mineralization mechanisms observed during composition selection of Se-barite could mark important steps toward the remediation of contaminants through coprecipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Infrared detection of (H 2 O) 20 isomers of exceptional stability: A drop-like and a face-sharing pentagonal prism cluster

Water clusters containing fully coordinated water molecules are model systems that mimic the local environment of the condensed phase. Present knowledge about the water cluster size regime in which the transition from the allsurface to the fully solvated water molecules occurs is mainly based on theoretical predictions in lieu of the absence of precisely size resolved experimental measurements. Here, we report size and isomer selective infrared (IR) spectra of (H 2 O) 20 clusters tagged with a sodium atom by employing IR excitation modulated photoionization spectroscopy. The observed absorption patterns in the OH stretching ”fingerprint” region are consistent with the theoretically predicted spectra of two structurally distinct isomers: A drop-like cluster with a fully coordinated (interior) water and an edge-sharing pentagonal prism cluster in which all atoms are on the surface. The observed isomers show exceptional stability and are predicted to be nearly isoenergetic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗