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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Customizable adaptive regularization techniques for B-spline modeling

B-spline models are a powerful way to represent scientific data sets with a functional approximation. However, these models can suffer from spurious oscillations when the data to be approximated are not uniformly distributed. Model regularization (i.e., smoothing) has traditionally been used to minimize these oscillations; unfortunately, it is sometimes impossible to sufficiently remove unwanted artifacts without smoothing away key features of the data set. In this article, we present a method of model regularization that preserves significant features of a data set while minimizing artificial oscillations. Our method varies the strength of a smoothing parameter throughout the domain automatically, removing artifacts in poorly-constrained regions while leaving other regions unchanged. Further, the proposed method selectively incorporates regularization terms based on first and second derivatives to maintain model accuracy while minimizing numerical artifacts. The behavior of our method is validated on a collection of two- and three-dimensional data sets produced by scientific simulations. In addition, a key tuning parameter is highlighted and the effects of this parameter are presented in detail. This paper is an extension of our previous conference paper at the 2022 International Conference on Computational Science (ICCS) (Lenz et al., 2022).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Control of donor-like effect in V2VI3 polycrystalline thermoelectric materials

Highlights: • Thermal control of donor-like effect for V{sub 2}VI{sub 3} polycrystalline materials is proposed. • Low-temperature sintering or hot deforming facilitates the donor-like effect. • Recovery role by high-temperature sintering/deforming enhances the Seebeck coefficient. • Temperature should be strictly selected for each V{sub 2}VI{sub 3} polycrystalline material. - Abstract: Intrinsic point defect plays a core role in improving thermoelectric performance of V{sub 2}VI{sub 3} polycrystalline materials. However, the control of intrinsic point defect is challenging during powder refinement due to the donor-like effect. This paper shows a systematic approach to thermal control the donor-like effect via engineering spark plasma sintering and hot deformation temperature. Bi{sub 2}Te{sub 2.85}Se{sub 0.15} polycrystalline alloy with high electron concentration was chosen as example to validate the method. The low Seebeck coefficient of n-type Bi{sub 2}Te{sub 2.85}Se{sub 0.15} polycrystalline, arising from strong donor-like effect after powder refinement, was enhanced by recovery role induced reduction in electron concentration through proper tuning sintering or deforming temperature. Repetitive hot deformation was applied to further improve the Seebeck coefficient via the recovery role and a maximum zT of 1.0 is obtained at 410 K. The present results give insights into developing higher performance V{sub 2}VI{sub 3} polycrystalline materials through thermal control the donor-like effect.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

At-power subcritical multiplication in the Advanced Test Reactor during nuclear requalification testing

Power division information during nuclear requalification of the Advanced Test Reactor (ATR) is of considerable interest as an importance function for observed changes to core reactivity. The degree to which a given physical subdivision of a critical reactor acts as a neutron source for other lobes is not analytically characterized for general application. When ATR operates at power, individual power-producing lobes rely on each other as neutron sources in order to maintain constant power, which in general requires either exactly critical multiplication within a reactor or an external neutron source. Here, this work shows that fuel element and lobe powers in ATR can be related with subcritical multiplication theory. Subcritical multiplication factors are computed with a physically validated analytical method based on actual at-power operation, quantifying for each lobe its dependence on other lobes as an external neutron source. This explanation is significant for ATR due to the desire to irradiate a large variety of experiments simultaneously, each having its impact on the core neutron population. For any physical subdivision of any other critical reactor, it is likewise true that the subdivision undergoes only subcritical multiplication.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2022

PCP consensus protein/peptide alphavirus antigens stimulate broad spectrum neutralizing antibodies

Vaccines based on proteins and peptides may be safer and if calculated based on many sequences, more broad-spectrum than those designed based on single strains. Physicochemical Property Consensus (PCP con ) alphavirus (AV) antigens from the B-domain of the E2 envelope protein were designed, synthesized recombinantly and shown to be immunogenic (i.e. sera after inoculation detected the antigen in dotspots and ELISA). Antibodies in sera after inoculation with B-region antigens based on individual AV species (eastern or Venezuelan equine encephalitis (EEEV con , VEEV con ), or chikungunya (CHIKV con ) bound only their cognate protein, while those designed against multiple species (Mosaik con and EVC con ) recognized all three serotype specific antigens. The VEEV con and EEEV con sera only showed antiviral activity against their related strains (in plaque reduction neutralization assays (PRNT 50/80 ). Peptides designed to surface exposed areas of the E2-A-domain of CHIKV con were added to CHIKV con inocula to provide anti-CHIKV antibodies. EVC con , based on three different alphavirus species, combined with E2-A-domain peptides from AllAV con , a PCPcon of 24 diverse AV, generated broad spectrum, antiviral antibodies against VEEV, EEEV and CHIKV, AV with less than 35% amino acid identity to each other (>65% diversity). This is a promising start to a molecularly defined vaccine against all AV. A further study with these antigens can illuminate what areas are most important for a robust immune response, resistant to mutations in rapidly evolving viruses. The validated computational methods can also be used to design broad spectrum antigens against many other pathogen families.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Direct measurement and calculation of rubber bulk modulus by piston-cylinder method using conventional mechanical testing equipment

This article describes a method to directly measure the bulk modulus of rubber using a piston-cylinder type apparatus. The function of the testing apparatus is to reliably transfer load to the water inside the vessel and allow for the accurate and continuous measurement of volumetric displacement as the contents are compressed. During the test, load is applied to a piston-cylinder containing the rubber test sample and water using a conventional mechanical testing load frame. Load and the travel of the piston are recorded by a load cell and extensometer, respectfully. A brass or stainless steel plug of the same dimensions as the test sample is tested as a control sample to isolate the compliance of the system, including the compressibility of water and compliance of the piston-cylinder. The results from this control test are used to disincorporate the compliance of the system from the sample test results. Load-linear displacement data are mathematically converted to pressure-volumetric displacement data, from which bulk modulus is calculated. The test apparatus and method are validated using the known bulk modulus of water. Finally, the bulk modulus for two similar rubbers is evaluated. The validity of the results and limitations of the device are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling stratified flames with and without shear using multiple mapping conditioning

A stochastic sparse particle approach is coupled with an artificial thickening flame (ATF) model for large eddy simulations (LES) to predict a series of turbulent premixed-stratified flames with and without shear and stratification. The thickened reaction progress variable serves as reference variable for the multiple mapping conditioning (MMC) mixing model which emulates turbulent mixing of the stochastic particles. The key feature of MMC is to enforce localness in this reference space when particle pairs are mixed and prevents unphysical mixing of burnt and unburnt fluid across the flame front. We apply MMC-ATF to three flames of a series of turbulent stratified flames and validate the method by comparison with experimental data. The new measurements feature increased accuracy in comparison to previously published data of the same flames due to a better signal-to-noise ratio and a setup which is less prone to beam steering. All flame locations are well predicted by the LES-ATF approach and an analysis of the MMC particle statistics demonstrates that MMC preserves the flamelet-like behaviour in regions where the experiments show low scatter around the flamelet solution. Predicted (local) deviations from the flamelet-solution are comparable to deviations observed in the measurements and variations in the flame structure due to differences in stratification and shear are reasonably well captured by the method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Digital force prediction for milling

This paper presents a fully digital, integrated approach for milling force prediction with arbitrary end mill-work material combinations. The approach includes: 1) structured light scanning to identify the end mill’s cutting edge macro-geometry along the tool axis; 2) structured light scanning to measure the cutting edge cross-sectional rake and relief profiles; 3) finite element analysis of orthogonal cutting to determine the force model coefficients that relate the force to chip area using the work material’s constitutive model and tool’s rake and relief profiles; and 4) time domain simulation with inputs that include the measured cutting edge macro-geometry, finite element-based force model, and measured structural dynamics. Milling force predictions are compared to in-process measurements to validate the method.

42 ENGINEERING↗
DOE OSTI2025

Controlling matric potential in microfluidics to examine microbial dynamics in unsaturated porous media

The use of microfluidics for the study of soil microbial ecology is an emerging field. Most microfluidic studies of biological systems, however, have been performed under fully saturated conditions that are not representative of natural soil. Therefore, while microfluidics offer many unique capabilities that other methodologies cannot, they are not currently suited to address the effects of matric potential, an important variable defining the microbial moisture niche. Here, a methodology is presented that allows the user to control the aqueous conditions within microfluidic networks by manipulating matric potential using a hanging water column. The method relies on hydrophilic surface treatment of the microfluidic device using polyvinyl alcohol (PVA) and incorporating a bed of small pores at the network boundaries, which serve as a porous ceramic plate analogue (PPA). The method was validated on a simple capillary bundle and then on a more complex pore network. A water retention curve, exhibiting hysteresis, was generated for the pore network over a narrow matric potential range of 0 to – 5 kPa. Both the drainage and wetting curves were reproducible, as were the spatial configuration and the number of fragmented moisture niches in the pore network, particularly on the drainage curve. In contrast, the wetting curve exhibited greater variability in spatial configuration due to the “ink bottle effect,” where capillarity was interrupted by wider pore bodies. Ultimately, the methodology provides realistic pore-scale moisture conditions that can be easily manipulated and maintained, enabling new opportunities to explore soil biophysics and microbial biogeography in unsaturated porous media. As a brief example, images showing the localization of fluorescently tagged Pantoea sp. YR343 at −4.3 kPa are presented, highlighting bacterial distributions in water films and air-water interfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A new method for quantifying 64 Cu in nuclear debris samples

Quantifying 64 Cu in post-detonation nuclear debris samples can provide important diagnostic information regarding the structural materials used within a nuclear device. However, this task is challenging due to the weak gamma emissions associated with the decay of 64 Cu, its short half-life (12.701 h), and the presence of interfering fission product radioisotopes. Large quantities of debris sample are generally needed to accurately quantify 64 Cu, which can be problematic in sample-limited scenarios where other radiometric analyses are required. Herein, we present a new method for the separation of 64 Cu from solutions of mixed fission products and demonstrate the quantification of its activity through use of gas-flow proportional beta counting. Here, the new method was validated through a series of rigorous tests and was shown to improve the detection limit of 64 Cu by over two orders of magnitude, from 2.5 × 10 6 to 1.3 × 10 4 atoms/sample for 100 min measurements.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement

The localized failures of gears introduce cyclic-transient impulses in the measured gearbox vibration signals. These impulses are usually identified from the sidebands around gear-mesh harmonics through the spectral analysis of cyclo-stationary signals. However, in practice, several high-powered applications of gearboxes like wind turbines are intrinsically characterized by nonstationary processes that blur the measured vibration spectra of a gearbox and deteriorate the efficacy of spectral diagnostic methods. Although order-tracking techniques have been proposed to improve the performance of spectral diagnosis for nonstationary signals measured in such applications, the required hardware for the measurement of rotational speed of these machines is often unavailable in industrial settings. Moreover, existing tacho-less order-tracking approaches are usually limited by the high time-frequency resolution requirement, which is a prerequisite for the precise estimation of the instantaneous frequency. To address such issues, a novel fault-signature enhancement algorithm is proposed that can alleviate the spectral smearing without the need of rotational speed measurement. This proposed tacho-less diagnostic technique resamples the measured acceleration signal of the gearbox based on the optimal warping path evaluated from the fast dynamic time-warping algorithm, which aligns a filtered shaft rotational harmonic signal with respect to a reference signal assuming a constant shaft rotational speed estimated from the approximation of operational speed. The effectiveness of this method is validated using both simulated signals from a fixed-axis gear pair under nonstationary conditions and experimental measurements from a 750-kW planetary wind turbine gearbox on a dynamometer test rig. Lastly, the results demonstrate that the proposed algorithm can identify fault information from typical gearbox vibration measurements carried out in a resource-constrained industrial environment.

17 WIND ENERGY↗
DOE OSTI2017

Design and simulation study of ultra-fast beam bunches split for three orthogonal planes high-energy electron dynamic radiography

Here a compact three orthogonal planes high-energy electron radiography system was proposed. One of the critical technologies, the ultra-fast beam bunches split from the bunch train are studied. The separated bunches could be transported to the three orthogonal planes of the target for dynamic radiography diagnostics. The key elements of the ultra-fast bunches split system are transverse deflecting cavity (TDC) and the twin septum magnet (TSM). The principle of TDC and TSM are briefly introduced. An example of the beam bunches split system for test experiment (40 MeV electron beam) with TDC and TSM is designed and studied by particle-tracking simulation and it confirms this method is valid and feasible. Especially with TSM, a compact three orthogonal planes radiography system can be realized. The evolution of the beam parameters along the beam line from simulation are investigated. The detailed design of the beam split system and beam dynamics simulation study are presented in this paper.

Zhao, Q. T.↗
DOE OSTI2018

Quantitative SIMS Imaging of Agar-Based Microbial Communities

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. Here, we show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling Short-Range Order in Disordered Rocksalt Cathodes by Pair Distribution Function Analysis

Pair distribution function (PDF) analysis is a powerful technique for the characterization of short-range order (SRO) in disordered materials. Accurate interpretation of experimental PDF data is critically reliant on the development of structural models that can account for local variations in site occupancies and bond lengths. To this end, we outline an approach to model SRO using first-principles calculations based on the cluster-expansion formalism. These methods are validated on neutron scattering data from two disordered rocksalt oxyfluorides, Li 1.3 Mn 0.4 Ti 0.3 O 1.7 F 0.3 and Li 1.3 Mn 0.4 Nb 0.2 Ti 0.1 O 1.7 F 0.3 . For each composition, we demonstrate that an average structure without any SRO fails to reproduce several key features in the experimental PDF. To pinpoint the origin of the suspected SRO in these materials, configurational and displacive effects were separately investigated using two disparate models. Special quasi-random structures were relaxed using density functional theory to account for local changes in bond lengths while maintaining a near-random ionic configuration. This leads to slightly improved accuracy but still misrepresents asymmetry in the first few peaks of the PDF. Monte Carlo simulations were performed to model configurational SRO on a fixed lattice, which by itself is shown to have a minimal influence on the PDF. Instead, we find that it is the bond length relaxations within environments created by SRO which controls the details of the PDF, thereby highlighting the subtle but important coupling between configurational and displacive SRO in disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Furthermore, fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Statistical White-Line Analysis in High-Throughput TXM-XANES for Chemical State Quantification

The transmission X-ray microscopy (TXM) based X-ray absorption near-edge structure (XANES) technique provides three-dimensional mapping of element-specific chemical states at nanometer-scale spatial resolution and micrometer-scale fields of view. However, compared to conventional volume-averaged XANES (VA-XANES) measurements, the inherently small voxel size in TXM-XANES leads to a lower signal-to-noise ratio, making full-spectrum analysis computationally demanding and less robust. Here, we present the structural and compositional conditions for a statistical white-line analysis framework under which chemical state information can be directly extracted from the white-line peak position in voxel spectra without the need for voxel-wise background subtraction or normalization, under well-defined structural and compositional conditions. The method is validated on layered oxide cathode materials, where low-order polynomial fitting accurately reproduces white-line features, and the extracted energy distributions correlate strongly with VA-XANES results. This statistical approach enables high-throughput, dose-efficient, and noise-robust chemical state quantification in TXM-XANES, offering broad applicability to functional materials requiring nanoscale oxidation-state mapping.

TXM↗
DOE OSTI2025

All-optical reconfiguration of single silicon-vacancy centers in diamond for non-volatile memories

Strain engineering is vital for tuning the optical and spin properties of solid-state color centers, enhancing spin coherence and compensating emission wavelength shift. Here, we develop an all-optical approach to directly modify the local strain of color centers at the nanoscale by migrating the nearby defect. High-power pulsed optical irradiation triggers defect migration, which subsequently leads to the redistribution of the local crystal lattice of the host material. This redistribution alters the strain experienced by nearby color centers. Using silicon-vacancy centers in diamond, we validate this method and demonstrate a ground state splitting enhancement of up to 1.8 THz. Unlike conventional methods, our approach requires no external fields or nanostructure modifications, enabling non-volatile strain control and optical memory functionality across wide temperature ranges. Its local, permanent nature offers a scalable path for enhancing spin coherence in large-scale quantum systems and has potential applications in photonic machine learning.

Nanoscale devices↗