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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 OSTI2026

Re-Evaluating Virtual Reality Manipulation Techniques for Precise Alignment of Complex 3D Objects

Prior research has developed a number of manipulation techniques that can achieve precise object placement in virtual reality, but studies of these techniques typically use simple objects. We conducted a study comparing two existing techniques, (AMP-IT and WISDOM), during alignment of objects with complex geometry to evaluate the potential influence of geometric complexity on performance, usability, workload and preference. Our findings indicate that participants had faster completion times and higher trial completion rates with AMP-IT on high-precision alignment tasks, contrary to earlier findings that used simple objects. Yet WISDOM is still preferred and considered more usable, despite increased workload and poorer performance, exposing participants' willingness to trade objective performance for comfort during use.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Phased array-based nonlinear wave mixing technique: Application to lack-of-fusion porosity characterization in additively manufactured metals

The objective of this research is to demonstrate the effectiveness of a phased array-based nonlinear wave mixing technique to characterize internal, localized microscale damage in an additively manufactured (AM) component. By using phased arrays for the generation of the incident waves, it is possible to produce a nonlinear wave mixing scanning technique without the need for immersion or changing coupling conditions. The phased arrays can be configured to generate incident waves in multiple directions that meet the resonance conditions required for nonlinear wave mixing at a variety of internal locations. This allows for the scanning of a specimen without the removal and re-coupling of the source transducers, leading to greater scanning speed and repeatability. To demonstrate the accuracy of this phased array wave mixing approach, measurements of acoustic nonlinearity in an AM component are first made with a bulk wave second harmonic generation through thickness measurement. Next, nonlinear wave mixing measurements are made with single element transducers to confirm the sensitivity of the proposed nonlinear wave mixing approach to lack-of-fusion porosity in AM metals. Finally, phased arrays are used to highlight the effectiveness of the proposed nonlinear wave mixing technique in these same AM components.

Acoustics↗
DOE OSTI2024

A Compound Data Poisoning Technique with Significant Adversarial Effects on Transformer-based Sentiment Classification Tasks

Transformer-based models have demonstrated much success in various natural language processing tasks. However, they are often vulnerable to adversarial attacks, such as data poisoning, which can intentionally fool the model into generating incorrect results. In this article, we present a novel, compound variant of a data poisoning attack on a transformer-based model that maximizes the poisoning effect while minimizing the scope of poisoning. Here we do so by combining the established data poisoning technique (label flipping) with a novel adversarial artifact selection and insertion technique aimed at minimizing detectability and the scope of the poisoning footprint. We find that by using a combination of these two techniques, we achieve a state-of-the-art attack success rate of approximately 90% while poisoning only 0.5% of the original training set, thus minimizing the scope and detectability of the poisoning action. These findings have the potential to advance the development of better data poisoning detection methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Characterization of Nanoscale Pores in Tight Gas Sandstones Using Complex Techniques: A Case Study of a Linxing Tight Gas Sandstone Reservoir

Pore structures with rich nanopores and permeability in tight gas reservoirs are poorly understood up to date. Advanced techniques are needed to be employed to accurately characterize pore structures, especially tiny pores which include micron and nanopores. In this study, various experimental techniques such as scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) T 2 , nitrogen adsorption method, and NMR cryoporometry (NMRC) are combined to interrogate the complex pore systems of the tight gas reservoir in the Linxing formation, Ordos Basin, China. Results show that tight gas sandstones are primarily comprised of residual interparticle and clay-dominated pores. Clay and quartz are two dominate minerals while pyrite occupies a nontrivial amount as well. The permeability of tight gas sandstones is very low, exhibiting an extremely poor positive correlation with porosity. While pore types and relative pore contents are more influential factors on the permeability, accurate characterization of pore size distribution is critical for the permeability of tight gas sandstones. Therefore, complementary characterization methods are carried out, indicating that neither small pores with radii < 100 nm (around peak 1 in NMR T 2 distribution) nor large pores with radii > 5 μ m (around peak 3 in NMR T 2 distribution) control the permeability by analyzing the connectivity of the pores in various size ranges, but rather pores averaging approximately 350 ± X nm (around peak 2 in NMR T 2 distribution) have sufficient connectivity to host and transmit hydrocarbons. The pore size of tight gas sandstones is dominated by the clay-rich mineral assemblage. The study shows that the NMRC technique can be a very promising method, especially when referred to as a promising “roadmap” on how to interrogate tight formations such as the tight gas sands or even shale especially for the nanopore characterization.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils

The peroxide value of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine peroxide values using field portable and process instrumentation; those efforts presented “best-case scenarios” with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique or combination thereof is best for predicting peroxide values. Following peroxide value assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression calibration models to predict the peroxide value of unknown oil samples. A global peroxide value model based on near-infrared (8 mm optical path length) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm optical path length near infrared (5.1), Raman (6.9) and 50 µm optical path length mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global peroxide value models based on low-level fusion of the NIR (8 and 24 mm optical path length) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes. This work demonstrates the difficulty of developing a truly global method for determining peroxide value of oils.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In-situ thermomechanical measurements during burst testing of Zr claddings using digital image correlation and infrared thermography techniques

Burst testing has long been a relied-on method for assessing fuel cladding materials in light-water reactoraccident scenarios. However, burst testing historically provided minimal in-situ observations beyond a few thermocouple readings, pressure from transducers, and post-test deformation measurements. Acquisition of full cladding thermomechanical data throughout a burst test would be invaluable to fuel system qualification, material model development and fuel performance code validation, such as the BISON fuel performance code. Recently, methodologies for simultaneously applying 2-dimensional digital image correlation and infrared thermography techniques to quantify the relationship between temperature, internal cladding pressure, and deformation during burst testing were developed. This work details results from the application of these techniques to burst testing of Zircaloy-4 cladding segments subjected to loss-of-coolant accident transients in an air environment. Two types of tests were performed with: (a) cladding segments connected to a fixed pressure reservoir as well as (b) closed systems where internal pressure increased during transients. In-situ thermomechanical measurements including strain and thermal gradient data are presented, demonstrating the effectiveness of applying combined surface measurement techniques to burst testing

Bell, Sam↗
DOE OSTI2020

A Novel Technique for Pulsed Operation of Magnetrons without Modulation of Cathode Voltage

Modern pulsed superconducting accelerators of megawatt beams require efficient RF sources controllable in phase and power. For each Superconducting RF (SRF) cavity is desirable a separate RF source with power up to hundreds of kW with pulse duration in the millisecond range. The efficiency of the traditional RF sources (klystrons, IOTs, solid-state amplifiers) is lower than that of the magnetrons, while the cost of a unit of RF power is much higher. Therefore the magnetron-based RF sources would significantly reduce the capital and operation costs in comparison with the traditional RF sources. A recently developed an innovative technique makes possible the pulsed generation of magnetrons powered below the self-excitation threshold voltage. This technique does not require pulse modulators to form RF pulses. The magnetron operation in this regime is stable, low noise, controllable in phase and power, and provides higher efficiency than other types of RF power sources. It allows operation in pulsed modes with large duty factor. The developed technique and its experimental verification are considered and discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Scalable Techniques for Stochastic Power Flow Problems (Final Report)

The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.

42 ENGINEERING↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2023

Numerical Studies of the On-Line Reactivity Monitoring Techniques in Subcritical Systems: Revisit of the Area-Ratio Method, the Neutron Source-Modulation Method, and the Flux-to-Current Ratio Method

In the subcritical systems, the subcriticality level must be monitored continuously to ensure the safe operation of the systems. Techniques such as the neutron source-modulation method and the flux-to-current ratio method have been proposed for on-line reactivity measurements of the subcritical systems. However, the accuracy of these methods is unknown in the actual applications. In this report, the fundamental concepts of these techniques are visited, with numerical simulation techniques developed to validate these on-line reactivity monitoring methodologies. Specifically, the Monte Carlo numerical simulation results show that the neutron source-modulation method is not accurate in determining the reactivity of the subcritical systems. The flux-to-current ratio method can provide on-line reactivity measurements, and its spatial effects have been studied and well understood through the numerical simulations of the fuel loading of the neutron source facility of Ukraine. In addition, a modified version of the area-ratio method is proposed for the on-line measurements of the absolute reactivity of the subcritical systems. Monte Carlo numerical simulations showed that this method can provide the absolute reactivity of the subcritical systems within ~5% error, if the neutron detectors are placed close to the fuel assembly interface with the reflector zone or in the reflector zones away from the neutron source.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluating Optical Techniques to Characterize Solid State Samples for the Pu-238 Supply Program

This report documents steps that have been taken to establish advanced characterization capabilities for solid-state samples to support the 238 Pu Supply Program. The program has already invested significantly in spectroscopy and online monitoring development for liquid processes. Many of the data, analytical methods, and equipment could also be leveraged for the analysis of Np/Pu oxides and Np pellets to help classify material properties and link them to operations. The techniques described in this work include diffuse reflectance spectroscopy (DRS), Raman spectroscopy, and laser-induced breakdown spectroscopy (LIBS). Each technique is sensitive to various chemical and/or elemental species and can provide complimentary information to more standard methods such as powder x-ray diffraction and scanning electron microscopy. These options are remotely deployable via fiber-optic cables. DRS and Raman spectroscopy are already approved for glove box and hot cell work, but LIBS requires US Department of Energy approval for incorporation. Raman spectroscopy does require laser shielding, which means that DRS is the easiest method to implement. However, each technique provides complimentary data, and the most robust sample characterization could be achieved when all three, among other methods, are harnessed together. This report documents some of the progress made testing these capabilities, some of the challenges, and next steps to optimize the technology and integration strategies.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Characterizing the Uncertainty of Measurement of Traceable Isotope Ratios with Bayesian Statistical Techniques

Analytical techniques such as multicollector—inductively coupled plasma—mass spectrometry (MC-ICP-MS) are routinely employed at SRNL, other National Laboratories, and in academia to determine the precise isotopic composition of diverse natural and anthropogenic samples (e.g., rocks and nuclear materials). Quantifying and reporting uncertainty in such analyses, while regularly performed, have a rigorous statistical foundation. The Guide to the Expression of Uncertainty in Measurement 4 (GUM) outlines conventional techniques used to assess such uncertainty. As the accessibility and speed of statistical computing increase, there is a need to modernize conventional techniques. For example, Supplement 1 to the 3rd to the GUM suggests the use of approximation methods as an updated approach to the GUM.

McLarty, Ellis C.↗
DOE OSTI2024

An OVERVIEW of MICROPHONICS in CEBAF and CURRENT MODERATION TECHNIQUES

Superconducting RF (SRF) structures are susceptible to frequency detuning from external vibrations and modal mechanical resonances in the structure. These small disturbances, known as microphonics, require additional RF power in CW accelerating structures since the frequency is constantly shifting. In the Jefferson Lab CEBAF accelerator, time and frequency data of this frequency shift have been recorded for many years, allowing a retrospective analysis of different microphonics-mitigation techniques. Some of these techniques are specific to the design of each CEBAF cryomodule, for example implementing BNNT damping material on the cavity string. Other techniques are universal such as affixing vacuum lines and reinforcing waveguide structures.

Powers, Tom↗
DOE OSTI2025

Machine Learning-Based Technique for Automated Sensor Characterization

The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert s time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.

Zepeda, Cuevas [Chicago U., KICP]↗
DOE OSTI2025

The Effects of Manufacturing Techniques on Neutron-Irradiated C26M Mechanical Properties

Nuclear energy provides 13% of the total energy produced globally. To further improve the safety and reliability of nuclear reactors material challenges need to be successfully resolved. C26M/FeCrAl alloy systems can improve the safety and reliability of current Generation III reactors due to the potential benefits of a stable passivation layer from the Al, which can protect against corrosion, and promising mechanical performance at boiling- and light-water reactor temperatures. However, information is limited on how manufacturing techniques affect the mechanical performance of C26M in neutron-irradiated environments. In this research, C26M specimens were manufactured using three techniques and then irradiated at the Advanced Test Reactor at Idaho National Laboratory. This research aims to bridge this gap by investigating how the manufacturing techniques affects the mechanical performance of irradiated C26M at Generation III reactor relevant temperatures.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

A review of instrument techniques to measure magnetospheric cold electrons and ions

A review of the instruments and techniques to directly measure the full distributions of the cold-ion and cold-electron populations in the magnetosphere is presented. Relatively few studies have focused on the cold plasma populations of the magnetosphere due to difficulties associated with obtaining measurements. The cold particle populations are defined here as those with total energy approximately <100 eV which is an energy range for which measurements are difficult (regardless of species), but which often make up the bulk of the plasma density. These populations have known and suspected impacts on the structure and dynamics of the magnetosphere but to date have not yet been measured adequately. The lack of accurate measurements cold ion and electron populations through the magnetosphere makes closure of these science questions extremely difficult if not impossible. Reaching closure will require innovations in plasma spectrometers and associated techniques required to obtain high-fidelity measurements of the cold ion and electron populations in the magnetosphere. This paper seeks to review the instruments and techniques that have been used to date and present possible options for future missions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Development of a Vibration Technique Based on Geometric Optimization for Fatigue Life Evaluation of Sandwich Composite Structures

A major obstacle to obtaining cost-effective experimental data on the fatigue life of sandwich panels is the prohibitive amount of time and cost required to carry out millions of cycles. On the other hand, vibration techniques applied to sandwich geometries fail to match the stress patterns that are obtained from standard flexural fatigue tests. To overcome such limitations, a vibration-based fatigue technique is proposed, which entails the use of sandwich specimens whose geometries are optimized to reproduce the stress distribution observed during three point bend loading while vibrating at the first resonant frequency. The proposed vibration technique was experimentally validated. The results, compared with the average number of cycles to failure at different stress ratios obtained via the Three-Point Bending test, showed high levels of accuracy. The proposed method is robust and time effective and indicates the possibility of attaining fatigue lifetime prediction of a wide class of composite elements, such as sandwich panels.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding High-Voltage Behavior of Sodium-Ion Battery Cathode Materials Using Synchrotron X-ray and Neutron Techniques: A Review

Despite substantial research efforts in developing high-voltage sodium-ion batteries (SIBs) as high-energy-density alternatives to complement lithium-ion-based energy storage technologies, the lifetime of high-voltage SIBs is still associated with many fundamental scientific questions. In particular, the structure phase transition, oxygen loss, and cathode–electrolyte interphase (CEI) decay are intensely discussed in the field. Synchrotron X-ray and neutron scattering characterization techniques offer unique capabilities for investigating the complex structure and dynamics of high-voltage cathode behavior. In this review, to accelerate the development of stable high-voltage SIBs, we provide a comprehensive and thorough overview of the use of synchrotron X-ray and neutron scattering in studying SIB cathode materials with an emphasis on high-voltage layered transition metal oxide cathodes. We then discuss these characterizations in relation to polyanion-type cathodes, Prussian blue analogues, and organic cathode materials. Finally, future directions of these techniques in high-voltage SIB research are proposed, including CEI studies for polyanion-type cathodes and the extension of neutron scattering techniques, as well as the integration of morphology and phase characterizations.

25 ENERGY STORAGE↗