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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Review of Advanced Characterization Methods and Techniques for Amorphous and Poorly Crystalline Materials Applicable to Cementitious Waste Forms

This review covers advanced characterization methods of cementitious materials. The particular focus is to understand cementitious compositions with amorphous content because conventional techniques such as X-ray diffraction are more applicable to materials with long range order. Also of interest is advanced characterization that provides deeper insights into properties such as porosity. There are five groups of characterization methods discussed in this review which are: electron beam/microscopy, X-ray, neutron diffraction and scattering, nuclear magnetic resonance, and optical techniques. The techniques can be further grouped by the categories of nanoscale structural understanding (transmission electron microscopy and pair distribution function), microscale structural understanding (focused ion beam and x-ray tomography), microscopic elemental distributions (energy dispersive spectroscopy and X-ray fluorescence), and chemical binding information (electron energy loss spectroscopy, x-ray absorption spectroscopy, nuclear magnetic resonance, Raman spectroscopy, and infrared spectroscopy), with advantages and disadvantages of each method discussed. The recommendation for further research is to begin with techniques that are easier to prepare samples for, measure, and analyze, such as the optical techniques of Raman and infrared spectroscopy. If more information is needed, pursue collaborations, other techniques, or proposals for beam time at the synchrotron sources.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure. The captured edge profiles are transformed into essential boundary conditions. This allows the construction of a strongly formulated boundary value problem (BVP), classified as the Dirichlet problem. Capturing boundary conditions from the digital image is novel, although a similar approach was applied to the point cloud data. It was shown that the CPCM is more efficient in this hybrid simulation framework than the weak-form-based numerical schemes. Unlike the finite element method (FEM), it can avoid aligning boundary nodes with regression points. A three-point bending test of a rubber beam was simulated to validate the developed technique. The simulation results were benchmarked against numerical results by ANSYS and various relevant numerical schemes. The technique can effectively solve the Dirichlet-type BVP, yielding accurate deformation, stress, and strain values across the entire problem domain when employing a linear strain model and increasing the number of CPCM nodes. In addition, comparative analysis with conventional displacement tracking techniques verifies the developed technique’s robustness. The proposed technique effectively circumvents the inherent limitations of traditional monitoring methods resulting from the reliance on physical gauges or target markers so that a robust and non-contact solution for remote structural health monitoring in real-scale infrastructures can be provided, even in unfavorable experimental environments.

Chemistry↗
DOE OSTI2022

Evaluation of hydrograph separation techniques with uncertain end-member composition

Hydrograph separation is one of many approaches used to analyse shifts in source water contributions to stream flow resulting from climate change in remote watersheds. Understanding these shifts is vital, as shifts in source water contributions to a stream can shape water management decisions. Because remote watersheds are often inaccessible and have poorly characterized contributing water sources, or end-members, it is critical to understand the implications of using different hydrograph separation techniques in these data-limited environments. To explore the uncertainty associated with different techniques, results from two hydrograph separation techniques, mass balance and principle component analysis, were compared using 3 years of aqueous geochemical data from the East River watershed located in the Elk Mountains of Central Colorado. Solute concentrations of the end-members were characterized by both a limited set of direct chemical measurements of different sources and detailed seasonal instream chemistry to examine the influences of uncertain end-member compositions in a data-limited environment. Annual volumetric end-member contributions to stream flow had relatively good agreement across separation techniques. Large variations in time were observed in the hydrograph separations, depending on the end-member type, and estimated flow contributions varied between the selected solutes. End-member concentrations characterized by stream chemistry showed several limitations including a reduced number of distinguishable end-members and differences in timing of flow contributions. Here the results highlight the benefits of using multiple hydrograph separation techniques by providing a ‘weight-of-evidence’ approach to environments with limited end-member concentration data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advances in in situ/operando techniques for catalysis research: enhancing insights and discoveries

Abstract Catalysis research has witnessed remarkable progress with the advent of in situ and operando techniques. These methods enable the study of catalysts under actual operating conditions, providing unprecedented insights into catalytic mechanisms and dynamic catalyst behavior. This review discusses key in situ techniques and their applications in catalysis research. Advances in in situ electron microscopy allow direct visualization of catalysts at the atomic scale under reaction conditions. In situ spectroscopy techniques like X-ray absorption spectroscopy and nuclear magnetic resonance spectroscopy can track chemical states and reveal transient intermediates. Synchrotron-based techniques offer enhanced capabilities for in situ studies. The integration of in situ methods with machine learning and computational modeling provides a powerful approach to accelerate catalyst optimization. However, challenges remain regarding radiation damage, instrumentation limitations, and data interpretation. Overall, continued development of multi-modal in situ techniques is pivotal for addressing emerging challenges and opportunities in catalysis research and technology.

Chen, Linfeng↗
DOE OSTI2022

Melting and phase relations of Fe-Ni-Si determined by a multi-technique approach

Many studies have suggested silicon as a candidate light element for the cores of Earth and Mercury. However, the effect of silicon on the melting temperatures of core materials and thermal profiles of cores is poorly understood, due to disagreements among melt detection techniques, uncertainties in sample pressure evolution during heating, and sparsity of studies investigating the combined effects of nickel and silicon on the phase diagram of iron. Here, in this study we develop a multi-technique approach for measuring the high-pressure melting and solid phase relations of iron alloys and apply it to Fe 0.8 Ni 0.1 Si 0.1 (Fe-11wt%Ni-5.3wt%Si), a composition compatible with recent estimates for the cores of Earth and Mercury. This approach combines results (20-83 GPa) from two atomic-level techniques: synchrotron Mossbauer spectroscopy (SMS) and synchrotron x-ray diffraction (XRD). Melting is independently detected by the loss of the Mossbauer signal, produced exclusively by solid-bound iron nuclei, and the onset of a liquid diffuse x-ray scattering signal. The use of a burst heating and background updating method for quantifying changes in the reference background during heating facilitates the determination of liquid diffuse signal onsets and leads to strong reproducibility and excellent agreement in melting temperatures determined separately by the two techniques. XRD measurements additionally constrain the hcp-fcc phase boundary and in-situ pressure evolution of the samples during heating. We apply our updated thermal pressure model to published SMS melting data on fcc-Fe and fcc-Fe 0.9 Ni 0.1 to precisely evaluate the effect of silicon on melting temperatures. We find that the addition of 10 mol% Si to Fe 0.9 Ni 0.1 reduces melting temperatures by ~250 K at low pressures (<60 GPa) and flattens the hcp-fcc phase boundary. Extrapolating our results, we constrain the location of the hcp-fcc-liquid quasi-triple point at 147±14 GPa and 3140±90 K, which implies a melting temperature reduction of 500 K compared with Fe 0.9 Ni 0.1 . The results demonstrate the advantages of combining complementary experimental techniques in investigations of melting under extreme conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A survey on processing-in-memory techniques: Advances and challenges

Processing-in-memory (PIM) techniques have gained much attention from computer architecture researchers, and significant research effort has been invested in exploring and developing such techniques. Increasing the research activity dedicated to improving PIM techniques will hopefully help deliver PIM’s promise to solve or significantly reduce memory access bottleneck problems for memory-intensive applications. We also believe it is imperative to track the advances made in PIM research to identify open challenges and enable the research community to make informed decisions and adjust future research directions. In this survey, we analyze recent studies that explored PIM techniques, summarize the advances made, compare recent PIM architectures, and identify target application domains and suitable memory technologies. We also discuss proposals that address unresolved issues of PIM designs (e.g., address translation/mapping of operands, workload analysis to identify application segments that can be accelerated with PIM, OS/runtime support, and coherency issues that must be resolved to incorporate PIM). We believe this work can serve as a useful reference for researchers exploring PIM techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Survey of Cyber Risk Analysis Techniques for Use in the Nuclear Industry

Using traditional probabilistic risk analysis methods for severe accident safety risk management on non-digital systems, structures, and components at nuclear power plants is well-established. In contrast, cyber risk analysis of digital assets is still an immature field with unproven techniques due, in part, to the continuously changing threat environment and the challenge of digital assets failing in unexpected ways. As the nuclear fleet continues to adopt digital instrumentation and control systems, it is increasingly important to have effective and efficient cyber risk analysis techniques to support risk management decisions, such as risk elimination by system redesign or risk mitigation by implementation of prioritized security controls. To understand the state of the art in cyber risk analysis for future research, we surveyed 36 publications across ten application domains. We describe our survey methodology and rate each technique based upon scope, adoptability, and repeatability. In this work, we examine the unique constraints of the nuclear industry and outline the strengths and weaknesses of using the cyber risk analysis techniques in the industry, highlighting gaps with current techniques. We also discuss challenges and potential research directions for advancing the science for both existing and new advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Brownian bridge-based speed imputation technique for truck energy consumption and emissions estimation

The available truck Global Positioning System (GPS) data, typically collected with large time gaps, rely on imputation techniques to obtain second-by-second data that are required in models for estimating truck energy consumption and emissions. However, existing speed imputation techniques either require a large amount of high-resolution data for model training or rely on special movement assumptions. Here, to fill the gap and effectively apply the low-resolution truck GPS datasets, this paper proposes a simple imputation technique that adopts the Brownian bridge structure to impute missing speed data. The proposed technique introduces a feasible imputation region and a combined drift into the imputation procedure to capture vehicle acceleration constraint, travel distance constraint, and speed volatility. The calibrated model is applied to a set of low-resolution truck GPS data. The results demonstrate the robustness of the proposed technique in enhancing estimation accuracy when using low-resolution GPS data to estimate fuel consumption and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Plasma and trap-based techniques for science with antimatter

Positrons (i.e., antielectrons) find use in a wide variety of applications, and antiprotons are required for the formation and study of antihydrogen. Available sources of these antiparticles are relatively weak. To optimize their use, most applications require that the antiparticles be accumulated into carefully prepared plasmas. We present an overview of the techniques that have been developed to efficiently accumulate low energy antiparticles and create, in particular, tailored antiparticle plasmas. Techniques are also described to create tailored antiparticle beams. Many of these techniques are based on methods first developed by the nonneutral plasma community using electron plasmas for increased data rate. They have enabled the creation and trapping of antihydrogen, have been critical to studies of positron and positronium interactions with matter, including advanced techniques to characterize materials and material surfaces, and have led to the creation and study of the positronium molecule. Rather than attempting to be comprehensive, we focus on techniques that have proven most useful, applications where there has been significant, recent progress, and areas that hold promise for future advances. Examples of the latter include the ever more precise comparisons of the properties of antihydrogen and hydrogen, tests of gravity using antihydrogen and positronium atoms, and efforts to create and study phases of the many-electron, many-positron system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

X-ray multi-probe data acquisition: A novel technique for laser pump x-ray transient absorption spectroscopy

We report the development and implementation of a novel data acquisition (DAQ) technique for synchrotron-based laser pump X-ray Transient Absorption (XTA) spectroscopy, called X-ray Multi-Probe DAQ (XMP DAQ). This technique utilizes high performance analog to digital converters and home-built software to efficiently measure and process the XTA signal from all x-ray pulses between laser excitations. XMP DAQ generates a set of time resolved x-ray absorption spectra at thousands of different pump–probe time delays simultaneously. Two distinct XMP DAQ schemes are deployed to accommodate different synchrotron storage ring filling patterns. Current Integration (CI) DAQ is a quasi-analog technique that implements a fitting procedure to extract the time resolved absorption intensity from the averaged fluorescence detector response. The fitting procedure eliminates issues associated with small drifts in the voltage baseline and greatly enhances the accuracy of the technique. Photon Counting (PC) DAQ is a binary technique that uses a time resolved histogram to calculate the XTA spectrum. While PC DAQ is suited to measure XTA data with closely spaced x-ray pulses (~10 ns) and a low count rate (<1 detected photon/pulse), CI DAQ works best for widely spaced pulses (tens of ns or greater) with a high count rate (>1 detected photon/pulse). XMP DAQ produces a two-dimensional XTA dataset, enabling efficient quantitative analysis of photophysical and photochemical processes from the sub-nanosecond timescale to 100 μs and longer.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Analysis techniques for blob properties from gas puff imaging data

Filamentary structures, also known as blobs, are a prominent feature of turbulence and transport at the edge of magnetically confined plasmas. They cause cross-field particle and energy transport and are, therefore, of interest in tokamak physics and, more generally, nuclear fusion research. Several experimental techniques have been developed to study their properties. Among these, measurements are routinely performed with stationary probes, passive imaging, and, in more recent years, Gas Puff Imaging (GPI). In this work, we present different analysis techniques developed and used on 2D data from the suite of GPI diagnostics in the Tokamak à Configuration Variable, featuring different temporal and spatial resolutions. Although specifically developed to be used on GPI data, these techniques can be employed to analyze 2D turbulence data presenting intermittent, coherent structures. We focus on size, velocity, and appearance frequency evaluation with, among other methods, conditional averaging sampling, individual structure tracking, and a recently developed machine learning algorithm. We describe in detail the implementation of these techniques, compare them against each other, and comment on the scenarios to which these techniques are best applied and on the requirements that the data must fulfill in order to yield meaningful results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Interference fringe (IF) technique for droplet contact angle and thickness measurements: Ultralow contact angle and nanoscale thickness measurement

Recently, reflection interference fringe (RIF) and transmission fringe (TIF) techniques have been introduced to investigate the origin of far-field interference fringe (IF) formation and to determine a droplet's contact angle and thickness by measuring the fringe radius. In this study, characteristics of the IF technique are analyzed based on the RIF and TIF by varying the schematics, such as configuration (transmission/reflection), the droplet's side (left-hand side/right-hand side), and the substrate types (flat/prism). The analysis also investigates the refraction effect at the droplet edge and the maximum incidence and contact angles. The schematic variation shows that the widest contact angle range can be measured in a transmission configuration with droplet's right-hand side, and that the fringe radius decreases with incidence angles on a prism substrate, consistent with the recent observation. Refraction at the droplet edge causes the fringe radius to increase or decrease depending on the degree of refraction. Based on the characteristics study, it is revealed that the IF technique can determine nanometer-scale thicknesses below 100 nm on droplets, corresponding to ultra-small contact angles of less than 0.01°, with an extended working distance of 3000 mm and an optimized incidence angle, assuming a spherical profile. This finding is significant, as it demonstrates that the nanoscale thickness can be determined in situ under ambient conditions using a simple optical configuration, without requiring a sophisticated setup, such as a microscope. It is anticipated that the IF technique can be combined with other nanoscale thickness measurement techniques to enhance its measurement reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advancing Reel-to-Reel Inspection Techniques for Long HTS Conductors: Comparison and Innovations

The continuous advancement of high-temperature superconductor (HTS) technologies has greatly accelerated the development and deployment of HTS applications. Among the critical tools supporting these advancements are reel-to-reel (R2R) critical current (I c ) measurement techniques, which are extensively used by both manufacturers and end users to characterize long-length REBCO conductors. These techniques play a vital role in quality assurance and quality control (QA/QC), ensuring the reliability and performance of HTS conductors and applications throughout the production cycle. We have developed a range of in-house devices for R2R measurements at the University of Houston and Princeton Plasma Physics Laboratory. These include one-dimensional (1D) scan using a magnetic circuit (MC) and two-dimensional (2D) magnetic field mapping systems based on scanning probe array microscope (SPAM) or scanning probe microscopy (SPM). Each technique offers distinct advantages: the MC system provides ultra-fast scanning speeds, ideal for rapid inspection in large-scale industrial production; the high-resolution SPM delivers detailed insights for conductor research and development; and the SPAM, with its simpler mechanical setup, can be upgraded for higher field and lower temperature conditions with a balanced 2D resolution. Here we compared the magnetization and detection capabilities of these techniques through experiments on rare-earth barium copper oxide (REBCO) coated conductor samples, with data analysis supported by numerical simulations. Based on our comprehensive comparative studies, we propose enhancements for each measurement system and provide guidelines for selecting the optimal technique combinations to meet specific application requirements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Filterscope Techniques for Parasitic Signal Screening

Here, the filterscope diagnostic uses bandpass filters and photomultiplier tubes (PMTs) to detect specific spectral emission lines. A filterscope was used to measure the W I 400.88 nm line emission as a function of ion energy on the Radio Frequency Plasma Interaction Experiment (RF PIE) for the purpose of assessing W erosion on plasma-facing components (PFCs). Different filter techniques are being explored and compared in order to effectively screen out nearby impurity lines, like the Ar II 401.39 nm line. The effectiveness of these techniques is determined by comparing the measurements to a high-resolution 1.0 m Czerny–Turner spectrometer with 0.012 nm spectral resolution. The ability to filter out nearby impurity emissions is useful when imaging PFCs in fusion devices including divertor and antenna guard limiters. Initial results with a helium plasma show little difference between the two techniques at higher bias voltages. In a helium plasma at lower dc bias voltages, a two-filter technique with filters at two separate wavelengths was shown to be more effective at screening out background signals. Data collected with an argon plasma however show the technique with overlapping filters on the line of interest is a closer match to spectrometer data at lower dc bias voltages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Measurement techniques using the electron beam profile scanner at the Fermilab Main Injector

This work presents techniques for non-invasive transverse profile measurements of high-intensity proton beams using an Electron Beam Profile Scanner (EBPS). The EBPS utilizes low-energy electrons as a probe to analyze the transverse size of proton beams, allowing for potential analysis on a single-bunch basis. Recent upgrades to the Fermilab Main Injector have enhanced beam power on target to 1 MW, with future developments targeting 2 MW. The higher beam power has increased the demand for non-invasive diagnostics, as invasive methods can disrupt operations.The techniques presented include 1) the slow scan technique, which serves as a proof of concept for the probe beam, 2) the one-shot scan technique for measuring horizontal beam profiles, and 3) the raster scan technique for analyzing horizontal beam profiles as a function of the longitudinal distribution of the beam. The profiles obtained will be crucial for studying and understanding instabilities in high-power, high-intensity proton beams. This will contribute to optimizing the operation of high-power proton accelerators by minimizing beam loss, activation, and damage to both the diagnostics and the accelerator components.

Mwaniki, Matilda [IIT, Chicago]↗
DOE OSTI2020

Considerations for using Privacy Preserving Machine Learning Techniques for Safeguards

In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume II – Predicting Material Performance from Material Microstructure

This report describes the current state of modeling and simulation techniques for predicting the properties of materials fabricated with advanced manufacturing techniques, given the initial microstructure of the material. The report includes a literature survey and a gap analysis outlining and prioritizing key issues in applying these modeling and simulation techniques to nuclear reactor structural materials. The discussion covers both physics-based and data-driven modeling techniques and includes a broad range of manufacturing techniques and materials that may have future nuclear applications. This report is the second in a two-part series, with the first report covering modeling and simulation methods for predicting the initial, as-manufactured structure of advanced manufacturing materials, given a description of the process. Both reports focus on a set of manufacturing technologies likely to be applied to reactor structural components. Taken together, the two reports provide a complete summary of the current state of processing-structure-properties models for advanced manufacturing as well as a survey of applications to reactor structural materials

42 ENGINEERING↗
DOE OSTI2021

Verification of Combined VR Techniques, Derivation of Future Time Equation, and Integration of LLNL Pulsed Sphere V&V Suite [Slides]

To determine whether the combination of forced-collision and DXTRAN variance-reduction (VR) techniques is unbiased, and to gain insight into the operation of these techniques, proof that first-moment estimates from Monte Carlo simulations employing both techniques are unbiased is developed. A general background on the forced-collision and DXTRAN VR techniques and their combination is given. Proof of an unbiased simulation is outlined by showing the equivalence of the history score moment equations of simulations with these techniques in use. A report with detailed proof of this equivalence is available upon request. The derivation of the future time equation using a similar approach, as well as a summary of the addition of the LLNL Pulsed Sphere experiments to the MCNP verification and validation suite, is also briefly discussed.

97 MATHEMATICS AND COMPUTING↗