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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hotspot formation due to shock-induced pore collapse in 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX): Role of pore shape and shock strength in collapse mechanism and temperature

The shock to detonation transition in heterogeneous high energy density solids starts with the spatial localization of mechanical energy into so-called hotspots that form due to the interaction between the leading wave and microstructural features and defects. We used large-scale molecular dynamics to characterize the hotspots resulting from the shock-induced collapse of cylindrical voids and elongated cracks focusing on the effect of shock strength, defect shape, and size. The temperature fields resulting from the collapse of cracks elongated along the shock direction show significantly higher sensitivity to both shock strength and size than cylindrical voids. Cracks 80 nm in length result in temperatures almost three times higher than voids 80 nm in diameter, reaching values corresponding to the ideal case of isentropic recompression of a gas. The molecular dynamics trajectories reveal the atomic origin of this contrasting behavior. While circular voids undergo a transition from viscoelastic pore collapse to a hydrodynamic regime with increasing shock strength, shock focusing in elongated cracks results in jetting and vaporization which, upon recompression, leads to increased heating.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Generation of lognormal synthetic Lyman-α forest spectra for P 1 D analysis

The one-dimensional flux power spectrum (P 1 D ) of the Lyman-α forest probes small-scale structure in the intergalactic medium (IGM) and is therefore sensitive to a variety of cosmological and astrophysical parameters. These include the amplitude and shape of the matter power spectrum, the thermal history of the IGM, the sum of neutrino masses, and potential small-scale fluctuations due to the nature of dark matter. However, P 1 D is also highly sensitive to observational and instrumental systematics, making accurate synthetic spectra essential for validating analyses and quantifying these effects, especially in high-volume surveys like the Dark Energy Spectroscopic Instrument (DESI). We present an efficient lognormal mock framework for generating one-dimensional Lyman-α forest spectra tailored for P 1 D analysis. Our method captures the redshift evolution of the mean transmitted flux and the scale-dependent shape and amplitude of the one-dimensional flux power spectrum by tuning Gaussian field correlations and transformation parameters. Across the DESI Early Data Release (EDR) redshift range (2.0 ≤ z ≤ 3.8), and a wide range of scales (10 -4 s km -1 ≤ k ≤ 1.0 s km -1 ), our mocks recover the mean flux evolution with redshift to sub-percent accuracy, and the P 1 D at the percent level. Additionally, we discuss potential extensions of this framework, such as the incorporation of astrophysical contaminants, continuum uncertainties, and instrumental effects. Such improvements would expand its utility in ongoing and upcoming surveys and enable a broader range of validation efforts and systematics studies for P 1 D inference and precision cosmology.

Lyman alpha forest↗
DOE OSTI2024

Tuning the spin dynamics and magnetic phase transitions of the Cantor alloy via composition and sample processing protocols: A muon spin relaxation study

CrMnFeCoNi, also called the Cantor alloy, is a well-known high-entropy alloy whose magnetic properties have recently become a focus of attention. Here, we present a detailed muon spin relaxation study of the influence of chemical composition and sample processing protocols on the magnetic phase transitions and spin dynamics of several different Cantor alloy samples. Specific samples studied include a pristine equiatomic sample, samples with deficient and excess Mn content, and equiatomic samples magnetized in a field of 9 T or plastically deformed in pressures up to 0.5 GPa. The results confirm the sensitive dependence of the transition temperature on composition and demonstrate that post-synthesis pressure treatments cause the transition to become significantly less homogeneous throughout the sample volume. In addition, we observe critical spin dynamics in the vicinity of the transition in all samples, reminiscent of canonical spin glasses and magnetic materials with ideal continuous phase transitions. Application of an external magnetic field suppresses the critical dynamics in the Mn-deficient sample, while the equiatomic and Mn-rich samples show more robust critical dynamics. The spin-flip thermal activation energy in the paramagnetic phase increases with Mn content, ranging from 3.1⁢(3) × 10 -21 J for 0% Mn to 1.2⁢(2) × 10 -20 J for 30% Mn content. These results shed light on critical magnetic behavior in environments of extreme chemical disorder and demonstrate the tunability of spin dynamics in the Cantor alloy via chemical composition and sample processing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The UV Photoinduced Ring-Closing Reaction of Cyclopentadiene Probed with Ultrafast Electron Diffraction

Conjugated cyclic organic molecules are common across many fields such as pharmaceuticals, are naturally occurring in biological systems, and are used in synthetic materials. One particular area of interest from a photochemical point of view is the formation of highly strained cyclic organics. We investigate the photoinduced reaction of cyclopentadiene, a five-membered organic ring molecule which can form strained three and four carbon rings after photoexcitation with UV light, with the gas-phase ultrafast electron diffraction instrument at the SLAC MeV-UED facility. Electron diffraction offers a direct probe sensitive to the nuclear geometry during the reaction, allowing for the determination of the distribution of products formed following photoexcitation. We observe the simultaneous formation of the highly strained ring- closed bicyclo[2.1.0]pentene and vibrationally hot cyclopentadiene within the temporal resolution of the experiment, and determine the relative yield of all reaction products. Furthermore, the experimental results are in good agreement with the predictions of trajectory simulations.

Computational Chemistry↗
DOE OSTI2024

Dependence of high- Z redeposition on the field-to-surface pitch angle and other sheath parameters in tokamaks

Accurately predicting redeposition is vital for high-Z plasma-facing component (PFC) survivability in magnetic confinement fusion. In this study, we categorize high-Z redeposition into three mechanisms: geometric-driven (prompt), sheath-driven (local), and scrape-off-layer-driven (far) redeposition. To investigate these mechanisms, we employ Monte Carlo transport codes to simulate azimuthally symmetric tungsten source erosion and redeposition in a tokamak. By iteratively analyzing critical parameters, we evaluate redeposition scaling for each mechanism. Specifically, we investigate the impact of magnetic-field-to-PFC pitch angle assumptions on PFC losses into the scrape-off layer. Our findings reveal significant pitch angle sensitivity due to an asymmetric prompt vs local redeposition trade-off. These results enhance our understanding of redeposition phenomena in fusion plasma environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Investigating the eco‐evolutionary response of microbiomes to environmental change

Abstract Microorganisms are the primary engines of biogeochemical processes and foundational to the provisioning of ecosystem services to human society. Free‐living microbial communities (microbiomes) and their functioning are now known to be highly sensitive to environmental change. Given microorganisms' capacity for rapid evolution, evolutionary processes could play a role in this response. Currently, however, few models of biogeochemical processes explicitly consider how microbial evolution will affect biogeochemical responses to environmental change. Here, we propose a conceptual framework for explicitly integrating evolution into microbiome–functioning relationships. We consider how microbiomes respond simultaneously to environmental change via four interrelated processes that affect overall microbiome functioning (physiological acclimation, demography, dispersal and evolution). Recent evidence in both the laboratory and the field suggests that ecological and evolutionary dynamics occur simultaneously within microbiomes; however, the implications for biogeochemistry under environmental change will depend on the timescales over which these processes contribute to a microbiome's response. Over the long term, evolution may play an increasingly important role for microbially driven biogeochemical responses to environmental change, particularly to conditions without recent historical precedent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nuclear Data for High Energy Ion Interactions and Secondary Particle Production

Understanding the harmful effects of galactic cosmic rays (GCRs) on space exploration requires a substantial amount of nuclear data. Specifically, the interaction of energetic GCR charged particles with spacecraft materials generates secondary radiations that, through energy deposition, can harm astronauts and electronic systems. By identifying the gaps in our knowledge of the relevant nuclear data – interaction cross sections – and identifying ways to fill those gaps – with measurements, compilations, evaluations, disseminations, reaction modeling, sensitivity studies, and uncertainty quantification – the safety and viability of space exploration can be improved. This work surveys the state of the art in this interdisciplinary field and identifies promising collaborative research topics that have significant potential to advance our understanding of the effects of the space radiation environment on space exploration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Development of a Radiation-Tolerant Front End Digitizer

High-radiation and high-temperature environments represent notoriously detrimental conditions for electronics. Yet sensors and instrumentation are critically important for the safe operation of nuclear reactors and for the validity of the scientific experiments conducted within them. Traditionally, sensors in such extreme environments operate with few active components, resulting in small signals (mV–V, nA–µA range) that must be transmitted through long cable runs before digitization by sensitive data acquisition systems located in clean, less-harsh environments. Long cables are prone to picking up noise through electromagnetic interference and distortion caused by their parasitic impedances, resulting in signal degradation. The Front End Digitizer (FREND) system described and demonstrated herein seeks to address these issues by enabling the placement of a radiation-resistant analog front end within reactor containment, or other high-radiation environments. FREND will enable early signal pre-amplification, digitization, and optical encoding within the high-radiation field to transmit sensor signals over an optical fiber to the non-nuclear environment of an instrument room. Early signal pre-amplification and digitization maintain signal integrity, whereas optical transmission renders the system blind to induced electromagnetic noise over the long cable runs. This report describes the FREND initial prototype, which can multiplex and optically encode data from up to four sensor inputs, though, in principle, this can be extended to any number of sensor inputs. The end result is an extremely flexible, high-fidelity system.

42 ENGINEERING↗
DOE OSTI2022

Beyond the Standard Model physics prospects at DUNE

The Deep Underground Neutrino Experiment (DUNE) is an international project for neutrino physics and proton-decay searches, currently in the design and construction stages. Once built, DUNE will consist of two detectors exposed to the world's most intense neutrino beam. The near detector will record neutrino interactions near the beginning of the beamline, at Fermilab. The other, much larger, detector, comprising four 17-kton liquid argon time projection chambers (LArTPCs), will be installed at a depth of 1.5 km at the Sanford Underground Research Facility in South Dakota, about 1300 km away from the neutrino source.The unique combination of the high-intensity neutrino beam with DUNE's high-resolution near detector system and massive LArTPC far detector enables a variety of probes of BSM physics, either novel or with unprecedented sensitivity, from the potential discovery of new particles (sterile neutrinos or dark matter), to precision tests of the three-flavour neutrino mixing paradigm, or the detailed study of rare processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Advancement of Commercial Intumescent Expanding Foams for Deactivation and Decommissioning in the Nuclear Sector - 20198

Florida International University (FIU), in collaboration with The Department of Energy's Office of Environmental Management (DOE-EM), Savannah River National Laboratory (SRNL), and sites across the Savannah River complex, have identified an operational requirement for a fixative technology that is intended to immobilize and/or isolate residual contamination within a 3-dimensional space. Fixation of radiological contamination can reduce worker risk and mitigate potentially hazardous conditions, however nearly every marketed contamination fixative has been found to be flammable; a significant concern in radiological facilities. Coupled with this, industry fixatives are normally used as a thin coating which can present problems when attempting to stabilize irregular geometry or areas that are difficult to access whilst ensuring full coverage. The technical evaluation and advancement of commercial-off-the-shelf (COTS) polyurethane foams has yielded a down-selected candidate that shows potential in meeting the requirements to support deactivation and decommissioning activities. Several performance criteria have been established and tested to progress the technology readiness level towards an active field demonstration (TRL-7). Such criteria include: mechanical failure limits, adhesive and cohesive properties, thermal/fire resilience, determining thermal behavior, ability to immobilize contamination, and a means of non-destructive evaluation of applications. The test scenario examined was targeted towards an application for decommissioning nuclear pipework, in which the down-selected polyurethane foam would act as a barrier to segregate pipework and mitigate the potential for release during cutting, packaging, and storage operations. Testing carried out at SRNL included: mechanical evaluation of tensile, compressive, and adhesion strength by dynamic mechanical analysis (DMA), as well as thermogravimetric analysis (TGA). FIU examined the foam's fixative properties by utilizing phosphorescent europium-dysprosium doped strontium aluminate powder to investigating the extent to which contamination can be immobilized. FIU has also exploited previous successes in the field of intumescent technologies to assess the down-selected foam's tolerance to an extreme fire scenario, while maintaining the ability to effectively mitigate a contamination release. Parallel to this, extensive thermal investigations were carried out to determine the upper boundary of anticipated heat generation during the curing process as heat generation has the potential to compromise rubber parts of contaminated enclosures. These investigations subsequently yielded a promising method for a non-destructive application evaluation by means of infrared thermography. Utilizing the high sensitivity of modern IR cameras, coupled with the heat generated during the curing process of the polyurethane foam, FIU has been exploring the concept of monitoring the external pipe surface for indications of an irregular or abnormal application, thus informing operational decision making. The testing carried out utilized several current 'best fit' ASTM standards, which serve as helpful guidelines for testing, however, a precise definition of the operational parameters and requirements is still necessary. With continued collaboration with SRNL, FIU aims refine said definitions and develop new standards by which this, and other decommissioning technologies, can be accredited by relevant standards based testing. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

$|\Delta \mathcal{B}| =2$: A State of the Field, and Looking Forward--A brief status report of theoretical and experimental physics opportunities

The origin of the matter-antimatter asymmetry apparently obligates the laws of physics to include some mechanism of baryon number ($\mathcal{B}$) violation. Searches for interactions violating $\mathcal{B}$ and baryon-minus-lepton number $\mathcal{(B-L)}$ represent a rich and underutilized opportunity. These are complementary to the existing, broad program of searches for $\mathcal{L}$-violating modes such as neutrinoless double $\beta$-decay which could provide deeper understandings of the plausibility of leptogenesis, or $\mathcal{B}$-violating, $\mathcal{(B-L)}$-conserving processes such as proton decay. In particular, a low-scale, post-sphaleron violation mechanism of $\mathcal{(B-L)}$ could provide a \textit{testable} form of baryogenesis. Though theoretically compelling, searches for such $\mathcal{(B-L)}$-violating processes like $\Delta\mathcal{B}=2$ dinucleon decay and $n\rightarrow\bar{n}$ remain relatively underexplored experimentally compared to other rare processes. By taking advantage of upcoming facilities such as the Deep Underground Neutrino Experiment and the European Spallation Source, this gap can be addressed with new intranuclear and free searches for neutron transformations with very high sensitivity, perhaps greater than three orders of magnitude higher than previous experimental searches. This proceedings reports on recent theoretical and experimental advances and sensitivities of next-generation searches for neutron transformations were detailed as part of the Amherst Center for Fundamental Interactions Workshop, "Theoretical Innovations for Future Experiments Regarding Baryon Number Violation," directly coordinated with the Rare Processes and Precision Measurements Frontier.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Low-symmetry vacancy-related spin qubit in hexagonal boron nitride

Abstract Point defect qubits in semiconductors have demonstrated their outstanding capabilities for high spatial resolution sensing generating broad multidisciplinary interest. Hexagonal boron nitride (hBN) hosting point defect qubits have recently opened up new horizons for quantum sensing by implementing sensing foils. The sensitivity of point defect sensors in hBN is currently limited by the linewidth of the magnetic resonance signal, which is broadened due to strong hyperfine couplings. Here, we report on a vacancy-related spin qubit with an inherently low symmetry configuration, the VB2 center, giving rise to a reduced magnetic resonance linewidth at zero magnetic fields. The VB2 center is also equipped with a classical memory that can be utilized for storing population information. Using scanning transmission electron microscopy imaging, we confirm the existence of the VB2 configuration in free-standing monolayer hBN.

Chemistry↗
DOE OSTI2020

Stastically determined experimental uncertainties in photon Doppler velocimetry (PDV) measurements

Shock-ramp experiments place high demands on the precision, accuracy, and temporal resolution of transformed velocimetry signals. To minimize uncertainty after total propagation of a shockramp experiment, ideally multiple PDV traces are used. However, each trace has some uncertainty that is a function of the PDV system and analysis of the velocimetry data. In order to determine a reasonable experimental estimate of minimum uncertainty, we calculate observed uncertainties in as-fielded PDV systems using multiple channels to sample the velocity on each shot. We also calculate the uncertainty’s sensitivity to choice of analysis methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improved field assessments of chemicals and explosives using high-resolution gamma-ray spectroscopy with a tagged neutron interrogation system

A fi eld-portable tagged neutron interrogation system is being developed for detection of explosives and chemical warfare agents by prompt gamma-ray neutron activation analysis. The system combines an associated particle imaging deuterium-tritium neutron generator with a high-purity germanium gamma-ray detector. Fine spatial resolution neutron and alpha detectors enable precise mapping of characteristic gamma-ray emission distributions onto high-clarity neutron radiographic images. A narrow coincidence gate associated with each tagged neutron ensures a large signal-to-background ratio, thus signifi cantly improving sensitivity to the chemical compositions of the items being assessed. Recent experimental results recorded from test objects involving mock explosives and other chemicals are presented.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗