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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Community structure – Ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. In this work, we test these assertions using methane (CH 4 )-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH 4 oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Performance of three-dimensional printed nasopharyngeal swabs for COVID-19 testing

At the start of the COVID-19 pandemic, the US faced nationwide shortages of nasopharyngeal swabs due to both overwhelmed supply chains and an increase in demand. To address this shortfall, multiple 3D printed swabs were ultimately produced and sold for COVID-19 testing. In this work, we present a framework for mechanical and functional bench-testing of nasopharyngeal swabs using standard and widely available material testing equipment. Using this framework, we offer a comprehensive, quantitative comparison of the 3D printed swabs to benchmark their performance against traditional flocked swabs. The test protocols were designed to emulate the clinical use of the nasopharyngeal swabs and to evaluate potential failure modes. Overall, the 3D printed swabs performed comparably to, or outperformed, the traditional swabs in all mechanical tests. While traditional swabs outperformed some of the new 3D printed swabs in terms of sample uptake and retention, similar amounts of RNA were recovered from both 3D printed and traditional swabs.

3D printing↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for inverse problems: Determining material properties for heterogeneous systems

Here, we determine spatially varying discontinuous material properties using a domain-decomposition based physics-informed neural networks (PINNs) framework named the Adaptive Interface-PINNs or AdaI-PINNs (Roy et al., 2024). We propose the use of distinct neural networks for the field variables and material properties within each material, utilizing adaptive activation functions. While the neural networks across different materials share the same weights and biases, their activation functions are uniquely tailored using a hyperparameter that influences the slope of the activation function. The proposed framework is tested on several one-dimensional and two-dimensional benchmark examples, and its performance is compared with conventional PINNs and existing domain-decomposition PINNs frameworks, namely, the Multi-domain physics-informed neural network (M-PINN), and the eXtended physics-informed neural networks (XPINNs). The results demonstrate that the proposed approach can determine randomly distributed discontinuous material properties with an L 2 error of $\mathscr{O}$ (10 -3 ) for the material property and the root-mean-square error of $\mathscr{O}$ (10 -3 ) for the primary variable while the other approaches yield errors that are approximately two orders of magnitude larger (that is, $\mathscr{O}$ (10 -1 )). Moreover, the spatial distribution of material properties obtained using the proposed framework is in close agreement with the true distribution, whereas the other approaches fare much worse. Additionally, the proposed approach is approximately 40% faster than its competitors, indicating its potential as a robust alternative for solving inverse problems in heterogeneous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploring the parameter space of MagLIF implosions using similarity scaling. II. Current scaling

Magnetized liner inertial fusion (MagLIF) is a magneto-inertial-fusion (MIF) concept, which is presently being studied on the Z pulsed power facility. The MagLIF platform has achieved interesting plasma conditions at stagnation and produced significant fusion yields in the laboratory. Given the relative success of MagLIF, there is a strong interest to scale the platform to higher peak currents. However, scaling MagLIF is not entirely straightforward due to the large dimensionality of the experimental input parameter space and the numerous physical processes involved in MIF implosions. Here, in this work, we propose a novel method to scale MagLIF loads to higher currents. Our method is based on similarity (or similitude) scaling and attempts to preserve much of the physics regimes already known or being studied on today's Z pulsed-power driver. By avoiding significant deviations into unexplored and/or less well-understood regimes, the risk of unexpected outcomes on future scaled-up experiments is reduced. Using arguments based on similarity scaling, we derive the scaling rules for the experimental input parameters characterizing a MagLIF load (as functions of the characteristic current driving the implosion). We then test the estimated scaling laws for various metrics measuring performance against results of 2D radiation–magneto-hydrodynamic hydra simulations. Agreement is found between the scaling theory and the simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach

We present global predictions of the ground state mass of atomic nuclei based on a novel Machine Learning algorithm. We combine precision nuclear experimental measurements together with theoretical predictions of unmeasured nuclei. This hybrid data set is used to train a probabilistic neural network. In addition to training on this data, a physics-based loss function is employed to help refine the solutions. The resultant Bayesian averaged predictions have excellent performance compared to the testing set and come with well-quantified uncertainties which are critical for contemporary scientific applications. We assess extrapolations of the model’s predictions and estimate the growth of uncertainties in the region far from measurements.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Testing dark matter halo properties using self-similarity

ABSTRACT We use self-similarity in N-body simulations of scale-free models to test for resolution dependence in the mass function and two-point correlation functions of dark matter haloes. We use 10243 particle simulations performed with abacus , and compare results obtained with two halo finders: friends-of-friends (fof ), and rockstar . The fof mass functions show a systematic deviation from self-similarity which is explained by resolution dependence of the fof mass assignment previously reported in the literature. Weak evidence for convergence is observed only starting from haloes of several thousand particles, and mass functions are overestimated by at least as much as $20-25{{\ \rm per\ cent}}$ for haloes of 50 particles. The mass function of the default rockstar halo catalogue (with bound virial spherical overdensity mass), on the other hand, shows good convergence of the order of 50 to 100 particles per halo, with no detectable evidence at the few percent level of any systematic dependence for larger particle number. Tests show that the mass unbinding procedure in rockstar is the key factor in obtaining this much improved resolution. Applying the same analysis to the halo–halo two point correlation function, we find again strong evidence for convergence only for rockstar haloes, at separations sufficiently large so that haloes do not overlap. At these separations, we can exclude dependence on resolution at the $5-10{{\ \rm per\ cent}}$ level once haloes have of the order of 50 to 100 particles. At smaller separations results are not converged even at significantly larger particle number, and bigger simulations would be required to establish the resolution required for convergence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spin Splitting Energy of Transition Metals: A New, More Affordable Wave Function Benchmark Method and Its Use to Test Density Functional Theory

Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe 2+ , Fe 3+ , and Co 3+ , including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. Furthermore, we find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method—in terms of computational cost and in terms of accuracy on monatomic systems—and therefore we chose this method for molecular benchmarks. Then Kohn–Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF 2 , FeCl 2 , and CoF 2 . We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Critical role of acceptor dopants in designing highly stable and compatible proton-conducting electrolytes for reversible solid oxide cells

Proton-conducting electrolytes are receiving increasing attention due to their high ionic conductivity at intermediate temperatures, enabling the operation of solid oxide cells with high energy efficiency at low cost. However, the effect of B-site dopants on the properties of doped barium hafnate-cerate electrolyte materials, especially in single cells under operating conditions, has not been systematically studied. Here we report our findings in the development of a series of proton-conducting electrolytes with a general formula of BaHf 0.1 Ce 0.7 R 0.2 O 3–δ (BHCR172, R = Yb, Er, Y, Gd, Sm). Here, the results reveal that electrical conductivity, ionic transference number, chemical stability against steam and CO 2 , and compatibility with NiO during sintering are all closely correlated with the dopant size. In particular, the reaction with NiO is found to strongly affect the properties of the electrolytes and hence cell performance. Among all tested compositions, BaHf 0.1 Ce 0.7 Yb 0.2 O 3–δ (BHCYb172) shows excellent chemical stability and minimal reactivity towards NiO, as predicted from density functional theory (DFT)-based calculations and confirmed by experimental results. In addition, proton-conducting reversible solid oxide cells (P-ReSOCs) based on the optimized electrolyte composition, BHCYb172, demonstrate exceptional performance and stability, achieving a remarkable peak power density of 1.74 W cm –2 (O 2 as the oxidant) at 600 °C in the fuel cell mode and a high current density of 2.0 A cm –2 at 1.3 V and 600 °C in the steam electrolysis mode while maintaining excellent durability for over 1000 h.

25 ENERGY STORAGE↗
DOE OSTI2020

Low-cost desalination of seawater and hypersaline brine using nanophotonics enhanced solar energy membrane distillation

A stand-alone small-scale nanophotonics enhanced solar membrane distillation (NESMD) testbed was designed, developed, and tested for desalinating seawater and high salinity feedwaters. This NESMD system can take almost any source water and turn it into clean water with sunlight as the only energy source. The NESMD technology applies nanophotonic coating materials on a commercial hydrophobic polypropylene support of a polytetrafluoroethylene (PTFE) membrane surface. The photothermal coating serves as a solar thermal collector, absorbs solar energy, and generates highly localized heat on the membrane, while the rest of the membrane performs membrane distillation functions. The presented NESMD system is equipped with an internal heat recovery system with no need for external electricity and no additional water for cooling. The NESMD testbed is installed and tested at Rice University campus (29.7174° N, 95.4018° W). In this study, real seawater from Galveston Bay, Texas, U.S. and high salinity simulated feedwaters (total dissolved solids (TDS) of 113 200–200 000 PPM) have been tested for long-term testing under the weather conditions of Houston, Texas. Here, the field testing results showed stable desalination performance in consecutive 5–8 hour operation cycles, with a TDS removal of ≥99.5% in all experiments. An average daily membrane flux of ≥0.75 L m –2 h –1 was achieved at a solar intensity close to 1 kW m –2 without an external heat exchanger. Further investigations and improvements are required to enhance the performance of the reactor since it is still a new promising technology.

14 SOLAR ENERGY↗
DOE OSTI2020

In situ multimodal imaging for nanoscale visualization of tribofilm formation

A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Integrating biomechanics in evolutionary studies, with examples from the amphidromous goby model system

The functional capacities of animals are a primary factor determining survival in nature. In this context, understanding the biomechanical performance of animals can provide insight into diverse aspects of their biology, ranging from ecological distributions across habitat gradients to the evolutionary diversification of lineages. To survive and reproduce in the face of environmental pressures, animals must perform a wide range of tasks, some of which entail tradeoffs between competing demands. Moreover, the demands encountered by animals can change through ontogeny as they grow, sexually mature or migrate across environmental gradients. To understand how mechanisms that underlie functional performance contribute to survival and diversification across challenging and variable habitats, we have pursued diverse studies of the comparative biomechanics of amphidromous goby fishes across functional requirements ranging from prey capture and fast-start swimming to adhesion and waterfall climbing. The pan-tropical distribution of these fishes has provided opportunities for repeated testing of evolutionary hypotheses. By synthesizing data from the lab and field, across approaches spanning high-speed kinematics, selection trials, suction pressure recordings, mechanical property testing, muscle fiber-type measurements and physical modeling of bioinspired designs, we have clarified how multiple axes of variation in biomechanical performance associate with the ecological and evolutionary diversity of these fishes. Here our studies of how these fishes meet both common and extreme functional demands add new, complementary perspectives to frameworks developed from other systems, and illustrate how integrating knowledge of the mechanical underpinnings of diverse aspects of performance can give critical insights into ecological and evolutionary questions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Technical analysis of filter testing at the U.S. Department of Energy Filter Test Facility

The U.S. Department of Energy (DOE) technical standard DOE-STD-3020-2015 requires verification testing at the Filter Test Facility (FTF) of high-efficiency particulate air (HEPA) filters to be installed in nuclear facility (Hazard Category 1, 2, 3, and radiological facilities) confinement ventilation systems, or to be installed in habitability systems (e.g., filters for protection of workers required to act for the control and mitigation of emergency situations). Filters in these applications perform a safety function in accident situations, are designated as important to safety, or are necessary for habitability systems. Different FTFs have operated for decades, and results of tests are available to examine the need for and benefits of continued execution of 100 percent QA verification testing. The objective of this study and resulting report was to assess the need for 100 percent QA testing at the current FTF in Maryland, based on an examination of a database of test results from 2013 to August 2020. Filters that require independent testing per DOE-STD-3020-2015 to be installed in nuclear facilities are sent to the FTF before being shipped to the facilities. The FTF examines the documentation (e.g., certificates of compliance, results of particle penetration and airflow resistance testing by the manufacturers, labels affixed to filters and packages, and other requirements specified in purchase orders by the nuclear facility operators), implements visual inspections of the physical state of the filters, and checks the dimensions of frames. Filters that meet the documentation and visual inspection requirements are subjected to particle penetration and airflow resistance testing. In case of rejections, the filters are shipped back to the manufacturers, at the cost of the manufacturers, for replacement. Filters that pass all tests are shipped to the nuclear facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Experiences with SYCL on AMD GPUs with Kokkos

With the recent diversification of the hardware landscape in the high-performance computing (HPC) community, performance-portability solutions are becoming more and more important. One of the most popular choices is Kokkos, which recently became a Linux Foundation project. Most of its development is supported by the US Department of Energy and the French Alternative Energies and Atomic Energy Commission. Kokkos is implemented as a C++ library with multiple backends to support CPUs as well as various GPU architectures. These backends include OpenMP, CUDA, HIP, and also SCYL. This approach enables users to leverage the preferred vendor toolchain for the respective platform (e.g. CUDA, ROCm, OneAPI). The SYCL backend is used to target Intel GPUs, in particular to support the Aurora exascale supercomputer. However, SYCL itself also offers a large degree of portability, and in fact Kokkos’ CI for SYCL has been running on NVIDIA hardware due to a lack of access to Intel GPUs. In this report, we describe our experience with using Kokkos SYCL backend on AMD GPUs targeting the Frontier supercomputer at Oak Ridge National Laboratory. The two major SYCL implementations are DPC++ and AdaptiveCpp. While the Kokkos SYCL backend has been implemented using the former, the latter was the first implementation to target AMD GPUs. We will discuss the experience with both of these SYCL implementations in terms of functionality and performance. Using Kokkos to evaluate SYCL toolchains has a number of benefits. Kokkos’ use of SYCL is fairly complex, exercising features such as graphs, relocatable device functions, atomics – including for non-arithmetic types, as well as pinned and page migratable memory allocations. Kokkos also needs to implement capabilities such as Kokkos’ hierarchical parallelism that are not a straight-forward mapping to SYCL capabilities. Furthermore, a large number of libraries and applications that represent diverse use cases are implemented in Kokkos, providing readily available test cases for a toolchain evaluation. Preliminary results show that support for AMD GPUs in DPC++ is much less mature than for NVIDIA GPUs or Intel GPUs. While the situation has improved significantly over the last year, we still encounter many runtime failures, dispatching problems, and code generation issues. With AdaptiveCpp the challenges arise even earlier in the evaluation process. Since Kokkos’ SYCL implementation is largely focused on supporting Intel GPUs, we opted to leverage SYCL extensions which are available in DPC++ but not in AdaptiveCpp. Furthermore, AdaptiveCpp appears to be less conformant with the SYCL2020 standard which Kokkos relies on. In some cases, we are able to work around the lack of feature support, in other cases we have to disable certain Kokkos capabilities to evaluate the toolchain. Our evaluation will leverage Kokkos’ unit tests to establish basic functionality and feature completeness. We then use simple benchmarks for components of a CG implementation as a measure of usability and performance of the SYCL toolchains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Single Primary Heat Extraction and Removal Emulator (SPHERE) Long Duration Testing

For the development of heat-pipe cooled microreactors, it is crucial to thoroughly understand the characteristics and functioning of heat pipes across a wide spectrum of operating conditions. Passive heat removal and its long-term performance stability are critical factors in this context. Enhanced experimental data is vital for evaluating the operational lifespan of alkali metal heat pipes. Idaho National Laboratory (INL) has successfully conducted an extended duration test on a high-performance sodium-filled heat pipe, closely monitoring the axial temperature profile, power supplied by the heaters, and heat removed by a gas-gap calorimeter. The results from this testing provide valuable data that are instrumental in supporting heat pipe validation efforts. Specifically, this data aids in the development and validation of Sockeye, the Multiphysics Object-Oriented Simulation Environment (MOOSE) tool under the US-DOE NEAMS program designed for heat pipe modeling. By comparing experimental results with Sockeye’s predictions, the tool's accuracy and reliability can be assessed and improved, thereby enhancing its capability to simulate heat pipe operations under various conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

The Green's Function Model Intercomparison Project (GFMIP) Protocol

The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere-only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

OpenCGRA: An Open-Source Unified Framework for Modeling,Testing, and Evaluating CGRAs

Coarse-grained reconfigurable arrays (CGRAs),loosely defined as arrays of functional units (e.g, adder, sub-tractor, multiplier, divider, or larger multi-operation units, butsmaller than a general-purpose core) interconnected through aNetwork-on-Chip, provide higher flexibility than domain-specificASIC accelerators while offering increased hardware efficiencywith respect to fine-grained reconfigurable devices, such as FieldProgrammable Gate Arrays (FPGAs). The fast evolving fieldsof machine learning and edge computing, which are seeing acontinuous flow of novel algorithms and larger models, makeCGRAs ideal target architectures to allow domain specializationwithout loosing too much generality. They also generally offerquicker and more effective reconfigurability than FPGAs, po-tentially allowing adaptation during actual algorithm execution,and implement a dataflow programming paradigm that adaptswell to these emerging workloads. Designing and generating aCGRA, however, still requires to define the type and number ofthe specific functional units, implement their interconnect andthe network topology, and perform its simulation and validation,given a variety of workloads of interest.In this paper, we propose OpenCGRA, a Python-based unifiedframework that integrates generation, modeling, testing and eval-uation for CGRAs. OpenCGRA is the first open-source integratedframework able to support the full top-to-bottom design flow forspecializing and implementing CGRAs: modeling at different ab-straction levels (functional level, cycle level, register-transfer level),generation, simulation, testing at different granularities (unit test-ing, integration testing, property-based testing), and characteriza-tion (area, power, and timing). OpenCGRAs will be made availableon GitHub.

CGRA, synthesis↗
DOE OSTI2023

High spatial resolution direct conversion amorphous selenium X-ray detectors with monolithically integrated CMOS readout

Recent progress in the field of micron-scale spatial resolution direct conversion X-ray detectors for high-energy synchrotron light sources serve applications ranging from nondestructive and noninvasive microscopy techniques which provide insight into the structure and morphology of crystals, to medical diagnostic measurement devices. Amorphous selenium ( a -Se) as a wide-bandgap thermally evaporated photoconductor exhibits ultra-low thermal generation rates for dark carriers and has been extensively used in X-ray medical imaging. Being an amorphous material, it can further be deposited over large areas at room temperatures and at substantially lower costs as compared to crystalline semiconductors. Here, to address the demands for a high-energy and high spatial resolution X-ray detector for synchrotron light source applications, we have thermally evaporated a -Se on a Mixed-Mode Pixel Array Detector (MM-PAD) Application Specific Integrated Circuit (ASIC). The ASIC format consists of 128 × 128 square pixels each 150 μm on a side. A 200 μm a -Se layer was directly deposited on the ASIC followed by a metal top electrode. The completed detector assembly was tested with 45 kV Ag and 23 kV Cu X-ray tube sources. The detector fabrication, performances, Modulation Transfer Function (MTF) measurements, and simulations are reported.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spread spectrum time domain reflectometry (SSTDR) and frequency domain reflectometry (FDR) cable inspection using machine learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, justification for continued cable use must shift to a condition-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. The Pacific Northwest National Laboratory (PNNL) Accelerated and Real Time Experimental Nodal Analysis (ARENA) cable motor test bed was used to test the response of a commercial spread spectrum time domain reflectometry (SSTDR) system, a laboratory instrument software-controlled SSTDR, and a vector network analyzer-based frequency domain reflectometry (FDR) system to various cable anomalies. The three instrument systems were able to interrogate cables over a range of frequency bandwidths that can be helpful for human data analysis. Data were subjected to supervised and unsupervised machine learning (ML) analyses to distinguish normal undamaged cable responses from anomalous cable responses. Both supervised and unsupervised ML approaches produced encouraging results with an undamaged/anomalous prediction accuracy from 0.69% to 0.87%. Recommendations for further development and field implementation include increased and more balanced sample sets particularly including more training data.

SSTDR, FDR, Reflectometry, Machine Learning, ARENA↗