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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 271 records · Page 15

Laser powder bed fusion of ODS Fe–Cr–Al (0.3Zr, 0.3Y 2 O 3 ): Unveiling processing-microstructure- mechanical property relationships

Here, this study investigates the fabrication of oxide dispersion strengthened (ODS) Fe-Cr-Al alloys via laser powder bed fusion (LPBF) with strategic additions of 0.3 wt% Zr and 0.3 wt% Y 2 O 3 for enhanced mechanical performance in nuclear applications. Systematic processing parameter optimization yielded three distinct conditions: one low-density product with significant defects and two near-full-density materials with improved consolidation. Comprehensive characterization confirmed single-phase α-ferrite matrix formation with successful incorporation of Y-, Zr-, O-, and C-rich precipitates characteristic of ODS alloys. However, precipitate density remained low (∼10 7 cm −3 ), resulting in sink strength values substantially below optimal levels for radiation resistance. Microhardness values (mid-200s HV) correlated inversely with grain size following the Hall-Petch relationship, indicating grain boundary strengthening as the dominant mechanism rather than precipitation strengthening. The optimized processing conditions achieved excellent mechanical properties with room temperature yield strength of approximately 500 MPa and 30 % elongation, demonstrating superior strength-ductility synergy compared to other additively manufactured ODS materials and performance consistent with literature values for LPBF-processed ODS-FeCrAl alloys. This investigation reveals both the potential and limitations of LPBF processing for ODS Fe-Cr-Al alloys. While successful defect-free fabrication was achieved, results highlight the critical need for systematic optimization of processing parameters and post-processing heat treatments to enhance precipitate density for effective dispersion strengthening and radiation resistance while maintaining additive manufacturing advantages.

Additive manufacturing↗

Shielded and Low-Damping SPM Probes for Quantitative Electrical and Electrochemical Characterization (Phase IIA)

The purpose of this DOE SBIR award was to develop new scanning probe microscopy tools for the elucidation of electrical and electrochemical properties at the nanoscale. High performance probes are important for energy materials research. In both solar cells and batteries, the essential physics and chemistry occur at the nanoscale and nanoscale characterization tools are required for their elucidation. Two products were developed: an electrically shielded probe and an electrically conductive probe with low leakage currents. Our processes were based on post processing of existing probes and fabrication methods were tested, leading to a laser micromachining based approach that led to the first minimal viable product. We invented a method to make a reliable electrical contact that attaches a flexible printed circuit board to the chip. enable leak-free operation crucial when used in conductive liquids and electrolytes. This proprietary solution improves chip handling, reduces contamination, and maintains effective electrical contact. The probes fabricated in this Phase IIa are a minimal viable product which attracted attention from various tip manufacturers and instrument manufacturers alike.

36 MATERIALS SCIENCE↗

Materials Scorecards, Phase 1: Advanced Materials and Manufacturing Technology

This report presents preliminary material score cards (Phase 1) based on a survey of industry experts and the limited literature available on the state of advanced manufacturing of materials for nuclear applications. Seven reactor types were considered, and the data is presented in tabular form. The caveat is that the scores are based on limited data and expert judgement. Considerable work remains to be done to prioritize materials for advanced manufacturing to support existing and advanced reactors. A central database of processing conditions, resulting microstructure, post processing, properties, and performance of these materials is needed to support the accelerated adoption of advanced manufacturing by the industry.

36 MATERIALS SCIENCE↗

Use of inverse quasi-epitaxy to modify order during post-deposition processing of organic photovoltaics

Disclosed herein are methods for fabricating an organic photovoltaic device comprising depositing an amorphous organic layer and a crystalline organic layer over a first electrode, wherein the amorphous organic layer and the crystalline organic layer contact one another at an interface; annealing the amorphous organic layer and the crystalline organic layer for a time sufficient to induce at least partial crystallinity in the amorphous organic layer; and depositing a second electrode over the amorphous organic layer and the crystalline organic layer. In the methods and devices herein, the amorphous organic layer may comprise at least one material that undergoes inverse-quasi epitaxial (IQE) alignment to a material of the crystalline organic layer as a result of the annealing.

36 MATERIALS SCIENCE↗

Data reduction through optimized scalar quantization for more compact neural networks

Raw data generation for several existing and planned large physics experiments now exceeds TB/s rates, generating untenable data sets in very little time. Those data often demonstrate high dimensionality while containing limited information. Meanwhile, Machine Learning algorithms are now becoming an essential part of data processing and data analysis. Those algorithms can be used offline for post processing and post data analysis, or they can be used online for real time processing providing ultra low latency experiment monitoring. Both use cases would benefit from data throughput reduction while preserving relevant information: one by reducing the offline storage requirements by several orders of magnitude and the other by allowing ultra fast online inferencing with low complexity Machine Learning models. Moreover, reducing the data source throughput also reduces material cost, power and data management requirements. In this work we demonstrate optimized nonuniform scalar quantization for data source reduction. This data reduction allows lower dimensional representations while preserving the relevant information of the data, thus enabling high accuracy Tiny Machine Learning classifier models for online fast inferences. We demonstrate this approach with an initial proof of concept targeting the CookieBox, an array of electron spectrometers used for angular streaking, that was developed for LCLS-II as an online beam diagnostic tool. We used the Lloyd-Max algorithm with the CookieBox dataset to design an optimized nonuniform scalar quantizer. Optimized quantization lets us reduce input data volume by 69% with no significant impact on inference accuracy. When we tolerate a 2% loss on inference accuracy, we achieved 81% of input data reduction. Finally, the change from a 7-bit to a 3-bit input data quantization reduces our neural network size by 38%.

97 MATHEMATICS AND COMPUTING↗

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗

Evaluation of In-Situ Analysis Strategies at Scale for Power Efficiency and Scalability

The increasing gap between available compute power and I/O capabilities is resulting in simulation pipelines running on leadership computing facilities being reformulated. In particular, in-situ processing is complementing conventional post-process analysis, however, it can be performed by using the same compute resources as the simulation or using secondary dedicated resources. In this paper, we focus on three different in-situ analysis strategies, which use the same compute resources as the ongoing simulation but different data movement strategies. We evaluate the costs incurred by these strategies in terms of run time, scalability and power/energy consumption. Furthermore, we extrapolate power behavior to peta-scale and investigate different design choices through projections. Experimental evaluation at full machine scale on Titan supports that using fewer cores per node for in-situ analysis is the optimum choice in terms of scalability. Hence, further research effort should be devoted towards developing in-situ analysis techniques following this strategy in future high-end systems.

97 MATHEMATICS AND COMPUTING↗

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. These inputs and outputs were used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems at the Brady Hot Springs Geothermal Site. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Brady Hot Springs Geothermal Site.

15 GEOTHERMAL ENERGY↗

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Desert Peak Geothermal Field.

15 GEOTHERMAL ENERGY↗

Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files are used with the Geothermal Exploration Artificial Intelligence for the Salton Sea Geothermal Site to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Salton Sea Geothermal Site.

15 GEOTHERMAL ENERGY↗

Assessment of the Corrosion Risks to a Double Shell Tank During the Selective Removal of a Cesium-rich Supernate Layer - 20227

The Direct Feed Low Activity Waste (DF-LAW) activity will provide the initial feed to the Waste Treatment and Immobilization Plant at the Hanford Tank Farm facility. Feed preparation for DF-LAW will be carried out in multiple double shell waste tanks (DST) utilizing the Tank Side Cesium Removal (TSCR) process. Tank AP-106 will be an integral part of the TSCR process and hence key to the DFLAW activity. Prior to being utilized for this purpose, the Cs-137 concentration levels in the AP-106 supernate must be reduced significantly. The AP-106 re-purposing process manages normal waste tank addition procedures such that waste acceptance criteria objectives for Cs-137 removal are achieved. As this process was being developed, several concerns regarding tank integrity during and after repurposing of Tank AP-106, and the associated tanks (i.e., AP-102, AN-101, and AP-108), were addressed. The potential corrosion degradation mechanisms identified based on process knowledge included: general and pitting corrosion, caustic stress corrosion cracking, concentration cell corrosion, and microbiologically induced corrosion (MIC). A systematic approach was undertaken to assess the risk of corrosion during the AP-106 re-purposing process. The assessment considered the initial and present condition of the tank, the service history of the tank, the environmental conditions created in each tank during each stage of the process, process timing, and corrosion testing and modeling that approximated tank conditions. Based on this information, recommendations were provided to minimize the exposure of the tank to corrosive conditions. These recommendations included time limits for each stage of the process, staging of corrosion inhibitor solutions should process delays occur, and waste sampling with potential chemistry adjustments at defined steps in the process. Additionally, recommendations for post-process supernate chemistry adjustments and tank inspections were put forth. The greatest risk for this process occurs during the manipulation of large quantities of Columbia River water (i.e., greater than 450,000 gallons) within AP-106, the associated tanks and the supporting infrastructure (i.e., transfer line piping). This risk becomes more pronounced if there is a process upset and the tank walls remain exposed to a corrosive condition longer than intended. As long as the river water is blended into the supernate in a timely fashion, and the waste is adjusted appropriately with corrosion inhibitors, corrosion may be minimized and the final condition of the supernate in AP-106 and the associated tanks is expected to be in compliance with corrosion chemistry requirements. Contingency plans will be made to minimize the impact of a process upset. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Minimum critical masses and their uncertainties for several fissile nuclides and reflectors - 14296

A systematic effort was undertaken to reevaluate the minimum critical mass for several fissile nuclides and reflectors. This was done using MCNP6 in combination with several modern nuclear data libraries, viz. ENDF/B-VII.1, JENDL-4.0 and JEFF-3.1.1. This combination was benchmarked extensively against criticality safety benchmarks. The procedure to extract the minimum critical mass from the MCNP6 calculations was carefully implemented, so that it would have a negligible impact on the accuracy of the end results. All parts of the calculation, i.e. nuclear data processing, MCNP6 models, and post-processing, were applied consistently for all cases, involving varying fissile nuclides and reflectors. Results for the minimum critical mass were generated for {sup 233,235}U, {sup 236,239,241}Pu, {sup 242m}Am, {sup 243,245,247}Cm, and {sup 249,251}Cf, for the case of water moderation and water reflection. For {sup 235}U, the minimum critical mass was also calculated for cases with other reflectors, such as beryllium, heavy water, graphite, lead, and concrete. The results for the water reflection cases are in good agreement with most of the literature values, but for the cases with reflectors such as graphite, lead, or concrete, there are sizable differences. The accuracy of the results was assessed in two ways. First, a comparison was made with criticality safety benchmark results, by selecting benchmarks that resemble the minimum mass systems the most. It was clear that for {sup 233,235}U and {sup 239}Pu with water reflection, the differences in minimum critical masses between the libraries are consistent with the differences obtained for benchmark cases. The difference between the benchmark calculations and the benchmark values is then an indication of the accuracy with which one can simulate comparable systems. Secondly, sensitivity runs were performed with the new MCNP6 sensitivity option, based on ENDF/B-VII.1 nuclear data. For each fissile nuclide, the sensitivity of k{sub eff} to cross sections such as capture, fission, elastic, inelastic was calculated for the minimum critical mass case. The same was done for the {sup 1}H and {sup 16}O cross sections in the moderator and reflector. The uncertainty in k{sub eff} was calculated by combining the sensitivity profiles with the appropriate ENDF/B-VII.1 covariance matrix, using the SUSD code. As a final step, the uncertainty in k{sub eff} can be translated to an uncertainty in the minimum critical mass. (author)

42 ENGINEERING↗

In situ and in-transit analysis of cosmological simulations

Abstract Modern cosmological simulations have reached the trillion-element scale, rendering data storage and subsequent analysis formidable tasks. To address this circumstance, we present a new MPI-parallel approach for analysis of simulation data while the simulation runs, as an alternative to the traditional workflow consisting of periodically saving large data sets to disk for subsequent ‘offline’ analysis. We demonstrate this approach in the compressible gasdynamics/ N -body code Nyx, a hybrid $\mbox{MPI}+\mbox{OpenMP}$ MPI + OpenMP code based on the BoxLib framework, used for large-scale cosmological simulations. We have enabled on-the-fly workflows in two different ways: one is a straightforward approach consisting of all MPI processes periodically halting the main simulation and analyzing each component of data that they own (‘ in situ ’). The other consists of partitioning processes into disjoint MPI groups, with one performing the simulation and periodically sending data to the other ‘sidecar’ group, which post-processes it while the simulation continues (‘in-transit’). The two groups execute their tasks asynchronously, stopping only to synchronize when a new set of simulation data needs to be analyzed. For both the in situ and in-transit approaches, we experiment with two different analysis suites with distinct performance behavior: one which finds dark matter halos in the simulation using merge trees to calculate the mass contained within iso-density contours, and another which calculates probability distribution functions and power spectra of various fields in the simulation. Both are common analysis tasks for cosmology, and both result in summary statistics significantly smaller than the original data set. We study the behavior of each type of analysis in each workflow in order to determine the optimal configuration for the different data analysis algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗

Digital pile-up rejection for plutonium experiments with solution-grown stilbene

A solution-grown stilbene detector was used in several experiments with plutonium samples including plutonium oxide, mixed oxide, and plutonium metal samples. Neutrons from different reactions and plutonium isotopes are accompanied by numerous gamma rays especially by the 59-keV gamma ray of 241Am. Identifying neutrons correctly is important for nuclear nonproliferation applications and makes neutron/gamma discrimination and pile-up rejection necessary. Each experimental dataset is presented with and without pile-up filtering using a previously developed algorithm. The experiments were simulated using MCNPX-PoliMi, a Monte Carlo code designed to accurately model scintillation detector response. Collision output from MCNPX-PoliMi was processed using the specialized MPPost post-processing code to convert neutron energy depositions event-by-event into light pulses. The model was compared to experimental data after pulse-shape discrimination identified waveforms as gamma ray or neutron interactions. We show that the use of the digital pile-up rejection algorithm allows for accurate neutron counting with stilbene to within 2% even when not using lead shielding

Bourne, M. M.↗

PDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks

The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transportation. Microtransit, a flexible and demand-responsive service using smaller vehicles within defined zones, can be effectively modeled as a PDPTW. Yet, the need for driver breaks—a key human constraint—is frequently overlooked in PDPTW solutions, despite being necessary for regulatory compliance. This study presents a novel mixed-integer linear programming formulation for the Pickup and Delivery Problem with Time Windows and Driver Breaks (PDPTW-DB). To the best of our knowledge this formulation is the first to consider mandatory periodic driver breaks within optimized Microtransit routes. The proposed model incorporates regulatory compliant break scheduling directly within the vehicle routing optimization framework. By considering driver break requirements as an integral component of the optimization process, rather than as a post-processing step, the model enables the generation of routes that respect hours of service regulations while minimizing operational costs. This integrated approach facilitates the generation of schedules that are operationally efficient and prioritize driver welfare through driver breaks. We work with a public transit agency from the southern USA, and highlight the specific nuances of driver break optimization, and present a Pickup and Delivery Problem with Time Windows formulation for optimizing Microtransit operations and scheduling driver breaks. We validate our approach using real-world data from the transit agency. Our results validate our formulation in producing cost-effective, and regulation-compliant solutions.

Applied Computing, Transportation↗

A Synchronized Sensor Array for Remote Monitoring of Avian and Bat Interactions with Offshore Renewable Energy Facilities

Wind energy production in the U.S. is projected to increase to 35% of our nation’s energy by 2050. This substantial increase in the U.S. is only a portion of the global wind industry growth, as many countries strive to reduce greenhouse gas emissions. A major environmental concern and potential market barrier for expansion of wind energy is bird and bat mortality from impacts with turbine blades, towers, and nacelles. Carcass surveys are the standard protocol for quantifying mortality at onshore sites. This method is imperfect, however, due to survey frequency at remote sites, removal of carcasses by scavengers between surveys, searcher efficiency, and other biases as well as delays of days to weeks or more in obtaining information on collision events. Furthermore, carcass surveys are not feasible at offshore wind energy sites. Near-real-time detection and quantification of interaction rates is possible at both onshore and offshore wind facilities using an onboard, integrated sensor package with data transmitted to central processing centers. We developed and experimentally tested an array of sensors that continuously monitors for interactions (including impacts) of birds and bats with wind turbines. The synchronized array includes three sensor nodes: (1) vibration (accelerometers and contact microphones), (2) optical (visual and infrared spectrum cameras), and (3) bioacoustics (acoustic and ultrasonic microphones). Accelerometers and contact acoustic microphones are placed at the root of each blade to detect impact vibrations and sound waves propagating through the structure. On-board data processing algorithms using wavelet analysis detect impact signals exceeding background vibration. Stereo-visual and infrared cameras were placed on the nacelle to allow target tracking, distance, and size calculations. On-board image processing and target detection algorithms identify moving targets within the camera field of view. Bioacoustic recorders monitor vocalizations and echolocations to aid in identifying organisms involved in interactions. Data from all sensors are temporarily stored in ring (i.e., circular) buffers with a duration varying by sensor type. Detection of target presence or impact by any of the sensors can trigger the archiving of data from all buffers for transmission to a central data processing center for evaluation and post-processing. This mitigates the risk of “data mortgages” posed by continual recording and minimizes personnel time required to manually review event data. We first conducted individual component tests at laboratories and field sites in Corvallis and Newport, Oregon, and Seattle and Sequim, Washington. We conducted additional component tests on research wind turbines at the North American Wind Research and Training Center, Mesalands Community College (MCC; General Electric 1.5 MW turbine), New Mexico, and the National Wind Technology Center, National Renewable Energy Laboratory (NREL; Controls Advanced Research Turbines 3 [CART 3] 600 kW Westinghouse turbine), Colorado. We conducted fully integrated system tests at NREL in October 2014 and April 2015. We used only research wind turbines so that we could conduct controlled, experimentally generated impacts using empty and water-filled tennis balls shot from a compressed air cannon on the ground. The approx. 57-140 g tennis balls (depending on water content) were at the upper mass range for bats, but lower mass range for marine birds. Therefore, the ability to detect collisions of most seabirds is likely greater than our experiments demonstrate, but possibly lower for some bats depending on the background signal of a given turbine. Vibration data demonstrated that background signals of operating turbines varied markedly among the CART 3 under normal operation (greatest), GE (moderate), and CART 3 during idle rotation (generator not engaged; least). In total, we measured 63 experimental blade impacts on the two research turbines. Impaction detection was dependent on background signals, position of impact on the blade (a tip strike resulted in the strongest impact signal), and impact kinetics (velocity of ball and whether the ball struck the surface of the blade or the leading edge of the blade struck the ball). Overall detection percentage ranged from 100% for the “quietest” conditions (CART 3 idle rotation), down to 35% for the noisiest (CART 3 normal operation). Impact signals were detected from sensors on more than one blade (i.e., blades other than the blade struck) 50% - 75% of the time. Stereo imaging provided valuable metrics, but increased data processing and equipment cost. Given the cost of cameras with sufficient resolution for target identification, we suggest mounting cameras directly on the blades to continuously view the entire rotor swept area with the fewest number of cameras. Bioacoustic microphones provide taxonomic identification, as well as information on ambient noise levels. They also assist in identifying environmental conditions such as hail storms, high winds, thunder, lightning, etc., that may contribute to a collision or a false positive detection. We demonstrated a proof of concept for an integrated sensor array to detect and identify bird and bat collisions with wind turbines. The next phase of research and development for this system will miniaturize and integrate sensors from all three nodes into a single wireless package that can be attached directly to the blade. This next generation system would use all “smart” sensors capable of onboard data processing to drastically reduce data streams and processing time on a central computer. A provisional patent for the blade mounted system was submitted by Oregon State University and recorded by the U.S. Patent and Trademark Office (application no. 62313028). Eventually, technology and industry advances will allow this low cost monitoring system to be designed into materials during manufacturing so that all turbines could be monitored with either a subset or full suite of sensors. As standard equipment on all commercial turbines, the sensor suite would allow the industry to effectively monitor whether individual turbines were causing mortalities or not and under what circumstances. It would also provide real-time evaluation of mechanical and structural integrity of a turbine via vibration, image, and acoustic data streams, thereby permitting modifications in operation to limit environmental or mechanical damage.

17 WIND ENERGY↗