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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development of an Additively Manufactured Subscale Secondary Sealed Container for the NASA FROSTE Project

This presentation details the development of an additively manufactured (AM) subscale test article for the secondary sealed container (SSC) as part of the NASA FROSTE project. FROSTE is focused on the collection of regolith samples from shadowed regions of the Moon and the preservation of those samples at cryogenic temperatures for return to Earth. Our team was integrated into the FROSTE program to leverage innovative design approaches and additive manufacturing capabilities in support of a scalable development strategy, where the subscale configuration serves as the development path toward a full-scale SSC. Scalmalloy was selected as the primary material for all AM components due to its favorable strength-to-weight ratio, thermal conductivity, and demonstrated performance in aerospace applications. Its aluminum-based composition supports robust mechanical behavior at cryogenic temperatures while enabling efficient heat transfer and control of thermal gradients within the containment system. The SSC architecture consists of an outer container assembly that houses a phase change material (PCM) tank, which in turn contains primary containers holding the regolith. Thermal management relies on controlled conductive and radiative heat transfer, including a thermal connection assembly that interfaces the PCM tank to an external cryocooler via a thermal strap, and IMLI surrounding the PCM tank to inhibit radiative heat transfer. The outer container assembly incorporates sealing interfaces, thermal connection ports, and I/O feedthroughs, with PTFE spring seals used at critical interfaces to maintain containment integrity. The PCM tank is manufactured as a single monolithic Scalmalloy component and incorporates an integral lattice structure to minimize thermal gradients, internal channels for thermocouple routing, and interface features for thermal connection assembly integration. The tank is centrally suspended within the outer container using support rings, with G10 insulating components employed to inhibit thermal leaks. This work describes the design methodology, AM approach, and key considerations used to inform the design.

regolith↗
DOE OSTI2022

Implementation of Manifold-Based Combustion Models in a Highly Scalable Low Mach Number Reacting Flow Solver: Preprint

Manifold-based representations of the thermochemistry are often employed in conjunction with large eddy eimulation (LES) to lower the cost of combustion simulations. This work describes steps taken to implement this modeling approach in PeleLM, a scalable and performance-portable low Mach number flow solver. Most significantly, this includes adapting the projection method used by PeleLM to satisfy the mass conservation constraint for use with manifold-based models. The implementation is designed to be general across manifold-based models, including both those that employ traditional tabulation and those that employ neural networks. An initial demonstration for simple test cases is presented and will be used for performance assessment.

high-performance computing↗
DOE OSTI2026

Battery Material Synthesis and Scalability using a 50L Taylor Vortex Reactor (Final CRADA Report)

Under this agreement, Laminar will loan Argonne a 50L Taylor Vortex Reactor (TVR) and provide mechanical troubleshooting guidance and consulting to ensure the successful setup of the pilot-scale synthesis process. The U.S. Department of Energy (DOE) will allocate funding for the labor and materials required for the study. To evaluate the physical and electrochemical properties of the materials produced by the 50L TVR, Argonne will perform comprehensive characterizations, including XRD, SEM, PSA, ICP, tap density, and coin half-cell testing. Throughout the collaboration, Argonne will provide feedback and recommendations for mechanical improvements to the reactor system. Furthermore, Argonne will credit Laminar as a collaborator in any presentations or publications resulting from data generated by the system. Laminar will retain no rights to experimental results or intellectual property generated through the experiments conducted with the 50L TVR at Argonne.

25 ENERGY STORAGE↗
DOE OSTI2024

A graph embedding‐based approach for automatic cyber‐physical power system risk assessment to prevent and mitigate threats at scale

Abstract Power systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large‐scale power infrastructures as cyber‐physical systems is still in its early stages. Drawing inspiration from machine‐learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large‐scale cyber‐physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high‐dimensional structures in low‐dimensional spaces, facilitating advanced machine‐learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding‐based approach, the authors present a structured and methodical framework for risk assessment in cyber‐physical systems. The proposed graph embedding‐based risk analysis framework aims to provide a more insightful perspective on cyber‐physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber‐physical power system models: the Western System Coordinating Council (WSCC) 9‐Bus System and the Illinois 200‐Bus System , thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Sun, Shining↗
DOE OSTI2020

Modular, Mobile Systems for the Treatment of Contaminated Water at Three Magnox Sites in the United Kingdom - 20421

Veolia Nuclear Solutions (VNS), and its mitigated entity, Veolia Nuclear Solutions Federal Services (VNSFS), are designing, overseeing the fabrication and installation, and supporting the commissioning of highly mobile and modular skid-based water treatment systems to assist in the decommissioning of three Magnox reactor sites based in the U.K. These Modular Active Effluent Treatment Plants (MAETP) will be deployed at the Chapelcross, Hinkley Point A, and Dungeness A sites to process contaminated water through the use of ion exchange systems and/or filtration units. At the time of writing, two systems have been installed and inactively commissioned, and the third system is expected to be delivered in 2020. Veolia has utilized a multi-national team of engineers, based in the UK and the US, to effectively leverage the best of Veolia expertise in the design and delivery of mobile, modular systems. The VNS team continues to refine the modular, mobile, and scalable approach to water processing system delivery, and has successfully patented the evolving technology for proprietary protection. The intent of this technology investment is to improve the functionality, mobility, and modularity, resulting in a system which can be adapted to a broad range of throughput and isotope removal requirements to achieve the most cost effective, flexible system possible for customers. Designing, fabricating, and factory-testing the modules off site followed by onsite installation, testing, start-up, and commissioning ensures expedited delivery and setup, as well as cost savings for nuclear applications. For the MAETP systems, VNS's previous nuclear site experience and ongoing Research and Development (R and D), combined with the resulting mobile/modular water processing systems developed and successfully deployed by VNS, have proven to be important inputs for the successful end-design of the systems, materials selection, system testing and commissioning. The lessons learned in the development and continued enhancement of the patented systems described in this paper will prove useful in advancing and deploying future systems for other nuclear sites, where rapid customizing and cost-effective implementation are critical factors. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2005

Fabrication end Deployment Testing of Meter Solar Sail Quadrants for a Scaleable Square Solar Sail Ground Test System

In order for solar sail propulsion technologies to be considered as a viable option for a wide range of near term practical missions a predictable, stable, reliable, manufactureable, scaleable, and cost effective system must be developed and tested first on earth and then on orbit. The design and development of a Scaleable Square Solar Sail System (S^4) is well underway a t AEC-Able Engineering Co. Inc., and the design and production of the Solar Sails for this system is being carried out by SRS Technologies. In April and May of 2004 a single quadrant 10-meter system was tested at NASA LARC's vacuum chamber and a four quadrant 20-meter system has been designed and built for deployment and testing in the Spring of 2005 at NASA/Glenn Research Center's Plumb Brook Facility. SRS has developed an effective and efficient design for triangular sail quadrants that are supported are three points and provide a flat reflective surface with a high fill factor. This sail design is robust enough for deployments in a one atmosphere, one gravity environment and incorporates several advanced features including adhesiveless seaming of membrane strips, compliant edge borders to allow for film membrane cord strain mismatch without causing wrinkling and low mass (3% of total sail mass) ripstop. This paper will outline the sail design and fabrication process, the lessons learned and the resulting mature production, packaging and deployment processes that have been developed. It will also highlight the scalability of the equipment and processes that were developed to fabricate and package the sails. Based on recent experience, SRS is confidant that flight worthy solar sails in the 40-120-meter size range with areal density in the 4-5g/sq m (sail minus structure) range can be produced with existing technology. Additional film production research will lead to further reductions in film thickness to less than 1 micron enabling production of sails with areal densities as low as 20 g/sq m using the current design resulting in a system areal density of as low as 5.3g/sq m. These areal densities are low enough to allow nearly all of the Solar Sail missions that have been proposed by the scientific community and the fundamental technology required to produce these sails has been demonstrated on the ground test sails that have recently been built. These demonstrations have shown that the technology is mature enough to build sails needed to support critical science missions. Solar Sails will be an enabling technology for NASA's Vision for Space Exploration by allowing communication satellite orbits that can maintain continuous communication with the polar regions of the Moon and Mars and to support solar weather monitoring to provide early warning of solar flares and storms that could threaten the safety of astronauts and other spacecraft.

Laue, Greg↗
DOE OSTI2022

An Efficient, Scalable IO Framework for Sparse Data: larcv3

Neutrino physics is one of the fundamental areas of research into the origins and properties of the Universe. Many experimental neutrino projects use sophisticated detectors to observe properties of these particles, and have turned to deep learning and artificial intelligence techniques to analyze their data. From this, we have developed \texttt{larcv}, a \texttt{C++} and \texttt{Python} based framework for efficient IO of sparse data with particle physics applications in mind. We describe in this paper the \texttt{larcv} framework and some benchmark IO performance tests. \texttt{larcv} is designed to enable fast and efficient IO of ragged and irregular data, at scale on modern HPC systems, and is compatible with the most popular open source data analysis tools in the Python ecosystem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗
DOE OSTI2023

The Influence of Nonlocal Metal–Dielectric Environments on Physical and Chemical Processes

Plasmonic nanolayers and laminar metallic/dielectric multilayers were originally developed for optical cloaking applications and lensing applications that could potentially image objects whose size was below the diffraction limit. These assemblies were initially formed from gold or silver nanorods grown within an alumina mesh. However, more recently, assemblies with similar properties have also been prepared by sequential thin-layer deposition of alternating layers of gold and magnesium fluoride (MgF 2 ). These metal/dielectric composite materials enable control of the dielectric constant in the directions perpendicular to the layers and balance the real and imaginary dielectric constants of the assembly such that the speed and the amplitude of the waves traveling through the assembly are not attenuated. In this Account, we will also focus on a few of the applications ranging from surface wetting to fluorescence quenching to enhancement of photochemical reactions. First, we will share an introduction to processes used to create these materials, which are combinations of low refractive index metals and transparent higher index materials arranged in a scalable repeating fashion. Two fabrication methods were employed: an electrochemical deposition of Ag nanorods into an anodized alumina matrix which produced materials with an anisotropic negative refractive index material within the plane of the film and lamellar metal/dielectric layers in which the negative index perpendicular to the growth direction. These alternating layers of plasmonic metals and dielectric materials were ultimately chosen to prepare films for further testing, because of their relative ease of fabrication. We will continue with a discussion of a few of the applications of both of these nonlocal dielectric composite materials including more specialized plasmonic, composite, and hyperbolic metamaterials including fluorescence quenching, photochemical reactions, and surface wetting. In each of these applications, the unique response caused by the enhancement of the electric field and the interface between hyperbolic materials and plasmonic materials as they interact photophysically with their near neighbors is presented. In each of the applications, the enhanced electric field extends from the composite substrate layer to interact with its near neighbors and beyond. Furthermore, the presence of this extended interaction can be observed in the form of decreased emission lifetime, enhancement of photochemical reaction rates, and changes in the surface energies measured by contact angle goniometry. In this Account, all of these situations will be addressed. Finally, we will conclude with a summary and vision for the future as well as a discussion of the unique challenges and opportunities available as research active faculty at an HBCU.

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

Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li 7 La 3 Zr 2 O 12 solid electrolytes

Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.

25 ENERGY STORAGE↗
DOE OSTI2020

Measuring the effectiveness of high-performance Co-Optima biofuels on suppressing soot formation at high temperature

Soot emissions in combustion are unwanted consequences of burning hydrocarbon fuels. The presence of soot during and following combustion processes is an indication of incomplete combustion and has several negative consequences including the emission of harmful particulates and increased operational costs. Efforts have been made to reduce soot production in combustion engines through utilizing oxygenated biofuels in lieu of traditional nonoxygenated feedstocks. The ongoing Co-Optimization of Fuels and Engines (Co-Optima) initiative from the US Department of Energy (DOE) is focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The Co-Optima program has identified a handful of biofuel compounds from a list of thousands of potential candidates. In this study, a shock tube was used to evaluate the performance of soot reduction of five high-performance biofuels downselected by the Co-Optima program. Current experiments were performed at test conditions between 1,700 and 2,100 K and 4 and 4.7 atm using shock tube and ultrafast, time-resolve laser absorption diagnostic techniques. The combination of shock heating and nonintrusive laser detection provides a state-of-the-art test platform for high-temperature soot formation under engine conditions. Soot reduction was found in ethanol, cyclopentanone, and methyl acetate; conversely, an α-diisobutylene and methyl furan produced more soot compared to the baseline over longer test times. For each biofuel, several reaction pathways that lead towards soot production were identified. The data collected in these experiments are valuable information for the future of renewable biofuel development and their applicability in engines.

09 BIOMASS FUELS↗
DOE OSTI2024

Experimental Validation of a Modular All-Electric Power Take-Off Topology for Wave Energy Converter Enabling Marine Renewable Energy Interconnection

Power electronic converters are an enabling technology for the emerging marine energy applications, such as using ocean waves to produce electricity. This paper outlines the power take-off system and its key components used in a wave energy converter offering modularity and scalability to generate power efficiently. The proposed power take-off system was implemented based on a modular multilevel converter and could be deployed to convert any alternating current electrical energy to a different alternating current for interconnection to grid or non-grid applications. Examples of widespread deployment are supplying electricity to coastal communities or producing clean drinking water. The analysis using both the simulation tests and laboratory experiments verified the design objectives and basic functionality of the developed power take-off system. An acceptable response using a field programmable gate array-based controlled laboratory testbench was achieved, complying with guidelines specified in the prevalent industry standards. Seamless operation during steady-state and transients for the studied wave energy converter was achieved as supported by the obtained results. The key findings of this work were experimentally examined under different load conditions, direct current bus voltage fluctuations, and generator speed–torque regulation. The ability of the power take-off system to generate high-power quality of the waveforms, e.g., against adhering to the IEEE 519-2022 standard for total harmonic distortion limits, is also confirmed.

Engineering↗
DOE OSTI2025

Electric Drive Technologies Consortium (EDTC)/ Cost competitive, high-Performance, highly Reliable (CPR) Power Devices on 4H-SiC (Final Report)

4H-Silicon carbide (4H-SiC) is a wide bandgap semiconductor that offers superior material properties over silicon, including higher critical electric field, thermal conductivity, and electron saturation velocity. These advantages make 4H-SiC highly attractive for high-voltage, high-efficiency power electronics. However, realizing the full potential of SiC requires device technologies that are not only high-performing but also manufacturable and reliable under real-world operating conditions. This report summarizes the outcomes of a five-year R&D effort funded by the U.S. Department of Energy (DOE) under the Electric Drive Technologies Consortium (EDTC), focused on developing cost-competitive, high-performance, and highly reliable (CPR) power devices on 4H-SiC substrates. The program targeted scalable and manufacturable 1.2 kV-class SiC MOSFETs optimized for next-generation electric vehicles, renewable energy systems, and industrial power conversion. The project delivered transformative advancements in SiC power device performance and ruggedness. Particularly, Specific on-resistance (R on,sp ) was reduced by up to 37%, from ~4.0 m$\Omega \cdot$cm 2 in earlier designs to an industry-leading 2.40 m$\Omega \cdot$cm 2 , driven by optimized doping, refined JFET widths, and layout engineering. Breakdown voltages (BV) exceeded 1600 V, marking improvement over legacy baselines, and demonstrating the robustness of newly implemented junction profiles and edge terminations. Short-circuit withstand time (SCWT) saw a remarkable 4$\times$ increase, from ~2 $\mu$s to over 8 $\mu$s, achieved through the successful deployment of deep P-well structures (~1.8–2.0 $\mu$m) via channeling implantation. This innovative process breakthrough enabled precise junction formation without MeV-class implantation tools, reduced leakage under high field stress, and allowed even the shortest-channel devices (down to 0.3 $\mu$m) to achieve both high BV and excellent ruggedness—breaking the traditional trade-off between conduction efficiency and blocking capability. Several novel architectures pushed the performance envelope further. JBSFETs—featuring embedded Schottky portions—eliminated bipolar degradation and drastically reduced third-quadrant leakage, while Ladder MOSFETs introduced a clever orthogonal conduction path that achieved a 15.4% reduction in R on,sp over standard linear designs. Switching performance reached new benchmarks: short-channel devices showed a 31% reduction in total switching energy compared to 0.5 $\mu$m counterparts, while maintaining manageable gate drive requirements. Layout-optimized structures not only improved transconductance but also accelerated switching transitions, pointing to real-world benefits in converter-level efficiency. The devices also passed rigorous reliability validation. Stress-tested across TDDB, HTGB, HTRB, HVP, and burn-in, the devices screened under 30 V/10 hr and 43 V/1 s protocols consistently exhibited tighter lifetime distributions and long-term oxide robustness. These screening techniques proved effective in identifying latent defects and ensuring deployment-grade reliability. Meanwhile, advanced 3D TCAD simulations revealed and resolved electric field hotspots—particularly in HEXFET corners—where fields exceeding 4.8 MV/cm were mitigated through geometry-aware layout corrections. Overall, the results of this project demonstrate a manufacturable and scalable SiC power device platform that addresses key DOE performance targets for efficient, robust, and reliable 1.2kV 4H-SiC Power Devices. The developed technologies represent a meaningful step forward in the commercial readiness of high-voltage SiC solutions and provide a strong foundation for continued advancement in wide bandgap power electronics.

42 ENGINEERING↗
DOE OSTI2020

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Pt–Co truncated octahedral nanocrystals: a class of highly active and durable catalysts toward oxygen reduction

We report a facile and scalable synthesis of Pt–Co truncated octahedral nanocrystals (TONs) by employing Pt(acac) 2 and Co(acac) 2 as precursors, together with CO molecules and Mn atoms derived from the decomposition of Mn 2 (CO) 10 as a reductant and a {111} facet-directing agent, respectively. Both the composition and yield of the Pt–Co TONs could be varied through the introduction of CHCl 3 . When tested at 80 °C using membrane electrode assembly (MEA), the 4 nm Pt 2.6 Co TONs gave a mass activity of 294 A g Pt –1 at beginning-of-life (BOL) and it increased to 384 A g Pt –1 during recovery cycles. The mass activity at BOL only dropped by 24% after 30 000 voltage cycles at end-of-life (EOL) in a metal dissolution accelerated stress test. The Pt 2.6 Co/C catalyst outperformed the commercial TKK Pt 3 Co/C (230 A g Pt –1 at BOL and 40% loss after 30 000 cycles at EOL) in terms of both activity and durability. Our systematic analysis suggested that the enhancement in activity can be attributed to the combination of small, uniform size and well-defined {111} facets. This new class of catalysts holds promise for applications in proton-exchange membrane fuel cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Microbial inoculants for soil restoration: A Risk-Proportional Stewardship Framework Integrating Strain-Resolved Genomics and Adaptive Governance

Global soil degradation and increasing reliance on chemical inputs threaten agricultural sustainability, driving interest in microbial inoculants as tools for soil restoration. These biological products have the potential to enhance nutrient cycling, improve soil structure, and support plant resilience, but their environmental release raises important safety and stewardship considerations. Here, we propose a risk-proportional framework for the responsible deployment of microbial inoculants grounded in release-based stewardship. The framework integrates genome-resolved strain identification, exclusionary hazard screening, bioassay-based risk triage, ecological testing under realistic conditions, and monitored field deployment. Drawing on evidence from microbial ecology and invasion biology, we highlight how inoculants can alter resident microbial communities, influence ecosystem function, and, in some cases, facilitate gene flow, underscoring the need for risk assessment. We further outline a federated, genome-informed data infrastructure to support traceability, cross-jurisdiction learning, and adaptive management. Together, this approach provides a scalable and scientifically grounded pathway to balance innovation and safety, enabling microbial technologies to contribute to soil restoration and climate-resilient agriculture.

Edlund, Anna [OATH Inc]↗
NASA NTRS1986

Effect of specimen geometry on the energy absorption capability of composite materials

Static crushing tests were conducted on graphite and Kevlar reinforced epoxy tubes to examine the influence of specimen geometry on the energy absorption capability of composite materials. Tube inside diameter to wall thickness (D/t) ratio was determined to significantly affect the energy absorption capability of composite materials. As D/t ratio decreases, the energy absorption capability increases nonlinearly. The energy absorption capability of K/E tubes was found to be geometrically scalable but energy absorption of Gr/E tubes was not geometrically scalable.

Farley, G. L.↗
DOE OSTI2021

SMART-COM – Scalable Multi-Agent Adaptive Resolution Tools for Collaborative Outage Management

The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗