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At least 145 records · Page 8

Fracture toughness evaluations for spent nuclear fuel dry storage canister welds and spent nuclear fuel clad-pellet structures

Integrity of spent nuclear fuel (SNF) interim storage canisters is very important to the safety of the back-end nuclear fuel cycle. Stress corrosion cracking (SCC) potential of interim storage canister has been considered as a high priority. Because no post-weld heat treatment was required for forming these canisters, the high tensile residual stress existed within these canister welds. This can change the fracture resistance capacity significantly as well as increase SCC potential. Due to relative thin shell thickness of a canister weldment, the spiral notch torsion test (SNTT) method was used to estimate the canister weldment fracture toughness. SNTT was developed to measure the intrinsic fracture toughness of structural materials using small specimens. The SNTT method has been applied to a wide variety of structural materials, such as low-alloy steels, stainless steel, aluminum alloy, ceramics, concrete, and composites. The SNTT system operates by applying pure torsion to cylindrical specimens with a notch line that spirals around the specimen at a 45° pitch. In order to carry out pure torsion load mode, biaxial tension/torsion tester was developed accordingly to perform SNTT protocol. Moreover, applying fracture mechanics approach to SNF system reliability investigation is warranted due to the inherent flaws and hydride structures existed in a SNF system after nuclear reactor operation. However, none of the existing fracture toughness data deal with fuel cladding specific geometry or spent fuel material conditions, such as cladding structure with the pellet-inserts and the associated pellet clad mechanical interactions induced mixed-mode damage mechanisms. Thus, the development of an intrinsic fracture mechanics approach that is suitable for SNF materials is needed. Furthermore, due to thin wall and small dimension of clad tubing structure, the SNTT method was used to estimate the clad tubing structure fracture toughness. Fracture testing were performed on the received stainless steel canister weldment, most SNTT weld samples fracture initiation sites are at heat-affected zone (HAZ) regions. The estimated fracture toughness J Q ’ for the baseline SS304 steel is at 283 kJ/m². The estimated JQ’ for the SS304/308 weld and baseline metals are 148 kJ/m 2 and 459 kJ/m 2 , respectively. Out of cell fracture testing for spent fuel structure were carried out on the surrogate rods made of Zr-4 clad and alumina inserts, the estimated fracture toughness values for baseline Zr-4 cladding with alumina-pellet inserts are: (1) For SNTT samples with a short or medium crack length, between 5.4-mm and 8-mm, the estimate J IQ upon fracture initiation for the baseline Zr-4 cladding is at 50 kJ/m 2 with 2-sigma uncertainty of 3.26 kJ/m 2 , and the associated K IQ is at 67.46 MPa$\sqrt{m}$; and (2) For SNTT samples with a long crack length, around 13-mm, the crack initialization is deviated from that of the Mode-I tensile fracture and appears to be a mixed-mode fracture of Mode I - tensile stress and Mode III - out of plane shear stress; the estimated J MQ is at 18.9 kJ/m 2 , the associated K MQ is at 41.4 MPa$\sqrt{m}$.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ASTM D03 Workshop: Developing a Hydrogen Contamination Detector Analyzer [Slides]

Non-hydrogen constituents in the fuel steam can cause irreversible damage to FC systems and therefore should be avoided. The objectives are: 1. Develop a low-cost fast response device (analyzer) to measure impurities in a dry hydrogen fuel stream at or above the SAE J2719 levels, 2. Develop understanding of a working mechanism and improve the analyzer by identifying the best materials and their configuration, and 3. Test the analyzer in real-world environments.

42 ENGINEERING↗

Design, construction, and testing of no-insulation small subscale solenoids for compact tokamaks

Fusion energy systems studies (FESS) for next-step devices based on the most promising magnetic configurations indicate that high magnetic fields and high current density for magnet coil systems may reduce device size and lower the cost. High current density and radiation resistant fusion magnets are particularly beneficial for low cost, low aspect ratio compact reactor designs such as Fusion Nuclear Science Facility (FNSF), Fusion Pilot Plant (FPP) of low-aspect ratio spherical tokamak (ST) or compact stellarators. Unlike typical high field magnets for nuclear magnetic resonance (NMR), magnetic resonance imaging (MRI), or high energy physics research applications, neutron irradiation damage to organic insulations in the coil winding pack is a critical issue for next generation fusion reactors where orders of magnitude higher neutron fluence than those in present experimental reactors such as ITER are expected. Moreover, a high coil winding pack current density is needed for high field magnets in low cost, compact radial build next step fusion reactors. The slow current charging time, however, is an issue in fully non-insulated coils. In this work, we present the design, construction and testing of subscale Nb3Sn solenoids, up to half the diameter of the central solenoid (CS) for National Spherical Torus Experiment (NSTX), with and without inter-layer insulation for enhancing radiation resistance while improving the winding pack current density and coil performance. The major radius for the NSTX/NSTX-Upgrade (reference for compact ST) is 0.854/0.934 meter, and 4.8 meters for FNSF. The magnetic field for NSTX/NSTX-U at the plasma center is 0.6/1 Tesla and 9 Tesla for FNSF. The inner diameter of the central solenoid coil is 0.2/0.4 meter for NSTX/NSTX-U and 1.2 meters for FNSF. The current charging and discharging behavior of the prototype solenoids was investigated to quantify performance advantages of a simplified coil fabrication without error-prone vacuum pressure impregnation (VPI) for the removal of epoxy organic insulation. Scalability of the no insulation concept for fusion can be addressed via engineered coating for novel insulation on contact resistance or intra-layer no insulations. Radiation resistance and coil winding efficiency were significantly improved in the no insulation coils for next step compact fusion reactors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Self‐Healing System for Polydicyclopentadiene Thermosets

Self-healing offers promise for addressing structural failures, increasing lifespan, and improving durability in polymeric materials. Implementing self-healing in thermoset polymers faces significant manufacturing challenges, especially due to the elevated temperature requirements of thermoset processing. To introduce self-healing into structural thermosets, the self-healing system must be thermally stable and compatible with the thermoset chemistry. This article demonstrates a self-healing microcapsule-based system stable to frontal polymerization (FP), a rapid and energy-efficient manufacturing process with a self-propagating exothermic reaction (≈200 °C). A thermally latent Grubbs-type complex bearing two N-heterocyclic carbene ligands addresses limitations in conventional G2-based self-healing approaches. Under FP's elevated temperatures, the catalyst remains dormant until activated by a Cu(I) co-reagent, ensuring efficient polymerization of the dicyclopentadiene (DCPD) upon damage to the polyDCPD matrix. The two-part microcapsule system consists of one capsule containing the thermally latent Grubbs-type catalyst dissolved in the solvent, and another capsule containing a Cu(I) coagent blended with liquid DCPD monomer. Using the same chemistry for both matrix fabrication and healing results in strong interfaces as demonstrated by lap-shear tests. In an optimized system, the self-healing system restores the mechanical properties of the tough polyDCPD thermoset. Self-healing efficiencies greater than 90% via tapered double cantilever beam tests are observed.

36 MATERIALS SCIENCE↗

Evaluation of an in vitro three-dimensional HepaRG spheroid model for genotoxicity testing using the high-throughput CometChip platform

Three-dimensional (3D) culture systems are increasingly being used for genotoxicity studies due to improved cell-to-cell interactions and tissue-like structures that are limited or lacking in 2D cultures. The present study optimized a 3D culture system using metabolically competent HepaRG cells for in vitro genotoxicity testing. 3D HepaRG spheroids, formed in 96- or 384-well ultra-low attachment plates, were exposed to various concentrations of 34 test articles, including 8 direct-acting and 11 indirect-acting genotoxicants/carcinogens as well as 15 compounds that show different genotoxic responses in vitro and in vivo. DNA damage was evaluated using the high-throughput CometChip assay with concurrent cytotoxicity assessment by the ATP assay in both 2D and 3D cultures. 3D HepaRG spheroids maintained a stable phenotype for up to 30 days with higher levels of albumin secretion, cytochrome P450 gene expression, and enzyme activities compared to 2D cultures. 3D spheroids also demonstrated a higher sensitivity than 2D cultures for detecting both direct- and indirect-acting genotoxicants/carcinogens, indicating a better prediction of in vivo genotoxicity responses. When DNA damage dose-response data were quantified using PROAST software, 3D spheroids generally had lower or similar benchmark dose values compared to 2D HepaRG cells and were more comparable with primary human hepatocytes. These results demonstrate that 3D models can be adapted to the CometChip technology for high-throughput genotoxicity testing and that 3D HepaRG spheroids may be used as a reliable and pragmatic in vitro approach to better support the hazard identification and risk assessment of potential human genotoxic carcinogens.

60 APPLIED LIFE SCIENCES↗

Multiple Hail Impact Testing

For resilient energy delivery PV modules and systems must withstand extreme weather events such as hailstorms, which are the leading cause of PV insurance claims. Currently, the industry testing is limited to one strike at a time, but in real hailstorms multiple hail strikes can occur within a fraction of a second. In this project we test if multiple simultaneous or near-simultaneous hail strikes cause more damage than with single hail strike testing.

14 SOLAR ENERGY↗

Petrophysical and geomechanical properties of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well

Knowledge of petrophysical and geomechanical properties of gas hydrate-bearing sediments are essential for predicting reservoir response due to gas production from gas hydrate reservoirs. That information will be critical parameters for designing production well completion such as specification of depressurization pump, water storage tank, and mesh size of sand screen. In December 2018, Stratigraphic Test Well Hydrate-01 was drilled in the western part of the Prudhoe Bay Unit, Alaska North Slope as part of the technical planning effort for a future long-term production test by collaborative team of DOE/NETL, USGS, and MH21-S (Boswell et al., 2020, Collett et al., 2020, Okinaka et al., 2020). Data set of logging-while-drilling (LWD) were acquired (Haines et al., 2020, Suzuki et al., 2019) and core sampling depth was determined on-site.Side-wall pressure coring was conducted to recover gas hydrate-bearing sediments from two reservoir sections named Unit-B and Unit-D. A total of 34 cores were successfully recovered by 5 runs of a wire-line deployed pressure corer (CoreVault® System - Halliburton). Core analysis scheme of this project are shown in Figure 1. All cores were quenched in liquid nitrogen while at high pressure in the laboratory of Stratum Reservoir, LLC. at Anchorage (Figure 1, a)). And the cores were removed from the pressure corer autoclave with temperature support of dry ice and stored under liquid nitrogen at atmospheric pressure. 19 damaged cores were processed to index property measurements directly such as grain size, grain density. 4 of another 17 cores were depressurized and trimmed for making a plug to analyze petrophysical properties of host sediments. Unsteady-state permeability test was conducted to obtain relative water permeability to gas and core scale NMR T2 distribution measurement was performed for evaluating pore size distribution at Houston (Figure 1, b)). Remained high quality 13 cores were preserved with gas hydrate for advanced laboratory analysis. National Institute of Advanced Industrial Science and Technology, as a part of the Japanese National Hydrate Research Program (MH21-S, funded by Ministry of Economy, Trade and Industry), received the samples at Sapporo, Japan for advanced core analysis. High-resolution X-ray CT was used to analyze the quality of the samples, which showed undisturbed lithological layers. Cores were lathed into cylindrical shape and distributed for multi property measurements (Figure 1, c)).<p>As a result, sediment from Unit-D is categorized as silty sand at ~37% porosity with ~80% gas hydrate saturation. An average hydration number n = 6.16 was measured by Raman spectroscopy. An average intrinsic permeability of ~400 mD and in situ effective permeability (with hydrate) on the order of ~10 mD. The Unit B recovered cores consisted of well sorted sand at ~40% porosity with ~95% gas hydrate saturation. An average intrinsic permeability of ~1 Darcy and in situ effective permeability on the order of ~30 mD was measured for the Unit B cores. There was a small permeability reduction due to porosity loss with increasing effective stress that simulated consolidation behavior along with depressurization in the highly permeable sandy sediment. The apparent minimum change in porosity and permeability may be caused by the low compressibility of quartz sand grains in the recovered cores. XRD and thermal conductivity analysis also suggested high quartz content. Triaxial compression tests established internal friction angles based on the Mohr-Coulomb's failure criterion, which are 40° for hydrate-bearing sediment and 29.8° for hydrate free sediment.</p>

Yoneda, Jun↗

IDENTIFICATION OF POTENTIAL SUPERCONDUCTOR QUENCH PRECURSORS USING FREQUENCY DOMAIN FEATURE ANALYSIS

Superconducting magnets are important pieces of technology in the world of particle accelerators, allowing researchers to study atomic and subatomic phenomena, among other things. In some instances, superconductors can lose this non-resistive property in a phenomenon known as quenching, which can cause damage to the magnets. This potential danger prompts the introduction of systems to predict when a quench is imminent; one such implementation is through the use of acoustic sensors that detect vibrations within the magnet. Within these acoustic sensor signals, significantly above-noise disturbances (referred to as ”events”) can be identified. Our research applies the statistical framework of a permutation test to features calculated from the power spectral density (PSD) to distinguish between events far from the quench at the end of the signal to events at the start of the signal. We found that dividing the PSD into frequency bands produced a feature capable of distinguishing between events early in the signal and late in the signal leading up the quench, providing a promising starting place for future quench prediction systems.

Roehrig, Benjamin [Northern Illinois U.]↗

Summary of Marine and Hydrokinetic (MHK) Composites Testing at Montana State University

Marine and hydrokinetic (MHK) energy technologies convert the energy of waves, tides, and river and ocean currents into electricity. The primary structure of MHK energy devices have difficult and challenging environments for which fiber reinforced plastics are often considered. For cost benefits, glass fiber reinforced plastics (GFRP) are the most prevalent system under consideration. Montana State University and Sandia National Laboratories have performed research into the moisture effects on the stiffness, strength, and damage of GFRPs for many years. This paper presents a summary of a portion of this effort and also provides references to the thesis and conferences that contain the detailed information. The results include models of moisture absorption, effects of stress on moisture uptake, effects of moisture on damage modes and development, laminate stacking order effects, and culminates with moisture uptake effects on a large sample of industry collected coupons.

13 HYDRO ENERGY↗

Feature Engineering and Ensemble Methods for Imbalanced ICS Intrusion Detection: Pipeline Audit and Constrained Evaluation

Industries are becoming increasingly connected and are more vulnerable to cyberattacks due to the widened attack surface. Industrial Control Systems (ICS) are among the most critical sectors that malicious actors can target, as such attacks can cause significant operational disruption and physical damage. It is imperative to detect such attacks as early as possible. This paper evaluates constraint-conditioned optimistic performance estimates for traditional ML models in ICS intrusion detection (i.e., estimates obtained under contiguous, non-shuffled temporal evaluation without test-set alteration, but with pre-split feature engineering that may introduce temporal leakage, due to dataset constraints). Our findings are threefold. First, we quantify how iterative feature engineering affects tree-based ensemble performance and examine how pipeline decisions (split strategy, sampling scope, and cleaning policy) can inflate or reduce reported IDS results under constraint-bound evaluation. Second, we compare intrinsic class-imbalance handling across ensemble models. Third, under our current pipeline constraints (including pre-split feature engineering), CatBoost achieves the best performance on Water Storage Tank (accuracy: 0.9831, class-1 F1: 0.9682), while Light- GBM achieves the best performance on Gas Pipeline (accuracy: 0.9618, class-1 F1: 0.9086).

97 MATHEMATICS AND COMPUTING↗

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗

Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform

The goal of the Scalable Thin Light-Emitting Diode (LED) Light Sheet Platform project is to derisk the manufacturing scalability for a high chip count heterogeneous smart lighting platform, with the potential to enable significant energy savings through dynamic directional light control and custom. Specifically, the project derisks the scalability of a disruptive new computer controlled microassembly fabrication process SRI International is developing, to address fundamental cost barriers to mass production of high chip count systems. This is key for enabling mass adoption and thus maximum societal energy savings impact. The LED light sheet technology is a smart illumination platform that can be applied to lighting, signage, and display. It has features and a form factor similar to bendable or conformal OLED light sheets but uses more efficient LEDs with a remote phosphor layer that is very close to the LED to deliver a luminous efficacy that exceeds 125 lumen/Watt and enable > 50% Lighting Application Efficiency (LAE) energy savings. During Budget Period 1 (BP1), all of the BP1 milestones were successfully completed: (M2.0.1) Design demonstrator details that will meet the final project goals, (M6.1.1) Show lighting output model can predict illuminance, spatial, spectral distribution for specific light-sheet designs and use case, (M3.2.1) Automated loading supports 200 chip arrays, and (M3.3.1) Finish first interconnect process run for 200 chip array. The BP1 Go/No-Go Decision Point (G/NG 1) 200 chip demonstrator sample was in the process of final assembly and test at the end of BP1 on December 31, 2023. The objective was successfully achieved on January 16, 2024, when a wired 200-chip sample underwent confirmation testing that demonstrated a 93.75% first pass electrical yield that successfully exceeded the 75% first-pass electrical yield BP1 G/NG requirement. In addition, all 93.75% of the sample devices lit up, further demonstrating the ability to assemble and transfer small LED chips without damaging their functionality.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Review of Ultrasonic Methods for Monitoring, Damage Detection, and Processing of Lithium-Ion Batteries Throughout Their Life Cycle

Lithium-ion batteries (LIBs) are the leading technology used in consumer electronics, electric vehicles, and grid-level electrochemical energy storage applications. The ever-increasing use of LIBs has highlighted a gap in understanding of their behavior throughout their life cycle. Current monitoring systems rely on electrical and sometimes temperature measurements to assess the internal state which limits information about complex electrochemical processes. In response, ultrasonic testing (UT) has shown promise for non-invasive assessment due to its ease of use and sensitivity to mechanical changes which are correlated with electrochemical changes within the battery. We summarize the research in UT methods applied to LIBs throughout their life cycle. We also discuss physics-based and data-driven modeling approaches used to interpret ultrasonic signals in the context of LIBs, with an emphasis on the existing challenge of establishing rigorous links between electrochemical behavior and elastic and poroelastic wave physics to gain insight regarding physical changes in the LIB that can be directly measured using UT. Finally, we discuss the challenges of implementing UT across the LIB life cycle and identify opportunities for further research. This review aims to provide helpful guidance to researchers and practitioners of UT in the growing field of UT for electrochemical battery systems.

25 ENERGY STORAGE↗

Repair and Resource Scheduling in Unbalanced Distribution Systems Using Neighborhood Search

—This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming (MILP) model is developed for co-optimizing crews, resources, and network operations. The MILP model coordinates damage isolation, network reconfiguration, distributed generator re-dispatch, and crew/resource logistics. In addition, a framework for integrating different types of photovoltaic (PV) systems in the restoration process is developed. We consider two different types of crews, namely, line crews for damage repair and tree crews for obstacle removal. We also model the repair resource logistic constraints. Furthermore, a new algorithm is developed for solving the distribution system repair and restoration problem (DSRRP). The algorithm starts by solving DSRRP using an assignmentbased method, then a neighborhood search method is designed to iteratively improve the solution. The proposed method is validated on modified IEEE 123- and 8500-bus distribution test systems.

Outage management↗

In-situ Detection of Glovebox Glove Degradation Prior to Glove Failure; Effects on Safety, Waste, and Operational Costs - 20402

Glovebox glove pressure decay leak testing and analysis of the data can greatly improve glovebox safety, minimize Transuranic (TRU) glove waste, and minimize operational cost. It is well known, the weakest point of containment on a glovebox is the glove. Mitigating unplanned openings in gloves is critical to minimizing operational and safety costs in glovebox operations. Mitigating unplanned glove openings due to glove failures will be discussed in this paper. The lack of an engineered solution to determine a gloves operational life in nuclear operations, has lead to use of theoretical and manual subjective methods to determine the life and safety of a glovebox glove. Whether the glove is inspected visually prior to use, or gloves are changed regularly to theoretically avoid failure, both the operators PPE and the room are being exposed to contamination, or un-necessary amounts of TRU glove waste are being generated. Millions of dollars yearly in operational costs are spent on glove failures due to loss of production, incident analysis, regulatory audits, clean up, and paperwork. In a nuclear application, a glove failure could contaminate an operator and laboratory, shut down the operation for weeks, potentially create a regulatory audit, and potentially create a media frenzy; the damages to the organization can be astronomical. Elimination of glove failures is possible by tracking glove material degradation and setting limits to allow glove change when it becomes necessary, prior to glove failure. Analytical pressure decay leak testing allows the detection of material degradation, and in turn the ability to limit operational glove failures. A German based company called MK Versuchsanlagen, e.K., has developed an advanced Glove Integrity Testing System. The system, with its use of proprietary RFID and special software technology, is unique in its capabilities. The system is capable to perform highly accurate regular glove testing on any size glovebox line in minimal time. The system records and can analyze a tremendous amount of system data that in turn can determine, for example, a safe glove change time prior to a glove material failure. This paper will show how an advanced Glove Integrity Testing System can detect glove material degradation and help determine a safe change point prior to glove failure. Pressure decay curves of new gloves and recorded effects of accelerated aging on the glove over time will be shown. The use of this technology in nuclear facilities can greatly improve glovebox operational safety, minimize glovebox glove TRU waste, and save organizations tremendous costs in downtime, clean up, documentation, and potential regulatory review. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High-Entropy Alloy R&D for Accelerator Beam Window Applications

High-Entropy Alloys are a class of novel material that can offer improved resistance to beam-induced radiation damage and thermal shock. Development of these new alloys to serve as beam windows in multi-megawatt accelerator target applications is ongoing at Fermilab. Currently we are investigating AlCoCrMnTiV alloy systems of 4-6 components for service as beam windows; these compositions are predicted by CALPHAD simulation to have a low density and single-phase BCC crystal structure. The microstructures of these systems are being studied by electron microscopy techniques such as energy dispersive X-ray spectroscopy (EDS) to determine elemental homogeneity and composition, electron backscatter diffraction (EBSD) to quantify grain structure and orientation, and transmission electron microscopy (TEM) to observe defect structures and precipitate formation; nanoindentation is used to probe microstructural mechanical properties. Initial bulk property characterization utilizes differential scanning calorimetry to quantify specific heat capacity (cp), dilatometry to determine the coefficient of thermal expansion (CTE), and time-domain thermoreflectance (TDTR) to measure thermal conductivity (K). A miniature tensile testing apparatus is also being developed to test tensile properties. Post-irradiation examination is currently ongoing for several of these compositions that have been irradiated by low-energy ions to damage levels and at a temperature relevant to beam window applications at future next-generation accelerator facilities. This talk will briefly describe the alloy design and synthesis before going into more depth covering microstructural pre-characterization, and post-irradiation examination results from low-energy ion irradiated specimens. This will be followed by the plans for alloy down selection and future prototypic proton irradiations.

43 PARTICLE ACCELERATORS↗

Frost prediction using machine learning and deep neural network models

This study describes accurate, computationally efficient models that can be implemented for practical use in predicting frost events for point-scale agricultural applications. Frost damage in agriculture is a costly burden to farmers and global food security alike. Timely prediction of frost events is important to reduce the cost of agricultural frost damage and traditional numerical weather forecasts are often inaccurate at the field-scale in complex terrain. In this paper, we developed machine learning (ML) algorithms for the prediction of such frost events near Alcalde, NM at the point-scale. ML algorithms investigated include deep neural network, convolution neural networks, and random forest models at lead-times of 6–48 h. Our results show promising accuracy (6-h prediction RMSE = 1.53–1.72°C) for use in frost and minimum temperature prediction applications. Seasonal differences in model predictions resulted in a slight negative bias during Spring and Summer months and a positive bias in Fall and Winter months. Additionally, we tested the model transferability by continuing training and testing using data from sensors at a nearby farm. We calculated the feature importance of the random forest models and were able to determine which parameters provided the models with the most useful information for predictions. We determined that soil temperature is a key parameter in longer term predictions (>24 h), while other temperature related parameters provide the majority of information for shorter term predictions. The model error compared favorable to previous ML based frost studies and outperformed the physically based High Resolution Rapid Refresh forecasting system making our ML-models attractive for deployment toward real-time monitoring of frost events and damage at commercial farming operations.

97 MATHEMATICS AND COMPUTING↗

Thermodynamic assessment of the quaternary WTaCrV refractory high entropy alloy as a means to guide experimental approaches

The deployment of fusion energy poses challenges for materials in plasma facing components to withstand high temperatures and thermal gradients, particle implantation and neutron damage. The current material of choice is tungsten, although property degradation limits its consideration in future fusion reactors. Hence, materials with better resistance to harsh environments need to be developed for fusion energy to become a reality. High entropy alloys are being explored as potential candidates with some compositions showing good radiation resistance to defect cluster formation. One of these materials is the WTaCrV system, although only one composition has been tested under ion irradiation. In this work, we study the thermodynamic properties of the entire quaternary alloy composition range. Coupling first principles calculations, cluster expansion approaches, and Monte Carlo methods, we access the free energy functionals, short-range ordering as a function of temperature, and atomic configurations that can be compared to experimental observations. We use this data to inform experiments into compositions with higher propensity to form solid solutions, instead of phase separating. With this formalism we have developed thermodynamic database (TDB) files that can be used to plot quaternary phase diagrams.

Cluster Expansion↗