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At least 937 records · Page 52

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DOE OSTI2021

Transient testing of uranium silicide fuel in zircaloy and silicon carbide cladding

Using the newly restarted Transient Reactor Test (TREAT) facility at Idaho National Laboratories, fresh (unirradiated) U 3 Si 2 fuel pellets were tested under reactivity-initiated accident conditions in dry helium capsules. These tests were performed with total energy depositions sufficient to induce melting of the U 3 Si 2 fuel pellets based on available thermophysical property data. The instrumented experiments utilized in-pile thermocouples and infrared pyrometers to measure the cladding temperature during the transient, which are in reasonable agreement with predicted peak cladding temperatures using a simple BISON fuel performance model. This same model is then used to predict expected cladding stresses during the transients in areas where pellet cladding interaction is expected. It was shown that for transient energy depositions up to 528J/g rod like geometry of the test articles was maintained. While it is acknowledged that more confirmatory testing is required in more prototypic environments, these first of their kind experiments have demonstrated that unirradiated U 3 Si 2 fuel and unirradiated SiC-SiC claddings can likely retain a “rod like” geometry for transient energy depositions up to 528J/g.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Development of Lattice-Mismatched GaInAsP for Radiation Hardness

We develop lattice-mismatched GaInAsP as an alternative alloy to pure As-based alloys currently used in III-V multijunction solar cells. Increasing the alloy phosphorous and indium content while maintaining an optimal bandgap may allow high efficiency multijunction devices with increased radiation hardness. Here, 1.0-eV GaInAsP is developed and implemented into single and multijunction solar cell devices. The lattice-mismatched GaInAsP must be grown strain free, and the subcell thickness must be maintained below the thickness where surface-driven phase separation occurs. As observed in transmission electron microscopy and cathodoluminescence imaging, phase separation strengthens in the GaInAsP layer and leads to interfacial defect formation when the cell thickness is too great. We show single junction 1.0-eV Ga 0.5 In 0.5 As 0.7 P 0.3 with excellent carrier collection and a bandgap-voltage offset of 0.40 V. This material quality approaches that of 1.0-eV Ga 0.7 In 0.3 As used in inverted metamorphic multijunction devices, but has increased phosphorus content and consequently is expected to have a higher radiation resistance. We incorporate the 1.0-eV GaInAsP subcell into a 3-junction inverted metamorphic solar cell to test the performance of the subcell in a multijunction. No additional loss is observed upon integration into a multijunction cell: both the carrier collection and voltage of the GaInAsP subcell are unchanged from single junction devices. While further materials development and radiation testing is still required, these preliminary results indicate that lattice-mismatched GaInAsP can be effectively used in multijunction solar cells to replace radiation-soft materials.

14 SOLAR ENERGY↗

DOE OSTI2020

Comparison of Fission Product Release Predictions using PARFUME with Results from the AGR-2 Irradiation Experiment

The PARFUME (PARticle FUel ModEl) code was used to predict fission product release from tristructural isotropic (TRISO) coated fuel particles and compacts during the second irradiation experiment (AGR-2) of the Advanced Gas Reactor Fuel Development and Qualification Program. The PARFUME model for the Advanced Gas reactor (AGR)GR-2 experiment used the fuel compact volume average temperature for each of the 560 days of irradiation to calculate the release of fission products of silver, cesium, and strontium from a representative particle for a select number of AGR -2 compacts. In addition, safety tests were performed on 15 compacts ranging from 1500 to 1800°C to determine fission product release at temperatures that bound reactor accident conditions. PARFUME was used to calculate the fission product release of silver, cesium, strontium, and krypton during these safety tests. Post-irradiation examination (PIE) measurements provided the data on release of fission products from the fuel compacts and fuel particles, and retention of fission products in the compacts outside the silicon carbide (SiC) layer. The predicted fraction release from PARFUME was then compared to PIE measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Next-generation anion exchange membrane water electrolyzers operating for commercially relevant lifetimes

Alkaline anion exchange membrane (AEM) water electrolysis has gained increasing attention due to its potential to achieve low-cost, high performance hydrogen production. However, most existing membranes are not durable in industrial settings. In this work, we demonstrate good performance relative to industrial parameters using Sustainion® anion exchange membranes. Long-duration tests showed stable performance of 1 A/cm 2 at 1.85 V with a degradation rate of less than 1 μV/h over 10,000 h. The projected lifetime is thus over 20 years. Daily on/off cycling performance over the course of 30 years was simulated experimentally through accelerated voltage shock tests, resulting in a performance loss of only 0.15 μV/cycle over 11,000 cycles. As shown through impact and crossover testing, an improvement in performance is achieved by the addition of zirconia to the polymer matrix and mechanically reinforcing the membrane.

08 HYDROGEN↗

DOE OSTI2024

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗

DOE OSTI2022

Antioxidant Activity, Microbiological Quality, and Acceptability of Spontaneously Fermented Shrimp Sausage (Litopenaeus vannamei)

Fermented shrimp sausages are prepared spontaneously with Litopenaeus vannamei as raw material. Shrimp is one of the marine sources with rich chitosan as bioactive compounds, antioxidants, vitamin E, and probiotic lactic acid bacteria (LAB) produced by fermentation processes. This study aimed to analyze the variations in antioxidant activity, vitamin E content, total LAB, total pathogenic bacteria, pH, and acceptability of shrimp sausage produced at different fermentation times. A completely randomized experimental design study was performed using four levels of exposure time, including control (0 days), 1, 2, and 3 days. The treatment was conducted spontaneously with 1.2% salt concentration, a drying temperature of 50°C for 3 h, and fermentation at 35°C. The evaluated parameters included the antioxidant activity measured with the radical 2,2-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) method, vitamin E levels by high-performance liquid chromatography, total LAB with total plate count, and Escherichia coli bacteria by the most probable number method. Salmonella sp. and Staphylococcus aureus were estimated by the identification method. A pH meter was used to assess acidity, and hedonic organoleptic testing was performed for taste, aroma, color, and texture. The results show significant differences in antioxidant activity, vitamin E, and shrimp sausage acceptability at varied fermentation times p ≤ 0.05 . However, the best formulation was obtained with the first-day fermented shrimp sausage, as shown by its bioactive content and the level of acceptability.

Afifah, Diana N.↗

DOE OSTI2022

3D Simulations of gas injection on callovo-oxfordian claystone assuming spatial heterogeneity and anisotropy

A series of gas injection tests on Callovo-Oxfordian (COx) claystone from the Bure underground research laboratory (URL) in France were carried out at the British Geological Survey (BGS). The tests were performed using a triaxial apparatus specifically designed to capture small volumetric strains induced by the injected gas flow and consequent material dilatancy. The long-duration experiments were monitored throughout. Measurements also included pressure, stresses (axial and radial stresses prescribed for each test stage), rate of gas inflow, gas outflow volume as well as pore-pressures observed at various points of the sample. A coupled hydro-gas-mechanical 3D numerical model has been developed to simulate the tests. Initial permeability is assumed heterogeneous throughout the specimen and embedded fractures are incorporated in the formulation. Gas pressure-induced deformations during the test lead to variations of permeability due to changes in matrix porosity and, especially, fracture aperture as well as fracture orientation due to material anisotropy. A programme of sensitivity analyses involving the variation of different aspects and parameters of the model contributes to a better understanding of the phenomena and highlights its complexity. The model is able to reproduce the observed behaviour of the tests.

58 GEOSCIENCES↗

DOE OSTI2020

Local Truncation Error-Informed Code Verification

The method of manufactured solutions (MMS) has become increasingly popular in conducting code verification studies on predictive codes, such as nuclear power system codes and computational fluid dynamic codes. The reason for the popularity of this approach is that it can be used when an analytical solution is not available. Using MMS, code developers are able to verify that their code is free of coding errors that impact the observed order of accuracy. While MMS is still an excellent tool for code verification, it does not identify coding errors that are of the same order as the numerical method. This paper presents a method that combines MMS with modified equation analysis (MEA), which calculates the local truncation error (LTE) to identify coding error up to and including the order of the numerical method. This method is referred to as modified equation analysis methd of manufactured solutions (MEAMMS). MEAMMS is then applied to a custom-built code, which solves the shallow water equations, to test the performance of the code verification method. MEAMMS is able to detect all coding errors that impact the implementation of the numerical scheme. To show how MEAMMS is different than MMS, they are both applied to the same first-order numerical method test problem with a first-order coding error. When there are first-order coding errors, only MEAMMS is able to identify them. Finally, this shows that MEAMMS is able to identify a larger set of coding errors while still being able to identify the coding errors MMS is able to identify.

42 ENGINEERING↗

DOE OSTI2025

Demonstration of Electroreduction Technology to Convert GNF Uranium Oxide Powder to Metal

Global Nuclear Fuel – Americas LLC (GNF) has partnered with Argonne National Laboratory to demonstrate electroreduction of uranium oxides produced by deconversion of UF 6 to uranium metal through the Gateway for Accelerated Innovation in Nuclear (GAIN) program under the U.S. Department of Energy to accelerate the domestic production of metallic advanced reactor fuels. Electroreduction of uranium oxide was first demonstrated and patented by Argonne in the early 2000s as a technology to convert used oxide nuclear fuel from light water reactors to metal for further fuel reprocessing. More recently, electroreduction has been proposed as a front-end technology for metallization of uranium oxides produced by deconversion of UF 6 and for scrap recovery of oxide materials. During the electroreduction process, UO 2 powder is contained in a stainless-steel mesh basket with a cathode lead located in the center of the UO 2 bed. The basket is immersed in lithium chloride molten salt electrolyte containing 1 wt% lithium oxide along with a platinum anode and a nickel/nickel oxide (Ni/NiO) reference electrode. Current is applied to the cell between the cathode and anode to reduce the UO 2 to metallic uranium via a solid-state reduction reaction. Oxide ions released from the UO 2 during reduction are transported through the salt to the anode where oxygen gas is evolved. Once reduction is complete, the basket containing the metallicized uranium is removed from the salt and can be processed to remove the salt and consolidate the uranium into an ingot for use in metallic fuel fabrication. This project was performed to provide evidence of the electroreduction technology readiness level for metallization of UO 2 powder, identify and retire technical risks for industrialization of electroreduction, and accelerate the path to commercialization for metallic fast reactor fuel production. To that end, five electroreduction tests were performed with UO 2 provided by GNF and the resulting product was analyzed for the extent of conversion to metal and for impurity contents of the metal product to verify that electroreduction does not introduce impurities that would prevent use of the product in metallic fuel fabrication.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Evolving Ensembles of Spiking Neural Networks for Neuromorphic Systems

Evolutionary algorithms have been proposed as a solution to overcome many of the challenges associated with training spiking neural networks. While evolutionary optimization for spiking neural networks is very flexible, its performance has difficulty scaling to complex tasks and correspondingly complex network structures. Here we propose a method for evolving ensembles of spiking neural networks. By using ensemble learning, the flexibility of evolutionary optimization is fully preserved while scaling to more challenging tasks. We test the performance of the proposed method using handwritten digit classification. We investigate multiple strategies for constructing ensembles of spiking neural networks, and demonstrate that evolving ensembles of SNNs offers significant performance advantages over evolutionary optimization.

Elbrecht, Daniel↗

DOE OSTI2022

Combined TREAT-LOC & SATS Integral LOCA Experiment Plan

The Transient Reactor Test Facility (TREAT) loss-of-coolant (LOC) and highburnup (HBu) experiment series, along with the Severe Accident Test Station (SATS) HBu experiment series, are integral LOC accident (LOCA) experiments planned under the Department of Energy (DOE) Advanced Fuels Campaign (AFC) program, which aims to support burnup extension needs by addressing identified R&D priorities in order to achieve an improved understanding of fuel fragmentation, relocation, and dispersal (FFRD) of HBu fuel during LOCA events. Priorities have been identified by the Electric Power Research Institute (EPRI)’s Collaborative Research on Advanced Fuel Technologies (CRAFT) Fuel Performance and Testing Technical Experts Group (FPTTEG). The data produced under this plan will be used to further validate and confirm existing models and inform future R&D and model development. The experimental program was specifically developed to address data gaps and opportunities identified via detailed review of the existing public knowledge base on LOCA FFRD, as well as reviewing specific experimental development activities regarding prototypic LOCA conditions for light-water reactor (LWR) systems. The test program relies on a unique combination of in- and out-of-pile experimental approaches to provide a clear tieback to the existing integral and semi-integral LOCA experiment database, using state-of-the-art facilities. More importantly, the program will systematically investigate the impacts of prototypic HBu fuel/cladding thermomechanical behaviors under postulated LWR LOCA conditions not yet fully investigated. These conditions correspond with prototypic decay-energy heatup (DEH) and stored-energy heatup (SEH) conditions. First, TREAT’s unique capability will enable the first evaluation of the impact of SEH conditions on HBu fuels. The test program will emphasize the development of an improved mechanistic understanding of key phenomena through independent experimental systems, development of a database to support fuel performance modeling tools, world-leading advanced materials characterization, and the most advanced approach to in situ diagnostics ever deployed to evaluate FFRD. The results will represent a significant leap forward in evaluating prototypic conditions and novel data to support modeling development and validation, as well as to inform the technical basis for LOCA-induced FFRD.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface

Abstract Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented with embedded physics and a technique known as algorithmic differentiation. We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g., permeability or P-wave velocity), that embeds physical knowledge of the subsurface properties into inverse analysis and improves its performance. We tested the application of this approach on four geologic problems: two heterogeneous hydraulic conductivity fields, a hydraulic fracture network, and a seismic inversion for P-wave velocity. This physics-embedded inverse analysis approach consistently characterizes these geological problems accurately. Furthermore, the excellent performance in matching the observational data demonstrates the reliability of the proposed method. Moreover, the application of algorithmic differentiation makes this an easy and fast approach to inverse analysis when dealing with complicated geological structures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Modeling of gap conductance for LWR fuel rods applied in the BISON code

A new gap conductance model is proposed in this study as a combination of Toptan’s model and the Ross-Stoute model. A variance-based sensitivity analysis is performed to understand how simulation results depend on all input parameters of the proposed model. Additionally, new modeling options (e.g. fill gas thermal conductivity, temperature jump distance, thermal accommodation coefficient, etc.) are added into the nuclear fuel performance code, BISON. The need for further investigation of the gap heat transfer between fuel and cladding in BISON motivated this study to evaluate its impact on the code’s predictions. New gap conductance modeling is proposed. A series of integral-effects validation tests is performed: (1) to demonstrate the impact of the proposed model on the code’s fuel temperature predictions at the beginning of life and through the reactor’s life; (2) to ensure that the proposed model is capable of accurately modeling gap heat transfer characteristics in real-world problems; and (3) to investigate the impact of the estimation of fission gas release on the fuel temperature predictions with the proposed model. Overall, the results indicate that the proposed gap conductance model improves BISON’s predictions.

42 ENGINEERING↗

DOE OSTI2024

AdvEP

AdvEP is a code repository which contains PyTorch implementations of various adversarial attacks on a deep neural network trained with Equilibrium Propagation (EP), which is a neuromorphic learning framework. AdvEP allows for the training, testing, and conducting white/black-box attacks of EP models on a wide variety of applications and datasets. AdvEP is based on the open-source code https://github.com/Laborieux-Axel/Equilibrium-Propagation which was developed to train energy models. AdvEP was created by modifying the original code to perform and test against adversarial attacks. AdvEP was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. AdvEP interfaces heavily with the open-source PyTorch Python package as well as the open-source Adversarial Robustness Toolbox (ART) package.

Mansingh, Siddarth↗

DOE OSTI2022

Impulse Noise Sampling at 9965 - Armag

One detonation test was monitored for impulse noise at Thunder Range on November 6, 2020. The TNT equivalency for this shot was 100 lbs. Ground zero for this test was located at an open area of Range 7. The Armag, where MOW were remotely located, was just south of the east end of the TR shock tube The purpose of this sampling event was to characterize the noise attenuation provided by the Armag which will be used as the primary firing location in a future test series. To determine attenuation provided by the Armag, one sound level monitor was placed inside and a second monitor was placed outside the hardened structure at the same distance from ground zero. The Armag was located 1300 feet from ground zero. Essential personnel performing these tests were remotely located inside the Armag and wore hearing protection with a minimum NRR of 23. Members of the Workforce (MOW) who are exposed to noise levels above 140 dBC, regardless of hearing protection worn, are required to be enrolled into the SNL Hearing Conservation Program which includes audiometric testing, online training (HCP100) and wearing hearing protection.

42 ENGINEERING↗

DOE OSTI2021

Experimental and computational analysis of bending fatigue failure in chopped carbon fiber chip reinforced composites

With a better balance among good mechanical performance, high freedom of design, and low material and manufacturing cost, chopped carbon fiber chip reinforced sheet molding compound (SMC) composites show great potential in different engineering applications. Here in this paper, bending fatigue behaviors of SMC composites considering the heterogeneous fiber orientation distributions have been thoroughly investigated utilizing both experimental and computational methods. First, four-point bending fatigue tests are performed with designed SMC composites, and the local modulus is adopted as a metric to represent the local fiber orientation of two opposing sides. Interestingly, SMC composites with and without large discrepancy in local modulus of opposing sides show different fatigue behaviors. Interrupted tests are conducted to explore the bending fatigue failure mechanism, and the damage processes of valid specimens are also closely examined. We find that the fatigue failure of SMC composites under four-point bending is governed by crack propagation instead of crack initiation. Because of this, the heterogeneous local fiber orientations of both sides of the specimen influence fatigue life. The microstructure of the lower side shows a direct influence while that of the upper side also exhibiting influence which becomes more prominent for high cycle fatigue cases. Furthermore, a hybrid micro–macro computational model is proposed to efficiently study the cyclic bending behavior of SMC composites. The region of interest is reconstructed with a modified random sequential absorption algorithm to conserve all the microstructural details including the heterogeneous fiber orientation, while the rest of the regions are modeled as homogenized macro-scale continua. Combined with a framework to capture the progressive fatigue damage under cyclic bending, the bending fatigue behaviors of SMC composites are accurately captured by the hybrid computational model comparing with our experimental analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A Moving Embedded Boundary Approach for the Compressible Navier-Stokes Equations in a Block-Structured Adaptive Refinement Framework

A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.

adaptive refinement↗

DOE OSTI2021

Surfactant-Aided Low-Salinity Waterflooding for Low-Temperature Carbonate Reservoirs

Carbonate reservoirs tend to be oil-wet/mixed-wet and heterogeneous because of mineralogy and diagenesis. The objective of this study is to improve oil recovery in low-temperature dolomite reservoirs using low-salinity and surfactant-aided spontaneous imbibition. The low-salinity brine composition was optimized using ζ-potential measurements, contact-angle (CA) experiments, and a novel wettability-alteration measure. Significant wettability alteration was observed on dolomite rocks at a salinity of 2,500 ppm. We evaluated 37 surfactants by performing CA, interfacial-tension (IFT), and spontaneous-imbibition experiments. Here, three (quaternary ammonium) cationic and one (sulfonate) anionic surfactants showed significant wettability alteration and produced 43–63% of original oil in place (OOIP) by spontaneous imbibition. At a low temperature (35°C), oil recovery by low-salinity effect is small compared with that by wettability-altering surfactants. Coreflood tests were performed with a selected low-salinity cationic surfactant solution. A novel coreflood was proposed that modeled heterogeneity and dynamic imbibition into low-permeability regions. The results of the “heterogeneous” coreflood were consistent with that of spontaneous-imbibition tests. These experiments demonstrated that a combination of low-salinity brine and surfactants can make originally oil-wet dolomite rocks more water-wet and improve oil recovery from regions bypassed by waterflood at a low temperature of 35°C.

02 PETROLEUM↗