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At least 865 records · Page 48

A Unified Testing Platform to Mature Blockchain Applications for Grid Emulation Environments

Blockchain technology is a relatively novel technology that can be used to develop more decentralized, autonomous and tamper-evident solutions. A feature that can aid Transactive Energy Systems to reach their goals by enabling individual actors to communicate and reach consensus with other participants in a more decentralized fashion. However, technical barriers to evaluate and adopt this type of technology within the electrical domain still exist. To facilitate this task, BLOSEM Unified Testing Platform (UTP), a DOE-sponsored, multi-lab effort intends to accelerate the development of solutions by offering a common set of reusable services that can be used to interconnect existent grid tools with blockchain services. UTP is intended to serve as development platform that can provide application engineers with the technical means to evaluate potential blockchain solutions, by enabling them to concentrate on the actual application functionalities while at the same time abstracting the connectivity and performance measurement tasks. The use of BLOSEM UTP is further demonstrated by implementing two potential use cases that are intended to validate both the feasibility of implementing these applications as blockchain-based solutions while also demonstrating the features provided by UTP.

blockchain co-simulation↗

Evaluation of the MARVEL Reactor Inhalation Dose Consequences

A dose consequence analysis was performed to support the preliminary Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort. The purpose of the MARVEL project is to develop a nuclear microreactor applications test bed at Idaho National Laboratory (INL) to perform research and development on various operational features of microreactors to ultimately improve integration of microreactors to end-user applications. The MARVEL concept is a 100 kilowatt (kW) thermal (kWth) and approximately 20-kW electric (kWe) generating microreactor. The MARVEL system will be located in the INL TREAT facility in the north high-bay equipment pit. The analysis considers the bounding release fractions of the MARVEL reactor concept and documents the dose consequences to the public and collocated worker.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

ECAR-5127 Rev 1 Evaluation of the MARVEL Reactor Inhalation Dose Consequences

The following dose consequence analysis is performed to support the preliminary Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort. The purpose of the MARVEL project is to develop a nuclear microreactor applications test bed at Idaho National Laboratory (INL) to perform research and development on various operational features of microreactors to ultimately improve integration of microreactors to end-user applications. The MARVEL concept is a 100 kilowatt (kW) thermal (kWth) and approximately 20-kW electric (kWe) generating microreactor. The MARVEL system will be located in the INL TREAT facility in the north high-bay equipment pit. This ECAR considers the bounding release fractions of the MARVEL reactor concept and documents the dose consequences to the public and collocated worker.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Safety Analysis of FeCrAl Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The U.S. nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. This program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering a second license renewal. The Risk-Informed Systems Analysis Pathway has two main goals: (1) The deployment of methodologies and technologies that enable a better representation of the safety margins and factors that contribute to cost and safety, and (2) The development of advanced applications that enable cost-effective plant operation. As part of this pathway, the Enhanced Resilient Plant project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels, diverse and flexible coping strategies, enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the Enhanced Resilient Plant project is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. This report documents research and development conducted in support of deployment of accident-tolerant fuels. This project performed safety analyses for the steady-state normal operation, anticipated operational occurrences, and design-basis accidents of a representative four-loop pressurized water reactor model with Zr and FeCrAl accident-tolerant fuel clad with higher enrichment and burnup supporting plant refueling cycles of 18 and 24 months. The source terms and environmental impacts were studied for a large-break loss of coolant accident, including uncertainty analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Transverse mode analysis for free-space laser beams using Bayesian analysis

Reliable and rapid assessment of the transverse mode quality of a free-space laser beam has a wide range of applications in laser development, research, and utilization. It has become even more important with recent advances in developing orbital angular momentum photon beams across a broad spectral region. In this work, a general modal analysis method for a free-space multimode laser beam has been developed based on Bayesian analysis. After transforming mode decomposition into a linear system problem, a Gaussian probabilistic model is used to find a closed-form solution. The method is found to be robust with the presence of Gaussian noise. Prior knowledge about the mode content can be incorporated into the method to improve the solution for situations when coherent disturbances or contamination are present in the laser beam. This method can be used to analyze the mode content for laser beams in different bases, such as Hermite–Gaussian (HG) modes and Laguerre–Gaussian (LG) modes. Three applications of this method are presented: a detailed modal analysis of the beam image from the incoherent intensity addition of HG modes and two examples of mode decomposition using the complex wavefront from the coherent superposition of HG and LG modes. The feasibility of this method is demonstrated using various simulation results. Based on digital images of a laser beam recorded without complex wavelength-limiting optics, in principle, this method can be used in a wide wavelength range from infrared to ultraviolet, and possibly x ray.

Liu, Peifan (ORCID:0000000273816153)↗

Risk-Informed ATF and FLEX Analysis for an Enhanced Resilient BWR Under Design-Basis and Beyond-Design-Basis Accidents

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.

99 GENERAL AND MISCELLANEOUS↗

PROCESS-STRUCTURE-PROPERTY RELATIONSHIPS IN LASER POWDER BED FUSION PRODUCED 17-4 PH STEEL

Laser powder bed fusion (LPBF) is a metal additive manufacturing method that produces non-traditional microstructures as a result of the rapid solidification and thermal cycling inherent to the process. When using LPBF-produced material in application, these unique microstructures challenge the applicability of well developed mechanical property databases achieved by conventional heat treatments. For wider adoption of this technology, a more holistic understanding is necessary on how process attributes develop material structure, which dictate mechanical properties. This dissertation explores the process– structure–property relationships in LPBF 17-4 PH steel through systematic evaluation of atmospheric processing and heat treatment effects on microstructure and mechanical performance. Specimens were fabricated under controlled build environments, subjected to a range of solutionizing, homogenizing, and aging treatments, and characterized using optical microscopy, electron back scatter diffraction (EBSD), and X-ray diffraction (XRD) to quantify phase evolution. Tensile testing was performed to directly link heat treatment pathway and nitrogen absorption to mechanical performance. This work demonstrates where conventional heat treatment standards are applicable to LPBF 17-4 PH steel and where modifications are required. By directly correlating phase stability, nitrogen effects, and tensile response, this work provides practical guidelines for tailoring post-processing strategies. These findings underscore that successful application of LPBF 17-4 PH steel requires explicit consideration of both build environment and post-processing. By linking processing conditions to microstructure and performance, this work advances understanding of critical variables that govern reliability of additively manufactured precipitation-hardened stainless steels in demanding applications.

Brown, Benjamin [Kansas City National Security Cam↗

Semicomputational calculation of Bragg shift in stratified materials

The fiber Bragg grating (FBG) may be viewed as a one dimensional photonic band-gap crystal by virtue of the periodic spatial perturbation imposed on the fiber core dielectric material. Similar to media supporting Bloch waves, the engraved weak index modulation, presenting a periodic “potential” to an incoming guided mode photon of the fiber, yields useful spectral properties that have been the basis for sensing applications and emerging quantum squeezing and solitons. The response of an FBG sensor to arbitrary external stimuli represents a multiphysics problem without a known analytical solution despite the growing use of FBGs in classical and quantum sensing and metrology. Here, we study this problem by first presenting a solid mechanics model for the thermal and elastic states of a stratified material. Additionally, the model considers an embedded optical material domain that represents the Bragg grating, here in the form of an FBG. Using the output of this model, we then compute the optical modes and their temperature- and stress-induced behavior. The developed model is applicable to media of arbitrary shape and composition, including soft matter and materials with nonlinear elasticity and geometric nonlinearity. Finally, we employ the computed surface stress and temperature distributions along the grating to analytically calculate the Bragg shift, which is found to be in reasonable agreement with our experimental measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Role of Polycyclic Aromatic Alkylammonium Cations in Tuning the Electronic Properties and Band Alignment of Two-Dimensional Hybrid Perovskite Semiconductors

Two-dimensional hybrid organic–inorganic perovskites (HOIPs) have recently drawn intense attention as potential photovoltaic materials. However, n = 1 two-dimensional (2D) HOIPs face the challenge of low conductivity between the inorganic layers, leading to unsatisfactory device performance. Interestingly, 2D HOIPs employing π-conjugated molecules as organic moieties show energy and charge transfers between organic and inorganic layers, indicating potentially efficient carrier transport for photovoltaic applications. Nevertheless, the development of 2D HOIP-based solar cells especially utilizing polycyclic aromatic alkylammonium as cations is in its infancy. Herein, we investigated the electronic structure and band alignment of a series of n = 1 2D Ruddlesden–Popper (RP) phase HOIPs containing different polycyclic aromatic groups and alkyl chains, based on density functional theory calculations. We find that the polycyclic aromatic group plays an important role in controlling the functionality of 2D HOIPs by directly modifying band-edge states, and the band alignment at the organic–inorganic interface can be designed to promote either exciton trapping or dissociation for light-emitting or photovoltaic applications, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Risk-Informed Analysis for Enhanced Resilient Nuclear Power Plant with Initiatives including ATF, FLEX, and Advanced Battery Technology

This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2021 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed Systems Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, the incorporation of augmented or new passive cooling systems, the advanced battery technology with extended capacity, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors? safety features and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. The ERP R&D efforts in FY 2021 are focused on three industry initiatives, including accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), and advanced battery technology with extended capacity.

99 GENERAL AND MISCELLANEOUS↗

A Quantum-Inspired Tensor Network Algorithm for Constrained Combinatorial Optimization Problems

Combinatorial optimization is of general interest for both theoretical study and real-world applications. Fast-developing quantum algorithms provide a different perspective on solving combinatorial optimization problems. In this paper, we propose a quantum-inspired tensor-network-based algorithm for general locally constrained combinatorial optimization problems. Our algorithm constructs a Hamiltonian for the problem of interest, effectively mapping it to a quantum problem, then encodes the constraints directly into a tensor network state and solves the optimal solution by evolving the system to the ground state of the Hamiltonian. We demonstrate our algorithm with the open-pit mining problem, which results in a quadratic asymptotic time complexity. Our numerical results show the effectiveness of this construction and potential applications in further studies for general combinatorial optimization problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Machine learning models for rat multigeneration reproductive toxicity prediction

Reproductive toxicity is one of the prominent endpoints in the risk assessment of environmental and industrial chemicals. Due to the complexity of the reproductive system, traditional reproductive toxicity testing in animals, especially guideline multigeneration reproductive toxicity studies, take a long time and are expensive. Therefore, machine learning, as a promising alternative approach, should be considered when evaluating the reproductive toxicity of chemicals. We curated rat multigeneration reproductive toxicity testing data of 275 chemicals from ToxRefDB (Toxicity Reference Database) and developed predictive models using seven machine learning algorithms (decision tree, decision forest, random forest, k-nearest neighbors, support vector machine, linear discriminant analysis, and logistic regression). A consensus model was built based on the seven individual models. An external validation set was curated from the COSMOS database and the literature. The performances of individual and consensus models were evaluated using 500 iterations of 5-fold cross-validations and the external validation data set. The balanced accuracy of the models ranged from 58% to 65% in the 5-fold cross-validations and 45%–61% in the external validations. Prediction confidence analysis was conducted to provide additional information for more appropriate applications of the developed models. The impact of our findings is in increasing confidence in machine learning models. We demonstrate the importance of using consensus models for harnessing the benefits of multiple machine learning models (i.e., using redundant systems to check validity of outcomes). While we continue to build upon the models to better characterize weak toxicants, there is current utility in saving resources by being able to screen out strong reproductive toxicants before investing in vivo testing. The modeling approach (machine learning models) is offered for assessing the rat multigeneration reproductive toxicity of chemicals. Our results suggest that machine learning may be a promising alternative approach to evaluate the potential reproductive toxicity of chemicals.

consensus model↗

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Robustness and printed sensor qualification

A limiting factor of additive manufactured (AM) sensors for in-pile applications is the development of appropriate interconnection and packaging strategies that can maintain reliable performance in extreme environments. Failure mechanisms in these harsh conditions could include, but not limited to, materials interaction (i.e., intermetallic formation) and coefficient of thermal expansion (CTE) mismatch between the individual components of the sensors. To mitigate premature failure and enable the successful sustained operation of AM sensors, non-destructive qualification tests are used as an intermediate process control step used for verifying robustness and reliability of the sensor before they are deployed. A materials system of interest is the use of barium strontium titanium oxide (BST) films on stainless steel 316L (SS316L) substrate. Due to BST’s high dielectric constant and tunable dielectric properties, there is an interest for its application as an insulation/encapsulation layer for capacitive strain gauges when printed on structural materials. Previous work on the BST/SS316L material system, however, showed that the BST cracks when exposed to temperatures up to 600 °C due to CTE mismatch between the printed BST film and the metallic substrate. When comparing different fabrication techniques, less surface cracking was observed in the samples that deposited thinner (i.e., 2-20 μm) than samples that were thicker (i.e., 135 µm – 300 µm). The objective of this report is to establish a qualification process that will determine and address any challenges (i.e., mechanical failure of thick prints) of the AM sensor prior to its application in experimental tests. To demonstrate the qualification process in this report, laser spallation and uniaxial tensile tests using dynamic and quasi-static loading, respectively, will be discussed.

36 - MATERIALS SCIENCE↗

Diffusion bonded compact heat exchanger in Inconel 740H for high temperature and high-pressure applications

It is desired to develop heat exchangers able to be operated at high temperatures (750°C) and pressures (3636 psi) for use in advanced Brayton power cycle. Conventional materials have not had the high strength at temperature required for these applications previously, however a fairly new material Inconel 740H developed by Special Metals for the ultra-supercritical water fossil industry has shown good performance under these conditions. In further efforts to capitalize on these new high strength high temperature alloys CompRex has developed a diffusion bonding procedure capable of alloying compact high effectiveness heat exchangers that can perform under these high temperature and high-pressure conditions. Initial tests of the heat exchanger are being conducted at the University of Wisconsin using supercritical CO2 working fluid. The bonding process has been adjusted such that the strength of the bonded block has achieved over 90% yield and tensile strength of the 740H base material values. Grain size before and after bonding were measured to determine the extent of grain growth and grain diffusion across the interface. A discussion of the heat exchanger design, etching and initial tensile tests on sample bonds will be discussed.

14 SOLAR ENERGY↗

Diffusion bonded compact heat exchanger in Inconel 740H for high temperature and high-pressure applications

It is desired to develop heat exchangers able to be operated at high temperatures (750˚C) and pressures (3636 psi) for use in advanced Brayton power cycle. Conventional materials have not had the high strength at temperature required for these applications previously, however a fairly new material Inconel 740H developed by Special Metals for the ultra-supercritical water fossil industry has shown good performance under these conditions. In further efforts to capitalize on these new high strength high temperature alloys CompRex has developed a diffusion bonding procedure capable of alloying compact high effectiveness heat exchangers that can perform under these high temperature and high-pressure conditions. Initial tests of the heat exchanger are being conducted at the University of Wisconsin using supercritical CO2 working fluid. The bonding process has been adjusted such that the strength of the bonded block has achieved over 90% yield and tensile strength of the 740H base material values. Grain size before and after bonding were measured to determine the extent of grain growth and grain diffusion across the interface. A discussion of the heat exchanger design, etching and initial tensile tests on sample bonds will be discussed.

14 SOLAR ENERGY↗

Bioelectrochemical reactor to manage anthropogenic sulfate pollution for freshwater ecosystems: Mathematical modeling and experimental validation

Anthropogenic sulfate loading into otherwise low-sulfate freshwater systems can cause significant ecological consequences as a biogeochemical stressor. To address this challenge, in situ bioremediation technologies have been developed to leverage naturally occurring microorganisms that transform sulfate into sulfide rather than implementing resource-intensive physio-chemical processes. However, bioremediation technologies often require the supply of electron donors to facilitate biological sulfate reduction. Bioelectrochemical systems (BES) can be an alternative approach for supplying molecular hydrogen as an electron donor for sulfate-reducing bacteria through water electrolysis. Although the fundamental mechanisms behind BESs have been studied, limited research has evaluated the design and operational parameters of treatment systems when developing BESs on a scale relevant to environmental systems. Further, this study aimed to develop an application-based mathematical model to evaluate the performance of BESs across a range of reactor configurations and operational modes. The model was based on sulfate transformation by hydrogenotrophic sulfate-reducing bacteria coupled with the recovery of solid iron sulfide species formed by the oxidative dissolution of dissolved ferrous iron from a stainless steel anode. Sulfate removal closely corresponded to the rate of electrolytic hydrogen production and hydraulic residence time but was less sensitive to specific microbial rate constants. The mathematical model results were compared to experimental data from a pilot-scale BES tested with nonacidic mine drainage as a case study. The close agreement between the mathematical model and the pilot-scale BES experiment highlights the efficacy of using a mathematical model as a tool to develop a conceptual design of a scaled-up treatment system.

54 ENVIRONMENTAL SCIENCES↗

Effect of Al substitution on the magnetocaloric properties of Ni-Co-Mn-Sn multifunctional alloys

Ni-Mn-based metamagnetic shape memory alloys have been extensively studied due to their multifunctional properties including magnetocaloric effect (MCE), magnetoresistance effect, and magnetic-field-induced strain. However, the large intrinsic thermal hysteresis of these alloys sets a limit on further development for practical applications. Here, with a few atomic percent Al substitution, we greatly reduced the thermal hysteresis and transformation temperature interval while maintaining the large magnetization difference (ΔM) between austenite and martensite. The simultaneous achievement of a large ΔM and low thermal hysteresis leads to a remarkable enhancement in MCE upon Al substitution, and a maximum magnetic entropy change of 31.6 J/kg K is achieved under a field of 5 T in Ni 39 Co 11 Mn 40 Sn 8 Al 2 . Furthermore, our in situ high-energy X-ray diffraction experiments show that the Ni 39 Co 11 Mn 40 Sn 8 Al 2 has good geometric compatibility between austenite and martensite, which accounts for the reduced thermal hysteresis in this alloy. This study is instructive for the development of high-performance magnetocaloric materials in the metamagnetic shape memory alloys.

36 MATERIALS SCIENCE↗