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At least 1,045 records · Page 58

Understanding Costs Associated with Wind Energy Opposition and Stakeholder Engagement

Wind energy social science research historically focused on the social acceptance of wind energy development. Research in this field is robust, and scholars have identified drivers influencing attitudes and acceptance. The criteria defining the opposition of wind energy, and their costs, although related, are less well understood. This gap in research includes the costs of delayed and failed projects to communities and developers. The International Energy Agency (IEA) Wind Task 28 - The Social Science of Wind Energy Acceptance outlined a work package to help answer that question. The first deliverable for IEA Wind Task 28, Work Package 2, was an annotated bibliography that identified key pieces of literature that quantify the costs of opposition to wind projects. Although there is a robust wind social acceptance literature, our efforts highlighted that there has been little research directly quantifying the cost of opposition, engagement, delays, and failures. To directly summarize the appropriate literature and provide context for potential future work, the literature review ranged from directly relevant articles to works providing context and valuable information for our research objective in the future. This associated deliverable, a briefing document summarizing the outcomes of our literature search, is meant to guide future research on opposition to wind energy for IEA Task 28 and beyond.

opposition↗

Use of Systems Engineering in Repurposing Coal-Fired Power Plants with Malta Pumped Thermal Energy Storage System

he electric sector across North America is facing a transition. Both economics and policy decisions have pointed towards a broad retirement of fossil assets across markets. Owners are facing the problem of how to evolve the base of the electric sector from fossil asset to greener alternative. Coal-fired power plants built the modern electricity grid. Their rotating machinery are the beating heart of the grid, providing essential resiliency and reliability services. Power plant retirements are disruptive to plant workforces and cause outsized impacts on surrounding communities. The transition from thermal power plants that use rotating machinery to generate electricity (e.g., coal- and gas-fired plants) to variable, inverter-based generation (e.g., solar and wind) is affecting the reliability of the electric grid. Grid operators and national regulators have issued warnings about known and anticipated risk. In 2021, Malta Inc. was awarded a Department of Energy (DOE) grant to study how to integrate a Malta 100MW Pumped Heat Energy Storage (PHES) system with a retiring coal-fired power plant to meet emissions requirements, retain plant workforces, preserve communities, and maintain grid reliability. This presentation provides a summary of this study, focusing on how systems engineering approach was used to arrive at a proposed design concept that met multiple objectives and requirements. There will be three main parts for this presentation. The first part of the presentation will focus on how different systems engineering was applied for this work. In particular, the following areas: stakeholder engagement, site selection process, developing requirements and use cases for the integrated system, defining the system and its boundary, coming up with different system architecture/option, performing a techno-economic analysis to compare the different options and down selection of the preferred option, will be discusses. For these areas, discussion on the decisions on how much breadth and depth to go into each area will be provided. These discussions provide good insights into how to apply systems engineering. The second part of the presentation will provide a deeper dive into the two recommended integration options that repurpose coal-fired power plants with Malta PHES system. The comparison of the two options and general guidance of how to choose an option will be provided. This is particularly useful for utilities who are facing coal-plant retirements. The two options will be compared based on its performance (such as power output, efficiency), complexity, and cost. The social impact on local communities of the two options will also be discussed. The final part of the presentation will discuss the impact that this work has had, including Malta Inc. being invited to the White House to discuss progress and outcomes of this work with the Interagency Working Group on Coal and Power Plant Communities and Economic Revitalization. In summary, this presentation aims to provide a showcase of how sy

25 ENERGY STORAGE↗

Uncertainty Quantification in High-Low Dynamic System Coupling using RAVEN and TRANSFORM

This work demonstrates new functionality and applications stemming from the development of high-fidelity to low-fidelity (high-low) coupling for system simulations and to further explore the capabilities of the Risk Analysis Virtual Environment (RAVEN) in the performance of uncertainty quantification in this kind of high-low coupled system models. The work builds from previous work on high-low coupling that utilized COBRA-TF (CTF), the high-fidelity subchannel analysis code, with a low fidelity model built in ORNL’s TRANSFORM, the system analysis code, utilizing the Functional Mock-Up Interface (FMI). Steady-state and transient analysis examples using the high/low coupled models generated from CTF and TRANSFORM/FMI are investigated. The workflows for both steady-state and transient coupled simulations are described. A steady-state parameter sweep and uncertainty analysis of the primary flow rates and reactor power are demonstrated. Likewise, a transient pump trip and power ramp sensitivity studies are also demonstrated. This work elucidates some of the potential benefits and future needs of using RAVEN for high/low system coupling analysis of energy systems. It also shows some of the difficulties that can be encountered in coupling system simulations.

Williams, Wesley↗

BENCH-SCALE DEVELOPMENT OF A TRANSFORMATIVE MEMBRANE PROCESS FOR PRE-COMBUSTION CO 2 CAPTURE

This final technical report describes work conducted by Membrane Technology and Research, Inc. (MTR) for the Department of Energy, National Energy Technology Laboratory (DOE NETL) on development of the second generation (Gen-2) Proteus™ membrane modules and a pre-combustion membrane process for carbon dioxide (CO 2 ) capture from an Integrated Gasification Combined Cycle (IGCC) plant for power generation (award number DE-FE0031632). The work was conducted from October 1, 2018 through March 30, 2022. The overall goal of this project was to bring a Gen-2 version of the H2-selective Proteus membrane to bench-scale module (component) testing with real syngas. MTR was assisted in this project by Susteon, a technology development company with extensive experience in gasification processes, and the University of North Dakota Energy & Environmental Research Center (EERC), who provided the host site for the slipstream field testing. This report details the work conducted to optimize the Gen-2 Proteus membrane and develop modules capable of operation at 200°C; demonstrate membrane module performance processing coal-derived syngas during a field test at EERC; and optimize integration of a dual-membrane process into an IGCC with carbon capture. Work for this project included membrane optimization and scale-up, module component screening and fabrication of high-temperature lab- and bench-scale modules, design and fabrication of a bench-scale field test membrane skid, operation of the field test skid processing coal-derived syngas at EERC, and a detailed techno-economic analysis (TEA) of the MTR dual-membrane process for IGCC power plant pre-combustion CO 2 capture. This project validated recent membrane technology advancements, mitigates risk in future scale-up activities, and moved the membrane pre-combustion capture technology from TRL-4 to TRL-5. Key results for each major task are discussed in the report.

10 SYNTHETIC FUELS↗

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗

Estimating β eff from static, late-time Feynman neutron noise measurements

The effective delayed neutron fraction, β eff , is a kinematic parameter describing the contribution of delayed neutrons to the effective multiplication factor, $\kappa$ eff , and is of great interest to the nuclear criticality safety community and beyond. In fact, $\kappa$ eff presently must be inferred (as opposed to directly measured) since variables like β eff must be obtained from simulation, reference tables, or a dynamic or pulsed measurement where the assembly of fissile material is perturbed and not in steady state. Several recent works have proposed neutron noise techniques to estimate β eff from static measurements (such as benchmark experiments). This work experimentally investigates an approach based on looking at late-time (up to thousands of seconds) correlated neutrons in Feynman histograms. This work utilizes measurements of weapons grade plutonium and highly enriched uranium to construct late-time Feynman histograms and investigate a proposed methodology of estimating β eff from a fit of the distribution. Data is shown from both He-3 detectors and an organic scintillator array. This work is preliminary in nature, demonstrating some experimental feasibility and proposing improvements for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Standardization of Smart Contracts for Energy Markets and Operation

This work presents a formal review of smart contracts, including definitions, technical requirements, and potential power and energy-related use cases. This includes in-depth discussions covering cybersecurity, legality and interoperability goals that must be taken into consideration by potential end-users. The paper presents a first attempt towards the standardization of smart contracts (SCs) within the field of power and energy as a work in progress activity under the IEEE Standards Association (IEEE SA) P2418.5 Working Group. This work also proposes a holistic, language-agnostic reference model that is intended to accelerate the adoption of Distributed Ledger Technology (DLT) by industry stakeholders by providing standardized processes. Finally, the paper discusses key takeaways that must continue to be developed to increase SC usage within the energy industry.

Blockchain, smart contracts, DLT↗

Enhancing Worker Safety During Off-Site Construction of Energy-Efficient, Low-Carbon Exterior Envelope

The construction industry is not doing enough to embrace off-site modular construction. It is a missed opportunity for optimized energy efficiency because prefabricated exterior wall envelopes are lower in cost and faster and easier to install. Factory off-site construction offers improved safety for construction workers because work is done in a controlled environment, but lack of intent, understanding, and data is also a missed opportunity for enhancing worker safety. This research looks specifically at the prefabricated wall exterior envelope in the context of safety. The research question is "off-site factories build with ease of energy efficiency and lowered carbon emissions, but is the process safer?" This research was funded by NREL Student Training in Applied Research (STAR) program, University Partnerships Program, and Wells Fargo Bank. Key finding is that modular and prefabricated construction are perceived to be safer, but the accident rates are much higher than in the general construction and manufacturing industries. Proposed solutions to decrease accidents in off-site prefabricated construction includes safety training for workers, provide movable kiosks with PPE at workstations, ensure tools are well-maintained and place safety posters in visible locations. Future work includes improving worker safety to increase worker productivity, perform pilot demonstration, work with factory designers for new modular layout for worker safety, i.e., easy access to PPE kiosks, and work closely with OSHA so that they take notice of this safety niche.

drywall↗

Comparison of Approach-to-Critical Results in Current and Pulse Mode for Systems with High Starter Neutron Rates

Reactors and critical assemblies use a variety of detection systems to monitor the neutron population. The count rate is proportional to the neutron flux present at the location of the detector. When such systems are placed external to an assembly, it is often assumed that the relative leakage multiplication will be proportional to the detector count rate (assuming that the source term, system geometry, and detector placement have not changed). Such systems are often used in an approach-to-critical during reactor startup to ensure that the critical configuration is well predicted. Various types of detectors have been used during an approach-to-critical. These include 3 He, BF 3 , ion chambers, fission chambers, and fission foils. Any of these types of systems (or others) should work well when adequate counting statistics are available. These detector systems can be operated in either pulse or current mode. The National Criticality Experiments Research Center (NCERC) has two detection systems that are commonly used in critical assembly operations. The start-up (referred to as "SU" in this work) system is made up of 3 He proportional counters in pulse mode and the linear counter system (referred to as "LC" in this work) consists of compensated ion-chambers in current mode. Typically the SU system is used for approach-to-critical operations and the LC system is only used at/above delayed critical ( k eff = 1). This work investigates the use of the LC system for an approach-to-critical. It has been long hypothesized that such an approach would be feasible for systems with high starter neutron rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Strong-QCD Regime Measurement of the Proton’s Spin Structure

The theory of the strong force, Quantum Chromodynamics (QCD) remains one of the most important ways to understand the fundamental properties of ordinary matter. However, at low momentum transfer Q 2 , in the regime where the strong force becomes extremely strong, our understanding of QCD for ordinary nucleons becomes hazy. Several cutting edge theories such as Chiral Perturbation Theory (χPT) and Lattice QCD have provided valuable predictions in this regime, but Lattice QCD has not yet extended predictions of many important quantities to this kinematic region, and Chiral Perturbation Theory has faced several important disagreements with experimental data for the neutron over the last several decades. It is therefore of extreme importance to have a benchmark of experimental data in the low energy regime for the proton’s behavior, as a test of leading theories for the behavior of QCD in this regime. The E08-027 (g2p) experiment ran at Jefferson Lab in 2012 with the goal of collecting this valuable data, and though I was still completing my undergraduate studies at the time, I became involved in the analysis in 2015 and built on the previous work to complete it and analyze the exciting results. This experiment achieved a high precision measurement of the spin structure functions g1 and g2 for the proton, quantities which describe the internal spin structure of the proton. These measurements were taken in the valuable low Q 2 region described above, and used to extract several moments of these spin structure functions which can be directly compared to the cutting-edge predictions of Chiral Perturbation Theory. Though the experiment’s timeline was such that I didn’t have a chance to work directly on the experimental setup, I had the opportunity to acquire hands-on experience working on a polarized target at UNH which is very similar to the crucial polarized target used in the g2p experiment. Full details of the g2p experiment and my experimental work at the University of New Hampshire are presented in this thesis, as well as a detailed description of the analysis process and the exciting benchmark results, which serve as a direct test of all current and future theories of QCD in the low-Q 2 regime.

Ruth, David↗

Xe-100 Pebble Bed Small Modular Reactor: Solving Critical Challenges to Enable the Xe-100 Pebble Bed Advanced Reactor Concept (ARC) (Final Scientific and Technical Report)

This is the final progress report for the Department of Energy (DOE) – X Energy, LLC cooperative agreement DENE0008472. This report provides a high-level summary of the work performed during the entire period of performance, running from July 1, 2016 – June 30, 2022. This span of time covers the original 5-year award and a one year no-cost extension. There were four tasks within this project: (1) project management, (2) reactor design furtherance, (3) fuel development, and (4) Nuclear Regulatory Commission (NRC) engagement. Detailed reporting during execution of the project was provided by a total of 23 quarterly reports, 42 X-energy technical reports, and voluntary monthly update presentations. Other technical work products include 2 white papers and 2 Topical Report submitted to the Nuclear Regulatory Commission, 15 Potential Inventions documented, 4 patents issued, 3 patents pending, 8 peer reviewed journal articles, and 2 Oak Ridge National Laboratory Technical Manuscripts. All the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2016, Work Breakdown Structure 2.07 – X-Energy. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Design and License Application Development for TRISO-X (Final Scientific Technical Report)

This is the final progress report submitted by X-energy, LLC (XE) to the Department of Energy in support of cooperative agreement DE-NE0008745. This report provides a high-level summary of the work performed during the entire period of performance, running from August 24, 2018 – August 22, 2022. This span of time covers the original 3-year award and a one year no-cost extension. There were five tasks within this project: (1) project management, (2) systems engineering and studies, (3) TRISO-X Facility design, (4) facility license application development, and (5) support to application review. Detailed reporting during execution of the project was provided by a total of 16 quarterly reports, voluntary monthly update presentations, and annual summary presentations. Technical work products include 103 X-energy technical reports, 38 subcontractor (Centrus technical reports), 75 Nuclear Criticality Safety Evaluations/Calculation reports, and 272 miscellaneous design documents (e.g., Engineering Service Orders, Engineering Component Specifications, Procedures, Guidelines/Policies, Design and Interface Requirements documents, and Drawings). All 29 of the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2018, Work Breakdown Structure F.OA – Industry FOA FY 2018 Awards, F.03 – X-Energy TRISO-X Project. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Process Development of the Vaporizing Foil Actuator Welding Technique

The industrial focus on continuous improvement for products is leading design engineers to consider multi-material design concepts more frequently. The design concepts use the advantages of each material while simultaneously minimizing the drawbacks. It also allows for the overall weight of the products to be reduced. Some traditional joining methods, though, struggle to join dissimilar material combinations. A technique known as vaporizing foil actuator welding, which was developed around ten years ago, is a solid-state joining method that has the potential to overcome the barriers to dissimilar material joining. The biggest drawbacks of vaporizing foil actuator welding are that it is still exclusively used in laboratory settings and early in the technology development process. As such, there is not enough confidence in the process for it to be transitioned to manufacturing environments yet. This work begins by analyzing the current state of the technology and identifying a roadmap to achieve a transition to manufacturing. The analysis found that increased confidence in the technology requires sample to sample repeatability to be improved. Beyond that, the process also needs to be fully automated before it can be considered as a viable technique for mass production. In order to further develop the technique, a fully automated work cell was constructed. By removing the human element from the process, this cell helped identify iii the aspects which contribute to process variability. The positioning of the vaporizing foil actuator was identified as the most important factor in process stability. A small set of samples were made in the automated cell with the addition of one component epoxy adhesive around the perimeter of the weld. These samples showed improved process repeatability compared with the samples made without adhesive. This indicates that small amounts of adhesive may be critical in using the process in industrial settings. Additionally, work was performed with manual positioning and adhesive dispensing. This work found that a hybrid joint behaves like traditional weld bonding, where the addition of adhesive makes the joint stronger than if either of the two joining methods were used on their own. To realize this performance with vaporizing foil actuator welding, though, the adhesive needs to be protected from burning during the rapid compression of air during the impact process.

36 MATERIALS SCIENCE↗

Heat Exchanger Design for Waste Heat Recovery using Additive Manufacturing

With anticipated increases in global energy use and their associated emissions, there are many efforts to improve the emissions and efficiency of many industrial processes through waste heat recovery (WHR). To maximize improvements, the heat exchangers in WHR power cycles must be designed and optimized for a given heat source. Meanwhile, additive manufacturing (AM) is a single part manufacturing technique that provides the opportunity to develop unique and complex heat exchanger designs. Consequently, this work centers on the modeling, design, optimization, and testing of AM shell and tube heat exchangers for WHR. Specifically, a modified one-dimensional (1+1-D) and three-dimensional (3-D) heat exchanger models were developed and validated, with the 1+1-D model serving as the basis for design optimization. After modifications to the design to allow for AM, heat exchanger geometry optimizations were completed, targeting increased effectiveness across a range of physical parameters. Of the designs considered, nine were additively manufactured using Ti5553, and then tested using an external heat source and working fluid. Experimentally, the nineteen-tube, zero-baffle heat exchanger displayed the best overall performance, with the effects of dimensional accuracy, surface roughness, and baffles in the other designs also indicated. Next, the experimental results were used as inputs for the 1+1-D model. Although the original model was able to predict fluid outlet temperatures within 5% differences, larger variations in the heat exchanger performance parameters, temperature differences, and pressure drop necessitated optimizing the pressure drop and heat transfer calculations within the model. Thus, the resulting improved model was able to predict the heat transfer rates, heat source temperature difference, and effectiveness within 15% differences, while showing improvements in the pressure drops and working fluid temperature differences. The improved model serves as the foundation for future work to improve the design and performance of AM heat exchangers.

Spickler, Bailey Ann↗

Experiment and simulation of high-speed gas jet penetration into a semicircular fluidized bed

This work marks the third in a series of experiments that were in a semi-circular, gas-fluidized bed with side jets. In this work, the particles are (nominally) 1 mm ceramic beads. The bed is operated just at and slightly above and below the minimum fluidization velocity and additional fluidization is provided by two high-speed gas located on the sides of the bed near the flat, front face of the unit. Two primary measurements are taken: high-speed video recording of the front of the bed and bed pressure drop from a tap in the back of the bed. Particle Image Velocimetry (PIV) is used to determine particle motion, characterized as a mean Froude number, from the high-speed video. A CFD-DEM model of the bed is presented using the recently released MFIX-Exa code. Four model subvariants are considered using two methods of representing the jets and two drag models, both of which are calibrated to exactly match the experimentally measured minimum fluidization velocity. Although it is more difficult to determine the jet penetration depths in a straightforward manner as in the previous works using Froude number contours, the CFD-DEM results compare quite well to the PIV measurements, particularly for submodel flow Syam. Unfortunately, the good agreement of the solids-phase is overshadowed by significant disagreement in the gas-phase data. Specifically, the predicted time averaged standard deviation of the pressure drop is found to be over an order of magnitude larger than measured. Due to the low value of the measurements, just 1% of the mean bed pressure drop, it seems possible that the data is in error. On the other hand, the model may not be accurately capturing pressure attenuation through an under-fluidized region in the back of the bed. Without the possibility additional experiments to test the validity of the data, this work is simply being reported “as is” without being able to indicate which, either the simulation or the experiment, is more correct.<br>

Fullmer, William D.↗

Gas-Liquid Flow Modeling for Renewable Fuels Production

Aerobic/anaerobic and gas fermentation pathways have emerged as promising new technologies for the generation of renewable fuels/chemicals from biomass derived sugars, and mixtures of greenhouse/energy rich gas streams (CO2/CH4/H2/CO) via microbial action. Example pathways include sugars-to-ethanol conversion, biomethanation (CO2/H2 to CH4), biogas upgrading, CO fermentation and wet-waste conversion. Gas and liquid phase transport, mass-transfer, and mixing physics at large length scales can significantly affect microbial conversion rates, particularly when the microbial reaction requires a narrow set of conditions. These phenomena are difficult to study in small-scale bench-top reactors that are typically well-mixed. Predictive computational fluid dynamics (CFD) based simulations can therefore aid in the scale-up, design and optimization of these reactors. This work presents multiphase Euler-Euler CFD simulations of at-scale (~500 m3) bioreactors. Our mathematical model treats the gas and liquid as interpenetrating phases. This approach reduces the computational complexity of tracking individual gas bubbles that are several orders of magnitude smaller than reactor dimensions. We solve the Reynolds averaged Navier-Stokes (RANS) multiphase equations that account for phase and chemical species transport, interphase mass and momentum transfer and uses a phenomenological model for gas uptake by microbes. We use a customized solver derived from open-source CFD toolbox, OpenFOAM [1], to perform these simulations, which has been validated against small-scale reactors in our previous work [2]. There is currently a knowledge-gap regarding bubble-size distributions when using gas mixtures with vastly different properties, which can have a significant impact overall mass-transfer. For example, hydrogen bubbles are more buoyant compared to other relatively heavier gases (CO2/CH4/CO), resulting in a large distribution of residence times and bubble sizes. This work therefore develops a deeper understanding of bubble dynamics and interphase mass transfer in such heterogenous gas mixtures through well-resolved computational models. We use a population balance model (PBM) for bubble-size-distribution modeling that is validated against small-scale experiments in our solver with an uncertainty quantification study for bubble coalescence and break-up model parameters. Results pertaining to multiple simulations of gas-fermentation reactors are presented where gas mixtures with varying compositions of CO2/CH4/CO/H2 are imposed at the sparger boundaries. The spatio-temporal variations in bubble-size distribution and mass transfer coefficient are analyzed for varying superficial velocities and gas-compositions for varying sizes of bubble-column and airlift reactors. This work will also examine the performance of different reactor designs, viz. bubble column reactor, airlift reactor with an internal draft tube, and a stirred-tank reactor with Rushton impellers. Reactor mass-transfer coefficient, gas hold-up, and dissolved gas distribution are critically analyzed among reactors, and sensitivity studies pertaining to gas flow rates and reactor geometry will be presented. [1] Weller, H., Tabor, G., Jasak, H. and Fureby, C., A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in physics, 12, 6, 620--631, 1998. [2] Rahimi, M., Sitaraman, H., Humbird, D. and Stickel, J., Computational fluid dynamics study of full-scale aerobic bioreactors: Evaluation of gas-liquid mass transfer, oxygen uptake, and dynamic oxygen distribution, Chemical Engineering Research and Design, 139: 283-295.

BIOMASS FUELS↗

Preliminary Monte Carlo and Thermal Hydraulic Analysis using a Hybrid ETF-Corrected-Diffusion Prediction Block

This paper builds upon previous work to accelerate the Picard iteration (PI) method typically applied for coupled Monte Carlo-Thermal hydraulic (MC-TH) solutions. Previously, the use of the generalized transfer functions (GTFs) to predict variation in macroscopic cross sections following a perturbation in TH properties was demonstrated for a subset of simple 3D problems. In addition, the reduced-order transport prediction block relied on the first order perturbation (FOP) method, which was shown to have computational overheads. Recent work replaced the FOP block with a 1-group nodal diffusion solver to eliminate these overheads. While the use of diffusion is desirable for large-scale problems, the new solver introduces significant homogenization error. This work aims to address this issue by using the Jacobian-Free Newton Krylov (JFNK) method to generate a set of super homogenization (SPH) factors to improve the accuracy of the diffusion solution. The SPH factors will be used in conjunction with an improved cross section prediction method – the expanded transfer function (ETF) method – to produce a highly accurate flux prediction for an axial 1D boiling water reactor (BWR) pincell following a large perturbation in moderator density. The ETF-corrected diffusion (ETF-CD) block is shown to be highly accurate for the 1D test case. Future work will investigate the accuracy of the method for a realistic 3D pressurized water reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Neural networks for modeling and control of particle accelerators

Charged particle accelerators support a wide variety of scientific, industrial, and medical applications. They range in scale and complexity from systems with just a few components for beam acceleration and manipulation, to large scientific user facilities that span many kilometers and have hundreds-to-thousands of individually-controllable components. Specific operational requirements must be met by adjusting the many controllable variables of the accelerator. Meeting these requirements can be challenging, both in terms of the ability to achieve specific beam quality metrics in a reliable fashion and in terms of the time needed to set up and maintain the optimal operating conditions. One avenue toward addressing this challenge is to incorporate techniques from the fields of machine learning (ML) and artificial intelligence (AI) into the way particle accelerators are modeled and controlled. While many promising approaches within AI/ML could be used for particle accelerators, this dissertation focuses on approaches based on neural networks. Neural networks are particularly well-suited to modeling, control, and diagnostic analysis of nonlinear systems, as well as systems with large parameter spaces. They are also very appealing for their ability to process high-dimensional data types, such as images and time series (both of which are ubiquitous in particle accelerators). In this work, key studies that demonstrated the potential utility of modern neural network-based approaches to modeling and control of particle accelerators are presented. The context for this work is important: at the start of this work in 2012, there was little interest in AI/ML in the particle accelerator community, and many of the advances in neural networks and deep learning that enabled its present success had not yet been made at that time. As such, this work was both an exploration of possible application areas and a generator of proof-of-concept demonstrations in these areas.

43 PARTICLE ACCELERATORS↗