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At least 325 records · Page 18

Transformational challenge reactor analysis to inform preconceptual core design decisions: Sensitivity study of transient analysis in a hydride-moderated microreactor

The Transformational Challenge Reactor (TCR) program aims to demonstrate a revolutionary design approach enabled by advanced manufacturing and data analytics in the design of nuclear reactors. This article discusses scoping analyses of preconceptual designs to inform TCR design decisions and the evaluation of sensitivities and uncertainties on postulated transient scenarios. The applicability of the systems codes TRACE and RELAP5-3D to TCR transient analysis are examined, and RELAP5-3D models are used to examine the transient response of two candidate core designs at multiple power levels. Then, the uncertainty quantification code RAVEN is used to quantify the effect of several design parameters on reactivity-initiated accident (RIA) progression at hot zero power (HZP) and hot full power (HFP) as well as to assess the impact of uncertainties in transient parameters for the pressurized loss of forced cooling (PLOFC).When results were compared, TRACE and RELAP5-3D showed good agreement in their ability to predict system behavior, but RELAP5-3D calculations were closer to analytical predictions for the RIA. Furthermore, models for a PLOFC accident in two designs (a UO2 and TRISO core) at multiple power levels showed greater temperature margins for the TRISO core at all power levels. Using this information, along with other scoping analyses and constraints, the TCR design team selected a power level of 3 MWth and a TRISO-based core design. For this design RAVEN was applied to vary RIA parameters in RELAP5-3D models at HZP and HFP to understand the effect on figures of merit such as peak power, fuel and coolant temperature, and energy deposition. This sensitivity study found that the inserted reactivity worth was the most important parameter controlling all figures of merit, but for insertion up to 1.5$ no failure of TCR fuel is anticipated. For constant reactivity insertions, the magnitude of the fuel temperature coefficient was found to have the greatest effect on all figures of merit under most circumstances. These results not only demonstrate the anticipated robust safety of the proposed TCR fuel form but also provide a reference for future metal-hydride moderated systems to understand RIA behavior. In the PLOFC, the impact of heat transfer enhancement due to wavy flow channel effects dominated the variance in peak temperatures, and variations in heat exchanger elevation provided the greatest control on natural circulation flow rate. Additionally, no fuel particle failure is anticipated in the PLOFC.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Universal topological quantum computation with strongly correlated Majorana edge modes

Abstract Majorana-based quantum gates are not complete for performing universal topological quantum computation while Fibonacci-based gates are difficult to be realized electronically and hardly coincide with the conventional quantum circuit models. In reference Hu and Kane (2018 Phys. Rev. Lett. 120 066801), it has been shown that a strongly correlated Majorana edge mode in a chiral topological superconductor can be decomposed into a Fibonacci anyon τ and a thermal operator anyon ɛ in the tricritical Ising model. The deconfinement of τ and ɛ via the interaction between the fermion modes yields the anyon collisions and gives the braiding of either τ or ɛ . With these braidings, the complete members of a set of universal gates, the Pauli gates, the Hadamard gate and extra phase gates for one-qubit as well as controlled-NOT (CNOT) gate for two-qubits, are topologically assembled. Encoding quantum information and reading out the computation results can be carried out through electric signals. With the sparse-dense mixed encodings, we set up the quantum circuit where the CNOT gate turns out to be a probabilistic gate and design the corresponding devices with thin films of the chiral topological superconductor. As an example of the universal topological quantum computing, we show the application to Shor’s integer factorization algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Looking through model medieval green glasses: From color to recipe

Abstract The colors of medieval stained glasses depend on their chemical composition. The redox interactions in glass between iron and copper and their influence on the color were investigated in two soda‐lime silicate model glasses. Both glasses have close iron and copper redox ratios and copper oxidizes iron when the iron content is smaller than the copper content. The redox speciation of iron and copper was determined using combining x‐ray and optical absorption spectroscopies in relation with the resulting color. The molar extinction coefficient of Cu 2+ was estimated from the combined analysis to be 32 mol/L/cm. The glass color change from green to blue‐green color is assigned to the decrease of the total iron content, confirming that ancient glassmakers could control the final color with the glass recipe. These results provide reference data for further spectroscopic investigations of medieval stained glasses. Comparison with ancient copper‐colored green glass compositions suggests that the higher ratio of copper to iron total contents was imposed by the more reducing melting conditions in medieval furnaces.

Hunault, Myrtille O. J. Y.↗

MELCOR Accident Progression and Source Term Demonstration Calculations for a HTGR

MELCOR is an integrated thermal hydraulics, accident progression, and source term code for reactor safety analysis that has been developed at Sandia National Laboratories for the United States Nuclear Regulatory Commission (NRC) since the early 1980s. Though MELCOR originated as a light water reactor (LWR) code, development and modernization efforts over the past decades have expanded its application scope to include non-LWR reactor concepts. Current MELCOR development efforts include providing the NRC with the analytical capabilities to support regulatory readiness for licensing non-LWR technologies under Strategy 2 of the NRC's near-term Implementation Action Plans. Beginning with the Next Generation Nuclear Project (NGNP), MELCOR ha s undergone a range of enhancements to provide analytical capabilities for modeling the spectrum of advanced non-LWR concepts. This report describes the generic plant model developed to demonstrate MELCOR capabilities to perform high-temperature gas reactor (HTGR) safety evaluations. The generic plant model is based on publicly available PMBR-400 design information. For plant aspects (e.g., reactor building size and leak rate) that are not described in the PBMR-400 references, the analysts made assumptions needed to construct a MELCOR full-plant model. The HTGR model uses a TRi-structural ISOtropic (TRISO)-particle fuel pebble-bed reactor with a primary system rejecting heat to a recuperative heat exchange r. Surrounding the reactor vessel is a reactor cavity contained within a confinement room cooled by the Reactor Cavity Cooling System (RCCS). Example calculations are performed to show the plant response and MELCOR capabilities to characterize a range of accident conditions. The accidents selected for evaluation consider a range of degraded and failed modes of operation for key safety functions providing reactivity control, primary system heat removal and reactor vessel decay heat removal, and confinement cooling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Estimation of the time for steam generator trip due to cyber intrusions

The time required to trip a pressurized water reactor (PWR) by inserting malicious signals into its steam generator (SG) control system has been studied using the Generic PWR (GPWR) Simulator. A semi-analytical model is developed to approximately reproduce the simulator response and understand the dynamics of the control unit. A series of two proportional-integral controllers determines control action according to preset constants, the readings from the feedwater level sensor, and those from feedwater and steam flowrate transmitters. It is observed that the most important factor that determines whether a trip will occur is how much additional water is added to or withheld from the SG over time compared to normal operating conditions. In order to determine the effects of control action on the SG, changes in mass inventory are considered. This approach models the SG water level as a function of mass inventory and has a backward temporal memory. A Python interface is developed for the GPWR framework to automatically simulate different spoofing scenarios and post-process the related data. We observe that the trip times predominantly depend on flow mismatch and/or level errors. Controller parameters, including the integral time and gain constants, either speed up or slow down the rate of progression to a trip setpoint but do not cause a trip by themselves. The reactor can trip on a high-level signal when the reading crosses above 78%, increased from its reference level of 57%, or a low-level reading when it is below 25%. The present results show roughly how long the operators would have to respond to an attack, given a specific set of spoofing signals within the issue space analyzed. Furthermore, we have generated a simple surface by fitting a combination of exponential functions to the data obtained from the GPWR Simulator. In general, trips on a low level have been observed to occur faster than those on a high level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Large-Scale Analysis to Optimize the Control and V2V Communication Protocols for CDA Agreement-Seeking Cooperation

Cooperative driving automation (CDA) Class C, agreement-seeking cooperation, is an innovative and practical solution that can promote cooperation among general passenger vehicles on the road. However, more comprehensive studies are needed before establishing the standard protocols of agreement-seeking cooperation, such as communication frequency and the duration of cooperation. Here, this article presents an initiative study on the impacts of communication capabilities on agreement-seeking cooperation. Through a large-scale analysis by regulating vehicle-to-vehicle (V2V) communication metrics, this work suggests desirable system parameters that can maximize the benefits of cooperation and ensure reliable operability while avoiding exhaustive communication loads. As the first step, an example agreement-seeking cooperation system is created for a car-following scenario, including decision-making and control algorithms for autonomous vehicles. Then, software-in-the-loop tests explore the performance of the developed system as it encounters various communication risks, such as latency and message packet drops. The system performance metrics are evaluated from various angles, including the time consumed for the agreement-seeking process, cooperation ratio, and the ratio of faulty cooperation. Energy saving from the cooperation is assessed by using simulation software that can run multiple high-fidelity vehicle models simultaneously. Based on the analyses, this article suggests the V2V communication requirements for the reliable operation of CDA agreement-seeking, which can be referred to when developing the standard protocols of agreement-seeking cooperation.

42 ENGINEERING↗

Influence of simple terrain on the spatial variability of a low-level jet and wind farm performance in the AWAKEN field campaign

In wind energy research, scientific challenges are often associated with complex terrain sites, where orography, vegetation, and buildings disrupt flow uniformity. However, even sites characterized as simple terrain can exhibit significant spatial variability in wind speed, particularly during stable boundary layers (SBLs) and low-level jets (LLJs). This study investigates these terrain interactions using both simulations and observations from the American WAKe ExperimeNt (AWAKEN). We employ a multiscale Weather Research and Forecasting (WRF) model simulation, integrating mesoscale forcing in the coarse domains and representing three rows of turbines from the King Plains wind farm as generalized actuator disks (GAD) in the large-eddy simulation (LES) domains. During a nocturnal LLJ event on 3 April 2023, the downstream, wake-affected turbine rows outperformed the upstream, unwaked row by 25 %–51 %. This counterintuitive result arises from terrain-induced streamwise variations in hub-height wind speed of approximately 4 m s −1 over 5 km – equivalent to ∼50 % of the upstream reference speed. This enhancement outweighs the wake-induced reduction in mean wind speed (∼12 %) and global blockage effects reported in the literature (∼1 %–3.4 %). The multiscale simulations capture the intra-farm spatial variability in power performance observed in SCADA data. Terrain-induced vertical displacement of the LLJ, coupled with large wind shear below the jet maximum, drives the substantial streamwise acceleration within the wind farm. These findings underscore the importance of accounting for spatial variability related to terrain, even in simple landscapes, particularly during LLJ conditions. Incorporating such effects into reduced-order modeling frameworks for wind farm design and control could significantly enhance their effectiveness.

17 WIND ENERGY↗

Modernizing the Legacy Fission Wire Measurement System for the Advanced Test Reactor-Critical Facility

Operational lifetime extensions of existing research reactors have emphasized the need for refurbishment, replacements, and upgrades to supporting equipment and instrumentation. The Advanced Test Reactor (ATR) at Idaho National Laboratory (INL), which entered service in 1967, has recently completed the sixth core internals change-out and has scheduled operations until at least 2040. Reactor maintenance and operational risk management is critically important in the research reactor community, however supporting measurement systems sometimes get overlooked when maintenance is planned. The Fission Wire Measurement System (FWMS) is a custom measurement system designed in the 1960s to measure the beta-particle activity of irradiated uranium-aluminum fission wires. This measurement is conducted to determine the fission rate profile of the Advanced Reactor Test Critical (ATR-C) facility. The ATR-C is an open-pool, low-power test reactor that was purpose driven to resemble ATR and is used to qualify experiment configurations and verify core models prior to full-power experiment irradiations in ATR. A power distribution measurement in ATR-C uses uranium-aluminum wires that are distributed throughout the ATR-C core to validate simulation and modeling results. These measurements require 340 to 1500 wires to be irradiated and measured within a 12-hour window. The activity of the wires is measured in the required time with the FWMS, which was put into service in 1965 at the Radiation Measurements Laboratory (RML). The system consists of 4 measurement channels and one reference channel, each with a 2-pi proportional gas flow detector and the measurement channels each have an automated sample changer. This legacy system is crucial to the continued operations of ATR and has undergone some minor hardware upgrades since 1965, however the system presently relies on custom control boards, custom gas ion chambers, analog amplifiers/discriminators, and a user interface (UI) for the system written in outdated code. Much of the equipment and software is custom with no commercial replacements or support and limited documentation. The existing control software requires an operating system that is no longer supported, creating more vulnerabilities to continued operations. A project is underway with a third-party vendor to design, build, and document a new control and data acquisition system (CDAS) for the FWMS. The new upgrade will replace the control system, computer, UI, sample changer motors, and main power supply while maintaining the interface with existing detector hardware. The upgraded system will be operated in parallel with the current hardware and software to conduct validation testing. This equipment upgrade demonstrates the commitment at ATR to ensuring successful operations and potential future research reactors at INL.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Outdoor Test Bed Performance of a Power Line Sensor Using a Real-Time Event Simulator

This report summarizes the design and application of an outdoor power line sensor testbed (OPLST) with a real-time simulator and power meter to compare a potential transformer (PT) and current transformer (CT) versus an advanced line-post sensor. The OPLST was created to validate advanced medium-voltage (20/34.5 kV) outdoor power line sensors used in electrical distribution systems. Electrical utilities have installed metering and relay-protection transformers like PTs and CTs for several decades. The PTs/CTs are iron core measurement transformers based on the electromagnetic induction principle and provide reliable data in normal grid operation. However, new outdoor power line sensors (OPLS) using other technologies like voltage divider, Rogowski coil and optical principles have become available and may have favorable performance and costs compared to PTs/CTs. Therefore, the importance of testing these technologies with the PT/CT, to compare the measured phase voltage/current at different power grid scenarios is crucial to understand the performance of these new OPLS. For this study a G&W Electric Model CVS-36-O power line sensor was chosen as the OPLS to test with voltage/current signals. An OPAL-RT Technologies Model OP4510 real-time simulator and Schweitzer Engineering Laboratories Model SEL-735 power meter were installed with the 20/34.5 kV OPLST to compare the measured transient events collected from an advanced OPLS and the PT/CT. This system is installed at the Distributed Energy Communications and Control (DECC) lab, Oak Ridge National Laboratory (ORNL). The simulator generated different power grid scenarios (electrical faults, capacitor bank operation, service restoration, etc.), and its analog-output signals were connected to the voltage/current amplifiers that feed the 20/34.5 kV aerial cable loop through the PT/CT devices. Additional PT/CT devices were also wired with the medium voltage aerial cable loop to measure the phase current/voltage signals and server as references. After each test, common format for transient data exchange (COMTRADE) files were collected from the SEL-735 power meter and used to compare the performance of the OPLS with the PT/CT. The behavior of analog signals, harmonic components, total harmonic distortion and crest factors were assessed and found favorable for the G&W sensor as compared to the reference PT/CT.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Exploring the Impact of Near-Term Innovations on the Technical Potential of Land-Based Wind Energy

Land based wind may play a critical role in reaching emissions reductions goals and high renewable contribution scenarios with capacity expansion modeling results estimating over 1 terawatt of land-based wind by 2035 to reach 100% clean electricity. Deployment of land-based wind at this magnitude may require significant investments in transmission infrastructure and will require significant land area for new wind and transmission. Cost reductions via technological advancements in wind turbine design, construction, and maintenance will have a major role in enabling the scale of deployment required. Since 1998, the levelized cost of wind energy has fallen by over 60% due to improvements in capacity factors, advancements in turbine controls, and cost reductions in installation, operation, and maintenance. These cost reduction pathways, generally referred to as wind technology "innovations", have enabled significant increases in the capacity and electric generation share of wind power in the United States. Nevertheless, achievements of past wind innovations have not led to widespread wind deployment outside of high wind speed geographies. This study evaluates the potential of near-term innovations to expand the geographic range of economically viable land-based wind power production in the United States. Many challenges to future deployment of wind power can be associated with increasing concentration in high-wind areas. As more wind power is deployed in these same areas, it is likely that residential and regulatory resistance to further deployment will increase, access to transmission will diminish, and options for distant companies and governments with renewable energy goals will remain limited. Therefore, this analysis aims to emphasize the potential for innovations to enable land-based wind in regions with limited wind deployment and with lower wind resource and better access to transmission.

17 WIND ENERGY↗

Modeling Riverine Dissolved and Particulate Organic Carbon Fluxes from Two Small Watersheds in the Northeastern United States

The coupled carbon (C) cycle across terrestrial and aquatic environments at the watershed scale has been identified as an important, but poorly constrained component of the global carbon budget. Here, we extended Soil and Water Assessment Tool (SWAT) with coupled riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) modules (referred to as SWAT-C hereafter). Results show that SWAT-C reproduced daily POC and DOC fluxes well in two watersheds in the Northeastern United States. We found that SWAT-C tended to underestimate high flows and peak DOC and POC fluxes. Uncertainty analysis indicated flux uncertainties associated with POC and DOC simulation were larger than those for flow simulation. Sensitive parameters controlling POC and DOC biogeochemical processes were identified along with how these parameters influence mechanisms underlying C cycling. We anticipate that the tool developed and applied here will inform C related ecosystem services in watershed assessment and planning.

Dissolved organic carbon, Particulate organic carb↗

A Pore‐Scale Investigation of Mineral Precipitation Driven Diffusivity Change at the Column‐Scale

Abstract Mineral precipitation affects the pore structure and thus transport properties of porous media. In this study, we investigated the pore‐scale dynamics of precipitation in diffusion controlled systems and the resulting impacts on the effective diffusivity, using a micro‐continuum reactive transport model. Forty two‐dimensional pore structures representing both idealized and realistic geometries were simulated with consideration of different precipitation scenarios and rates. A homogeneous nucleation scenario reproduced patterns observed in previous experimental study showing mixing‐induced precipitation, and a surface growth scenario captured the pattern for mineral precipitation on a substrate with the same or similar mineral structures. In all cases, local precipitation resulted in the reduction in the average porosity of the domain ( Φ ) until the cessation of diffusive transport and the termination of precipitation. The minimum porosity reached was referred to as the critical porosity ( Φ c ). The effective diffusivity ( D eff ) decreased with Φ and dropped sharply to effectively zero, that is, the critical effective diffusivity ( D eff c ), as Φ c was reached. These pore‐scale dynamics can be captured by a revised relationship that explicitly considers the critical porosity and the corresponding effective diffusivity, and the pre‐exponential coefficient and the exponent of the relationship varied with initial pore structure and the precipitation kinetics. Overall, the homogeneous nucleation scenario results in systematically larger Φ c and coefficients that give rise to a sharper decrease in diffusivity as Φ c is approached, compared to the surface growth scenario. The revised relationship was also implemented at continuum scale and used to examine column scale diffusivity change and reactions.

58 GEOSCIENCES↗

A Two-Step Control Approach for Torque Ripple and Vibration Reduction in Switched Reluctance Motor Drives

The objective of this work is to reduce the torque ripple and vibration in Switched Reluctance Motor (SRM) drives. To achieve such a goal, a two-step approach is proposed. In the first step, the reference current is profiled using an optimization method, aimed to reduce the torque pulsation. In the second, the optimum current profile is applied to the SRM through an adaptive hysteresis band controller to actively cancel the radial vibration. The proposed technique uses an optimization procedure based on the Field Reconstruction Method (FRM) and Non-Derivative Optimization Method to find the optimal current profile that mitigates the torque pulsation, however, the investigation has shown that the proposed excitation leads to a higher radial vibration, which has been mitigated by using an adaptive hysteresis band controller. The theoretical basis for the proposed approach is initially presented, followed by system modeling and simulation. In addition, experimental verification has been conducted using an 8/6 SRM to show the feasibility of the proposed approach. The proposed method alleviates the acoustic noise and torque pulsation in SRM and offers an effective step towards the prevalent use of SRM in a wide range of applications.

42 ENGINEERING↗

An Update to the National Renewable Energy Laboratory Baseline Wind Turbine Controller

The National Renewable Energy Laboratory's 5-MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the 5-MW wind turbine uses a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into fast-paced development cycles, as systems engineering tools such as Wind-Plant Integrated System Design & Engineering Model (WISDEM ®) [1] are employed, and as a greater focus on controls co-design practices is encouraged, demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5-MW controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process while maintaining or improving the performance of the legacy NREL 5-MW controller.

17 WIND ENERGY↗

Causes of and Solutions to Wind Speed Bias in NREL's 2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf

This report provides the results of a detailed analysis into the causes of high wind speed bias in the 20-year wind resource data set for offshore California the National Renewable Energy Laboratory (NREL) released in 2020, herein called CA20. The data set was developed using the state-of-the-art Weather Research and Forecasting (WRF) model. Notably, no floating lidars were available at the time in offshore California to validate offshore hub-height wind speeds. In late 2020, the Pacific Northwest National Laboratory (PNNL) deployed two floating lidars in the California outer continental shelf (OCS), near the Bureau of Ocean Energy Management (BOEM) call areas of Humboldt and Morro Bay. Using these observations through 2021, NREL found considerable bias in modeled hub-height winds at both locations: up to +2 m/s at Humboldt over a 6-month period, and up to +1 m/s at Morro Bay over a one-year period. Upon the discovery of this bias, the Department of Energy (DOE) and BOEM funded NREL and PNNL to investigate the causes of, impacts of, and solutions to the bias in the CA20 data set. This report summarizes the findings of this research. We first investigated whether different WRF model setups could lead to reduced bias. We found that the choice of planetary boundary layer (PBL) scheme - which controls the vertical turbulent mixing of momentum, heat, and moisture in the lowermost part of the atmosphere - greatly affected hub-height wind speeds in the region. Specifically, switching from the Mellor-Yamada-Nakanishi-Niino (MYNN) scheme used in CA20 (and widely used across a range of operational and research weather models) to the less common Yonsei University (YSU) scheme nearly eliminated the bias at both the Humboldt and Morro Bay lidar locations. The large discrepancy between the MYNN- and YSU-modeled hub-height winds pointed towards the role of atmospheric stability. In general, PBL schemes agree well in conditions of high turbulence and mixing, normally referred to as "unstable" conditions. By contrast, PBL schemes start to diverge in "stable" conditions, where turbulence is low and thermal stratification (i.e., higher temperature air sitting on top of colder air) greatly suppresses vertical mixing. Under such conditions, winds aloft can decouple from surface effects and greatly accelerate, causing high wind speeds at hub-height and frequent low-level jets (LLJs). We determined that these stable conditions are in fact dominant in offshore California. The region is characterized by moderate-to-extreme stable stratification with a LLJ on average around 200 meters above sea-level. To our knowledge, no wind energy area globally has as strongly stable stratification as offshore California. Under these extreme conditions, we determined that the MYNN scheme models higher stability than YSU, resulting in less vertical turbulent mixing than YSU, allowing for the acceleration of hub-height winds, more intense LLJs, and higher-amplitude inertial oscillations. Using surface observations, we found that MYNN overestimates near-surface stability, whereas YSU tends to model stability better. We then considered several short-term case studies to assess additional meteorological drivers of the bias at Humboldt. We found that during synoptic scale northerly flows driven by the North Pacific High and inland thermal low, a coastal warm bias in the MYNN case studies contributes to the modeled wind speed bias by altering the boundary layer thermodynamics via a thermal wind mechanism. Given the strong performance of the YSU-based runs in offshore California, NREL has produced and published an updated version of the CA20 data set with YSU as the PBL scheme. This updated data set is now part of NREL's 2023 National Offshore Wind (NOW-23) data set, which covers all the U.S. offshore waters. The development and final validation of the NOW-23 data set in offshore California is documented in this report.

17 WIND ENERGY↗

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗

Understanding plasma turbulence through exact coherent structures

Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a generalized framework to analyze plasma turbulence that utilizes periodic orbit theory. In periodic orbit theory, doubly periodic solutions (coherent structures) of the governing equation(s) serve as building blocks of the considered turbulent dynamics. To illustrate the concept and method, the particularly simple Kuramoto–Sivashinsky (referred to here as LMRT for the original authors: LaQuey, Mahajan, Rutherford, and Tang) trapped-ion mode toy model is used. By applying numerical optimization techniques to the LMRT equation, we extract coherent spacetime patterns that represent the library of allowable fundamental structures of the equation. These structures provide a framework to systematically describe turbulence as a composition of recurrent solutions, revealing an underlying order within chaotic plasma motion. Although illustrated here using the simplified LMRT model for clarity, this framework provides a general strategy that can be extended to more complex and realistic models of plasma turbulence, including gyrokinetic systems. This offers a new method for predicting and potentially controlling transport processes in fusion plasmas by providing a bridge between nonlinear dynamical systems theory and plasma physics in the form of a generalized framework with which to analyze and understand spatially extended nonlinear partial differential equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Heavy-Ion-Induced Lung Tumors: Dose- & LET-Dependence

There is a limited published literature reporting dose-dependent data for in vivo tumorigenesis prevalence in different organs of various rodent models after exposure to low, single doses of charged particle beams. The goal of this study is to reduce uncertainties in estimating particle-radiation-induced risk of lung tumorigenesis for manned travel into deep space by improving our understanding of the high-LET-dependent dose-response from exposure to individual ion beams after low particle doses (0.03 - 0.80 Gy). Female CB6F1 mice were irradiated with low single doses of either oxygen, silicon, titanium, or iron ions at various energies to cover a range of dose-averaged LET values from 0.2 - 193 keV/µm, using 137Cs γ-rays as the reference radiation. Sham-treated controls were included in each individual experiment totally 398 animals across the 5 studies reported. Based on power calculations, between 40 - 156 mice were included in each of the treatment groups. Tumor prevalence at 16 months after radiation exposure was determined and compared to the age-matched, sham-treated animals. Results indicate that lung tumor prevalence is non-linear as a function of dose with suggestions of threshold doses depending on the LET of the beams. Histopathological evaluations of the tumors showed that the majority of tumors were benign bronchioloalveolar adenomas with occasional carcinomas or lymphosarcomas which may have resulted from metastases from other sites.

60 APPLIED LIFE SCIENCES↗