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DOE OSTI2022

Supply Chain Risk Management: Data Structuring

Supply chain risk management (SCRM) is an area of research that addresses both logistics concepts to maximize efficiency, reliability, and revenue as well as risk features, such as potential weak points, break points, and vulnerabilities within the supply chain. SCRM is used to find risks introduced at each node in a supply chain and how these risks can impact a company’s products, individuals, customers, and reputation. SCRM is a relatively new field, so standardized processes including data structuring are not fully documented. This paper explains the importance of a standard data structuring methodology and how it can enhance current SCRM efforts. Data ingest, structuring, and analysis are predominantly managed by humans. Automating some of the less complex steps can positively impact SCRM by allowing human analysts to focus on more strategic analyses. Types of data to be collected and structured are collected via publicly available information related to hardware, software, and corporate entities. After the data has been collected, the information is formatted in a specific manner, conforming to a schema, to allow for more effective and efficient ingest for further analysis. This paper outlines data structures used by Pacific Northwest National Laboratory for SCRM research and analysis purposes. These structures have been used for hundreds of analyses and have been successful in developing a common baseline. Data structuring is one of the first steps in data standardization, which will further mature and enhance the SCRM research area.

supply chain risk management, data structuring, re↗

DOE OSTI2014

TU-C-12A-07: Characterization of Longitudinal Reproducibility of Quantitative Diffusion Imaging Data Acquired with Four Different Protocols Using a Phantom

Purpose: To characterize and compare the longitudinal reproducibility of diffusion imaging data acquired with four different protocols using a phantom. Methods: The Diffusive Quantitative Imaging Phantom (DQIP) was constructed using fifteen cylindrical compartments within a larger compartment, filled with deionized water doped with CuSO4 and NaCl. The smaller compartments contained arrays of hexagonal or cylindrical glass capillaries of varying inner diameters, for differing restraint of water diffusion. The sensitivity of diffusion imaging metrics to signal-to-noise ratio (SNR) was probed by doping compartments with differing ratios of deuterium oxide to H2O. A cork phantom enclosure was constructed to increase thermal stability during scanning and a cork holder was made to reproduce scanner positioning. Four different protocols of DWI (diffusion weighted imaging) and DTI (Diffusion tensor imaging) imaging were assembled on a GE Excite HDx 3.0T MRI scanner to collect imaging data over 9-10 days. Data was processed with in-house software created in Matlab to obtain fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values. Results: All DTI and DWI sequences showed good longitudinal stability of mean FA and ADC values per compartment, exhibiting low standard deviation ∼9%. A t-test was performed to compare mean FA values from the DTI clinical protocol to those of the DTI special protocol, indicating significantly different values in the majority of compartments. ANOVA performed on ADC values for all DTI and DWI sequences also showed significantly different values in a majority of compartments. Conclusion: This work has the potential for quantifying systemic variations between diffusion imaging sequences from different platforms. Characterization of DWI and DTI performance were done over four sequences with predictable results. This data suggests that the DQIP phantom may be a reliable method of monitoring day-to-day and scan-to-scan variation in diffusion imaging sequences from different platforms. Schott Glass North America and The Phantom Laboratory have donated materials and personnel time to this project.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Persistent DynAMICS

Persistent DynAMICS is a lightweight software platform that enables distributed sensing systems to operate as a unified, responsive network. It integrates with existing sensors, data systems, and processing tools as an overlay, without requiring hardware replacement or increasing user burden. As data is collected, the system identifies situations that require additional attention and directs selected sensors to gather more information. For example, if a sensor detects an unusual condition along a pipeline, the system can task nearby sensors or different sensing modalities to confirm the event and focus data collection where it is needed. To support this, the platform forms temporary groups of sensors that work together to address specific objectives. Once complete, these groups are dissolved and resources are reassigned as needed. Communication is handled through an integrated messaging framework with client and server components, enabling reliable operation and data continuity even in low-bandwidth or intermittent connectivity environments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Commissioning of the Mu2e tracker DAQ, planning for the Vertical Slice Test and pre-pattern recognition studies

The primary objective of the Mu2e experiment at Fermilab is to search for the neutrino-less coherent $\mu \rightarrow e$ conversion in the field of an aluminum nucleus ($\mu^- \text{Al} \rightarrow e^- \text{Al}$). The signature of this process is a monochromatic Conversion Electron (CE) with an energy of approximately 104.97 MeV \cite{bartoszek2015mu2e}. Within the Standard Model (SM), the branching ratio for this process, including neutrino masses and oscillation, is expected to be less than $\mathcal{O}(10^{-50})$. This value is far beyond current experimental capabilities. However, models of physics beyond the SM predict much higher relative rates, approaching an observable level. The SINDRUM II experiment set an upper limit on muon conversion at $7 \times 10^{-13}$ (90\% CL) on Au target \cite{SINDRUMII:2006dvw}, and the Mu2e collaboration aims to improve this limit by four orders of magnitude. Observing this process would provide a clear evidence of physics beyond the Standard Model. A brief discussion of the theoretical and experimental aspects is provided in Chapter \ref{intr}. Mu2e adopts a sophisticated experimental setup to achieve its goals, further described in Chapter \ref{mu2echapter}. The central part of the Mu2e detector is the tracker, that consists of 18 tracking stations. The tracker must provide excellent momentum resolution, approximately 1 MeV/c, to distinguish the monochromatic CE signal from the background. To minimize the energy losses, a straw tube tracker will be used \cite{bobbb}. Chapter \ref{chaptertrk} provides an overview of the straw tracker design and its working principles. This Thesis presents a comprehensive study of the Mu2e tracker, covering complementary aspects from initial commissioning to optimization and first steps of the calibration processes. My work at Fermilab has been focused on the complete Data Acquisition (DAQ) testing from both hardware and software perspectives. I was involved in the commissioning of the Mu2e DAQ system and the Vertical Slice Test (VST) of the tracker. The VST encompasses the entire testing chain, from the straws to the readout, and to processed data on disk. I was also focused on the offline analysis, especially on pre-pattern recognition studies, to explore the best methods for identifying $\delta$-electrons during the data taking. Chapter \ref{commissioning} details the commissioning of the tracker DAQ system, emphasizing the importance of understanding of the readout process before the data acquisition. This includes validating the readout logic and firmware through Monte Carlo simulations to confirm functionality and buffering, monitoring the quality of the data from the tracker preamplifiers and front-end electronics, and assessing overall DAQ performance to ensure reliability during future calibration and data-taking. Chapter \ref{planning} discusses the initial steps towards the tracker calibration. The ultimate goal is to perform a time calibration of the first assembled station of the tracker using cosmic muons, aiming for a longitudinal hit position resolution better than 4 cm. This involves determining the signal propagation times and channel-to-channel delays. I performed a Monte Carlo study to determine the impact of the station orientation on the quality of the calibration, in particular on the cosmic track reconstruction, focusing on potential biases that could arise. These studies provide essential insights into the operation, optimization, and calibration of the Mu2e tracker system. Given the high data volume expected during Mu2e operations, estimated at approximately 7 PBytes per year, optimizing memory usage and minimizing CPU consumption are critical. A significant challenge lies in effectively flagging $\delta$-electron hits, which are the primary source of hits in the tracker, without compromising the efficiency of CE hit detection and track reconstruction. A detailed study of pre-pattern recognition and a thorough comparison of two $\delta$-electron flagging algorithms is provided in Chapter \ref{delta}. In Chapter \ref{conclusions}, the findings are concisely summarized, offering a comprehensive synthesis of the research and emphasizing the key insights derived from this study.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

Low-noise, radiation tolerant SiCpms

Over the last 10 years, our R&D effort has resulted in a steady progress on improving Geiger detector array technology performance, verifying their reliability and developing three cell layout libraries containing more than 2200 primitive cells for Si and SiC Geiger based single-photon detectors and silicon ROIC array fabrication. Awards from DOE, NASA and DOD, as wells as commercial R&D orders supported much progress, relevant to this program. The expertise gained and the technologies developed or qualified during these programs provided the design database and expertise to carry out the development of this new SiC photomultiplier (SiCpm) technology, successful fabrication of SiCpm detectors, and evaluation of their radiation hardness. After irradiation with protons and neutrons at 1015cm-2 and 1014cm-2 respectively, SiCpms proved radiation hardness, exceeding the expected radiation tolerance The defects induced by irradiation were mainly point defects. A new improved DLTS method (fDLTS – full wave DLTS) hardware and data processing software specific to investigating radiation damage in SiC was developed. Further work is needed to better characterize and control defects induced by charged particles. We recommend further funding of radiation hardened technology development and validation; qualification of device-specific characterization methods like f-DLTS, development of more methods to evaluate defects in SiC, more active involvement of the national labs in evaluating the SiCpm devices, and DOE support of technology transfer to a qualified foundry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Automatic Selection of High-Fidelity Models and Surrogates for Uncertainty Analysis

Surrogate models (SMs) with distinct features developed in the last decade provide an efficient substitute to the high-fidelity physical simulations. However, it is generally challenging to quantify the accuracy of surrogate models in a region of interest and examine reliability in the overall domain without additional system evaluations. This paper introduces a new scheme, automated adaptive model selection, to adaptively construct and quantify a set of surrogate models and automatically switch between the surrogates and a high-fidelity code. Cross-validation approaches, such as KFold, Leave One Out (LOO) and Leave P Out (LPO), are employed to assess the global accuracy of the surrogates. The switching strategy is based on local validation metrics, crowding distance, that are able to provide an assessment on the goodness of the prediction made by the surrogates. This decision metric decides whether the surrogates are good enough for a certain realization or whether the high-fidelity code needs to be executed. This new scheme has been implemented in Risk Analysis in Virtual ENvironment (RAVEN) software, which can be employed to accelerate the Probabilistic Risk Assessment (PRA) and Uncertainty Quantification (UQ) processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

NUTRON NESHAPs Dashboard

My project aims to enhance the Nuclear Material Tracking Application (NUTRON) software by integrating a tool for the National Emission Standards for Hazardous Air Pollutants (NESHAP) emissions calculations and presenting this data on a dashboard. Inefficiencies in the current NESHAP calculation process were addressed, which will result in more timely regulatory compliance efforts. Key improvements include revising the transfer request system, incorporating effective dose calculations, and developing a data visualization dashboard into NUTRON. The project involved creating a wireframe, preparing an Engineering Calculations and Analysis Report (ECAR), stakeholder meetings, and providing supplemental documentation. Key findings indicate that the proposed modifications will streamline the NESHAP calculation process, reduce human error, and provide REC personnel with accurate and timely data for material use determinations and dose estimations. Future work focuses on completing the NUTRON modifications and fully integrating the new features, ensuring a more efficient and reliable system for tracking and reporting nuclear material transfers.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

Maintenance of Maywood Laboratory Operations Support During Contractor Transition and Replacement of the Project Databases - 16329

In December 2013, Cabrera Services (Cabrera) executed transition of the FUSRAP Maywood Superfund Site remediation project operations, including an on-site accredited environmental lab, from a large business that had established technology infrastructure in place for over a decade which required updating to support the expected remediation scope and client needs. As of November 2015, Cabrera has shipped over 116,000 yd{sup 3} of contaminated soil to disposal facilities. During the transition, the USACE FUSRAP Maywood Laboratory (UFML) continued to support project operations, providing the expected timely and reliable results and maintaining their New Jersey Department of Environmental Protection certification for all parameters of concern, while having to cope with new challenges and additional tasks having the potential to disrupt the laboratory's ability to support project operations. This case study examines the challenges with maintaining a certified radiochemistry laboratory and an aggressive remediation schedule during a period of prime contractor transition which included a complete IT infrastructure overhaul, and conversion of the existing Microsoft Access laboratory database and project Electronic Data Management System (EDMS) to a customized commercial solution. Challenges: I. Procurement of a new database subcontractor and working closely with them to achieve the following: a. Migration of all environmental (including radiological, chemical, and quality control), health and safety, and spatial data as well as reports, queries, and analytical instrument software processes from a MS Access data management system to a SQL server system; and b. Verification that the functionality and data integrity of the databases remained intact. II. The onsite laboratory was changed over to a new onsite network and the following tasks were completed with little or no interruption to site operations by January 10, 2014: i. Installation of new instrument personal computers (PCs) and making them fully operational; ii. Configuration of the lab domain and server to host the LIMS (replaced all servers/domain/workstations with Windows 7 and Server 2012 machines). iii. Networking of the laboratory building into the rest of the project site via fiber optic cabling across the site. iv. Upgrade of the wide area network (WAN) data connection to high-speed Fiber Optic service; v. Upgrade of the telephones into voice over internet protocol (VOIP) phones. vi. Splitting of the database into front ends and a centralized back-end hosted on the new server to allow simultaneous access for fixes and improvements. III. Phone service interruption; phone systems were operational by January 10, 2014. Additional Tasks: I. Revision of the USACE FUSRAP Maywood Laboratory (UFML) Quality Systems Manual Rev. 1 Submitted 01/16/14; II. Writing of the Uniform Federal Policy Quality Assurance Project Plan Rev. 1 (UFP-QAPP) submitted 1/21/14. This document replaced the prior project data quality plan, the Chemical Data Quality Management Plan. III. Support of USACE communications to the New Jersey Department of Environmental Protection (NJDEP) on lab management and personnel transition to Cabrera. This work was important since it ensured a smooth transition and shows how critical project records infrastructure such as databases, can be upgraded with minimal interruption of project support. Such work may provide benefit to other similar projects, especially long term projects where database infrastructure upgrades may be beneficial in terms of improved efficiencies in data recording and transfer, and improved security in data storage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Advanced Computing is at the Forefront of a New “Moonshot” Revolutionizing the North American Power Grid

In the 50+ years since the first humans landed on the moon, computing has grown at breakneck speed. We are faced with another challenge that is just as daunting, and just as important to overcome-modernizing the North American electric power grid-and high-performance computing (HPC) systems with specialized software will be an important element in rising to this challenge. We describe at a high level how software developed in the ExaSGD project addresses this "moonshot" goal by utilizing exascale computing and a novel high performance solver software stack to support the mission of decarbonizing power grid operations in an environment of uncertain weather and climate. To reach the exascale benchmark the team has made a number of first-of-their-kind innovations, including novel method for stochastic optimization, fine grained parallel methods for modeling power systems, and GPU resident sparse numerical linear solvers.

17 WIND ENERGY↗

DOE OSTI2013

Advanced Simulation and Computing Fiscal Year 14 Implementation Plan, Rev. 0.5

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Moreover, ASC’s business model is integrated and focused on requirements-driven products that address long-standing technical questions related to enhanced predictive capability in the simulation tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Advanced Simulation & Computing FY15 Implementation Plan Volume 2, Rev. 0.5

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. As the program approaches the end of its second decade, ASC is intently focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Where possible, the program also enables the use of high-performance simulation and computing tools to address broader national security needs, such as foreign nuclear weapon assessments and counternuclear terrorism.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Advanced Simulation and Computing Implementation Plan, FY15, Rev. 1

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. As the program approaches the end of its second decade, ASC is intently focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Where possible, the program also enables the use of high-performance simulation and computing tools to address broader national security needs, such as foreign nuclear weapon assessments and counter-nuclear terrorism.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Advanced Simulation and Computing FY17 Implementation Plan, Version 0

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further away from the original test base. Where possible, the program also enables the use of high performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and counter nuclear terrorism.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

ASC FY17 Implementation Plan, Rev. 1

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

pyEF: A Python Framework for QM and QM/MM Atom-Wise Electric Field Analysis

We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this QM-derived electric field evaluation tool through several tests. To assess the influence of the underlying QM method and charge partitioning scheme on these electrostatic quantities, we analyze over 250 configurations of an acetone solute molecule in five solvents of variable polarity. We find that electric field calculations are highly sensitive to the choice of charge partitioning method. Even among real-space charge schemes, acetone Stark tuning rates differ by up to a factor of 2. Benchmarking computed solvent dipole moments against experimental bulk values, we conclude that the CM5, ADCH, and Hirshfeld-I charge schemes most reliably capture solvent electrostatics and therefore provide a more faithful foundation for computing electric fields. When constructed from these real-space charges, electric fields are nearly insensitive to basis set size and monotonically increase in magnitude with higher Fock exchange. We also demonstrate efficient convergence of QM electrostatics when more distant molecules are represented solely by MM point charges, reducing computational overhead. Leveraging these findings, we demonstrate the use of pyEF to deduce environmental effects on a transition metal complex from a Ga 4 L 6 12– nanocage and quantify the dominant role of organic linkers in orchestrating electrostatic preorganization.

electric fields↗

DOE OSTI2018

Design Considerations for Secure Wireless Sensor Communication Systems in Harsh Electromagnetic Environments of Nuclear Reactor Facilities

Wireless sensors can potentially play a significant role in safety, efficiency, and reliability of the instrumentation and control process in current and next generation nuclear power reactors. While conventional narrowband wireless sensors have shown a certain level of success in some nuclear power plants (NPPs), the radio frequency (RF) propagation challenges posed by the heavy metallic and cluttered environment of NPPs has prevented their widespread use in such operations. Furthermore, these challenges include RF wave propagation in harsh (reflective, absorptive, cluttered) environments, data security issues, and RF interference to and from other devices in the vicinity of a nuclear reactor core. In this paper, first we address how ultrawideband (UWB) RF technology can complement the narrowband (i.e., WiFi) solutions that have been used in some NPPs by providing an alternative solution in addressing the signal propagation issues in such electromagnetically harsh environments. Second, we discuss and present the UWB software simulation results on multipath harsh environments, and then address the data security issues. In the final sections of the paper, we present the experimental results of using UWB signaling in a representative harsh environment conducted at the Massachusetts Institute of Technology research reactor site. We plan to develop the UWB communications hardware based on the results of this paper and report on its performance in the field with emphasis on the security aspects of the system in a subsequent paper.

42 ENGINEERING↗