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Assessment of Potential Dose and Environmental Impacts from Proposed Testing at the INL National Security Test Range

This assessment uses screening-level models to calculate potential environmental impacts from proposed tests at two locations at the Idaho National Laboratory (INL) National Security Test Range (NSTR) site. Proposed tests could be conducted using 11 different radioactive material types that include K 2 O, LaBr 3 , KBr, Cu, Zr, F, Ga, Ga 2 O 3 , NaNO 2 , Ga-68, and Tc-99m. The tests could potentially release radioactive material to the atmosphere and radionuclides and other contaminants to the soil, which could leach into the unsaturated zone and migrate to the aquifer. Atmospheric transport of radionuclides to potential human receptors and time-integrated air concentrations were calculated with a Gaussian plume model and three years of hourly meteorological data. Potential surface-soil impacts were calculated with the computer program mixing-cell model (MCM). Groundwater impacts were calculated with the computer programs MCM and GWSCREEN. Radiological doses from potential atmospheric releases were calculated for public receptors off the INL Site and for workers at nearby INL facilities. Results were compared to regulatory dose limits. Maximum potential groundwater concentrations were estimated in the aquifer below the NSTR site and compared to drinking water standards or risk-based screening levels for resident tap water. Soil concentrations were calculated and compared to risk-based screening levels for workers and potential future residents. All impacts were estimated based on the assumption that 12 tests are conducted annually using all 11 material types for 15 years. This document provides the resources to enable a subject matter expert in the field of environmental assessments to replicate the modeling and calculations. The methodology and parameters are presented in the text. All electronic files, including computer-code input, output, executable files, batch files, scripts, and spreadsheet files, are contained in a zip file that can be accessed by selecting “Additional Information” (select Native File) in the INL Electronic Document Management System (EDMS). It is highly unlikely the test scenarios evaluated in this ECAR will adversely impact human health based on comparisons of calculated dose and concentration against regulatory standards and risk-based screening levels. Conservative estimates of dose to workers and the public from atmospheric transport of possible radionuclide releases are far below federal radiation protection standards. Conservative estimates of potential contaminant concentrations in groundwater are less than federal drinking water standards or screening levels. Predicted radionuclide concentrations in surface soils are below risk-based screening levels, except for Ge-68 (material Ga-68) for the worker. The Ge-68 soil concentration can be made less than the worker PRG, if the number of annual tests using Ga-68 is reduced from 12 to 6. However, the sum of ratios still exceeds one because of the high K-40 ratio. If the EF of the worker (number of days the worker is in the contaminated testing area) is reduced from 225 days/yr (default value for full time worker) to 112 days/yr, the Ge-68 ratio is less than one and the sum of ratios is less than one. Actual radiation doses and groundwater and surface-soil concentrations are likely to be much less than those calculated because of the conservative assumptions and parameters employed in the modeling. For example, atmospheric-transport calculations assume the entire inventory of each material type is readily released to the atmosphere and no plume deposition, depletion, or radioactive decay occurs during transport. The calculations also assume the same meteorological conditions (e.g., wind velocity, wind direction, stability class) that produce the maximum 95th percentile concentration (i.e., concentration representing the 95th percentile of a distribution of concentrations derived from 3 years of hourly meteorological data) at each receptor location are the same for all 12 tests during the year, and each receptor is assumed to be present during all 12 tests. The surface-soil assessment assumes the entire inventory of each test is deposited in the top 5 cm of soil. No atmospheric dispersal is assumed, and the radionuclides are subject only to leaching and radioactive decay. The groundwater-pathway modeling is conservative in that it is one-dimensional in the unsaturated zone (no lateral spreading/dilution) and assumes the entire inventory of contaminants infiltrates into the ground at the same location for every test. This is especially conservative for particulate radionuclides because they would have to dissolve or corrode first and some would be dispersed into the atmosphere. The groundwater receptor is also assumed to consume water directly from a hypothetical well positioned in the location of maximum concentration. In addition, conservative degradation rates were used, and volatilization was not considered for the nonradradioactive chemicals modeled. And finally, the calculations assume all 12 tests will be performed at the same place at both locations, and all 11 radioactive material types will be used for each test. This is conservative because it is anticipated that no more than two material types will be used per test.

99 GENERAL AND MISCELLANEOUS↗

Laboratory Evaluation of Commercial Utility Microgrid Controller Test Results

The functional requirements of many microgrid controllers (MGCs) are expanding and evolving to meet growing utility and community needs. At a high level, the utility microgrid controller serves resilience and reliability use cases by coordinating transitions between grid-connected and islanded states and by managing the system during island operations. This includes control scenarios that require the microgrid controller to use flexible microgrid boundaries, maintain energy balance, coordinate with peer systems, and manage grid-forming (GFM) and grid-following (GFL) distributed energy resources (DER). In order to evaluate these functional enhancements, microgrid controller test plans must also be developed to ensure that the implemented controllers provide adequate performance. This report provides MGC test plans for both island operation and transition functions. The functions covered in this report include feeder level energy management, island constraint management, secondary voltage and frequency control, black start, and synchronized reconnection. This second edition update also includes results from applying the tests to a commercial utility microgrid controller. These results evaluate the performance and reliability of the controller under various operational scenarios. It identifies specific areas where the controller excels and highlights gaps that need to be addressed for future enhancements. The application of these test plans on real-world system behavior provides insights on commercial equipment readiness for field deployment. These test cases can be applied to utility-managed microgrid controllers that exclusively manage utility-owned equipment; the tests also apply to third-party managed microgrid controllers that coordinate with utility- and customer-owned equipment. The report can also be used by technology developers and project developers in industry to evaluate control strategies and performance characteristics for community microgrid controllers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluation of Thermal & Mechanical Properties of Additively Manufactured Monolithic SiC for Solar Receiver Applications

Increasing the operating temperatures of solar receivers is paramount to the efficiency of concentrated solar thermal (CST) and solar power (CSP) systems. Owing to its high temperature stability combined with excellent thermal and optical properties, SiC has been the material of choice for application in high-temperature solar receivers. State-of-the-art SiC volumetric concentrating solar air receivers such as the honeycomb design have successfully demonstrated in field exit air temperatures approaching 800oC. However, a successful application of CST systems for the decarbonization of heat reliant industrial sectors requires significant increases in the temperature capability of SiC receiver technology. Supported by an award from the Solar Technology Office (SETO), US Department of Energy (DOE), GE Research in collaboration with Heliogen Holdings Inc, is engaged in the development of an ultra-High Operating Temperature SiC-matrix Solar Thermal Air Receiver (HOTSSTAR) enabled by additive manufacturing. The program objective is to design and demonstrate a techno-economically viable SiC air receiver technology that can achieve exit air temperatures up to 1100oC for CST applications. We report and discuss the results of our testing and evaluation of thermal and mechanical properties of reaction-bonded SiC fabricated via binder jet printing to support the receiver component design, development, and analyses.

14 SOLAR ENERGY↗

Development of A Hardware-In-the-Loop (HIL) Testbed for Cyber-Physical Security in Smart Buildings

As smart buildings move towards open communication technologies, providing access to the Building Automation System (BAS) through the building's intranet, or even remotely through the Internet, has become a common practice. However, BAS was historically developed as a closed environment and designed with limited cyber-security considerations. Thus, smart buildings are vulnerable to cyber-attacks with the increased accessibility. This study introduces the development and capability of a Hardware-in-the-Loop (HIT) testbed for testing and evaluating the cyber-physical security of typical BASs in smart buildings. The testbed consists of three subsystems: (1) a real-time HIL emulator simulating the behavior of a virtual building as well as the Heating, Ventilation, and Air Conditioning (HVAC) equipment via a dynamic simulation in Modelica; (2) a set of real HVAC controllers monitoring the virtual building operation and providing local control signals to control HVAC equipment in the HIL emulator; and (3) a BAS server along with a web-based service for users to fully access the schedule, setpoints, trends, alarms, and other control functions of the HVAC controllers remotely through the BACnet network. The server generates rule-based setpoints to local HVAC controllers. Based on these three subsystems, the HIL testbed supports attack/fault-free and attack/fault-injection experiments at various levels of the building system. The resulting test data can be used to inform the building community and support the cyber-physical security technology transfer to the building industry.

Li, Guowen↗

NRAP-Open-IAM: NRAP Open Source Integrated Assessment Model

Note: This is the last version (a2.6.1) of NRAP-Open-IAM released during NRAP Phase II in 2022. The latest version of NRAP-Open-IAM is available here: https://edx.netl.doe.gov/dataset/phase-iii-nrap-open-iam NRAP-Open-IAM is an open-source software product that enables quantification of containment effectiveness and leakage risk at storage sites in the context of system uncertainties and variability. NRAP-Open-IAM represents the next-generation in a line of systems-based computational models developed for quantitative geological carbon storage (GCS) risk assessment. The model comprises a set of reduced-order and analytical models of various components of the GCS system, potential leakage pathways, receptors of concern including impact to groundwater resources and the atmosphere, a framework to support stochastic simulation, time stepping, uncertainty quantification, other analytical functionality for scenario and risk-performance evaluation, and a basic graphical user interface to support scenario development, data input simulation definition, and basic post-processing and results display. As the NRAP Open-IAM functionality continues to evolve, we continue to add to its capability to develop quantitative, probabilistic, and time-dependent profiles of the evolution of risk at a GCS site and evaluate the influence of uncertain parameters on uncertainty in predicted risk. It can be used to quantify the dynamics of reservoir saturation plume and pressure-affected area, for evaluation of the area of potential groundwater impact (i.e., Area of Review) and monitoring requirements to support cost and regulatory analysis, and for consideration of different post-injection site care and closure scenarios. This submission contains the current version of NRAP-Open-IAM available for evaluation and testing. To use the NRAP-Open-IAM, download the source code (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/4c24a3da-3b40-4ffe-9892-c807ae9f8760) then open the NRAP-Open-IAM user's guide (https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669) to read more about the tool. Installation instructions for Windows, Mac, and Linux can be found in the "installers" folder of the extracted NRAP-Open-IAM folder and describe setup of environment (e.g., Python libraries) needed for proper work of the tool. Test of installation can be done by running "python openiam_setup_tests.py" in the "setup" folder. The installation test also runs a test suite to see if the NRAP-Open-IAM has been installed correctly. To run the test suite separately, run "python iam_test.py" in the "test" folder. User's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/8b27335a-343c-4836-b8a3-3ad0bdc9e669 Developer's guide: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/3bc6ee7d-609d-4eb6-80ba-fa6130ee0313 Reservoir simulation data used in some examples distributed with NRAP-Open-IAM: - Kimberlina: https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/eb62cece-61b2-4037-9b6d-32407dde2ab8 - Kimberlina (compartmentalized): https://edx.netl.doe.gov/dataset/08f396c8-bc5f-44ad-a028-6e98a6ea6d70/resource/366f9530-3b32-4b84-affe-ab2df1d9a8b5 - FutureGen 2.0: https://edx.netl.doe.gov/dataset/futuregen-2-0-1008-simulation-reservoir-lookup-table NRAP-Open-IAM GitLab repository: https://gitlab.com/NRAP/OpenIAM Related publications: - Bacon, D., Yonkofski, C., Brown, C., Demirkanli, D. and Whiting, J., 2019. Risk-based post injection site care and monitoring for commercial-scale carbon storage: Reevaluation of the FutureGen 2.0 site using NRAP-Open-IAM and DREAM. International Journal of Greenhouse Gas Control 90: 102784. - Bacon, D. Demirkanli, D., and White, S., 2020. Probabilistic risk-based Area of Review (AoR) determination for a deep-saline carbon storage site. International Journal of Greenhouse Gas Control 102: 103153. - Harp, D., Oldenburg, C., and Pawar, R., 2019. A metric for evaluating conformance robustness during geologic CO2 sequestration operations. International Journal of Greenhouse Gas Control 85: 100-108. - Lackey, G., Vasylkivska, V., Huerta, N., King, S., and Dilmore, R., 2019. Managing well leakage risks at a geologic carbon storage site with many wells, International Journal of Greenhouse Gas Control, 88 :182-194. - Vasylkivska, V., Dilmore, R., Lackey, G., Zhang, Y., King, S., Bacon, D., Chen, B., Mansoor, K., and Harp, D., 2021. NRAP-Open-IAM: A flexible open-source integrated assessment model for geologic carbon storage risk assessment and management, Environmental Modelling & Software, 143: 105114. Presentations: - Chen, B., Harp, D., and Pawar, R., A data assimilation approach (ES-MDA) coupling with NRAP-Open-IAM for quantifying uncertainty reduction in geological CO2 sequestration. AGUFM 2019: T44A-02. - Chen, B., and Harp, D., Improving risk analysis precision for geologic CO2 sequestration by quantifying the uncertainty reduction before and after acquiring monitoring data. 14th Greenhouse Gas Control Technologies Conference, Melbourne, Australia, 2018, pp. 21-26. - Harp, D., National Risk Assessment Partnership Task 2: Containment Assurance. No. LA-UR-19-28654, Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2019. - Vasylkivska, V., King, S., Bacon, D., Harp, D., Chen, B., Mansoor, K., Onishi, T., Yang, Y., Zhang, Y., and Keating, E., NRAP-Open-IAM: An open-source integrated assessment model, poster, Mastering the Subsurface Through Technology Innovation, Partnerships and Collaboration: Carbon Storage and Oil and Natural Gas Technologies Review Meeting, Pittsburgh, PA, August 13-16, 2018. - Vasylkivska, V., Lackey, G., King, S., Wentworth, A., Huerta, N., Creason, C., DiGiulio, J., Yang, Y., and Dilmore, R., Long-term risk analysis of a geologic CO2 storage project during the post-injection period, SIAM Conference on Computational Science and Engineering, Spokane, WA, February 25-March 1, 2019. - Vasylkivska, V., Overview of the NRAP-Open-IAM tool for carbon storage (beta release), 2019 Annual NRAP Tool Users Meeting, Pittsburgh, PA, August 27, 2019. - Vasylkivska, V., Bacon, D., Chen, B., Dilmore, R., Harp, D., King, S., Lackey, G., Lindner, E., Liu, G., Mansoor, K. and Zhang, Y., NRAP-Open-IAM: A new, open-source code for integrated assessment of geologic carbon storage containment effectiveness and leakage risk, poster, American Geophysical Union Fall Meeting 2020 (virtual meeting), December 2020. - Vasylkivska, V., NRAP open-source integrated assessment model and relevant application, oral presentation, NRAP workshop "NRAP Tools for Geologic Carbon Storage Risk-Based Decision Making" held in conjunction with Groundwater Protection Council (GWPC) 2021 Annual Forum (virtual meeting), Salt Lake City, UT, September 2021. - Vasylkivska, V., NRAP-Open-IAM: open-source integrated assessment model, digital poster/demonstration, software demonstration session, 2022 Carbon Management Project Review Meeting, August 16, 2022

AoR↗

Panel Session 108: Technology Transfer and Commercialization: Innovative Solutions for Global Opportunities

This panel focus was to build the connection between innovative solutions and the various industries looking for more efficient methods, products, and processes in Tech Transfer and Commercialization. This panel had interest across the entire conference base, whether they are encountering a challenge, introducing an innovative solution, or are the host that is trying to get from a pure research / Research, Development, Demonstration, Testing, and Evaluation solution to one that is commercially viable and robust enough for long term and/or high risk deployment scenarios and which will support greater chance of success and positive outcomes. Panelists with presentations: Practical, Successful Technology Transfer (Laurie Judd); Technology Needs for Clean-up of Mercury Contamination on the Oak Ridge Reservation (Renee Echols); US DOE Office of Technology Transitions (Kyle Wiley); Technology Transfer in Support of Delivering Clean-up Missions (Kristan Schruder); Mission to Market (J. Chris Ford)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Human and Technology Integration Evaluation of Advanced Automation and Data Visualization

While the existing United States (U.S.) light water reactors are highly reliable, safe, and provide a significant proportion of carbon-free electricity, the cost of operating and maintaining them has become less competitive compared to other electricity generating sources. The reason for the gap in operating and maintenance (O&M) costs can be at least in part attributed to the advent of new digital technologies that other electricity generating industries are currently using. Advanced capabilities including digital instrumentation and control (I&C) systems, advanced automation and analytics, and greater span of data integration (i.e., connectedness) across these non-nuclear plants has transformed the way work is performed and ultimately given them a competitive advantage in terms of the cost required for operating, maintaining, and supporting them. To reduce O&M cost and address obsolescence of the aging I&C infrastructure of the existing U.S. light water reactors, the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Plant Modernization Pathway is conducting targeting multidisciplinary research that 1) delivers a sustainable business model to enable a cost-competitive U.S. nuclear industry and 2) is developing technology modernization solutions that address aging and obsolescence challenges. The work described in this report supports these two objectives and describes the demonstration of human and technology integration across recent industry collaborations to support their large-scale digital I&C modifications. This technical report describes the demonstration of the human and technology integration methodology in performing full-scale performance-based human-in-the-loop tests to evaluate plant-specific advanced automation and data visualization applications within these collaborators’ digital modifications. This technical report also documents future applications of human and technology integration that expand beyond main control room modernization and digital I&C upgrades, which have been a central focus to date. Thus, this technical report discusses how to implement human and technology integration across new business opportunities and how to develop an evaluation plan that defines measures and criteria, and documents key assumptions to support full plant modernization.

99 GENERAL AND MISCELLANEOUS↗

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

Countering Weapons of Mass Destruction (CWMD) Device Cybersecurity Characterization Process and Profile

Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state, and to rapidly recover operational capabilities for essential functions after a successful attack. The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.” As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Countering Weapons of Mass Destruction (CWMD) Device Cybersecurity Characterization Process and Profile

Countering Weapons of Mass Destruction (CWMD) recognizes that threats in the cyberspace domain continue to grow, which requires CWMD devices and supporting systems to be both cybersecure (ability to protect or defend from cyber-attacks) and resilient (ability to maintain required capability in the face of adversity) to cyber threats. The CWMD cybersecurity characterization approach in this document supports existing cyber resilience activities within the Acquisition Lifecycle Framework. Similarly, this process supports existing Department of Homeland Security Cyber Resilience Test and Evaluation activities, which consist of iterative processes, starting at the initiation of system acquisition and continuing throughout the entire device and system life cycle. Cyber resilience is the ability of an information system to continue to operate while under attack, even if in a degraded or debilitated state,1 and to rapidly recover operational capabilities for essential functions after a successful attack.2 The goal of the security characterization task for CWMD is to support the development of a CBRN device-dependent profile that aligns with device network capabilities and maps to recommended security controls to create a characterization security profile impact levels. The impact levels for CWMD devices should be characterized as Low (L), Moderate (M), High (H) to align with the low, moderate, high control baselines. To estimate the impact levels, the device’s security-related attributes are translated into the security objectives: Confidentiality (C), Integrity (I), and Availability (A), known as the CIA triad. The potential impact for each device can be L, M, H, for devices that connect and transmit different types of data and may have different impact levels. National Institute of Standards and Technology Federal Information Processing Standards Publication 199 states, “the potential impact values assigned to the respective security objectives shall be the highest value from among those security categories that have been determined for each type of information resident on the information system.”3 As CWMD is determining the cybersecurity impact levels of CBRN devices based on network connections and data transfers, the impact levels are aligned with the associated attributes of network connections and communications. For example, if the device system is connected to a wireless network and transmits different data types based on the confidentiality of the data, the highest impact value for each security objective should represent the device’s CIA impact level. This document is intended to be used by test managers, test team, and program managers.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Target Detection via Cognitive Radars Using Change-Point Detection, Learning, and Adaptation

Many radar detection algorithms that assume a stationary environment (clutter) have been proposed and analyzed over the years. However, in practice, changes in the nonstationary environment can perturb the parameters of the clutter distribution, or even alter the clutter distribution family, which can greatly deteriorate the target detection capability. To avoid such potential performance degradation, cognitive radar systems are envisioned which are required to rapidly realize the nonstationarity, accurately learn the new characteristics of the environments, and adaptively update the detector. In this paper, aiming to develop a fully cognitive radar for target detection in nonstationary environments, we propose a unifying framework that integrates (i) change-point detection of clutter distributions by using a data-driven cumulative sum (CUSUM) algorithm and its extended version, (ii) learning/identification of clutter distribution by applying sparse theory and kernel density estimation methods, and (iii) adaptive target detection by automatically modifying the likelihood-ratio test and corresponding detection threshold. Further, with extensive numerical examples, we demonstrate the achieved improvements in detection performance due to the proposed framework in comparison to a nonadaptive case, an adaptive matched filter (AMF) method, and the clairvoyant case. Herein, we also use Wilcoxon rank-sum tests to evaluate the statistical significance of the performance improvements

42 ENGINEERING↗

Evaluation of smart charging for electric vehicle-to-building integration: A case study

Higher electric vehicle (EV) adoption will stress the importance of demand flexibility to achieve more economic, efficient, and reliable grid operation. Charging technologies will be paramount in shifting temporally to better fit the variable generation of wind and solar. As such, analysis is warranted on the benefits of EV charge scheduling with respect to installation cost, operation cost, difficulty of implementation, and grid flexibility. We tackle this by analyzing the cost savings of implementing an EV charge scheduling infrastructure to reduce demand charges and installation costs. In this paper, we analyze a case study for operation of 16 level 2 chargers and 1 fast charger for two different building types. We then evaluate various test phases for controlling building and charging loads using an adaptive charging network (ACN) algorithm to characterize the ACN’s potential to reduce overall project cost.

30 DIRECT ENERGY CONVERSION↗

A framework for strategic discovery of credible neural network surrogate models under uncertainty

The widespread integration of deep neural networks in developing data-driven surrogate models for high-fidelity simulations of complex physical systems highlights the critical necessity for robust uncertainty quantification techniques and credibility assessment methodologies, ensuring the reliable deployment of surrogate models in consequential decision-making. Here, this study presents the Occam Plausibility Algorithm for surrogate models (OPAL-surrogate), providing a systematic framework to uncover predictive neural network-based surrogate models within the large space of potential models, including various neural network classes and choices of architecture and hyperparameters. The framework is grounded in hierarchical Bayesian inferences and employs model validation tests to evaluate the credibility and prediction reliability of the surrogate models under uncertainty. Leveraging these principles, OPAL-surrogate introduces a systematic and efficient strategy for balancing the trade-off between model complexity, accuracy, and prediction uncertainty. The effectiveness of OPAL-surrogate is demonstrated through two modeling problems, including the deformation of porous materials for building insulation and turbulent combustion flow for ablation of solid fuels within hybrid rocket motors.

42 ENGINEERING↗

Self-reported health impacts of do-it-yourself air cleaner use in a smoke-impacted community

Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM 2.5 ) from smoke. We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM 2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM 2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM 2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the ring tension test (RTT) for robust determination of material strengths

The ring tension test (RTT) is an experimental method for determining mechanical behavior in a material’s circumferential or hoop direction. It is a crucial test for testing anisotropic materials with tube geometry, such as nuclear fuel cladding or irradiated pipes. Several RTT configurations exist, each with their own advantages and disadvantages. However, this test is significantly more complex than traditional tensile testing and can be especially sensitive to small differences and inconsistencies in the test setup and geometry, ultimately affecting the derived mechanical properties. Previous research has focused on method development, and little work has been done on understanding the subtle differences between an ideal test and experiments, specifically when the tests are performed on highly irradiated materials in hot cells. In this work, a finite element-based investigation of the RTT is conducted to fill this gap. The two most used test configurations are investigated, comparing their ability to determine accurate material strengths through plastic deformation. Several non-ideal conditions and uncontrollable effects which are likely to occur during experimental testing such as machining tolerances, variations of specimen geometry from nominal dimensions, rotation of specimens and fixturing, and other test setup discrepancies are studied. The sensitivity of measured strengths to these conditions is presented. A mechanics-based approach to describing and correcting raw data to determine actual strengths is also included for one of the configurations, resulting in a robust correction method with highly accurate material strength measurements. Finally, based on these analyses, the hemicylindrical mandrel configuration is recommended with a gauge region oriented at a 45° angle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Processing aluminum alloy with hybrid wire arc additive manufacturing and ultrasonic nanocrystalline surface modification to improve porosity, surface finish, and hardness

Here, in this paper, a novel hybrid wire arc additive manufacturing (WAAM) and ultrasonic nanocrystal surface modification (UNSM) on porosity manipulation and surface properties of aluminum 5356 alloys was studied. The goal is to improve the quality of the WAAM-built part by eliminating bigger pores and reducing its size, reducing surface roughness, and increasing surface hardness. The as-built WAAM and WAAM-UNSM-treated samples were quantitatively studied for porosity using an X-ray micro-computed tomography (μ-CT). The surface roughness was measured on the surface profile of the same samples before and after UNSM treatment. Followed by the Vickers micro-hardness tests to evaluate the hardness modified by the influence of the UNSM treatment. It was found that the bigger pores in the as-built WAAM samples were eliminated and the medium-sized pores were shrunk to almost half the size after the UNSM treatment. Further, the UNSM treatment showed a significant improvement in both surface roughness and hardness on the WAAM Al5356 samples. This experimental work demonstrates the critical advantages of hybrid WAAM-UNSM in improving the qualities of the WAAM processed parts.

Hardness↗

Revealing the complex chemistry of grain boundaries in K-doped BaFe 2 As 2 with atom probe tomography

Iron-based superconductors have attractive properties for high-field applications, but there is a lack of understanding of the effect of grain boundary chemistry on the in-field performance. The near atomic-scale resolution, ppm sensitivity and 3D analysis offered by atom probe tomography make it a powerful tool to investigate the nanoscale structure and chemistry of these defects in fine-grained K-doped BaFe 2 As 2 samples. A computational method to systematically extract and compare the Gibbsian interfacial excess of chemical species across grain boundaries has been explored in this work. The robustness of the method has been tested by evaluating the effects of selected variables on simulated APT datasets. The accuracy and precision of the calculated Gibbsian interfacial excess were found to be stable over a range of analysis conditions: varying grain boundary widths and detection efficiencies, spatial precisions below 1.5 nm, and bin widths between 1.2 and 1.6 nm. For the K-doped BaFe 2 As 2 samples studied, segregation of As, Ba, K and impurities of O, Na, and Sb were found at grain boundaries. The Gibbsian excess values were found to vary widely between different boundaries, showing the complexity of the grain boundary chemistry in this material. Possible links between the observed critical current density (Jc) of these samples and their nano- and micro-structure have also been investigated and discussed.

36 MATERIALS SCIENCE↗

Characterization of advanced nuclear materials under extreme environments

The performance of materials under extreme environments poses important fundamental questions about the behavior of condensed matter under far-from-equilibrium conditions. These conditions create challenges in materials design, testing and evaluation. One important aspect of advancing nuclear power is the discovery and investigation of new classes of materials able to withstand the harsh environments in nuclear reactors. However, investigating and understanding the performance of these materials requires sophisticated tools and characterization techniques and skills. Furthermore, the goal of this special issue is to present recent research on the characterization of the response of candidate advanced nuclear materials to extreme environments.

36 MATERIALS SCIENCE↗