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At least 1,045 records · Page 58

Simulating the Impact of Dynamic Rerouting on Metropolitan-scale Traffic Systems

The rapid introduction of mobile navigation aides that use real-time road network information to suggest alternate routes to drivers is making it more difficult for researchers and government transportation agencies to understand and predict the dynamics of congested transportation systems. Computer simulation is a key capability for these organizations to analyze hypothetical scenarios; however, the complexity of transportation systems makes it challenging for them to simulate very large geographical regions, such as multi-city metropolitan areas. In this article, we describe enhancements to the Mobiliti parallel traffic simulator to model dynamic rerouting behavior with the addition of vehicle controller actors and vehicle-to-controller reroute requests. The simulator is designed to support distributed-memory parallel execution using discrete event simulation and be scalable on high-performance computing platforms. We demonstrate the potential of the simulator by analyzing the impact of varying the population penetration rate of dynamic rerouting on the San Francisco Bay Area road network. Using high-performance parallel computing, we can simulate a day in the San Francisco Bay Area with 19 million vehicle trips with 50 percent dynamic rerouting penetration over a road network with 0.5 million nodes and 1 million links in less than three minutes. We present a sensitivity study on the dynamic rerouting parameters, discuss the simulator’s parallel scalability, and analyze system-level impacts of changing the dynamic rerouting penetration. Furthermore, we examine the varying effects on different functional classes and geographical regions and present a validation of the simulation results compared to real-world data.

97 MATHEMATICS AND COMPUTING↗

Verification and Validation of the STAT7 Code

This document presents the verification and validation of the STAT7 Version 1.0 code which has been developed to perform the steady-state thermal hydraulic safety calculation of the MIT Research Reactor required upon conversion of the reactor from highly enriched uranium fuel to low- enriched uranium fuel. The key capabilities of the code including the statistical processing, water property generation, and thermal hydraulic solution are verified independently. While the first two capabilities are checked using statistical tests and NIST data tables, each component of the thermal hydraulic solution is verified using simple geometry test problems. The comparison between results obtained by the code and hand calculations on these problems shows that each of these components work correctly. Additionally, a comprehensive comparison between STAT7 Version 1.0 and PLTEMP/ANL Version 4.2 calculations for a five-channel test problem is performed for the validation. The good agreement between the obtained results for all thermal hydraulic parameters belonging to the fuel core region is achieved. An issue in bypass flowrate calculation was detected when both fin-friction and bypass flow calculations are involved. This problem can be corrected in a later version of the code. However, it does not affect the application of STAT7 as it has been used to date where the flow distribution in the core region and bypass channel is specified as an input parameter.

97 MATHEMATICS AND COMPUTING↗

“Experimental investigation of the governing parameters of atmospheric ice nucleation using field-collected and laboratory generated aerosol particles and its application in cloud resolving models” (Final Report)

The objective of this research project is to improve our understanding of the role of aerosol particles acting as ice-nucleating particles (INPs) which in turn define the mixed-phase and cirrus cloud radiative properties and thus climate. The focus is placed on how the physicochemical particle population properties determine the particles’ ability to initiate ice nucleation. This research project combined micro-spectroscopic particle analysis, experimental ice nucleation studies, and model sensitivity studies to advance our predictive capability of the formation of mixed-phase and cirrus clouds. These project activities have led to new ice nucleation data from laboratory generated and ambient (authentic) aerosol particles furthering process-level understanding, insights in the role of organic aerosol in ice formation, and advancements in the interpretation and parameterization of ice nucleation.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Modeling and Nuclear Data Needs for Active Neutron Interrogation

This document is the primary deliverable for a scoping study proposed to DOE National Laboratory Announcement Number LAB 19-2114 in the NNSA research area. The study supports user applications employing active neutron interrogation by providing a science plan to improve the modeling capability and the nuclear data that radiation transport codes use. Users rely on the accuracy of the elastic scattering and non-elastic cross-sections spanning thermal energies to 14 MeV (and higher in some cases) for modeling the neutron transport through complex geometries of materials potentially composed of many elements. While the elastic scattering cross-section data are accepted for all commonly occurring elements, the non-elastic cross-section data and the associated emission data include reaction channels that require attention. The study focused on the non-elastic reactions that emit secondary, also known as prompt, gammas with the premise that many users would benefit from improved modeling of these reactions. Many users develop material assay technologies based upon gamma signatures from radiative capture, inelastic scattering, and reactions on low-Z isotopes emitting multiple particles, so the nuclear data gaps, modeling deficiencies, and recommendations for addressing the shortfalls were assessed for these reactions. Fission gammas were excluded from this study because there are other efforts underway to address known shortfalls. Follow-on efforts that successfully execute the recommendations will tangibly improve to the ability to model gamma signatures and backgrounds for user applications, such as controlled substance detection, oil-well logging, and space exploration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advanced Simulation and Computing (FY22 Implementation Plan Rev 0)

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY22. The Initial IP, effective , should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Workshop on Manufacturing and Integration Challenges for Analog and Neuromorphic Computing

The U.S. Department of Energy’s (DOE’s) Advanced Manufacturing Office (AMO) held its third virtual workshop on Semiconductor R&D for Energy Efficiency on August 11-13, 2021. This public workshop – titled “Manufacturing and Integration Challenges for Analog and Neuromorphic Computing” – brought together more than 180 leading scientific and technical experts to identify challenges and opportunities to improve manufacturing capabilities for analog and neuromorphic computing architectures to significantly increase energy efficiency of microelectronic devices. The workshop featured perspectives of researchers from national laboratories, universities, government agencies, and industry with expertise in novel and emerging devices, processes, and metrology and characterization. This workshop is intended to inform an AMO research, development, demonstration, and deployment (RDD&D) plan to significantly reduce semiconductor energy use by 2030. It was co-sponsored by the Semiconductor Research Corporation (SRC) and the DOE Office of Science’s Advanced Scientific Computing Research (ASCR).

97 MATHEMATICS AND COMPUTING↗

Development of self-sensing materials for extreme environments based on metamaterial concept and additive manufacturing

Structural health monitoring of an engineered component in a harsh environment is critical for multiple DOE missions including nuclear fuel cycle, subsurface energy production/storage, and energy conversion. Supported by a seeding Laboratory Directed Research & Development (LDRD) project, we have explored a new concept for structural health monitoring by introducing a self-sensing capability into structural components. The concept is based on two recent technological advances: metamaterials and additive manufacturing. A self-sensing capability can be engineered by embedding a metastructure, for example, a sheet of electromagnetic resonators, either metallic or dielectric, into a material component. This embedment can now be realized using 3-D printing. The precise geometry of the embedded metastructure determines how the material interacts with an incident electromagnetic wave. Any change in the structure of the material (e.g., straining, degradation, etc.) would inevitably perturbate the embedded metastructures or metasurface array and therefore alter the electromagnetic response of the material, thus resulting in a frequency shift of a reflection spectrum that can be detected passively and remotely. This new sensing approach eliminates complicated environmental shielding, in-situ power supply, and wire routing that are generally required by the existing active-circuit-based sensors. The work documented in this report has preliminarily demonstrated the feasibility of the proposed concept. The work has established the needed simulation tools and experimental capabilities for future studies.

36 MATERIALS SCIENCE↗

ASC FY2023 Implementation Plan Revision 0

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

97 MATHEMATICS AND COMPUTING↗

Development of Microreactor Automated Control System (MACS): Surrogate Plant-level Modeling and Control Algorithms Integration

This report discusses progress on the modeling and integration task as part of the development of Microreactor Automated Control System (MACS). What follows is a discussion of the software tools used to develop a surrogate microreactor plant-level model, MACS module development, and a summary of the findings from integration with a hardware-in-the-loop (HIL) setup at Idaho National Laboratory (INL). Oak Ridge National Laboratory worked with INL to understand available hardware at INL (such as existing control platforms). With this information and using a preliminary framework for MACS with software interfaces defined, surrogate models and initial automated control algorithms were created for integration into the hardware to provide a HIL demonstration platform for MACS. Available reduced order reactor models that leverage existing microreactor neutronics and thermal hydraulics models have been integrated in the surrogate plant-level model. The surrogate model has been evaluated for sensitivity of all parameters and the MACS software modules (including the surrogate model) have been demonstrated to interact with the hardware. The integration, however, pointed to the need for further improvements to the framework—and specifically improvements to the interfaces to ensure that the HIL simulator is capable of longer-term stable operation with MACS in the loop. These improvements will be the focus of future research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, 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 work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and 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 from the original test base. While the focus remains on the U.S. nuclear weapons program, 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 nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗

Radiation-Hardened GaN HEMT and Cell Design, Modeling, and Fabrication for Nuclear Instrumentation Applications

Recent advances in nuclear power generation technologies show great promise for efficient, safe generation of carbon-free power in the near future. Consequently, many new generation reactor designs are being pursued by government and industry groups, including both fission- and fusion-based technologies. Radiation- and temperature-tolerant sensor technology continues to advance, yet development of the electronics/instrumentation technologies suitable for these environments have fallen behind. Industry has adequately addressed harsh environment electronics needs for low earth orbit satellites, but the much more extreme conditions associated with electronics placed near or in a reactor core remain unaddressed. This project investigates the use of gallium nitride (GaN) circuit technology to address the unique needs for sensor interface electronics and communications in reactor environments. This report provides a summary of the first year’s project activities related to developing and optimizing devices and circuits for this GaN high electronic mobility transistor (HEMT) process. Activities reported include multiple analog and digital circuit designs simulated using custom Verilog-A models generated from measured GaN devices fabricated in the target process. Digital circuit designs included fundamental logic circuits such as an inverter, NAND, NOR, AND and OR gates, as well as a 5-stage ring oscillator. Each design was simulated using an open-source SPICE simulator, and an integrated circuit layout was produced of each design for use in future fabrication. Analog circuit designs focused on the fundamental building blocks to be used to construct sensor interface and communications circuits. These included current mirrors, matched differential pairs, and a Gilbert cell mixer design, each with an associated integrated circuit layout. Layout tools used for these designs included two open-source packages—KLayout and Magic—which were customized for specific use with the OSU GaN process layers. Design rules and preliminary device extraction capabilities were built for the Magic tool to enable device extraction and subsequent netlist generation for SPICE simulation. Finally, future research directions for year two are summarized. When the year-two directions are implemented, the project will be in position to advance the state of the art in electronics for near- or in-reactor sensor interfacing and communications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Simulation and Computing: FY25 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

97 MATHEMATICS AND COMPUTING↗

Real-Time Testbed for Smart Grid Recloser Controller

The growing need for a low voltage recloser has become apparent due to the rise in requirements for a smart grid. This includes more detailed management of power flow forward (towards load) and backward (towards generation), source synchronization in real time, more indepth fault responses, and the use of green energy. The SEL-651R-2 relay is a device that can manage these needs, especially in fault response and synchronization, and is commonly used in systems called microgrids. Microgrids are distribution level systems that are able to operate separated from the main grid, are typically installed much closer to the load(s), and are fed by distributed energy resources (DERs), such as wind, solar or diesel generators. The SEL-651R-2 is normally used in the field with presets operative settings, but the Western Michigan University (WMU) Center for Interdisciplinary Research on Secure, Efficient and Sustainable Energy Technology (WMU InterEnergy Center) wished to test this device in its range of capabilities for microgrid application. A Hardware-In-the-Loop (HIL) testbed was implemented and used through the Real Time Digital Simulator (RTDS) using the RSCAD software to test the SEL-651R-2's use cases and functions. The testbed includes a microgrid with interconnection to a larger main grid, and the relay is meant to control the recloser at the point of common coupling (PCC) between the main grid and microgrid. The testbed shows how basic protections, reclosing, and synchronization checks function when handling faults that affect both the microgrid and the main grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems (Final Report for AEOLUS)

The AEOLUS Center is dedicated to developing a unified optimization-under-uncertainty framework for: (1) learning predictive models from data; and (2) optimizing experiments, processes, and designs governed by these models, all driven by complex, uncertain energy systems. AEOLUS addresses the critical need for principled, rigorous, scalable, and structure-exploiting capabilities for exploring parameter and decision spaces of complex forward simulation models. This report summarizes the key highlights of our research during the period of performance.

97 MATHEMATICS AND COMPUTING↗

Turbulence dissipation rate estimated from lidar observations during the LAPSE-RATE field campaign

The International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) hosted a flight week in July 2018 to demonstrate unmanned aircraft systems' (UASs) capabilities in sampling the atmospheric boundary layer. This week-long experiment was called the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. Numerous remotely piloted aircraft and ground-based instruments were deployed with the objective of capturing meso- and microscale phenomena in the atmospheric boundary layer. The University of Oklahoma deployed one Halo Streamline lidar, and the University of Colorado Boulder deployed two WindCube lidars. In this paper, we use data collected from these Doppler lidars to estimate turbulence dissipation rate throughout the campaign. We observe large temporal variability of turbulence dissipation close to the surface with the WindCube lidars that is not detected by the Halo Streamline. However, the Halo lidar enables estimating dissipation rate within the whole boundary layer, where a diurnal variability emerges. We also find a higher correspondence in turbulence dissipation between the WindCube lidars, which are not co-located, compared to the Halo and WindCube lidar that are co-located, suggesting a significant influence of measurement volume on the retrieved values of dissipation rate.

WIND ENERGY↗

Electric Motor Thermal Management

During FY 2022, NREL efforts focused on supporting collaborations with external research partners within the Electric Drive Technologies research consortium. The poster highlights collaborations with SNL, ORNL, and Georgia Tech. The collaboration with SNL utilized NREL's experimental capabilities to mechanically characterize SNL-provided material samples for motor applications. The collaboration with ORNL supported efforts to refine the design of a high-speed, non-heavy-rare-earth outer-rotor motor. The collaboration with Georgia Tech focused on a novel cooling technique for electric machines. NREL supported the effort by leading the thermal analysis and design of advanced machines.

ADVANCED PROPULSION SYSTEMS↗

Implementation and testing of the GPT sensitivities in TRIPOLI-4

Computing the sensitivity of given reactor parameters with respect to nuclear data is mandatory in key applications such as the assessment of reactor safety or core design. In recent years, the development of Monte Carlo methods capable of estimating sensitivity coefficients based on the Standard or Generalized Perturbation Theory (SPT and GPT, respectively) has attracted intensive research efforts, especially in view of having reference golden standard simulations to be compared to faster but approximate deterministic calculations. Following our previous implementation and validation of the SPT functionalities in the Monte Carlo TRIPOLI-4, devoted to the sensitivity of the k eigenvalue, in this work we detail the development of GPT methods for ratios of reaction rates, and validate them against a few relevant benchmark results. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗