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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54

Modeling and Simulation Tool to Improve Urban Search Planning (NA22 Final Report)

The venture project Tool to Improve Urban Search Planning (LL14-V-Urban Search Planning ToolPD3RS) supported two major types of effort: 1) development of a software prototype search planning tool, with the goal of transitioning the tool to operational users for evaluation and possible adoption; 2) enabling research to better understand the radiation characteristics of an urban environment, with implications for deployment of radiation detection systems in that environment. The first effort has resulted in prototype software, Optimization Planning Tool for Urban Search (OPTUS), that has been distributed to a limited set of potential users, including users within the NNSA emergency response community. The second effort supported various research topics including high fidelity radiation transport modeling in urban environments, measurement campaigns for model validation, development of vehicle-based high purity germanium (HPGe) detector systems and supporting data analysis, and computational capabilities for archiving and managing large data sets. While some of these related efforts have informed the models and software design of the OPTUS tool, in large part they pursued more basic research, some of which has evolved into separate DNN R&D projects. Project performers included Oak Ridge National Laboratory (ORNL), Lawrence Berkeley National Laboratory (LBNL) and the Remote Sensing Laboratory (RSL), in addition to Lawrence Livermore Laboratory (LLNL), the project lead. The project also supported university research, including several internships at the laboratories.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Visualization of the Eastern Renewable Generation Integration Study: Preprint

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the U.S. Eastern Interconnection and Quebec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions. state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Battery Thermal Characterization

A well-designed thermal management system is critical to the life and performance of electric-drive vehicles (EDVs) hybrids (HEVs), plug-in hybrids (PHEVs), and all-electric vehicles (EVs). Temperature and temperature uniformity both significantly affect the performance, lifespan, and safety of vehicle energy storage devices. NREL conducts thermal management research and development (R&D) to optimize battery performance and extend useful life. A recognized leader in battery thermal analysis and characterization, NREL evaluates electrical and thermal performance of battery cells, modules, and packs, full energy storage systems, and the interaction of these systems with other vehicle components. The lab's performance assessments factor in the design of the thermal management system, the thermal behavior of the cell, battery lifespan, and safety of the energy storage system, as well as full integration into a vehicle. The lithium-ion (Li-ion) batteries found in most of today's electric-drive vehicles are smaller and more lightweight than previous nickel-metal hydride (NiMH) technology, but they are also more sensitive to overheating, overcharging, and extreme spikes in temperature known as thermal runaway. High temperatures diminish battery life and increase battery replacement costs, while low temperatures decrease battery power and capacity, all of which impact vehicle range, performance, and affordability. NREL's breakthrough research is focused on reducing thermal barriers to achieve more uniform temperatures. NREL uses its R&D 100 Award-winning Isothermal Battery Calorimeters, the only instruments in the world capable of such precise thermal measurements, for much of this research. Calorimeter readings are paired with thermal imaging of batteries using infrared cameras to evaluate battery temperature distribution. In addition, NREL is working with industry to develop computer-aided engineering software tools to optimize thermal management of batteries. NREL's analysis for the U.S. Advanced Battery Consortium (USABC) show that optimized thermal management can increase battery power by more than 10%. Without proper thermal management, an EDV battery can last more than 10 years in a temperate climate, like in Minnesota, but only 7 years in a hot climate, such as in Arizona. In extreme instances, battery overheating can pose safety hazards, including fires. Performance: Maintaining desired temperature ranges is critical in optimizing EDV battery storage capacity, lifespan, and performance, and eventually impacts cost and consumer acceptance. NREL's breakthrough research focuses on achieving more uniform temperatures while a vehicle is in motion and actively generating heat, as well as when it is parked and exposed to ambient temperatures over prolonged periods of time. Safety: Most energy storage systems deliver maximum performance at higher temperatures. However, this extreme heat can overload systems and create dangerous conditions. NREL evaluation helps to more effectively regulate thermal characteristics, providing greater safeguards and stronger performance. NREL has invented a device that emulates internal short circuits in batteries to better understand how to prevent future failures and related hazards.

25 ENERGY STORAGE↗

Architecture for Web-Based Visualization of Large-Scale Energy Domains: Preprint

With the growing penetration of inverter-based distributed energy resources and increased loads through electrification, power systems analyses are becoming more important and more complex. Moreover, these analyses increasingly involve the combination of interconnected energy domains with data that are spatially and temporally increasing in scale by orders of magnitude, surpassing the capabilities of many existing analysis and decision-support systems. We present the architectural design, development, and application of a high-resolution web-based visualization environment capable of cross-domain analysis of tens of millions of energy assets, focusing on scalability and performance. Our system supports the exploration, navigation, and analysis of large data from diverse domains such as electrical transmission and distribution systems, mobility and electric vehicle charging networks, communications networks, cyber assets, and other supporting infrastructure. We evaluate this system across multiple use cases, describing the capabilities and limitations of a web-based approach for high-resolution energy system visualizations.

grid modernization↗

Comparison of 1D and 2D particle-in-cell simulations for DC magnetron sputtering discharges

One-dimensional and two-dimensional particle-in-cell (PIC)/Monte Carlo collision simulations are performed for a balanced direct current magnetron sputtering (DCMS) discharge. The plasma parameters obtained by both simulations above the target racetrack share similar features and magnitudes under similar discharge intensities, i.e., similar local discharge current densities. The commonly observed high-energy tail of electron energy distribution in DCMS discharges is reproduced in both simulations. Additionally, the accuracy and applicability of using onedimensional simulations to qualitatively investigate the characteristics of balanced DCMS discharge are confirmed. In terms of capturing the key physical mechanisms in DCMS, one-dimensional PIC simulation is an efficient method, which could largely alleviate the computational expense and preserve the physical fidelity of modeling results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Implementation of a Spacer Grid Rod Thermal-Hydraulic Reconstruction (ROTHCON) Capability into the Thermal-Hydraulic Subchannel Code CTF

The Consortium for Advanced Simulation of Light Water Reactors is developing a core simulator capability known as the Virtual Environment for Reactor Applications (VERA) to address nuclear industry challenge problems such as crud-induced power shift (CIPS). The CTF thermal-hydraulic (T/H) subchannel code provides thermal feedback in the coupled neutronics, T/H, crud chemistry simulation that VERA performs. It has been discovered that the coarse meshing approach used by CTF (in which fuel rods are discretized into four azimuthal segments) can be a source of error in predicting crud growth and boron distribution in VERA CIPS calculations. Spacer grid effects lead to complex rod-to-fluid heat transfer behavior that, when not resolved, can lead to error in the prediction of crud growth and boron deposition. A higher-fidelity computational fluid dynamics approach can be used instead of CTF, but this leads to excessive simulation times. This paper presents an approach for using high-fidelity computational fluid dynamics data to create shape functions that are used in CTF to reconstruct rod surface heat transfer behavior as a function of spacer grid geometry. The approach is demonstrated for a 5 × 5 rod bundle facility with five mixing vane grids under a range of operating conditions encountered in nominal pressurized water reactor conditions. Furthermore, it is demonstrated that the grid heat transfer maps are successful at introducing a higher-fidelity heat transfer modeling capability into CTF.

CFD-informed↗

Graph Algorithms in PGAS: Chapel and UPC++

The Partitioned Global Address Space (PGAS) programming model can be implemented «««< HEAD either with programming language features or with runtime library APIs, each implementation favoring different aspects (e.g., productivity, abstraction, flexibility, or performance). Certain language and runtime features, such as collectives, explicit and asynchronous communication primitives, and constructs facilitating overlap of communication and computation (such as futures and conjoined futures) can enable better performance and scaling for irregular applications, in particular for distributed graph analytics. We compare graph algorithms in one of each of these environments: the Chapel PGAS programming language and the UPC++ PGAS runtime library. We implement algorithms for breadth-first search and triangle counting graph kernels in both environments. We discuss the code in each of the environments, and compile performance data on a Cray Aries and an Infiniband platform. Our results show that the library-based approach of UPC++ currently provides strong performance while Chapel provides a high-level abstraction that, harder to optimize, still provides comparable performance. We argue that various language primitives and runtime library features should be considered in conjunction with each other to design future graph analytics libraries so as to incorporate the best of both worlds.

Distributed Algorithms, Graph algorithms, HPC↗

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of local warm forming of high strength steel using near infrared ray energy

The automotive industry has been pressed to satisfy more rigorous fuel efficiency requirements to promote energy conservation, safety features and cost containment. To satisfy this need, high strength steel has been developed and used for many different vehicle parts. The use of high strength steels, however, requires careful analysis and creativity in order to accommodate its relatively high springback behavior. An innovative method, called local warm forming with near infrared ray, has been developed to help promote the use of high strength steels in sheet metal forming. For this method, local regions of the work piece are heated using infrared ray energy, thereby promoting the reduction of springback behavior. In this research, a V-bend test is conducted with DP980. After springback, the bend angles for specimens without local heating are compared to those with local heating. Numerical analysis has been performed using the commercial program, DEFORM-2D. This analysis is carried out with the purpose of understanding how changes to the local stress distribution will affect the springback during the unloading process. The results between experimental and computational approaches are evaluated to assure the accuracy of the simulation. Subsequent numerical simulation studies are performed to explore best practices with respect to thermal boundary conditions, timing, and applicability to the production environment.

97 MATHEMATICS AND COMPUTING↗

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids with Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids With Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. Demand-side participation cannot be leveraged effectively without explicitly including the distribution system dynamics in the optimization-based wholesale market operations. This project grew from a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the lower voltage system (distribution or microgrid) can also sell (buy) excess (necessary) energy from the transmission system. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. An ideal microgrid is defined as an electric entity capable of operating in both interconnected (with the high-voltage grid) and islanded mode. As such, the microgrid should incorporate generating units (traditional units and intermittent) and if needed, exchange power with the high-voltage grid. The interplay between the microgrid and high-voltage grid motivated the development of the co-optimization approach to ensure efficient performance of the interconnected network. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community

Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functional materials and acceleration of their design will require addressing the deficiencies that currently exist in materials informatics, particularly a lack of standardized experimental data management. The challenges associated with experimental data management are especially true for combinatorial materials science, where advancements in automation of experimental workflows have produced datasets that are often too large and too complex for human reasoning. The data management challenge is further compounded by the multimodal and multi-institutional nature of these datasets, as they tend to be distributed across multiple institutions and can vary substantially in format, size, and content. Furthermore, modern materials engineering requires the tuning of not only composition but also of phase and microstructure to elucidate processing–structure–property–performance relationships. To adequately map a materials design space from such datasets, an ideal materials data infrastructure would contain data and metadata describing (i) synthesis and processing conditions, (ii) characterization results, and (iii) property and performance measurements. In this work, we present a case study for the low-barrier development of such a dashboard that enables standardized organization, analysis, and visualization of a large data lake consisting of combinatorial datasets of synthesis and processing conditions, X-ray diffraction patterns, and materials property measurements generated at several different institutions. While this dashboard was developed specifically for data-driven thermoelectric materials discovery, we envision the adaptation of this prototype to other materials applications, and, more ambitiously, future integration into an all-encompassing materials data management infrastructure.

36 MATERIALS SCIENCE↗

On the study of threshold intensity dependence on the gain and loss processes in laser induced spark ignition of molecular hydrogen

In the present work, a numerical analysis is performed to investigate the comparative contribution of the mechanisms responsible for electron gain and losses in laser spark ignition and plasma formation of H{sub 2}. The analysis considered H{sub 2} over pressure range 150 -3000 torr irradiated by a Nd:YAG laser radiation at wavelengths 1064 and 532 nm with pulse length 5.5 ns. The study based on a modified electron cascade model by one of the authors which solves numerically the time dependent Boltzmann equation as well as a set of rate equations that describe the rate of change of the excited states population. The model includes most of the physical processes that might take place during the interaction. Computations of The threshold intensity are performed for the combined and separate contribution of each of the gain and loss processes. Reasonable agreement with the measured values over the tested pressure range is obtained only for the case of the combined contribution. Basing on the calculation of the electron energy distribution function, the determined relations of the time evolution of the electrons density for selected values of the tested gas pressure region revealed that photo-ionization of the excited states could determine the time of electron generation and hence spark ignition. Collisional ionization contributes to this phenomenon only at the high pressure regime. Loss processes due to electron diffusion, vibrational excitation are found to have significant effect over examined pressure values for the two applied laser wavelengths.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

X-ray scatter correction method for dedicated breast computed tomography

Purpose: To improve image quality and accuracy in dedicated breast computed tomography (BCT) by removing the x-ray scatter signal included in the BCT projections. Methods: The previously characterized magnitude and distribution of x-ray scatter in BCT results in both cupping artifacts and reduction of contrast and accuracy in the reconstructions. In this study, an image processing method is proposed that estimates and subtracts the low-frequency x-ray scatter signal included in each BCT projection postacquisition and prereconstruction. The estimation of this signal is performed using simple additional hardware, one additional BCT projection acquisition with negligible radiation dose, and simple image processing software algorithms. The high frequency quantum noise due to the scatter signal is reduced using a noise filter postreconstruction. The dosimetric consequences and validity of the assumptions of this algorithm were determined using Monte Carlo simulations. The feasibility of this method was determined by imaging a breast phantom on a BCT clinical prototype and comparing the corrected reconstructions to the unprocessed reconstructions and to reconstructions obtained from fan-beam acquisitions as a reference standard. One-dimensional profiles of the reconstructions and objective image quality metrics were used to determine the impact of the algorithm. Results: The proposed additional acquisition results in negligible additional radiation dose to the imaged breast ({approx}0.4% of the standard BCT acquisition). The processed phantom reconstruction showed substantially reduced cupping artifacts, increased contrast between adipose and glandular tissue equivalents, higher voxel value accuracy, and no discernible blurring of high frequency features. Conclusions: The proposed scatter correction method for dedicated breast CT is feasible and can result in highly improved image quality. Further optimization and testing, especially with patient images, is necessary to characterize its impact on clinical performance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

TBAA20: Task-Based Algorithms and Applications

The new challenges posed by Exascale system architectures have resulted in difficulty achieving a desired scalability using traditional distributed ­memory runtimes. Task­-based programming models show promise in addressing these challenges, providing application developers with a productive and performant approach to programming on next generation systems. Empirical studies show that task-based models can overcome load ­balancing issues that are inherent to traditional distributed ­memory runtimes, and that task-­based runtimes perform comparably to those systems when balanced. This panel is designed to explore the advantages of task-­based programming models on modern and future HPC systems from an industry, university, and national lab perspective. It aims at gathering application experts and proponents of these models to present concrete and practical examples of using task­-based runtimes to overcome the challenges posed by Exascale system architectures. This report describes the objectives, activities, and outcomes of the panel TBAA: Task­-Based Algorithms and Applications which was held at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 20) on November 18, 2020.

97 MATHEMATICS AND COMPUTING↗

Precision QCD, Hadronic Structure & Forward QCD, Heavy Ions: Report of Energy Frontier Topical Groups 5, 6, 7 submitted to Snowmass 2021

This report was prepared on behalf of three Energy Frontier Topical Groups of the Snowmass 2021 Community Planning Exercise. It summarizes the status and implications of studies of strong interactions in high-energy experiments and QCD theory. We emphasize the rich landscape and broad impact of these studies in the decade ahead. Hadronic interactions play a central role in the high-luminosity Large Hadron Collider (LHC) physics program, and strong synergies exist between the (HL-)LHC and planned or proposed experiments at the U.S. Electron-Ion Collider, CERN forward physics experiments, high-intensity facilities, and future TeV-range lepton and hadron colliders. Prospects for precision determinations of the strong coupling and a variety of nonperturbative distribution and fragmentation functions are examined. We also review the potential of envisioned tests of new dynamical regimes of QCD in high-energy and high-density scattering processes with nucleon, ion, and photon initial states. The important role of the high-energy heavy-ion program in studies of nuclear structure and the nuclear medium, and its connections with QCD involving nucleons are summarized. We address ongoing and future theoretical advancements in multi-loop QCD computations, lattice QCD, jet substructure, and event generators. Cross-cutting connections between experimental measurements, theoretical predictions, large-scale data analysis, and high-performance computing are emphasized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radiological characterization and Decommissioning of Research and Power Reactors - 15602

The production of the detailed activity and dose rate atlases (ADAs) is one of the indispensable measures in the decommissioning process of nuclear reactors which allows to determine the radiation field for optimal radiation protection as well as to quantify and characterize nuclear waste for disposal. High-detailed simulation models capable of performing neutron and radiation transport calculations at different levels of precision and details are applied for this purpose. Within the framework of the research project 'Decommissioning of Research and Power Reactors', funded by the German Federal Ministry of Education and Research (BMBF), and implemented by the Institute of Nuclear Engineering and Technology Transfer (NET) -RWTH Aachen, sophisticated simulation tools are developed. The enhances capability of these tools for the generation of the activity and dose rate distribution are tested and demonstrated on the shutdown German research reactor FRJ-2. To achieve the project goal different computational steps were required: 1. Development of a calculational CAD-based model for Monte Carlo neutron and gamma transport simulation using converter tool McCad 2. Design of the neutron source which reproduce the neutron distribution leaving the core 3. Enhancement of the simulation performance by using the hybrid deterministic Monte Carlo variance reduction methods 4. Calculation of N-flux distribution in the entire geometry 5. Development of couple codes between MCNP5 and the activation code ORIGEN2.2 This paper describes the main significant project milestones. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗