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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

PFLOTRAN Development FY2021

The Spent Fuel & Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for valuating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2021 advances of the PFLOTRAN Development group of the SFWST Campaign. The mission of this group is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of generic disposal concepts. In FY 2021, development proceeded along three main thrusts: software infrastructure, code performance, and process model advancement. Software infrastructure improvements included implementing an Agile software development framework and making improvements to the QA Test Suite. Code performance improvements included development of advanced linear and nonlinear solvers as well as design of flexible smoothing algorithms for capillary pressure functions. Process modeling advancements included the addition of flexible thermal conductivity function definitions and refinement of multi-continuum reactive transport to support Sandia’s participation in DECOVALEX. This report fulfills the GDSA PFLOTRAN Development Work Package Level 3 Milestone – PFLOTRAN Development, FY2021, M3SF-21SN010304072.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

The Analysis Description Language Ecosystem: Latest developments and physics applications

We present latest developments in Analysis Description Language (ADL), a declarative domain-specific language describing the physics algorithm of a HEP data analysis decoupled from software frameworks. Analyses written in ADL can be integrated into any framework for various tasks. ADL is a multipurpose construct with uses ranging from analysis design to preservation, reinterpretation, queries, visualisation, combination, etc. The most advanced infrastructure to execute ADL on events is the CutLang runtime interpreter. Recent technical developments include an automated interface with different data types, generation of the abstract syntax tree, a visualization tool that that auto-converts analysis flows to graphs, incorporation of trained machine learning models and a Jupyter-based plotting tool. We also report physics implications including a large scale LHC analysis implementation and validation effort for beyond the standard model reinterpretation purposes and studies with ATLAS and CMS open data.

Sekmen, Sezen [Kyungpook National Univ., Daegu (Ko↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

An Advanced Meso-Scale Peridynamic Modeling Technology using High-Performance Computing for Cost-Effective Product Design and Testing of Carbon Fiber Reinforced Polymer Composites in Light-weight Vehicles

We study a peridynamic composite modeling technology based on the discontinuous Galerkin finite element method, implemented in the commercial LS-DYNA software, for modeling and prediction of failure in carbon fiber reinforced polymer composites. The proposed technology is developed for the material failure analysis at the meso-scale, which provides the prevailing fiber-matrix interaction mechanism, without adoption of the representative volume element method and thus avoiding complicated numerical calibration procedures. Three types of experimental tests—in-plane coupon test, out-of-plane coupon test, and a component crash test—are simulated in a high-performance computing environment to assess the performance of the proposed peridynamic composite modeling technology.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mixed-precision numerics in scientific applications: survey and perspectives

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of up to 8x compared to double-precision in extreme compute-intensive workloads, remain largely untapped in most scientific applications. A growing number of efforts have shown that mixed-precision algorithmic innovations can deliver superior performance without sacrificing accuracy. These developments should prompt computational scientists to seriously consider whether their scientific modeling and simulation applications could benefit from the acceleration offered by new hardware and mixed-precision algorithms. In this survey, we (1) review progress across diverse scientific domains—fluid dynamics, weather and climate, quantum chemistry, and computational genomics—that have begun adopting mixed-precision strategies; (2) examine state-of-the-art algorithmic techniques such as iterative refinement, splitting and emulation schemes, and adaptive precision solvers; (3) assess their implications for accuracy, performance, and resource utilization; and (4) survey the emerging software ecosystem that enables mixed-precision methods at scale. We conclude with perspectives and recommendations on cross-cutting opportunities, domain-specific challenges, and the role of co-design between application scientists, numerical analysts, and computer scientists. Collectively, this survey underscores that mixed-precision numerics can reshape computational science by aligning algorithms with the evolving landscape of hardware capabilities.

Graphics processing units↗
DOE OSTI2020

Raytracing the long trace profiler

The optical design of the Long Trace Profiler optical system is explored with a commercial raytrace program, Zemax OpticStudio™ (ZOS)1, with the intent of finding and correcting sources of systematic error. ZOS provides both geometric raytracing tools and physical optics Gaussian beam propagation and diffraction image calculation tools, and two design modes, sequential component (SC) and non-sequential component (NSC) that are optimized for different aspects of the design process. The original LTP-II system employs a singlet lens with a 1250 mm focal length. It is optimized to provide minimum distortion over a surface slope angle range of ±5 mrad. Using the ZOS tools, we are able to simulate ghost rays that produce distortion in the beam spot image and can minimize the distortion by deliberate misalignment of the beamsplitter (BS) components. Unfortunately, the reference beam is compromised because of the component tilts. The most recent LTP500 system design simplifies the optical system and makes the reference beam usable again, even with misalignment of the polarizing beamsplitter (PBS). Two lenses are designed for the LTP500 - a cemented doublet that has been fabricated, and a singlet with one aspheric surface. Both have focal distances of 500 mm with an expanded angular measurement range of ±10 mrad. The aspheric singlet provides superior performance. ZOS allows the import of wavefront measurement data produced by commercial interferometer software. We apply the wavefront error measurement from the cemented doublet to the model to show that the 19nm RMS wavefront error needs to be improved by at least a factor of ten in order to reduce the systematic error to a level that will allow the LTP to approach its design limit of a few tens of nanoradians.

Takacs, Peter Z.↗
DOE OSTI2022

A full-ring variable-aperture cadmium zinc telluride system for whole-body single photon emission computed tomography: realistic simulations with phantoms

Single photon emission computed tomography (SPECT) is an imaging modality that has demonstrated its utility in a number of clinical indications. Despite this progress, a high sensitivity, high spatial resolution, multi-tracer SPECT with a large field of view suitable for whole-body imaging of a broad range of radiotracers for theranostics is not available. Purpose We have designed a cadmium zinc telluride (CZT) variable-aperture full-ring SPECT scanner instrumented with a broad-energy tungsten collimator intended to fill this technological gap. The final purpose is to provide a multi-tracer solution for brain and whole-body imaging. Our static SPECT scanner breaks the paradigm of the standard dual- and triple-head rotational SPECT systems, utilizing a larger detector area in each scan increasing the sensitivity. We provide a demonstration of the performance of our design using a realistic model of our detector with simulated body-sized 99mTc phantoms. Methods We developed a realistic model of our detector by using a combination of a Geant4 Monte Carlo simulation and a CZT detector response model based on a finite element model. Our approach models the characteristic low-energy tail effect in CZT that noticeably affects the sensitivity and the quality of the scatter correction in CZT detectors. We implement a modified dual energy window scatter correction adapted to include the CZT low-energy tail effect. A dedicated correction is also developed to eliminate the undesirable truncation observed in images given the presence of detector edges and gaps between detectors, due to the non-rotational nature of our device. Corrections for the attenuation, detector response and the presence of collimators are also included. The images are reconstructed using the maximum-likelihood expectation-maximization algorithm implemented in the reconstruction open software STIR. Detector and reconstruction performance are characterized with a Derenzo phantom and a body-sized National Electrical Manufacturers Association (NEMA) Image Quality (IQ) phantom containing 99mTc. Results Our SPECT design can resolve 6.4mm rods in a Derenzo phantom and obtain a good image contrast with the IQ phantom. Explicit testing of the gap and edge correction is provided, showing an excellent performance in eliminating the image truncation artifacts. Our modified scatter correction shows no overestimation of the contrast-recovery ratio for our realistic CZT detector model, as opposed to the cases without correction and with a standard dual-energy window scatter correction. Conclusions In this paper, we further demonstrate the performance of our design for whole-body imaging purposes. This adds to our previous demonstration of improved qualitative and quantitative 99mTc imaging for brain perfusion and 123I imaging for dopamine transport with respect to state-of-the-art NaI dual-head cameras. We show that our design performs similarly to the VERITON SPECT from Spectrum Dynamics, a commercial full-ring CZT SPECT camera, with the potential advantage of the broader energy range of application given by our custom-design tungsten collimators. Here, our device combines high sensitivity and image resolution with a broad-energy imaging application for the purpose of clinical imaging and theranostics of emerging radionuclides.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Discerning structure sensitivity of Ni-core Pd-shell nanoparticles for enhanced nitrite reduction

Denitrification using Pd-based catalysts converts N-oxyanions into harmless products. However, the metal cost and scarcity are barriers to application. In this work, we synthesize water-suspended, structure-controlled Ni-core/Pd-shell nanoparticles (Ni@Pd NPs) that show Pd-catalyzed nitrite (NO 2 − ) reduction catalysis promoted by Ni. The NPs immobilized on Al 2 O 3 (0.47 wt % Pd and 0.74 wt % Ni) have higher NH 4 + selectivity and higher catalytic activity than wet-impregnated Pd/Al 2 O 3 (1.0 wt % Pd), i.e., 315.4 vs. 132.1 Lg surface Pd −1 min −1 . X-ray photoelectron spectroscopy (XPS) and CO-diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS) analyses show that Ni increases Pd electron density, which is proposed to lower the bond dissociation energy barrier for nitric oxide surface intermediate. Low-coordinated Pd atoms correlate to high activity and low NH 4 + selectivity. Using CatCost software, we estimate Ni@Pd/Al 2 O 3 to have a ∼40% lower manufacturing cost compared to wet-impregnated Pd/Al 2 O 3 . This rationally designed catalyst illustrates how nickel promotes Pd catalysis and how Pd usage can be lowered for denitrification and other hydrogenation reactions.

CO-DRIFTS↗
DOE OSTI2024

Thermal Analysis of a Polypropylene Capacitor for Resonant Tuning Networks in WPT Applications

This study presents the thermal analysis of polypropylene capacitors operating at high frequencies and high currents used in the resonant tuning networks for electric vehicle (EV) wireless charging systems. The thermal analysis and performance results of the CELEM polypropylene capacitors are presented at different currents for a polyphase wireless power transfer (WPT) system while the study can be expanded to other capacitors by different manufacturers. Thermal equivalent circuit of the capacitor is derived and required cold plate size and design calculations are conducted by modeling the polypropene capacitor in MATLAB. The polypropene capacitor's finite element analysis (FEA) model is developed using COMSOL Multiphysics simulation software, and the thermal characteristics and analysis of the capacitor are presented in this paper.

Aktas, Ahmet↗
DOE OSTI2020

DUCTED ASSEMBLY STEADY STATE HEAT TRANSFER SOFTWARE

The Ducted Assembly Steady State Heat transfer software (DASSH) performs full core, steady state, subchannel temperature calculations for hexagonal, ducted assemblies. DASSH is targeted for use in the early stages of the reactor design process when assembly characteristics may not be defined or are undergoing considerable changes. DASSH provides a relatively rapid assessment of the temperature and flow distribution to inform reactor design updates and analysis.

ATZ, MILOSIVO↗
DOE OSTI2022

ML-PSA

The computer code uses a parallel simulated annealing framework with embedded machine learning components to solve multi-constrained optimization problems. The software automatically balances the execution of low and high fidelity physics models within the optimization procedure. The low fidelity model is used to rapidly explore the design space while the high fidelity physics model is executed sparingly to account for complex design constraints that are not resolved by the quickly executing low fidelity model.

Gurecky, William↗
DOE OSTI2021

Griffin-m

Griffin-m is a MOOSE-based reactor multiphysics application that streamlines the analysis of a variety of nuclear multiphysics simulations, including steady-state and transient radiation transport, core performance, fuel depletion, criticality and decay heat calculations, reprocessing and post-irradiation examination. This streamlining is accomplished via enhanced flexibility of the tools, uniform syntax in the MOOSE framework, dynamic linking of all relevant physics and a single point of execution. The design for flexible multi-physics, multi-radiation, multi-scheme tasks demands and ultimately makes Griffin-m a highly extendable code system. A software quality assurance (SQA) procedure is enforced during Griffin-m development. The Griffin-m version will be the main production version and it includes the MCC3 code, which was originally developed at Argonne National Laboratory to prepare cross sections for fast reactors.

Ortensi, Javier [Idaho National Laboratory (INL), ↗
DOE OSTI2024

MCM (Marine Carbon Management) [SWR-24-122]

The marine carbon management software is an open-source Python based software that contains generic models for marine carbon capture, marine carbon dioxide removal, marine carbon capture and utilization, marine carbon capture and storage. The models include design parameters, operational conditions and scenarios and technology costs.

Niffenegger, James↗
DOE OSTI2021

A survey of software implementations used by application codes in the Exascale Computing Project

The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Preliminary Thermal-Hydraulic Analysis of the UTA–2 Subcritical Linear Accelerator–Driven System

The National Nuclear Security Administration’s mission includes establishing a reliable supply of 99 Mo without highly enriched uranium. Oak Ridge National Laboratory (ORNL) supports this objective through collaborative research and development with industrial partners. Niowave Inc., a current partner, is currently designing a subcritical linear accelerator-driven system (ADS) and preparing for the US Nuclear Regulatory Commission’s licensing process. Niowave’s system has the potential to efficiently supply medical radioisotopes. The technology includes a superconducting electron accelerator and a pile of both natural and low-enriched uranium (LEU) targets. The process fissions uranium and many valuable isotopes can then be extracted from the targets. Niowave is currently iterating through conceptual and detailed design processes for several system sizes. This report discusses UTA–2, which is at the demonstration stage. UTA–2 will validate numerical modeling results with experimental measurements before progressing to the detailed design of UTA–3, the commercial-sized ADS. The thermal-hydraulic behavior of the UTA–2 core design was numerically investigated using STAR-CCM+, as described in this report. STAR-CCM+, a state-of-the-art computational fluid dynamics (CFD) software that was commercially developed by Siemens, has an extensive user base and a set of validation studies. It is also compliant with the American Society of Mechanical Engineers’ Nuclear Quality Assurance 1 standard. Three cases are investigated in this report. Case 1 quantified the temperature field within the UTA–2 assembly and water tank using only conduction as the method of thermal energy transport. This simplified approach was overly conservative and yielded wetted cladding temperatures above the coolant saturation temperature. In this case, the maximum temperature of the wetted cladding surface of the highest power rod exceeded the saturation temperature of water by 63.8°C. Because of the overly conservative approach taken in Case 1 and its negative subcooled margin, buoyancy-driven natural circulation flow physics were implemented in Case 2. Adding coolant motion significantly distributed the thermal energy of the system through convective heat transfer. This relatively small amount of convective heat transfer significantly reduced system temperatures and increased the subcooled margin from –63.8 to 61.3°C. This margin confirmed that no boiling was expected during normal operation of UTA–2 at 230 W. Case 3 had no additional physics models but considered an overpower event during which the power of each LEU and natural uranium rod was at its respective peak values. This resulted in a study with the total assembly power equal to 176% of the nominal power of 230 W considered in Cases 1 and 2. The resulting natural circulation flows were slightly enhanced. The subcooled margin decreased slightly to 46.3°C, which is still a significant margin to local boiling of the water within the tank. This margin confirmed that no boiling was expected during an abnormal operation of UTA–2 at 406 W.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Comparison of Attila Transport Code with MCNP in the Analysis of Small Modular Reactor Shielding

Of great importance in the design of a nuclear power plant is the evaluation of shielding from the ionizing radiation produced in the core of the nuclear reactor. This requires simulation software to predict the dose rates in the areas of interest. These problems are referred to as deep penetration problems, as they involve the reduction of a radiation field by two or three orders of magnitude or more. This makes accurate analyses difficult for Monte Carlo based solutions that rely on enough particles being sampled in an area of interest. Comparing the simulation of the same modeled system with more than one computer application, especially one that uses a different algorithmic approach, is a way to gain confidence in the results. In this research, two models were created, one in Monte Carlo N Particle (MCNP) which uses a stochastic algorithmic approach, and the other in Attila, which uses a deterministic algorithmic approach to test the validity of the model and to estimate the dose rates in the area of interest. Successful comparison of the two models is a way we can validate the model used for that estimation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

PyZebrascope: An Open-Source Platform for Brain-Wide Neural Activity Imaging in Zebrafish

Understanding how neurons interact across the brain to control animal behaviors is one of the central goals in neuroscience. Recent developments in fluorescent microscopy and genetically-encoded calcium indicators led to the establishment of whole-brain imaging methods in zebrafish, which record neural activity across a brain-wide volume with single-cell resolution. Pioneering studies of whole-brain imaging used custom light-sheet microscopes, and their operation relied on commercially developed and maintained software not available globally. Hence it has been challenging to disseminate and develop the technology in the research community. Here, we present PyZebrascope, an open-source Python platform designed for neural activity imaging in zebrafish using light-sheet microscopy. PyZebrascope has intuitive user interfaces and supports essential features for whole-brain imaging, such as two orthogonal excitation beams and eye damage prevention. Its camera module can handle image data throughput of up to 800 MB/s from camera acquisition to file writing while maintaining stable CPU and memory usage. Its modular architecture allows the inclusion of advanced algorithms for microscope control and image processing. As a proof of concept, we implemented a novel automatic algorithm for maximizing the image resolution in the brain by precisely aligning the excitation beams to the image focal plane. PyZebrascope enables whole-brain neural activity imaging in fish behaving in a virtual reality environment. Thus, PyZebrascope will help disseminate and develop light-sheet microscopy techniques in the neuroscience community and advance our understanding of whole-brain neural dynamics during animal behaviors.

59 BASIC BIOLOGICAL SCIENCES↗