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DOE OSTI2021

Libpanda: A High Performance Library for Vehicle Data Collection

Cyber-Physical Systems (CPS) generally involve time-critical components due to physical dynamics, therefore necessitating high-performance subsystems. This is also true in data collection scenarios to infer physical phenomena. This paper covers Libpanda as an example of a component that has been designed to address performance issues in CPS implementations. Libpanda is a C++ library that interfaces software with a Comma.ai Panda device. Pandas are used for installation in modern vehicles to read the vehicle CAN bus, providing rich sensor data and limited vehicle control through message injection. The motivation to design lib-panda stems from the lack of performance in Python-based code that runs on inexpensive hardware like a Raspberry Pi. In such situations, Python code would result in utilizing 92% CPU while also dropping around 40% of the CAN packet due to bottlenecks. Without using different tools, inconsistent data collection means a loss of time-based vehicle state interpretation. Libpanda addresses these issues through implementation in a different language and implementation of different design paradigms involving asynchronous calls and multithreading. The Panda also features a GPS module that allows multiple instances to synchronize clocks for large-scale data collection scenarios. Libpanda has been designed with time-synchronization in mind to aid in the measurement of inter-vehicle dynamics. The performance improvements of libpanda have resulted in it becoming an important component in automotive dynamics research that requires a higher technical performance in large-scale experiments.

Bunting, Matthew↗

DOE OSTI2025

A Safe Response to Renewable Energy Hazards

The International Association of Fire Fighters (IAFF) and Underwriters Laboratories, LLC (UL) in conjunction with UL Solutions initiated a joint project in 2022 under an agreement with the United States Department of Energy-Office of Energy Efficiency and Renewable Energy (DOE-EERE). This project focused on two separate and important initiatives related to energy efficiency in residential buildings. Initiative 1: Fire Performance on Energy Efficient Exterior Walls. Initiative 2: Firefighting Tactics in Residential Properties with Building Energy Storage Systems (BESS). The project’s first initiative addresses concerns surrounding new technologies with enhanced, energy-efficient exterior walls installed on residential properties. The concerns of fire rapidly traveling vertically up the exterior of these walls were examined. This addressed a growing concern from the first responder community that many times, the fires on the exterior of residential buildings have already evolved into an attic fire by the time of arrival – making it problematic to address the fire scenario. The test plan for Initiative 1 incorporated a modified version of an American Society for Testing and Materials (ASTM) test method, ASTM E2707, Standard Test Method for Determining Fire Penetration of Exterior Wall Assemblies Using a Direct Flame Impingement Exposure, as the foundation of the research. The test method involved a wall structure intended to represent retrofit construction to evaluate how fire would spread vertically or laterally. The second aspect of the UL-IAFF Project focuses on the fire service response to Residential Battery Energy Storage System (RBESS) incidents. These simulation tests were constructed in the large-scale fire test facility at UL Solutions’ Northbrook, IL campus. A baseline test was conducted that involved a test structure with no batteries—shelving units populated with standardized commodities, representing a typical garage with cellulosic and plastic contents. Three additional tests have been conducted to generate data with the contribution of energy storage system (ESS) batteries to compare fire and explosion hazards against the baseline test. Through this work, fire service tactical considerations can be explored. From the data, the team can determine 1) the visual indicators of a residential fire that has involved an RBESS (or, potentially, other large batteries) and 2) the impact of fire service-initiated ventilation of the structure on the fire conditions and explosion risks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1989

Conservation equations and physical models for hypersonic air flows over the aeroassist flight experiment vehicle

The code development and application program for the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA), with emphasis directed toward support of the Aeroassist Flight Experiment (AFE) in the near term and Aeroassisted Space Transfer Vehicle (ASTV) design in the long term is reviewed. LAURA is an upwind-biased, point-implicit relaxation algorithm for obtaining the numerical solution to the governing equations for 3-D, viscous, hypersonic flows in chemical and thermal nonequilibrium. The algorithm is derived using a finite volume formulation in which the inviscid components of flux across cell walls are described with Roe's averaging and Harten's entropy fix with second-order corrections based on Yee's Symmetric Total Variation Diminishing scheme. Because of the point-implicit relaxation strategy, the algorithm remains stable at large Courant numbers without the necessity of solving large, block tri-diagonal systems. A single relaxation step depends only on information from nearest neighbors. Predictions for pressure distributions, surface heating, and aerodynamic coefficients compare well with experimental data for Mach 10 flow over an AFE wind tunnel model. Predictions for the hypersonic flow of air in chemical and thermal nonequilibrium over the full scale AFE configuration obtained on a multi-domain grid are discussed.

Gnoffo, Peter A.↗

DOE OSTI2024

TDCOSMO - XVI. Measurement of the Hubble constant from the lensed quasar WGD 2038–4008

Time-delay cosmography is a powerful technique to constrain cosmological parameters, particularly the Hubble constant (H0). The TDCOSMO Collaboration is performing an ongoing analysis of lensed quasars to constrain cosmology using this method. In this work, we obtain constraints from the lensed quasar WGD 2038−4008 using new time-delay measurements and previous mass models by TDCOSMO. This is the first TDCOSMO lens to incorporate multiple lens modeling codes and the full time-delay covariance matrix into the cosmological inference. The models are fixed before the time delay is measured, and the analysis is performed blinded with respect to the cosmological parameters to prevent unconscious experimenter bias. We obtain DΔ t = 1.68−0.38+0.40 Gpc using two families of mass models, a power-law describing the total mass distribution, and a composite model of baryons and dark matter, although the composite model is disfavored due to kinematics constraints. In a flat ΛCDM cosmology, we constrain the Hubble constant to be H0 = 65−14+23 km s−1 Mpc−1. The dominant source of uncertainty comes from the time delays, due to the low variability of the quasar. Future long-term monitoring, especially in the era of the Vera C. Rubin Observatory’s Legacy Survey of Space and Time, could catch stronger quasar variability and further reduce the uncertainties. This system will be incorporated into an upcoming hierarchical analysis of the entire TDCOSMO sample, and improved time delays and spatially-resolved stellar kinematics could strengthen the constraints from this system in the future.Key words: gravitational lensing: strong / cosmological parameters / distance scale⋆ Corresponding author; kcwong19@gmail.com.⋆⋆ NHFP Einstein fellow.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

ParFlow Sand Tank: A tool for groundwater exploration

The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

A software-aided workflow for precinct-scale residential redevelopment

Growing urban populations, combined with environmental challenges, have placed significant pressure on urban planning to supply housing while addressing policy issues such as sustainability, affordability, and liveability. The interrelated nature of these issues, combined with the requirement of evidence-based planning, has made decision-making so complex that urban planners need to combine expertise on energy, water, carbon emissions, transport and economic development along with other bodies of knowledge necessary to make well-informed decisions. This paper presents two geospatial software systems that can assist in the mediation of complexity, by allowing users to assess a variety of planning metrics without expert knowledge in those disciplines. Using Envision and Envision Scenario Planner (ESP), both products of the Greening the Greyfields research project funded by the Cooperative Research Centre for Spatial Information (CRCSI) in Australia, we demonstrate a workflow for identifying potential redevelopment precincts and designing and assessing possible redevelopment scenarios to optimise planning outcomes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Modeling and Simulation of Xe-100-type Pebble Bed Gas-Cooled Reactor with SCALE

The US Department of Energy (DOE) announced the Advanced Reactor Demonstration Program (ARDP) to accelerate the deployment of advanced reactor concepts. Awardees of ARDP funds are expected to demonstrate the operation of an advanced reactor within 7 years of receiving the award. X-Energy’s advanced reactor concept, the Xe-100, was selected as one of two advanced reactor concepts to receive funding to demonstrate the operation of its high-temperature gas-cooled pebble-bed reactor before the end of this decade. As a result of this push to bring advanced reactors to maturation and commercialization, transition and deployment scenario studies are being performed under the Systems Analysis and Integration (SA&I) campaign within the DOE Office of Nuclear Energy (DOE-NE) to evaluate the transition of the current US commercial fleet of light-water reactors (LWRs) to a future fleet of advanced reactors consisting of a mix of ARDP type reactor concepts and advanced LWRs. To accurately evaluate the front- and back-end resource requirements, it is important to perform reactor physics calculations to determine the discharge burnup and isotopic content, fuel residence time, as well as other parameters. For this purpose, a summer project funded by the SA&I campaign allowed for the setup of SCALE models for full-core Xe-100 type high-temperature gas-cooled pebble-bed reactor and a Xe-100 type slice using publicly available information. The core-averaged equilibrium compositions and zone-wise equilibrium compositions for the slice and 3D models, respectively, were obtained following an iterative depletion method developed by Bostelmann et al. using SCALE’s reactor physics sequence TRITON. The slice model was used with TRITON to generate burnup-dependent cross section libraries at different temperatures which can be used with SCALE’s ORIGAMI code to rapidly determine fuel inventory and therefore to perform quick sensitivity studies on parameters such as the pebble location in the core. The SCALE/TRITON transport and depletion calculation for the Xe-100 type slice model indicates that the isotopic concentrations are in good agreement at 1,300 effective full power days (EFPD) for 235 U. An analysis of 236 U results match 239 Pu results would seem to indicate a typographical error in Mulder and Boyes wherein the reported results of 236 U and 239 Pu are reversed. In addition to SCALE/TRITON calculations, a new capability within SCALE/ORIGAMI for the simulation of pebble-bed reactors was used to study the burnup sensitivity with respect to the pebble pathway through the core. The SCALE/ORIGAMI results show that pebbles that travel closer to the reflector for the entire depletion history have a higher burnup than pebbles that travel through the middle of the core because of the higher thermal to fast flux ratio near the reflector. Consequently, a pebble’s burnup is strongly affected by the pebble’s pathway for each pass. Additional phenomena such as temperature distributions in the core and different travel times of the pebbles in the individual radial zones further affect the burnup distribution. The sensitivity of the discharge vector to the pebble pathways taken during each pass can be evaluated in the future using SCALE/ORIGAMI now that the SCALE inputs have been established.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding

Galaxy-scale strong gravitational lensing can not only provide a valuable probe of the dark matter distribution of massive galaxies, but also provide valuable cosmological constraints, either by studying the population of strong lenses or by measuring time delays in lensed quasars. Due to the rarity of galaxy-scale strongly lensed systems, fast and reliable automated lens finding methods will be essential in the era of large surveys such as Large Synoptic Survey Telescope, Euclid and Wide-Field Infrared Survey Telescope. To tackle this challenge, we introduce CMU DeepLens, a new fully automated galaxy-galaxy lens finding method based on deep learning. This supervised machine learning approach does not require any tuning after the training step which only requires realistic image simulations of strongly lensed systems. We train and validate our model on a set of 20 000 LSST-like mock observations including a range of lensed systems of various sizes and signal-to-noise ratios (S/N). We find on our simulated data set that for a rejection rate of non-lenses of 99 per cent, a completeness of 90 per cent can be achieved for lenses with Einstein radii larger than 1.4 arcsec and S/N larger than 20 on individual g-band LSST exposures. Finally, we emphasize the importance of realistically complex simulations for training such machine learning methods by demonstrating that the performance of models of significantly different complexities cannot be distinguished on simpler simulations. We make our code publicly available at https://github.com/McWilliamsCenter/CMUDeepLens.

gravitational lensing: strong↗

DOE OSTI2025

Evaluating an Earth system model from a water manager perspective

Abstract. The large spatial scale of global Earth system models (ESMs) is often cited as an obstacle to using the output by water resource managers in localized decisions. Recent advances in computing have improved the fidelity of hydrological responses in ESMs through increased connectivity between model components. However, the models are seldom evaluated for their ability to reproduce metrics that are important for and resonate with practitioners or that allow practitioners to situate higher-resolution model outputs within a cascade of uncertainty stemming from different models and scenarios. We draw on the combined experience of the author team and water manager workshop participants to identify salient water management metrics and evaluate whether they are credibly reproduced over the conterminous USA by the Community Earth System Model v2 (CESM2) Large Ensemble. We find that, while the exact values may not match the observations, aspects such as interannual variability can be reproduced by CESM2 for the mean wet day precipitation and length of dry spells. CESM2 also captures the proportion of total annual precipitation that derives from the heaviest rain days in watersheds that are not snow-dominated. Aggregating the 7 d mean daily runoff to two-digit Hydrological Unit Code (HUC2) watersheds also shows that rain-dominated regions capture the timing and interannual variability of annual maximum and minimum flows. We conclude that there is potential for far greater use of large-ensemble ESMs, such as CESM2, in long-range water management decisions to supplement high-resolution regional projections.

Tye, Mari R. (ORCID:0000000324911020)↗

NASA NTRS2009

Laboratory for Atmospheres 2008 Technical Highlights

The 2008 Technical Highlights describes the efforts of all members of the Laboratory for Atmospheres. Their dedication to advancing Earth Science through conducting research, developing and running models, designing instruments, managing projects, running field campaigns, and numerous other activities, is highlighted in this report. The Laboratory for Atmospheres (Code 613) is part of the Earth Sciences Division (Code 610), formerly the Earth Sun Exploration Division, under the Sciences and Exploration Directorate (Code 600) based at NASA s Goddard Space Flight Center in Greenbelt, Maryland. In line with NASA s Exploration Initiative, the Laboratory executes a comprehensive research and technology development program dedicated to advancing knowledge and understanding of the atmospheres of Earth and other planets. The research program is aimed at understanding the influence of solar variability on the Earth s climate; predicting the weather and climate of Earth; understanding the structure, dynamics, and radiative properties of precipitation, clouds, and aerosols; understanding atmospheric chemistry, especially the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and advancing our understanding of physical properties of Earth s atmosphere. The research program identifies problems and requirements for atmospheric observations via satellite missions. Laboratory scientists conceive, design, develop, and implement ultraviolet, infrared, optical, radar, laser, and lidar technology for remote sensing of the atmosphere. Laboratory members conduct field measurements for satellite data calibration and validation, and carry out numerous modeling activities. These modeling activities include climate model simulations, modeling the chemistry and transport of trace species on regional-to-global scales, cloud-resolving models, and development of next-generation Earth system models. Interdisciplinary research is carried out in collaboration with other laboratories and research groups within the Earth Sciences Division, across the Sciences and Exploration Directorate, and with partners in universities and other Government agencies. The Laboratory for Atmospheres is a vital participant in NASA s research agenda. Our Laboratory often has relatively large programs, sizable satellite missions, and observational campaigns that require the cooperative and collaborative efforts of many scientists. We ensure an appropriate balance between our scientists responsibility for these large collaborative projects and their need for an active individual research agenda. This balance allows members of the Laboratory to continuously improve their scientific credentials. Members of the Laboratory interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratory raises the public s awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. The Laboratory makes substantial efforts to attract new scientists to the various areas of atmospheric research. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of our science products. This report describes our role in NASA s mission, gives a broad description of our research, and summarizes our scientists major accomplishments during calendar year 2008. The report also contains useful information on human resources, scientific interactions, and outreach activities.

Cote, Charles E.↗

DOE OSTI2022

Performance of the Initial Implementation of the Shift Monte Carlo Code in SCALE 6.3

The Shift Monte Carlo code will be introduced in SCALE 6.3 as an alternative to the KENO V.a, KENO-VI, and Monaco codes. Calculations were performed to establish the performance of Shift for criticality safety analyses within the criticality safety analyses sequence (CSAS) based on models in the Verified, Archived Library of Inputs and Data (VALID). This test suite contains over 600 critical experiment models covering a broad range of fissile materials and neutron energy spectra. The comparisons presented include calculated k eff values and runtime performance for serial calculations and a selection of parallel calculations. Comparisons are presented for multigroup (MG) and continuous-energy (CE) calculations for KENO V.a and KENO-VI models. Results generated with a beta version of SCALE 6.3 indicate excellent agreement in k eff values between KENO and Shift. The largest differences in the average k eff value calculated for the 15 categories of KENO V.a models are 0.00020 ± 0.00011 Δ k for MG calculations and 0.00011 ± 0.00005 Δ k for CE calculations. Similar comparisons in three categories using KENO-VI result in the largest differences for MG calculations: as 0.00004 ± 0.00003 Δ k , and -0.00002 ± 0.00003 Δ k for CE. The preliminary results also indicate that Shift is faster than KENO on a per particle basis, especially for fast spectrum systems. The uncertainty per history is also higher, however, so the Monte Carlo figure of merit is higher for KENO for thermal and intermediate spectrum systems. As expected, Shift generally has better speedup than KENO for parallel calculations, regardless of neutron energy spectrum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Xyce Parallel Electronic Simulator Users' Guide Version 6.7.

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: Capability to solve extremely large circuit problems by supporting large-scale parallel com- puting platforms (up to thousands of processors). This includes support for most popular parallel and serial computers. A differential-algebraic-equation (DAE) formulation, which better isolates the device model package from solver algorithms. This allows one to develop new types of analysis without requiring the implementation of analysis-specific device models. Device models that are specifically tailored to meet Sandia's needs, including some radiation- aware devices (for Sandia users only). Object-oriented code design and implementation using modern coding practices. Xyce is a parallel code in the most general sense of the phrase -- a message passing parallel implementation -- which allows it to run efficiently a wide range of computing platforms. These include serial, shared-memory and distributed-memory parallel platforms. Attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The information herein is subject to change without notice. Copyright c 2002-2017 Sandia Corporation. All rights reserved. Trademarks Xyce TM Electronic Simulator and Xyce TM are trademarks of Sandia Corporation. Orcad, Orcad Capture, PSpice and Probe are registered trademarks of Cadence Design Systems, Inc. Microsoft, Windows and Windows 7 are registered trademarks of Microsoft Corporation. Medici, DaVinci and Taurus are registered trademarks of Synopsys Corporation. Amtec and TecPlot are trademarks of Amtec Engineering, Inc. All other trademarks are property of their respective owners. Contacts World Wide Web http://xyce.sandia.gov https://info.sandia.gov/xyce (Sandia only) Email xyce@sandia.gov (outside Sandia) xyce-sandia@sandia.gov (Sandia only) Bug Reports (Sandia only) http://joseki-vm.sandia.gov/bugzilla http://morannon.sandia.gov/bugzilla

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Wing design for a civil tiltrotor transport aircraft

The goal of this research is the proper tailoring of the civil tiltrotor's composite wing-box structure leading to a minimum-weight wing design. With focus on the structural design, the wing's aerodynamic shape and the rotor-pylon system are held fixed. The initial design requirement on drag reduction set the airfoil maximum thickness-to-chord ratio to 18 percent. The airfoil section is the scaled down version of the 23 percent-thick airfoil used in V-22's wing. With the project goal in mind, the research activities began with an investigation of the structural dynamic and aeroelastic characteristics of the tiltrotor configuration, and the identification of proper procedures to analyze and account for these characteristics in the wing design. This investigation led to a collection of more than thirty technical papers on the subject, some of which have been referenced here. The review of literature on the tiltrotor revealed the complexity of the system in terms of wing-rotor-pylon interactions. The aeroelastic instability or whirl flutter stemming from wing-rotor-pylon interactions is found to be the most critical mode of instability demanding careful consideration in the preliminary wing design. The placement of wing fundamental natural frequencies in bending and torsion relative to each other and relative to the rotor 1/rev frequencies is found to have a strong influence on the whirl flutter. The frequency placement guide based on a Bell Helicopter Textron study is used in the formulation of frequency constraints. The analysis and design studies are based on two different finite-element computer codes: (1) MSC/NASATRAN and (2) WIDOWAC. These programs are used in parallel with the motivation to eventually, upon necessary modifications and validation, use the simpler WIDOWAC code in the structural tailoring of the tiltrotor wing. Several test cases were studied for the preliminary comparison of the two codes. The results obtained so far indicate a good overall agreement between the two codes.

Rais-Rohani, Masoud↗

NASA NTRS2003

Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS

The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed.

Pawson, Steven↗

DOE OSTI2017

ORIGEN-based Nuclear Fuel Inventory Module for Fuel Cycle Assessment: Final Project Report

The goal of this project, “ORIGEN-based Nuclear Fuel Depletion Module for Fuel Cycle Assessment" is to create a physics-based reactor depletion and decay module for the Cyclus nuclear fuel cycle simulator in order to assess nuclear fuel inventories over a broad space of reactor operating conditions. The overall goal of this approach is to facilitate evaluations of nuclear fuel inventories for a broad space of scenarios, including extended used nuclear fuel storage and cascading impacts on fuel cycle options such as actinide recovery in used nuclear fuel, particularly for multiple recycle scenarios. The advantages of a physics-based approach (compared to a recipe-based approach which has been typically employed for fuel cycle simulators) is in its inherent flexibility; such an approach can more readily accommodate the broad space of potential isotopic vectors that may be encountered under advanced fuel cycle options. In order to develop this flexible reactor analysis capability, we are leveraging the Origen nuclear fuel depletion and decay module from SCALE to produce a standalone “depletion engine” which will serve as the kernel of a Cyclus-based reactor analysis module. The ORIGEN depletion module is a rigorously benchmarked and extensively validated tool for nuclear fuel analysis and thus its incorporation into the Cyclus framework can bring these capabilities to bear on the problem of evaluating long-term impacts of fuel cycle option choices on relevant metrics of interest, including materials inventories and availability (for multiple recycle scenarios), long-term waste management and repository impacts, etc. Developing this Origen-based analysis capability for Cyclus requires the refinement of the Origen analysis sequence to the point where it can reasonably be compiled as a standalone sequence outside of SCALE; i.e., wherein all of the computational aspects of Origen (including reactor cross-section library processing and interpolation, input and output processing, and depletion/decay solvers) can be self-contained into a single executable sequence. Further, to embed this capability into other software environments (such as the Cyclus fuel cycle simulator) requires that Origen’s capabilities be encapsulated into a portable, self-contained library which other codes can then call directly through function calls, thereby directly accessing the solver and data processing capabilities of Origen. Additional components relevant to this work include modernization of the reactor data libraries used by Origen for conducting nuclear fuel depletion calculations. This work has included the development of new fuel assembly lattices not previously available (such as for CANDU heavy-water reactor assemblies) as well as validation of updated lattices for light-water reactors updated to employ modern nuclear data evaluations. The CyBORG reactor analysis module as-developed under this workscope is fully capable of dynamic calculation of depleted fuel compositions from all commercial U.S. reactor assembly types as well as a number of international fuel types, including MOX, VVER, MAGNOX, and PHWR CANDU fuel assemblies. In addition, the Origen-based depletion engine allows for CyBORG to evaluate novel fuel assembly and reactor design types via creation of Origen reactor data libraries via SCALE. The establishment of this new modeling capability affords fuel cycle modelers a substantially improved ability to model dynamically-changing fuel cycle and reactor conditions, including recycled fuel compositions from fuel cycle scenarios involving material recycle into thermal-spectrum systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2002

Magnetohydrodynamic MACH Code Used to Simulate Magnetoplasmadynamic Thrusters

The On-Board Propulsion program at the NASA Glenn Research Center is utilizing a state of-the-art numerical simulation to model the performance of high-power electromagnetic plasma thrusters. Such thrusters are envisioned for use in lunar and Mars cargo transport, piloted interplanetary expeditions, and deep-space robotic exploration of the solar system. The experimental portion of this program is described in reference 1. This article describes the numerical modeling program used to guide the experimental research. The synergistic use of numerical simulations and experimental research has spurred the rapid advancement of high-power thruster technologies for a variety of bold new NASA missions. From its inception as a U.S. Department of Defense code in the mid-1980's, the Multiblock Arbitrary Coordinate Hydromagnetic (MACH) simulation tool has been used by the plasma physics community to model a diverse range of plasma problems--including plasma opening switches, inertial confinement fusion concepts, compact toroid formation and acceleration, z-pinch implosion physics, laser-target interactions, and a variety of plasma thrusters. The MACH2 code used at Glenn is a time-dependent, two-dimensional, axisymmetric, multimaterial code with a multiblock structure. MACH3, a more recent three-dimensional version of the code, is currently undergoing beta tests. The MACH computational mesh moves in an arbitrary Lagrangian-Eulerian (ALE) fashion that allows the simulation of diffusive-dominated and dispersive-dominated problems, and the mesh can be refined via a variety of adaptive schemes to capture regions of varying characteristic scale. The mass continuity and momentum equations model a compressible viscous fluid, and three energy equations are used to simulate nonthermal equilibrium between electrons, ions, and the radiation field. Magnetic fields are modeled by an induction equation that includes resistive diffusion, the Hall effect, and a thermal source for magnetic fields. Various models of plasma resistivity are included, along with ablation models and multiport circuit solvers. The set of equations is closed using either an ideal gas or real equation of state.

Mikellides, Pavlos G.↗

DOE OSTI2018

Assessment of different coarse graining strategies to simulate polydisperse gas-solids flow

Continuum methods require the additional development of solids stress closures for polydisperse powders based on complex kinetic theories that are non-trivial to develop, code, and numerically converge for the wide range of fluidization regimes from very dilute to dense/frictional flow limit. On the other hand, it is straightforward to model the flow of polydisperse granular materials by treating particles as discrete rigid bodies that are tracked following simple physical laws of motion. The coarsening of these discrete methods by lumping several particles in a parcel alleviates the significant computational cost associated with these discrete methods while introducing some inaccuracies in the numerical results. In this research, we explore two different coarse graining methods that can be applied to polydisperse powders, namely the same statistic weight method (SSW) and the same size parcel method (SSP), and assess their accuracy by comparison with the finest simulation results obtained with a discrete element method (DEM). For Geldart group B powders fluidized at a relative low superficial velocity, the numerical results indicate that the SSW is more accurate than the SSP method. For type A powders fluidized at relatively high velocity, these two methods predict similar results. Interestingly, up to four times increase in the speed of simulation of the SSP method was obtained because the original polydisperse powder is scaled to a mono-disperse system in terms of particle-particle collision. Lastly, these results suggest that the SSP method is more favorable for the simulation of fluidized beds due to its accuracy and efficiency while the SSW method may be used for granular flow and dense fluidized bed systems where capturing the size segregation of particles due to collision is important.

42 ENGINEERING↗

DOE OSTI2026

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Rodriguez, Alex [Argonne National Laboratory (ANL)↗