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At least 775 records · Page 43

Improving the performance of medical imaging applications using SYCL

As opposed to the Open Computing Language (OpenCL) programming model, in which host and device codes are generally written in different programming languages, SYCL can combine host and device codes for an application in a type-safe way to improve development productivity and performance portability. Hence, this report shows the experimental results of applying the SYCL programming model to medical imaging applications for a study on performance portability and programming productivity between OpenCL and SYCL. Rodinia is a widely used open-source benchmark suite for heterogeneous computing. We choose two medical imaging applications (Heart Wall and Particle Filter) in the benchmark suite, migrate the OpenCL implementations of the applications to the SYCL implementations, and evaluate their performance and productivity on Intel® microprocessors that contain a central processing unit (CPU) and an integrated graphics processing unit (GPU). The maturing SYCL compilers, which are based on a conformant implementation of the SYCL 1.2.1 Khronos specification, have been actively optimized for Intel® computing platforms. The experimental results are promising in terms of the raw performance and productivity. Although the SYCL implementation of the Heart Wall application does not execute successfully on a CPU, the SYCL implementations of the application can achieve comparable or better performance than the OpenCL implementation on Intel® integrated GPUs. For the Particle Filter application, the performance difference between the SYCL and OpenCL implementations is comparable on the GPUs for most cases, but the SYCL implementations are on average 4X faster than the OpenCL implementations on Intel® Xeon® CPUs. For programming productivity, we arguably use lines of code as a way to measure programming productivity in software. The SYCL programs reduce the lines of code of the OpenCL programs by 52% and 38% for the Heart Wall and Particle Filter, respectively. The results indicate that SYCL is a promising programming model for heterogeneous computing with the maturing compilers. We organize the remainder of the report as follows. Section II introduces the SYCL programming model, compares the major differences between an OpenCL program and a SYCL program, and describes the characteristics of the two applications. Section III describes the SYCL programming model in more details, and shows the SYCL implementation of a kernel function in the Particle Filter application as an example. In Section IV, we evaluate the performance of the applications on the CPUs and GPUs. Section V concludes the report.

59 BASIC BIOLOGICAL SCIENCES↗

Procedure for Creating, Reviewing, and Submitting Input Files into the Benchmark Library

Los Alamos National Laboratory (LANL) has a number of criticality benchmark input files, modeled for use with MCNP, developed and maintained by various organizations including the Nuclear Criticality Safety (NCS) Division, XCP-3, and XCP-5. The purpose of this procedure is to standardize input file creation, review, and maintenance. This procedure incorporates existing practices used by IRSN as documented in the original report and the translation from French in addition to practices used by the LANL NCS Division as documented in. The report relates to input files used for the validation of the continuous energy Monte Carlo code MCNP6 but is general enough to be extended to other codes. This report describes the procedure on how to prepare and use benchmarks (taken mainly from the ICSBEP Handbook) for the validation of calculation routes. In particular, this report describes the procedure to follow in the creation of the input files and their integration in the experimental validation databases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Distribution Grid Impacts of Community Solar [Slides]

Community solar (CS) projects often face uncertain interconnection costs and fees associated with distribution grid infrastructure upgrades required to connect the project. These costs can determine the economic viability of a CS project, but they are difficult to assess. Cost uncertainty can discourage new projects and prevent communities from accessing the benefits of community solar projects. At the same time, CS deployment strategies hold potential to defer or avoid some distribution costs due to new loads. To mitigate CS interconnection costs, it is important to find least-cost combinations of distribution system infrastructure solutions (transformer upgrades, reconductoring, voltage regulators, storage), and to understand how location of CS projects within a feeder impact distribution grid upgrade costs. This study aims to quantify CS impacts on the distribution grid and provide policy and regulatory insights and CS deployment strategies to address them. It is the first analysis that has systematically studied the technical impacts of community solar projects on a wide range of distribution feeders using state-of-the-art optimization and power flow tools. The analysis employs Berkeley Lab’s novel Least-cost Optimal Distribution Grid Expansion (LODGE) model, a deterministic version of the REPAIR model, that optimally upgrades hundreds or even thousands of distribution circuits or feeders. This is the first application of the LODGE model. LODGE finds the least-cost portfolio of traditional distribution system upgrades to integrate CS in combination with alternative solutions, such as utility-owned storage and downsizing CS capacity. Working with a set of least-cost solutions per feeder allows us to benchmark, compare and find techno-economic trends in CS interconnection.

14 SOLAR ENERGY↗

New correlated numerical methods for attosecond molecular single and double ionization

This project resulted in the development of ASTRA, a new molecular ionization code capable of describing single and double ionization processes in polyatomic molecules with correlated electrons and time-dependent fields. Key achievements include: (i) the development of the PRISM hybrid-integral library enabling core-ionization and high-angular-momentum convergence; (ii) implementation of time-dependent Schrödinger equation solvers for pump–probe spectroscopies; (iii) validation against experimental and theoretical benchmarks for atoms and molecules; and (iv) extension to two-photon double ionization using the finite-pulse virtual-sequential model. These developments establish ASTRA as a versatile platform for attosecond molecular dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Elevating SolTrace's Capabilities for the Next Generation of Concentrating Solar Analysis

SolTrace is an open-source Monte Carlo ray tracing software developed at NREL. SolTrace can characterize concentrating solar thermal (CST) collector optical performance and is CST technology agnostic. Shown in Fig. 1, SolTrace is a foundational tool in NREL's CST system and component modeling suite. SolTrace's generic surface elements can flexibly model novel collector and receiver designs to predict spatial and temporal flux distributions - critical to understand for CST component design, performance prediction, and system integration. Since its initial development, SolTrace has over 1,650 references on Google Scholar, over 9,800 downloads since 2017, and has served the CST research and development community as a benchmark of 3rd party verification. SolTrace provides users with many options for defining surface shape and boundaries. However, SolTrace provides limited documentation which can result in a steep learning curve for new users. Additionally, SolTrace lacks the computational performance required to evaluate optical performance of a CST system over the course of a year and/or iteratively over design parameters in a timely manner. To address this, we are working towards a new release of SolTrace that enables increased computational throughput by implementing ray tracing acceleration structures and enabling GPU parallelization. Additionally, we are working to improve SolTrace's usability, accessibility, and maintainability by (1) automating solar position time-dependent simulation processes, (2) creating general CST collector templates of grouped elements, (3) updating the user interface to better visualize model inputs and outputs, and (4) creating a user support network through forums, "how to" videos, and documentation.

14 SOLAR ENERGY↗

TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry

We present TChem-atm, a performance-portable approach that enables efficient simulation of chemically detailed and multiphase atmospheric chemistry on modern heterogeneous computing architectures. Unlike previous efforts that rely on architecture-specific code or focus exclusively on gas-phase chemistry, TChem-atm supports fully coupled gas–aerosol systems with execution across CPUs, NVIDIA GPUs, and AMD GPUs through the Kokkos programming model. It integrates the flexible multiphase capabilities of the Community Atmospheric Model Chemistry Package (CAMP) with the high-performance kinetic routines of TChem, and includes automatic Jacobian construction with support for a range of stiff ODE solvers. In a proof-of-concept integration with the particle-resolved model PartMC, TChem-atm reproduces the existing PartMC–CAMP implementation within solver tolerances and delivers substantial GPU speedups, especially for large particle populations. Performance benchmarks reveal substantial speedups on GPU platforms, particularly for large particle populations, with consistent results across hardware backends. TChem-atm enables performance-portable execution across CPUs and GPUs, though optimal efficiency may require modest architecture-specific tuning (e.g., team and vector sizes), with up to a twofold improvement on the NVIDIA H100. It directly supports sectional and particle-resolved host models, while modal aerosol schemes require minor adaptation to provide particle-scale quantities such as representative diameters. By enabling chemically detailed, multiphase simulations with performance portability and host-model flexibility, TChem-atm facilitates the incorporation of advanced chemistry into atmospheric models.

Díaz-Ibarra, Oscar Homero [Sandia National Laborat↗

Conceptual Design and Structural Optimization of NASA Environmentally Responsible Aviation (ERA) Hybrid Wing Body Aircraft

Simultaneously achieving the fuel consumption and noise reduction goals set forth by NASA's Environmentally Responsible Aviation (ERA) project requires innovative and unconventional aircraft concepts. In response, advanced hybrid wing body (HWB) aircraft concepts have been proposed and analyzed as a means of meeting these objectives. For the current study, several HWB concepts were analyzed using the Hybrid wing body Conceptual Design and structural optimization (HCDstruct) analysis code. HCDstruct is a medium-fidelity finite element based conceptual design and structural optimization tool developed to fill the critical analysis gap existing between lower order structural sizing approaches and detailed, often finite element based sizing methods for HWB aircraft concepts. Whereas prior versions of the tool used a half-model approach in building the representative finite element model, a full wing-tip-to-wing-tip modeling capability was recently added to HCDstruct, which alleviated the symmetry constraints at the model centerline in place of a free-flying model and allowed for more realistic center body, aft body, and wing loading and trim response. The latest version of HCDstruct was applied to two ERA reference cases, including the Boeing Open Rotor Engine Integration On an HWB (OREIO) concept and the Boeing ERA-0009H1 concept, and results agreed favorably with detailed Boeing design data and related Flight Optimization System (FLOPS) analyses. Following these benchmark cases, HCDstruct was used to size NASA's ERA HWB concepts and to perform a related scaling study.

Quinlan, Jesse R.↗

Solution of stochastic media transport problems using a numerical quadrature-based method

We present a new conceptual framework for analyzing transport problems in random media. We decompose such problems into stratified subproblems according to the number of material pseudo-interfaces within realizations. For a given subproblem we assign pseudo-interface locations in each realization according to product quadrature rules, which allows us to deterministically generate a fixed number of realizations. Quadrature integration of the solutions of these realizations thus approximately solves each subproblem; the weighted superposition of solutions of the subproblems approximately solves the general stochastic media transport problem. We revisit some benchmark problems to determine the accuracy and efficiency of this approach in comparison to randomly generated realizations. We find that this method is very accurate and fast when the number of pseudo-interfaces in a problem is generally low, but that these advantages quickly degrade as the number of pseudo-interfaces increases. (authors)

97 MATHEMATICS AND COMPUTING↗

High-Resolution Analysis Products to Support Severe Weather and Cloud-to-Ground Lightning Threat Assessments over Florida

The Applied Meteorology Unit (AMU) located at the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) implemented an operational configuration of the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS), as well as the ARPS numerical weather prediction (NWP) model. Operational, high-resolution ADAS analyses have been produced from this configuration at the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) over the past several years. Since that time, ADAS fields have become an integral part of forecast operations at both NWS MLB and SMG. To continue providing additional utility, the AMU has been tasked to implement visualization products to assess the potential for supercell thunderstorms and significant tornadoes, and to improve assessments of short-term cloud-to-ground (CG) lightning potential. This paper and presentation focuses on the visualization products developed by the AMU for the operational high-resolution ADAS and AR.PS at the NWS MLB and SMG. The two severe weather threat graphics implemented within ADAS/ARPS are the Supercell Composite Parameter (SCP) and Significant Tornado Parameter (SIP). The SCP was designed to identify areas with supercell thunderstorm potential through a combination of several instability and shear parameters. The SIP was designed to identify areas that favor supercells producing significant tornadoes (F2 or greater intensity) versus non-tornadic supercells. Both indices were developed by the NOAAINWS Storm Prediction Center (SPC) and were normalized by key threshold values based on previous studies. The indices apply only to discrete storms, not other convective modes. In a post-analysis mode, the AMU calculated SCP and SIP for graphical output using an ADAS configuration similar to the operational set-ups at NWS MLB and SMG. Graphical images from ADAS were generated every 15 minutes for 13 August 2004, the day that Hurricane Charley approached and made landfall on the Florida peninsula. Several tornadoes struck the interior of the Florida peninsula in advance of Hurricane Charley's landfall during the daylight hours of 13 August. Since SPC had previously examined this case using SCP and SIP graphics generated from output of the Rapid Update Cycle (RUC) model, this day served as a good benchmark to compare and validate the high-resolution ADAS graphics against the smoother RUC analyses, which serves as background fields to the ADAS analyses. The ADAS-generated SCP and STP graphics have been integrated into the suite of products examined operationally by NWS MLB forecasters and are used to provide additional guidance for assessment of the near-storm environment during convective situations.

Case, Jonathan↗

Biochemical Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels and Products: 2020 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for biochemical platform research. It allows the impact of research progress to be quantified in terms of economic improvements in the overall cellulosic biofuel production process for a particular conversion pathway. As such, initial benchmarks can be established for currently demonstrated performance and progress can be tracked towards out-year goals to ultimately demonstrate cost-competitive cellulosic biofuel technology. The purpose of this report is to benchmark the latest experimental developments across a number of potential bioconversion pathways as quantified by modeled minimum fuel selling prices (MFSPs), as a measure of current status relative to those final targets. For this state of technology, TEA models were run for two separate biological conversion pathways to fuels, based on available data for integrated biomass deconstruction and hydrolysate processing; namely carboxylic acids (primarily butyric acid) and diols (2,3-butanediol [BDO]), reflecting NREL's recently-published 2018 biochemical design report focused on those two pathways. The models were run across three scenarios for lignin utilization, namely combustion, conversion to coproducts based on "base case" performance with biomass hydrolysate, and conversion to coproducts based on "high" performance demonstrated with model lignin monomer components. Relative to prior 2019 benchmarks, the 2020 SOT achieved further MFSP reductions of approximately $1/gallon gasoline equivalent, primarily attributed to improvements in pretreatment that led to both cost reductions and yield improvements.

09 BIOMASS FUELS↗

Variational control forces for enhanced sampling of nonequilibrium molecular dynamics simulations

We introduce a variational algorithm to estimate the likelihood of a rare event within a nonequilibrium molecular dynamics simulation through the evaluation of an optimal control force. Optimization of a control force within a chosen basis is made possible by explicit forms for the gradients of a cost function in terms of the susceptibility of driven trajectories to changes in variational parameters. We consider probabilities of time-integrated dynamical observables as characterized by their large deviation functions and find that in many cases, the variational estimate is quantitatively accurate. Additionally, we provide expressions to exactly correct the variational estimate that can be evaluated directly. We benchmark this algorithm against the numerically exact solution of a model of a driven particle in a periodic potential, where the control force can be represented with a complete basis. Additionally, we then demonstrate the utility of the algorithm in a model of repulsive particles on a line, which undergo a dynamical phase transition, resulting in singular changes to the form of the optimal control force. In both systems, we find fast convergence and are able to evaluate large deviation functions with significant increases in statistical efficiency over alternative Monte Carlo approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Summary of Validation Studies for the Integrated TIGER Series Performed on ACORN Plus-up 218468/99

The Integrated TIGER Series (ITS) transport code is a valuable tool for photon-electron transport. A seven-problem validation suite exists to make sure that the ITS transport code works as intended. It is important to ensure that data from benchmark problems is correctly compared to simulated data. Additionally, the validation suite did not previously make use of a consistent quantitative metric for comparing experimental and simulated datasets. To this end, the goal of this long-term project was to expand the validation suite both in problem type and in the quality of the error assessment. To accomplish that, the seven validation problems in the suite were examined for potential drawbacks. When a drawback was identified, the problems were ranked based on severity of the drawback and approachability of a solution. We determined that meaningful improvements could be made to the validation suite by improving the analysis for the Lockwood Albedo problem and by introducing the Ross dataset as an eighth problem to the suite. The Lockwood error analysis has been completed and will be integrated in the future. The Ross data is unfinished, but significant progress has been made towards analysis.

97 MATHEMATICS AND COMPUTING↗

Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation

This Final Scientific and Technical Report summarizes work performed under the Phase IIA SBIR project “Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation” (DE-SC0020906) from August 2023 through August 2025. The objective of the Phase IIA effort was to mature and harden capabilities developed during Phase II, with the goal of enabling practical interoperability between Coreform’s isogeometric analysis (IGA) technologies and the Multiphysics Object-Oriented Simulation Environment (MOOSE), while improving robustness, performance, and scalability for complex, nuclear-relevant geometries. Over the course of Phase IIA, the project established and validated an extraction-based interoperability pathway between Coreform tools and MOOSE. A combined mesh and matrix format was defined collaboratively with MOOSE developers and integrated into the solver, enabling standard MOOSE workflows to operate on data exported from Coreform’s IGA and Flex Representation Method (FRM) pipelines. Early demonstrations validated architectural compatibility using linear solid mechanics problems, while later efforts focused on benchmark testing and external use. By the end of the project period, engineers at BWXT were able to independently set up and execute a simulation using the Coreform–MOOSE workflow and provide direct feedback that informed further refinement. In parallel, substantial effort was devoted to improving the robustness of trimmed U-spline construction for complex CAD geometries. A growing test suite of nuclear-relevant models was compiled through collaboration with multiple stakeholders and used to drive extensive bug fixing and reliability improvements. These efforts resulted in improved robustness and performance, including the addition of fallback capabilities that enhance reliability when the underlying commercial CAD kernel fails. Performance-oriented work progressed later in the project, with the development and demonstration of methods to decompose complex geometries into structured subregions and updated data representations to support more efficient solver processing. Additionally, extensive enhancements to threadsafe parallel data structures and trimming operations established a foundation for scalable processing of large assemblies. Collaboration with Sandia National Laboratories on the SGM geometric modeling kernel advanced to a functioning interface test case, positioning the workflow for future kernel integration. Overall, the Phase IIA effort successfully transitioned the project from architectural proof-of-concept to externally exercised, solver-integrated capability, while clarifying remaining technical challenges related to standardization, performance optimization, and kernel integration.

42 ENGINEERING↗

Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps

Abstract Interpretation of cryo-electron microscopy (cryo-EM) maps requires building and fitting 3D atomic models of biological molecules. AlphaFold-predicted models generate initial 3D coordinates; however, model inaccuracy and conformational heterogeneity often necessitate labor-intensive manual model building and fitting into cryo-EM maps. In this work, we designed a protein model-building workflow, which combines a deep-learning cryo-EM map feature enhancement tool, CryoFEM (Cryo-EM Feature Enhancement Model) and AlphaFold. A benchmark test using 36 cryo-EM maps shows that CryoFEM achieves state-of-the-art performance in optimizing the Fourier Shell Correlations between the maps and the ground truth models. Furthermore, in a subset of 17 datasets where the initial AlphaFold predictions are less accurate, the workflow significantly improves their model accuracy. Our work demonstrates that the integration of modern deep learning image enhancement and AlphaFold may lead to automated model building and fitting for the atomistic interpretation of cryo-EM maps.

59 BASIC BIOLOGICAL SCIENCES↗

A New Era of Nuclear Criticality Experiments: The First 10 Years of Radiation Test Object Operations at NCERC

The work presented in this paper focuses on the first 10 years (2011–2020) of radiation test object (RTO) operations at the National Criticality Experiments Research Center. RTOs are subcritical configurations of special nuclear material that are built by hand. These configurations are utilized for benchmark experiments, detector testing/characterization, and training. An overview of the types of measurements used in RTO operations is given as well as a history of RTO operations at Los Alamos National Laboratory from 1944–2011.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advances in Integrally Formed Metallic Structures

NASA Langley Research Center (LaRC) is applying flow forming technology to aerospace aluminum alloys for the manufacture of integrally stiffened cylinders that meet aircraft fuselage or launch vehicle specifications. High-strength 2xxx series alloys, in various temper/product form conditions, are being compared with medium-strength, very formable AA 6061 as the benchmark. Screening of candidate materials traditionally relies on empirical forming trials, but more recently on metrics derived from constant nominal strain rate tensile testing. In this work, the established hierarchy of formability metrics is adopted as the baseline; tensile area reduction, work hardening exponent, and modulus of resilience. The suite of metrics can be expanded based on phenomenological and mechanistic considerations of plastic flow instabilities to incorporate anisotropy ratio, rate of work hardening, and dynamic strain aging effects. Separate research thrusts at LaRC are aimed at formulating a protocol for scalable production of fully formed, defect-free components: 1) quantifying the extended set of formability metrics from constant and jump strain rate tensile tests with digital image correlation (DIC); 2) using statistically designed experiments on a vertical spin/flow forming facility (WF VUD-600®) to isolate the effect of convenient process variables, such as axial feed rate and thickness reduction; and 3) predicting the effect of feed ratio (roller translation relative to mandrel rotation speeds) on material response via process modeling using the DEFORM® simulation software. Current results will be discussed in terms of correlating intrinsic material properties with the bulk workability characteristics to successfully fabricate cylinders with complex cross-sections.

Aluminum↗

Critical Experiment Design Phase 2 Report for Integral Request 304

This report documents the second phase of the critical experiment design process (CED-2) conducted as part of integral experiment request (IER) 304. The purpose of IER-304 is to develop a temperature-dependent critical experiment capability at the Sandia National Laboratories critical experiment facility using low-enriched uranium oxide fuel. Only a few benchmark quality critical experiments are currently available to validate criticality safety computational methods at temperatures other than room temperature. Recent advancements in computational techniques such as implementation of on-the-fly Doppler broadening techniques and advanced treatment of thermal scattering data necessitate the development of additional experimental capabilities in this area. The work described in this report developed representative configurations using 7uPCX and BUCCX fuels, analyzed the physics exercised by the different arrays, and analyzed the estimated experimental uncertainties. This report also scopes the information necessary for performing modifications to the reactor to accommodate operation at elevated and reduced temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Search for magnetic monopoles and stable particles with high electric charges in $\sqrt{s}$ = 13 TeV pp collisions with the ATLAS detector

We present a search for magnetic monopoles and high-electric-charge objects using LHC Run 2 $\sqrt{s}$ = 13 TeV proton-proton collisions recorded by the ATLAS detector. A total integrated luminosity of 138 fb –1 was collected by a specialized trigger. No highly ionizing particle candidate was observed. Considering the Drell-Yan and photon-fusion pair production mechanisms as benchmark models, cross-section upper limits are presented for spin-0 and spin-1/2 magnetic monopoles of magnetic charge 1g D and 2g D and for high-electric-charge objects of electric charge 20 ≤ |z| ≤ 100, for masses between 200 GeV and 4000 GeV. The search improves by approximately a factor of three the previous cross-section limits on the Drell-Yan production of magnetic monopoles and high-electric charge objects. Also, the first ATLAS limits on the photon-fusion pair production mechanism of magnetic monopoles and high-electric-charge objects are obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗