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At least 973 records · Page 54

CFD-Based Design of Turbopump Inlet Duct for Reduced Dynamic Loads

Numerical simulations have been completed for a variety of designs for a 90 deg elbow duct. The objective is to identify a design that minimizes the dynamic load entering a LOX turbopump located at the elbow exit. Designs simulated to date indicate that simpler duct geometries result in lower losses. Benchmark simulations have verified that the compressible flow codes used in this study are applicable to these incompressible flow simulations.

Rothermel, Jeffry↗

LISA Framework for Enhancing Gravitational Wave Signal Extraction Techniques

This paper describes the development of a Framework for benchmarking and comparing signal-extraction and noise-interference-removal methods that are applicable to interferometric Gravitational Wave detector systems. The primary use is towards comparing signal and noise extraction techniques at LISA frequencies from multiple (possibly confused) ,gravitational wave sources. The Framework includes extensive hybrid learning/classification algorithms, as well as post-processing regularization methods, and is based on a unique plug-and-play (component) architecture. Published methods for signal extraction and interference removal at LISA Frequencies are being encoded, as well as multiple source noise models, so that the stiffness of GW Sensitivity Space can be explored under each combination of methods. Furthermore, synthetic datasets and source models can be created and imported into the Framework, and specific degraded numerical experiments can be run to test the flexibility of the analysis methods. The Framework also supports use of full current LISA Testbeds, Synthetic data systems, and Simulators already in existence through plug-ins and wrappers, thus preserving those legacy codes and systems in tact. Because of the component-based architecture, all selected procedures can be registered or de-registered at run-time, and are completely reusable, reconfigurable, and modular.

Thompson, David E.↗

BlackjackBench: Portable Hardware Characterization

DARPA's AACE project aimed to develop Architecture Aware Compiler Environments that automatically characterize the hardware and optimize the application codes accordingly. We present the BlackjackBench suite, a collection of portable micro-benchmarks that automate system characterization, plus statistical analysis techniques for interpreting the results. BlackjackBench discovers the effective sizes and speeds of the hardware environment rather than the often unattainable peak values. We aim at hardware features that can be observed by running executables generated by existing compilers from standard C codes. We characterize the memory hierarchy, including cache sharing and NUMA characteristics of the system, properties of the processing cores affecting execution speed, and the length of the OS scheduler time slot. We show how these features of modern multicores can be discovered programmatically. We also show how the features could interfere with each other resulting in incorrect interpretation of the results, and how established classification and statistical analysis techniques reduce experimental noise and aid automatic interpretation of results.

99 GENERAL AND MISCELLANEOUS↗

An Efficient, Scalable IO Framework for Sparse Data: larcv3

Neutrino physics is one of the fundamental areas of research into the origins and properties of the Universe. Many experimental neutrino projects use sophisticated detectors to observe properties of these particles, and have turned to deep learning and artificial intelligence techniques to analyze their data. From this, we have developed \texttt{larcv}, a \texttt{C++} and \texttt{Python} based framework for efficient IO of sparse data with particle physics applications in mind. We describe in this paper the \texttt{larcv} framework and some benchmark IO performance tests. \texttt{larcv} is designed to enable fast and efficient IO of ragged and irregular data, at scale on modern HPC systems, and is compatible with the most popular open source data analysis tools in the Python ecosystem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks

Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are required to perform calculations within the strict timing constraints for real-time operation. However, traditional computing platforms responsible for running these algorithms incur a large overhead due to communication protocols, memory accesses, and static (often generic) architectures. In this work, we implement a low-latency Multi-Layer Perceptron (MLP) processor using Field Programmable Gate Arrays (FPGAs). Unlike CPUs and Graphics Processing Units (GPUs), our FPGA-based design can directly interface sensors, storage devices, display devices and even actuators, thus reducing the delays of data movement between ports and compute pipelines. Moreover, the compute pipelines themselves are tailored specifically to the application, improving resource utilization and reducing idle cycles. We demonstrate the effectiveness of our approach using mass-spectrometry data sets for real-time cancer detection. We demonstrate that correct parameter sizing, based on the application, can reduce latency by 20% on average. Furthermore, we show that in an application with tightly coupled data-path and latency constraints, having a large amount of computing resources can actually reduce performance. Using mass-spectrometry benchmarks, we show that our proposed FPGA design outperforms both CPU and GPU implementations, with an average speedup of 144x and 21x, respectively. In our work, we demonstrate the importance of application-specific optimizations in order to minimize latency and maximize resource utilization for MLP inference. By directly interfacing and processing sensor data with ultra-low latency, FPGAs can perform real-time analysis during procedures and provide diagnostic feedback that can be critical to achieving higher percentages of successful patient outcomes.

60 APPLIED LIFE SCIENCES↗

Influence of Pt-Metal Alloy Catalysts with Various Ionomers on Oxygen Reduction Reaction in Fuel Cell Application

Pt-M/C (M = Co, Ni, Mn, etc.) alloy catalysts exhibit superior oxygen reduction reaction (ORR) activity compared to pure Pt/C, leading to a high energy efficiency in hydrogen fuel cells. However, many Pt-M/C alloy catalysts were synthesized and evaluated at the lab scale in model test-bed systems like rotating disc electrodes, which don't always correlate to performance within a fuel cell system; there is a clear need to evaluate catalysts in electrodes that can be prepared at industrially relevant scales to evaluate how factors like ink formulation can greatly affect device-level of fuel cell performance. Herein, three commercial Pt-M/C alloy catalysts (two Pt-Co/C and one Pt-Ni/C) were comprehensively characterized by various techniques. The results show that the average particle sizes of the three catalysts are close to 5 nm; the atomic ratio of Pt/M is around 4; and the M was successfully embedded into Pt lattice, resulting in the positive shift of Pt 4f in XPS spectra and XRD patterns. These catalytic materials were incorporated into 9 different cathode catalyst layers (CCLs) with three kinds of ionomers (Nafion D2020, high oxygen permeability ionomer (HOPI), and Aquivion D79-25BS), and their performance in proton exchange membrane fuel cells (PEMFCs) were investigated. The results demonstrate that the Pt-Co/C catalysts possess a higher mass activity (MA) than Pt-Ni/C; the cathodes with Nafion ionomer provide the highest MA while electrodes with Aquivion ionomer showed the lowest activity, attributed to poor H+ conductivity resulting from suboptimal ionomer incorporation. Finally, these alloys were shown to exceed DOE targets for MA and H2/Air performance reported in the recent publications at beginning of life and after 90k cycle catalyst AST protocol. This study provides valuable performance benchmarks for these materials guiding future Pt-M/C catalyst design and material integration for heavy duty PEMFC applications.

08 HYDROGEN↗

A Co-Design Study Of Fusion Whole Device Modeling Using Code Coupling

Complex workflows consisting of multiple simulation and analysis codes running concurrently through in-memory coupling is becoming popular due to inherent advantages in online management of large-scale data, resilience, and the code development process. However, orchestrating such a multi-application workflow to efficiently utilize resources on a heterogeneous architecture is challenging. In this paper, we present our results with running the Fusion Whole Device Modeling benchmark workflow on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory. We explore various resource distribution and process placement mechanisms, including sharing compute nodes between processes from separate applications. We show that fine-grained process placement can have a significant impact towards efficient utilization of the compute power of a node on Summit, and conclude that sophisticated tools for performing co-design studies of multi-application workflows can play an important role towards efficient orchestration of such workflows.

Choi, Jong Youl↗

Development and Testing of the VITAMIN-B7/BUGLE-B7 Coupled Neutron-Gamma Multigroup Cross-Section Libraries

The U.S. Nuclear Regulatory Commission s Regulatory Guide 1.190 states that calculational methods used to estimate reactor pressure vessel (RPV) fluence should use the latest version of the Evaluated Nuclear Data File (ENDF). The VITAMIN-B6 fine-group library and BUGLE-96 broad-group library, which are widely used for RPV fluence calculations, were generated using ENDF/B-VI data, which was the most current data when Regulatory Guide 1.190 was issued. We have developed new fine-group (VITAMIN-B7) and broad-group (BUGLE-B7) libraries based on ENDF/B-VII. These new libraries, which were processed using the AMPX code system, maintain the same group structures as the VITAMIN-B6 and BUGLE-96 libraries. Verification and validation of the new libraries was accomplished using diagnostic checks in AMPX, unit tests for each element in VITAMIN-B7, and a diverse set of benchmark experiments including critical evaluations for fast and thermal systems, a set of experimental benchmarks that are used for SCALE regression tests, and three RPV fluence benchmarks. The benchmark evaluation results demonstrate that VITAMIN-B7 and BUGLE-B7 are appropriate for use in LWR shielding applications, and meet the calculational uncertainty criterion in Regulatory Guide 1.190.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model

Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging in dimensions larger than one. The relative simplicity of this model, embodied by the sparseness of the Hamiltonian matrix, allows for its efficient implementation on quantum computers, and for its approximate solution using variational algorithms such as the variational quantum eigensolver. While these algorithms have been shown to reproduce the qualitative features of the Hubbard model, their quantitative accuracy in terms of producing true ground state energies and other properties, and the dependence of this accuracy on the system size and interaction strength, the choice of variational ansatz, and the degree of spatial inhomogeneity in the model, remains unknown. Here we present a rigorous classical benchmarking study, demonstrating the potential impact of these factors on the accuracy of the variational solution of the Hubbard model on quantum hardware, for systems with up to 32 qubits. We find that even when using the most accurate wavefunction ansätze for the Hubbard model, the error in its ground state energy and wavefunction plateaus for larger lattices, while stronger electronic correlations magnify this issue. Concurrently, spatially inhomogeneous parameters and the presence of off-site Coulomb interactions only have a small effect on the accuracy of the computed ground state energies. Our study highlights the capabilities and limitations of current approaches for solving the Hubbard model on quantum hardware, and we discuss potential future avenues of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

HDRMC, an accelerated Monte Carlo dose calculator for high dose rate brachytherapy with CT-compatible applicators

Purpose: To present a new accelerated Monte Carlo code for CT-based dose calculations in high dose rate (HDR) brachytherapy. The new code (HDRMC) accounts for both tissue and nontissue heterogeneities (applicator and contrast medium). Methods: HDRMC uses a fast ray-tracing technique and detailed physics algorithms to transport photons through a 3D mesh of voxels representing the patient anatomy with applicator and contrast medium included. A precalculated phase space file for the{sup 192}Ir source is used as source term. HDRM is calibrated to calculated absolute dose for real plans. A postprocessing technique is used to include the exact density and composition of nontissue heterogeneities in the 3D phantom. Dwell positions and angular orientations of the source are reconstructed using data from the treatment planning system (TPS). Structure contours are also imported from the TPS to recalculate dose-volume histograms. Results: HDRMC was first benchmarked against the MCNP5 code for a single source in homogenous water and for a loaded gynecologic applicator in water. The accuracy of the voxel-based applicator model used in HDRMC was also verified by comparing 3D dose distributions and dose-volume parameters obtained using 1-mm{sup 3} versus 2-mm{sup 3} phantom resolutions. HDRMC can calculate the 3D dose distribution for a typical HDR cervix case with 2-mm resolution in 5 min on a single CPU. Examples of heterogeneity effects for two clinical cases (cervix and esophagus) were demonstrated using HDRMC. The neglect of tissue heterogeneity for the esophageal case leads to the overestimate of CTV D90, CTV D100, and spinal cord maximum dose by 3.2%, 3.9%, and 3.6%, respectively. Conclusions: A fast Monte Carlo code for CT-based dose calculations which does not require a prebuilt applicator model is developed for those HDR brachytherapy treatments that use CT-compatible applicators. Tissue and nontissue heterogeneities should be taken into account in modern HDR brachytherapy planning.

61 RADIATION PROTECTION AND DOSIMETRY↗

Validation of Criticality Analysis Capability of SuperMC with ICSBEP

SuperMC is a general purpose, intelligent and multifunctional, continuous energy Monte Carlo program for the design and safety evaluation of nuclear systems. It is designed to perform the comprehensive neutronics calculation, taking the radiation transport as the core and including the depletion, radiation source term/dose/biohazard, material activation and transmutation, etc. The latest version of SuperMC can perform the simulation of neutron, photon and coupled neutron and photon transport, and also equipped with the functions of automatic modeling and visualization. SuperMC has been verified by more than 2000 benchmark models and experiments including the handbook of International Criticality Safety Benchmark Evaluation Project (ICSBEP), the Shielding Integral Benchmark Archive Database (SINBAD), etc. The fusion reactor (ITER benchmark model, FDS Fusion Reactors), fast reactors (BN600, CLEAR-I), PWR reactors (HM, BEAVRS) and cases from the International Reactor Physics handbook Evaluation Program (IRPhEP) were employed for validating the comprehensive capability for reactor applications. In this paper, the validation of SuperMC based on the handbook of ICSBEP will be presented. ICSBEP, released by OECD/NEA, contains criticality safety benchmark specifications derived from experiments that were performed at various nuclear critical facilities around the world, which was widely used to verify neutronic codes and associated nuclear data libraries for criticality safety analysis. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Benchmark Generation and Simulation at Extreme Scale

The path to extreme scale high-performance computing (HPC) poses several challenges related to power, performance, resilience, productivity, programmability, data movement, and data management. Investigating the performance of parallel applications at scale on future architectures and the performance impact of different architectural choices is an important component of HPC hardware/software co-design. Simulations using models of future HPC systems and communication traces from applications running on existing HPC systems can offer an insight into the performance of future architectures. This work targets technology developed for scalable application tracing of communication events. It focuses on extreme-scale simulation of HPC applications and their communication behavior via lightweight parallel discrete event simulation for performance estimation and evaluation. Instead of simply replaying a trace within a simulator, this work promotes the generation of a benchmark from traces. This benchmark is subsequently exposed to simulation using models to reflect the performance characteristics of future-generation HPC systems. This technique provides a number of benefits, such as eliminating the data intensive trace replay and enabling simulations at different scales. The presented work features novel software co-design aspects, combining the ScalaTrace tool to generate scalable trace files, the ScalaBenchGen tool to generate the benchmark, and the xSim tool to assess the benchmark characteristics within a simulator.

Lagadapati, Mahesh↗

WE-F-201-02: Review TG-186 and WGMBDCA Guidelines, Commission Process, and Dosimetry Benchmarks

With the recent introduction of heterogeneity correction algorithms for brachytherapy, the AAPM community is still unclear on how to commission and implement these into clinical practice. The recently-published AAPM TG-186 report discusses important issues for clinical implementation of these algorithms. A charge of the AAPM-ESTRO-ABG Working Group on MBDCA in Brachytherapy (WGMBDCA) is the development of a set of well-defined test case plans, available as references in the software commissioning process to be performed by clinical end-users. In this practical medical physics course, specific examples on how to perform the commissioning process are presented, as well as descriptions of the clinical impact from recent literature reporting comparisons of TG-43 and heterogeneity-based dosimetry. Learning Objectives: Identify key clinical applications needing advanced dose calculation in brachytherapy. Review TG-186 and WGMBDCA guidelines, commission process, and dosimetry benchmarks. Evaluate clinical cases using commercially available systems and compare to TG-43 dosimetry.

60 APPLIED LIFE SCIENCES↗

Building Benchmark Data Platform

This project is a three-year, four-laboratory collaboration to collect and curate a handful of high-resolution building systems datasets that have broad applicability to address highest-impact use cases. We will collect and curate high-resolution, well-calibrated time series of building operational and indoor/outdoor environmental data, which are crucial to understanding and optimizing building energy efficiency performance and demand flexibility capabilities as well as benchmarking energy algorithms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

BuildingQA: A Benchmark for Natural Language Question Answering over Building Knowledge Graphs

Graph-based representations of building metadata using ontologies like Brick are vital for smart building applications, but querying them remains a challenge for practitioners. Knowledge Graph Question Answering (KGQA) systems, meant to retrieve answers from natural language questions, traditionally require large-scale training data, making them ill-suited for the specialized and data-scarce building domain. The advent of Large Language Models (LLMs) offers a paradigm shift, enabling zero-shot natural language querying without building/domain-specific training. Yet, there is no standardized benchmark for building-specific KGQA which can guide and validate research in this area. To address this gap, our work makes three primary contributions. First, we introduce the BuildingQA Benchmark Dataset, constructed through a multi-stage process of collecting practitioner data, augmenting it with LLMs for linguistic diversity, and curating a final set of 188 questions across 4 buildings. Second, we characterize the benchmark's complexity and ambiguity, introducing a novel method to quantify its "lexical gap" and providing a four-stage diagnostic framework for analyzing how systems fail. Third, we benchmark zero-shot LLM-powered KGQA systems to establish baseline performance and analyze their failure modes. Our evaluation reveals that top-performing systems achieve a maximum F1 score of only 0.38. This result does not indicate a failure of these powerful systems, but rather underscores the unique challenges posed by our benchmark. It demonstrates a critical performance gap, showing that current methods successful on general KGs struggle with the specific lexical and structural nuances of the building domain. BuildingQA1 thus provides the benchmark dataset and foundational analysis needed to drive the development of novel, domain-aware methods required to unlock the use of semantic data in buildings.

Mulayim, Ozan Baris↗

High-Temperature Gas-Cooled Pebble-Bed Reactors Running In And Transient Modeling Capabilities Demonstration

This study presents a comprehensive benchmarking and verification effort of several thermal-hydraulic and multiphysics capabilities for high-temperature gas-cooled reactor (HTGR) applications. The first part of this effort focuses on the running-in verification of Griffin's multiphysics capabilities, specifically for simulating the evolution of Pebble Bed reactor cores from startup to equilibrium. In the absence of validation data, code-to-code comparisons are conducted with Kugelpy, showing good agreement for key quantities like maximum power density and fresh core k-eigenvalue predictions. However, discrepancies in equilibrium core predictions suggest potential issues with cross sections, underscoring the need for further refinement and evaluation. The HTTF system analysis code benchmark involves RELAP5-3D, SAM, and GAMMA+ to assess their predictive capabilities for HTTF behavior under both normal operation and pressurized conduction cooldown (PCC) transient conditions. While there is good agreement in predicting major parameters such as coolant temperature, solid temperature, and flow distribution, discrepancies in transient behavior highlight differences in modeling approaches, nodalizations, and heat transfer models. The HTTF lower plenum CFD benchmark employs nekRS to simulate flow mixing phenomena, successfully capturing relevant flow physics and demonstrating mesh independence in complex geometries. Preliminary results suggest a relatively uniform temperature field but significant unsteadiness in the flow, requiring time-averaging analyses. The GPBR200 system analysis code benchmark uses SAM's core channel and porous media models, incorporating an RCCS loop for decay heat removal. During steady-state and transient conditions, including protected de-pressurized and pressurized loss of forced cooling (DLOFC and PLOFC), both models show good agreement in predicting temperature profiles and key parameters. Notably, while the core channel model underpredicts convective heat transfer effects, both models maintain temperatures well below the TRISO fuel safety limit. These benchmarking efforts collectively enhance the predictive capabilities of the tools used in HTGR design and safety analysis, guiding developments to improve their accuracy and applicability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RADSAT Benchmarks for Prompt Gamma Neutron Activation Analysis Measurements

The accurate and efficient simulation of coupled neutron-photon problems is necessary for several important radiation detection applications. Examples include the detection of nuclear threats concealed in cargo containers and prompt gamma neutron activation analysis for nondestructive determination of elemental composition of unknown samples. High-resolution gamma-ray spectrometers are used in these applications to measure the spectrum of the emitted photon flux, which consists of both continuum and characteristic gamma rays with discrete energies. Monte Carlo transport is the most commonly used simulation tool for this type of problem, but computational times can be prohibitively long. This work explores the use of multi-group deterministic methods for the simulation of coupled neutron-photon problems. The main purpose of this work is to benchmark several problems modeled with RADSAT and MCNP to experimental data. Additionally, the cross section libraries for RADSAT are updated to include ENDF/B-VII cross sections. Preliminary findings show promising results when compared to MCNP and experimental data, but also areas where additional inquiry and testing are needed. The potential benefits and shortcomings of the multi-group-based approach are discussed in terms of accuracy and computational efficiency.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Skel: Generative Software for Producing Skeletal I/O Applications

Massively parallel computations consist of a mixture of computation, communication, and I/O. As part of the co-design for the inevitable progress towards exascale computing, we must apply lessons learned from past work to succeed in this new age of computing. Of the three components listed above, implementing an effective parallel I/O solution has often been overlooked by application scientists and was usually added to large scale simulations only when existing serial techniques had failed. As scientists teams scaled their codes to run on hundreds of processors, it was common to call on an I/O expert to implement a set of more scalable I/O routines. These routines were easily separated from the calculations and communication, and in many cases, an I/O kernel was derived from the application which could be used for testing I/O performance independent of the application. These I/O kernels developed a life of their own used as a broad measure for comparing different I/O techniques. Unfortunately, as years passed and computation and communication changes required changes to the I/O, the separate I/O kernel used for benchmarking remained static no longer providing an accurate indicator of the I/O performance of the simulation making I/O research less relevant for the application scientists. In this paper we describe a new approach to this problem where I/O kernels are replaced with skeletal I/O applications automatically generated from an abstract set of simulation I/O parameters. We realize this abstraction by leveraging the ADIOS middleware's XML I/O specification with additional runtime parameters. Skeletal applications offer all of the benefits of I/O kernels including allowing I/O optimizations to focus on useful I/O patterns. Moreover, since they are automatically generated, it is easy to produce an updated I/O skeleton whenever the simulation's I/O changes. In this paper we analyze the performance of automatically generated I/O skeletal applications for the S3D and GTS codes. We show that these skeletal applications achieve performance comparable to that of the production applications. We wrap up the paper with a discussion of future changes to make the skeletal application better approximate the actual I/O performed in the simulation.

99 GENERAL AND MISCELLANEOUS↗