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

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At least 685 records · Page 38

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

AI-based foundation models like FourCastNet, GraphCast are revolutionizing weather and climate predictions but are not yet ready for operational use. Their limitation lies in the absence of a data assimilation system to incorporate real-time Earth system observations, crucial for accurately forecasting events like tropical cyclones. To overcome these obstacles, we introduce a generic real-time data assimilation framework and demonstrate its end-to-end performance on the Frontier supercomputer. This framework comprises two primary modules: an ensemble score filter (EnSF), which significantly outperforms the state-of-the-art data assimilation method, and a vision transformer-based surrogate capable of real-time adaptation through the integration of observational data. We demonstrate both the strong and weak scaling of our framework up to 1024 GPUs on the Exascale supercomputer, Frontier. Our results not only illustrate the framework's exceptional scalability on high-performance computing systems, but also demonstrate the importance of supercomputers in real-time data assimilation for weather and climate predictions.

Lu, Dan↗

Program structure-based blocking

Embodiments relate to program structure-based blocking. An aspect includes receiving source code corresponding to a computer program by a compiler of a computer system. Another aspect includes determining a prefetching section in the source code by a marking module of the compiler. Yet another aspect includes performing, by a blocking module of the compiler, blocking of instructions located in the prefetching section into instruction blocks, such that the instruction blocks of the prefetching section only contain instructions that are located in the prefetching section.

97 MATHEMATICS AND COMPUTING↗

Program structure-based blocking

Embodiments relate to program structure-based blocking. An aspect includes receiving source code corresponding to a computer program by a compiler of a computer system. Another aspect includes determining a prefetching section in the source code by a marking module of the compiler. Yet another aspect includes performing, by a blocking module of the compiler, blocking of instructions located in the prefetching section into instruction blocks, such that the instruction blocks of the prefetching section only contain instructions that are located in the prefetching section.

97 MATHEMATICS AND COMPUTING↗

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗

FY25 MOOSE Usability Improvements: 3D Meshing Capabilities, Initiation of Geometry Support for Monte Carlo Tools, and Enhancement of MOOSE/Workbench User Input Interactions

Usability improvements have been made to MOOSE and Workbench in FY25 to enhance usability and user workflows. Assorted enhancement have been made to MOOSE’s intrinsic meshing capabilities in order to enable more flexible and complex meshing of nuclear reactor systems, in particular for 3D applications. Mesh generators have been added to perform operations such as batch mesh generation, surface mesh generation, and creation of 3D transition layers. These mesh generation capabilities make it much easier to generate high quality non-extruded 3D meshes. Additionally, work to integrate Monte Carlo reactor physics simulations into MOOSE-based multi-physics workflows has reached another milestone with the implementation of the Constructive Solid Geometry (CSG) base framework. This framework lays the foundation for mesh generators to offer the user a generic CSG output option (as opposed to a finite element mesh). To support users, workshop on the MOOSE Reactor Module was delivered which featured hands-on examples using the NEAMS Workbench on INL’s High Performance Computing system. Recent updates to the NEAMS Workbench, WASP, and the MOOSE language server have introduced several improvements aimed at making MOOSE-based simulation setup and input management faster, more accurate, and easier to use. Key capabilities that have been added include multi-tab-stop autocompletion, visual input diagnostics, developer-directed data visualizations, upgraded ParaView integration, and Workspace-level file tracking. Together, these changes make it easier for users to build, validate, and manage complex MOOSE-based simulation models — especially those involving reusable components, included files, and datasets. The improvements are designed to save time, reduce input errors, and help users get to a successful simulation run faster, with more confidence in the results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

OECD/NEA EGMPEBV Activities in Multi-Physics Verification and Validation

The Expert Group on Multi-Physics Experimental Data, Benchmarks and Validation (EGMPEBV) was established in 2014 by the Nuclear Energy Agency (NEA) at the Organization for Economic Co-operation and Development (OECD) to establish processes for certification of experimental data and development of benchmark models for validation of Multi-Physics (MP) Modeling and Simulation (M and S) computational systems. The aim of the group is to provide member countries with guidelines and recommendations for validating and improving their novel multi-physics simulations, and with an access to key experimental data. To be used to their full potential, these novel tools will require a more complex suite of validation experiments due to the multiple energy, spatial and temporal scales, as well as the number of physical phenomena being simulated. They will also require accurate measurements of all terms, including coupling terms representing the feedback effects, in situations where the appropriate experimental techniques and facilities might not exist today. However, the ability to conduct validation experiments has for certain applications progressed at a slower pace than for computational methods, or in some cases it has significantly regressed (through shutdown of facilities, or through retirement of experts). In addition, as modelling capabilities are reaching deeper levels in single physics phenomena and in coupled behaviors, appropriate experimental techniques may not yet exist. Validation of multiple physics models requires a wide variety of experimental data, which emphasizes the importance of maximizing the use of historically accumulated data to avoid the significant cost of performing similar experiments today. Moreover, the pedigree and quality of this data as it pertains to modern day simulation methods may be insufficient for rigorous validation of high fidelity modeling and simulation tools. Thus, these data can often exhibit limitations including a lack of measurement accuracy or a lack of knowledge of the measurement uncertainty in the experimental techniques; an absence of measurements for some critical parameters; an obscuring of relationships between individual physics phenomena owing to the output data resolution; or simply an inability to allow for a detailed reinterpretation of the experiments based on the documented information. The organization of the EGMPEBV relies on three Task Forces, focused on 1) Experimental Data Qualification and Benchmark Evaluation; 2) Methods and Standards, and 3) Specific Applications. Task Force 1 is focused on providing better and more accurate experimental datasets, which support validation of high-fidelity multi-physics modelling and simulation (M and S) tools. At the same time it has to consider the incompleteness of past experimental data sets (in terms of data, documentation, or uncertainties) and with the limited number of available multi-physics experimental facilities. Task Force 2 is designed to develop validation methods and guidelines, and uncertainty qualification for the new family of multi-physics, multi-scale codes in the context of emerging demands such as longer fuel cycles and power uprate. Task Force 3 is focused on applications of validation experiments and has the objective to organize multi-physics M and S benchmarks involving validation experiments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

AI-Science for Performance Optimization and Diagnosis of Science Instrument Federations

Next generation of science workflows are expected to be executed over complex federations composed of supercomputers, science instruments, storage systems and networks, with new additions of the edge and cloud systems and services. The sheer complexity of these multi-domain federations makes it hard to manage them and optimize their performance, as small impedance mismatches (that can dynamically develop between systems) could drastically degrade the entire federation performance. Recent proliferation of Software Defined Everything (SDX) technologies combined with containerization frameworks provide custom instruments that can monitor and collect critical measurements at various levels to support diagnoses and performance optimization; but their data too enormous for human operators and analysts to process and generate decisions. Machine Learning (ML) methods that extract critical parameters, relationships and trends from the data offer general solutions. Artificial Intelligence (AI) and ML methods must be custom-developed for these problems based on solid, rigorous foundations, since black-box approaches are often ineffective and unsound.We propose to develop comprehensive AI-Science for the performance of science federations to (i) monitor and control storage, networks, experiments, and computing systems across multiple domains via softwarization layers, at speeds and scales orders of magnitude superior to current practice, (ii) optimally realize and orchestrate complex workflows with high performance by using dynamic state and performance estimation methods, and (iii) aggregate measurements across sites and time to develop infrastructure-level profiles, optimizations and diagnoses using AI-Science based on foundational principles from ML, game theory, and information fusion areas.

Rao, Nageswara↗

A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

33 ADVANCED PROPULSION SYSTEMS↗

Analog-to-digital converter based on voltage-controlled superconducting devices

The increasing demand for cryogenic electronics in superconducting and quantum computing systems calls for ultra-energy-efficient data conversion architectures that remain functional at deep cryogenic temperatures. Here, in this work, we present the first design of a voltage-controlled superconducting flash analog-to-digital converter (ADC) based on a voltage-controlled quantum-enhanced Josephson junction field-effect transistor (JJFET). Exploiting its strong gate tunability and transistor-like behavior, the JJFET offers a scalable alternative to conventional current-controlled superconducting devices while aligning naturally with CMOS-style design methodologies. Building on our previously developed Verilog-A compact model calibrated to experimental data, we design and simulate a three-bit JJFET-based flash ADC targeted for integration within cryogenic control and readout circuitry in quantum computing. The core comparator block is realized through careful bias current selection and augmented with a three-terminal nanocryotron to precisely define reference voltages. Cascaded JJFET comparators ensure robust voltage gain, cascadability, and logic-level restoration across stages. Simulation results demonstrate accurate quantization behavior with ultra-low power dissipation, underscoring the feasibility of voltage-driven superconducting mixed-signal circuits. This work establishes a critical step toward unifying superconducting logic and data conversion, paving the way for scalable cryogenic architectures in quantum–classical co-processors, low-power artificial intelligence accelerators, and next-generation energy-constrained computing platforms.

Analog-to-digital converter↗

Parallel Evolutionary Optimization for Neuromorphic Network Training

One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

97 MATHEMATICS AND COMPUTING↗

Nek5000/RS performance on advanced GPU architectures

The authors explore performance scalability of the open-source thermal-fluids code, NekRS, on the U.S. Department of Energy's leadership computers, Crusher, Frontier, Summit, Perlmutter, and Polaris. Particular attention is given to analyzing performance and time-to-solution at the strong-scale limit for a target efficiency of 80%, which is typical for production runs on the DOE's high-performance computing systems. Several examples of anomalous behavior are also discussed and analyzed.

97 MATHEMATICS AND COMPUTING↗

Vancouver 2: Improving Programmability of Contemporary Heterogeneous Architectures, Final Report

The University of Oregon (UO) was a partner in the Vancouver 2 project together with Oak Ridge National Laboratory (ORNL), the University of Illinois-Urbana/Champaign (UIUC), and the Geor- gia Institute of Technology (GT). UO’s objective in the project was to advance the performance technology for evolving heterogenous computing systems, especially for exascale platforms. During the project period, our efforts focused on the advances taking place in manycore and accelera- tor processors, specifically those found in GPU and MIC devices. In addition to the design and development of novel performance measurement and analysis techniques, UO demonstrated these capabilities on real HPC applications and current generation heterogeneous machines. The following final report summarizes our accomplishments during the Vancouver 2 project, highlighting research work in the recent year (Year 3).

97 MATHEMATICS AND COMPUTING↗

The CMS Tier0 goes cloud and grid for LHC Run 2

In 2015, CMS will embark on a new era of collecting LHC collisions at unprecedented rates and complexity. This will put a tremendous stress on our computing systems. Prompt Processing of the raw data by the Tier-0 infrastructure will no longer be constrained to CERN alone due to the significantly increased resource requirements. In LHC Run 2, we will need to operate it as a distributed system utilizing both the CERN Cloud-based Agile Infrastructure and a significant fraction of the CMS Tier-1 Grid resources. In another big change for LHC Run 2, we will process all data using the multi-threaded framework to deal with the increased event complexity and to ensure efficient use of the resources. Furthermore, this contribution will cover the evolution of the Tier-0 infrastructure and present scale testing results and experiences from the first data taking in 2015.

97 MATHEMATICS AND COMPUTING↗

NARAC Dispersion Model Product Integration With RadResponder

Work on enhanced cooperation and interoperability of Nuclear Incident Response Teams (NIRT) is a joint effort between DHS/FEMA, DOE/NNSA and EPA. One such effort was the integration between the RadResponder Network, a resource sponsored by FEMA for the management of radiological data during an emergency, and the National Atmospheric Advisory Center (NARAC), a DOE/NNSA modeling resource whose predictions are used to aid radiological emergency preparedness and response. Working together under a FEMA-sponsored project these two radiological response assets developed a capability to read and display plume model prediction results from the NARAC computer system in the RadResponder software tool. As a result of this effort, RadResponder users have been provided with NARAC modeling predictions of contamination areas, radiological dose levels, and protective action areas (e.g., areas warranting worker protection or sheltering/evacuation) to help guide protective action decisions and field monitoring surveys, and gain key situation awareness following a radiological/nuclear accident or incident (e.g., nuclear power plant accident, radiological dispersal device incident, or improvised nuclear detonation incident). This document describes the details of this integration effort.

54 ENVIRONMENTAL SCIENCES↗

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data

Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

58 GEOSCIENCES↗

On the optimal sizing of power take-off systems for wave energy converters

The power take-off (PTO) system in a wave energy converter (WEC) is the means by which the energy in an ocean wave is converted into useful energy. There has been a general lack of technology convergence in the wave energy industry and PTO design has been largely device-specific with the design process determined by the WEC developer. An optimized PTO design can significantly affect the efficiency, reliability, performance, and overall cost and viability of a device. There remains a need in the marine energy industry for best practices and efficient design processes to be identified as it could greatly benefit developers and researchers in designing an optimal WEC PTO. This research utilizes the open-source Matlab-Simulink based software, WEC-Sim, which was developed by the National Renewable Energy Laboratory, and the Eagle, a high-performance computing system, to model and optimize two WECs of different archetypes and then investigates if any trends exist that can be exploited for greater efficiency in optimal PTO design. The results from this research indicate that there may be an optimal sizing for WEC PTOs for both power and PTO force rating and that substantial reductions can be made in the cost of a device without significant loss in the energy produced. Furthermore this optimal sizing may be independent of WEC type and deployment location. With an optimal, or near optimal, approach to WEC PTO sizing demonstrated, a methodology is proposed to address the challenge of nameplate ratings in the wave energy industry.

13 HYDRO ENERGY↗

PHISICS User Manual

PHISICS (Parallel and Highly Innovative Simulation for INL Code System) is a reactor physics package developed at the Idaho National Laboratory. It is composed of several modules: a nodal and semi-structured transport core solver (INSTANT), a depletion module (MRTAU), a time-dependent solver (TimeIntegrator), a cross-section interpolation and manipulation framework (MIXER), a SuperHomogenization scheme (SPH) a criticality search module (CRITICALITY), a fuel management and shuffling component (SHUFFLE) and a coupling API with RELAP5-3D. PHISICS has been built in a highly modular fashion so that different physical models can be activated or deactivated depending on the physics relevant to the particular type of analysis. This approach simplifies development as well as mid- and long-term maintenance of the code. PHISICS is entirely written in FORTRAN 95/2003. Each of its components is fully parallelized and designed to take full advantage of shared-memory computers (multiprocessor desktops and workstations) and middle to large high-performance computing systems (10 to 1000 processors). The aim of this document is to detail the input requirements for PHISICS (and all its modules) focusing on the input structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗