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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

New Horizons for High-Performance Computing

Here we provide an overview of the past, present, and a diverse collection of future computer architecture alternatives for HPC. The end of Moore’s Law influenced the current HPC architecture focus on accelerated compute nodes composed of CPU and GPU computing components integrated into massively parallel processor architecture systems. There are many alternatives for future HPC directions, with different technologies, computing ecosystems, opportunities for lead user application-driven customization, and the role of open innovation business models. This paper provides an overview of these different new horizons for HPC, an organizing principle to focus future computing research, different public-private partnership models, and the critical role of workforce development.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

GASNet-EX: A High-Performance, Portable Communication Library for Exascale

Partitioned Global Address Space (PGAS) models, typified by such languages as Unified Parallel C (UPC) and Co-Array Fortran, expose one-sided communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity. GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. We describe and evaluate several features and enhancements that have been introduced to address the needs of modern client systems. Microbenchmark results demonstrate the RMA performance of GASNet-EX is competitive with several MPI-3 implementations on current HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Software For Advanced Large-scale Analysis Of Magnetic Confinement For Numerical Design, Engineering & Research (salamander)

As magnetic confinement fusion energy gains traction internationally to enable abundant energy production, designing components for fusion systems is a pressing challenge. During the planned lifetime of a fusion device, components evolve in extreme environments and must withstand large, repeated thermal loads and bombardment by 14 MeV neutrons, plasma ions, and neutral particles (deuterium, tritium, and helium), corrosive conditions, etc. All these physical processes take place simultaneously, interact in intricate ways, and impose important constraints that can affect performance. Experimental data is rare and costly to obtain, making design particularly challenging. Predictive computational frameworks must be an integral part of an accelerated and cost-effective design process by modeling fusion system performance in simulated environments. To better understand component degradation and operational impacts on their performance, the Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER) is designed as an open-source, fully integrated, multiphysics, multiscale, NQA-1 compliant framework facilitating 3D, high-fidelity fusion system modeling. To that end, SALAMANDER is a MOOSE-based framework, and therefore leverages MOOSE upstream libraries such as PETSc and libMesh to deliver sophisticated finite element, finite volume, and nonlinear solver technology for fusion energy simulations. SALAMANDER couples MOOSE physics module capabilities—such as thermal hydraulics, heat conduction, Navier-Stokes, and thermomechanics—with tritium transport via TMAP8, neutronics via Cardinal, and nascent particle-in-cell capabilities. Direct simulation Monte Carlo methods will be used to address neutral transport near the walls. By coupling all these physics in an integrated application, SALAMANDER will enable high-fidelity modeling of irradiation levels and plasma exposure conditions of plasma facing components and their impact on heat and tritium distributions, as well as the resulting mechanical constraints experienced by the plasma facing components and performance of blanket systems. Furthermore, SALAMANDER will be particularly suited for engineering studies thanks to the stochastic tool module readily available in MOOSE, allowing for extended uncertainty quantification and risk analysis studies. It is also able to use computer-aided design (CAD) meshes to model complex geometries, which is indispensable for fusion systems. SALAMANDER therefore supports design, safety, engineering, and research projects for magnetic confinement fusion systems

Simon, Pierre-Clement [Idaho National Laboratory (↗
DOE OSTI2013

A dual cone-beam CT system for image guided radiotherapy: Initial performance characterization

Purpose: The purpose of this study is to evaluate the performance of a recently developed benchtop dual cone-beam computed tomography (CBCT) system with two orthogonally placed tube/detector sets. Methods: The benchtop dual CBCT system consists of two orthogonally placed 40 Multiplication-Sign 30 cm flat-panel detectors and two conventional x-ray tubes with two individual high-voltage generators sharing the same rotational axis. The x-ray source to detector distance is 150 cm and x-ray source to rotational axis distance is 100 cm for both subsystems. The objects are scanned through 200 Degree-Sign of rotation. The dual CBCT system utilized 110 Degree-Sign of projection data from one detector and 90 Degree-Sign from the other while the two individual single CBCTs utilized 200 Degree-Sign data from each detector. The system performance was characterized in terms of uniformity, contrast, spatial resolution, noise power spectrum, and CT number linearity. The uniformities, within the axial slice and along the longitudinal direction, and noise power spectrum were assessed by scanning a water bucket; the contrast and CT number linearity were measured using the Catphan phantom; and the spatial resolution was evaluated using a tungsten wire phantom. A skull phantom and a ham were also scanned to provide qualitative evaluation of high- and low-contrast resolution. Each measurement was compared between dual and single CBCT systems. Results: Compared to single CBCT, the dual CBCT presented: (1) a decrease in uniformity by 1.9% in axial view and 1.1% in the longitudinal view, as averaged for four energies (80, 100, 125, and 150 kVp); (2) comparable or slightly better contrast (0{approx}25 HU) for low-contrast objects and comparable contrast for high-contrast objects; (3) comparable spatial resolution; (4) comparable CT number linearity with R{sup 2}{>=} 0.99 for all four tested energies; (5) lower noise power spectrum in magnitude. Dual CBCT images of the skull phantom and the ham demonstrated both high-contrast resolution and good soft-tissue contrast. Conclusions: The performance of a benchtop dual CBCT imaging system has been characterized and is comparable to that of a single CBCT.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Manifold Learning-Based Polynomial Chaos Expansions for High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantities of interest of the computational or analytical model. For this purpose, we employ Grassmannian diffusion maps, a two-step nonlinear dimension reduction technique which allows us to reduce the dimensionality of the data and identify meaningful geometric descriptions in a parsimonious and inexpensive manner. Polynomial chaos expansion is then used to construct a mapping between the stochastic input parameters and the diffusion coordinates of the reduced space. An adaptive clustering technique is proposed to identify an optimal number of clusters of points in the latent space. The similarity of points allows us to construct a number of geometric harmonic emulators which are finally utilized as a set of inexpensive pretrained models to perform an inverse map of realizations of latent features to the ambient space and thus perform accurate out-of-sample predictions. Thus, the proposed method acts as an encoder-decoder system which is able to automatically handle very high-dimensional data while simultaneously operating successfully in the small-data regime. The method is demonstrated on two benchmark problems and on a system of advection-diffusion-reaction equations which model a first-order chemical reaction between two species. In all test cases, the proposed method is able to achieve highly accurate approximations which ultimately lead to the significant acceleration of UQ tasks.

42 ENGINEERING↗
DOE OSTI2022

Advanced CO 2 Capture Solvent Systems for Dynamic Power Generation

RTI International, in collaboration with Pacific Northwest National Laboratory (PNNL), Carbon Capture Simulation for Industry Impact (CCSI 2 ), Electricity Power Research Institute (EPRI), and West Virginia University (WVU), successfully completed a joint research effort in developing a cost-effective, resilient, load-following advanced CO 2 capture technology for natural gas power plants. The project’s objective was to develop a CO 2 capture process that maximizes the net present value (NPV) of the electricity sale by minimizing the levelized cost of electricity (LCOE) under dynamic plant loads and high renewable penetration environments. The two key innovations developed in this project were the use of (i) advanced water-lean solvents (WLSs) and (ii) process intensification equipment, such as a rotating packed bed (RPB) absorber and dual-stage flash regeneration. The process’s low CO 2 capture cost is realized through WLSs’ low energy required for solvent regeneration, which lowers the operating cost while RPBs intensify the absorption process and reduces the power plant capital cost. A suite of advanced computational and simulation packages was implemented to guide the process design, validate the dynamic response of the capture plant, evaluate system-wide performance, and maximize the power plant’s profit. The project also engaged with power producers and other stakeholders to ensure its technical relevance and techno-economic viability. The development of this highly disruptive CO 2 capture technology could accelerate the industry adoption and thereby lower the greenhouse gas emissions of the U.S. power sector. Deployment of this technology can increase the reliability and decrease the cost of electricity generation in the U.S. by enabling the use of low-carbon fossil fuels to balance fluctuations of renewable energy availability.

03 NATURAL GAS↗
DOE OSTI2025

Benchmarking Density Functional Theory Methods for Efficient Calculations of a Strongly Correlated Li 1– x Ni 1– y O 2−δ System

Transition metal oxides (TMOs), such as LiNiO 2 , are promising candidates for energy storage and electronic devices due to their unique electronic properties, exceptional physical and chemical characteristics, and ability to adopt multiple oxidation states. However, accurately predicting their properties using mean-field density functional theory (DFT) is challenging due to the presence of strongly correlated d-electrons and the complex interplay between their structural, electronic, and magnetic responses. These challenges are further exacerbated by the need to model defects, surfaces, and interfaces, which require computationally efficient, large-scale simulations. To address these issues, we carry out a benchmark study on the Li 1–x NiO 2 system, evaluating the performance of several popular functionals. Our findings demonstrate that combining SCAN functional relaxation with single-step HSE calculations provides a practical and scalable computational strategy. This approach balances accuracy and efficiency, enabling high-throughput simulations of strongly correlated TMOs and improved predictive modeling capability of TMOs for practical applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Energy-efficient Mott activation neuron for full-hardware implementation of neural networks

To circumvent the von Neumann bottleneck, substantial progress has been made towards in-memory computing with synaptic devices. However, compact nanodevices implementing non-linear activation functions are required for efficient full-hardware implementation of deep neural networks. Here, in this work, we present an energy-efficient and compact Mott activation neuron based on vanadium dioxide and its successful integration with a conductive bridge random access memory (CBRAM) crossbar array in hardware. The Mott activation neuron implements the rectified linear unit function in the analogue domain. The neuron devices consume substantially less energy and occupy two orders of magnitude smaller area than those of analogue complementary metal–oxide semiconductor implementations. The LeNet-5 network with Mott activation neurons achieves 98.38% accuracy on the MNIST dataset, close to the ideal software accuracy. We perform large-scale image edge detection using the Mott activation neurons integrated with a CBRAM crossbar array. Our findings provide a solution towards large-scale, highly parallel and energy-efficient in-memory computing systems for neural networks.

electrical and electronic engineering↗
DOE OSTI2024

Shifting Between Compute and Memory Bounds: A Compression-Enabled Roofline Model

In the evolving landscape of high-performance computing, especially to fight the end of Moore’s Law and Dennard’s Scaling, the ability to shift between compute-bound and memory-bound states is critical for enhancing adaptability and flexibility to diverse system and domain-specific architectures. Such capability is vital for optimizing performance across distinguished hardware configurations, such as accelerators, memory hierarchies, and cache systems. Despite that ad hoc optimization techniques, such as compressed/approximate computation, have been enabled for compute-/data-intensive computing for improved performance in distinct hardware settings, there lacks an understanding of 1) the rational behind performance improvement; 2) capability of different optimizations; 3) what optimization to respond to specific computational and memory demands. This work proposes a compression-enabled roofline model to facilitate this adaptability with data compression techniques to balance and transform between computational and memory demands. This model enables applications to adjust in response to the specific strengths and limitations of the underlying hardware and system to optimize resource utilization. The effectiveness of this approach is demonstrated with matrix multiplication kernels on different input sizes, with turning on/off various compression techniques, including 1) low-precision floating point; 2) sparse matrix formulation; and 3) compressed arrays with ZFP. By reducing memory transfer volumes and cache misses and increasing data locality and computational intensity through compression, the specific roofline model can transform between compute and memory bounds to align more efficiently with system capabilities. This advancement not only improves overall performance but also maximizes adaptability in diverse computing environments.

Naraparaju, Ramasoumya [University of Washington]↗
DOE OSTI2016

SU-F-J-74: High Z Geometric Integrity and Beam Hardening Artifact Assessment Using a Retrospective Metal Artifact Reduction (MAR) Reconstruction Algorithm

Purpose: To test the efficacy of a retrospective metal artifact reduction (MAR) reconstruction algorithm for a commercial computed tomography (CT) scanner for radiation therapy purposes. Methods: High Z geometric integrity and artifact reduction analysis was performed with three phantoms using General Electric’s (GE) Discovery CT. The three phantoms included: a Computerized Imaging Reference Systems (CIRS) electron density phantom (Model 062) with a 6.5 mm diameter titanium rod insert, a custom spine phantom using Synthes Spine hardware submerged in water, and a dental phantom with various high Z fillings submerged in water. Each phantom was reconstructed using MAR and compared against the original scan. Furthermore, each scenario was tested using standard and extended Hounsfield Unit (HU) ranges. High Z geometric integrity was performed using the CIRS phantom, while the artifact reduction was performed using all three phantoms. Results: Geometric integrity of the 6.5 mm diameter rod was slightly overestimated for non-MAR scans for both standard and extended HU. With MAR reconstruction, the rod was underestimated for both standard and extended HU. For artifact reduction, the mean and standard deviation was compared in a volume of interest (VOI) in the surrounding material (water and water equivalent material, ∼0HU). Overall, the mean value of the VOI was closer to 0 HU for the MAR reconstruction compared to the non-MAR scan for most phantoms. Additionally, the standard deviations for all phantoms were greatly reduced using MAR reconstruction. Conclusion: GE’s MAR reconstruction algorithm improves image quality with the presence of high Z material with minimal degradation of its geometric integrity. High Z delineation can be carried out with proper contouring techniques. The effects of beam hardening artifacts are greatly reduced with MAR reconstruction. Tissue corrections due to these artifacts can be eliminated for simple high Z geometries and greatly reduced for more complex geometries.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

pnnl/mcl-runtime

The Minos Computing Library (MCL) is a task-based programming language and runtime for extremely heterogeneous systems. MCL facilitates writing program for heterogeneous devices and porting applications across different systems and devices. MCL supports asynchronous execution of computing tasks on all available heterogeneous devices, including GPUs, FGPAs, fixed-point accelerators, and AI accelerators. MCL provides a high-level programming interface and automatically and autonomously performs resource management, load balancing, and locality-aware scheduling.

Central, PNNL Developer↗
DOE OSTI2024

Outcomes of HPC User Support using a Science Gateway AI Assistant

High Performance Computing (HPC) is a vital resource for nuclear energy research, facilitating advanced simulations and complex modeling of the quantification and qualification of advanced reactor technology. However, a common gap in knowledge exists around utilizing HPC systems, particularly for nuclear energy researchers unfamiliar with specific HPC systems. A researcher may be well-versed in using one HPC system and understanding its associated processes. Yet, they might struggle when faced with a different HPC system and its unique processes. HPC support staff play a crucial role in addressing these challenges by providing educational resources and assisting users. However, they also face the challenge of maintaining these systems and ensuring they run efficiently for all users, a responsibility that can be challenging to scale effectively with the increasing demand and expansion of HPC systems. This paper addresses this knowledge gap with an artificial intelligence (AI) assistant that offers on-demand, site-specific HPC support for researchers. Idaho National Laboratory (INL) has deployed an AI assistant that is intended to supplement expert HPC support staff and assist nuclear energy researchers. This paper reports on a four-and-a-half-month study evaluating the integration of an AI assistant within a science gateway, with the goal of enhancing existing HPC support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Validation of Numerical Tools for Calculating Reactivity Feedback in Sodium Fast Reactors Using SEFOR Experimental Data

The Southwest Experimental Fast Oxide Reactor (SEFOR) was an experimental sodium-cooled fast breeder reactor operated from 1969 to 1972 with experiments designed to measure Doppler reactivity feedback in a wide temperature range from around 350 °F to temperatures approaching the melting point of mixed oxide fuel of around 5000 °F, providing valuable data for code validations. Co-supported by the Department of Energy (DOE) Fast Reactor Program (FRP) and the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the SEFOR benchmark project focused on using the experimental data to validate numerical tools that are used in industry and academia to design and license sodium-cooled fast reactors (SFRs). By the end of FY-25, substantial progress was achieved in the SEFOR benchmark study. A variety of numerical tools commonly used for modeling SFRs were applied to develop models for SEFOR core configurations I-D, I-E, I-I, and I-J. These included Monte Carlo codes such as MCNP, Serpent, and Shift; deterministic codes such as the legacy Argonne Reactor Computation (ARC) suite and the high-fidelity NEAMS code Griffin; and the system analysis code SAS4A/SASSYS-1 (SAS). Using these models, both SEFOR zero-power experiments and power-ascending tests were successfully simulated. Comparisons were performed against experimental measurements of core criticalities, reflector worth, kinetics parameters (Λ/βeff), isothermal reactivity feedback (from 350 °F to 760 °F at zero power), and power-ascending reactivity feedback (as power increased from 0.4 MW to 17 MW). In general, these comparisons demonstrated very good agreement between numerical results and experimental data. In Fiscal Year 26 (FY-26), the SEFOR benchmark project will continue to address the modeling issues identified in FY-25. Effort will focus on the simulation of reactivity insertion transients in SEFOR core II using the ARC/SAS model. Future work will also focus on incorporating BISON into the SEFOR core modeling process to enable the first Multiphysics simulations of the isothermal tests based on the MOOSE framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Manganese-Based Magnets: Manganese-Based Permanent Magnet with 40 MGOe at 200°C

REACT Project: PNNL is working to reduce the cost of wind turbines and EVs by developing a manganese-based nano-composite magnet that could serve as an inexpensive alternative to rare-earth-based magnets. The manganese composite, made from low-cost and abundant materials, could exceed the performance of today’s most powerful commercial magnets at temperature higher than 200°C. Members of PNNL’s research team will leverage comprehensive computer high-performance supercomputer modeling and materials testing to meet this objective. Manganese-based magnets could withstand higher temperatures than their rare earth predecessors and potentially reduce the need for any expensive, bulky engine cooling systems for the motor and generator. This would further contribute to cost savings for both EVs and wind turbines.

ARPA-E↗
DOE OSTI2018

DRAGON: breaking GPU memory capacity limits with direct NVM access

Heterogeneous computing with accelerators is growing in importance in high performance computing (HPC). Recently, application datasets have expanded beyond the memory capacity of these accelerators, and often beyond the capacity of their hosts. Meanwhile, nonvolatile memory (NVM) storage has emerged as a pervasive component in HPC systems because NVM provides massive amounts of memory capacity at affordable cost. Currently, for accelerator applications to use NVM, they must manually orchestrate data movement across multiple memories and this approach only performs well for applications with simple access behaviors. To address this issue, we developed DRAGON, a solution that enables all classes of GP-GPU applications to transparently compute on terabyte datasets residing in NVM. DRAGON leverages the page-faulting mechanism on the recent NVIDIA GPUs by extending capabilities of CUDA Unified Memory (UM). Our experimental results show that DRAGON transparently expands memory capacity and obtain additional speedups via automated I/O and data transfer overlapping.

Markthub, Pak↗
DOE OSTI2018

Computational Studies of Solid Stoppers for Generating Intense Exotic Radioactive Ion Beams at FRIB

Low-emittance beams of rare isotopes at low energies (less than 3 MeV/u) are required for many high precision measurements in nuclear science research. Such beams will be produced at the Facility for Rare Isotope Beams (FRIB) by first slowing down and thermalizing or stopping fast fragmentation beams, and subsequently reaccelerating them to the required energies for experiments. The use of a solid stopper has the potential to provide high-intensity reaccelerated beams of many species. We performed simulations of the processes critical for generating beams in solid stoppers, including beam heating, external heating, diffusive release, effusive transport, and surface sticking. Using a variety of software tools, we investigated the viability of numerous solid stopper system designs for FRIB. We present our computational approach, the physical processes we modeled, the codes we used, and our results. We conclude with a proof-of-concept solid stopper system that releases ions sufficiently quickly for experiments with unstable reaccelerated beams at FRIB.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

High-Fidelity Simulation of Flow-Induced Vibrations in Helical Steam Generators for Small Modular Reactors

Flow-induced vibration (FIV) is a widespread problem in energy systems as they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occur. Given the importance of reliable components in the nuclear industry, FIV has long been a major concern in the safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from FIV and related failures. In this paper we discuss the use of the computational fluid dynamics code Nek5000 coupled to the structural code Diablo to simulate the flow in helical coil heat exchangers and associated FIV. In particular, one-way coupled calculations are performed, where pressure and tractions data are loaded into the structural model. The main focus of this paper is on validation of this capability. Fluid-only Nek5000 large eddy simulations are first compared against dedicated high-resolution experiments. Then, one-way coupled calculations are performed with Nek5000 and Diablo for two data sets that provide FIV data for validation. These calculations were aimed at simulating available legacy FIV experiments in helical steam generators in the turbulent buffeting regime. In this regime one-way coupling is judged sufficient since the pressure loads do not cause substantial displacements. It is also the most common source of vibration in helical steam generators at the low flows expected in integral pressurized water reactors. We discuss validation of two-way coupled experiments and benchmarks toward the simulation of fluid elastic instability. We briefly discuss the application of these methods to grid-to-rod fretting.

Flow-Induced Vibration↗
DOE OSTI2018

Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the system’s stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. In conclusion, these methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

33 ADVANCED PROPULSION SYSTEMS↗