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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Deployment and Evaluation of SciStream on OLCF's Advanced Computing Ecosystem (ACE)

The growing demand for real-time analysis, experimental steering, and decision-making in scientific workflows has created a need for tightly coupled integrations between experimental facilities and high-performance computing (HPC) systems. The Department of Energy’s Integrated Research Infrastructure (IRI) initiative highlights data streaming as a key capability for enabling memory-to-memory data transfers, bypassing the limitations of traditional store-and-forward models. SciStream is a toolkit developed by researchers at Argonne National Laboratory (ANL) to support such streaming by addressing cross-domain security, delegated authentication, and application transparency. We deployed and evaluated SciStream on the Oak Ridge Leadership Computing Facility’s (OLCF) Advanced Computing Ecosystem (ACE) infrastructure, leveraging the Olivine OpenShift cluster and its high-bandwidth Data Streaming Nodes (DSNs) as gateway nodes. Our evaluation included synthetic streaming workloads derived from IRI science workflows, a streaming simulator, and integration with RabbitMQ to handle low-level messaging. This report documents the deployment process, performance evaluation, and challenges encountered, along with opportunities for future improvements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Software Deployment Process at NERSC: Deploying the Extreme-scale Scientific Software Stack (E4S) Using Spack at the National Energy Research Scientific Computing Center (NERSC)

One of the many benefits of using a high-performance computing (HPC) system at a Department of Energy (DOE) Office of Science (SC) HPC facility is the large number of software products, built and optimized for the system. The HPC center staff and HPC vendors provide optimized software such as libraries and even full scientific applications, ready to be used by users as building blocks to accelerate scientific discovery. Behind each provided packaged software module are a large number of decisions - which compiler, optimizations, variants/options - to build the software on the target system. And, even before the software gets deployed, the software must be developed, tested, and maintained, including deprecating old versions and ensuring compatibility across versions. The software lifecycle is complex and is further convoluted by a web of interdependencies on other software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data Center Market Report

The data center market is poised to explode in the coming decade due to undeniable drivers such as continued adoption of generative AI, increased data storage needs, and enterprise integration of AI in numerous industries [1] [2] [3]. Scalable power and increased computational capacity are at the forefront of considerations for hyperscalers, the major cloud service providers in this space. Lawrence Livermore National Laboratory is uniquely poised to help with informed decision making for data center market leaders during this phase of explosive expansion. National grid modeling expertise and cutting edge innovations in computer cooling systems place LLNL in an enviable position for creating economic impact in the data center industry by leveraging its expertise in these areas which can help the data center market keep up with growing demand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU Architectures

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures—such as the Intel “Knights Landing” Xeon Phi and Skylake Xeon processors—with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.

Mills, Richard T↗
DOE OSTI2016

solveME: fast and reliable solution of nonlinear ME models

Background Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Results Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints. Conclusions Just as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields.

Biochemistry & Molecular Biology↗
DOE OSTI2014

Computational Design of Advanced Nuclear Fuels

The objective of the project was to develop a method for theoretical understanding of nuclear fuel materials whose physical and thermophysical properties can be predicted from first principles using a novel dynamical mean field method for electronic structure calculations. We concentrated our study on uranium, plutonium, their oxides, nitrides, carbides, as well as some rare earth materials whose 4f eletrons provide a simplified framework for understanding complex behavior of the f electrons. We addressed the issues connected to the electronic structure, lattice instabilities, phonon and magnon dynamics as well as thermal conductivity. This allowed us to evaluate characteristics of advanced nuclear fuel systems using computer based simulations and avoid costly experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

SU-D-BRF-05: A Novel System to Provide Real-Time Image-Guidance for Intrauterine Tandem Insertion and Placement

Purpose: To develop a system that provides real-time image-guidance for intrauterine tandem insertion and placement for brachytherapy. Methods: The conceptualized system consists of an intrauterine tandem with a transparent, lensed tip, a flexible miniature fiber optic scope, light source and interface for CCD coupling. The tandem tip was designed to act as a lens providing a wide field-of-view (FOV) with minimal image distortion and focus length appropriate for the application. The system is designed so that once inserted, the image-guidance component of the system can be removed and brachytherapy can be administered without interfering with source transport or disturbing tandem placement. Proof-of-principle studies were conducted to assess the conceptualized system's (1) lens functionality (clarity, focus and FOV) (2) and ability to visualize the cervical os of a female placed in the lithotomy position. Results: A prototype of this device was constructed using a commercial tandem modified to incorporate a transparent tip that internally coupled with a 1.9mm diameter fiber optic cable. The 900mm-long cable terminated at an interface that provided illumination as well as facilitated visualization of patient anatomy on a computer. The system provided a 23mm FOV with a focal length of 1cm and provided clear visualization of the cervix, cervical fornix and cervical os. The optical components of the system are easily removed without perturbing the position of a tandem placed in a common fixation clamp. Conclusion: Clinicians frequently encounter difficulty inserting an intrauterine tandem through the cervical os, circumventing fibrotic tissue or masses within the uterus, and positioning the tandem without perforating the uterus. To mitigate these challenges, we have designed and conducted proof-of- principle studies to discern the utility of a prototype device that provides real-time image-guidance for intrauterine tandem placement using fiber optic components.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2011

Gyrokinetic particle-in-cell optimization on emerging multi- and manycore platforms

The next decade of high-performance computing (HPC) systems will see a rapid evolution and divergence of multi- and manycore architectures as power and cooling constraints limit increases in microprocessor clock speeds. Understanding efficient optimization methodologies on diverse multicore designs in the context of demanding numerical methods is one of the greatest challenges faced today by the HPC community. In this paper, we examine the efficient multicore optimization of GTC, a petascale gyrokinetic toroidal fusion code for studying plasma microturbulence in tokamak devices. For GTC’s key computational components (charge deposition and particle push), we explore efficient parallelization strategies across a broad range of emerging multicore designs, including the recently-released Intel Nehalem-EX, the AMD Opteron Istanbul, and the highly multithreaded Sun UltraSparc T2+. We also present the first study on tuning gyrokinetic particle-in-cell (PIC) algorithms for graphics processors, using the NVIDIA C2050 (Fermi). Our work discusses several novel optimization approaches for gyrokinetic PIC, including mixed-precision computation, particle binning and decomposition strategies, grid replication, SIMDized atomic floating-point operations, and effective GPU texture memory utilization. Overall, we achieve significant performance improvements of 1.3–4.7× on these complex PIC kernels, despite the inherent challenges of data dependency and locality. Finally, our work also points to several architectural and programming features that could significantly enhance PIC performance and productivity on next-generation architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Schwinger-Keldysh coset construction

The coset construction is a tool for systematically building low energy effective actions for Nambu-Goldstone modes. This technique is typically used to compute time-ordered correlators appropriate for S-matrix computations for systems in their ground state. In this paper, we extend this technique to the Schwinger-Keldysh formalism, which enables one to calculate a wider variety of correlators and applies also to systems in a mixed state. We focus our attention on internal symmetries and demonstrate that, after identifying the appropriate symmetry breaking pattern, Schwinger-Keldysh effective actions for Nambu-Goldstone modes can be constructed using the standard rules of the coset construction. Particular emphasis is placed on the thermal state and ensuring that correlators satisfy the KMS relation. We also discuss explicitly the power counting scheme underlying our effective actions. We comment on the similarities and differences between our approach and others that have previously appeared in the literature. In particular, our prescription does not require the introduction of additional “diffusive” symmetries and retains the full non-linear structure generated by the coset construction. We conclude with a series of explicit examples, including a computation of the finite-temperature two-point functions of conserved spin currents in non-relativistic paramagnets, antiferromagnets, and ferromagnets. Along the way, we also clarify the discrete symmetries that set antiferromagnets apart from ferromagnets, and point out that the dynamical KMS symmetry must be implemented in different ways in these two systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

A practical discrete-adjoint method for high-fidelity compressible turbulence simulations

Methods and computing hardware advances have enabled accurate predictions of complex compressible turbulence phenomena, such as the generation of jet noise that motivates the present effort. However, limited understanding of underlying physical mechanisms restricts the utility of such predictions since they do not, by themselves, indicate a route to design improvements. Gradient-based optimization using adjoints can circumvent the flow complexity to guide designs, though this is predicated on the availability of a sufficiently accurate solution of the forward and adjoint systems. These are challenging to obtain, since both the chaotic character of the turbulence and the typical use of discretizations near their resolution limits in order to efficiently represent its smaller scales will amplify any approximation errors made in the adjoint formulation. Formulating a practical exact adjoint that avoids such errors is especially challenging if it is to be compatible with state-of-the-art simulation methods used for the turbulent flow itself. Automatic differentiation (AD) can provide code to calculate a nominally exact adjoint, but existing general-purpose AD codes are inefficient to the point of being prohibitive for large-scale turbulence simulations. Here, we analyze the compressible flow equations as discretized using the same high-order workhorse methods used for many high-fidelity compressible turbulence simulations, and formulate a practical space–time discrete-adjoint method without changing the basic discretization. A key step is the definition of a particular discrete analog of the continuous norm that defines our cost functional; our selection leads directly to an efficient Runge–Kutta-like scheme, though it would be just first-order accurate if used outside the adjoint formulation for time integration, with finite-difference spatial operators for the adjoint system. Its computational cost only modestly exceeds that of the flow equations. We confirm that its accuracy is limited by computing precision, and we demonstrate it on the aeroacoustic control of a mixing layer with a challengingly broad range of turbulence scales. For comparison, the error from a corresponding discretization of the continuous-adjoint equations is quantified to potentially explain its limited success in past efforts to control jet noise. The differences are illuminating: the continuous-adjoint is shown to suffer from exponential error growth in (reverse) time even for the best-resolved largest turbulence scales. Implications for jet noise reduction and turbulence control in general are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Generalized Quasi-Static Mooring System Modeling with Analytic Jacobians

This paper presents a generalized and efficient method for quasi-static analysis of mooring systems, including complex scenarios such as when shared mooring lines interconnect multiple floating wind or wave energy devices. While quasi-static mooring models are well established, most published formulations are focused on specific applications, and no publicly available implementations provide efficient handling of large mooring system networks. The present formulation addresses these gaps by: (1) formulating solutions for edge cases not typically supported by quasi-static models; (2) creating a fully generalized model structure such that any combination of mooring lines, point masses, and floating bodies can be assembled; and (3) deriving analytic expressions for the system Jacobians (stiffness matrices) so that systems with many degrees of freedom can be solved efficiently. These techniques form the theory basis of MoorPy, an open-source mooring analysis library. The model is demonstrated on nine scenarios of increasing complexity with features of interest for offshore renewable energy applications. When compared with steady-state results from a lumped-mass dynamic model, the results show that the quasi-static formulation accurately calculates profiles and tensions and that its analytic approach provides more efficient and reliable computation of system stiffness matrices than finite-differencing methods. These results verify the accuracy of the MoorPy model.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Computer Security for I and C Systems at Nuclear Facilities - 116

Cyber-attacks on Instrumentation and Control (I and C) systems may jeopardize the safety and security of nuclear facilities by contributing to sabotage or aiding in the unauthorized removal of nuclear material. The effects of cyber-attacks on I and C systems important to safety to safety may result in a wide range of consequences, such as a temporary loss of process control or unacceptable radiological consequences. Public awareness of cyber-attacks that affect I and C systems may also undermine confidence in the safety and security of nuclear facilities. The International Atomic Energy Agency (IAEA) recognizes the need for the guidance on the protection of I and C systems that provide safety, security, or auxiliary functions at nuclear facilities from cyber-attacks. To meet this need, The IAEA has developed a new Nuclear Security Series publication with the provisional title Computer Security of Instrumentation and Control Systems at Nuclear Facilities which builds upon and expands the guidance published in Nuclear Security Series No. 17 Computer Security at Nuclear Facilities (2011) . This publication will be formally released in 2017 as Technical Guidance and will be the second international consensus publication dedicated to Computer Security at Nuclear Facilities. It was developed in parallel with the new IAEA Nuclear Safety publications providing recommendations on I and C systems at research reactors (RR) and nuclear power plants (NPP) . The purpose of this paper is to provide an overview of this publication and its application. The paper will also discuss its relation to other IAEA Nuclear Security Series (NSS) publications on computer security. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

BWR Full Fuel Assembly Testing and Validation

This report describes the Consortium for Advanced Simulation of Light Water Reactors (CASL) work conducted for completion of the Thermal Hydraulics Methods (THM) Level 3 milestone THM.CLS.P15.10: BWR Full Fuel Assembly Testing and Validation. The extension of existing boiling closure designed for Pressurized Water Reactors (PWRs) to the high void fraction condition of Boiling Water Reactors (BWRs) is one of the challenges for Multiphase Computational Fluid Dynamics (M-CFD) applications. In the efforts aimed at developing the advanced boiling closure for BWRs, the baseline closure model, so-called ‘Zero’ closure, has been developed based on the GEN-I closure for PWRs which was used as a starting point. Since this simplest closure model is robust but does not contain any explicit description of the complex high void fraction mechanisms, the applicability of M-CFD needs to be evaluated before developing advanced closures for BWRs. To support this need, the high fidelity M-CFD simulation with Zero closure has been conducted for the BWR full fuel assembly. The capabilities of M-CFD with Zero closure were evaluated against the international OECD/NRC BFBT benchmark data. The scalability of the M-CFD application to the nuclear fuel assembly was demonstrated with the INL High Performance Computing (HPC) system. This report presents the recent view of the best practices on M-CFD for BWRs to provide a useful reference to identify and overcome common challenges in the M-CFD applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Towards New Metrics for High-Performance Computing Resilience

Ensuring the reliability of applications is becoming an increasingly important challenge as high-performance computing (HPC) systems experience an ever-growing number of faults, errors and failures. While the HPC community has made substantial progress in developing various resilience solutions, it continues to rely on platform-based metrics to quantify application resiliency improvements. The resilience of an HPC application is concerned with the reliability of the application outcome as well as the fault handling efficiency. To understand the scope of impact, effective coverage and performance efficiency of existing and emerging resilience solutions, there is a need for new metrics. In this paper, we develop new ways to quantify resilience that consider both the reliability and the performance characteristics of the solutions from the perspective of HPC applications. As HPC systems continue to evolve in terms of scale and complexity, it is expected that applications will experience various types of faults, errors and failures, which will require applications to apply multiple resilience solutions across the system stack. The proposed metrics are intended to be useful for understanding the combined impact of these solutions on an application's ability to produce correct results and to evaluate their overall impact on an application's performance in the presence of various modes of faults.

Fault Tolerance↗
DOE OSTI2015

Computational redesign reveals allosteric mutation hotspots of organophosphate hydrolase that enhance organophosphate hydrolysis

Organophosphates are widely used for peaceful (agriculture) and military purposes (chemical warfare agents). The extraordinary toxicity of organophosphates and the risk of deployment, make it critical to develop means for their rapid and efficient deactivation. Organophosphate hydrolase (OPH) already plays an important role in organophosphate remediation, but is insufficient for therapeutic or prophylactic purposes primarily due to low substrate affinity. Current efforts focus on directly modifying the active site to differentiate substrate specificity and increase catalytic activity. Here, we present a novel strategy for enhancing the general catalytic efficiency of OPH through computational redesign of the residues that are allosterically coupled to the active site and validated our design by mutagenesis. Specifically, we identify five such hot-spot residues for allosteric regulation and assay these mutants for hydrolysis activity against paraoxon, a chemical-weapons simulant. A high percentage of the predicted mutants exhibit enhanced activity over wild-type (k cat =16.63 s -1 ), such as T199I/T54I (899.5 s -1 ) and C227V/T199I/T54I (848 s -1 ), while the Km remains relatively unchanged in our high-throughput cell-free expression system. Further computational studies of protein dynamics reveal four distinct distal regions coupled to the active site that display significant changes in conformation dynamics upon these identified mutations. These results validate a computational design method that is both efficient and easily adapted as a general procedure for enzymatic enhancement.

organophosphate hydrolase↗
DOE OSTI2025

Gate-Based Quantum Simulation of Gaussian Bosonic Circuits on Exponentially Many Modes

We introduce a framework for simulating, on an ( n + 1 )-qubit quantum computer, the action of a Gaussian bosonic (GB) circuit on a state over 2 n modes. Specifically, we encode the initial bosonic state’s expectation values over quadrature operators (and their covariance matrix) as an input qubit state. This is then evolved by a quantum circuit that effectively implements the symplectic propagators induced by the GB gates. We find families of GB circuits and initial states leading to efficient quantum simulations. For this purpose, we introduce a dictionary that maps between GB and qubit gates such that particle- (non-particle-) preserving GB gates lead to real- (imaginary-) time evolutions at the qubit level. For the special case of particle-preserving circuits, we present a bounded-error-quantum-polynomial time (BQP)-complete GB decision problem, indicating that GB evolutions of Gaussian states on exponentially many modes are as powerful as universal quantum computers. We also perform numerical simulations of an interferometer on ∼ 8 × 10 9 modes, illustrating the power of our framework. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Temperature Rise on Liner Surfaces of Fuel Cell Electric Vehicle Tanks during Fueling Process

Herein, the temperature of the inner tank walls, or plastic liners, of composite pressure tanks in fuel cell electric vehicles during fueling using three‐dimensional computational fluid dynamics (CFD) models is evaluated. The liner materials are limited to 85.0 °C to prevent thermal stress causing material failure that would result in a hydrogen leak. Therefore, the temperature of hydrogen gas must be limited to below 85.0 °C during the fueling process as dictated by the current fueling protocol. However, there are limited experimental or simulation data confirming that the temperature changes do not exceed the threshold. Herein, the liner temperatures with CFD tank models for two sizes of type IV tanks representative of the upper and lower system bounds that are close to the SAE J2601 fueling protocol (36.0 and 244.0 L) are evaluated. First, each model's reliability is validated with experimental data and then analyzed, and the data are used to evaluate the maximum hydrogen and liner temperatures under real‐world fueling conditions. The evaluation shows that the maximum liner surface temperature of each tank model is at least 7 °C lower than that of the hydrogen. Additionally, there is at least 12 °C difference found between the upper limit and actual liner temperatures.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Universal and interpretable classification of atomistic structural transitions via unsupervised graph learning

Materials processing often occurs under extreme dynamic conditions leading to a multitude of unique structural environments. These structural environments generally occur at high temperatures and/or high pressures, often under non-equilibrium conditions, which results in drastic changes in the material's structure over time. Computational techniques, such as molecular dynamics simulations, can probe the atomic regime under these extreme conditions. However, characterizing the resulting diverse atomistic structures as a material undergoes extreme changes in its structure has proved challenging due to the inherently non-linear relationship between structures as large-scale changes occur. Here, we introduce SODAS++, a universal graph neural network framework, that can accurately and intuitively quantify the atomistic structural evolution corresponding to the transition between any two arbitrary phases. We showcase SODAS++ for both solid–solid and solid–liquid transitions for systems of increasing geometric and chemical complexity, such as colloidal systems, elemental Al, rutile and amorphous TiO 2 , and the non-stoichiometric ternary alloy Ag 26 Au 5 Cu 19 . Finally, we show that SODAS++ can accurately quantify all transitions in a physically interpretable manner, showcasing the power of unsupervised graph neural network encodings for capturing the complex and non-linear pathway, a material's structure takes as it evolves.

36 MATERIALS SCIENCE↗