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NASA NTRS1989

Automating the multiprocessing environment

An approach to automate the programming and operation of tree-structured networks of multiprocessor systems is discussed. A conceptual, knowledge-based operating environment is presented, and requirements for two major technology elements are identified as follows: (1) An intelligent information translator is proposed for implementating information transfer between dissimilar hardware and software, thereby enabling independent and modular development of future systems and promoting a language-independence of codes and information; (2) A resident system activity manager, which recognizes the systems capabilities and monitors the status of all systems within the environment, is proposed for integrating dissimilar systems into effective parallel processing resources to optimally meet user needs. Finally, key computational capabilities which must be provided before the environment can be realized are identified.

Arpasi, Dale J.↗

DOE OSTI2020

MAPPER – A NOVEL CAPABILITY TO SUPPORT NUCLEAR MODEL VALIDATION AND MAPPING OF BIASES AND UNCERTAINTIES

This paper overviews the initial results of a new project at the Oak Ridge National Laboratory -- supported via an internal seed funding program -- focused on the development of a novel computational capability, called MAPPER, to support model validation. The MAPPER development aims to eliminate the need for empirical criteria, such as similarity indices, often employed to identify applicable experiments for given application conditions. To achieve that, MAPPER employs an information-theoretic-based approach, based on the Kullback-Leibler (KL) divergence principle, to combine responses of available or to-be-built experiments with application responses of interest using a training set of samples generated using randomized execution of the experiments and the application high fidelity analysis models. These samples are condensed using reduced order modeling techniques in the form of a joint probability distribution function (PDF) connecting each application response of interest with a new effective experimental response. The initial focus of the MAPPER capability will be to support the confirmatory analysis required for criticality safety analysis of storage facilities which require k-eff biases to be known for safe operation. This paper reports some of the initial results obtained with MAPPER as applied to a set of critical experiments for which existing similarity-based methods have been shown to provide inaccurate estimates of the biases.

Mertyurek, Ugur↗

DOE OSTI2020

An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem

The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.

genetic algorithm↗

DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗

DOE OSTI2022

Physically rigorous reduced-order flow models of fractured subsurface environments without explosive computational cost

Fractured media models comprise discontinuities of multiple lengths (e.g. fracture lengths and apertures, wellbore area) that fall into the relatively insignificant length scales spanning millimeter-scale fractures to centimeter-scale wellbores in comparison to the extensions of the field of interest, and challenge the conventional discretization methods imposing highly-fine meshing and formidably large numerical cost. By utilizing the recent developments in the finite element analysis of electromagnetics that allow to represent material properties on a hierarchical geometry, this project develops computational capabilities to model fluid flow, heat conduction, transport and induced polarization in large-scale geologic environments that possess geometrically-complex fractures and man-made infrastructures without explosive computational cost. The computational efficiency and robustness of this multi-physics modeling tool are demonstrated by considering various highly-realistic complex geologic environments that are common in many energy and national security related engineering problems.

42 ENGINEERING↗

NASA NTRS2000

Performance Assessment of OVERFLOW on Distributed Computing Environment

The aerodynamic computer code, OVERFLOW, with a multi-zone overset grid feature, has been parallelized to enhance its performance on distributed and shared memory paradigms. Practical application benchmarks have been set to assess the efficiency of code's parallelism on high-performance architectures. The code's performance has also been experimented with in the context of the distributed computing paradigm on distant computer resources using the Information Power Grid (IPG) toolkit, Globus. Two parallel versions of the code, namely OVERFLOW-MPI and -MLP, have developed around the natural coarse grained parallelism inherent in a multi-zonal domain decomposition paradigm. The algorithm invokes a strategy that forms a number of groups, each consisting of a zone, a cluster of zones and/or a partition of a large zone. Each group can be thought of as a process with one or multithreads assigned to it and that all groups run in parallel. The -MPI version of the code uses explicit message-passing based on the standard MPI library for sending and receiving interzonal boundary data across processors. The -MLP version employs no message-passing paradigm; the boundary data is transferred through the shared memory. The -MPI code is suited for both distributed and shared memory architectures, while the -MLP code can only be used on shared memory platforms. The IPG applications are implemented by the -MPI code using the Globus toolkit. While a computational task is distributed across multiple computer resources, the parallelism can be explored on each resource alone. Performance studies are achieved with some practical aerodynamic problems with complex geometries, consisting of 2.5 up to 33 million grid points and a large number of zonal blocks. The computations were executed primarily on SGI Origin 2000 multiprocessors and on the Cray T3E. OVERFLOW's IPG applications are carried out on NASA homogeneous metacomputing machines located at three sites, Ames, Langley and Glenn. Plans for the future will exploit the distributed parallel computing capability on various homogeneous and heterogeneous resources and large scale benchmarks. Alternative IPG toolkits will be used along with sophisticated zonal grouping strategies to minimize the communication time across the computer resources.

Djomehri, M. Jahed↗

NASA NTRS2016

DNS of Low-Pressure Turbine Cascade Flows with Elevated Inflow Turbulence Using a Discontinuous-Galerkin Spectral-Element Method

Recent progress towards developing a new computational capability for accurate and efficient high-fidelity direct numerical simulation (DNS) and large-eddy simulation (LES) of turbomachinery is described. This capability is based on an entropy- stable Discontinuous-Galerkin spectral-element approach that extends to arbitrarily high orders of spatial and temporal accuracy, and is implemented in a computationally efficient manner on a modern high performance computer architecture. An inflow turbulence generation procedure based on a linear forcing approach has been incorporated in this framework and DNS conducted to study the effect of inflow turbulence on the suction- side separation bubble in low-pressure turbine (LPT) cascades. The T106 series of airfoil cascades in both lightly (T106A) and highly loaded (T106C) configurations at exit isentropic Reynolds numbers of 60,000 and 80,000, respectively, are considered. The numerical simulations are performed using 8th-order accurate spatial and 4th-order accurate temporal discretization. The changes in separation bubble topology due to elevated inflow turbulence is captured by the present method and the physical mechanisms leading to the changes are explained. The present results are in good agreement with prior numerical simulations but some expected discrepancies with the experimental data for the T106C case are noted and discussed.

Garai, Anirban↗

NASA NTRS2015

DNS of Flow in a Low-Pressure Turbine Cascade Using a Discontinuous-Galerkin Spectral-Element Method

A new computational capability under development for accurate and efficient high-fidelity direct numerical simulation (DNS) and large eddy simulation (LES) of turbomachinery is described. This capability is based on an entropy-stable Discontinuous-Galerkin spectral-element approach that extends to arbitrarily high orders of spatial and temporal accuracy and is implemented in a computationally efficient manner on a modern high performance computer architecture. A validation study using this method to perform DNS of flow in a low-pressure turbine airfoil cascade are presented. Preliminary results indicate that the method captures the main features of the flow. Discrepancies between the predicted results and the experiments are likely due to the effects of freestream turbulence not being included in the simulation and will be addressed in the final paper.

Low-Pressure Turbine Cascade↗

NASA NTRS1984

A review of recent developments in flight test techniques at the Ames Research Center, Dryden Flight Research Facility

New flight test techniques in use at Ames Dryden are reviewed. The use of the pilot in combination with ground and airborne computational capabilities to maximize data return is discussed, including the remotely piloted research vehicle technique for high-risk testing, the remotely augmented vehicle technique for handling qualities research, and use of ground computed flight director information to fly unique profiles such as constant Reynolds number profiles through the transonic flight regime. Techniques used for checkout and design verification of systems-oriented aircraft are discussed, including descriptions of the various simulations, iron bird setups, and vehicle tests. Some newly developed techniques to support the aeronautical research disciplines are discussed, including a new approach to position-error determination, and the use of a large skin friction balance for the measurement of drag caused by various excrescencies.

Layton, G. P.↗

NASA NTRS2001

Processors, Pipelines, and Protocols for Advanced Modeling Networks

Predictive capabilities arise from our understanding of natural processes and our ability to construct models that accurately reproduce these processes. Although our modeling state-of-the-art is primarily limited by existing computational capabilities, other technical areas will soon present obstacles to the development and deployment of future predictive capabilities. Advancement of our modeling capabilities will require not only faster processors, but new processing algorithms, high-speed data pipelines, and a common software engineering framework that allows networking of diverse models that represent the many components of Earth's climate and weather system. Development and integration of these new capabilities will pose serious challenges to the Information Systems (IS) technology community. Designers of future IS infrastructures must deal with issues that include performance, reliability, interoperability, portability of data and software, and ultimately, the full integration of various ES model systems into a unified ES modeling network.

Coughlan, Joseph↗

NASA NTRS2018

NASA SPLICE Project: Development and Testing of Precision Landing GN&C Technologies

NASA's technology advancement needs for entry, descent and landing call for high-precision, high-rate sensors that can improve navigation accuracy and vehicle control performance. Higher landing accuracy is required for any future human lander missions, and likely, for most robotic missions 1,2. Sensors and algorithms that significantly reduce navigation errors and can image the local terrain will enable landing at locations of high scientific interest that would otherwise pose significant risk to the vehicle. The Safe and Precise Landing-Integrated Capabilities Evolution project, or SPLICE, is developing precision landing and hazard avoidance (PL&HA) technologies for NASA and for potential commercial space flight missions. SPLICE technologies include sensors, algorithms, advanced space flight computing capabilities, and simulation tools used to integrate and study guidance, navigation, and control (GN&C) system performance. SPLICE efforts include hardware-in-the-loop (HWIL) simulation testing, ground testing, and flight testing, including reuse of hardware from the CoOperative Blending of Autonomous Landing Technologies (COBALT) suborbital flight-test payload3,4. Two of the precise navigation sensors that are being developed and matured within SPLICE are LiDARs. Since 2006, NASA Langley has been developing a Navigation Doppler LiDAR (NDL) for precise velocity measurements, and SPLICE is building an NDL engineering test unit (ETU) that will be brought up to TRL 6 following environmental and high-speed1,2 testing. NASA Goddard is developing a Hazard Detection LiDAR (HD LiDAR) engineering development unit (EDU) for SPLICE that has relevance to future human and robotic lander missions. The HD LiDAR will be flight test and matured to TRL 5.

Restrepo, Carolina I.↗

DOE OSTI2021

Preliminary Assessment of Qiskit Quantum Simulator Capabilities for Development of Quantum Hopfield Neural Network for Anomaly Detection Applications (Q4 Report)

Quantum information processing offers potentially faster performance compared to the classical counterpart. The goal of this work is to investigate performance of Quantum Hopfield Neural Network for applications to anomaly detection. Preliminary study consist of assessment of computational capabilities of Qiskit quantum simulator. Eventual objective is to implement Quantum Hopfield Network algorithm for detection of weak nuisance and anomaly signal in the presence of strong and highly varying background in gamma radiation data measured during environmental screening.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Large Eddy simulation of turbulence: A subgrid scale model including shear, vorticity, rotation, and buoyancy

The Reynolds numbers that characterize geophysical and astrophysical turbulence (Re approximately equals 10(exp 8) for the planetary boundary layer and Re approximately equals 10(exp 14) for the Sun's interior) are too large to allow a direct numerical simulation (DNS) of the fundamental Navier-Stokes and temperature equations. In fact, the spatial number of grid points N approximately Re(exp 9/4) exceeds the computational capability of today's supercomputers. Alternative treatments are the ensemble-time average approach, and/or the volume average approach. Since the first method (Reynolds stress approach) is largely analytical, the resulting turbulence equations entail manageable computational requirements and can thus be linked to a stellar evolutionary code or, in the geophysical case, to general circulation models. In the volume average approach, one carries out a large eddy simulation (LES) which resolves numerically the largest scales, while the unresolved scales must be treated theoretically with a subgrid scale model (SGS). Contrary to the ensemble average approach, the LES+SGS approach has considerable computational requirements. Even if this prevents (for the time being) a LES+SGS model to be linked to stellar or geophysical codes, it is still of the greatest relevance as an 'experimental tool' to be used, inter alia, to improve the parameterizations needed in the ensemble average approach. Such a methodology has been successfully adopted in studies of the convective planetary boundary layer. Experienc e with the LES+SGS approach from different fields has shown that its reliability depends on the healthiness of the SGS model for numerical stability as well as for physical completeness. At present, the most widely used SGS model, the Smagorinsky model, accounts for the effect of the shear induced by the large resolved scales on the unresolved scales but does not account for the effects of buoyancy, anisotropy, rotation, and stable stratification. The latter phenomenon, which affects both geophysical and astrophysical turbulence (e.g., oceanic structure and convective overshooting in stars), has been singularly difficult to account for in turbulence modeling. For example, the widely used model of Deardorff has not been confirmed by recent LES results. As of today, there is no SGS model capable of incorporating buoyancy, rotation, shear, anistropy, and stable stratification (gravity waves). In this paper, we construct such a model which we call CM (complete model). We also present a hierarchy of simpler algebraic models (called AM) of varying complexity. Finally, we present a set of models which are simplified even further (called SM), the simplest of which is the Smagorinsky-Lilly model. The incorporation of these models into the presently available LES codes should begin with the SM, to be followed by the AM and finally by the CM.

Canuto, V. M.↗

DOE OSTI2020

Evaluation of Low Dose Silicon Carbide Temperature Monitors

Thermocouples are generally used to provide real-time temperature indications in instrumented tests performed at materials and test reactors. Melt wires or paint spots are often included in such tests as an independent technique of detecting peak temperatures incurred during irradiation. In addition, less expensive static capsule tests, which have no leads attached for real-time data transmission, often rely on melt wires and paint spots as a post-irradiation technique for peak temperature indication. Unfortunately, these techniques are limited in that they can only detect whether a single temperature is or is not exceeded. Silicon carbide (SiC) monitors are advantageous because a single monitor can be used to determine the peak temperature reached within a relatively broad range (200 – 800°C). Although the use of SiC monitors was proposed more than five decades ago, the ultimate performance limits of this technique are not fully understood. The Nuclear Science User Facilities (NSUF) is the United States Department of Energy Office of Nuclear Energy's only designated nuclear energy user facility. Its mission is to provide nuclear energy researchers access to world-class capabilities and to facilitate the advancement of nuclear science and technology. This mission is supported by providing access to state-of-the-art experimental irradiation testing, post irradiation examination facilities, and high performance computing capabilities as well as technical and scientific assistance for the design and execution of projects. As part of an NSUF project, low dose silicon carbide monitors were irradiated in the Belgian Reactor 2 and were then evaluated both at the SCK•CEN and at Idaho National Laboratory's High Temperature Test Laboratory to determine their peak temperature achieved during irradiation. The technical significance of this work was that the monitors were irradiated to a dose that was significantly less than recommended in published literature. This paper will discuss the evaluation process, the irradiation test, and the performance of the low dose silicon carbide temperature monitors.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Toward Exascale: Overview of Large Eddy Simulations and Direct Numerical Simulations of Nuclear Reactor Flows with the Spectral Element Method in Nek5000

At the beginning of the last decade, Petascale supercomputers (i.e., computers capable of more than 1 petaFLOP) emerged. Now, at the dawn of exascale supercomputing, we provide a review of recent landmark simulations of portions of reactor components with turbulence-resolving techniques that this computational power has made possible. In fact, these simulations have provided invaluable insight into flow dynamics, which is difficult or often impossible to obtain with experiments alone. We focus on simulations performed with the spectral element method, as this method has emerged as a powerful tool to deliver massively parallel calculations at high fidelity by using large eddy simulation or direct numerical simulation. We also limit this paper to constant-property incompressible flow of a Newtonian fluid in the absence of other body or external forces, although the method is by no means limited to this class of flows. We briefly review the fundamentals of the method and the reasons it is compelling for the simulation of nuclear engineering flows. We review in detail a series of Petascale simulations, including the simulations of helical coil steam generators, fuel assemblies, and pebble beds. Even with Petascale computing, however, limitations for nuclear modeling and simulation tools remain. In particular, the size and scope of turbulence-resolving simulations are still limited by computing power and resolution requirements, which scale with the Reynolds number. In the final part of this paper, we discuss the future of the field, including recent advancements in emerging architectures such as GPUbased supercomputers, which are expected to power the next generation of high-performance computers.

computational fluid dynamics↗

DOE OSTI2023

SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing

In many neuromorphic workflows, simulators play a vital role for important tasks such as training spiking neural networks, running neuroscience simulations, and designing, implementing, and testing neuromorphic algorithms. Currently available simulators cater to either neuroscience workflows (e.g., NEST and Brian2) or deep learning workflows (e.g., BindsNET). Problematically, the neuroscience-based simulators are slow and not very scalable, and the deep learning-based simulators do not support certain functionalities that are typical of neuromorphic workloads (e.g., synaptic delay). In this paper, we address this gap in the literature and present SuperNeuro, which is a fast and scalable simulator for neuromorphic computing capable of both homogeneous and heterogeneous simulations as well as GPU acceleration. We also present preliminary results that compare SuperNeuro to widely used neuromorphic simulators such as NEST, Brian2, and BindsNET in terms of computation times. We demonstrate that SuperNeuro can be approximately 10×--300× faster than some of the other simulators for small sparse networks. On large sparse and large dense networks, SuperNeuro can be approximately 2.2×--3.4× faster than the other simulators, respectively.

Date, Prasanna↗

NASA NTRS1981

Interactive design and analysis of future large spacecraft concepts

An interactive computer aided design program used to perform systems level design and analysis of large spacecraft concepts is presented. Emphasis is on rapid design, analysis of integrated spacecraft, and automatic spacecraft modeling for lattice structures. Capabilities and performance of multidiscipline applications modules, the executive and data management software, and graphics display features are reviewed. A single user at an interactive terminal create, design, analyze, and conduct parametric studies of Earth orbiting spacecraft with relative ease. Data generated in the design, analysis, and performance evaluation of an Earth-orbiting large diameter antenna satellite are used to illustrate current capabilities. Computer run time statistics for the individual modules quantify the speed at which modeling, analysis, and design evaluation of integrated spacecraft concepts is accomplished in a user interactive computing environment.

Garrett, L. B.↗