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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 55 records · Page 3

Porting the Kitten Lightweight Kernel Operating System to RISC-V

Hardware design in high-performance computing (HPC) is often highly experimental. Exploring new designs is difficult and time-consuming, requiring lengthy vendor cooperation. RISC-V is an open-source processor ISA that improves the accessibility of chip design, including the ability to do hardware/software co-design using open-source hardware and tools. Co-design allows design decisions to easily flow across the hardware/software boundary and influence future design ideas. However, new hardware designs require corresponding software to drive and test them. Conventional operating systems like Linux are massively complex and modification is time-prohibitive. In this paper, we describe our port of the Kitten lightweight kernel operating system to RISC-V in order to provide an alternative to Linux for conducting co-design research. Kitten's small code base and simple resource management policies are well matched for quickly exploring new hardware ideas that may require radical operating system modifications and restructuring. Our evaluation shows that Kitten on RISC-V is functional and provides similar performance to Linux for single-core benchmarks. This provides a solid foundation for using Kitten in future co-design research involving RISC-V.

Gordon, Nick↗

ART/Ada and CLIPS/Ada

Although they have reached a point of commercial viability, expert systems were originally developed in artificial intelligence (AI) research environments. Many of the available tools still work best in such environments. These environments typically utilize special hardware such as LISP machines and relatively unfamiliar languages such as LISP or Prolog. Space Station applications will require deep integration of expert system technology with applications developed in conventional languages, specifically Ada. The ability to apply automation to Space Station functions could be greatly enhanced by widespread availability of state-of-the-art expert system tools based on Ada. Although there have been some efforts to examine the use of Ada for AI applications, there are few, if any, existing products which provide state-of-the-art AI capabilities in an Ada tool. The goal of the ART/Ada Design Project is to conduct research into the implementation in Ada of state-of-the-art hybrid expert systems building tools (ESBT's). This project takes the following approach: using the existing design of the ART-IM ESBT as a starting point, analyze the impact of the Ada language and Ada development methodologies on that design; redesign the system in Ada; and analyze its performance. The research project will attempt to achieve a comprehensive understanding of the potential for embedding expert systems in Ada systems for eventual application in future Space Station Freedom projects. During Phase 1 of the project, initial requirements analysis, design, and implementation of the kernel subset of ART-IM functionality was completed. During Phase 2, the effort has been focused on the implementation and performance analysis of several versions with increasing functionality. Since production quality ART/Ada tools will not be available for a considerable time, and additional subtask of this project will be the completion of an Ada version of the CLIPS expert system shell developed by NASA. This tool will provide full syntactic compatibility with any eventual products of the ART/Ada design while allowing SSFP developers early access to this technology.

Culbert, Chris↗

Collinear dual-pulse laser optical breakdown and energy deposition

A non-equilibrium model for laser-generated plasmas is used to represent collinear dual nano-second-pulse interactions. In the specific case considered, the breakdown is initiated with an ultraviolet (UV) laser pulse at 266 nm, which pre-ionizes the gas, and it is followed by a near-infrared (NIR) pulse at 1064 nm, which deposits significant energy into the ionized mixture. The model is validated against corresponding experiments, and simulation results are interrogated to understand key features of the plasma-kernel dynamics and the post-discharge hydrodynamics. The hydrodynamics of the non-equilibrium plasma is governed by the two-temperature Navier–Stokes equations accounting for both multiphoton ionization and inverse bremsstrahlung. The interaction between the laser beam and the plasma is modeled based on the radiative transfer equation. The temporal and spatial offsets of the two pulses can generate ionization kernels with different topology and dynamics. It is shown that the UV pre-ionization pulse can tailor the plasma region, leading to a larger ionized volume than would occur for a single-pulse breakdown, and it increases the efficiency of the energy deposition for the following NIR discharge. Vorticity in the early post-discharge phase is generated via baroclinic torque from the misalignment of the radial gradient of density (sudden gas expansion) and the strong pressure gradient (initiated by energy deposition from the laser beam). It is predicted that the collinear dual pulse can be designed to specify the plasma kernel size, shape, and maximum temperature in the breakdown phase, and the initial post-breakdown vorticity and plasma-core decay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimum-AIV: A planning and scheduling system for spacecraft AIV

A project undertaken for the European Space Agency (ESA) is presented. The project is developing a knowledge based software system for planning and scheduling of activities for spacecraft assembly, integration, and verification (AIV). The system extends into the monitoring of plan execution and the plan repair phase. The objectives are to develop an operational kernel of a planning, scheduling, and plan repair tool, called OPTIMUM-AIV, and to provide facilities which will allow individual projects to customize the kernel to suit its specific needs. The kernel shall consist of a set of software functionalities for assistance in initial specification of the AIV plan, in verification and generation of valid plans and schedules for the AIV activities, and in interactive monitoring and execution problem recovery for the detailed AIV plans. Embedded in OPTIMUM-AIV are external interfaces which allow integration with alternative scheduling systems and project databases. The current status of the OPTIMUM-AIV project, as of Jan. 1991, is that a further analysis of the AIV domain has taken place through interviews with satellite AIV experts, a software requirement document (SRD) for the full operational tool was approved, and an architectural design document (ADD) for the kernel excluding external interfaces is ready for review.

Arentoft, M. M.↗

NASA and Blue Origin Collaborative Assessment of Precision Landing Algorithms and Computing

NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project is developing sensor, algorithm, and compute technologies for precision landing and hazard avoidance. These technologies are being tested as an integrated Precision Landing and Hazard Avoidance (PL&HA) system on Blue Origin’s New Shephard suborbital vehicle. A key goal for the computing element of this technology development is to characterize the performance of the SPLICE software workloads on the project’s Descent and Landing Computer (DLC). The DLC is a multi-core processor designed as a surrogate for NASA’s High-Performance Space Computer (HPSC). Measurements of the SPLICE workload performance on the DLC provides NASA insight on how PL&HA capabilities will perform on the HPSC, and guidance on how the SPLICE algorithms can be implemented to best utilize the DLC platform. This insight can also be used to derive requirements to guide trade studies on candidate computing architectures, for use on platforms like Blue Moon. NASA and Blue Origin are collaborating under an agreement to pursue this mutual benefit. Performance metrics collected are based on measurement of common compute resources such as percentage used of memory bandwidth, I/O utilization, interrupt latency, and kernel vs. user space code residency. Where possible existing performance counters and metrics that are part of the operating system kernel are used. As the design has a significant FPGA component, performance counters are identified and instantiated in the fabric to measure DMA performance and interface metrics. Collection of metrics is performed on the DLC with a representative workload that simulates a full landing cycle of the Blue Origin New Shepard vehicle. Consideration is given to the other compute implementations and whether they can run SPLICE algorithms at the same rate and with the same latency as the DLC. One option being considered is the use of a RISC-V soft core instantiated in a radiation resilient FPGA fabric such as the Xilinx KU60. Select algorithms from the SPLICE code will be run for comparison with the DLC. This paper describes how the DLC is instrumented to collect performance measurements of the SPLICE workloads, preliminary results from these measurements, and their implications on SPLICE algorithm implementation. The results of experimentation to derive candidate requirements for architecture trades on a PL&HA computing system are also presented.

computer performance↗

Assimilating partial observation to enhance feedback control of stochastic dynamical systems

Here, in this paper, we present a novel methodology to tackle feedback optimal control problems in scenarios where the exact state of the controlled process is unknown. It integrates data assimilation techniques and optimal control solvers to manage partial observation of the state process, a common occurrence in practical scenarios. Traditional stochastic optimal control methods assume full state observation, which is often not feasible in real-world fluid dynamics control problems. Our approach underscores the significance of utilizing observational data to inform control policy design. Specifically, we introduce a kernel learning backward stochastic differential equation (SDE) filter to enhance data assimilation efficiency and propose a sample-wise stochastic optimization method within the stochastic maximum principle framework. We demonstrate the efficacy and accuracy of our method in the control of advection-diffusion-reaction flow problem and the Dubins airplane maneuvering problem with model uncertainty.

data driven↗

A White Paper: Disposition Options for a High-Temperature Gas-Cooled Reactor

The high-temperature gas-cooled reactor (HTGR) is a uranium-fueled, graphite-moderated, gas-cooled nuclear reactor design concept capable of producing very high core outlet temperatures. Both types of HTGR have the tristructural isotropic (TRISO) fuel kernel at the heart of the fuel design. For the prismatic block-type HTGR, the TRISO particles are overcoated with a resinated graphitic matrix and pressed into fuel compacts, which are then heat treated and placed in the fuel channels of the prismatic-block-shaped fuel assemblies. For the pebble-bed-type HTGR, the TRISO particles are dispersed in a graphitic-matrix sphere, which is the basic unit for the reactor core. Despite having very different fuel designs, both types of HTGR are graphite-moderated, gas-cooled, thermal reactors using many of the same materials. As a result, both prismatic-block-type and pebble-bed-type HTGRs have similar radioactive waste streams, all of which require safe and secure storage and eventual disposition. Modern HTGR designs are based on a long and rich operating history of several different graphite-moderated, gas-cooled, thermal reactors. Several of these reactors have been shut down, the fuel has been placed in safe storage, and they have undergone some degree of decommissioning. As such, there is significant experience in the management of the spent nuclear fuel (SNF) and radioactive wastes associated with operating these reactors. This white paper will, (1) identify the definitions and regulations that apply to the safe and secure management, storage, and disposal of radioactive waste; and (2) identify the key radioactive waste streams from HTGRs and their characteristics. Idaho National Laboratory (INL) has significant experience in the management of SNF from HTGR predecessors. This experience should form the basis for the management and disposition efforts of the radioactive waste from any new HTGR-type small modular reactor, or microreactor intended for deployment at the INL site.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗

Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?

High-throughput structure-based screening of drug-like molecules has become a common tool in biomedical research. Recently, acceleration with graphics processing units (GPUs) has provided a large performance boost for molecular docking programs. Both cloud and high-performance computing (HPC) resources have been used for large screens with molecular docking programs; while NVIDIA GPUs have dominated cloud and HPC resources, new vendors such as AMD and Intel are now entering the field, creating the problem of software portability across different GPUs. Ideally, software productivity could be maximized with portable programming models that are able to maintain high performance across architectures. While in many cases compiler directives have been used as an easy way to offload parallel regions of a CPU-based program to a GPU accelerator, they may also be an attractive programming model for providing portability across different GPU vendors, in which case the porting process may proceed in the reverse direction: from low-level, architecture-specific code to higher-level directive-based abstractions. MiniMDock is a new mini-application (miniapp) designed to capture the essential computational kernels found in molecular docking calculations, such as are used in phar-maceutical drug discovery efforts, in order to test different solutions for porting across GPU architectures. Here we extend MiniMDock to GPU offloading with OpenMP directives, and compare to performance of kernels using CUDA and HIP on NVIDIA and AMD GPUs, respectively, as well as across different compilers, exploring performance bottlenecks. We document this reverse-porting process, from highly optimized device code to a higher-level version using directives, compare code structure, and describe barriers that were overcome in this effort.

Thavappiragasam, Mathialakan↗

Micromechanical Properties of the SiC and Pyrolytic Carbon Layers in Tristructural-Isotropic Coated Particles

Tristructural isotropic (TRISO) coated particle fuel was initially developed for high temperature gas cooled reactors (HTGR) and has been proposed for several other advanced reactor concepts. The design of TRISO particles focuses on preventing the release of fission products in normal and off-normal reactor conditions. The particle design features an actinide bearing fuel kernel that is surrounded by three pyrolytic carbon (PyC) layers and a silicon carbide layer (SiC). The mechanical stability of the particle and fission product retention for both metallic and gaseous fission products depend on the SiC layer. Post irradiation examination (PIE) of TRISO fuel from the first two US DOE Advanced Gas Reactor Fuel Development and Qualification Program irradiation campaigns, AGR-1 and AGR-2, had identified a low rate of particles exhibiting cracking in the SiC layer that did not propagate across the SiC layer. While cracking in the SiC is rare for test conditions and particles associated with the AGR program, understanding the stress state and mechanical properties of the SiC and PyC layers related to particle architecture can aid predicting thermomechanical response of TRISO fuel under the prescribed operation envelope and beyond as well as aiding in the development of similar fuel concepts for other advanced reactors. The presented investigation shows the relationship of the mechanical properties and mechanical response (e.g., understanding crack propagation) of the SiC and PyC layers relative to position within the particle. Testing was conducted on the inner and outer PyC layers of TRISO particles to quantify differences in mechanical behavior.

Montoya, Katherine [ORNL] (ORCID:0000000326955086)↗

Boundary-element shape sensitivity analysis for thermal problems with nonlinear boundary conditions

Implicit differentiation of the discretized boundary integral equations governing the conduction of heat in solid objects subjected to nonlinear boundary conditions is shown to generate an accurate and economical approach for the computation of shape sensitivities for this class of problems. This approach involves the employment of analytical derivatives of boundary-element kernel functions with respect to shape design variables. A formulation is presented that can consistently account for both temperature-dependent convection and radiation boundary conditions. Several iterative strategies are presented for the solution of the resulting sets of nonlinear equations and the computational performances examined in detail. Multizone analysis and zone condensation strategies are demonstrated to provide substantive computational economies in this process for models with either localized nonlinear boundary conditions or regions of geometric insensitivity to design variables. A series of nonlinear example problems are presented that have closed-form solutions.

Kane, James H.↗

A Second Generation Multi-Angle Imaging SpectroRadiometer (MISR-2)

The Multi-angle Imaging SpectroRadiometer (MISR) has been in Earth orbit since December 1999 on NASA's Terra spacecraft. This instrument provides new ways of looking at the Earth's atmosphere, clouds, and surface for the purpose of understanding the Earth's ecology, environment, and climate. To facilitate the potential future continuation of MISR's multi-angle observations, a study was undertaken in 1999 and 2000 under the Instrument Incubator Program (IIP) of NASA Code Y's Earth Science Technology Office (ESTO) to investigate and demonstrate the feasibility of a successor to MISR that will have greatly reduced size and mass. The kernel of the program was the design, construction, and testing of a highly miniaturized camera, one of the nine that would probably be used on a future space borne MISR-like instrument. This demonstrated that the size and mass reduction of the optical system and camera electronics are possible and that filters can be assembled to meet the miniaturized packaging requirements. An innovative, reflective optics design was used, enabling the wavelength range to be extended into the shortwave infrared. This was the smallest all-reflective camera ever produced by the contractor. A study was undertaken to determine the feasibility of implementing nine (multi-angle) cameras within a single structure. This resulted in several possible configurations. It would also be possible to incorporate one of the cameras into an airborne instrument.

spectroradiometers↗

X-ray Computed Tomography of Irradiated and Unirradiated AGR-3/4 Compacts A preliminary examination

What? Performed X-ray CT (XCT) on irradiated AGR-3/4 compacts Apparatus design Imaging results Preliminary analysis Extruded kernels DTF Identification Areas of interest for further exploration Why? Can provide non-destructive 3D perspective to enhance/compliment current PIE Potentially better quantitative measurements of certain features Better means of understanding any spatial distribution(s)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A method for computing the kernel of the downwash integral equation for arbitrary complex frequencies

For the design of active controls to stabilize flight vehicles, which requires the use of unsteady aerodynamics that are valid for arbitrary complex frequencies, algorithms are derived for evaluating the nonelementary part of the kernel of the integral equation that relates unsteady pressure to downwash. This part of the kernel is separated into an infinite limit integral that is evaluated using Bessel and Struve functions and into a finite limit integral that is expanded in series and integrated termwise in closed form. The developed series expansions gave reliable answers for all complex reduced frequencies and executed faster than exponential approximations for many pressure stations.

Desmarais, R. N.↗

A method of smoothed particle hydrodynamics using spheroidal kernels

We present a new method of three-dimensional smoothed particle hydrodynamics (SPH) designed to model systems dominated by deformation along a preferential axis. These systems cause severe problems for SPH codes using spherical kernels, which are best suited for modeling systems which retain rough spherical symmetry. Our method allows the smoothing length in the direction of the deformation to evolve independently of the smoothing length in the perpendicular plane, resulting in a kernel with a spheroidal shape. As a result the spatial resolution in the direction of deformation is significantly improved. As a test case we present the one-dimensional homologous collapse of a zero-temperature, uniform-density cloud, which serves to demonstrate the advantages of spheroidal kernels. We also present new results on the problem of the tidal disruption of a star by a massive black hole.

Fulbright, Michael S.↗

Enhancement of sub-thermal neutron flux through cold polyethylene

Total thermal neutron cross section measurements serve as the primary means of validation for thermal neutron scattering kernels, an important quantity for neutron transport calculations. In an effort to improve the quality of thermal neutron scattering kernels, researchers at Rensselaer Polytechnic Institute (RPI) designed and constructed a polyethylene based cold moderation system to enhance neutron flux below 10 meV when coupled with the Enhanced Thermal Target (ETT) at the RPI Gaerttner LINAC. The final design yielded an increase in sub-thermal neutron flux (below 10 meV) by a factor of 4.5 for a moderator temperature of 37.5 K relative to the ETT alone. A further increase to a factor of 6 is expected after a minor geometry modification and decrease in polyethylene temperature to 25 K. This novel capability will be used to conduct total thermal neutron cross section measurements from 0.0005–10 eV for different materials including moderator materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Boosting RDataFrame performance with transparent bulk event processing

RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.

Guiraud, Enrico↗