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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multidimensional Numerical Modeling of Combustion Dynamics in a Non-Premixed Rotating Detonation Engine With Adaptive Mesh Refinement

In the present work, a novel computational fluid dynamics (CFD) methodology was developed to simulate full-scale non-premixed rotating detonation engines (RDEs). A unique feature of the modeling approach was the incorporation of adaptive mesh refinement (AMR) to achieve a good trade-off between model accuracy and computational expense. Here, unsteady Reynolds-averaged Navier–Stokes (RANS) simulations were performed for an Air Force Research Laboratory (AFRL) non-premixed RDE configuration with hydrogen as fuel and air as the oxidizer. The finite-rate chemistry model, along with a ten-species detailed kinetic mechanism, was employed to describe the H 2 -Air combustion chemistry. Three distinct operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel/air mass flowrates. For all conditions, the capability of the model to capture essential detonation wave dynamics was assessed. An exhaustive verification and validation study was performed against experimental data in terms of a number of waves, wave frequency, wave height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model was demonstrated to accurately predict the sensitivity of these wave characteristics to the operating conditions, both qualitatively and quantitatively. A comprehensive heat release analysis was also conducted to quantify detonative versus deflagrative burning for the three simulated cases. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

42 ENGINEERING↗
DOE OSTI2015

COMPASS: A Framework for Automated Performance Modeling and Prediction

Flexible, accurate performance predictions offer numerous benefits such as gaining insight into and optimizing applications and architectures. However, the development and evaluation of such performance predictions has been a major research challenge, due to the architectural complexities. To address this challenge, we have designed and implemented a prototype system, named COMPASS, for automated performance model generation and prediction. COMPASS generates a structured performance model from the target application's source code using automated static analysis, and then, it evaluates this model using various performance prediction techniques. As we demonstrate on several applications, the results of these predictions can be used for a variety of purposes, such as design space exploration, identifying performance tradeoffs for applications, and understanding sensitivities of important parameters. COMPASS can generate these predictions across several types of applications from traditional, sequential CPU applications to GPU-based, heterogeneous, parallel applications. Our empirical evaluation demonstrates a maximum overhead of 4%, flexibility to generate models for 9 applications, speed, ease of creation, and very low relative errors across a diverse set of architectures.

Lee, Seyong↗
DOE OSTI2023

Towards On-Chip Learning for Low Latency Reasoning with End-to-End Synthesis

The Software Defined Architectures (SODA) Synthesizer is an open-source compiler-based tool able to automatically generate domain-specialized systems targeting Application-Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) starting from high-level programming. SODA is composed of a frontend, SODA-OPT, which leverages the multilevel intermediate representation (MLIR) framework to interface with productive programming tools (e.g., machine learning frame-works), identify kernels suitable for acceleration, and perform high-level optimizations, and of a state-of-the-art high-level synthesis backend, Bambu from the PandA framework, to generate custom accelerators. One specific application of the SODA Synthesizer is the generation of accelerators to enable ultra-low latency inference and control on autonomous systems for scientific discovery (e.g., electron microscopes, sensors in particle accelerators, etc.). This paper provides an overview of the flow in the context of the generation of accelerators for edge processing to be integrated in transmission electron microscopy (TEM) devices, focusing on use cases from precision material synthesis. We show the tool in action with an example of design space exploration for inference on reconfigurable devices with a conventional deep neural network model (LeNet). Finally, we discuss the research directions and opportunities enabled by SODA in the area of autonomous control for scientific experimental workflows.

Castellana, Vito G.↗
DOE OSTI2015

DESTINY

DESTINY is a comprehensive tool for modeling 3D and 2D cache designs using SRAM,embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM), and phase change RAM (PCN). In its purpose, it is similar to CACTI, CACTI-3DD or NVSim. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for agiven memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target, etc. DESTINY has been validated against several cache prototypes. DESTINY is expected to boost studies of next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers.

Source record↗
DOE OSTI2020

Memory Analysis Tool

This tool traces all memory accesses to stack (static allocation) and heap (dynamic allocation) on a trace run in a particular hardware and then estimates execution time on given arbitrary hardware configurations for hardware design space exploration. It can also compute memory access statistics, such as reuse distance.

Sato, Kento↗
DOE OSTI2015

Enabling Exascale Hardware and Software Design through Scalable System Virtualization (Final Report)

The purpose of this project has been to extend the state of the art of systems software for high-end computing (HEC) platforms, and to use systems software to better enable the evaluation of potential future HEC platforms, for example exascale platforms. Such platforms, and their systems software, have the goal of providing scientific computation at new scales, thus enabling new research in the physical sciences and engineering. Over time, the innovations in systems software for such platforms also become applicable to more widely used computing clusters, data centers, and clouds. This was a five-institution project, centered on the Palacios virtual machine monitor (VMM) systems software, a project begun at Northwestern, and originally developed in a previous collaboration between Northwestern University and the University of New Mexico. In this project, Northwestern (including via our subcontract to the University of Pittsburgh) contributed to the continued development of Palacios, along with other team members. We took the leadership role in (1) continued extension of support for emerging Intel and AMD hardware, (2) integration and performance enhancement of overlay networking, (3) connectivity with architectural simulation, (4) binary translation, and (5) support for modern Non-Uniform Memory Access (NUMA) hosts and guests. We also took a supporting role in support for specialized hardware for I/O virtualization, profiling, configurability, and integration with configuration tools. The efforts we led (1-5) were largely successful and executed as expected, with code and papers resulting from them. The project demonstrated the feasibility of a virtualization layer for HEC computing, similar to such layers for cloud or datacenter computing. For effort (3), although a prototype connecting Palacios with the GEM5 architectural simulator was demonstrated, our conclusion was that such a platform was less useful for design space exploration than anticipated due to inherent complexity of the connection between the instruction set architecture level and the microarchitectural level. For effort (4), we found that a code injection approach proved to be more fruitful. The results of our efforts are publicly available in the open source Palacios codebase and published papers, all of which are available from the project web site, v3vee.org. Palacios is currently one of the two codebases (the other being Sandia’s Kitten lightweight kernel) that underlies the node operating system for the DOE Hobbes Project, one of two projects tasked with building a systems software prototype for the national exascale computing effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Accelerating Science Driven System Design With RAMP

Researchers from UC Berkeley, in collaboration with the Lawrence Berkeley National Lab, are engaged in developing an Infrastructure for Synthesis with Integrated Simulation (ISIS). The ISIS Project was a cooperative effort for “application-driven hardware design” that engages application scientists in the early parts of the hardware design process for future generation supercomputing systems. This project served to foster development of computing systems that are better tuned to the application requirements of demanding scientific applications and result in more cost-effective and efficient HPC system designs. In order to overcome long conventional design-cycle times, we leveraged reconfigurable devices to aid in the design of high-efficiency systems, including conventional multi- and many-core systems. The resulting system emulation/prototyping environment, in conjunction with the appropriate intermediate abstractions, provided both a convenient user programming experience and retained flexibility, and thus efficiency, of a reconfigurable platform. We initially targeted the Berkeley RAMP system (Research Accelerator for Multiple Processors) as that hardware emulation environment to facilitate and ultimately accelerate the iterative process of science-driven system design. Our goal was to develop and demonstrate a design methodology for domain-optimized computer system architectures. The tangible outcome is a methodology and tools for rapid prototyping and design-space exploration, leading to highly optimized and efficient HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Evaluation of the OpenCL AES Kernel using the Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. In this report, we evaluate the performance of the kernel using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board. Compared to the M506 module, the board provides more hardware resources for a larger design exploration space. The kernel performance is measured with the compute kernel throughput, an upper bound to the FPGA throughput. The report presents the experimental results in details. The Appendix lists the kernel source code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Performance and Energy Implications for Heterogeneous Computing Systems: A MiniFE Case Study

Heterogeneous computing systems, which employ a mix of general-purpose (GP) processors and accelerators such as graphics processing units (GPUs) or Field Programmable Gate Arrays (FPGAs), have the potential to offer much higher performance and lower energy usage than homogeneous systems. However, designing heterogeneous computing systems to achieve high performance and low energy usage is a challenging task. Designs that offer higher performance do not necessarily lead to lower energy consumption. Furthermore, mapping of applications to different computing devices can play a key role in performance and energy tradeoff. In this report, we present a detailed performance and energy study of executing a specific mini-application on different heterogeneous systems. The results show that hardware choices, application implementations, and mapping of applications to hardware can all significantly impact system performance and energy consumption and that the impact on performance and energy can be quite different. This study forms a basis for modeling the interdependencies of program structures and hardware execution units, which could be used to guide design space exploration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Surrogate Model Integration with MOOSE XFEM for Creep Crack Growth

Ferritic-martensitic steels are key structural materials for advanced reactors but experience time-dependent deformation and damage under prolonged high temperature and irradiation, leading to creep-driven crack initiation and growth. High-fidelity models—crystal plasticity with irradiation mechanisms, phase-field for microstructural evolution, and continuum-damage viscoplasticity—capture the underlying physics but are too computationally intensive for broad design-space exploration and uncertainty quantification. This milestone advances a scalable alternative by integrating a microstructure-sensitive surrogate creep model into the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework and extending it to fracture via the extended finite element method (XFEM). The surrogate model, developed with collaborators at Sandia and Los Alamos National Laboratories, maps relevant microstructural descriptors to the viscoplastic response of HT9. We embed this surrogate within a coupled deformation-damage workflow in MOOSE/XFEM to simulate creep-driven crack initiation and propagation. Implementation enhancements include updates to the material interface, a plastic correction phase involving microstructure evolution, and fracture criteria to ensure numerical robustness and compatibility with the surrogate structure. Demonstrations on canonical creep benchmarks spanning uniaxial and multiaxial states show that the surrogate reproduces key trends of high-fidelity models while substantially reducing computational cost. The resulting capability bridges physics fidelity and performance, providing a practical path to a predictive, microstructure-aware assessment of creep and fracture in reactor materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2016

High Fidelity Simulations of a Non-Premixed Rotating Detonation Engine

Over the last two decades, detonation based propulsion concepts have received a great deal of attention as a means to achieve significant improvement in the performance of air-breathing and rocket engines. Detonative combustion mode is particularly interesting due to the resulting pressure gain from reactants to products, faster heat release, decreased entropy generation, more available work and higher thrust compared to conventional deflagrative combustion. Rotating detonation engine (RDE) is one such class of novel combustor concepts. Realistic RDE configurations utilize separate fuel and air injection schemes, hence are not perfectly premixed. Moreover, the performance of RDEs is governed by a large number of design parameters and operating conditions. In this context, computational fluid dynamics (CFD) has the potential to enhance the understanding of RDE combustion and aid future development/optimization of this technology. In the present work, a CFD model was developed to simulate a representative non-premixed RDE combustor at the US Air Force Research Laboratory (AFRL). To resolve the reacting flow in the combustor, a finite-rate chemistry model was employed. In addition, adaptive mesh refinement (AMR) was incorporated to achieve a good trade-off between model accuracy and computational expense. Unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations were performed for the full combustor (including the separate fuel and air injection ports) geometry, with hydrogen as fuel and air as the oxidizer. A 10-species detailed kinetic mechanism was employed to describe the H2-Air combustion chemistry. Two different operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel and air mass flow rates. For both conditions, the capability of the model to capture the essential detonation wave dynamics was assessed. A validation study was performed against a wide variety of experimental data available on detonation wave frequency/height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model predicted the sensitivity of all these wave characteristics to the operating conditions with good accuracy, both qualitatively and quantitatively. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

Cocks, Peter A.↗
DOE OSTI2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗
NASA NTRS1995

Centrifugal and Axial Pump Design and Off-Design Performance Prediction

A meanline pump-flow modeling method has been developed to provide a fast capability for modeling pumps of cryogenic rocket engines. Based on this method, a meanline pump-flow code PUMPA was written that can predict the performance of pumps at off-design operating conditions, given the loss of the diffusion system at the design point. The design-point rotor efficiency and slip factors are obtained from empirical correlations to rotor-specific speed and geometry. The pump code can model axial, inducer, mixed-flow, and centrifugal pumps and can model multistage pumps in series. The rapid input setup and computer run time for this meanline pump flow code make it an effective analysis and conceptual design tool. The map-generation capabilities of the code provide the information needed for interfacing with a rocket engine system modeling code. The off-design and multistage modeling capabilities of PUMPA permit the user to do parametric design space exploration of candidate pump configurations and to provide head-flow maps for engine system evaluation.

Veres, Joseph P.↗
NASA NTRS2000

Mean Line Pump Flow Model in Rocket Engine System Simulation

A mean line pump flow modeling method has been developed to provide a fast capability for modeling turbopumps of rocket engines. Based on this method, a mean line pump flow code PUMPA has been written that can predict the performance of pumps at off-design operating conditions, given the loss of the diffusion system at the design point. The pump code can model axial flow inducers, mixed-flow and centrifugal pumps. The code can model multistage pumps in series. The code features rapid input setup and computer run time, and is an effective analysis and conceptual design tool. The map generation capability of the code provides the map information needed for interfacing with a rocket engine system modeling code. The off-design and multistage modeling capabilities of the code permit parametric design space exploration of candidate pump configurations and provide pump performance data for engine system evaluation. The PUMPA code has been integrated with the Numerical Propulsion System Simulation (NPSS) code and an expander rocket engine system has been simulated. The mean line pump flow code runs as an integral part of the NPSS rocket engine system simulation and provides key pump performance information directly to the system model at all operating conditions.

Veres, Joseph P.↗
NASA NTRS2015

Rho-Isp Revisited and Basic Stage Mass Estimating for Launch Vehicle Conceptual Sizing Studies

The ideal rocket equation is manipulated to demonstrate the essential link between propellant density and specific impulse as the two primary stage performance drivers for a launch vehicle. This is illustrated by examining volume-limited stages such as first stages and boosters. This proves to be a good approximation for first-order or Phase A vehicle design studies for solid rocket motors and for liquid stages, except when comparing to hydrogen-fueled stages. A next-order mass model is developed that is able to model the mass differences between hydrogen-fueled and other stages. Propellants considered range in density from liquid methane to inhibited red fuming nitric acid. Calculated comparisons are shown for solid rocket boosters, liquid first stages, liquid upper stages, and a balloon-deployed single-stage-to-orbit concept. The derived relationships are ripe for inclusion in a multi-stage design space exploration and optimization algorithm, as well as for single-parameter comparisons such as those shown herein.

Kibbey, Timothy P.↗
NASA NTRS2017

SpaceCubeX: A Framework for Evaluating Hybrid Multi-Core CPU FPGA DSP Architectures

The SpaceCubeX project is motivated by the need for high performance, modular, and scalable on-board processing to help scientists answer critical 21st century questions about global climate change, air quality, ocean health, and ecosystem dynamics, while adding new capabilities such as low-latency data products for extreme event warnings. These goals translate into on-board processing throughput requirements that are on the order of 100-1,000 more than those of previous Earth Science missions for standard processing, compression, storage, and downlink operations. To study possible future architectures to achieve these performance requirements, the SpaceCubeX project provides an evolvable testbed and framework that enables a focused design space exploration of candidate hybrid CPU/FPGA/DSP processing architectures. The framework includes ArchGen, an architecture generator tool populated with candidate architecture components, performance models, and IP cores, that allows an end user to specify the type, number, and connectivity of a hybrid architecture. The framework requires minimal extensions to integrate new processors, such as the anticipated High Performance Spaceflight Computer (HPSC), reducing time to initiate benchmarking by months. To evaluate the framework, we leverage a wide suite of high performance embedded computing benchmarks and Earth science scenarios to ensure robust architecture characterization. We report on our projects Year 1 efforts and demonstrate the capabilities across four simulation testbed models, a baseline SpaceCube 2.0 system, a dual ARM A9 processor system, a hybrid quad ARM A53 and FPGA system, and a hybrid quad ARM A53 and DSP system.

Hybrid Flight Architectures↗
NASA NTRSDate not supplied

TPSAS-NF1676L-23318-DND

Overview - Concept description - Quick summary of results - N+3 Conventional Configuration - Description of baseline - Comparison of baseline to Refined SUGAR concept - Simplifying assumptions - Propulsion system modeling - Boundary layer modeling - System performance - Weight estimates - System design space exploration - Results - Turboelectric concept benefits - System sensitivities - Future work - Conclusions

Jason R. Welstead↗
NASA NTRS2023

Modeling and Simulation of a Parallel Hybrid Electric Regional Aircraft for the Electrified Powertrain Flight Demonstration (EPFD) Program

This paper presents a parametric modeling and integrated aircraft sizing and synthesis approach for a charge depleting parallel hybrid electric architecture. The developed models are integrated within the baseline thin-haul and regional aircraft. In addition to the physical architecture, different modes of operation enabled by propulsion system electrification are also modeled parametrically. The modes of operation presented in this paper are the peak power shaving, climb power electric boost, in-flight battery recharging, and electric taxi. The sizing of the powertrain and the aircraft are performed within the multidisciplinary analysis and optimization environment, E-PASS. The consideration of the physical system and its operation together provides a holistic approach where the propulsion system and the airframe are designed under an optimized power and energy management strategy. The parametric nature of the work enables the design space exploration for electrification and lays the groundwork for future technology projection and uncertainty quantification studies. The developed capability is generic and can be applied on other aircraft classes. The work is done as part of the Electrified Powertrain Flight Demonstration program.

electrified powertrain flight demonstration↗