Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “high performance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ignition delay time and CO time-history measurements in a shock tube during high performance jet fuel surrogate combustion

The chemical kinetics of diisobutylene, a proposed biofuel, has been studied behind reflected shock waves near 10 atm over a temperature range of 1186 – 1414 K. A stoichiometric mixture consisting of 0.15% diisobutylene was used to investigate ignition behavior and speciation during oxidation experiments performed in a shock tube. Time resolved measurements of carbon monoxide were measured behind reflected shock waves with a continuous wave quantum cascade laser centered at a frequency of 2046.20 cm^-1 using a fixed-wavelength spectroscopy scheme.

09 BIOMASS FUELS↗
DOE OSTI2024

Integrating Experiments, Simulations, and Artificial Intelligence to Accelerate the Discovery of High-Performance Green Composites

The imperative for incorporating greener materials into the aerospace industry necessitates addressing significant challenges associated with the microstructural variability exhibited by recycled and sustainable feedstocks. In this study, we propose an integrated methodology that combines experimental investigations, finite element analysis, and artificial intelligence to develop sustainable composites with consistent properties. Our approach utilizes a pipeline comprising an automated mechanical tester, a finite element method simulator, and a convolutional neural network predictor to identify and optimize fabrication parameters for achieving desired mechanical characteristics in composites. By employing a nested-loop pipeline, our methodology improves sample efficiency, accuracy, and effectively bridges the gap between simulations and real-world performance. This unique methodology offers a promising avenue for facilitating the adoption of aerospace-appropriate green composites.

Athanasiou, Christos↗
DOE OSTI2024

Interfacial engineering for high performance carbon-based perovskite solar cells

Perovskite solar cells fabricated with carbon-based counter electrodes demonstrate decreased cost, enhanced simplicity and speed of production, and increased stability compared to those produced with standard metallic electrodes. This significant improvement of device stability, cost reduction, and production scalability indicates a promising direction for commercial development and availability of perovskite solar technology. The main limitation of carbon-based perovskite devices is the flawed contact between the carbon electrode and perovskite film which decreases device quality and performance, thereby necessitating treatment of the carbon/perovskite interface. This review provides an overview of the current state of carbon-based perovskite devices, discusses progress in carbon/perovskite interface modification methods, and suggests future directions for the research of carbon electrode/perovskite film interface manipulation.

14 SOLAR ENERGY↗
DOE OSTI2022

Inference-Optimized AI and High Performance Computing for Gravitational Wave Detection at Scale

We introduce an ensemble of artificial intelligence models for gravitational wave detection that we trained in the Summit supercomputer using 32 nodes, equivalent to 192 NVIDIA V100 GPUs, within 2 h. Once fully trained, we optimized these models for accelerated inference using NVIDIA TensorRT. We deployed our inference-optimized AI ensemble in the ThetaGPU supercomputer at Argonne Leadership Computer Facility to conduct distributed inference. Using the entire ThetaGPU supercomputer, consisting of 20 nodes each of which has 8 NVIDIA A100 Tensor Core GPUs and 2 AMD Rome CPUs, our NVIDIA TensorRT-optimized AI ensemble processed an entire month of advanced LIGO data (including Hanford and Livingston data streams) within 50 s. Our inference-optimized AI ensemble retains the same sensitivity of traditional AI models, namely, it identifies all known binary black hole mergers previously identified in this advanced LIGO dataset and reports no misclassifications, while also providing a 3X inference speedup compared to traditional artificial intelligence models. We used time slides to quantify the performance of our AI ensemble to process up to 5 years worth of advanced LIGO data. In this synthetically enhanced dataset, our AI ensemble reports an average of one misclassification for every month of searched advanced LIGO data. We also present the receiver operating characteristic curve of our AI ensemble using this 5 year long advanced LIGO dataset. This approach provides the required tools to conduct accelerated, AI-driven gravitational wave detection at scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Functionalization of Cathode–Electrolyte Interface with Ionic Liquids for High-Performance Quasi-Solid-State Lithium–Sulfur Batteries: A Low-Sulfur Loading Study

We introduce a quasi-solid-state electrolyte lithium-sulfur (Li–S) battery (QSSEB) based on a novel Li-argyrodite solid-state electrolyte (SSE), Super P–Sulfur cathode, and Li-anode. The cathode was prepared using a water-based carboxymethyl cellulose (CMC) solution and styrene butadiene rubber (SBR) as the binder while Li6PS5F0.5Cl0.5 SSE was synthesized using a solvent-based process, via the introduction of LiF into the argyrodite crystal structure, which enhances both the ionic conductivity and interface-stabilizing properties of the SSE. Ionic liquids (IL) were prepared using lithium bis(trifluoromethyl sulfonyl)imide (LiTFSI) as the salt, with pre-mixed pyrrolidinium bis(trifluoromethyl sulfonyl)imide (PYR) as solvent and 1,3-dioxolane (DOL) as diluent, and they were used to wet the SSE–electrode interfaces. The effect of IL dilution, the co-solvent amount, the LiTFSI concentration, the C rate at which the batteries are tested and the effect of the introduction of SSE in the cathode, were systematically studied and optimized to develop a QSSEB with higher capacity retention and cyclability. Interfacial reactions occurring at the cathode–SSE interface during cycling were also investigated using electrochemical impedance spectroscopy, cyclic voltammetry, and X-ray photoelectron spectroscopy supported by ab initio molecular dynamics simulations. This work offers a new insight into the intimate interfacial contacts between the SSE and carbon–sulfur cathodes, which are critical for improving the electrochemical performance of quasi-solid-state lithium–sulfur batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

A Fast Framework for Generating Radioactive Mixture Spectra and Its Application to Remote High-Performance Mixture Identification

Remote detection of radioactive materials in mixtures using handheld or portal detectors remains a challenge because of factors such as low concentration, environmental interference, sensor noise, and other complications. This work introduces a fast framework for generating realistic mixture spectra. Moreover, we present mixture isotope identification using data generated by the fast framework. Researchers have examined a range of conventional and recent algorithms within the fields of machine learning and deep learning. An application to uranium enrichment-level prediction has been included. Extensive simulation experiments validated the efficacy of the proposed framework.

GADRAS↗
DOE OSTI2024

Lattice Design and Advanced Modeling to Guide the Design of High-Performance Lightweight Structural Materials

Lightweight structural materials are required to increase the mobility of fission batteries. The materials must feature a robust combination of mechanical properties to demonstrate structural resilience. The primary objective of this project is to produce lightweight structural materials whose strength-to-weight ratios exceed those of the current widely used structural materials such as 316L stainless steels (316L SS). To achieve this, advanced modeling and simulation tools were employed to design lattice structures with different lattice parameters and different lattice types. A process was successfully developed for transforming lattice-structures models into Multiphysics Object Oriented Simulation Environment (MOOSE) inputs. Finite element modeling (FEM) was used to simulate the uniaxial tensile testing of the lattice-structured parts to investigate the stress distribution at a given displacement. The preliminary results showed that the lattice-structured sample displayed a lower Young’s modulus in comparison with the solid material and that the unit cell size of the lattice had a minimal effect. The novelty here is to apply up-front modeling to determine the best structure for the application before actually producing the sample. The approach of using modeling as a guiding tool for preliminary material design can significantly save time and cost for material development.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High performance context switching for virtualized FPGA accelerators

A hardware context manager in a field-programmable gate array (FPGA) device includes configuration logic configured to program one or more programming regions in the FPGA device based on configuration data for implementing a target configuration of the one or more programming regions. Context management logic in the hardware context manager is coupled with the configuration logic and saves a first context corresponding to the target configuration by retrieving first state information from the set of one or more programming regions, where the first state information is generated based on the target configuration, and storing the retrieved first state information in a context memory. The context management logic restores the first context by transferring the first state information from the context memory to the one or more programming regions, and causing the configuration logic to program the one or more programming regions based on the configuration data.

42 ENGINEERING↗
DOE OSTI2020

Obfuscation for high-performance computing systems

An example method includes initializing, by an obfuscation computing system, communications with nodes in a distributed computing platform, the nodes including one or more compute nodes and a controller node, and performing at least one of: (a) code-level obfuscation for the distributed computing platform to obfuscate interactions between an external user computing system and the nodes, wherein performing the code-level obfuscation comprises obfuscating data associated with one or more commands provided by the user computing system and sending one or more obfuscated commands to at least one of the nodes in the distributed computing platform; or (b) system-level obfuscation for the distributed computing platform, wherein performing the system-level obfuscation comprises at least one of obfuscating system management tasks that are performed to manage the nodes or obfuscating network traffic data that is exchanged between the nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Sequence optimizations in a high-performance computing environment

Embodiments are directed to techniques to determine dataflow graph instructions comprising one or more pick/switch instruction pairs and generate a reverse static single assignment graph based on the dataflow graph instructions, the reverse static single assignment graph comprising strongly connected components, each of the strongly connected components associated with at least one of the one or more pick/switch instruction pairs. Embodiments also include traversing the reverse static single assignment graph depth-first, and replace pick/switch instructions associated with strongly connected components having configuration values with compound instructions.

97 MATHEMATICS AND COMPUTING↗