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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design of detectors at the electron ion collider with artificial intelligence

Abstract Artificial Intelligence (AI) for design is a relatively new but active area of research across many disciplines. Surprisingly when it comes to designing detectors with AI this is an area at its infancy. The electron ion collider is the ultimate machine to study the strong force. The EIC is a large-scale experiment with an integrated detector that extends for about ±35 meters to include the central, far-forward, and far-backward regions. The design of the central detector is made by multiple sub-detectors, each in principle characterized by a multidimensional design space and multiple design criteria also called objectives. Simulations with Geant4 are typically compute intensive, and the optimization of the detector design may include non-differentiable terms as well as noisy objectives. In this context, AI can offer state of the art solutions to solve complex combinatorial problems in an efficient way. In particular, one of the proto-collaborations, ECCE, has explored during the detector proposal the possibility of using multi-objective optimization to design the tracking system of the EIC detector. This document provides an overview of these techniques and recent progress made during the EIC detector proposal. Future high energy nuclear physics experiments can leverage AI-based strategies to design more efficient detectors by optimizing their performance driven by physics criteria and minimizing costs for their realization.

Instruments & Instrumentation↗
NASA NTRS1997

Multidisciplinary Optimization Methods for Preliminary Design

An overview of multidisciplinary optimization (MDO) methodology and two applications of this methodology to the preliminary design phase are presented. These applications are being undertaken to improve, develop, validate and demonstrate MDO methods. Each is presented to illustrate different aspects of this methodology. The first application is an MDO preliminary design problem for defining the geometry and structure of an aerospike nozzle of a linear aerospike rocket engine. The second application demonstrates the use of the Framework for Interdisciplinary Design Optimization (FIDO), which is a computational environment system, by solving a preliminary design problem for a High-Speed Civil Transport (HSCT). The two sample problems illustrate the advantages to performing preliminary design with an MDO process.

Korte, J. J.↗
NASA NTRS2011

An Overview of NASA's Integrated Design and Engineering Analysis (IDEA) Environment

Historically, the design of subsonic and supersonic aircraft has been divided into separate technical disciplines (such as propulsion, aerodynamics and structures), each of which performs design and analysis in relative isolation from others. This is possible, in most cases, either because the amount of interdisciplinary coupling is minimal, or because the interactions can be treated as linear. The design of hypersonic airbreathing vehicles, like NASA's X-43, is quite the opposite. Such systems are dominated by strong non-linear interactions between disciplines. The design of these systems demands that a multi-disciplinary approach be taken. Furthermore, increased analytical fidelity at the conceptual design phase is highly desirable, as many of the non-linearities are not captured by lower fidelity tools. Only when these systems are designed from a true multi-disciplinary perspective, can the real performance benefits be achieved and complete vehicle systems be fielded. Toward this end, the Vehicle Analysis Branch at NASA Langley Research Center has been developing the Integrated Design and Engineering Analysis (IDEA) Environment. IDEA is a collaborative environment for parametrically modeling conceptual and preliminary designs for launch vehicle and high speed atmospheric flight configurations using the Adaptive Modeling Language (AML) as the underlying framework. The environment integrates geometry, packaging, propulsion, trajectory, aerodynamics, aerothermodynamics, engine and airframe subsystem design, thermal and structural analysis, and vehicle closure into a generative, parametric, unified computational model where data is shared seamlessly between the different disciplines. Plans are also in place to incorporate life cycle analysis tools into the environment which will estimate vehicle operability, reliability and cost. IDEA is currently being funded by NASA?s Hypersonics Project, a part of the Fundamental Aeronautics Program within the Aeronautics Research Mission Directorate. The environment is currently focused around a two-stage-to-orbit configuration with a turbine-based combined cycle (TBCC) first stage and a reusable rocket second stage. IDEA will be rolled out in generations, with each successive generation providing a significant increase in capability, either through increased analytic fidelity, expansion of vehicle classes considered, or by the inclusion of advanced modeling techniques. This paper provides the motivation behind the current effort, an overview of the development of the IDEA environment (including the contents and capabilities to be included in Generation 1 and Generation 2), and a description of the current status and detail of future plans.

Robinson, Jeffrey S.↗
DOE OSTI2023

Emerging opportunities for hybrid perovskite solar cells using machine learning

While there are several bottlenecks in hybrid organic–inorganic perovskite (HOIP) solar cell production steps, including composition screening, fabrication, material stability, and device performance, machine learning approaches have begun to tackle each of these issues in recent years. Different algorithms have successfully been adopted to solve the unique problems at each step of HOIP development. Specifically, high-throughput experimentation produces vast amount of training data required to effectively implement machine learning methods. Here, we present an overview of machine learning models, including linear regression, neural networks, deep learning, and statistical forecasting. Experimental examples from the literature, where machine learning is applied to HOIP composition screening, thin film fabrication, thin film characterization, and full device testing, are discussed. These paradigms give insights into the future of HOIP solar cell research. As databases expand and computational power improves, increasingly accurate predictions of the HOIP behavior are becoming possible.

Hering, Abigail R. (ORCID:0000000270806953)↗
DOE OSTI2021

From thermal catalysis to plasma catalysis: a review of surface processes and their characterizations

The use of atmospheric pressure plasma to enhance catalytic chemical reactions involves complex surface processes induced by the interactions of plasma-generated fluxes with catalyst surfaces. Industrial implementation of plasma catalysis necessitates optimizing the design and realization of plasma catalytic reactors that enable chemical reactions that are superior to conventional thermal catalysis approaches. This requires the fundamental understanding of essential plasma-surface interaction mechanisms of plasma catalysis from the aspect of experimental investigation and theoretical analysis or computational modeling. In addition, experimental results are essential to validate the relative theoretical models and hypotheses of plasma catalysis that was rarely understood so far, compared to conventional thermal catalysis. This overview focuses on two important application areas, nitrogen fixation and methane reforming, and presents a comparison of important aspects of the state of knowledge of these applications when performed using either plasma-catalysis or conventional thermal catalysis. We discuss the potential advantage of plasma catalysis over thermal catalysis from the aspects of plasma induced synergistic effect and in situ catalyst regeneration. In-situ/operando surface characterization of catalysts in plasma catalytic reactors is a significant challenge since the high pressure of realistic plasma catalysis systems preclude the application of many standard surface characterization techniques that operate in a low-pressure environment. Here, we present a review of the status of experimental approaches to probe gas-surface interaction mechanisms of plasma catalysis, including an appraisal of demonstrated approaches for integrating surface diagnostic tools into plasma catalytic reactors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

An Overview of Spray Modeling With OpenNCC and its Application to Emissions Predictions of a LDI Combustor at High Pressure

The open national combustion code (Open- NCC) is developed with the aim of advancing the current multi-dimensional computational tools used in the design of advanced technology combustors. In this paper we provide an overview of the spray module, LSPRAY-V, developed as a part of this effort. The spray solver is mainly designed to predict the flow, thermal, and transport properties of a rapidly evaporating multi-component liquid spray. The modeling approach is applicable over a wide-range of evaporating conditions (normal, superheat, and supercritical). The modeling approach is based on several well-established atomization, vaporization, and wall/droplet impingement models. It facilitates large-scale combustor computations through the use of massively parallel computers with the ability to perform the computations on either structured & unstructured grids. The spray module has a multi-liquid and multi-injector capability, and can be used in the calculation of both steady and unsteady computations. We conclude the paper by providing the results for a reacting spray generated by a single injector element with 600 axially swept swirler vanes. It is a configuration based on the next-generation lean-direct injection (LDI) combustor concept. The results include comparisons for both combustor exit temperature and EINOX at three different fuel/air ratios.

spray modeling↗
NASA NTRS1994

Overview of space power electronic's technology under the CSTI High Capacity Power Program

The Civilian Space Technology Initiative (CSTI) is a NASA Program targeted at the development of specific technologies in the areas of transportation, operations and science. Each of these three areas consists of major elements and one of the operation's elements is the High Capacity Power element. The goal of this element is to develop the technology base needed to meet the long duration, high capacity power requirements for future NASA initiatives. The High Capacity Power element is broken down into several subelements that includes energy conversion in the areas of the free piston Stirling power converter and thermoelectrics, thermal management, power management, system diagnostics, and environmental compatibility and system's lifetime. A recent overview of the CSTI High capacity Power element and a description of each of the program's subelements is given by Winter (1989). The goals of the Power Management subelement are twofold. The first is to develop, test, and demonstrate high temperature, radiation-resistant power and control components and circuits that will be needed in the Power Conditioning, Control and Transmission (PCCT) subsystem of a space nuclear power system. The results obtained under this goal will also be applicable to the instrumentation and control subsystem of a space nuclear reactor. These components and circuits must perform reliably for lifetimes of 7-10 years. The second goal is to develop analytical models for use in computer simulations of candidate PCCT subsystems. Circuits which will be required for a specific PCCT subsystem will be designed and built to demonstrate their performance and, also, to validate the analytical models and simulations. The tasks under the Power Management subelement will now be described in terms of objectives, approach and present status of work.

Schwarze, Gene E.↗
NASA NTRS2018

Testing with the Laser-Enhanced Arc Jet Facility (LEAF) at NASA Ames Research Center

NASA's new Laser-Enhanced Arcjet Facility (LEAF) employs 200 kilowatts of continuous-wave fiber lasers, combined with a 60-megawatt arc plasma jet, to simulate the combined radiative and convective heating is now operational and Orion heat-shield material is undergoing testing. This upgrade to the existing Interaction Heating Facility (IHF) involves the addition of high-power fiber lasers that project 1070nm radiative energy into the existing vacuum chamber. The optically expanded laser beam enters a side window of the test chamber to form either a uniform 150 x 150 mm or a 425 x 425 mm square spot on a wedge-shaped model holder. Combined heating levels of up to 180 W/cm2 convective with either 300 W/cm2 or 100 W/cm2 are achievable. This allows the arc jet and lasers to simulate dynamic entry-heating profiles encountered during entry by the Orion crew capsule for the lunar return conditions. New computational investigations are underway to explore testing with the objective of defining ablative material failure limit. Typical arc-jet testing is performed with test article that are stagnation or wedge geometries. The existing convective heating test facility combined with test article design limits how high a combined shear, heat-flux and pressure conditions can be achieved. With the addition of laser power of 200 kW, much higher combined conditions of high heat-flux, pressure and shear is achievable on a wedge or a swept-cylinder article. Such testing possibilities will allow us to progressively increase the combined conditions and explore when an ablative TPS material may fail. The presentation provides an overview of the LEAF and present results from the on-going Orion Testing.

Venkatapathy, Ethiraj↗
DOE OSTI2024

Science Use Case Design Patterns for Autonomous Experiments

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This paper introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further offers an overview of the 12 defined patterns and 4 examples of patterns of 2 different pattern classes. It also provides insight into building solutions from these patterns. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

Engelmann, Christian↗
DOE OSTI2025

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Ablation and Heating During Atmospheric Entry and Its Effect on Airburst Risk

Large meteoroids and asteroids entering the atmosphere endure tremendous heating from the shock heated air, and thereby lose a significant fraction of their mass during atmospheric entry a process known as ablation. The predicted evolution of the asteroids mass as it passes through the atmosphere can affect both the predicted energy deposition profile relevant to an airburst event, or the residual mass that strikes the ground in the case of an impact event. This presentation is divided roughly into two parts. In the first part, an overview of traditional models for heat transfer and ablation that are historically used in the meteor physics community is presented, and the validity in the asteroid entry regime discussed. Sensitivity analyses performed using the recently developed Fragment-Cloud Model (FCM) will be presented which show illustrate the range of sizes and entry parameters for which the predicted asteroid threat is most sensitive to the models for ablation and heat transfer. The second part of the presentation shall focus on recent work done under NASAs Asteroid Threat Assessment Project (ATAP) to develop new models for heat transfer and ablation using high-fidelity numerical simulation in concert with state-of-the-art experiments. Coupled computational fluid dynamics (CFD)radiation transport simulations preformed using the state-of-the-art entry modeling tools at NASA show that, for large meteoroids and asteroids, there can significant attenuation of the heat transfer to the surface (95 in some cases) by the products of ablation. In addition to the heat transfer, new models for the material response and ablation of asteroidal material have been developed [cite]. In the current work, we present finding from recent novel experiments performed in the arc jet facility at NASA Ames, which allows us to, in part, simulate the extreme environment experienced by the asteroid during entry. Briefly, the experimental set-up was comprised of a 1.5 conical article of machined H5 chondrite, which was exposed to a high-enthalpy flow resulting in approximately 4 kWcm2 of heating to the surface. A still frame capture from high-speed video taken during this experiment can be seen in Figure 1. In this figure, we can observe some of the major mechanisms for meteoroid ablation, such as melt flow, spallation (mechanical removal of material), and vaporization. Major findings from this, and other experiments will be discussed, as well progress on utilizing the data from the experiments to inform and develop improved models for ablation.

Asteroids↗
DOE OSTI2020

Brief Overview of the ASD Integrated Test Stand, Activities and Hazards

The ITS venue provides the first opportunity to fully assemble and test the performance of the injector; integrate, assemble and test four modules; measure the severity of the Beam Break-Up instability and perform the first set of beam measurements. Figure 1 shows a high level configuration of the ITS without the system of overhead cable management trays. The final configuration will integrate the injector, 4 modules (12 accelerator cells), 264 SSPP Line Replaceable Units (LRUs), global controls, data acquisition, and a subset of the downstream transport, Table 1. This was chosen because it provides the minimum accelerator cells required to measure the Beam Break-Up (BBU) instability and perform measurements required to validate the ASD beam transport computer models, which are priority measurements for commissioning.

43 PARTICLE ACCELERATORS↗
NASA NTRS1994

Computation of iodine species concentrations in water

During an evaluation of the use of iodine as a water disinfectant and the development of methods for measuring various iodine species in water onboard Space Freedom, it became necessary to compute the concentration of the various species based on equilibrium principles alone. Of particular concern was the case when various amounts of iodine, iodide, strong acid, and strong base are added to water. Such solutions can be used to evaluate the performance of various monitoring methods being considered. The authors of this paper present an overview of aqueous iodine chemistry, a set of nonlinear equations which can be used to model the above case, and a computer program for solving this system of equations using the Newton-Raphson method. The program was validated by comparing results over a range of concentrations and pH values with those previously presented by Gottardi for a given pH. Use of this program indicated that there are multiple roots to many cases and selecting an appropriate initial guess is important. Comparison of program results with laboratory results for the case when only iodine is added to water indicates the program gives high pH values for the iodine concentrations normally used for water disinfection. Extending the model to include the effects of iodate formation results in the computer pH values being closer to those observed, but the model with iodate does not agree well for the case in which base is added in addition to iodine to raise the pH. Potential explanations include failure to obtain equilibrium conditions in the lab, inaccuracies in published values for the equilibrium constants, and inadequate model of iodine chemistry and/or the lack of adequate analytical methods for measuring the various iodine species in water.

Schultz, John R.↗
NASA NTRS2006

Application of the H-Mode, a Design and Interaction Concept for Highly Automated Vehicles, to Aircraft

Driven by increased safety, efficiency, and airspace capacity, automation is playing an increasing role in aircraft operations. As aircraft become increasingly able to autonomously respond to a range of situations with performance surpassing human operators, we are compelled to look for new methods that help us understand their use and guide their design using new forms of automation and interaction. We propose a novel design metaphor to aid the conceptualization, design, and operation of highly-automated aircraft. Design metaphors transfer meaning from common experiences to less familiar applications or functions. A notable example is the "Desktop metaphor" for manipulating files on a computer. This paper describes a metaphor for highly automated vehicles known as the H-metaphor and a specific embodiment of the metaphor known as the H-mode as applied to aircraft. The fundamentals of the H-metaphor are reviewed followed by an overview of an exploratory usability study investigating human-automation interaction issues for a simple H-mode implementation. The envisioned application of the H-mode concept to aircraft is then described as are two planned evaluations.

Goodrich, Kenneth H.↗
NASA NTRS2002

Overview of High-Fidelity Modeling Activities in the Numerical Propulsion System Simulations (NPSS) Project

A high-fidelity simulation of a commercial turbofan engine has been created as part of the Numerical Propulsion System Simulation Project. The high-fidelity computer simulation utilizes computer models that were developed at NASA Glenn Research Center in cooperation with turbofan engine manufacturers. The average-passage (APNASA) Navier-Stokes based viscous flow computer code is used to simulate the 3D flow in the compressors and turbines of the advanced commercial turbofan engine. The 3D National Combustion Code (NCC) is used to simulate the flow and chemistry in the advanced aircraft combustor. The APNASA turbomachinery code and the NCC combustor code exchange boundary conditions at the interface planes at the combustor inlet and exit. This computer simulation technique can evaluate engine performance at steady operating conditions. The 3D flow models provide detailed knowledge of the airflow within the fan and compressor, the high and low pressure turbines, and the flow and chemistry within the combustor. The models simulate the performance of the engine at operating conditions that include sea level takeoff and the altitude cruise condition.

Veres, Joseph P.↗
NASA NTRS2016

The Kepler Science Data Processing Pipeline Source Code Road Map

We give an overview of the operational concepts and architecture of the Kepler Science Processing Pipeline. Designed, developed, operated, and maintained by the Kepler Science Operations Center (SOC) at NASA Ames Research Center, the Science Processing Pipeline is a central element of the Kepler Ground Data System. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center which hosts the computers required to perform data analysis. The SOC's charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Processing Pipeline, including, the software algorithms. We present the high-performance, parallel computing software modules of the pipeline that perform transit photometry, pixel-level calibration, systematic error correction, attitude determination, stellar target management, and instrument characterization.

Kepler pipeline software↗
NASA NTRS1988

Spacecraft applications of advanced global positioning system technology

This is the final report on the Texas Instruments Incorporated (TI) simulations study of Spacecraft Application of Advanced Global Positioning System (GPS) Technology. This work was conducted for the NASA Johnson Space Center (JSC) under contract NAS9-17781. GPS, in addition to its baselined capability as a highly accurate spacecraft navigation system, can provide traffic control, attitude control, structural control, and uniform time base. In Phase 1 of this program, another contractor investigated the potential of GPS in these four areas and compared GPS to other techniques. This contract was for the Phase 2 effort, to study the performance of GPS for these spacecraft applications through computer simulations. TI had previously developed simulation programs for GPS differential navigation and attitude measurement. These programs were adapted for these specific spacecraft applications. In addition, TI has extensive expertise in the design and production of advanced GPS receivers, including space-qualified GPS receivers. We have drawn on this background to augment the simulation results in the system level overview, which is Section 2 of this report.

Source record↗
DOE OSTI2021

Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗