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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Generation and characterization of carbon fiber microstructure in atomistic simulations

A clear understanding of carbon fiber (CF) microstructure is necessary for the development of high strength CFs. Here, we present an atomistic approach for generating and characterizing realistic mi- crostructures of CFs. Large-scale reactive molecular dynamics simulations are used to generate a set of distinct CF microstructures. Comprehensive characterization of the simulated microstructures is enabled by the development of a suite of computational structural analysis tools capable of evaluation of hy- bridization states of carbon atoms, populations and orientations of individual carbon rings, degree of graphitization, and pore size distribution. The calculation of X-ray diffraction profiles provides a direct link between the structural features of simulated samples and experimental data available for CFs. The CF generation algorithm is shown to produce microstructures with experimental densities and with structural characteristics matching those of PAN-based CFs. The key structural features affecting the properties of CFs, such as the relative fractions of graphitic, turbostratic and amorphous micro- constituents, degree of alignment, pore size distributions, and chemical cross-linking can be effectively controlled in simulations, thus enabling efficient exploration of structureeproperties relationships in CFs. The capabilities of the developed approach are illustrated by performing computational analysis of the mechanical deformation and fracture of CFs under axial tensile loading.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Structural Tailoring of SSME Blades (vanes)

The engine blade design optimization program STAEBL (Structural Tailoring of Engine Blades) is available at the NASA Lewis computer facility. The analysis capabilities of this program were extended to typical loading conditions for SSME turbopump blades including thermal and pressure loading. Input files for representative SSME blade designs were developed and sample optimization studies for these blades completed. The structural tailoring program combines a general optimization package and a finite element blade analysis package. The analysis package's capabilities include natural frequency, maximum stress, and forced response computation, and fatigue life and flutter analysis. Optimization is performed using the feasible directions method. The current design is modified by perturbing the design variables so that the design constraints are satisfied while the objective function, such as blade weight, is reduced at the maximum rate. The program's geometric design variables include blade thickness distribution, thickness to chord ratios, and root chord.

Rubinstein, R.↗
DOE OSTI2024

End-to-End Encryption for Cyber-Physical Systems Using Fully Homomorphic Encryption

Cyber-physical systems require reliable, safe, and secure control of critical infrastructure, combining computational and networking capabilities, which heighten the risk of cyber attacks. These attacks can disrupt the physical process, causing unforeseen consequences. One solution is the use of fully homomorphic encryption (FHE) to protect the control loop, allowing for secure computations and communications without compromising signal and control system privacy. The challenge with FHE, however, is its requirement for inputs to be integers. This presentation introduces a modified Learning With Errors (LWE) FHE approach that encodes control system dynamics and signals into integers. Our proposed scheme leverages a generalized LWE encoding function and modifies the Gentry-Sahai-Waters gadget decomposition tool to encrypt the control system. Using the modified LWE scheme, we formalize a fully encrypted control system, supported by simulated results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Encrypted Control Using Modified Learning With Errors-based Schemes

Cyber-physical systems (CPSs) require reliable, safe, and secure control of critical infrastructure, combining computational and networking capabilities, which heighten the risk of cyber attacks. These attacks can disrupt the physical process, causing unforeseen consequences. One solution is the use of fully homomorphic encryption (FHE) to protect the control loop, allowing for secure computations and communications without compromising signal and control system privacy. The challenge with FHE, however, is its requirement for inputs to be integers. This paper introduces a modified Learning With Errors (LWE) FHE approach that encodes control system dynamics and signals into integers. Our proposed scheme leverages a generalized LWE encoding function and modifies the Gentry-Sahai-Waters (GSW) gadget decomposition tool to encrypt the control system. Using the modified LWE scheme, we formalize a fully encrypted control system, supported by simulated results.

42 - ENGINEERING↗
DOE OSTI2021

Quantum Computer-Aided Design: Digital Quantum Simulation of Quantum Processors

With the increasing size of quantum processors, submodules that constitute the processor hardware will become too large to accurately simulate on a classical computer. Therefore, one would soon have to fabricate and test each new design primitive and parameter choice in time-consuming coordination between design, fabrication, and experimental validation. Here we show how one can design and test the performance of next-generation quantum hardware—by using existing quantum computers. Focusing on superconducting transmon processors as a prominent hardware platform, we compute the static and dynamic properties of individual and coupled transmons. We show how the energy spectra of transmons can be obtained by variational hybrid quantum-classical algorithms that are well suited for near-term noisy quantum computers. In addition, single- and two-qubit gate simulations are demonstrated via Suzuki-Trotter decomposition. Our methods pave a promising way towards designing candidate quantum processors when the demands of calculating submodule properties exceed the capabilities of classical computing resources.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2012

Development, Verification and Use of Gust Modeling in the NASA Computational Fluid Dynamics Code FUN3D

This paper presents the implementation of gust modeling capability in the CFD code FUN3D. The gust capability is verified by computing the response of an airfoil to a sharp edged gust. This result is compared with the theoretical result. The present simulations will be compared with other CFD gust simulations. This paper also serves as a users manual for FUN3D gust analyses using a variety of gust profiles. Finally, the development of an Auto-Regressive Moving-Average (ARMA) reduced order gust model using a gust with a Gaussian profile in the FUN3D code is presented. ARMA simulated results of a sequence of one-minus-cosine gusts is shown to compare well with the same gust profile computed with FUN3D. Proper Orthogonal Decomposition (POD) is combined with the ARMA modeling technique to predict the time varying pressure coefficient increment distribution due to a novel gust profile. The aeroelastic response of a pitch/plunge airfoil to a gust environment is computed with a reduced order model, and compared with a direct simulation of the system in the FUN3D code. The two results are found to agree very well.

Bartels, Robert E.↗
DOE OSTI2024

TRUST Sensors in Environments: Accelerometers (SE-A) Report, Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. The TRUST project consists of five "low-complexity", single-feature testbeds used to conduct experiments with accompanying models and simulations. Each of the five single feature testbeds aims to isolate an engineering feature or behavior of interest, then work towards improving the fundamental engineering understanding of that feature. Additionally, the single feature testbeds are used to identify capability development needs that can help reduce model and experimental uncertainty.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

decision support↗
NASA NTRS2015

Experimental and Computational Sonic Boom Assessment of Lockheed-Martin N+2 Low Boom Models

Flight at speeds greater than the speed of sound is not permitted over land, primarily because of the noise and structural damage caused by sonic boom pressure waves of supersonic aircraft. Mitigation of sonic boom is a key focus area of the High Speed Project under NASA's Fundamental Aeronautics Program. The project is focusing on technologies to enable future civilian aircraft to fly efficiently with reduced sonic boom, engine and aircraft noise, and emissions. A major objective of the project is to improve both computational and experimental capabilities for design of low-boom, high-efficiency aircraft. NASA and industry partners are developing improved wind tunnel testing techniques and new pressure instrumentation to measure the weak sonic boom pressure signatures of modern vehicle concepts. In parallel, computational methods are being developed to provide rapid design and analysis of supersonic aircraft with improved meshing techniques that provide efficient, robust, and accurate on- and off-body pressures at several body lengths from vehicles with very low sonic boom overpressures. The maturity of these critical parallel efforts is necessary before low-boom flight can be demonstrated and commercial supersonic flight can be realized.

Cliff, Susan E.↗
NASA NTRS2019

Optimal Control within the Context of Multidisciplinary Design, Analysis, and Optimization

Multidisciplinary design, analysis and optimization involves modeling the interactions of complex systems across a variety of disciplines. The optimization of such systems can be a computationally expensive exercise with multiple levels of nested nonlinear solvers running under an optimizer.The application of optimal control in project development often involves performing trajectory optimization for fixed vehicle designs or parametric sweeps across some key vehicle properties.This information is then relayed to the subsystem design teams who update their designs and relay some bulk characteristics back to the trajectory optimization procedure.This iteration is then repeated until the design closes.However, with increasing interest in more tightly coupled systems, such as electric and hybrid-electric aircraft propulsion and boundary layer ingestion, this process is prone to ignore subtle coupling between vehicle subsystem designs and vehicle operation on a given mission.Integrating trajectory optimization into a tightly coupled multidisciplinary design procedure can be computationally prohibitive, depending on the complexity of the subsystem analyses and the optimal control technique applied.To address these issues a new optimal control software tool, Dymos, has been developed.Dymos is built upon NASA's OpenMDAO software and can leverage its capabilities to efficiently compute gradients for the optimization and optimize complex models in parallel on distributed memory systems.This report provides some explanation into the numerical methods employed in Dymos and provides several use cases that demonstrate its performance on traditional optimal control problems and improvements ino techniques have been used extensively in recent decades to solve a variety of optimal control problems, typically in the form of aerospace vehicle trajectory optimization.

pseudospectral↗
DOE OSTI2022

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Basic Energy Sciences Roundtable: Opportunities for Basic Research for Next-Generation Quantum Systems

For decades, scientists have predicted that devices based on “quantum phenomena” will be able to store and manipulate information to provide radical new approaches for computing, communication, and sensing. However, only recently have quantum phenomena been incorporated into technologies for next-generation computers, sensors, and detectors that demonstrate performance characteristics rivaling those of their conventional counterparts. These devices clearly demonstrate the enormous potential for future quantum-based technologies. The novel quantum device capabilities currently envisioned include enhanced resolution in imaging, sensors, and detectors; advanced cryptography for more secure communication; and significantly larger computational capabilities at speeds far greater than those possible in classical computing. However, realizing these advances requires a detailed understanding of how quantum systems (including quantum materials or assemblies of trapped ions and electrons) behave, accurate knowledge of how to integrate the components into complex systems, and precise control of the structures. In this context, creating and controlling quantum states within molecules and materials offer exciting scientific opportunities for fundamental research, as well as for enabling next-generation quantum-based technologies. Numerous questions remain, ranging from how quantum interactions may enable innovation through the creation of novel quantum systems, to how these new quantum technologies can advance our understanding of matter and chemistry at the most fundamental levels. To address these questions and identify priority research opportunities (PROs), the US Department of Energy (DOE) Office of Basic Energy Sciences (BES) convened a roundtable of experts in quantum materials and quantum systems encompassing the fields of physics, chemistry, materials synthesis science, device engineering, detector technology, and atomic-scale characterization techniques. This group of experimentalists and theorists met on October 30–31, 2017, to explore scientific research opportunities in this rapidly moving field, in which BES support can play a key role in advancing and utilizing quantum information science (QIS). The goals of this roundtable were to define the unique roles for BES in this active research field and to provide input on future research directions, forming the basis for a coordinated, long-term research effort that will enable major advances in quantum-based science and technology. BES is uniquely positioned to advance this field because of its long history of fundamental research support for both materials and chemical sciences, along with its construction and operation of world-class scientific user facilities. Fundamental research in this area is strongly coupled to DOE efforts in scientific computing, high-energy physics, and accelerator/detector research and related to activities in “Beyond Moore’s Law” computing, next-generation semiconductor materials, and exascale computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1970

Prediction of electron density in the boundary layer on entry vehicles with ablation

A rather general computer code has been developed for the numerical solution of the laminar boundary layer and thin shock layer (stagnation point only) equations for a multi-component gas mixture with finite reaction rates. The purpose of this paper is to indicate the capabilities of this computer program by presenting solutions for pure air flows and flows with carbon ablation. At the body surface the effects of oxidation and sublimation of carbon are taken into account with the following species included in the gas model: 0 2 , N 2 , O, N, NO, NO + , C 1 , C 2 , C 3 , CN, CO, and CO 2 . Results for the boundary layer along a 10° half-angle hyperboloid with ablation of carbon are compared to pure air results. Shock layer results for several wall temperatures and altitudes are presented and compared to pure air results. Other types of problems that can be solved with this computer code are indicated.

F. G. Blottner↗
NASA NTRS1990

Hypercube-Computer Analysis Of Electromagnetic Scattering

Capabilities of hypercube and parallel processing demonstrated. Report describes use of Mark III Hypercube computer to analyze scattering of electromagnetic waves. Purpose of study to assess utility of parallel computing in such computation-intensive problems as large-scale electromagnetic scattering. Two electromagnetic codes based on different algorithms converted to run on Mark III Hypercube. First code implements finite-difference, time-domain solution of Maxwell's curl equations. Second code is Numerical Electromagnetics Code (NEC-2) which embodies frequency-domain method and developed to analyze electromagnetic responses of antennas and other metallic structures. On Mark III Hypercube with 32 active nodes, largest lattice contains about 2,048,000 unit cells.

Patterson, J. E.↗