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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 433 records · Page 24

AQDrop Quantum Service (AQDrop) v1.0

AQDrop is a job management system designed to streamline access to the Advanced Quantum Testbed (AQT) at NERSC (National Energy Research Scientific Computing Center). It serves as a centralized middleware layer between researchers and quantum processing hardware. Key Features: AQDrop provides a FastAPI-based server backed by PostgreSQL for job submission, queue management, and role-based access control (members, operators, and administrators). Users submit Qiskit circuits via JSON payloads, which are queued, dispatched to the QPU through the Qubic API, and returned as measurement counts. A Python client library and web dashboard round out the interface options. Primary Use: Researchers submit quantum circuit jobs from a laptop or login node; an operator client executes those jobs on the AQT's physical QPU and returns results — all coordinated through the central API. Advantages: Compared to ad-hoc or direct hardware access, AQDrop adds structured queue management, auditable job-status tracking and OAuth2 authentication — reducing scheduling conflicts and unauthorized access. Its containerized deployment also improves reproducibility and scalability. Overall, AQDrop functions as a purpose-built quantum job broker tailored to NERSC's specific hardware and institutional access requirements.

Caplinger, Evan [Lawrence Berkeley National Labora↗

Fan Noise Prediction: Status and Needs

The prediction of fan noise is an important part to the prediction of overall turbofan engine noise. Advances in computers and better understanding of the flow physics have allowed researchers to compute sound generation from first principles and rely less on empirical correlations. While progress has been made, there are still many aspects of the problem that need to be explored. This paper presents some recent advances in fan noise prediction and suggests areas that still need further development. Fan noise predictions that support the recommendations are taken from existing publications.

Huff, Dennis L.↗

MAVRIC Flutter Model Transonic Limit Cycle Oscillation Test

The Models for Aeroelastic Validation Research Involving Computation semi-span wind-tunnel model (MAVRIC-I), a business jet wing-fuselage flutter model, was tested in NASA Langley's Transonic Dynamics Tunnel with the goal of obtaining experimental data suitable for Computational Aeroelasticity code validation at transonic separation onset conditions. This research model is notable for its inexpensive construction and instrumentation installation procedures. Unsteady pressures and wing responses were obtained for three wingtip configurations clean, tipstore, and winglet. Traditional flutter boundaries were measured over the range of M = 0.6 to 0.9 and maps of Limit Cycle Oscillation (LCO) behavior were made in the range of M = 0.85 to 0.95. Effects of dynamic pressure and angle-of-attack were measured. Testing in both R134a heavy gas and air provided unique data on Reynolds number, transition effects, and the effect of speed of sound on LCO behavior. The data set provides excellent code validation test cases for the important class of flow conditions involving shock-induced transonic flow separation onset at low wing angles, including Limit Cycle Oscillation behavior.

Edwards, John W.↗

MAVRIC Flutter Model Transonic Limit Cycle Oscillation Test

The Models for Aeroelastic Validation Research Involving Computation semi-span wind-tunnel model (MAVRIC-I), a business jet wing-fuselage flutter model, was tested in NASA Langley's Transonic Dynamics Tunnel with the goal of obtaining experimental data suitable for Computational Aeroelasticity code validation at transonic separation onset conditions. This research model is notable for its inexpensive construction and instrumentation installation procedures. Unsteady pressures and wing responses were obtained for three wingtip configurations of clean, tipstore, and winglet. Traditional flutter boundaries were measured over the range of M = 0.6 to 0.9 and maps of Limit Cycle Oscillation (LCO) behavior were made in the range of M = 0.85 to 0.95. Effects of dynamic pressure and angle-of-attack were measured. Testing in both R134a heavy gas and air provided unique data on Reynolds number, transition effects, and the effect of speed of sound on LCO behavior. The data set provides excellent code validation test cases for the important class of flow conditions involving shock-induced transonic flow separation onset at low wing angles, including LCO behavior.

Edwards, John W.↗

CaTs Lab (CHAOS and Thermal Sciences Laboratory)

The CHAOS and Thermal Sciences Laboratory (CaTs) at James Madison University evolved into a noteworthy effort to increase minority representation in the sciences and mathematics. Serving ten students and faculty directly, and nearly 50 students indirectly, CaTs, through recruitment efforts, workshops, mentoring programs, tutorial services and research and computational laboratories, fulfilled its intent to initiate an academically enriched research program aimed at strengthening the academic and self-actualization skills of undergraduate students with potential to pursue doctoral study in the sciences. The stated goal of the program was to increase by 5% the number of enrolled mathematics and science students into the program. Success far exceeded the program goals by producing 100% graduation rate of all supported recipients during its tenure, with 30% of the students subsequently in pursuit of graduate degrees. Student retention in the program exceeded 90% and faculty participation exceeded the three members involved in mentoring and tutoring, gaining multi-disciplinary support. Aggressive marketing of the program resulted in several paid summer internships and commitments from NASA and an ongoing relationship with CHROME, a nationally recognized organization which focuses on developing minority students in the sciences and mathematics. Success of the program was only limited by the limited fiscal resources at NASA which resulted in phasing out of the program.

Teate, Anthony A.↗

Airport-Noise Levels and Annoyance Model (ALAMO) user's guide

A guide for the use of the Airport-Noise Level and Annoyance MOdel (ALAMO) at the Langley Research Center computer complex is provided. This document is divided into 5 primary sections, the introduction, the purpose of the model, and an in-depth description of the following subsystems: baseline, noise reduction simulation and track analysis. For each subsystem, the user is provided with a description of architecture, an explanation of subsystem use, sample results, and a case runner's check list. It is assumed that the user is familiar with the operations at the Langley Research Center (LaRC) computer complex, the Network Operating System (NOS 1.4) and CYBER Control Language. Incorporated within the ALAMO model is a census database system called SITE II.

Deloach, R.↗

METCAN: The metal matrix composite analyzer

Metal matrix composites (MMC) are the subject of intensive study and are receiving serious consideration for critical structural applications in advanced aerospace systems. MMC structural analysis and design methodologies are studied. Predicting the mechanical and thermal behavior and the structural response of components fabricated from MMC requires the use of a variety of mathematical models. These models relate stresses to applied forces, stress intensities at the tips of cracks to nominal stresses, buckling resistance to applied force, or vibration response to excitation forces. The extensive research in computational mechanics methods for predicting the nonlinear behavior of MMC are described. This research has culminated in the development of the METCAN (METal Matrix Composite ANalyzer) computer code.

Hopkins, Dale A.↗

Atomate2: modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science.

97 MATHEMATICS AND COMPUTING↗

Heterogeneous Distributed Computing for Computational Aerosciences

The research supported under this award focuses on heterogeneous distributed computing for high-performance applications, with particular emphasis on computational aerosciences. The overall goal of this project was to and investigate issues in, and develop solutions to, efficient execution of computational aeroscience codes in heterogeneous concurrent computing environments. In particular, we worked in the context of the PVM[1] system and, subsequent to detailed conversion efforts and performance benchmarking, devising novel techniques to increase the efficacy of heterogeneous networked environments for computational aerosciences. Our work has been based upon the NAS Parallel Benchmark suite, but has also recently expanded in scope to include the NAS I/O benchmarks as specified in the NHT-1 document. In this report we summarize our research accomplishments under the auspices of the grant.

Sunderam, Vaidy S.↗

Aviation Safety Research at NASA Langley: Applications of Physiological Computing and Neuroergonomics

The emerging field of research, known as Neuroergonomics, maintains that in order to investigate complex real-world behavior it is necessary to undePhysiological Computing systems are technological systems that incorporate physiological data from humans into their functionality or display these data at their interfaces. Neuroergonomics examines the brain mechanisms and underlying human–technology interaction in increasingly naturalistic settings representative of work and in everyday-life situations. The presenters will introduce Physiological Computing and Neuroergonomics in applications that vary from social robotics and videogames in laboratory settings to firearms training in virtual reality to aviation operations in highly ecological environments.

Aviation Safety Research↗

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Future fundamental combustion research for aeropropulsion systems

Physical fluid mechanics, heat transfer, and chemical kinetic processes which occur in the combustion chamber of aeropropulsion systems were investigated. With the component requirements becoming more severe for future engines, the current design methodology needs the new tools to obtain the optimum configuration in a reasonable design and development cycle. Research efforts in the last few years were encouraging but to achieve these benefits research is required into the fundamental aerothermodynamic processes of combustion. It is recommended that research continues in the areas of flame stabilization, combustor aerodynamics, heat transfer, multiphase flow and atomization, turbulent reacting flows, and chemical kinetics. Associated with each of these engineering sciences is the need for research into computational methods to accurately describe and predict these complex physical processes. Research needs in each of these areas are highlighted.

Mularz, E. J.↗

Future fundamental combustion research for aeropropulsion systems

Physical fluid mechanics, heat transfer, and chemical kinetic processes which occur in the combustion chamber of aeropropulsion systems were investigated. With the component requirements becoming more severe for future engines, the current design methodology needs the new tools to obtain the optimum configuration in a reasonable design and development cycle. Research efforts in the last few years were encouraging but to achieve these benefits research is required into the fundamental aerothermodynamic processes of combustion. It is recommended that research continues in the areas of flame stabilization, combustor aerodynamics, heat transfer, multiphase flow and atomization, turbulent reacting flows, and chemical kinetics. Associated with each of these engineering sciences is the need for research into computational methods to accurately describe and predict these complex physical processes. Research needs in each of these areas are highlighted.

Mularz, E. J.↗

Multi-color incomplete Cholesky conjugate gradient methods for vector computers

In this research, we are concerned with the solution on vector computers of linear systems of equations, Ax = b, where A is a larger, sparse symmetric positive definite matrix. We solve the system using an iterative method, the incomplete Cholesky conjugate gradient method (ICCG). We apply a multi-color strategy to obtain p-color matrices for which a block-oriented ICCG method is implemented on the CYBER 205. (A p-colored matrix is a matrix which can be partitioned into a pXp block matrix where the diagonal blocks are diagonal matrices). This algorithm, which is based on a no-fill strategy, achieves O(N/p) length vector operations in both the decomposition of A and in the forward and back solves necessary at each iteration of the method. We discuss the natural ordering of the unknowns as an ordering that minimizes the number of diagonals in the matrix and define multi-color orderings in terms of disjoint sets of the unknowns. We give necessary and sufficient conditions to determine which multi-color orderings of the unknowns correpond to p-color matrices. A performance model is given which is used both to predict execution time for ICCG methods and also to compare an ICCG method to conjugate gradient without preconditioning or another ICCG method. Results are given from runs on the CYBER 205 at NASA's Langley Research Center for four model problems.

Poole, E. L.↗

Research Software Engineering: Introducing a New Computing in Science & Engineering Department

Here, this article introduces the new Research Software Engineering (RSEng) department at Computing in Science & Engineering. Through a conversation with the department coeditors, we highlight why RSEng matters, how it differs from industrial software engineering, what it means to be an RSE, and the scholarly and practical questions that lie ahead. Along the way, we draw on emerging literature, case studies, and community perspectives to frame the profession and practice of RSEng within computational science and engineering.

Lamprecht, Anna-Lena [Univ. of Potsdam (Germany)] ↗

Aeroelasticity of wing and wing-body configurations on parallel computers

The objective of this research is to develop computationally efficient methods for solving aeroelasticity problems on parallel computers. Both uncoupled and coupled methods are studied in this research. For the uncoupled approach, the conventional U-g method is used to determine the flutter boundary. The generalized aerodynamic forces required are obtained by the pulse transfer-function analysis method. For the coupled approach, the fluid-structure interaction is obtained by directly coupling finite difference Euler/Navier-Stokes equations for fluids and finite element dynamics equations for structures. This capability will significantly impact many aerospace projects of national importance such as Advanced Subsonic Civil Transport (ASCT), where the structural stability margin becomes very critical at the transonic region. This research effort will have direct impact on the High Performance Computing and Communication (HPCC) Program of NASA in the area of parallel computing.

Byun, Chansup↗

Research in progress and other activities of the Institute for Computer Applications in Science and Engineering

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics and computer science during the period April 1, 1993 through September 30, 1993. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustic and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science.

Source record↗

Dynamic Deformation Measurements of an Aeroelastic Semispan Model

The techniques used to acquire, reduce, and analyze dynamic deformation measurements of an aeroelastic semispan wind tunnel model are presented. Single-camera, single-view video photogrammetry (also referred to as videogrammetric model deformation, or VMD) was used to determine dynamic aeroelastic deformation of the semispan 'Models for Aeroelastic Validation Research Involving Computation' (MAVRIC) model in the Transonic Dynamics Tunnel at the NASA Langley Research Center. Dynamic deformation was determined from optical retroreflective tape targets at five semispan locations located on the wing from the root to the tip. Digitized video images from a charge coupled device (CCD) camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. Videogrammetric dynamic data were acquired at a 60-Hz rate for time records of up to 6 seconds during portions of this flutter/Limit Cycle Oscillation (LCO) test at Mach numbers from 0.3 to 0.96. Spectral analysis of the deformation data is used to identify dominant frequencies in the wing motion. The dynamic data will be used to separate aerodynamic and structural effects and to provide time history deflection data for Computational Aeroelasticity code evaluation and validation.

Graves, Sharon S.↗