Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “applied computing → operations research”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Fuzzy set approach to quality function deployment: An investigation

The final report of the 1992 NASA/ASEE Summer Faculty Fellowship at the Space Exploration Initiative Office (SEIO) in Langley Research Center is presented. Quality Function Deployment (QFD) is a process, focused on facilitating the integration of the customer's voice in the design and development of a product or service. Various input, in the form of judgements and evaluations, are required during the QFD analyses. All the input variables in these analyses are treated as numeric variables. The purpose of the research was to investigate how QFD analyses can be performed when some or all of the input variables are treated as linguistic variables with values expressed as fuzzy numbers. The reason for this consideration is that human judgement, perception, and cognition are often ambiguous and are better represented as fuzzy numbers. Two approaches for using fuzzy sets in QFD have been proposed. In both cases, all the input variables are considered as linguistic variables with values indicated as linguistic expressions. These expressions are then converted to fuzzy numbers. The difference between the two approaches is due to how the QFD computations are performed with these fuzzy numbers. In Approach 1, the fuzzy numbers are first converted to their equivalent crisp scores and then the QFD computations are performed using these crisp scores. As a result, the output of this approach are crisp numbers, similar to those in traditional QFD. In Approach 2, all the QFD computations are performed with the fuzzy numbers and the output are fuzzy numbers also. Both the approaches have been explained with the help of illustrative examples of QFD application. Approach 2 has also been applied in a QFD application exercise in SEIO, involving a 'mini moon rover' design. The mini moon rover is a proposed tele-operated vehicle that will traverse and perform various tasks, including autonomous operations, on the moon surface. The output of the moon rover application exercise is a ranking of the rover functions so that a subset of these functions can be targeted for design improvement. The illustrative examples and the mini rover application exercise confirm that the proposed approaches for using fuzzy sets in QFD are viable. However, further research is needed to study the various issues involved and to verify/validate the methods proposed.

Masud, Abu S. M.↗
NASA NTRS1991

Digital optical computers at the optoelectronic computing systems center

The Digital Optical Computing Program within the National Science Foundation Engineering Research Center for Opto-electronic Computing Systems has as its specific goal research on optical computing architectures suitable for use at the highest possible speeds. The program can be targeted toward exploiting the time domain because other programs in the Center are pursuing research on parallel optical systems, exploiting optical interconnection and optical devices and materials. Using a general purpose computing architecture as the focus, we are developing design techniques, tools and architecture for operation at the speed of light limit. Experimental work is being done with the somewhat low speed components currently available but with architectures which will scale up in speed as faster devices are developed. The design algorithms and tools developed for a general purpose, stored program computer are being applied to other systems such as optimally controlled optical communication networks.

Jordan, Harry F.↗
NASA NTRSDate not supplied

Full-Envelope Aero-Propulsive Model Identification for Lift+Cruise Aircraft Using Computational Experiments

This paper describes a process utilizing computational fluid dynamics experiments to develop a reduced-order, integrated propulsion-airframe aerodynamic model for a lift+cruise electric vertical takeoff and landing (eVTOL) reference aircraft concept. eVTOL configurations exhibit aerodynamic characteristics of both fixed-wing and rotary-wing aircraft as well as complex phenomena, such as propulsion-airframe interactions. Consequently, conventional aircraft aerodynamic modeling strategies require modification when applied to these unique aircraft. A novel aero-propulsive modeling approach using design of experiments techniques and computational fluid dynamics simulations is postulated for modeling a lift+cruise aircraft configuration. Aero-propulsive models are developed throughout the operational flight envelope to enable continuous flight dynamics simulations from hover through forward flight. The model adequacy is assessed using validation data acquired separately from data used to identify the model and indicates that the models have sufficient predictive capability. Research findings are presented with a discussion of unique lift+cruise aircraft aerodynamic characteristics and practical strategies to inform future aero-propulsive modeling and simulation efforts for eVTOL aircraft.

lift+cruise↗
NASA NTRS2022

Optimal Estimation Framework for Ocean Color Atmospheric Correction and Pixel-level Uncertainty Quantification

Ocean color remote sensing requires compensation for atmospheric scattering and absorption (aerosol, Rayleigh, and trace gases), referred to as atmospheric correction (AC). AC allows inference of parameters such as spectrally resolved remote sensing reflectance ( R rs )(λ) ; sr 1 ) at the ocean surface from the top-of-atmosphere reflectance. Often, the uncertainty of this process is not fully explored. Bayesian inference techniques provide a simultaneous AC and uncertainty assessment via a full posterior distribution of the relevant variables, given the prior distribution of those variables and the radiative transfer (RT) likelihood function. Given uncertainties in the algorithm inputs, the Bayesian framework enables better constraints on the AC process by using the complete spectral information compared to traditional approaches that use only a subset of bands for AC. This paper investigates a Bayesian inference research method (Optimal Estimation, OE) for ocean color AC by simultaneously retrieving atmospheric and ocean properties using all visible and near-infrared spectral bands. The OE algorithm analytically approximates the posterior distribution of parameters based on normality assumptions and provides a potentially viable operational algorithm with a reduced computational expense. We developed a Neural Network (NN) RT forward model look-up-table-based emulator to increase algorithm efficiency further and thus speed up the likelihood computations. We then applied the OE algorithm to synthetic data and observations from the MODerate resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua spacecraft. We compared the R rs )(λ) retrieval and its uncertainty estimates from the OE method with in-situ validation data from the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and Aerosol Robotic Network Ocean Color (AERONET-OC) datasets. The OE algorithm improved R rs )(λ) estimates relative to the NASA standard operational algorithm by improving all statistical metrics at 443, 555, and 667 nm. Unphysical negative R rs )(λ) , which often appear in complex water conditions, was reduced by a factor of 3. The OE-derived pixel-level R rs )(λ) uncertainty estimates were also assessed relative to in-situ data and were shown to have skill.

Atmospheric correction↗
DOE OSTI2026

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Rodriguez, Alex [Argonne National Laboratory (ANL)↗
NASA NTRS2001

Making the EZ Choice

Analytical Mechanics Associates, Inc. (AMA), of Hampton, Virginia, created the EZopt software application through Small Business Innovation Research (SBIR) funding from NASA's Langley Research Center. The new software is a user-friendly tool kit that provides quick and logical solutions to complex optimal control problems. In its most basic form, EZopt converts process data into math equations and then proceeds to utilize those equations to solve problems within control systems. EZopt successfully proved its advantage when applied to short-term mission planning and onboard flight computer implementation. The technology has also solved multiple real-life engineering problems faced in numerous commercial operations. For instance, mechanical engineers use EZopt to solve control problems with robots, while chemical plants implement the application to overcome situations with batch reactors and temperature control. In the emerging field of commercial aerospace, EZopt is able to optimize trajectories for launch vehicles and perform potential space station- keeping tasks. Furthermore, the software also helps control electromagnetic devices in the automotive industry.

Source record↗
NASA NTRS1999

Probabilistic Analysis of Aircraft Gas Turbine Disk Life and Reliability

Two series of low cycle fatigue (LCF) test data for two groups of different aircraft gas turbine engine compressor disk geometries were reanalyzed and compared using Weibull statistics. Both groups of disks were manufactured from titanium (Ti-6Al-4V) alloy. A NASA Glenn Research Center developed probabilistic computer code Probable Cause was used to predict disk life and reliability. A material-life factor A was determined for titanium (Ti-6Al-4V) alloy based upon fatigue disk data and successfully applied to predict the life of the disks as a function of speed. A comparison was made with the currently used life prediction method based upon crack growth rate. Applying an endurance limit to the computer code did not significantly affect the predicted lives under engine operating conditions. Failure location prediction correlates with those experimentally observed in the LCF tests. A reasonable correlation was obtained between the predicted disk lives using the Probable Cause code and a modified crack growth method for life prediction. Both methods slightly overpredict life for one disk group and significantly under predict it for the other.

Melis, Matthew E.↗
NASA NTRS2015

Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator

NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.

Allen, B. Danette↗
DOE OSTI2024

Speeding up and reducing memory usage for scientific machine learning via mixed precision

Scientific machine learning (SciML) has emerged as a versatile approach to address complex computational science and engineering problems. Within this field, physics-informed neural networks (PINNs) and deep operator networks (DeepONets) stand out as the leading techniques for solving partial differential equations by incorporating both physical equations and experimental data. However, training PINNs and DeepONets require significant computational resources, including long computational times and large amounts of memory. In search of computational efficiency, training neural networks using half precision (float16) rather than the conventional single (float32) or double (float64) precision has gained substantial interest, given the inherent benefits of reduced computational time and memory consumed. However, we find that float16 cannot be applied to SciML methods, because of gradient divergence at the start of training, weight updates going to zero, and the inability to converge to a local minima. To overcome these limitations, we explore mixed precision, which is an approach that combines the float16 and float32 numerical formats to reduce memory usage and increase computational speed. Our experiments showcase that mixed precision training not only substantially decreases training times and memory demands but also maintains model accuracy. Here, we also reinforce our empirical observations with a theoretical analysis. The research has broad implications for SciML in various computational applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Overview of aerothermodynamic loads definition study

Over the years, NASA has been conducting the Advanced Earth-to-Orbit (AETO) Propulsion Technology Program to provide the knowledge, understanding, and design methodology that will allow the development of advanced Earth-to-orbit propulsion systems with high performance, extended service life, automated operations, and diagnostics for in-flight health monitoring. The objective of the Aerothermodynamic Loads Definition Study is to develop methods to more accurately predict the operating environment in AETO propulsion systems, such as the Space Shuttle Main Engine (SSME) powerhead. The approach taken consists of 2 parts: to modify, apply, and disseminate existing computational fluid dynamics tools in response to current needs and to develop new technology that will enable more accurate computation of the time averaged and unsteady aerothermodynamic loads in the SSME powerhead. The software tools are detailed. Significant progress was made in the area of turbomachinery, where there is an overlap between the AETO efforts and research in the aeronautical gas turbine field.

Gaugler, Raymond E.↗
NASA NTRS2002

Simulating the Dynamics of Earth's Core: Using NCCS Supercomputers Speeds Calculations

If one wanted to study Earth's core directly, one would have to drill through about 1,800 miles of solid rock to reach liquid core-keeping the tunnel from collapsing under pressures that are more than 1 million atmospheres and then sink an instrument package to the bottom that could operate at 8,000 F with 10,000 tons of force crushing every square inch of its surface. Even then, several of these tunnels would probably be needed to obtain enough data. Faced with difficult or impossible tasks such as these, scientists use other available sources of information - such as seismology, mineralogy, geomagnetism, geodesy, and, above all, physical principles - to derive a model of the core and, study it by running computer simulations. One NASA researcher is doing just that on NCCS computers. Physicist and applied mathematician Weijia Kuang, of the Space Geodesy Branch, and his collaborators at Goddard have what he calls the,"second - ever" working, usable, self-consistent, fully dynamic, three-dimensional geodynamic model (see "The Geodynamic Theory"). Kuang runs his model simulations on the supercomputers at the NCCS. He and Jeremy Bloxham, of Harvard University, developed the original version, written in Fortran 77, in 1996.

Source record↗
NASA NTRS2000

Temperature Distribution Within a Defect-Free Silicon Carbide Diode Predicted by a Computational Model

Most solid-state electronic devices diodes, transistors, and integrated circuits are based on silicon. Although this material works well for many applications, its properties limit its ability to function under extreme high-temperature or high-power operating conditions. Silicon carbide (SiC), with its desirable physical properties, could someday replace silicon for these types of applications. A major roadblock to realizing this potential is the quality of SiC material that can currently be produced. Semiconductors require very uniform, high-quality material, and commercially available SiC tends to suffer from defects in the crystalline structure that have largely been eliminated in silicon. In some power circuits, these defects can focus energy into an extremely small area, leading to overheating that can damage the device. In an effort to better understand the way that these defects affect the electrical performance and reliability of an SiC device in a power circuit, the NASA Glenn Research Center at Lewis Field began an in-house three-dimensional computational modeling effort. The goal is to predict the temperature distributions within a SiC diode structure subjected to the various transient overvoltage breakdown stresses that occur in power management circuits. A commercial computational fluid dynamics computer program (FLUENT-Fluent, Inc., Lebanon, New Hampshire) was used to build a model of a defect-free SiC diode and generate a computational mesh. A typical breakdown power density was applied over 0.5 msec in a heated layer at the junction between the p-type SiC and n-type SiC, and the temperature distribution throughout the diode was then calculated. The peak temperature extracted from the computational model agreed well (within 6 percent) with previous first-order calculations of the maximum expected temperature at the end of the breakdown pulse. This level of agreement is excellent for a model of this type and indicates that three-dimensional computational modeling can provide useful predictions for this class of problem. The model is now being extended to include the effects of crystal defects. The model will provide unique insights into how high the temperature rises in the vicinity of the defects in a diode at various power densities and pulse durations. This information also will help researchers in understanding and designing SiC devices for safe and reliable operation in high-power circuits.

Kuczmarski, Maria A.↗
DOE OSTI2026

Genesis Mission-Enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE)

Argonne National Laboratory is supporting the U.S. Department of Transportation’s (USDOT’s) Bureau of Transportation Statistics (BTS) with collaborative research on development and application of privacy preserving AI frameworks that leverage unmatched AI expertise and secure computing resources made available through the U.S. Genesis Mission1 . This research advances U.S. energy security goals by supporting a safe offshore energy industry with secure, domain-specific AI tools to analyze confidential industry datasets collected by BTS to rapidly improve identification of hazards, precursors, and systemic safety risks in high-risk operational environments. The staged, security-first approach begins with development and testing of Argonne’s Genesis Mission-enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE) framework within Argonne’s accredited secure computing enclave (ABLE) leveraging Argonne’s AI scientific assistant substrate (AISAC). Methods to build synthetic datasets were developed together with BTS for use in preparing synthetic datasets that can be used to validate data containment, governance, and security controls in the ABLE environment. Future research directions would focus on applying the Genesis-SAFE framework to CIPSEA-protected datasets entirely within ABLE to support confidentiality-preserving analysis of safety risks, trends, and contributing factors.

Kim, Hyekyung [Argonne National Laboratory (ANL), ↗
NASA NTRS1997

Improving Vacuum Cleaners

Under a Space Act Agreement between the Kirby company and Lewis Research Center, NASA technology was applied to a commercial vacuum cleaner product line. Kirby engineers were interested in advanced operational concepts, such as particle flow behavior and vibration, critical factors to improve vacuum cleaner performance. An evaluation of the company 1994 home care system, the Kirby G4, led to the refinement of the new G5 and future models. Under the cooperative agreement, Kirby had access to Lewis' holography equipment, which added insight into how long a vacuum cleaner fan would perform, as well as advanced computer software that can simulate the flow of air through fans. The collaboration resulted in several successes including fan blade redesign and continuing dialogue on how to improve air-flow traits in various nozzle designs.

Source record↗
NASA NTRS2010

The Value of Biomedical Simulation Environments to Future Human Space Flight Missions

With the ambitious goals to send manned missions to asteroids and onto Mars, substantial work will be required to ensure the well being of the men and women who will undertake these difficult missions. Unlike current International Space Station or Shuttle missions, astronauts will be required to endure long-term exposure to higher levels of radiation, isolation and reduced gravity. These new operation conditions will pose health risks that are currently not well understood and perhaps unanticipated. Therefore, it is essential to develop and apply advanced tools to predict, assess and mitigate potential hazards to astronaut health. NASA s Digital Astronaut Project (DAP) is working to develop and apply computational models of physiologic response to space flight operation conditions over various time periods and environmental circumstances. The collective application and integration of well vetted models assessing the physiology, biomechanics and anatomy is referred to as the Digital Astronaut. The Digital Astronaut simulation environment will serve as a practical working tool for use by NASA in operational activities such as the prediction of biomedical risks and functional capabilities of astronauts. In additional to space flight operation conditions, DAP s work has direct applicability to terrestrial biomedical research by providing virtual environments for hypothesis testing, experiment design, and to reduce animal/human testing. A practical application of the DA to assess pre and post flight responses to exercise is illustrated and the difficulty in matching true physiological responses is discussed.

Mulugeta, Lealem↗
NASA NTRS1992

HSR combustion analytical research

Increasing the pressure and temperature of the engines of a new generation of supersonic airliners increases the emissions of nitrogen oxides (NO(x)) to a level that would have an adverse impact on the Earth's protective ozone layer. In the process of evolving and implementing low emissions combustor technologies, NASA LeRC has pursued a combustion analysis code program to guide combustor design processes, to identify potential concepts of the greatest promise, and to optimize them at low cost, with short turnaround time. The computational analyses are evaluated at actual engine operating conditions. The approach is to upgrade and apply advanced computer programs for gas turbine applications. Efforts were made in further improving the code capabilities for modeling the physics and the numerical methods of solution. Then test cases and measurements from experiments are used for code validation.

Nguyen, H. Lee↗
NASA NTRS2015

Simulated Tiltrotor Aircraft Operation in Close Proximity to a Building in Wind and Ground-Effect Conditions

A mid-fidelity computational fluid dynamics tool called RotCFD specifically developed to aid in rotorcraft studies has been applied to the study of wake interactions of civiltiltrotor aircraft in the immediate vicinity of buildings, in- and out-of-ground-effect, with and without winds, consistent with notional tiltrotor operations from urban vertiports. Such civil tiltrotor operations from urban vertiports could potentially enable city-center-to-city center commercial transport. However, in order to one day realize such civil tiltrotor operations, though, it is necessary to better understand the wake interaction and interactional aerodynamic operating environment of urban vertiports. In the early 2000s, a series of 7-by-10 Ft. wind tunnel tests were conducted at NASA Ames Research Center that began to explore some of these civil tiltrotor and vertiport wake interactioninteractional aerodynamics issues. This study seeks to validate computation fluid dynamic predictions against these early wind tunnel experimental results and, thereby, continue exploration of this important research area.

Rotorcraft↗
NASA NTRS2011

Analysis of Exhaust Plume Effects on Sonic Boom for a 59-Degree Wing Body Model

Reducing or eliminating the operational restrictions of supersonic aircraft over populated areas has led to extensive research at NASA. Restrictions are due to the disturbance of the sonic boom, caused by the coalescence of shock waves formed off the aircraft. Recent work has been performed to reduce the magnitude of the sonic boom N-wave generated by airplane components with focus on shock waves caused by the exhaust nozzle plume. Previous Computational Fluid Dynamics (CFD) analyses showed how the shock wave formed at the nozzle lip interacted with the nozzle boat-tail expansion wave. The nozzle lip shock moved with increasing nozzle pressure ratio (NPR) and reduced the nozzle boat-tail expansion. Lip shock movement caused a favorable change in the observed pressure signature. These results were applied to a simplified supersonic vehicle geometry with no inlets and no tail, in which the goal was to demonstrate how under-expanded nozzle operation reduced the sonic boom signature by twelve percent. A secondary goal was to demonstrate the use of the Cart3D inviscid code for off-body pressure signatures including the nozzle plume effect.

Castner, Raymond S.↗