SEARCH · Search NASA

Results for “Computing methodologies”

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.

SourceResearch connectionFrom yearThrough year

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

At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

NASA NTRS2019

High-Fidelity Multidisciplinary Sensitivity Analysis Framework for Multipoint Rotorcraft Optimization

A multidisciplinary, gradient-based sensitivity-analysis methodology is evaluated for optimization of rotorcraft configurations. The tightly coupled discipline models include physics-based fluid dynamics and rotorcraft comprehensive analysis. A discretely-consistent adjoint method accounts for sensitivities of the unsteady flow and unstructured, dynamic, over set grids, while sensitivities of structural responses to aerodynamic loads are computed using a complex-variable method. The methodology is applied to optimize the shape of UH-60A Blackhawk helicopter blades for hover and forward flight conditions. The objective of the multipoint design is to simultaneously increase the rotorcraft figure of merit in a hover flight and reduce the rotor power in a forward flight. Trimmed loose-coupling solutions for the baseline configuration are used to initiate the tight-coupling multidisciplinary analysis. Target thrust and rolling and pitching moments are enforced as optimization constraints. The optimized configuration improves the optimization metrics at both design points. The improved performance and all constraints are maintained over many revolutions beyond the optimization interval, satisfying the required flight conditions. Computational cost of the optimization cycle is assessed in a high-performance computing environment and found affordable for design of rotorcraft in general level-flight conditions.

Wang, Li↗

DOE OSTI2025

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗

DOE OSTI2024

Noise reduction of stochastic density functional theory for metals

Density Functional Theory (DFT) has become a cornerstone in the modeling of metals. However, accurately simulating metals, particularly under extreme conditions, presents two significant challenges. First, simulating complex metallic systems at low electron temperatures is difficult due to their highly delocalized density matrix. Second, modeling metallic warm-dense materials at very high electron temperatures is challenging because it requires the computation of a large number of partially occupied orbitals. This study demonstrates that both challenges can be effectively addressed using the latest advances in linear-scaling stochastic DFT methodologies. Despite the inherent introduction of noise into all computed properties by stochastic DFT, this research evaluates the efficacy of various noise reduction techniques under different thermal conditions. Our observations indicate that the effectiveness of noise reduction strategies varies significantly with the electron temperature. Furthermore, we provide evidence that the computational cost of stochastic DFT methods scales linearly with system size for metal systems, regardless of the electron temperature regime.

Chemistry↗

NASA NTRSDate not supplied

Validation of Cryogenic Propellant Tank Self-Pressurization by Leveraging Reduced Order Modeling within Computational Fluid Dynamics Simulation

Validation of cryogenic propellant tank self-pressurization was performed using a hybrid Computational Fluid Dynamics (CFD) and reduced order modeling methodology. Data from a liquid hydrogen ground test conducted at the K-site facility at the National Aeronautics and Space Administration (NASA) Glenn Research Center was used for the validation effort. Liquid phase dynamics were explicitly resolved with a CFD tool. Vapor phase dynamics were modeled as a point mass that communicated heat from the tank wall to the liquid phase via a boundary condition used at the gas-liquid interface. The method proved to be more accurate, robust, and efficient than explicit resolution of the dynamics using a standard Volume of Fluid (VOF) methodology. The subject pressurization process was found to be heavily dependent upon both the relatively high liquid temperature gradient near the gas-liquid interface and the natural convection flow path. Modeling the gas-liquid interface as an immovable surface eliminated temperature gradient destroying gas-liquid interface velocities observed in VOF simulations, and correspondingly enabled more rapid simulation since interface advection was not allowed. The single phase computational domain also facilitated the ability to demonstrate spatial resolution convergence of natural convection cells within the liquid which significantly impacted the tank pressurization rate. This work was used to demonstrate the critical physics for tank self-pressurization and numerical methodologies that may be used to best resolve those physics. The findings informed development and operation of production level CFD tools used in the Fluid Dynamics Branch at NASA Marshall Space Flight Center.

J. M. Brodnick↗

NASA NTRS1989

Probabilistic structural analysis: Introductory remarks

The development of probabilistic structural analysis methodology consists of the following program elements: (1) composite load spectra models, (2) computational probabilistic structural analysis methods, and (3) probabilistic constitutive relationships. The development of the probabilistic structural analysis methodology is a joint program of NASA Lewis in-house and sponsored research. The objective of this session is to illustrate recent progress on the application of this methodology to determine the reliability of structural components for rocket propulsion systems. The session contains descriptions of and progress reports on the following specific activities: (1) The NESSUS computer code, (2) approximate methods, (3) advanced methods, (4) composite load spectra applications, (5) probabilistic fracture mechanisms, and (6) probability of failure and risk analysis. Collectively, the progress to date demonstrates that the structural durability of hot engine structural components can be effectively evaluated in a formal probabilistic/reliability framework.

Chamis, Christos C.↗

NASA NTRS1981

A programing system for research and applications in structural optimization

The paper describes a computer programming system designed to be used for methodology research as well as applications in structural optimization. The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities existing in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of contraints and design variables. Features shown in numerical examples include: (1) variability of structural layout and overall shape geometry, (2) static strength and stiffness constraints, (3) local buckling failure, and (4) vibration constraints. The paper concludes with a review of the further development trends of this programing system.

Sobieszczanski-Sobieski, J.↗

NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗

NASA NTRS1990

Airframe structural optimization for maximum fatigue life

A methodology is outlined for optimization of airframe structures under dynamic constraints to maximize service life of specified fatigue-critical components. For practical airframe structures, this methodology describes the development of sensitivity analysis and computational procedures for constraints on the steady-state dynamic response displacements and stresses. Strain energy consideration is used for selection of structural members for modification. Development of a design model and its relation to an analysis model, as well as ways to reduce the dimensionality of the problem via approximation concepts, are described. This methodology is demonstrated using an elastic stick model for the MH-53J helicopter to show service life improvements of the hinge fold region.

D. P. Schrage↗

DOE OSTI2026

Design, Processing, and Properties of WTaCrV-Hf Multi-principal Element Alloys

Refractory multi-principal element alloys are candidates for high-temperature structural components due, in part, to their high strength and high melting points. Single-phase materials are initially preferred for isotropic material properties as a function of time and temperature in service conditions. This work outlines a computational rank-ordering and experimental validation methodology for single-phase body-centered-cubic phase stability in WTaCrV-Hf alloys using order–disorder transition temperature. Eight compositions were fabricated by arc-melting and heat-treated at 1400 °C for 24 hrs. X-ray diffraction, energy-dispersive x-ray spectroscopy, and Vickers hardness testing showed alloys with order–disorder transition temperatures below 600 °C formed a single-phase body-centered-cubic structure during solidification and remained single-phase after heat-treatment. The sample possessing the lowest order–disorder transition temperature exhibited slip traces suggestive of room-temperature plastic deformation under Vickers indentation, with both heat-treated single-phase samples exhibiting hardnesses over 800 HV with little cracking compared to tungsten. These results establish order–disorder transition temperature as a viable predictive parameter for multi-principal element alloy phase stability. The methodology outlined in this work provides a framework for future design, fabrication, and characterization of high-temperature structural multi-principal element alloys.

CALPHAD↗

DOE OSTI2026

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗

NASA NTRS1973

Computer software documentation

A tutorial in the documentation of computer software is presented. It presents a methodology for achieving an adequate level of documentation as a natural outgrowth of the total programming effort commencing with the initial problem statement and definition and terminating with the final verification of code. It discusses the content of adequate documentation, the necessity for such documentation and the problems impeding achievement of adequate documentation.

Comella, P. A.↗

NASA NTRS1983

The Hierarchical Specification and Mechanical Verification of the SIFT Design

The formal specification and proof methodology employed to demonstrate that the SIFT computer system meets its requirements are described. The hierarchy of design specifications is shown, from very abstract descriptions of system function down to the implementation. The most abstract design specifications are simple and easy to understand, almost all details of the realization were abstracted out, and are used to ensure that the system functions reliably and as intended. A succession of lower level specifications refines these specifications into more detailed, and more complex, views of the system design, culminating in the Pascal implementation. The section describes the rigorous mechanical proof that the abstract specifications are satisfied by the actual implementation.

Source record↗

NASA NTRS1985

Vibration control experiment design for the 15-m hoop/column antenna

A test program is designed for a ground-based vibration control experiment utilizing as the test article the 15-M Hoop/Column Antenna. Overall objectives of the designed ground-based test program include: (1) the validation of large space structure (LSS) control systemm techniques; (2) the validation of LSS parameter identification techniques: (3) the evaluation of actuator of actuator and sensor placement methodology; and (3) the validation of LSS computer models. Critical concerns in LSS Controls and Dynamics are: low frequency vibrational modes, close modal spacing, parameter uncertainties, controller software limitations, nonlinearities and coupling of modes through damping. Analytical results are presented which include compensator designs for varying compensator order.

Ham, F. M.↗

NASA NTRS1985

Heat transfer in aeropropulsion systems

Aeropropulsion heat transfer is reviewed. A research methodology based on a growing synergism between computations and experiments is examined. The aeropropulsion heat transfer arena is identified as high Reynolds number forced convection in a highly disturbed environment subject to strong gradients, body forces, abrupt geometry changes and high three dimensionality - all in an unsteady flow field. Numerous examples based on heat transfer to the aircraft gas turbine blade are presented to illustrate the types of heat transfer problems which are generic to aeropropulsion systems. The research focus of the near future in aeropropulsion heat transfer is projected.

Simoneau, R. J.↗

NASA NTRS1987

A technique for evaluating the application of the pin-level stuck-at fault model to VLSI circuits

Accurate fault models are required to conduct the experiments defined in validation methodologies for highly reliable fault-tolerant computers (e.g., computers with a probability of failure of 10 to the -9 for a 10-hour mission). Described is a technique by which a researcher can evaluate the capability of the pin-level stuck-at fault model to simulate true error behavior symptoms in very large scale integrated (VLSI) digital circuits. The technique is based on a statistical comparison of the error behavior resulting from faults applied at the pin-level of and internal to a VLSI circuit. As an example of an application of the technique, the error behavior of a microprocessor simulation subjected to internal stuck-at faults is compared with the error behavior which results from pin-level stuck-at faults. The error behavior is characterized by the time between errors and the duration of errors. Based on this example data, the pin-level stuck-at fault model is found to deliver less than ideal performance. However, with respect to the class of faults which cause a system crash, the pin-level, stuck-at fault model is found to provide a good modeling capability.

Palumbo, Daniel L.↗

NASA NTRS1988

Fully-coupled analysis of jet mixing problems. Three-dimensional PNS model, SCIP3D

Numerical procedures formulated for the analysis of 3D jet mixing problems, as incorporated in the computer model, SCIP3D, are described. The overall methodology closely parallels that developed in the earlier 2D axisymmetric jet mixing model, SCIPVIS. SCIP3D integrates the 3D parabolized Navier-Stokes (PNS) jet mixing equations, cast in mapped cartesian or cylindrical coordinates, employing the explicit MacCormack Algorithm. A pressure split variant of this algorithm is employed in subsonic regions with a sublayer approximation utilized for treating the streamwise pressure component. SCIP3D contains both the ks and kW turbulence models, and employs a two component mixture approach to treat jet exhausts of arbitrary composition. Specialized grid procedures are used to adjust the grid growth in accordance with the growth of the jet, including a hybrid cartesian/cylindrical grid procedure for rectangular jets which moves the hybrid coordinate origin towards the flow origin as the jet transitions from a rectangular to circular shape. Numerous calculations are presented for rectangular mixing problems, as well as for a variety of basic unit problems exhibiting overall capabilities of SCIP3D.

Wolf, D. E.↗

NASA NTRS1989

Mars Rover imaging systems and directional filtering

Computer literature searches were carried out at Duke University and NASA Langley Research Center. The purpose is to enhance personal knowledge based on the technical problems of pattern recognition and image understanding which must be solved for the Mars Rover and Sample Return Mission. Intensive study effort of a large collection of relevant literature resulted in a compilation of all important documents in one place. Furthermore, the documents are being classified into: Mars Rover; computer vision (theory); imaging systems; pattern recognition methodologies; and other smart techniques (AI, neural networks, fuzzy logic, etc).

Wang, Paul P.↗

NASA NTRS1991

Computer code for single-point thermodynamic analysis of hydrogen/oxygen expander-cycle rocket engines

This analysis and this computer code apply to full, split, and dual expander cycles. Heat regeneration from the turbine exhaust to the pump exhaust is allowed. The combustion process is modeled as one of chemical equilibrium in an infinite-area or a finite-area combustor. Gas composition in the nozzle may be either equilibrium or frozen during expansion. This report, which serves as a users guide for the computer code, describes the system, the analysis methodology, and the program input and output. Sample calculations are included to show effects of key variables such as nozzle area ratio and oxidizer-to-fuel mass ratio.

Glassman, Arthur J.↗