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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Methodology for simulation of unsteady flows to determine the time-dependent interference between stationary and moving boundaries

A new methodology is developed to simulate unsteady flows about prescribed and aerodynamically determined moving boundary problems. The method couples the fluid dynamics and rigid-body dynamics equations to capture the time-dependent interference between stationary and moving boundaries. The unsteady, compressible, inviscid (Euler) equations are solved on dynamic, unstructured grids by an explicit, finite-volume, upwind method. For efficiency, the grid adaptation is performed within a window around the moving object. The Eulerian equations of the rigid-body dynamics are solved by a Runge-Kutta method in a non-inertial frame of reference. The two-dimensional flow solver is validated by computing the flow past a sinusoidally-pitching airfoil and comparing these results with the experimental data. The overall methodology is used for two two-dimensional examples: the flow past an airfoil which is performing a three-degrees-of-freedom motion in a transonic freestream, and the free-fall of a store after separation from a wing-section. Then the unstructured mesh methodology is extended to three-dimensions to simulate unsteady flow past bodies in relative motion, where the trajectory is determined from the instantaneous aerodynamics. The flow solver and the adaptation scheme in three dimensions are validated by simulating the transonic, unsteady flow around a wing undergoing a forced, periodic, pitching motion, and comparing the results with the experimental data. To validate the trajectory code, the six-degrees-of-freedom motion of a store separating from a wing was computed using the experimentally determined force and moment fields, then comparing with an independently generated trajectory. Finally, the overall methodology was demonstrated by simulating the unsteady flowfield and the trajectory of a store dropped from a wing. The methodology, its computational cost notwithstanding, has proven to be accurate, automated, easy for dynamic gridding, and relatively efficient for the required man-hours.

Singh, Kamakhya Prasad↗
DOE OSTI2024

The quality/cosmology tension for a post-inflation QCD axion

Abstract It is difficult to construct a post-inflation QCD axion model that solves the axion quality problem (and hence the Strong CP problem) without introducing a cosmological disaster. In a post-inflation axion model, the axion field value is randomized during the Peccei-Quinn phase transition, and axion domain walls form at the QCD phase transition. We emphasize that the gauge equivalence of all minima of the axion potential (i.e., domain wall number equals one) is insufficient to solve the cosmological domain wall problem. The axion string on which a domain wall ends must exist as an individual object (as opposed to a multi-string state), and it must be produced in the early universe. These conditions are often not satisfied in concrete models. Post-inflation axion models also face a potential problem from fractionally charged relics; solving this problem often leads to low-energy Landau poles for Standard Model gauge couplings, reintroducing the quality problem. We study several examples, finding that models that solve the quality problem face cosmological problems, and vice versa. This is not a no-go theorem; nonetheless, we argue that it is much more difficult than generally appreciated to find a viable post-inflation QCD axion model. Successful examples may have a nonstandard cosmological history (e.g., multiple types of cosmic axion strings of different tensions), undermining the widespread expectation that the post-inflation QCD axion scenario predicts a unique mass for axion dark matter.

Physics↗
DOE OSTI2026

Neural-Network Inverse Design of SRF Cavities and Transmons for Bosonic Quantum Computation

Three-dimensional superconducting radio-frequency (SRF) cavities provide exceptionally long-lived electromagnetic modes and, when coupled to nonlinear elements such as transmon qubits, become promising architectures for bosonic quantum information processing. The inverse design of such systems, i.e., recovering device geometries that produce specified electromagnetic and coupling targets, is generally a one-to-many problem. The qubit-cavity coupling strength depends sensitively on both the transmon geometry and its position within the cavity's electromagnetic field. As these systems scale up and their design parameter spaces grow, the cost of conventional iterative simulation becomes prohibitive. We present two deep neural network (DNN) approaches that address this inverse-design problem at complementary levels of the design stack. The first proposes SRF cavity geometries that produce target cavity observables. The second proposes transmon qubit designs that produce target qubit-cavity parameters - the coupling rate, qubit frequency, and anharmonicity $(g, ν_q, α)$. The recovered candidate designs match the targets to within ~5% (cavity) and ~2% (transmon), confirmed by end-to-end re-simulation. Both approaches map desired device behavior directly to candidate designs, a fast alternative to the iterative simulation studies usually required.

Yaker, Joseph [Fermilab; Northwestern U.]↗
DOE OSTI2025

Application of physics-informed neural networks (PINNs) solution to coupled thermal and hydraulic processes in silty sands

Abstract The accurate modeling of water and heat transport in soils is crucial for both geo-environmental and geothermal engineering. Traditional modeling methods are problematic because they require well-defined boundaries and initial conditions. Recently, physics-informed neural networks (PINNs), which incorporate partial differential equations (PDEs) to solve forward and inverse problems, have attracted increasing attention in machine learning research. In this study, we applied PINNs to tackle hydraulic and thermal transport coupling forward problems in silty sands. A fully connected deep neural network was utilized for training. This neural network model leverages automatic differentiation to apply the governing equations as constraints, based on the mathematical approximations established by the neural network itself. We conducted forward problems and compared the solutions derived from PINNs with those from Finite Element Method (FEM) simulations. The forward problem results demonstrate the PINNs model’s capability in predicting hydraulic transport, heat transport, and thermal–hydraulic coupling in silty sands under various boundary conditions. The PINNs exhibited great performance in simulating the thermal–hydraulic coupling problem. The accuracy of the PINNs solutions shows its potential for simulation in geotechnical engineering.

Feng, Yuan↗
NASA NTRS2006

Challenges for Future UV Imaging of the Earth's Ionosphere and High Latitude Regions

Large scale imaging of Geospace has played a significant role in the recent advances in the comprehension of the coupled Solar-Terrestrial System. The Earth's ionospheric far ultraviolet emissions provide a rich tapestry of observations that play a key role in sorting out the dominant mechanisms and phenomena associated with the coupling of the ionosphere and magnetosphere (MI). The MI coupling is an integral part of the Solar-Terrestrial and as such, future observations in this region should focus on understanding the coupling and the impact of solar variability. This talk will focus on the outstanding problems associated with the coupled Solar-Terrestrial system that can be best addressed using far ultraviolet imaging of the Earthls ionosphere. Challenges of global scale imaging and high-resolution imaging will be discussed and how these are driven by unresolved compelling science questions of magnetospheric configuration, and auroral dynamics.

Spann, James↗
NASA NTRS1980

An investigation of dynamic-analysis methods for variable-geometry structures

Selected space structure configurations were reviewed in order to define dynamic analysis problems associated with variable geometry. The dynamics of a beam being constructed from a flexible base and the relocation of the completed beam by rotating the remote manipulator system about the shoulder joint were selected. Equations of motion were formulated in physical coordinates for both of these problems, and FORTRAN programs were developed to generate solutions by numerically integrating the equations. These solutions served as a standard of comparison to gauge the accuracy of approximate solution techniques that were developed and studied. Good control was achieved in both problems. Unstable control system coupling with the system flexibility did not occur. An approximate method was developed for each problem to enable the analyst to investigate variable geometry effects during a short time span using standard fixed geometry programs such as NASTRAN. The average angle and average length techniques are discussed.

Austin, F.↗
NASA NTRSDate not supplied

Understanding Resilience Optimization Architectures With an Optimization Problem Repository

Optimizing a system’s resilience can be challenging, especially when it involves considering both the inherent resilience of a robust design and the active resilience of a health management system to a set of computationally-expensive hazard simulations. While prior work has developed specialized architectures to effectively and efficiently solve combined design and resilience optimization problems, the comparison of these architectures has been limited to a single case study. To further study resilience optimization formulations, this work develops a problem repository which includes previously-developed resilience optimization problems and additional problems presented in this work: a notional system resilience model, a pandemic response model, and a cooling tank hazard prevention model. This work then uses models in the repository at large to understand the characteristics of resilience optimization problems and study the applicability of optimization architectures and decomposition strategies. Based on the comparisons in the repository, applying an optimization architecture effectively requires understanding the alignment and coupling relationships between the design and resilience models, as well as the efficiency characteristics of the algorithms. While alignment determines the necessity of a surrogate of resilience cost in the upper-level design problem, coupling determines the overall applicability of a sequential, alternating, or bilevel structure. Additionally, the application of decomposition strategies is dependent on there being limited interactions between variable sets, which often does not hold when a resilience policy is parameterized in terms of actions to take in hazardous model states rather than specific given scenarios.

Resilience↗
NASA NTRS1984

A unified theory of electrodynamic coupling in coronal magnetic loops - The coronal heating problem

The coronal heating problem is studied, and it is demonstrated that Ionson's (1982) LRC approach results in a unified theory of coronal heating which unveils a variety of new heating mechanisms and which links together previously proposed mechanisms. Ionson's LRC equation is rederived, focusing on various aspects that were not clarified in the original article and incorporating new processes that were neglected. A parameterized heating rate is obtained. It is shown that Alfvenic surface wave heating, stochastic magnetic pumping, resonant electrodynamic heating, and dynamical dissipation emerge as special cases of a much more general formalism. This generalized theory is applied to solar coronal loops and it is found that active region and large scale loops are underdamped systems. Young active region loops and (possibly) bright points are found to be overdamped systems.

Ionson, J. A.↗
NASA NTRS1987

Development of a coupled expert system for the spacecraft attitude control problem

A majority of the current expert systems focus on the symbolic-oriented logic and inference mechanisms of artificial intelligence (AI). Common rule-based systems employ empirical associations and are not well suited to deal with problems often arising in engineering. Described is a prototype expert system which combines both symbolic and numeric computing. The expert system's configuration is presented and its application to a spacecraft attitude control problem is discussed.

Kawamura, K.↗
NASA NTRS1982

Input impedance and mutual coupling of rectangular microstrip antennas

A moment method solution to the problem of input impedance and mutual coupling of rectangular microstrip antenna elements is presented. The formulation uses the grounded dielectric slab Green's function to account rigorously for the presence of the substrate and surface waves. Both entire basis (EB) and piecewise sinusoidal (PWS) expansion modes are used, and their relative advantages are noted. Calculations of input impedance and mutual coupling are compared with measured data and other calculations.

Pozar, D. M.↗
NASA NTRS1980

Distributed parameter system coupled ARMA expansion identification and adaptive parallel IIR filtering - A unified problem statement

A novel interconnection of distributed parameter system (DPS) identification and adaptive filtering is presented, which culminates in a common statement of coupled autoregressive, moving-average expansion or parallel infinite impulse response configuration adaptive parameterization. The common restricted complexity filter objectives are seen as similar to the reduced-order requirements of the DPS expansion description. The interconnection presents the possibility of an exchange of problem formulations and solution approaches not yet easily addressed in the common finite dimensional lumped-parameter system context. It is concluded that the shared problems raised are nevertheless many and difficult.

Johnson, C. R., Jr.↗
NASA NTRS2004

Sensitivity Equation Derivation for Transient Heat Transfer Problems

The focus of the paper is on the derivation of sensitivity equations for transient heat transfer problems modeled by different discretization processes. Two examples will be used in this study to facilitate the discussion. The first example is a coupled, transient heat transfer problem that simulates the press molding process in fabrication of composite laminates. These state equations are discretized into standard h-version finite elements and solved by a multiple step, predictor-corrector scheme. The sensitivity analysis results based upon the direct and adjoint variable approaches will be presented. The second example is a nonlinear transient heat transfer problem solved by a p-version time-discontinuous Galerkin's Method. The resulting matrix equation of the state equation is simply in the form of Ax = b, representing a single step, time marching scheme. A direct differentiation approach will be used to compute the thermal sensitivities of a sample 2D problem.

Hou, Gene↗
NASA NTRS1982

Solidification of a binary mixture

The time dependent concentration and temperature profiles of a finite layer of a binary mixture are investigated during solidification. The coupled time dependent Stefan problem is solved numerically using an implicit finite differencing algorithm with the method of lines. Specifically, the temporal operator is approximated via an implicit finite difference operator resulting in a coupled set of ordinary differential equations for the spatial distribution of the temperature and concentration for each time. Since the resulting differential equations set form a boundary value problem with matching conditions at an unknown spatial point, the method of invariant imbedding is used for its solution.

Antar, B. N.↗
NASA NTRS1987

Thermoplasticity of coupled bodies in the case of stress-dependent heat transfer

The problem of the thermal stresses in coupled deformable bodies is formulated for the case where the heat-transfer coefficient at the common boundary depends on the stress-strain state of the bodies (e.g., is a function of the normal pressure at the common boundary). Several one-dimensional problems are solved in this formulation. Among these problems is the determination of the thermal stresses in an n-layer plate and in a two-layer cylinder.

Kilikovskaya, O. A.↗
NASA NTRS1998

Design Process for High Speed Civil Transport Aircraft Improved by Neural Network and Regression Methods

A key challenge in designing the new High Speed Civil Transport (HSCT) aircraft is determining a good match between the airframe and engine. Multidisciplinary design optimization can be used to solve the problem by adjusting parameters of both the engine and the airframe. Earlier, an example problem was presented of an HSCT aircraft with four mixed-flow turbofan engines and a baseline mission to carry 305 passengers 5000 nautical miles at a cruise speed of Mach 2.4. The problem was solved by coupling NASA Lewis Research Center's design optimization testbed (COMETBOARDS) with NASA Langley Research Center's Flight Optimization System (FLOPS). The computing time expended in solving the problem was substantial, and the instability of the FLOPS analyzer at certain design points caused difficulties. In an attempt to alleviate both of these limitations, we explored the use of two approximation concepts in the design optimization process. The two concepts, which are based on neural network and linear regression approximation, provide the reanalysis capability and design sensitivity analysis information required for the optimization process. The HSCT aircraft optimization problem was solved by using three alternate approaches; that is, the original FLOPS analyzer and two approximate (derived) analyzers. The approximate analyzers were calibrated and used in three different ranges of the design variables; narrow (interpolated), standard, and wide (extrapolated).

Hopkins, Dale A.↗
NASA NTRS2018

A Realization of Bias Correction Method in the GMAO Coupled System

Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of the climate system. The cold or warm sea surface temperature (SST) bias in the tropics is still a problem common to most coupled ocean atmosphere general circulation models (CGCMs). The precipitation biases in CGCMs are also accompanied by SST and surface wind biases. The deficiencies and biases over the equatorial oceans through their influence on the Walker circulation likely contribute the precipitation biases over land surfaces. In this study, we introduce an approach in the CGCM modeling to correct model biases. This approach utilizes the history of the model's short-term forecasting errors and their seasonal dependence to modify model's tendency term and to minimize its climate drift. The study shows that such an approach removes most of model climate biases. A number of other aspects of the model simulation (e.g. extratropical transient activities) are also improved considerably due to the imposed pre-processed initial 3-hour model drift corrections. Because many regional biases in the GEOS-5 CGCM are common amongst other current models, our approaches and findings are applicable to these other models as well.

Chang, Yehui↗
NASA NTRS1977

Charge-coupled differential amplifier

Device solves problem of differential voltage gain in sampled-data metal-oxide semiconductor, producing gain at any frequency compatible with CCD operation, with low noise, low power, good linearity, and high stability.

Hewes, C. R.↗