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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

An airfoil design method for viscous flows

An airfoil design procedure is described that has been incorporated into an existing two-dimensional Navier-Stokes airfoil analysis method. The resulting design method, an iterative procedure based on a residual-correction algorithm, permits the automated design of airfoil sections with prescribed surface pressure distributions. This paper describes the inverse design method and the technique used to specify target pressure distributions. An example airfoil design problem is described to demonstrate application of the inverse design procedure. It shows that this inverse design method develops useful airfoil configurations with a reasonable expenditure of computer resources.

Malone, J. B.↗
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.]↗
NASA NTRS2007

Effect of Ducting on Radio Occultation Measurements: An Assessment Based on High-Resolution Radiosonde Soundings

Recent studies have shown that the presence of elevated ducts in the lower atmosphere has an adverse effect on the inversion of GPS radio occultation data. The problem arises because the microwave refractivity within and below an elevated duct is no longer uniquely determined by the bending angle profile. Applying Abel inversion without a priori knowledge of the duct will introduce a negative bias in the retrieved refractivity profile within and below the duct. In this work, high vertical resolution radiosonde data are used to give a quantitative assessment of the characteristics and effects of ducts, including their frequency of occurrences, heights, and thicknesses at different latitudes and seasons. The negative bias from the Abel-retrieved refractivity profiles resulting from these ducts is also computed. The results give a strong indication that ducting in the lower troposphere is a frequent phenomenon over the tropics and midlatitudes. The ducts are shown to be predominantly caused by sharp changes in the vertical structure of water vapor. The majority of the ducts are found to be below 2 km, with a median duct layer thickness of about 100 m. The negative refractivity bias is shown to be largest below 2 km, with a median value of about 0.5-1% in the tropics and 0.2-0.5% in midlatitudes. The bias is about a factor of 2-3 smaller between 2 to 3 km and is negligible above 4 km.

signals↗
DOE OSTI2022

A combined experimental and numerical approach that eliminates the non-uniqueness associated with the Johnson-Cook parameters obtained using inverse methods

Abstract Johnson-Cook constitutive model is a commonly used material model for machining simulations. The model includes five parameters that capture the initial yield stress, strain-hardening, strain-rate hardening, and thermal softening behavior of the material. These parameters are difficult to determine using experiments since the conditions observed during machining (such as high strain-rates of the order of $$10^5$$ 10 5 /sec - $$10^6$$ 10 6 /sec) are challenging to recreate in the laboratory. To address this problem, several researchers have recently proposed inverse approaches where a combination of experiments and analytical models are used to predict the Johnson-Cook parameters. The errors between the measured cutting forces, chip thicknesses and temperatures and those predicted by analytical models are minimized and the parameters are determined. In this work, it is shown that only two of the five Johnson-Cook parameters can be determined uniquely using inverse approaches. Two different algorithms, namely, Adaptive Memory Programming for Global Optimization (AMPGO) and Particle Swarm Optimization (PSO), are used for this purpose. The extended Oxley’s model is used as the analytical tool for optimization. For determining a parameter’s value, a large range for each parameter is provided as an input to the algorithms. The algorithms converge to several different sets of values for the five Johnson-Cook parameters when all the five parameters are considered as unknown in the optimization algorithm. All of these sets, however, yield the same chip shape and cutting forces in FEM simulations. Further analyses show that only the strain-rate and thermal softening parameters can be determined uniquely and the three parameters present in the strain-hardening term of the Johnson-Cook model cannot be determined uniquely using the inverse method. A combined experimental and numerical approach is proposed to eliminate this determine all parameters uniquely.

42 ENGINEERING↗
DOE OSTI2022

Physics constrained learning for data-driven inverse modeling from sparse observations

Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that measures the discrepancy between predictions and observations in some chosen norm. This loss function often includes the PDE constraints as a penalty term when only sparse observations are available. As a result, the PDE is only satisfied approximately by the solution. However, the penalty term typically slows down the convergence of the optimizer for stiff problems. We present a new approach that trains the embedded DNNs while numerically satisfying the PDE constraints. We develop an algorithm that enables differentiating both explicit and implicit numerical solvers in reverse-mode automatic differentiation. This allows the gradients of the DNNs and the PDE solvers to be computed in a unified framework. We demonstrate that our approach enjoys faster convergence and better stability in relatively stiff problems compared to the penalty method. Furthermore, our approach allows for the potential to solve and accelerate a wide range of data-driven inverse modeling, where the physical constraints are described by PDEs and need to be satisfied accurately.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Planning collision free paths for two cooperating robots using a divide-and-conquer C-space traversal heuristic

A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.

Weaver, Johnathan M.↗
NASA NTRS1976

The quarter-point quadratic isoparametric element as a singular element for crack problems

The quadratic isoparametric elements which embody the inverse square root singularity are used for calculating the stress intensity factors at tips of cracks. The strain singularity at a point or an edge is obtained in a simple manner by placing the mid-side nodes at quarter points in the vicinity of the crack tip or an edge. These elements are implemented in NASTRAN as dummy elements. The method eliminates the use of special crack tip elements and in addition, these elements satisfy the constant strain and rigid body modes required for convergence.

Hussain, M. A.↗
DOE OSTI2020

Detecting an underground tunnel by applying joint traveltime and waveform inversion

Underground tunnel and void detection is a challenging geophysical problem, and many methods have been proposed. Seismic techniques are promising because of the large seismic velocity contrasts between the air-filled void and the surrounding sediment and concrete. We apply a joint seismic traveltime and waveform inversion method to image a buried tunnel with concrete walls and a void space inside. The joint inversion images the top of the concrete tunnel as a high-velocity anomaly and the void space as a low-velocity anomaly. The location of the velocity anomalies predicted by the method agrees with the known location of the tunnel. As a comparison, the stand-alone full waveform inversion is also applied to the data. The first-arrival traveltime tomography shows weak nonlinearity but fails to image the hidden low-velocity layer. Full waveform inversion is able to image complex near-surface structures, but fitting waveforms may not honor the traveltime fit, especially when the data contain noise. Synthetic and real data tests show that the joint inversion method retains the advantages of both traveltime inversion and full waveform inversion and overcomes their respective drawbacks at the same time. The field example shows the joint inversion provides a better reconstruction of the high-velocity feature representing the top of the concrete wall in terms of its magnitude and location.

58 GEOSCIENCES↗
NASA NTRS1987

Measurement from satellites of land surface parameters and fluxes in the thermal infrared bands: Problems and methods

The main problems arising in the elaboration of accurate and reliable algorithms for extracting land surface parameters and flux from their measured radiances are discussed. Methods of solution in the thermal infrared spectral domain are described. Particular interest is given to the inversion of thermal models and to the problems resulting from the heterogeneity of the observed surfaces.

Becker, F.↗
NASA NTRS1991

Inversion techniques for recovering two-dimensional distributions of auroral emission rates from tomographic rocket photometer measurements

This paper demonstrates how the spatial distribution of optical emission rates within an auroral arc may be recovered from rocket photometer measurements made in a tomographic spin scan mode. The tomographic inversion procedures required to recover this information and the implementation of two inversion algorithms that are particularly well suited for dealing with the problem of noise in the observational data are described. The performance of the inversion algorithms and the limitations of the rocket tomography technique are assessed using various sets of simulated rocket measurements that were generated from 'known' auroral emission-rate distributions. The simulations are used to investigate how the quality of the tomographic recovery may be influenced by various factors such as noise in the data, rocket penetration of the auroral form, background sources of emission, smearing due to the photometer field of view, and temporal variations in the auroral form.

Mcdade, Ian. C.↗
DOE OSTI2022

Active meta-learning for predicting and selecting perovskite crystallization experiments

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. Here in this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Memristive linear algebra

The advent of memristive devices offers a promising avenue for efficient and scalable analog computing, particularly for linear algebra operations essential in various scientific and engineering applications. This paper investigates the potential of memristive crossbars in implementing matrix inversion algorithms. We explore both static and dynamic approaches, emphasizing the advantages of analog and in-memory computing for matrix operations beyond multiplication. In particular, we demonstrate that the electrical properties of memristive crossbars uniquely suit them for the evolution of a family of matrix exponentials, which can be exploited for the efficient computation of matrix inverses and online solutions for linear problems. Our results demonstrate that memristive arrays can reduce computational complexity. We also study power consumption and show a tradeoff between precision and energy. Furthermore, we address the challenges of device variability, precision, and scalability, providing insights into the practical implementation of these algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1969

some comments on the use of infrared radiometry for remote atmospheric probing

A critique is presented of the lead paper by L.D. Kaplan on infrared radiometry. The following topics are analyzed: the extent to which the desirable thermal resolution of the lower troposphere can be achieved, the effects of complex cloud structure on infrared data, the effective weighting function if linearization is possible, remote sounding from below the atmosphere, first-guess fields and operational techniques to blend satellite infrared data into a mix of data from various meteorological systems, a simple inversion procedure for thermal structure, and problems arising from cloud and haze layers of variable amount and emissivity.

Godson, W. L.↗
NASA NTRS1974

Estimation of elastic aircraft parameters using the maximum likelihood method

The application of the maximum likelihood method to estimate the aerodynamic parameters of elastic flight vehicles in a symmetric flight condition is discussed. In this application, particular attention is directed toward the center of mass, elastic deformation, and sensor equations of motion. It is shown that the two major computational problems to be overcome are the inversion of large-sized matrices and the time-wise integration of a large number of linear, ordinary, differential equations.

Schwanz, R. C.↗
NASA NTRS1979

Low-speed single-element airfoil synthesis

The use of recently developed airfoil analysis/design computational tools to clarify, enrich and extend the existing experimental data base on low-speed, single element airfoils is demonstrated. A discussion of the problem of tailoring an airfoil for a specific application at its appropriate Reynolds number is presented. This problem is approached by use of inverse (or synthesis) techniques, wherein a desirable set of boundary layer characteristics, performance objectives, and constraints are specified, which then leads to derivation of a corresponding viscous flow pressure distribution. Examples are presented which demonstrate the synthesis approach, following presentation of some historical information and background data which motivate the basic synthesis process.

Mcmasters, J. H.↗
NASA NTRS1984

Simulations of the stratocumulus-topped boundary layer with a third-order closure model

A third order closure model is proposed by Andre et al. (1982), in which the time rate of change terms, the relaxation and rapid effects for the pressure related terms, and the clipping approximation are included along with the quasi-normal closure, to study turbulence in a cloudy layer which is cooled radiatively from above. A spurious oscillation which is strongest near the inversion occurs. An analysis of the problem shows that the oscillation arises from the mean gradient and buoyancy terms of the triple moment equations; these terms are largest near the cloud top. The oscillation is physical, rather than computational. In nature the oscillation is effectively damped, by a mechanism which apparently is not included in our model. In the stably stratified layer just above the mixed layer top, turbulence can excite gravity waves, whose energy is radiated away. Because the closure assumption for the pressure terms does not take into account the transport of wave energy, the model generates spurious oscillations. Damping of the oscillations is possible by introducing diffusion terms into the triple moment equations. With a large enough choice for the diffusion coefficient, the oscillation is effectively eliminated. The results are quite sensitive to the ad hoc eddy coefficient.

Moeng, C. H.↗
NASA NTRS1983

An upper bound on the radius of a highly electrically conducting lunar core

Parker's (1980) nonlinear inverse theory for the electromagnetic sounding problem is converted to a form suitable for analysis of lunar day-side transfer function data by: (1) transforming the solution in plane geometry to that in spherical geometry; and (2) transforming the theoretical lunar transfer function in the dipole limit to an apparent resistivity function. The theory is applied to the revised lunar transfer function data set of Hood et al. (1982), which extends in frequency from 10 to the -5th to 10 to the -3rd Hz. On the assumption that an iron-rich lunar core, whether molten or solid, can be represented by a perfect conductor at the minimum sampled frequency, an upper bound of 435 km on the maximum radius of such a core is calculated. This bound is somewhat larger than values of 360-375 km previously estimated from the same data set via forward model calculations because the prior work did not consider all possible mantle conductivity functions.

Hobbs, B. A.↗
NASA NTRS1990

Random-Field Estimation For Dynamics Of Robots

Report discusses use of random-field mathematical models as alternatives to deterministic models of classical mechanics to describe dynamics of robot arms. These alternative models used to establish relationship between methods of estimation theory and robot dynamics. Approach yields new class of algorithms performing computations typical of estimation theory to solve such fundamental problems in robotics as forward and inverse dynamics and inverse kinematics.

Rodriguez, Guillermo↗