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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Ultra-high-power plasma switch INPIS for pulse power systems

A novel plasma switch, the inverse pinch switch (IN-PIS), with a combination geometry based on an inverse-pinch mechanism, has been tested and shown to alleviate the shortcomings of conventional spark gaps. The INPIS switch or INPIStron is currently being upscaled for high-voltage (approximately 1 MV) operation with a multigap arrangement similar to Sandia's rimfire electrodes used for ultra-high-voltage hold off. Preliminary results of the multigap INPIS tests at 230 kV and plasma-puff initiation methods are presented, and an application to compact pulser systems is discussed.

Lee, Ja H.↗
NASA NTRS1993

STEP: Satellite Test of the Equivalence Principle. Report on the phase A study

During Phase A, the STEP Study Team identified three types of experiments that can be accommodated on the STEP satellite within the mission constraints and whose performance is orders of magnitude better than any present or planned future experiment of the same kind on the ground. The scientific objectives of the STEP mission are to: test the Equivalence Principle to one part in 10(exp 17), six orders of magnitude better than has been achieved on the ground; search for a new interaction between quantum-mechanical spin and ordinary matter with a sensitivity of the mass-spin coupling constant g(sub p)g(sub s) = 6 x 10(exp -34) at a range of 1 mm, which represents a seven order-of-magnitude improvement over comparable ground-based measurements; and determine the constant of gravity G with a precision of one part in 10(exp 6) and to test the validity of the inverse square law with the same precision, both two orders of magnitude better than has been achieved on the ground.

Blaser, J. P.↗
NASA NTRS2003

Helioseismic Observations of the Structure and Dynamics of a Rotating Sunspot Beneath the Solar Surface

Time-distance helioseismology is applied to study the subphotospheric structures and dynamics of an unusually fast-rotating sunspot observed by the Michelson Doppler Imager on bead SOH0 in 2000 August. The subsurface sound speed structures and velocity fields are obtained for the sunspot region at different depths from 0 to 12 Mm. By comparing the subsurface sound speed variations with the surface magnetic field, we find evidence for structural twists beneath the visible surface of this active region, which may indicate that magnetic twists often seen at the photosphere also exist beneath the photosphere. We also report on the observation of subsurface horizontal vortical flows that extend to a depth of 5 Mm around this rotating sunspot and present evidence that opposite vortical flows may exist below 9 Mm. It is suggested that the vortical flows around this active region may build up a significant amount of magnetic helicity and energy to power solar eruptions. Monte Carlo simulation has been performed to estimate the error propagation, and in addition the sunspot umbra is masked to test the reliability of our inversion results. On the basis of the three-dimensional velocity fields obtained from the time-distance helioseismology inversions, we estimate the subsurface kinetic helicity at different depths for the first time and conclude that it is comparable to the current helicity estimated from vector magnetograms.

Zhao, Junwei↗
NASA NTRS2009

A Relationship Between Constraint and the Critical Crack Tip Opening Angle

Of the various approaches used to model and predict fracture, the Crack Tip Opening Angle (CTOA) fracture criterion has been successfully used for a wide range of two-dimensional thin-sheet and thin plate applications. As thicker structure is considered, modeling the full three-dimensional fracture process will become essential. This paper investigates relationships between the local CTOA evaluated along a three-dimensional crack front and the corresponding local constraint. Previously reported tunneling crack front shapes were measured during fracture by pausing each test and fatigue cycling the specimens to mark the crack surface. Finite element analyses were run to model the tunneling shape during fracture, with the analysis loading conditions duplicating those tests. The results show an inverse relationship between the critical fracture value and constraint which is valid both before maximum load and after maximum load.

Johnston, William M.↗
NASA NTRS2017

Wideband Reconfigurable Harmonically Tuned GaN SSPA for Cognitive Radios

The paper presents the architecture of a wideband reconfigurable harmonically-tuned Gallium Nitrate (GaN) Solid State Power Amplifier (SSPA) for cognitive radios. When interfaced with the physical layer of a cognitive communication system, this amplifier topology offers broadband high efficiency through the use of multiple tuned input/output matching networks. This feature enables the cognitive radio to reconfigure the operating frequency without sacrificing efficiency. This paper additionally presents as a proof-of-concept the design, fabrication, and test results for a GaN inverse class-F type amplifier operating at X-band (8.4 GHz) that achieves a maximum output power of 5.14-W, Power Added Efficiency (PAE) of 38.6, and Drain Efficiency (DE) of 48.9 under continuous wave (CW) operation.

Cognitive↗
NASA NTRS2017

Multiband Reconfigurable Harmonically Tuned Gallium Nitride (GaN) Solid-State Power Amplifier (SSPA) for Cognitive Radios

The paper presents the architecture of a wideband reconfigurable harmonically-tuned Gallium Nitride (GaN) Solid State Power Amplifier (SSPA) for cognitive radios. When interfaced with the physical layer of a cognitive communication system, this amplifier topology offers broadband high efficiency through the use of multiple tuned input/output matching networks. This feature enables the cognitive radio to reconfigure the operating frequency without sacrificing efficiency. This paper additionally presents as a proof-of-concept the design, fabrication, and test results for a GaN inverse Class-F type amplifier operating at X-band (8.4 GHz) that achieves a maximum output power of 5.14-W, Power Added Efficiency (PAE) of 38.6 percent, and Drain Efficiency (DE) of 48.9 percent under continuous wave (CW) operation.

Cognitive↗
NASA NTRS1950

Summary of the Aerodynamic Characteristics and Flying Qualities Obtained from Flights of Rocket-Propelled Models of an Airplane Configuration Incorporating a Sweptback Inversely Tapered Wing at Transonic and Low-Supersonic Speeds

Flight tests have been conducted on rocket-propelled models of an airplane configuration incorporating a sweptback wing with inverse taper to investigate the drag, stability, and control characteristics at transonic and supersonic speeds. The models were tested with a conventional tail arrangement in the Mach number range from 0.55 to 1.2. In addition to the various aerodynamic parameters obtained, the flying qualities were computed for a full-scale airplane with the center-of-gravity location at 18 percent of the mean aerodynamic chord. Also, included in this investigation are drag measurements made on relatively simple fixed-control models tested with both conventional and V-tail arrangements.

Mitcham, Grady L.↗
NASA NTRS1973

Inversion layer solar cell fabrication and evaluation

Silicon solar cells operating with induced junctions rather than diffused junctions have been fabricated and tested. Induced junctions were created by forming an inversion layer near the surface of the silicon by supplying a sheet of positive charge above the surface. This charged layer was supplied through three mechanisms: (1) applying a positive potential to a transparent electrode separated from the silicon surface by a dielectric, (2) contaminating the oxide layer with positive ions, and (3) forming donor surface states that leave a positive charge on the surface. A movable semi-infinite shadow delineated the extent of sensitivity of the cell due to the inversion region. Measurements of the response of the inversion layer cell to light of different wavelengths indicated it to be more sensitive to the shorter wavelengths of the sun's spectrum than conventional cells. The greater sensitivity occurs because of the shallow junction and the strong electric field at the surface.

Call, R. L.↗
DOE OSTI2023

Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface

Abstract Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented with embedded physics and a technique known as algorithmic differentiation. We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g., permeability or P-wave velocity), that embeds physical knowledge of the subsurface properties into inverse analysis and improves its performance. We tested the application of this approach on four geologic problems: two heterogeneous hydraulic conductivity fields, a hydraulic fracture network, and a seismic inversion for P-wave velocity. This physics-embedded inverse analysis approach consistently characterizes these geological problems accurately. Furthermore, the excellent performance in matching the observational data demonstrates the reliability of the proposed method. Moreover, the application of algorithmic differentiation makes this an easy and fast approach to inverse analysis when dealing with complicated geological structures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bi-fidelity Gradient-Based Approach for Nonlinear Well Logging Inverse Problems

Solving a non-linear inverse problem is challenging in computational science and engineering. Sampling based methods require a large number of model valuations; gradientbased methods require fewer model evaluations but only find the local minima. Multifidelity optimization combines the low fidelity model and the high-fidelity model to achieve both high accuracy and high efficiency. In this paper, we present a bi-fidelity approach to solve non-linear inverse problems. In the bi-fidelity inversion method, the low-fidelity model is used to acquire a good initial guess, and the high-fidelity model is used to locate the global minimum. Combined with a multi-start optimization scheme, the proposed approach significantly increases the possibility of finding the global minimum for nonlinear inverse problems with many local minima. The method is tested with two toy problems and then applied to an electromagnetic well logging inverse problem, which is difficult to solve using traditional gradient-based methods. The bi-fidelity method provides promising inversion results and can be easily applied to traditional gradient-based methods.

42 ENGINEERING↗
DOE OSTI2022

Joint Inversion of Body Wave Arrival Times, Surface Wave Dispersion Data and Receiver Functions: Method and Application to South China

In this work, we have developed a new joint inversion method that incorporates body wave arrival times, surface wave dispersion and receiver functions to simultaneously update earthquake locations and constrain three-dimensional P-wave (Vp) and S-wave velocity (Vs) models. Due to complementary sensitivities of the three types of data, the proposed joint inversion algorithm can reduce the intrinsic non-uniqueness of inversions using fewer types of data and better determine smooth velocity variations and velocity discontinuities. Synthetic tests demonstrate the advantages of this new joint inversion algorithm in resolving velocity structures, especially in constraining velocity gradients across the Moho interface. We have applied the proposed joint inversion algorithm to image the lithosphere velocity structure of south China. The inverted Vp and Vs models fit body wave arrival times, surface wave dispersion and receiver functions well. We further analyzed the distribution of Vs gradients across the Moho interface in detail, which helps us better understand tectonics in south China.

58 GEOSCIENCES↗
NASA NTRS2021

Thermal Conductivity Estimation from Transient Test Data with Embedded Thermocouples using Genetic Algorithm Optimization

Inverse heat transfer methodology previously developed to estimate thermal properties of high temperature fibrous insulation from embedded thermocouples was applied to the thermoplastic polymer, polyether-ether-ketone (PEEK). A small experimental setup was utilized to test the PEEK sample between temperatures of 300 K and 525 K at atmospheric pressure. Cylindrical plugs of PEEK with three thermocouples embedded at various depths were incorporated in the test sample. The experimental PEEK thermocouple data were used as the boundary and initial conditions of a one-dimensional numerical thermal model to predict the internal temperatures of the material. The thermal conductivity of PEEK was estimated with the Continuous Genetic Algorithm optimization technique by searching for the coefficients of a functional form of thermal conductivity that minimized the difference between the experimentally measured and model predicted internal temperature values. The thermal testing, one-dimensional numerical thermal model, optimization algorithm, analysis, and results are presented.

Thermal Properties↗
DOE OSTI2024

PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments

This article describes PyOED, a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, the current version of PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to “enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.” This article provides a brief description of the PyOED layout and philosophy and provides a set of exemplary test cases and tutorials to demonstrate the potential of the package.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PYOED: AN ETENSIBLE SUITE FOR DATA ASSIMILATION AND MODEL-CONSTRAINED OPTIMAL DESIGN OF EXPERIMENTS

SF-23-005 PyOED is a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to ``enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.'' PyOED will be continuously expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators.

ATTIA, AHMEDMOHAMED↗
DOE OSTI2023

An Assessment of the Laminar Hypersonic Double-Cone Experiments in the LENS-XX Tunnel

This is an investigation on two experimental datasets of laminar hypersonic flows, over a double-cone geometry, acquired in Calspan—University at Buffalo Research Center’s Large Energy National Shock (LENS)-XX expansion tunnel. These datasets have yet to be modeled accurately. A previous paper suggested that this could partly be due to mis-specified inlet conditions. The authors of this paper solved a Bayesian inverse problem to infer the inlet conditions of the LENS-XX test section and found that in one case they lay outside the uncertainty bounds specified in the experimental dataset. However, the inference was performed using approximate surrogate models. Here in this paper, the experimental datasets are revisited and inversions for the tunnel test-section inlet conditions are performed with a Navier–Stokes simulator. The inversion is deterministic and can provide uncertainty bounds on the inlet conditions under a Gaussian assumption. It was found that deterministic inversion yields inlet conditions that do not agree with what was stated in the experiments. An a posteriori method is also presented to check the validity of the Gaussian assumption for the posterior distribution. This paper contributes to ongoing work on the assessment of datasets from challenging experiments conducted in extreme environments, where the experimental apparatus is pushed to the margins of its design and performance envelopes.

42 ENGINEERING↗
NASA NTRS1997

Microgravity vestibular investigations: perception of self-orientation and self-motion

Four astronauts experienced passive whole-body rotation in a number of test sessions during a 7-day orbital mission. Pitch (Y-axis) and roll (X-axis) rotation required subject orientations on the rotator in which the otolith system was at radius of 0.5 m. Thus subjects experienced a constant -0.22 Gz stimulus to the otoliths during the 60 s constant-velocity segments of "pitch" and "roll" ramp profiles. The Gz stimulus, a radius-dependent vector ranging from -0.22 Gz at the otoliths to +0.36 Gz at the feet, generated sensory information that was not interpreted as inversion in any of the 16 tests carried out in flight (12 in pitch and 4 in roll orientation). None of the subjects was rotated with head off-center during the first 33 h of the mission. In the state of orbital adaptation of these subjects, a -0.22 Gz otolith stimulus did not provide a vertical reference in the presence of a gradient of +Gz stimuli to the trunk and legs.

NASA Experiment Number 284058↗
DOE OSTI2022

A machine learning approach to determine the elastic properties of printed fiber-reinforced polymers

This work focuses on the simultaneous determination of the elastic constants and the fiber orientation state for a short fiber-reinforced polymer composite by performing a minimum of experimental tests. Here we introduce a methodology that enables the inverse determination of fiber orientation state and the in-situ polymer properties by performing tensile tests at the composite coupon level. We demonstrate the approach for the extrusion deposition additive manufacturing (EDAM) process to illustrate one application of the methodology, but the development is such that it can be applied to short fiber-reinforced polymer (SFRP) systems processed via other methods. Currently, developing composites additive manufacturing digital twins require extensive material characterization. In particular, the mechanical characterization of the orthotropic elastic properties of a composite involves extensive sample preparation and testing, therefore the elasticity tensor is generally populated using a micromechanics model. This, however, requires measuring the fiber orientation state in addition to knowing the constituent material properties. Experimentally measuring the fiber orientation state can be tedious and time consuming. Further, optical methods are limited to resolving the orientation of cylindrical fibers or cluster of non-cylindrical fibers, and computed tomography (CT) methods scan regions of volume that are much smaller than a full printed bead. Therefore, we propose a methodology, accelerated by machine learning, to identify the anisotropic mechanical properties and fiber orientation state at the same time. Early results show that inference of the fiber orientation and composite properties is possible with as few as three tensile tests. Our results show that a combination of the choice of the micromechanics model and reliable set of experiments can yield the nine elastic constants, as well as, the fiber orientation state.

36 MATERIALS SCIENCE↗