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At least 145 records · Page 8

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NASA NTRS2009

Hybrid NN/SVM Computational System for Optimizing Designs

A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily oversimplified to fit the scope of this article, an SVM can be characterized as an algorithm that (1) effects a nonlinear mapping of input vectors into a higher-dimensional feature space and (2) involves a dual formulation of governing equations and constraints. One advantageous feature of the SVM approach is that an objective function (which one seeks to minimize to obtain coefficients that define an SVM mathematical model) is convex, so that unlike in the cases of many NN models, any local minimum of an SVM model is also a global minimum.

Rai, Man Mohan↗

NASA NTRSDate not supplied

Effects of Spaceflight Relevant Carbon Dioxide Levels on Pathogenesis Related Microbial Characteristics

BACKGROUND Multiple stressors in the spaceflight environment have the potential to alter microbial pathogenesis and virulence characteristics, including microgravity, radiation, and hostile/confined conditions. This combination of factors may lead to a stacking of risks, potentially creating unexpected increase in the risk of infectious disease. One understudied variable is the higher CO2 atmospheric concentration. The current Spaceflight Maximum Allowance Concentration (SMAC) for 24-hour average CO2 is 0.4% (3 mm Hg). These elevated ambient CO2 levels aboard the ISS could potentially influence the diversity and phenotypic responses of the resident microbial communities from both the spacecraft environment (air, surface, water) and crewmembers (gut, nasal, skin microbiomes). METHODS For these studies, we will evaluate the response of Staphylococcus aureus, Streptococcus pneumoniae and Enterobacter aerogenes, which are opportunistic pathogens that are of medical significance and have been or are likely to be found aboard spacecraft. These microorganisms will be cultured in both spaceflight analog and control conditions at CO2levels representing terrestrial atmospheric concentration of 0.04% (0.3 mmHg), ISS elevated concentration of 0.4% (3 mm Hg), and an unexpected elevated concentration of 1 % (7.6 mmHg) to represent a worst case scenario. DISCUSSION Overwhelming evidence from studies performed in food microbiology, marine biology and terrestrial environmental biology suggest altered gene expression, selective bacterial inhibition, increased growth and diversity, and increased antibiotic resistance of bacterial communities individually and in biofilm formation when exposed to increased levels of CO2. While many of these findings are based on levels of CO2 higher than would be found during spaceflight exploration missions, the potential for subtle changes in CO2 levels to exacerbate infectious disease risks warrants an evaluation of pathogen responses to spaceflight CO2 conditions. Our study will provide answers to spaceflight relevant atmospheric conditions, as described in the Risk of Adverse Health Effects Due to Host-Microorganism Interaction (GapMicro 103).

A A Medina-Colorado↗

NASA NTRS1991

Graphite/copper alloy interfacial energies determined using the sessile drop method

Graphite surfaces are not wet by pure copper. This lack of wetting is responsible for a debonding phenomenon that was found in continuous graphite fiber/copper matrix composites materials subjected to elevated temperatures. By suitably alloying copper, its capability to wet graphite surfaces can be enhanced. In situ measurements of graphite/copper alloy wetting angles were made using the sessile drop method. Interfacial energy values were calculated based upon these measurements.

Devincent, Sandra M.↗

NASA NTRSDate not supplied

Analysis of Mars 2020 Entry with Coupled Material Response and CFD

When computing the response of an ablating thermal protection system during entry, the aerothermal environment and material response are traditionally computed independently, with the introduction of a blowing correction term in the material response model to account for the outgassing of char and pyrolysis gases. This study presents an approach, where the pyrolysis blowing gases, calculated within the PATO material response code, are integrated into the DPLR hypersonic CFD code via a blowing boundary condition. This methodology employs an iterative process, whereby the blown pyrolysis gas products from PATO are incorporated into DPLR, refining surface heating predictions. The NEQAIR code is used to compute radiative heating. The method is applied in computing 3D material response of the Mars 2020 entry. When compared with uncoupled material response, the coupled simulations show a lower surface heat flux initially and a higher heat flux at peak heating as shown in Fig. 1. This is in agreement with previous work using a sphere case with environments from MSL.

Heat Transfer↗

NASA NTRS2000

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗

NASA NTRSDate not supplied

Analysis of Mars 2020 Entry with Coupled Material Response and CFD

When computing the response of an ablating thermal protection system during entry, the aerothermal environment and material response are traditionally computed independently, with the introduction of a blowing correction term in the material response model to account for the outgassing of char and pyrolysis gases. This study presents an approach, where the pyrolysis blowing gases, calculated within the PATO material response code [1], are integrated into the DPLR hypersonic CFD code [2] via a blowing boundary condition. This methodology employs an iterative process, whereby the blown pyrolysis gas products from PATO are incorporated into DPLR, refining surface heating predictions. The NEQAIR code is used to compute radiative heating [3]. The method is applied in computing 3D material response of the Mars 2020 entry. When compared with uncoupled material response, the coupled simulations show a lower surface heat flux initially and a higher heat flux at peak heating as shown in Fig. 1. This is in agreement with previous work using a sphere case with environments from MSL [4].

Heat Transfer↗

DOE OSTI2020

Application of emerging monitoring techniques at the Illinois Basin – Decatur Project

The Illinois Basin – Decatur Project is a large-scale carbon capture and storage demonstration project located in Decatur, Illinois, USA. In this project, one million metric tons of carbon dioxide (CO 2 ) was captured from an ethanol production facility and successfully injected into a deep saline reservoir over a period of three years. The scale of this project presented an opportunity to explore emerging technologies for effective long-term monitoring of the carbon capture and storage site. This research documents the application of three emerging monitoring techniques: (1) a prototype “open-path” sensor, a method of continuously monitoring atmospheric CO 2 by applying tunable diode laser absorption spectroscopy to provide a warning system for personnel safety along pipelines and at wellheads; (2) the Greenhouse Gas Laser Imaging Tomography Experiment (GreenLITE), an automated system for measuring two-dimensional spatial distribution of atmospheric CO 2 concentrations; and (3) periodic aerial imagery, a method of documenting surface-vegetation dynamics to detect vegetative responses to CO 2 leaks. The objective of this work was to assess the advantages and limitations of these monitoring techniques and quantify their reliability over an extended deployment at an active industrial site. These results will aid in determining viability of long-term monitoring on a commercial scale.

42 ENGINEERING↗

DOE OSTI2026

Disentangling High Harmonic Generation from Surface and Bulk States of a Topological Insulator

The discovery of topological phases has introduced a new dimension to materials science. Three-dimensional (3D) topological insulators (TIs) are a remarkable class of matter that is insulating in the bulk while hosting conductive topological surface states (TSSs) with unique charge and spin properties. High-order harmonic generation (HHG) has emerged as a powerful tool to probe condensed matter systems by providing insights into their electronic structure and dynamic behavior. Here, we investigate HHG in the prototype 3D-TI Bi$_2$Se$_3$. We demonstrate that the contributions of bulk and surface states to the harmonic emission can be controlled by tuning the thickness of thin film samples. An ultrathin (6 nm) film substantially enhances HHG from the surface states, while the bulk states dominate HHG in a thicker (50 nm) film. By applying a quasi-static terahertz perturbing field, we disentangle the bulk and surface responses and reveal the significant impact of the surface states' shift vector and Berry curvature on HHG. Our study provides effective methods for isolating the optical responses of TSSs from those of the bulk, which opens the door to resolving an ongoing debate regarding whether it is possible to reliably extract topological signatures in HHG.

Atomic Physics (physics.atom-ph)↗

NASA NTRS1987

Acoustic fatigue - A Monte Carlo approach

The present paper reviews the basic concepts of nonlinear structural response to surface flow and acoustic pressure inputs. A time domain solution and the Monte Carlo method are utilized to estimate the required statistics of the nonlinear response. Simulation procedures of multi-dimensional and multi-variate random processes are discussed. Application of these procedures to acoustic fatigue of flight structures are considered. Numerical examples are included to illustrate the applicability of this method for the solution of nonlinear problems.

Vaicaitis, R.↗

NASA NTRS2006

Control Surface Interaction Effects of the Active Aeroelastic Wing Wind Tunnel Model

This paper presents results from testing the Active Aeroelastic Wing wind tunnel model in NASA Langley s Transonic Dynamics Tunnel. The wind tunnel test provided an opportunity to study aeroelastic system behavior under combined control surface deflections, testing for control surface interaction effects. Control surface interactions were observed in both static control surface actuation testing and dynamic control surface oscillation testing. The primary method of evaluating interactions was examination of the goodness of the linear superposition assumptions. Responses produced by independently actuating single control surfaces were combined and compared with those produced by simultaneously actuating and oscillating multiple control surfaces. Adjustments to the data were required to isolate the control surface influences. Using dynamic data, the task increases, as both the amplitude and phase have to be considered in the data corrections. The goodness of static linear superposition was examined and analysis of variance was used to evaluate significant factors influencing that goodness. The dynamic data showed interaction effects in both the aerodynamic measurements and the structural measurements.

Heeg, Jennifer↗

NASA NTRS1998

Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle

The use of response surface models and kriging models are compared for approximating non-random, deterministic computer analyses. After discussing the traditional response surface approach for constructing polynomial models for approximation, kriging is presented as an alternative statistical-based approximation method for the design and analysis of computer experiments. Both approximation methods are applied to the multidisciplinary design and analysis of an aerospike nozzle which consists of a computational fluid dynamics model and a finite element analysis model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations. Four optimization problems are formulated and solved using both approximation models. While neither approximation technique consistently outperforms the other in this example, the kriging models using only a constant for the underlying global model and a Gaussian correlation function perform as well as the second order polynomial response surface models.

Simpson, Timothy W.↗

DOE OSTI2022

System and method thermopile energy harvesting for subsurface well bore sensors

A system and method for powering a borehole sensor with thermal energy is disclosed. The system includes a tubular pipe inserted into a subsurface borehole. A borehole casing is coaxially disposed with the tubular pipe. An annular space between the casing and the tubular pipe has a power source placed in the borehole to power a sensor in response to a temperature gradient between a surface of the casing and a surface of the tubular pipe. The method includes attaching thermopiles on the borehole casing or tubing; placing the thermopile in the annulus between the casing and the tubing; inducing a thermal gradient across the thermopile; generating an electrical energy in response to the temperature gradient; powering the sensor from the generated energy; and monitoring vertical expansion of a CO2 plume.

Bryan, Charles R.↗

NASA NTRS2001

Accuracy Assessment of Response Surface Approximations for Supersonic Turbine Design

There is a growing trend to employ CFD tools to supply the necessary information for design optimization of fluid dynamics components/systems. Such results are prone to uncertainties due to reasons including discretization. errors, incomplete convergence of computational procedures, and errors associated with physical models such as turbulence closures. Based on this type of information, gradient-based optimization algorithms often suffer from the noisy calculations, which can seriously compromise the outcome. Similar problems arise from the experimental measurements. Global optimization techniques, such as those based on the response surface (RS) concept are becoming popular in part because they can overcome some of these barriers. However, there are also fundamental issues related to such global optimization technique such as RS. For example, in high dimensional design spaces, typically only a small number of function evaluations are available due to computational and experimental costs. On the other hand, complex features of the design variables do not allow one to model the global characteristics of the design space with simple quadratic polynomials. Consequently a main challenge is to reduce the size of the region where we fit the RS, or make it more accurate in the regions where the optimum is likely to reside. Response Surface techniques using either polynomials or and Neural Network (NN) methods offer designers alternatives to conduct design optimization. The RS technique employs statistical and numerical techniques to establish the relationship between design variables and objective/constraint functions, typically using polynomials. In this study, we aim at addressing issues related to the following questions: (1) How to identify outliers associated with a given RS representation and improve the RS model via appropriate treatments? (2) How to focus on selected design data so that RS can give better performance in regions critical to design optimization? (3) How to combine NN and polynomial techniques for improving the accuracy of the RS model?

Papila, Nilay↗

NASA NTRS2014

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗

NASA NTRS1998

Shear-Sensitive Liquid Crystal Coating Method: Surface-Inclination Effects on Shear Vector Measurements

The shear-sensitive liquid crystal coating (SSLCC) method is an image-based technique for both visualizing dynamic surface-flow phenomena, such as transition and separation, and for measuring the continuous shear-stress vector distribution acting on an aerodynamic surface. Under proper lighting and viewing conditions (discussed below), the coating changes color in response to an applied aerodynamic shear. This color-change response is continuous and reversible, with a response time of milliseconds, and is a function of both the shear magnitude and the shear vector orientation relative to the observer. The liquid crystal phase of matter is a weakly-ordered, viscous, non-Newtonian fluid state that exists between the nonuniform liquid phase and the ordered solid phase of certain organic compounds. Cholesteric liquid crystal compounds possess a helical molecular arrangement that selectively scatters white light, incident along the helical axis, as a three-dimensional spectrum. This property is linked to the helical pitch length, which is within the range of wavelengths in the visible spectrum. The pitch length, and hence the wavelength of the scattered light, is influenced by shear stress normal to the helical axis. This unique optical property produces a measurable color change in response to an applied shearing force. The full-surface shear stress vector measurement method, developed at NASA-Ames, is schematically illustrated. As with the visualization method, the coated test surface is illuminated from the normal direction with white light and the camera is positioned at an above-plane view angle of approximately 30 deg. Experiments have been initiated at NASA Ames to begin the process of quantifying surface-inclination (surface-curvature) effects on shear vector measurement accuracy. In preliminary experiments, surface-inclination angles theta(sub x), theta(sub y) of 0, +/-5, +/-10, and +/-15 deg were employed. In this arrangement, white-light illumination was positioned normal to the untilted test surface, and the camera above-plane view angle was set at 30 deg relative to the untilted test surface. As can be seen, vector-aligned lambda(sub d) values showed no dependence on theta(sub x) or theta(sub y) for absolute values of these tilt angles is less than or equal to 15 deg. Acquisition and analyses of full-surface color images are presently underway to definitively document the insensitivity limits of the shear vector measurement methodology to surface-slope variations.

Reda, Daniel C.↗

NASA NTRS2015

Measurement of Flaw Size From Thermographic Data

Simple methods for reducing the pulsed thermographic responses of delaminations tend to overestimate the size of the delamination, since the heat diffuses in the plane parallel to the surface. The result is a temperature profile over the delamination which is larger than the delamination size. A variational approach is presented for reducing the thermographic data to produce an estimated size for a flaw that is much closer to the true size of the delamination. The method is based on an estimate for the thermal response that is a convolution of a Gaussian kernel with the shape of the flaw. The size is determined from both the temporal and spatial thermal response of the exterior surface above the delamination and constraints on the length of the contour surrounding the delamination. Examples of the application of the technique to simulation and experimental data are presented to investigate the limitations of the technique.

Winfree, William P.↗

NASA NTRS2019

Evaluation of the Surface Reflectance Long-Term Data Record from AVHRR over Multiple Land Surface Types

In this work, we evaluate the performance of the AVHRR surface reflectance LTDR V4 using Landsat-5 Thematic Mapper (TM5) Collection-1 surface reflectance data over 440 globally distributed sites, which give a representative set of land surface types and climate conditions. Surface reflectance anisotropy effects were normalized using the VJB method, and spectral response differences were accounted for with spectral band adjustment factors (SBAFs) computed as a function of the Normalized Difference Vegetation Index (NDVI) from a set of over 100,000 hyperspectral spectra from Hyperion. The performance of the AVHRR record is reported in terms of the accuracy, precision, and uncertainty, as compared to the specifications of the reference product. Results show that the AVHRR record performance is close to the 0.071ρ+0.0071 specification defined in the original TM5 product evaluation.

LTDR↗

DOE OSTI2022

Estimating epistemic uncertainty in soil parameters for nonlinear site response analyses: Introducing the Latin Hypercube Sampling technique

This study quantifies the effects of epistemic uncertainty in soil parameters on nonlinear (NL) site response analysis (SRA) results, validated against the data recorded at a well-instrumented geotechnical downhole array located in Japan. To this end, a one-dimensional soil column model of the Service Hall Array (SHA) near the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) is developed using the finite element (FE) program LS-DYNA. The dynamic stress–strain relationship is characterized by a modified two-stage hyperbolic (MTH) NL backbone curve formulation capable of capturing soil behavior at both small- and large-shear strains. The model is then validated against the ground motion recordings to capture the model bias. The uncertainties associated with the shear-wave velocity profile (a small-strain soil property) and soil shear strength (a large-strain soil property) are incorporated in NL SRA to quantify their separate and joint randomization effects on the results. This study proposes using the Latin Hypercube Sampling (LHS) method as an efficient alternative to commonly used methods, such as Standard Monte Carlo (SMC), to account for uncertainty propagation in such reliability analysis. Both low-intensity and design-level records from the recordings at the SHA are applied to study the contribution of the small- and large-strain NL dynamic soil properties. Results from 46,200 NL FE analyses (23,100 per input motion) are presented. Measured and predicted site response, using recorded ground motions at this downhole array, is compared to assess the significance of soil parameter uncertainty on the observed ground motion dispersions. It is demonstrated that increasing the number of soft realizations and implementing higher level earthquake intensity lead to higher ground motion dispersion. Unlike past studies in randomization of Vs profiles with the SMC method, the LHS method is shown to have no significant effect on the predicted median surface response spectra and amplification factors (AFs) for this case study.

Engineering↗