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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 1,099 records · Page 61

An explicit finite-volume time-marching procedure for turbulent flow calculations

A method was developed which calculates two-dimensional, transonic, viscous flow in ducts. The finite-volume, time-marching formulation is used to obtain steady flow solutions of the Reynolds-averaged form of the Navier-Stokes equations. The entire calculation is performed in the physical domain. Control volumes are chosen so that smoothing of flow properties, typically required for stability, is not required. Different time steps are used in the different governing equations. A new pressure interpolation scheme is introduced which improves the shock capturing ability of the method. A multi-volume method for pressure changes in the boundary layer allows calculations which use very long and thin control volumes (length/height - 1000). The method is compared with two test cases. Essentially incompressible turbulent boundary layer flow in an adverse pressure gradient is calculated and the computed distributions of mean velocity and shear are in good agreement with the measurements. Transonic viscous flow in a converging diverging nozzle is calculated; the Mach number upstream of the shock is approximately 1.25. The agreement between the calculated and measured shock strength and total pressure losses is good.

Nicholson, Stephen↗

SU-F-E-09: Respiratory Signal Prediction Based On Multi-Layer Perceptron Neural Network Using Adjustable Training Samples

Purpose: Dynamic tracking of moving organs, such as lung and liver tumors, under radiation therapy requires prediction of organ motions prior to delivery. The shift of moving organ may change a lot due to huge transform of respiration at different periods. This study aims to reduce the influence of that changes using adjustable training signals and multi-layer perceptron neural network (ASMLP). Methods: Respiratory signals obtained using a Real-time Position Management(RPM) device were used for this study. The ASMLP uses two multi-layer perceptron neural networks(MLPs) to infer respiration position alternately and the training sample will be updated with time. Firstly, a Savitzky-Golay finite impulse response smoothing filter was established to smooth the respiratory signal. Secondly, two same MLPs were developed to estimate respiratory position from its previous positions separately. Weights and thresholds were updated to minimize network errors according to Leverberg-Marquart optimization algorithm through backward propagation method. Finally, MLP 1 was used to predict 120∼150s respiration position using 0∼120s training signals. At the same time, MLP 2 was trained using 30∼150s training signals. Then MLP is used to predict 150∼180s training signals according to 30∼150s training signals. The respiration position is predicted as this way until it was finished. Results: In this experiment, the two methods were used to predict 2.5 minute respiratory signals. For predicting 1s ahead of response time, correlation coefficient was improved from 0.8250(MLP method) to 0.8856(ASMLP method). Besides, a 30% improvement of mean absolute error between MLP(0.1798 on average) and ASMLP(0.1267 on average) was achieved. For predicting 2s ahead of response time, correlation coefficient was improved from 0.61415 to 0.7098.Mean absolute error of MLP method(0.3111 on average) was reduced by 35% using ASMLP method(0.2020 on average). Conclusion: The preliminary results demonstrate that the ASMLP respiratory prediction method is more accurate than MLP method and can improve the respiration forecast accuracy.

60 APPLIED LIFE SCIENCES↗

Generalized boost transformations in finite volumes and application to Hamiltonian methods

The investigation of hadron interactions within lattice QCD has been facilitated by the well-known quantisation condition, linking scattering phase shifts to finite-volume energies. Additionally, the ability to utilise systems at finite total boosts has been pivotal in smoothly charting the energy-dependent behaviour of these phase shifts. The existing implementations of the quantization condition at finite boosts rely on momentum transformations between rest and moving frames, defined directly in terms of the energy eigenvalues. This energy dependence is unsuitable in the formulation of a Hamiltonian. In this work, we introduce a novel approach to generalise the three-momentum boost prescription, enabling the incorporation of energy-independent finite-volume Hamiltonians within moving frames. We demonstrate the application of our method through numerical comparisons, employing a phenomenological ππ scattering example.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hypersonic Flow Computations on Unstructured Meshes

A method for computing inviscid hypersonic flow over complex configurations using unstructured meshes is presented. The unstructured grid solver uses an edge{based finite{volume formulation. Fluxes are computed using a flux vector splitting scheme that is capable of representing constant enthalpy solutions. Second{order accuracy in smooth flow regions is obtained by linearly reconstructing the solution, and stability near discontinuities is maintained by locally forcing the scheme to reduce to first-order accuracy. The implementation of the algorithm to parallel computers is described. Computations using the proposed method are presented for a sphere-cone configuration at Mach numbers of 5.25 and 10.6, and a complex hypersonic re-entry vehicle at Mach numbers of 4.5 and 9.8. Results are compared to experimental data and computations made with established structured grid methods. The use of the solver as a screening tool for rapid aerodynamic assessment of proposed vehicles is described.

Bibb, K. L.↗

Distinguishing homolytic vs heterolytic bond dissociation of phenylsulfonium cations with localized active space methods

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Furthermore, our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continuity conditions for tensor product Q-Bézier surfaces of degree (m, n)

Based on a kind of Q-Bézier surfaces with shape parameters, the basic properties of the surfaces and the geometric significance of the shape parameters are analyzed. To resolve the problem of shape control and adjustment of composite surfaces, the continuity conditions for Q-Bézier surfaces of degree (m, n) are investigated. Taking advantage of the terminal properties of generalized Bernstein basis functions, we derive the conditions of G{sup 1} and G{sup 2} continuity between two adjacent Q-Bézier surfaces. In addition, the specific steps of smooth continuity between Q-Bézier surfaces and the shape adjustment function of shape parameters for composite surfaces are discussed. The modeling examples show that the proposed smooth continuity conditions are not only intuitive and easy to implement, but also greatly enhance the shape adjustability, which provide a useful method for constructing complex surfaces in engineering design.

97 MATHEMATICS AND COMPUTING↗

Isolation and characterization of human islet stellate cells

Background and aims: We have previously demonstrated that islet stellate cells (ISCs) exhibiting a similar phenotype to classical pancreatic stellate cells (PSCs) could be isolated from rat islets, where they may contribute to islet fibrosis in type 2 diabetes mellitus (T2DM). This study was designed to determine whether human islets also contain ISC. Materials and methods: Using standard explants techniques, human ISCs were enriched from freshly isolated human islets. Immunofluorescence visualization of markers for PSCs(α-smooth muscle actin;α-SMA), desmin, vimentin, glial fibrillary acidic protein (GFAP) was used to characterize the human ISC. Cell counting kit-8 (CCK-8) was used to assess the proliferation of ISC. The wound-healing assay and the transwell migration were used to assess the migration capacity of ISC. Immunofluorescence against collagen typesI (col-I), collagen typesIII (col-III) and fibronectin (FN) was performed to identify extracellular matrix (ECM) component synthesized by ISC. Adipogenic and osteogenic differentiation were tried to detected stem cell potential. Results: In culture, ISC with triangular shape grow out from human islets. The passaged ISC expressed α-SMA, desmin, vimentin, GFAP and was positive for col-I, col-III and FN. The proliferation and migration ability of ISC was significantly slower than those of PSC. And both the human PSC and ISC were able to differentiate in vitro into adipocyte- and osteoblast-like cells. Conclusion: Similar to our previous rat experiment, the current study shows that human islets also contain ISC which is phenotypically similar but not identical to human PSC. - Highlights: • ISCs grow out from human islets. ISC expressed α-SMA, desmin, vimentin, GFAP and was positive for col-I, col-III and FN. The proliferation and migration ability of human islets contain ISC. • ISC is phenotypically similar but not identical to PSC. • ISC may play an important role in the islet fibrosis in T2DM.

60 APPLIED LIFE SCIENCES↗

Colloidosome like structures: self-assembly of silica microrods

Self-assembly of one-dimensional structures is attracting a great deal of interest because assembled structures can provide better properties compared to individual building blocks. We demonstrate silica microrod self-assembly by exploiting Pickering emulsion based strategy. Micron-sized silica rods were synthesized employing previously reported methods based on polyvinylpyrrolidone/ pentanol emulsion droplets. Moreover, rods self-assembled to make structures in the range of z10 40 mm. Smooth rods assembled better than segmented rods. Finally, the assembled structures were bonded by weak van der Waals forces.

36 MATERIALS SCIENCE↗

Reactive processing of textile-natural fiber reinforced anionic polyamide-6 composites

Nowadays natural fiber, used in reinforced composites, is widely concerned. However, no natural fiber reinforced reactive thermoplastic polymer grades had been prepared so far. Through our studies, it was demonstrated that there was a severe retardation and discoloration occurred in the reactive processing between anionic polyamide-6 (APA-6) and natural fiber, which result in incomplete polymerization when put together. In order to solve the problem, two methods were adopted in this paper, which are fiber pretreatment and usage of a new-style initiator called caprolactam magnesium bromide. The former is to remove sizing agent and impurities on the surface of fiber, and the latter is to weaken the side reactions between APA-6 and natural fiber by the nature of its lower reactivity and weaker alkaline. In cooperation with both methods, the severe retardation and discoloration had been improved significantly, so that the polymerization of APA-6 in natural fiber was occurred smoothly. Following textile-natural fiber reinforced APA-6 composites with an average thickness of 2.5 mm and a fiber volume content of 50% was prepared by vacuum assisted resin transfer molding (VARTM). The soxhlet extraction, dilute solution viscometry and differential scanning calorimeter (DSC) measurements respectively suggested the degree of conversion, viscosity-average molar mass and crystallization of composites was up to 94%, 11.3×104 and 50%. Remarkable improvement of mechanical properties were achieved through dynamic mechanical analysis (DMA), tensile and three-point bending test. Favorable interfacial adhesion and wettability were revealed by scanning electron microscopy (SEM) observation. Therefore, all of the above good performance make this new-style and environmentally friendly composites have broad application prospects.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Recipes for when physics fails: recovering robust learning of physics informed neural networks

Abstract Physics-informed neural networks (PINNs) have been shown to be effective in solving partial differential equations by capturing the physics induced constraints as a part of the training loss function. This paper shows that a PINN can be sensitive to errors in training data and overfit itself in dynamically propagating these errors over the domain of the solution of the PDE. It also shows how physical regularizations based on continuity criteria and conservation laws fail to address this issue and rather introduce problems of their own causing the deep network to converge to a physics-obeying local minimum instead of the global minimum. We introduce Gaussian process (GP) based smoothing that recovers the performance of a PINN and promises a robust architecture against noise/errors in measurements. Additionally, we illustrate an inexpensive method of quantifying the evolution of uncertainty based on the variance estimation of GPs on boundary data. Robust PINN performance is also shown to be achievable by choice of sparse sets of inducing points based on sparsely induced GPs. We demonstrate the performance of our proposed methods and compare the results from existing benchmark models in literature for time-dependent Schrödinger and Burgers’ equations.

97 MATHEMATICS AND COMPUTING↗

Resolving local structural motifs across the phase evolution of zinc titanates with computational x-ray absorption spectroscopy

Resolving the local structure motifs that characterize phase evolution as a function of composition is a key challenge in structure characterization of complex materials. Here, in this study, we combine first-principles simulations and x-ray absorption near-edge structures (XANES) analysis to gain insights into the structure evolution revealed by measurements across a combinatorial zinc titanate thin film, which was grown with smoothly varying composition over a wide range of the Ti:Zn ratio. Specifically, we propose a cluster blind-signal-separation (cBSS) method for XANES spectral analysis based on a library of the structures and spectra of representative local motifs. In addition to motifs from zinc titanate crystals, two types of Ti-defect models constructed in this study are key to the understanding of the structure characteristics in the Zn-rich region. The cBSS method makes use of both spectral clustering of the simulated site-XANES spectra library and the BSS procedure to construct high-fidelity spectral basis functions from an experimental spectral sequence. The method provides a rigorous measure of the spectral sensitivity and basis completeness. The results of the XANES analysis are corroborated with other experimental modalities, including x-ray diffraction and spectroscopic ellipsometry, to validate the cBSS method. The calculated motif weights resulting from fitting the XANES spectra with the cBSS basis probe the atomic structure characteristics of both crystalline and amorphous phases as a function of the Ti/Zn composition. The insights of the local structure motif evolution are pivotal to the understanding of the nonmonotonic trend in the optical gap, which may lead to potential applications through tuning the optical properties of zinc titanate. The workflow of the XANES spectral analysis developed in this work can be generalized to construct the structure-property relationship in a broad material space.

36 MATERIALS SCIENCE↗

Non-smooth Bayesian optimization in tuning scientific applications

Tuning algorithmic parameters to optimize the performance of large, complicated computational codes is an important problem involving finding the optima and identifying regimes defined by non-smooth boundaries in black-box functions. Within the Bayesian optimization framework, the Gaussian process surrogate model produces smooth mean functions, but functions in the tuning problem are often non-smooth, which is exacerbated by the fact that we usually have limited sequential samples from the black-box function. Here, motivated by these issues encountered in tuning, we propose a novel Gaussian process model called a clustered Gaussian process (cGP), where the components are dynamically updated by clustering. In our studies, the performance of cGP can be better than stationary GPs in nearly 90% of the experiments and better than non-stationary GPs in nearly 70% of the repeated experiments while requiring less computational cost. cGP provides a novel approach for dynamic GP, computes more efficiently than recursive partitioning, and discovers non-smoothness regimes. We provide extensive experiments including high-performance computing (HPC) and industrial simulation functions to show the effectiveness of our methods.

97 MATHEMATICS AND COMPUTING↗

Deep learning-based spatio-temporal estimate of greenhouse gas emissions using satellite data

Accurate estimation of greenhouse gases (GHGs) emissions is very important for developing mitigation strategies to climate change by controlling and reducing GHG emissions. This project aims to develop multiple deep learning approaches to estimate anthropogenic greenhouse gas emissions using multiple types of satellite data. NO2 concentration is chosen as an example of GHGs to evaluate the proposed approach. Two sentinel satellites (sentinel-2 and sentinel-5P) provide multiscale observations of GHGs from 10-60m resolution (sentinel-2) to ~kilometer scale resolution (sentinel-5P). Among multiple deep learning (DL) architectures evaluated, two best DL models demonstrate that key features of spatio-temporal satellite data and additional information (e.g., observation times and/or coordinates of ground stations) can be extracted using convolutional neural networks and feed forward neural networks, respectively. In particular, irregular time series data from different NO 2 observation stations limit the flexibility of long short-term memory architecture, requiring zero-padding to fill in missing data. However, deep neural operator (DNO) architecture can stack time-series data as input, providing the flexibility of input structure without zero-padding. As a result, the DNO outperformed other deep learning architectures to account for time-varying features. Overall, temporal patterns with smooth seasonal variations were predicted very well, while frequent fluctuation patterns were not predicted well. In addition, uncertainty quantification using conformal inference method is performed to account for prediction ranges. Overall, this research will lead to a new groundwork for estimating greenhouse gas concentrations using multiple satellite data to enhance our capability of tracking the cause of climate change and developing mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

Investigation of the fracture mechanics of boride composites

Fracture energies of WC-6Co, Boride 5 (ZrB2+SiC), Boride 8(ZrB2+SiC+C) and Boride 8-M2(ZrB2+SiC+C) were measured by slow bend and impact tests of notched charpy bars. Cobalt bonded tungsten carbide exhibited impact energies of 0.76 ft-lb or 73.9 in-lb/square inch. Boride 5 and the Boride 8 exhibit impact energies one third and one quarter of that observed for WC-6Co comparing favorably with measurements for SiC and Si3N4. Slow bend-notched bar-fracture energies for WC-6Co were near 2.6 in-lb/square inch or 1/20 the impact energies. Slow bend energies for Boride 8-M2, Boride 8 and Boride 5 were 58%, 42% and 25% of the value observed for WC-6Co. Fractograph showed differences for WC-6Co where slow bend testing resulted in smooth transgranular cleavage while samples broken by impact exhibited intergranular failures. By contrast the boride fractures showed no distinction based on testing method. Fabrication studies were conducted to effect alteration of the boride composites by alloying and introduction of graphite cloth.

Kaufman, L.↗

Comparison of atmospheric density data from mass spectrometers and atmospheric drag on the Aeros satellites

The comparison of perigee density data near 230 km for satellite Aeros-A has been extended to the complete mission time. The average ratio between orbital drag derived density and mass spectrometer measurements is very near to 1 with a large scatter reflected by a standard deviation of the order of 20%. A method of comparison was developed and tested which uses the observed rate of change of orbital period in comparison with the orbital decay computed from the actual mass spectrometer data measured at discrete positions along the orbit. This method proves that deviations from the average ratio of 1 between perigee densities from drag and mass spectrometers are due to the smoothing and poor resolution of the orbital drag technique.

Roemer, M.↗

Velocity-space synthesis of ISEE-1 measurements of the three dimensional electron distribution function

A computer package which produces contour plots of the three dimensional electron distribution function measured by an electron spectrometer aboard ISEE-1 is described. Examples of the contour plots and an explanation of how to use the program, including the necessary computer code for running the program on the GSFC 360/91 computer is presented. The method by which the discrete measurements of the distribution function, given by points on the four dimensional surface are synthesized into a smooth surface in a three dimensional space which can be contoured is described. The velocity components are parallel and perpendicular to the magnetic field, respectively, in the proper frame of the electrons.

Fitzenreiter, R. J.↗

A mathematical model for efficient estimation of aircraft motions

In the usual formulation of the aircraft state-estimation problem, motions along a flight trajectory are represented by a plant consisting of nonlinear state and measurement models. Problem solution using this formulation requires that both state- and measurement-dependent Jacobian matrices be evaluated along any trajectory. In this paper it is shown that a set of state variables can be chosen to realize a linear state model of very simple form, such that all nonlinearities appear in the measurement model. The potential advantage of the new formulation is computational: the Jacobian matrix corresponding to a linear state model is constant, a feature that should outweigh the fact that the measurement model is more complicated than in the conventinal formulation. To compare the modeling methods, aircraft motions from typical flight-test and accident data were estimated, using each formulation with the same off-line (smoothing) algorithm. The results of these experiments, reported in the paper, demonstrate clearly the computational superiority of the linear state-variable formulation. The procedure advocated here may be extended to other nonlinear estimation problems, including on-line (filtering) applications.

Bach, R. E., Jr.↗

Noniterative three-dimensional grid generation using parabolic partial differential equations

A new algorithm for generating three-dimensional grids has been developed and implemented which numerically solves a parabolic partial differential equation (PDE). The solution procedure marches outward in two coordinate directions, and requires inversion of a scalar tridiagonal system in the third. Source terms have been introduced to control the spacing and angle of grid lines near the grid boundaries, and to control the outer boundary point distribution. The method has been found to generate grids about 100 times faster than comparable grids generated via solution of elliptic PDEs, and produces smooth grids for finite-difference flow calculations.

Edwards, T. A.↗