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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Simulations of Water Flow in Relation to a Steady Criticality in an Unsaturated Alluvial Repository

Oak Ridge National Laboratory (ORNL) is examining the conditions under which a criticality event could be ruled out for large packages placed in an unsaturated alluvial repository. This work specifically examines the water level in a stylized waste package that is assumed (1) to fail on the top, and (2) to empty as water is driven away—not by boiling—but by fluid flow phenomena driven by thermal gradients. This analysis uses the PFLOTRAN code package. Specifically, this year’s work includes examination of the heat rate at which water is driven away for various percolation rates using the same assumptions listed in the 2022 annual report. The STANDARDS (formerly UNF-ST&DARDS) package has predicted dual-purpose canister (DPC) neutron multiplication factors (k-effectives) ranging above 1.1 (unitless) with failed components. The DPC designs were not created with the intent to use for disposal purposes. Emplacing such packages may be worth consideration if it can be shown that criticality is either extremely unlikely or of very low consequence to the repository’s safety case. This work aims to help establish hydrologic boundary conditions for a highly hypothetical, highly stylized subsurface criticality event. The approach to critical is assumed to be slow, producing steady heating rates under a few kilowatts. For a DPC containing capillary media, the simulated power required for dry-out was proportional to the percolation rate but was unaffected by the size of a large breech on top of the DPC. Results for single cases with no capillary media in the DPC suggest that higher infiltration rates may be required in those cases to cause flooding. Bounding mechanisms and assumptions must be identified and characterized further by performing additional perturbations to various input parameters to demonstrate robustness of the results. This might be accomplished by examining responses to power pulses to determine the system transfer function required to enable a reduced order feedback model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Develop a new integrated macro→micro←nano (MMN) multiscale modeling framework to optimize high strength aluminum alloys and processes for vehicle light-weighting​

Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further understanding of the relationship between microstructure and fracture properties of high-strength 6000-series alloys. This work started with microstructural characterization in both mesoscale and nanoscale and bending performance characterization of AA6111 HS2-T6 alloy at Ford, the MMN framework was applied to this alloy to simulate 3-point VDA bending. From the results of the macro-modeling of 3-point VDA bending, the critical region of fracture was identified, and the region geometry was used to construct the micro-model. The fracture criterion of micron-scale precipitates and aluminum matrix which contains submicron and nano particles (AL-SMP-NP) in the micro-model was calibrated and validated by comparing simulated and measured bending results. With the AL-SMP-NP fracture strain obtained, the fracture strain of Al-matrix containing nano particles (ALNP) will similarly be determined by a submicron scale-model using an edge-constrained FE modeling approach developed by Hu et al. With the ALNP fracture strain obtained, the fracture strain of Al-matrix containing no particles will similarly be determined by a nano scale-model using an edge-constrained FE modeling approach. After the MMN framework is built and fracture criterion calibrated, nano-model FE simulations with virtual microstructures was performed to obtain a reduced order model (ROM) of the fracture criterion of the ALNP as a function of volume fraction, size, and distribution of the nanoparticle. This nano→submicron→micro modeling part allows exploration of the influence of different material nanostructures from different process conditions on the bending properties within the multiscale bending simulation framework and the ROM of material bendability as a function of nanoparticle size and shape was established. This obtained reduced order model (ROM) could help guide the design and selection of materials to improve existing SPR process models that could replace trial-and-error rivet/die selection and help to design new rivet/die combinations capable of robustly joining new higher strength 6000 5 series alloys in automotive body structures. This would enable lightweighting of Ford vehicles leading to greater fuel efficiency and reduce manufacturing time and energy.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Extensional flow convecting a reactant undergoing a first order homogeneous reaction and diffusional mass transfer from a sphere at low to intermediate Peclet and Damkohler numbers

Forced convective diffusion-reaction is considered for viscous axisymmetric extensional convecting velocity in the neighborhood of a sphere. For Peclet numbers in the range 0.1 less than or equal to Pe less than or equal to 500 and for Damkohler numbers increasing with increasing Pe but in the overall range 0.02 less than or equal to Da less than or equal to 10, average and local Sherwood numbers have been computed. By introducing the eigenfunction expansion c(r, Theta) = Sum of c(n)(r)P(n)(cos Theta) into the forced convective diffusion equation for the concentration of a chemical species undergoing a first order homogeneous reaction and by using properties of the Legendre functions Pn(cos Theta), the variable coefficient PDE can be reduced to a system of N + 1 second order ODEs for the radial functions c(sub n)(r), n = 0, 1, 2,..., N. The adaptive grid algorithm of Pereyra and Lentini can be used to solve the corresponding 2(N + 1) first order differential equations as a two-point boundary value problem on 1 less than or equal to r less than or equal to r(sub infinity). Convergence of the expansion for a specific value of N can thus be established and provides 'spectral' behavior as well as the full concentration field c(r, Theta).

Shah, N. Y.↗
DOE OSTI2021

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗
NASA NTRS1995

The point spread function of the soft X-ray telescope aboard Yohkoh

The point spread function of the SXT telescope aboard Yohkoh has been measured in flight configuration in three different X-ray lines at White Sands Missile Range. We have fitted these data with an elliptical generalization of the Moffat function. Our fitting method consists of chi squared minimization in Fourier space, especially designed for matching of sharply peaked functions. We find excellent fits with a reduced chi squared of order unity or less for single exposure point spread functions over most of the CCD. Near the edges of the CCD the fits are less accurate due to vignetting. From fitting results with summation of multiple exposures we find a systematic error in the fitting function of the order of 3% near the peak of the point spread function, which is close to the photon noise for typical SXT images in orbit. We find that the full width to half maximum and fitting parameters vary significantly with CCD location. However, we also find that point spread functions measured at the same location are consistent to one another within the limit determined by photon noise. A 'best' analytical fit to the PSF as function of position on the CCD is derived for use in SXT image enhancemnent routines. As an aside result we have found that SXT can determine the location of point sources to about a quarter of a 2.54 arc sec pixel.

Martens, Petrus C.↗
DOE OSTI2023

Social support and cognitive function in Chinese older adults who experienced depressive symptoms: is there an age difference?

Objective This study examined the moderating effect of overall social support and the different types of social support on cognitive functioning in depressed older adults. We also investigated whether the moderating effect varied according to age. Methods A total of 2,500 older adults (≥60 years old) from Shanghai, China were enrolled using a multistage cluster sampling method. Weighted linear regression and multiple linear regression was utilized to analyze the moderating effect of social support on the relationship between depressive symptoms and cognitive function and to explore its differences in those aged 60–69, 70–79, and 80 years and above. Results After adjusting for covariates, the results indicated that overall social support (β = 0.091, p = 0.043) and support utilization (β = 0.213, p < 0.001) moderated the relationship between depressive symptoms and cognitive function. Support utilization reduced the possibility of the cognitive decline in depressed older adults aged 60–69 years (β = 0.310, p < 0.001) and 80 years and above (β = 0.199, p < 0.001), while objective support increased the possibility of cognitive decline in depressed older people aged 70–79 years (β = −0.189, p < 0.001). Conclusion Our findings highlight the buffering effects of support utilization on cognitive decline in depressed older adults. We suggest that age-specific measures should be taken when providing social support to depressed older adults in order to reduce the deterioration of cognitive function.

Jing, Yurong↗
DOE OSTI2023

Use of Sobol’ Variance-Based Global Sensitivity Analysis and Multidimensional Legendre Polynomial Fitting for Reduced Order Modeling

Sandia National Laboratories (SNL) has developed a novel reduced order modeling approach. Prioritization of inputs is accomplished using Sobo' indices obtained through a more efficient variance-based global sensitivity analysis. To determine the Sobo' functions, simulated input values are aligned to collocation points to permit the use of Gauss-Lobatto integration, thereby reducing the number of simulation trials needed by more than an order of magnitude compared to standard Monte Carlo approaches. Furthermore, by leveraging the orthogonality of Legendre polynomials in conjunction with those same simulations at the collocation nodes, an efficient fitting method is developed to represent the Sobo' functions from which a reduced order model (ROM) is constructed. The developed method is both more efficient computationally, and the resulting ROM is more accurate. The efficacy of this technique is demonstrated on a nonlinear polynomial test function as well as the nonlinear Ishigami and Sobo' g functions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Adjoint-Based Methodology for Time-Dependent Optimization

This paper presents a discrete adjoint method for a broad class of time-dependent optimization problems. The time-dependent adjoint equations are derived in terms of the discrete residual of an arbitrary finite volume scheme which approximates unsteady conservation law equations. Although only the 2-D unsteady Euler equations are considered in the present analysis, this time-dependent adjoint method is applicable to the 3-D unsteady Reynolds-averaged Navier-Stokes equations with minor modifications. The discrete adjoint operators involving the derivatives of the discrete residual and the cost functional with respect to the flow variables are computed using a complex-variable approach, which provides discrete consistency and drastically reduces the implementation and debugging cycle. The implementation of the time-dependent adjoint method is validated by comparing the sensitivity derivative with that obtained by forward mode differentiation. Our numerical results show that O(10) optimization iterations of the steepest descent method are needed to reduce the objective functional by 3-6 orders of magnitude for test problems considered.

Yamaleev, N. K.↗
DOE OSTI2021

Discrete Empirical Interpolation Method Based Dynamic Load Model Reduction

Dynamic load models add significant complexity to bulk power system time-domain simulations. The complexity is due to the large number of ordinary differential equations (ODEs) introduced by the dynamic load components such as induction motors. It is challenging to derive reduced-order models (ROMs) for dynamic loads due to the nonlinear functions in their governing equations. This paper applies the discrete empirical interpolation method enhanced proper orthogonal decomposition (DEIM-POD) to approximate the full dynamic load model with the ROM that minimizes the projection error of the nonlinear functions in dynamic load ODEs onto their dominant modes. This approach only requires evaluation of nonlinear functions at selected observation points. The observation points selected by DEIM also provide information for screening critical load buses where dynamic load model parameters contribute the most to the accuracy of ROM across multiple contingencies. The proposed approach is validated on IEEE 9-bus, WECC 179-bus and 2384-bus Polish systems.

bulk power system↗
NASA NTRS1983

Broadband transmission functions for atmospheric IR flux computations and climate studies

In order to reduce the size of precomputed tables which are used in the emissivity approach to computing IR radiation in a climate model, the three-dimensional transmission function in the water vapor bands is defined in this study by a simple regression equation consisting of three two-dimensional parameters. The transmittances in the 9.6 and 15 micron bands are individually parameterized as functions of the amount of scaled absorber. This approach can thus be applied to atmospheres with a variable CO2 concentration.

Chou, M.-D.↗
DOE OSTI2023

Single-Particle Measurements Reveal the Origin of Low Solar-to-Hydrogen Efficiency of Rh-Doped SrTiO 3 Photocatalysts

Solar-powered photochemical water splitting using suspensions of photocatalyst nanoparticles is an attractive route for economical production of green hydrogen. SrTiO 3 -based photocatalysts have been intensely investigated due to their stability and recently demonstrated near-100% external quantum yield (EQY) for water splitting using wavelengths below 360 nm. To extend the optical absorption into the visible, SrTiO 3 nanoparticles have been doped with various transition metals. Here, in this work, we demonstrate that doping SrTiO 3 nanoparticles with 1% Rh introduces midgap acceptor states which reduce the free electron concentration by 5 orders of magnitude, dramatically reducing built-in potentials which could otherwise separate electron–hole (e–h) pairs. Rhodium states also function as recombination centers, reducing the photocarrier lifetime by nearly 2 orders of magnitude and the maximum achievable EQY to 10%. Furthermore, the absence of built-in electric fields within Rh-doped SrTiO 3 nanoparticles suggests that modest e–h separation can be achieved by exploiting a difference in mobility between electrons and holes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Ramp Technology and Intelligent Processing in Small Manufacturing

To address the issues of excessive inventories and increasing procurement lead times, the Navy is actively pursuing flexible computer integrated manufacturing (FCIM) technologies, integrated by communication networks to respond rapidly to its requirements for parts. The Rapid Acquisition of Manufactured Parts (RAMP) program, initiated in 1986, is an integral part of this effort. The RAMP program's goal is to reduce the current average production lead times experienced by the Navy's inventory control points by a factor of 90 percent. The manufacturing engineering component of the RAMP architecture utilizes an intelligent processing technology built around a knowledge-based shell provided by ICAD, Inc. Rules and data bases in the software simulate an expert manufacturing planner's knowledge of shop processes and equipment. This expert system can use Product Data Exchange using STEP (PDES) data to determine what features the required part has, what material is required to manufacture it, what machines and tools are needed, and how the part should be held (fixtured) for machining, among other factors. The program's rule base then indicates, for example, how to make each feature, in what order to make it, and to which machines on the shop floor the part should be routed for processing. This information becomes part of the shop work order. The process planning function under RAMP greatly reduces the time and effort required to complete a process plan. Since the PDES file that drives the intelligent processing is 100 percent complete and accurate to start with, the potential for costly errors is greatly diminished.

Rentz, Richard E.↗
DOE OSTI2022

Design and optimization of supersonic turbines for detonation combustors

Detonation-based engines offer a potential surge in efficiency for compact thermal power systems. However, these cycles require ad-hoc components adapted to the high outlet velocity from the detonation combustors. This paper presents the design methodology of turbine stages suitable for supersonic inlet conditions and provides a detailed analysis of optimized turbine geometries. A reduced-order solver examines the supersonic blade rows’ functional design space, quantifies the turbine’s non-isentropic performance, and budgets the turbine loss for different optimized leading-edge designs and chord to pitch ratios. The shock-wave interactions were identified as the predominant contributor to turbine losses, and optimal pitch-chord ratios were determined for various inlet Mach numbers. Finally, with this tool, the specific-power output for a wide range of design configurations was computed; and the metal angle that ensures flow starting and maximizes power extraction was calculated. The detailed numerical study describes the flow interactions in a supersonic turbine and offers new correlations to guide the design of future supersonic turbines.

42 ENGINEERING↗
NASA NTRS1991

Closed-loop transfer recovery with observer-based controllers. II - Design

The paper focuses on the design problem related to the recovery of a target closed-loop transfer function using both full-order and reduced-order observer-based controllers. Design schemes for the reduced-order observer-based controllers are similar to those of full-order controllers; hence, for simplicity, only the case for full-order observer-based controller designs is given. Three types of design schemes are discussed in detail. The first one is an asymptotic time-scale eigenstructure assignment method, and the other two are optimization-based methods where a certain norm of the recovery matrix is minimized. Asymptotic behavior associated with each design method is highlighted. Relative advantages and disadvantages of both the ATEA and optimization-based schemes are discussed. A numerical example is used to illustrate the design possibilities from each of these methods, the available design freedom, and the significance of selecting the limit of the recovery matrix, especially in the case of a nonrecoverable design.

Chen, Ben M.↗
NASA NTRS2006

Dynamic Snap-Through of Thin-Walled Structures by a Reduced Order Method

The goal of this investigation is to further develop nonlinear modal numerical simulation methods for application to geometrically nonlinear response of structures exposed to combined high intensity random pressure fluctuations and thermal loadings. The study is conducted on a flat aluminum beam, which permits a comparison of results obtained by a reduced-order analysis with those obtained from a numerically intensive simulation in physical degrees-of-freedom. A uniformly distributed thermal loading is first applied to investigate the dynamic instability associated with thermal buckling. A uniformly distributed random loading is added to investigate the combined thermal-acoustic response. In the latter case, three types of response characteristics are considered, namely: (i) small amplitude vibration around one of the two stable buckling equilibrium positions, (ii) intermittent snap-through response between the two equilibrium positions, and (iii) persistent snap-through response between the two equilibrium positions. For the reduced order analysis, four categories of modal basis functions are identified including those having symmetric transverse (ST), anti-symmetric transverse (AT), symmetric in-plane (SI), and anti-symmetric in-plane (AI) displacements. The effect of basis selection on the quality of results is investigated for the dynamic thermal buckling and combined thermal-acoustic response. It is found that despite symmetric geometry, loading, and boundary conditions, the AT and SI modes must be included in the basis as they participate in the snap-through behavior.

Przekop, Adam↗
NASA NTRS2007

Dynamic Snap-Through of Thermally Buckled Structures by a Reduced Order Method

The goal of this investigation is to further develop nonlinear modal numerical simulation methods for application to geometrically nonlinear response of structures exposed to combined high intensity random pressure fluctuations and thermal loadings. The study is conducted on a flat aluminum beam, which permits a comparison of results obtained by a reduced-order analysis with those obtained from a numerically intensive simulation in physical degrees-of-freedom. A uniformly distributed thermal loading is first applied to investigate the dynamic instability associated with thermal buckling. A uniformly distributed random loading is added to investigate the combined thermal-acoustic response. In the latter case, three types of response characteristics are considered, namely: (i) small amplitude vibration around one of the two stable buckling equilibrium positions, (ii) intermittent snap-through response between the two equilibrium positions, and (iii) persistent snap-through response between the two equilibrium positions. For the reduced-order analysis, four categories of modal basis functions are identified including those having symmetric transverse, anti-symmetric transverse, symmetric in-plane, and anti-symmetric in-plane displacements. The effect of basis selection on the quality of results is investigated for the dynamic thermal buckling and combined thermal-acoustic response. It is found that despite symmetric geometry, loading, and boundary conditions, the anti-symmetric transverse and symmetric in-plane modes must be included in the basis as they participate in the snap-through behavior.

Przekop, Adam↗
NASA NTRSDate not supplied

An Interactive MATLAB Program for Fitting Transfer Functions to Frequency Responses

A computer program called FRFit (Frequency Response Fitting) is described for fitting single-input single-output transfer function models to empirical frequency response data. The program is interactive in that the user specifies ``elementary factors'' (gain, delay, pure differentiators and integrators, and first- and second-order zeros and poles) by entering numerical values or moving sliders in a graphical user interface. A nonlinear optimization can then be performed to obtain maximum likelihood estimates of transfer function parameters and uncertainties to provide feedback on the modeling and refine estimates. Several examples are discussed, including the identification of aircraft pitch dynamics from simulation data and data reported in the literature, approximating Theodorsen's function of unsteady aerodynamics, and obtaining a reduced-order model of a computational fluid dynamics code describing the unsteady aerodynamics around an aeroelastic wing. The program has some usefulness as a teaching aid, and can be applied to model structure determination, reduced-order modeling, preliminary analysis, and simple system identification problems. The program was written in MATLAB and is planned for public release through the NASA Software Catalog.

System identification↗
DOE OSTI2024

Multiparticle integral and differential correlation functions

This paper formalizes the use of integral and differential cumulants for measurements of multiparticle event-by-event transverse momentum fluctuations, rapidity fluctuations, as well as net-charge fluctuations. This enables the introduction of multiparticle balance functions, defined based on differential correlation functions (factorial cumulants), that suppress two- and three-prong resonance decays effects and enable measurements of underlying long-range correlations obeying quantum number conservation constraints. These multiparticle balance functions satisfy simple sum rules determined by quantum number conservation. It is additionally shown that these multiparticle balance functions arise as an intrinsic component of high-order net-charge cumulants. This implies that the magnitude of these cumulants, measured in a specific experimental acceptance, is strictly constrained by charge conservation and primarily determined by the rapidity and momentum width of these balance functions. The paper also presents techniques to reduce the computation time of differential correlation functions up to order n = 10 based on the methods of moments. Published by the American Physical Society 2024

Physics↗