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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Formulation and implementation of a practical algorithm for parameter estimation with process and measurement noise

A new formulation is proposed for the problem of parameter estimation of dynamic systems with both process and measurement noise. The formulation gives estimates that are maximum likelihood asymptotically in time. The means used to overcome the difficulties encountered by previous formulations are discussed. It is then shown how the proposed formulation can be efficiently implemented in a computer program. A computer program using the proposed formulation is available in a form suitable for routine application. Examples with simulated and real data are given to illustrate that the program works well.

Maine, R. E.↗
NASA NTRS1983

Formulation of a practical algorithm for parameter estimation with process and measurement noise

A new formulation is proposed for the problem of parameter estimation in dynamic systems with both process and measurement noise. The formulation applies to continuous-time state space system models with discrete-time measurements. Previous formulations of this problem encountered several theoretical and practical difficulties which are overcome by the new formulation. The most important element of the new formulation is a reparameterization of the unknown noise covariances. A computer program that implements the new formulation is available.

Maine, R. E.↗
DOE OSTI2020

The Influence of Printing Parameters, Post-Processing, and Testing Conditions on the Properties of Binder Jetting Additive Manufactured Functional Ceramics

This article outlines the current state-of-the-art binder jetting (BJT) additive manufacturing of functional ceramics. The impact of printing parameters, heat treatment processing, and testing conditions on the observed performance of these ceramics is discussed. Additionally, this article discusses the impact of physical properties such as density and mechanical strength on the overall performance of these functional ceramics. Although printing parameters and initial feedstock are crucial for the printability of the desired parts, other factors play an important role in the performance of the ceramic. Thermal post-processing is crucial to achieve optimized functional properties, while the testing orientation is key to obtaining the maximum output from the part. Finally, future research directions for this field are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Processing and flammability parameters of bismaleimide and some other thermally stable resin matrices for composites

The effect of processing variables on the flammability and mechanical properties of state-of-the-art and advanced resin matrices for graphite composites were studied. Resin matrices which were evaluated included state-of-the-art epoxy, phenolic-novolac, phenolic-Xylok, two types of bismaleimides, benzyl, polyethersulfone, and polyphenylsulfone. Comparable flammability and thermochemical data on graphite-reinforced laminates prepared with these resin matrices are presented, and the relationship of some of these properties to the anaerobic char yield of the resins is described.

Kourtides, D. A.↗
DOE OSTI2024

Robust Iterative Method for Symmetric Quantum Signal Processing in All Parameter Regimes

Here, this paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on quantum computers. Symmetric QSP focuses on representing target polynomials as products of matrices in SU(2) that possess symmetry properties. We present a novel Newton’s method tailored for efficiently solving the nonlinear system involved in determining the phase factors within the symmetric QSP framework. Our method demonstrates rapid and robust convergence in all parameter regimes, including the challenging scenario with ill-conditioned Jacobian matrices, using standard double precision arithmetic operations. For instance, solving symmetric QSP for a highly oscillatory target function α cos(1000x) (polynomial degree ≈ 1433) takes 6 iterations to converge to machine precision when α = 0.9, and the number of iterations only increases to 18 iterations when α = 1 – 10 -9 with a highly ill-conditioned Jacobian matrix. Leveraging the matrix product state structure of symmetric QSP, the computation of the Jacobian matrix incurs a computational cost comparable to a single function evaluation. Moreover, we introduce a reformulation of symmetric QSP using real-number arithmetics, further enhancing the method’s efficiency. Extensive numerical tests validate the effectiveness and robustness of our approach, which has been implemented in the QSPPACK software package.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Redox-Electrodialysis Model with Zero Fitting Parameters: Insights into Process Limitations, Design, and Material Interventions

Redox-Electrodialysis (r-ED) is an electrochemical desalination cell architecture that has recently received considerable interest, due to its low energy demand relative to electrochemical desalination technologies that rely on electrode-based ion removal. To further improve the energy efficiency of r-ED, we developed a lumped mathematical model with no adjustable parameters to investigate the various sources of overpotential within the cell. Existing models of electrodialysis and r-ED cells either do not accurately incorporate all phenomena contributing to the overpotential or utilize empirical fitting parameters. The model developed here indicates that ohmic overpotentials, especially in the diluate chamber, are the most significant contributors to energy losses. Based on this insight, we hypothesized that adding an ion exchange resin wafer in the diluate compartment would increase the ionic conductivity and decrease the energy demand. Experimental results showed an 18% reduction in specific energy use while achieving the same degree of salt removal (20 mM to 12 mM). Furthermore, the resin wafer enabled complete desalination to potable drinking levels at a current density previously unachievable within practical operating voltage limits (4.93 mA cm -2 ). We also expanded the model to explore differences in r-ED energy use between configurations using multiple cells and a single cell with increased area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Optimization of screw design for continuous wet granulation: A case study of metoprolol succinate ER tablets

This study aimed at understanding the effect of screw design on the critical characteristics of granules and tablets of an extended-release (ER) formulation for twin screw granulation process. The screw design parameters assessed included number of kneading elements (KEs) per kneading zone, distance separating kneading zones, staggering angle (SA) of kneading elements and number of sizing elements (SEs). These input variables were varied using a design of experiment (DoE) approach to manufacture granules. Particle size distribution (PSD), flow and bulk properties of the granules, breaking strength and dissolution of tablets manufactured using these granules were characterized. The results of least square fitting showed that KEs, SA, and SEs of the screws significantly (p -values < 0.05) affected the PSD, cohesion, compressibility (CPS), conditioned bulk density (CBD) and permeability of the granules. The KEs and SEs significantly (p -value < 0.05) affected the dissolution, which was attributed to their effects on CPS and CBD of the granules. The distance between kneading zones had no significant effect on granules and tablet characteristics. Finally, these results may be used to further study the interaction of the identified critical screw design parameters with other processing parameters for continuous manufacturing of this ER matrix-based tablet formulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Severity factor kinetic model as a strategic parameter of hydrothermal processing (steam explosion and liquid hot water) for biomass fractionation under biorefinery concept

Hydrothermal processes are an attractive clean technology and cost-effective engineering platform for bio-refineries based in the conversion of biomass to biofuels and high-value bioproducts under the basis of sustainability and circular bioeconomy. The deep and detailed knowledge of the structural changes by the severity of biomasses hydrothermal fractionation is scientifically and technological needed in order to improve processes effectiveness, reactors designs, and industrial application of the multi-scale target compounds obtained by stream explosion and liquid hot water systems. The concept of the severity factor [log 10 (R 0 )] established > 30 years ago, continue to be a useful index that can provide a simple description of the relationship between the operational conditions for biomass fractionation in second generation of biorefineries. Furthermore, this review develops a deep explanation of the hydrothermal severity factor based in lignocellulosic biomass fractionation with emphasis in research advances, pretreatment operations and the applications of severity factor kinetic model.

09 BIOMASS FUELS↗
NASA NTRS1988

Experiences in extraction of contact parameters from process-evaluation test-structures

Six-terminal-contact test structures are introduced for characterizing ohmic contacts between a metal and a heavily doped semiconductor layer. Specifically, the six-terminal test structure supplies the additional information needed in order to calculate the transmission length and eventual corrections to the characteristic resistance per unit width due to finite contact length. The essential feature of this test structure is a square contact with four taps in the lower (semiconductor) layer. Every other one of these taps is used for current injection ('front'). From the voltage drop at the opposite tap and the side taps, the 'end' resistance and the 'side' resistances are calculated. The test structures are shown to give valuable information complementary to the common front resistance measurements. The interfacial resistivity is obtained directly after proper correction for flange effects.

Lieneweg, Udo↗
DOE OSTI2022

A new multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential processes under process model and parametric uncertainty

Process-based models have been widely used for hydrologic modeling, and it is a common practice to use sensitivity analysis methods for excluding non-influential hydrologic processes from further investigation and/or model improvement. This study develops a new method called multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential system processes and parameters. MMADS is conceptually similar to the Morris method for addressing parametric uncertainty, but has a unique feature to address both process model uncertainty (i.e., a process may be represented by multiple process models) and process model parameter uncertainty (i.e., parameters associated with a process model are random). MMADS first evaluates absolute differences of a quantity of interest (i.e., a system model output) by varying process models and/or process model parameter values, and then calculates the mean and variance of the differences for investigating process influence. The mean measures overall influence of the process on the quantity of interest, and the variance estimates influence of nonlinear effects of the process and/or its interactions with other processes. MMADS is an extension of the Morris method from a parameter space to a joint parameter-model space for explicitly addressing both process model uncertainty and model parameter uncertainty. The performance of MMADS is evaluated by using two numerical experiments. One experiment is based on Sobol’s G*-function with ten product elements, and has analytical solutions of the MMADS mean and variance of absolute differences. The other experiment is for groundwater flow modeling which considers three processes (i.e., recharge, geology, and snowmelt) that interact with each other. Finally, results indicate that MMADS is computationally efficient and can identify non-influential processes of complex hydrological systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

A moving-window parameter adaptive control system for the F8-DFBW aircraft

This paper describes the moving-window parameter adaptive control system developed for the NASA F8-DFBW aircraft. The control system employs a parameter identification process that, iteratively, adjusts parameters of a model of the aircraft motions in a batch processing manner so that responses generated from the model fit the outputs of sensors stored in a finite record referred to as the moving window. Tests are made on the validity of the parameter estimates before using the parameters in an on-line design process. The on-line design process is an algebraic mapping of the parameters of the model into primary control system feedback and feedforward gains. The mapping was selected to satisfy specific flying quality characteristics over the range of parameter variations expected. Results are presented from simulation studies on the identification algorithm, tests for parameter validity, and the on-line design process.

Montgomery, R. C.↗