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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Characterization of 3D printing filaments containing metal additives and their particulate emissions

Polylactic acid (PLA) filaments are widely used in fused filament fabrication (FFF) processes (3D printing). Filament additives such as metallic particles incorporated into PLA to modify functional and aesthetic features of print objects are becoming increasingly popular. However, the identities and concentrations of low percentage and trace metals in these filaments have not been well described in either the literature or product safety information included with the product. Here, we report the structures and concentrations of metals in selected Copperfill, Bronzefill and Steelfill filaments. We also report size-weighted number concentrations and size-weighted mass concentrations of particulate emissions as a function of print temperature for each filament. Particulate emissions were heterogenous in shape and size with airborne particles below 50 nm diameter dominating the size-weighted particle concentrations and larger particles (approximately 300 nm) dominating the mass weighted particle concentration. Results indicate that potential exposure to particles in the nano-size range increase when using print temperatures above 200o C. Because inhalation exposure to nanoparticles has been linked to adverse health outcomes, we suggest that using lower print temperatures for specific metal-fill filaments may reduce their operational hazard.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recursion relations for 5-point conformal blocks

We consider 5-point functions in conformal field theories in d2 dimensions. Using weight-shifting operators, we derive recursion relations which allow for the computation of arbitrary conformal blocks appearing in 5-point functions of scalar operators, reducing them to a linear combination of blocks with scalars exchanged. We additionally derive recursion relations for the conformal blocks which appear when one of the external operators in the 5-point function has spin 1 or 2. Our results allow us to formulate positivity constraints using 5-point functions which describe the expectation value of the energy operator in bilocal states created by two scalars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1984

The ADS general-purpose optimization program

The mathematical statement of the general nonlinear optimization problem is given as follows: find the vector of design variables, X, that will minimize f(X) subject to G sub J (x) + or - 0 j=1,m H sub K hk(X) = 0 k=1,l X Lower I approx less than X sub I approx. less than X U over I i = 1,N. The vector of design variables, X, includes all those variables which may be changed by the ADS program in order to arrive at the optimum design. The objective function F(X) to be minimized may be weight, cost or some other performance measure. If the objective is to be maximized, this is accomplished by minimizing -F(X). The inequality constraints include limits on stress, deformation, aeroelastic response or controllability, as examples, and may be nonlinear implicit functions of the design variables, X. The equality constraints h sub k(X) represent conditions that must be satisfied precisely for the design to be acceptable. Equality constraints are not fully operational in version 1.0 of the ADS program, although they are available in the Augmented Lagrange Multiplier method. The side constraints given by the last equation are used to directly limit the region of search for the optimum. The ADS program will never consider a design which is not within these limits.

Vanderplaats, G. N.↗
DOE OSTI2022

An efficient decoder for a linear distance quantum LDPC code

Recent developments have shown the existence of quantum low-density parity check (qLDPC) codes with constant rate and linear distance. A natural question concerns the efficient decodability of these codes. In this paper, we present a linear time decoder for the recent quantum Tanner codes construction of asymptotically good qLDPC codes, which can correct all errors of weight up to a constant fraction of the blocklength. Our decoder is an iterative algorithm which searches for corrections within constant-sized regions. At each step, the corrections are found by reducing a locally defined and efficiently computable cost function which serves as a proxy for the weight of the remaining error.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

Formation Flight System Extremum-Seeking-Control Using Blended Performance Parameters

An extremum-seeking control system for formation flight that uses blended performance parameters in a conglomerate performance function that better approximates drag reduction than performance functions formed from individual measurements. Generally, a variety of different measurements are taken and fed to a control system, the measurements are weighted, and are then subjected to a peak-seeking control algorithm. As measurements are continually taken, the aircraft will be guided to a relative position which optimizes the drag reduction of the formation. Two embodiments are discussed. Two approaches are shown for determining relative weightings: "a priori" by which they are qualitatively determined (by minimizing the error between the conglomerate function and the drag reduction function), and by periodically updating the weightings as the formation evolves.

Ryan, John J.↗
DOE OSTI2024

RESIN: Responsible Innovation for Highly Recyclable Plastics - TASK 4: Risk Assessment Framework

This report covers the entirety of Task 4, but its main purpose is to deliver milestones ML4.4 and ML4.5, the last two SOPO milestones under Task 4. ML4.4 reports on the compatibility of polymer properties that affect both environmental performance and functional performance and the tradeoffs involved in turning these properties to the benefit of each. ML4.5 presents a complete set of information on the critical properties of benign target products, where benign products are defined as those with the shortest environmental lifetime which meet performance requirements. To support and provide context to the discussions of ML4.4 and ML4.5 and to provide a complete picture of Task 4, milestones 4.1-4.3 are briefly summarized at the beginning of the report. The discussion of ML4.4 introduces the notion of polymer persistence as a proxy for environmental risk. It then discusses the development and comparison of two machine leaning models explored for estimating polymer degradation rates, a random forest (RF) classifier and an RF regressor. Given the advantage of continuous outputs rather than simple classes, the RF regressor was incorporated in the Excel risk calculator, which to this point could implement the objectives of subtasks 4.1-4.3, estimating polymer release and redistribution. The ML4.4 discussion then addresses the effect of each of the three polymer features used by the RF regressor on polymer functional performance. These features are number molecular weight (Mn), glass transition temperature (T g ) and heat of fusion (H fus ). The discussion of ML4.5 reviews the conceptual framework of the risk model, which served as the foundation for developing the Excel risk calculator and describes the use of, and assumptions within, the calculator. Appendix A is further provided as a user’s guide for the calculator. To demonstrate how the calculator is intended to be used by developers in the design of low-risk polymers, an analysis of 27 hypothetical polymers defined by varying values for the three polymer features used by the RF regressor is presented. The range of parameter values selected produces estimates of polymer degradation rates and lifetimes that may be typical of various consumer products made from polyurethane polymers and shows how changes in polymer features affect lifetimes. The demonstration also predicts the final distribution of released polymer materials in environmental compartments as a function of consumer product mix and assumed leakage rates of end-of-life processes. Lastly, this report summarizes the achievement of Task 4 goals from original conception to final delivery and discusses how and to what degree to which each subtask goal was achieved.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression

Here, we use Gaussian stochastic weight averaging (SWAG) to assess the epistemic uncertainty associated with neural-network-based function approximation relevant to fluid flows. SWAG approximates a posterior Gaussian distribution of each weight, given training data, and a constant learning rate. Having access to this distribution, it is able to create multiple models with various combinations of sampled weights, which can be used to obtain ensemble predictions. The average of such an ensemble can be regarded as the 'mean estimation', whereas its standard deviation can be used to construct 'confidence intervals', which enable us to perform uncertainty quantification (UQ) with regard to the training process of neural networks. We utilize representative neural-network-based function approximation tasks for the following cases: (i) a two-dimensional circular-cylinder wake; (ii) the DayMET dataset (maximum daily temperature in North America); (iii) a three-dimensional square-cylinder wake; and (iv) urban flow, to assess the generalizability of the present idea for a wide range of complex datasets. SWAG-based UQ can be applied regardless of the network architecture, and therefore, we demonstrate the applicability of the method for two types of neural networks: (i) global field reconstruction from sparse sensors by combining convolutional neural network (CNN) and multi-layer perceptron (MLP); and (ii) far-field state estimation from sectional data with two-dimensional CNN. We find that SWAG can obtain physically-interpretable confidence-interval estimates from the perspective of epistemic uncertainty. This capability supports its use for a wide range of problems in science and engineering.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Thermo-oxidative stability studies of PMR-15 polymer matrix composites reinforced with various fibers

An experimental study was conducted to measure the thermo-oxidative stability of PMR-15 polymer matrix composites reinforced with various fibers and to observe differences in the way they degrade in air. The fibers that were studied included graphite and the thermally stable Nicalon and Nextel ceramic fibers. Weight loss rates for the different composites were assessed as a function of mechanical properties, specimen geometry, fiber sizing, and interfacial bond strength. Differences were observed in rates of weight loss, matrix cracking, geometry dependency, and fiber-sizing effects. It was shown that Celion 6000 fiber-reinforced composites do not exhibit a straight-line Arrhenius relationship at temperatures above 316 C.

Bowles, Kenneth J.↗
NASA NTRS1990

Thermo-oxidative stability studies of PMR-15 polymer matrix composites reinforced with various continuous fibers

An experimental study was conducted to measure the thermooxidative stability of PMR-15 composites reinforced with various fibers and to observe differences in the way they degrade in air. The fibers studied include graphite and the thermally stable Nicalon and Nextel ceramic fibers. Weight-loss rates for the different composites were assessed as a function of mechanical properties, specimen geometry, fiber sizing, and interfacial bond strength. Differences were observed in rates of weight loss, matrix cracking, geometry dependency, and fiber sizing effects. It was shown that Celion 6000 fiber-reinforced composites do not exhibit a straight-line Arrhenius relationship at temperatures above 316 C.

Bowles, Kenneth J.↗
NASA NTRS1981

Surface temperatures and glassy state investigations in tribology, part 4

Measurements were made of the limiting shear stress for two naphthenic oils of differing molecular weight and three blends of the lower molecular weight oil and polyalkylmethacrylate polymers of differing molecular weight. The two base oils reached the same limiting shear stress for the same temperature and pressure. This was also true for all the polymer solutions although the polymer reduced the limiting shear stress by about 15 percent. It is shown that limiting stress is more a function of material type than viscosity or molecular weight. A new falling body viscometer was constructed to operate to 230 C and 0.6 GPa. Another viscometer was constructed to extend the pressure range to 1.1 GPa. A concentrated contact simulator was developed which allows recording of the traction force while the slide-roll ratio is continuously varied and the rolling speed is maintained essentially constant by a single drive motor. The configuration is that of a crowned roller against a disk. Measurement of lubricant minimum film thickness of elliptical EHD contacts of various aspect ratios were made by optical interferometry. The data collected were used to evaluate the Hamrock and Dowson minimum film thickness model over a range of contract ellipticity ratio where the major axis of the contact ellipse was aligned both parallel and perpendicular to the direction of motion. A statistical analysis of the measured film thickness data showed that on the average the experimental data were 30 percent greater than the film thickness predicted by the model. Preliminary development of the application of a scanning infrared radiation system to a tribo-system was completed.

Bair, S. S.↗
DOE OSTI2025

Uncertainty propagation in feed-forward neural network models

We develop new uncertainty propagation methods for feed-forward neural network architectures with leaky ReLU activation functions subject to random perturbations in the input vectors. In particular, we derive analytical expressions for the probability density function (PDF) of the neural network output and its statistical moments as a function of the input uncertainty and the parameters of the network, i.e., weights and biases. A key finding is that an appropriate linearization of the leaky ReLU activation function yields accurate statistical results even for large perturbations in the input vectors. This can be attributed to the way information propagates through the network. We also propose new analytically tractable Gaussian copula surrogate models to approximate the full joint PDF of the neural network output. To validate our theoretical results, we conduct Monte Carlo simulations and a thorough error analysis on a multi-layer neural network representing a nonlinear integro-differential operator between two polynomial function spaces. Our findings demonstrate excellent agreement between the theoretical predictions and Monte Carlo simulations.

MLP networks↗
NASA NTRS2003

Artificial Neural Network with Hardware Training and Hardware Refresh

A neural network circuit is provided having a plurality of circuits capable of charge storage. Also provided is a plurality of circuits each coupled to at least one of the plurality of charge storage circuits and constructed to generate an output in accordance with a neuron transfer function. Each of a plurality of circuits is coupled to one of the plurality of neuron transfer function circuits and constructed to generate a derivative of the output. A weight update circuit updates the charge storage circuits based upon output from the plurality of transfer function circuits and output from the plurality of derivative circuits. In preferred embodiments, separate training and validation networks share the same set of charge storage circuits and may operate concurrently. The validation network has a separate transfer function circuits each being coupled to the charge storage circuits so as to replicate the training network s coupling of the plurality of charge storage to the plurality of transfer function circuits. The plurality of transfer function circuits may be constructed each having a transconductance amplifier providing differential currents combined to provide an output in accordance with a transfer function. The derivative circuits may have a circuit constructed to generate a biased differential currents combined so as to provide the derivative of the transfer function.

Tuan A Duong↗
NASA NTRS2017

Methods of Constructing a Blended Performance Function Suitable for Formation Flight

Two methods for constructing performance functions for formation fight-for-drag-reduction suitable for use with an extreme-seeking control system are presented. The first method approximates an a prior measured or estimated drag-reduction performance function by combining real-time measurements of readily available parameters. The parameters are combined with weightings determined from a minimum squares optimization to form a blended performance function.

control systems↗
DOE OSTI2022

Universal suppression of superfluid weight by non-magnetic disorder in $s$-wave superconductors independent of quantum geometry and band dispersion

Motivated by the experimental progress in controlling the properties of the energy bands in superconductors, significant theoretical efforts have been devoted to study the effect of the quantum geometry and the flatness of the dispersion on the superfluid weight. In conventional superconductors, where the energy bands are wide and the Fermi energy is large, the contribution due to the quantum geometry is negligible, but in the opposite limit of flat-band superconductors the superfluid weight originates purely from the quantum geometry of Bloch wave functions. Here, we study how the energy band dispersion and the quantum geometry affect the disorder-induced suppression of the superfluid weight. In particular, we consider non-magnetic disorder and s-wave superconductivity. Surprisingly, we find that the disorder-dependence of the superfluid weight is universal across a variety of models, and independent of the quantum geometry and the flatness of the dispersion. Our results suggest that a flat-band superconductor is as resilient to disorder as a conventional superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1997

Enhanced Multiobjective Optimization Technique for Comprehensive Aerospace Design

A multidisciplinary design optimization procedure which couples formal multiobjectives based techniques and complex analysis procedures (such as computational fluid dynamics (CFD) codes) developed. The procedure has been demonstrated on a specific high speed flow application involving aerodynamics and acoustics (sonic boom minimization). In order to account for multiple design objectives arising from complex performance requirements, multiobjective formulation techniques are used to formulate the optimization problem. Techniques to enhance the existing Kreisselmeier-Steinhauser (K-S) function multiobjective formulation approach have been developed. The K-S function procedure used in the proposed work transforms a constrained multiple objective functions problem into an unconstrained problem which then is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Weight factors are introduced during the transformation process to each objective function. This enhanced procedure will provide the designer the capability to emphasize specific design objectives during the optimization process. The demonstration of the procedure utilizes a computational Fluid dynamics (CFD) code which solves the three-dimensional parabolized Navier-Stokes (PNS) equations for the flow field along with an appropriate sonic boom evaluation procedure thus introducing both aerodynamic performance as well as sonic boom as the design objectives to be optimized simultaneously. Sensitivity analysis is performed using a discrete differentiation approach. An approximation technique has been used within the optimizer to improve the overall computational efficiency of the procedure in order to make it suitable for design applications in an industrial setting.

Chattopadhyay, Aditi↗
NASA NTRS2002

A Deterministic Interfacial Cyclic Oxidation Spalling Model: Algebraic Approximation, Descriptive Parameters, and Normalized Universal Curve - Part 2

A cyclic oxidation interfacial spalling model has been developed in Part 1. The governing equations have been simplified here by substituting a new algebraic expression for the series (Good-Smialek approximation). This produced a direct relationship between cyclic oxidation weight change and model input parameters. It also allowed for the mathematical derivation of various descriptive parameters as a function of the inputs. It is shown that the maximum in weight change varies directly with the parabolic rate constant and cycle duration and inversely with the spall fraction, all to the 1/2 power. The number of cycles to reach maximum and zero weight change vary inversely with the spall fraction, and the ratio of these cycles is exactly 1:3 for most oxides. By suitably normalizing the weight change and cycle number, it is shown that all cyclic oxidation weight change model curves can be represented by one universal expression for a given oxide scale.

Smialek, James L.↗
DOE OSTI2023

The star-formation history in the last 10 billion years from CIB cross-correlations

ABSTRACT The cosmic infrared background (CIB) traces the emission of star-forming galaxies throughout all cosmic epochs. Breaking down the contribution from galaxies at different redshifts to the observed CIB maps would allow us to probe the history of star formation. In this paper, we cross-correlate maps of the CIB with galaxy samples covering the range z ≲ 2 to measure the bias-weighted star-formation rate (SFR) density 〈bρSFR〉 as a function of time in a model independent way. This quantity is complementary to direct measurements of the SFR density ρSFR, giving a higher weight to more massive haloes, and thus provides additional information to constrain the physical properties of star formation. Using cross-correlations of the CIB with galaxies from the DESI Legacy Survey and the extended Baryon Oscillation Spectroscopic Survey, we obtain high signal-to-noise ratio measurements of 〈bρSFR〉, which we then use to place constraints on halo-based models of the star-formation history. We fit halo-based SFR models to our data and compare the recovered ρSFR with direct measurements of this quantity. We find a qualitatively good agreement between both independent data sets, although the details depend on the specific halo model assumed. This constitutes a useful robustness test for the physical interpretation of the CIB, and reinforces the role of CIB maps as valuable astrophysical probes of the large-scale structure. We report our measurements of 〈bρSFR〉 as well as a thorough account of their statistical uncertainties, which can be used to constrain star-formation models in combination with other data.

Astronomy & Astrophysics↗
DOE OSTI2020

Selectively Depolymerizable Polyurethanes from Unsaturated Polyols Cleavable by Olefin Metathesis

This communication describes a novel series of linear and crosslinked polyurethanes (PUs) and their selective depolymerization under mild conditions. Two unique polyols are synthesized bearing unsaturated units in a configuration designed to favor ring-closing metathesis (RCM) to five- and six-membered cycloalkenes. These polyols are co-polymerized with toluene diisocyanate to generate linear PUs and trifunctional hexamethylene- and diphenylmethane-based isocyanates to generate crosslinked PUs. The polyol design is such that the RCM reaction cleaves the backbone of the polymer chain. Upon exposure to dilute solutions of Grubbs’ catalyst under ambient conditions, the PUs are rapidly depolymerized to low molecular weight, soluble products bearing vinyl and cycloalkene functionalities. These functionalities enable further re-polymerization by traditional strategies for polymerization of double bonds. We anticipate that this general approach can be expanded to develop a range of chemically recyclable condensation polymers that are readily depolymerized by orthogonal metathesis chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗