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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Signs of nonmonotonic finite-volume corrections to 𝑔 𝐴

We study finite-volume (FV) corrections to determinations of 𝑔 𝐴 via lattice quantum chromodynamics (QCD) using analytic results and numerical analysis. We observe that 𝑆⁢𝑈⁡(2) heavy Baryon chiral perturbation theory does not provide an unambiguous prediction for the sign of the FV correction, which is not surprising when one also considers large-𝑁 𝑐 constraints on the axial couplings. We further show that nonmonotonic FV corrections are naturally allowed when one considers either including explicit Δ-resonance degrees of freedom or one works to higher orders in the chiral expansion. We investigate the potential impact of these FV corrections with a precision study of 𝑔 𝐴 using models of FV corrections that are monotonic and nonmonotonic. Using lattice QCD data that is approximately at the 1% level of precision, we do not see significant evidence of nonmonotonic corrections. Looking forward to the next phase of lattice QCD calculations, we estimate that calculations that are between the 0.1% and 1% level of precision may be sensitive to these FV artifacts. Finally, we present an update of the CalLat prediction of 𝑔 𝐴 in the isospin limit with subpercent precision, 𝑔$^{QCD}_{𝐴}$ = 1.2674⁢(96).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Towards Robustness Guarantees for Feedback-Based Optimization

Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.

approximation algorithms↗
DOE OSTI2020

Influence of Tabula Rasa on Process- and Light-Induced Degradation of Solar Cells Fabricated From Czochralski Silicon

Monocrystalline Si solar cells are fabricated from Czochralski (Cz) Si, which contains 10 17 –10 18 cm -3 oxygen atoms. Cz Si undergoes degradation during high-temperature thermal processing steps, such as dopant diffusion to form the p - n junction. This degradation in the bulk minority carrier lifetime can be related to the formation of oxygen precipitates. We found that a high-temperature annealing process known as tabula rasa (TR) not only mitigates process-induced degradation via oxygen precipitate nuclei dissolution, but also modifies subsequent light-induced degradation. We report on the bulk carrier lifetime of n - and p -type Cz Si after TR, which homogenizes the interstitial oxygen in the bulk Si to its monoatomic form in either an N 2 or O 2 environment. A control sample, which was not subjected to a TR processing step, experienced severe process-induced degradation during a boron emitter thermal budget as oxygen precipitates were formed in the Si bulk. These precipitates could be imaged using photoluminescence. Additionally, samples that underwent a TR processing step prior to the boron emitter thermal budget show efficient gettering of metallic impurities compared to the control sample, which showed a decline in the implied open-circuit voltage after the gettering step. Furthermore, modification of the interstitial oxygen bonding by TR had a strong effect on the light-induced degradation kinetics. Instead of a typically observed monotonic decrease, minority carrier lifetime increases first, followed by a nonmonotonic decrease over a ~20 h period. Finally, we conclude that by modifying the interstitial oxygen bonding via TR pretreatment, p -type Cz Si wafers become substantially resistant to harsh solar cell processes and strongly modified light-induced degradation, which would open alternative ways to mitigate this degradation mechanism.

14 SOLAR ENERGY↗
DOE OSTI2020

Grid-Forming Frequency Shaping Control for Low-Inertia Power Systems

As power systems transit to a state of high renewable penetration, little or no presence of synchronous generators makes the prerequisite of well-regulated frequency for grid-following inverters unrealistic. As such, there is a trend to resort to grid-forming inverters which set frequency directly. We propose a novel grid-forming frequency shaping control that is able to shape the aggregate system frequency dynamics into a first-order one with the desired steady-state frequency deviation and Rate of Change of Frequency (RoCoF) after a sudden power imbalance. The no overshoot property resulting from the first-order dynamics allows the system frequency to monotonically move towards its new steady-state without experiencing frequency Nadir, which largely improves frequency security. We prove that our grid-forming frequency-shaping control renders the system internally stable under mild assumptions. The performance of the proposed control is verified via numerical simulations on a modified Icelandic Power Network test case.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Enhancing Electron Microscopy Image Classification Using Data Augmentation

Manual labeling for machine learning tasks such as image classification is tedious and labor-intensive; as a result, scientific datasets suitable for deep learning applications are scarce and limited. While data augmentation techniques have shown promise for extending image datasets, very little work has been done to understand the impact of combining multiple augmentation methods sequentially or the limits of their effectiveness when combined. Our work addresses this gap by examining how standard and combinatorial data augmentation affects the performance of machine learning models when trained on small datasets for label classification tasks. For our analysis, we generate single, double and quadruple-augmented datasets for a microscopy image classification task using six standard augmentation methods, and compare the resultant improvements observed in binary classification accuracy with three standard image classification models (DenseNet169, MobileNetV2, ResNet101V2). Our experiments show a non-monotonic relationship between the number of simultaneous augmentation methods and classification accuracy, indicating that there is a trade-off between the degree of augmentation and the model performance. These findings suggest that the optimal number of augmentation methods will vary by domain and use case. We also find that the order in which augmentation methods are applied to a limited dataset matters when combining augmentation schemes, with our use case showing performance differences up to 2.6% when the augmentation order is reversed for double-augmented datasets. Our work offers insights to the limits of data augmentation when working on image classification tasks with limited datasets.

Welsman, Jordan A↗
DOE OSTI2023

An Incremental Gradient Method for Optimization Problems With Variational Inequality Constraints

We consider minimizing a sum of agent-specific nondifferentiable merely convex functions over the solution set of a variational inequality (VI) problem in that each agent is associated with a local monotone mapping. This problem finds an application in computation of the best equilibrium in nonlinear complementarity problems arising in transportation networks. We develop an iteratively regularized incremental gradient method where at each iteration, agents communicate over a directed cycle graph to update their solution iterates using their local information about the objective and the mapping. The proposed method is single-timescale in the sense that it does not involve any excessive hard-to-project computation per iteration. We derive nonasymptotic agent-wise convergence rates for the suboptimality of the global objective function and infeasibility of the VI constraints measured by a suitably defined dual gap function. Finally, the proposed method appears to be the first fully iterative scheme equipped with iteration complexity that can address distributed optimization problems with VI constraints over cycle graphs.

convergence↗
DOE OSTI2022

Numerical Solution of the Steady-State Network Flow Equations for a Non-Ideal Gas

Herein we formulate a steady-state network flow problem for non-ideal gas that relates injection rates and nodal pressures in the network to flows in pipes. For this problem, we present and prove a theorem on uniqueness of generalized solution for a broad class of non-ideal pressure-density relations that satisfy a monotonicity property. Further, we develop a Newton-Raphson algorithm for numerical solution of the steady-state problem, which is made possible by a systematic non-dimensionalization of the equations. The developed algorithm has been extensively tested on benchmark instances and shown to converge robustly to a generalized solution. Previous results [1]-[4], indicate that the steady-state network flow equations for an ideal gas are difficult to solve by the Newton-Raphson method because of its extreme sensitivity to the initial guess. In contrast, we find that non-dimensionalization of the steady-state problem is key to robust convergence of the Newton-Raphson method. We identify criteria based on the uniqueness of solutions under which the existence of a non-physical generalized solution found by a non-linear solver implies non-existence of a physical solution, i.e., infeasibility of the problem. Finally, we compare pressure and flow solutions based on ideal and non-ideal equations of state to demonstrate the need to apply the latter in practice. The solver developed in this article is open-source and is made available for both the academic and research communities as well as the industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Decentralized Market Mechanism for Energy Communities under Operating Envelopes

Here, we propose an operating envelopes (OEs) aware energy community market mechanism that dynamically charges/rewards its members based on two-part pricing. The OEs are imposed exogenously by a regulated distribution system operator (DSO) on the energy community's revenue meter and is subject to a generalized net energy metering (NEM) tariff design. By formulating the interaction of the community operator and its members as a Stackelberg game, we show that the proposed two-part pricing achieves a Nash equilibrium and maximizes the community's social welfare in a decentralized fashion while ensuring that the community's operation abides by the OEs. The market mechanism conforms with the cost-causation principle and guarantees community members a surplus level no less than their maximum surplus when they autonomously face the DSO. The dynamic and uniform community price is a monotonically decreasing function of the community's aggregate renewable generation. We also analyze the impact of exogenous parameters such as NEM rates and OEs on the value of joining the community. Lastly, through numerical studies, we showcase the community's welfare, and pricing, and compare its members' surplus to customers under the DSO's regime.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Distributed Finite-Time Termination for Consensus Algorithm in Switching Topologies

Here, in this article, we present a finite-time stopping criterion for consensus algorithms in networks with dynamic communication topology. Prior state of the art has established convergence to the consensus value; however, the asymptotic convergence of these algorithms poses a challenge in practical settings where the response from agents is required in finite time. To this end, we propose a maximum-minimum protocol that propagates the global maximum and minimum values of agent states (while running the consensus algorithm) in the network. This article focuses on establishing that the global maximum and minimum values are strictly monotonic even for a dynamic topology, and they can be used to distributively ascertain the closeness to convergence in finite time. We rigorously show that each node can have access to the global maximum and minimum by running the proposed maximum-minimum protocol to realize a finite-time stopping criterion for the otherwise asymptotic consensus algorithm. The practical utility of the algorithm is illustrated through experiments where each agent is instantiated by a NodeJS socket.io server.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Output Capacitance Loss of GaN HEMTs in Steady-State Switching

The output capacitance (C OSS ) loss, a loss produced when the device’s output capacitor is charged and discharged, has become a concern for GaN high electron mobility transistors (HEMTs) in high-frequency applications. This work presents a new, easy-to-implement method for the C OSS loss characterization based on the unclamped inductive switching (UIS) setup. As compared to prior approaches, this method involves the device’s ON-state conduction and could measure the C OSS loss in a single pulse and the steady-state switching. The C OSS loss of three types of mainstream commercial GaN HEMTs is characterized, which exhibit some common dependencies including a non-monotonic relation with the dv/dt (or resonance frequency), a linear relation with the ON-state current, a power-law relation with the peak blocking voltage, and little temperature dependence. In addition, their C OSS losses all show minimal distinctions in a single pulse and the steady-state switching, despite the increased on-resistance in the steady-state switching. Furthermore, this suggests that the traps accounting for the C OSS loss possess different de-trapping time constants as compared to the traps governing the dynamic on-resistance. Finally, a unified model is established to describe the C OSS loss of all three types of GaN HEMTs. These results provide important references for the high-frequency application of GaN HEMTs and new insights into the physical origin of their C OSS loss.1

42 ENGINEERING↗
DOE OSTI2024

Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative Values

Non-negative matrix factorization (NMF) is a dimensionality reduction technique that has shown promise for analyzing noisy data, especially astronomical data. For these datasets, the observed data may contain negative values due to noise even when the true underlying physical signal is strictly positive. Prior NMF work has not treated negative data in a statistically consistent manner, which becomes problematic for low signal-to-noise data with many negative values. In this paper we present two algorithms, Shift-NMF and Nearly-NMF, that can handle both the noisiness of the input data and also any introduced negativity. Both of these algorithms use the negative data space without clipping or masking and recover non-negative signals without any introduced positive offset that occurs when clipping or masking negative data. We demonstrate this numerically on both simple and more realistic examples, and prove that both algorithms have monotonically decreasing update rules.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Inference for Nonparanormal Partial Correlation via Regularized Rank-Based Nodewise Regression

Abstract Partial correlation is a common tool in studying conditional dependence for Gaussian distributed data. However, partial correlation being zero may not be equivalent to conditional independence under non-Gaussian distributions. In this paper, we propose a statistical inference procedure for partial correlations under the high-dimensional nonparanormal (NPN) model where the observed data are normally distributed after certain monotone transformations. The NPN partial correlation is the partial correlation of the normal transformed data under the NPN model, which is a more general measure of conditional dependence. We estimate the NPN partial correlations by regularized nodewise regression based on the empirical ranks of the original data. A multiple testing procedure is proposed to identify the nonzero NPN partial correlations. The proposed method can be carried out by a simple coordinate descent algorithm for lasso optimization. It is easy-to-implement and computationally more efficient compared to the existing methods for estimating NPN graphical models. Theoretical results are developed to show the asymptotic normality of the proposed estimator and to justify the proposed multiple testing procedure. Numerical simulations and a case study on brain imaging data demonstrate the utility of the proposed procedure and evaluate its performance compared to the existing methods. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Rotational flexural strength of cylindrical brittle specimens

Conventional static flexural strength testing of brittle cylindrical rods only subjects a small fraction of the entire specimen's area or volume to the maximum tensile stress. Thus, a nonconservative measured strength likely results since most flaws on the surface or in the bulk are not subjected to a sufficiently high tensile stress that can cause fracture. Here, to mitigate this, a rotational flexural tester and corresponding test method were developed whereby rotation and monotonically increasing three-point flexure were superimposed to investigate fracture response of solid glass cylinders. This combination of rotation and flexure subjects more area and volume of a cylindrical test specimen to tensile stress than a standard static (nonrotating) flexural test. As anticipated, failure stresses were lower for the rotational flexural test. Expressions for effective area and volume are provided for rotating solid rods and tubes subjected to three-point, four-point, uniform, and uniformly distributed load bending configurations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Dynamics and Structure of Molten Neodymium Titanate

Binary rare earth titanates can be vitrified using levitation melt quenching, and their glasses are promising for optical applications. To better understand their thermophysical properties and dynamics, we have used molecular dynamics (MD) and empirical potential structure refinement (EPSR) to simulate molten neodymium titanate, 83TiO 2 –17Nd 2 O 3 . The models are compared with high-energy synchrotron X-ray diffraction of the melt structure over 1060–1960 K and thermophysical property measurements of electrostatically levitated droplets over 1500–2200 K. As temperature increases, the network periodicity increases and the correlation length decreases, both in monotonic trends that suggest continuous structural evolution through the melt and supercooled liquid regimes. At 1900 K, the mean Ti–O and Nd–O coordination numbers are 5.8(5) and 6.7(5), compared to the glass, 5.72(6) and 7.70(26). The equilibrium melting point is measured as 1860(20) K, over 100 K higher than previous estimates. Viscosity data from MD are in good agreement with experimental measurements. The dynamic propensity of Nd is similar to that of the network-forming Ti, suggesting that Nd does not participate as a conventional modifier. The viscosity of this fragile liquid is likely controlled by the breaking of cation–oxygen bonds and rearrangements of Ti–O polyhedra.

molecular dynamics↗
DOE OSTI2025

Direction of impact for explainable risk assessment modeling

Abstract Several graphical indicators have been recently introduced to help analysts visualize the marginal effects of inputs in complex models. The insights derived from such tools may help decision‐makers and risk analysts in designing interventions. However, we know little about the adequacy and consistency of different indicators. This work investigates popular marginal effect indicators to understand whether they yield indications consistent with the properties of the quantitative model under inspection. Specifically, we examine the notions of monotonicity, Lipschitz, and concavity consistency. Surprisingly, only PD functions satisfy all these notions of consistency. However, when selecting the indicators, in addition to consistency, analysts need to consider the risk of model extrapolation. For situations where such risk is under control, we utilize individual conditional expectations together with PD plots. Two applications, on a NASA space risk assessment model and a susceptible exposed infected recovered (SEIR) model for the COVID‐19 pandemic illustrate the insights obtained from these indicators.

Mathematical Methods In Social Sciences↗
DOE OSTI2021

Unexpected Scaling of Peak Acceleration for a Yielding Mass-Spring System Subjected to a Triangular Base Acceleration Pulse

The use of bounding scenarios is a common practice that greatly simplifies the design and qualification of structures. However, this approach implicitly assumes that the quantities of interest increase monotonically with the input to the structure, which is not necessarily true for nonlinear structures. This paper surveys the literature for observations of nonmonotonic behavior of nonlinear systems and finds such observations in both the earthquake engineering and applied mechanics literature. Numerical simulations of a single degree-of-freedom mass-spring system with an elastic–plastic spring subjected to a triangular base acceleration pulse are then presented, and it is shown that the relative acceleration of this system scales nonmonotonically with the input magnitude in some cases. The equation of motion for this system is solved symbolically and an approximate expression for the relative acceleration is developed, which qualitatively agrees with the nonmonotonic behavior seen in the numerical results. The nonmonotonicity is investigated and found to be a result of dynamics excited by the discontinuous derivative of the base acceleration pulse, the magnitude of which scales nonmonotonically with the input magnitude due to the fact that the first yield of the spring occurs earlier as the input magnitude is increased. The relevance of this finding within the context of defining bounding scenarios is discussed, and it is recommended that modeling be used to perform a survey of the full range of possible inputs prior to defining bounding scenarios.

42 ENGINEERING↗
DOE OSTI2023

Property-Graded Stainless Steel 316L by Selective Laser Melting: Characterization & Design

Abstract The purpose of this research work is to characterize and inform the design of (mechanical) property-graded bulk structures made from a single metallic alloy via a laser powder bed fusion (LPBF) process, with an end goal of creating repeatable/reproducible functionally-graded additively manufactured (FGAM) parts. This paper specifically investigates the manufacture of stainless steel (SS) 316L structures via a pulsed selective laser melting (SLM) process, and the underlying causes of property variations (within a functionally-acceptable range) through various material characterization techniques. For this, a design of experiments spanning the volumetric energy density (VED) based process parameter design space was utilized to investigate the range of functionally-acceptable physical/mechanical properties achievable in SS 316L. Five sample conditions (made via different process parameter combinations) were down-selected for in-depth microstructure analysis and mechanical/physical property characterization; these were suitably selected to impart a wide and controllable property range (209–318 HV hardness, 90–99.9% relative density, and 154–211 GPa modulus). It was observed that property variations resulted from combinations of porosity types/amounts, martensitic phase fractions, and grain sizes. Based on these findings, property-graded standard test specimens were designed and manufactured for further investigation—tensile specimens having a monotonic hardness change along its gauge length, four-point bending specimens with varying elastic moduli as a function of the distance from the neutral axis, and Moore’s rotating beam fatigue specimens with moduli variations based on the distance from the center. Altogether, this work lays the foundation for understanding and designing the local and global mechanical performance of FGAM bulk structures.

Engineering↗
DOE OSTI2024

Experimental Investigation of the Effect of Air-Handling and DME-Propane Blends on the Performance and Emissions of a 4-Cylinder CI Engine

Dimethyl ether (DME) is considered an excellent alternative to diesel because of its higher cetane number and lower carbon content. Additionally, DME can be blended with abundantly available propane with minimal modifications to the propane infrastructure. This paper focuses on an experimental investigation of the effect of air-handling i.e., boost pressure and exhaust gas recirculation (EGR), and DME-propane blends on the combustion and emissions performance of a light-duty, four-cylinder, compression ignition (CI) engine. Here, the boost pressure and EGR sweeps were carried out and showed that higher boost pressures resulted in increased brake thermal efficiencies (BTE) at the expense of higher NOx emissions which could be reduced by an increase in EGR. The fuel sweeps were carried out at 0, 15 and 25% propane (neat, 85% and 75% DME) with 0% and 25% EGR. The fuel sweeps indicated that the ignition delay (ID) increased and burn duration (BD) decreased monotonically when the blend increased to 25% propane/75% DME. The results suggest optimum engine performance with neat DME at 105 kPa boost pressure and 25% EGR with propane addition improving the BTE with negligible increase in emissions. Higher contents of Propane, up to 25%, did not affect the variability of combustion, with standard deviations of burn duration and peak cylinder pressures below 1% for all test cases.

air-handling↗