SEARCH · Engineering Papers

Results for “gradient methods”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Methods of three-dimensional electrophoretic deposition for ceramic and cermet applications and systems thereof

A product according to one embodiment includes a first layer having a first composition, a first microstructure, and a first density; and a second layer above the first layer, the second layer having: a second composition, a second microstructure, and/or a second density. A gradient in composition, microstructure, and/or density exists between the first layer and the second layer, and either or both of the first layer and the second layer comprise non-spherical particles aligned along a longitudinal axis thereof.

Rose, Klint A.↗

DOE OSTI2024

Localized Evaluation for Constructing Discrete Vector Fields

Topological abstractions offer a method to summarize the behavior of vector fields, but computing them robustly can be challenging due to numerical precision issues. One alternative is to represent the vector field using a discrete approach, which constructs a collection of pairs of simplices in the input mesh that satisfies criteria introduced by Forman's discrete Morse theory. While numerous approaches exist to compute pairs in the restricted case of the gradient of a scalar field, state-of-the-art algorithms for the general case of vector fields require expensive optimization procedures. This paper introduces a fast, novel approach for pairing simplices of two-dimensional, triangulated vector fields that do not vary in time. The key insight of our approach is that we can employ a local evaluation, inspired by the approach used to construct a discrete gradient field, where every simplex in a mesh is considered by no more than one of its vertices. Specifically, we observe that for any edge in the input mesh, we can uniquely assign an outward direction of flow. We can further expand this consistent notion of outward flow at each vertex, which corresponds to the concept of a downhill flow in the case of scalar fields. Working with outward flow enables a linear-time algorithm that processes the (outward) neighborhoods of each vertex one-by-one, similar to the approach used for scalar fields. Here, we couple our approach to constructing discrete vector fields with a method to extract, simplify, and visualize topological features. Empirical results on analytic and simulation data demonstrate drastic improvements in running time, produce features similar to the current state-of-the-art, and show the application of simplification to large, complex flows.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

An ab initio exciton model for singlet fission

Here we present an ab initio exciton model that extends the Frenkel exciton model and includes valence, charge-transfer, and multiexcitonic excited states. It serves as a general, parameter-free, yet computationally efficient and scalable approach for simulation of singlet fission processes in multichromophoric systems. A comparison with multiconfigurational methods confirms that our exciton model predicts consistent energies and couplings for the pentacene dimer and captures the correct physics. Calculations of larger pentacene clusters demonstrate the computational scalability of the exciton model and suggest that the mixing between local and charge-transfer excitations narrows the gap between singlet and multiexcitonic states. Local vibrations of pentacene molecules are found to facilitate singlet–multiexcitonic state-crossing and hence are important for understanding singlet fission. The exciton model developed in this work also sets the stage for further implementation of the nuclear gradients and nonadiabatic couplings needed for first principles nonadiabatic quantum molecular dynamics simulations of singlet fission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Quantification of Oxygen Vacancies in SrFe0.5Cr0.5O3−δ Thin Films: Correlating Lattice Expansion with Oxidation State Variability

Oxygen vacancies (VO), even in the dilute regime, can significantly impact the physical and chemical properties of complex oxides. It is however challenging to reliably detect and adequately quantify such defects in thin film samples where the VO concentration and distribution may further vary in response to interfacial strain. Here, we present a method to quantify VO concentrations in SrFe0.5Cr0.5O3−δ (SFCO) epitaxial thin films. Through coherent Bragg rod analysis, X-ray absorption spectroscopy, and theoretical modeling, we systematically correlate the c-axis lattice expansion detected in SFCO films with a VO concentration gradient. Our results reveal a nearly linear relationship between oxygen off-stoichiometry and out-of-plane lattice expansion in coherently strained SFCO films, with δ increasing from 0.32 to 0.52 and the lattice expanding by ∼1.0%. Moreover, a significant decrease in Cr oxidation state (from Cr5+ to Cr3+) is observed as the VO concentration increases, while the Fe oxidation state remains fixed at Fe3+. Our findings provide a reliable way to quantify oxygen stoichiometry in complex oxides, offering a pathway to design materials with precisely tailored structure–property relationships.

Hossain, Mohammad Delower↗

DOE OSTI2024

Stress field measurements using quantitative schlieren

Quantitative schlieren analysis is extended here to optically transparent solids in quasi-static and dynamic experiments to measure stress distributions. The quasi-static experiments in polymethyl methacrylate (PMMA) compared refraction angles and stress gradients calculated from schlieren images to the analytical Flamant solution of a line load on a half-space. The quantitative schlieren measurements of the stress field in the thin sample with a load compared well to the analytical solution. The analysis method was then extended to explosive induced shock waves in PMMA. The explosive induced response of PMMA was experimentally studied using high-speed schlieren to visualize the shock propagation in conjunction with Photon Doppler Velocimetry (PDV) to record surface velocity histories. The stress state estimated from the schlieren images was compared to the stress calculated from the PDV measurements. High-speed imaging limitations caused the shock wave to not be fully resolved in the images, but was resolved in the PDV measurement. The stress state behind the shock calculated from the high-speed images followed a similar trend to the stress calculated from the PDV measurements.

Physics↗

DOE OSTI2024

Reducing measurement costs by recycling the Hessian in adaptive variational quantum algorithms

Abstract Adaptive protocols enable the construction of more efficient state preparation circuits in variational quantum algorithms (VQAs) by utilizing data obtained from the quantum processor during the execution of the algorithm. This idea originated with Adaptive Derivative-Assembled Problem-Tailored variational quantum eigensolver (ADAPT-VQE), an algorithm that iteratively grows the state preparation circuit operator by operator, with each new operator accompanied by a new variational parameter, and where all parameters acquired thus far are optimized in each iteration. In ADAPT-VQE and other adaptive VQAs that followed it, it has been shown that initializing parameters to their optimal values from the previous iteration speeds up convergence and avoids shallow local traps in the parameter landscape. However, no other data from the optimization performed at one iteration is carried over to the next. In this work, we propose an improved quasi-Newton optimization protocol specifically tailored to adaptive VQAs. The distinctive feature in our proposal is that approximate second derivatives of the cost function are recycled across iterations in addition to optimal parameter values. We implement a quasi-Newton optimizer where an approximation to the inverse Hessian matrix is continuously built and grown across the iterations of an adaptive VQA. The resulting algorithm has the flavor of a continuous optimization where the dimension of the search space is augmented when the gradient norm falls below a given threshold. We show that this inter-optimization exchange of second-order information leads the approximate Hessian in the state of the optimizer to be consistently closer to the exact Hessian. As a result, our method achieves a superlinear convergence rate even in situations where the typical implementation of a quasi-Newton optimizer converges only linearly. Our protocol decreases the measurement costs in implementing adaptive VQAs on quantum hardware as well as the runtime of their classical simulation.

Ramôa, Mafalda (ORCID:0000000302187801)↗

DOE OSTI2020

AMPPED LDRD: Advanced Models of the Physics & Phenomena of Electrical Discharge.

This Laboratory Directed Research and Development (LDRD) project aimed at addressing an unmet need for physics-based models that enable prediction of electrical breakdown in the presence of high voltage gradients and real-world environments. This project focused on understanding coupled plasma-surface feedback phenomena critical to electrical discharge processes and design of breakdown voltages, breakdown times, and breakdown paths. New secondary electron emission and coupled plasma-surface measurement methods and models were developed. Highly reproducible discharge experiments were developed to provide current-voltage data as a function of time, and methods were developed to condition electrodes for predictable discharge. To assess plasma-surface feedback mechanisms, new surface physics capabilities, including measurement systems for local and global photoemission yield and ion-induced secondary electron emission yield were developed. Discharge models were developed to incorporate these yields for predicting discharge behavior to understand influence of surface physics on discharge current and time evolution, and methods to accelerate these simulations were demonstrated. A key finding was that the initiation process of a non-vacuum discharge appears highly dependent on photoemission at the cathode. Advanced diagnostics were developed, including spatial electrical field imaging, spectroscopy of plasmas, and high-speed imaging of discharge event s in metal and dielectric environments. These diagnostics and improved electrical models are a step toward enabling quantitative design margins, assurance of safety architectures, and implementation of novel materials and technologies for wide ranging energy and electronics applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Towards determination of the strong coupling $α_s(m_Z)$ from four-flavor lattice QCD using the continuous $β$-function method

The precise value of the strong coupling $α_s(m_{Z})$ at the $Z$-boson mass $m_{Z}$ is essential for high-energy phenomenology and precision tests of quantum chromodynamics (QCD). We present the status of a program targeting a $\sim 0.3\%$ determination of $α_s(m_{Z})$ using the renormalization group $β$-function in the infinite volume gradient flow scheme based on lattice QCD simulations of degenerate four-flavor highly improved staggered quark (HISQ) ensembles. In particular, we analyze both tree-level cutoff effects and finite-mass effects. We also outline the next steps of the analysis, including the infinite-volume and continuum extrapolations required for a precise determination of $α_s(m_Z)$.

Mandlecha, Yash (ORCID:000000020587962X)↗

DOE OSTI2026

Towards determination of the strong coupling $α_s(m_Z)$ from four-flavor lattice QCD using the continuous $β$-function method

Mandlecha, Yash [Michigan State U.; Michigan State↗

DOE OSTI2026

Review of SiC material development for nuclear fusion applications: Cross-cutting research and emerging opportunities

The SiC-based materials, particularly SiC-fiber-reinforced SiC matrix (SiC/SiC) composites, show strong potential for structural and functional applications in future fusion power plants because they can operate at high temperatures with a range of coolants and breeders, thereby enabling higher energy conversion efficiency. Here, this paper presents recent advancements in the development of SiC-based materials, focusing on processing techniques and material performance and resistance under fusion-relevant environments. The processing activities have emphasized near-net-shape fabrication and the joining of SiC subcomponents, with processing methods and material compositions informed by previous irradiation experiments on various grades of SiC. Research on irradiation effects has remained focused on degradation mechanisms and the microstructural optimization of SiC/SiC composites irradiated to high neutron damage levels. Analysis of irradiation defects in SiC has advanced via the application of cutting-edge characterization methods, among which Raman spectroscopy is becoming a common tool to assess atomic-scale chemical disorder. Fusion–fission crosscutting irradiation research has explored combined effects in SiC/SiC composites with application-relevant geometries, including bowing of SiC/SiC composite channels under neutron flux gradients, stress evolution in SiC/SiC composite tubes under through-thickness temperature gradients, and irradiation-enhanced corrosion in SiC. Finally, research opportunities for component testing and assessment under fusion-relevant conditions, in support of emerging concepts from the private fusion sector, are discussed.

Advanced manufacturing↗

DOE OSTI2025

Collisionless conduction in a high-beta plasma: a collision operator for whistler turbulence

The regulation of electron heat transport in high-β, weakly collisional, magnetized plasma is investigated. A temperature gradient oriented along a mean magnetic field can induce a kinetic heat-flux-driven whistler instability (HWI), which back-reacts on the transport by scattering electrons and impeding their flow. Previous analytical and numerical studies have shown that the heat flux for the saturated HWI scales as β$^{-1}_{e}$. These numerical studies, however, had limited scale separation and consequently large fluctuation amplitudes, which calls into question their relevance at astrophysical scales. To this end, we perform a series of particle-in-cell simulations of the HWI across a range of β$_e$ and temperature-gradient length scales under two different physical set-ups. The saturated heat flux in all of our simulations follows the expected β$^{-1}_{e}$ scaling, supporting the robustness of the result. We also use our simulation results to develop and implement several methods to construct an effective collision operator for whistler turbulence. The results point to an issue with the standard quasi-linear explanation of HWI saturation, which is analogous to the well-known 90° scattering problem in the cosmic-ray community. Despite this limitation, the methods developed here can serve as a blueprint for future work seeking to characterize the effective collisionality caused by kinetic instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Structure optimization with stochastic density functional theory

Linear-scaling techniques for Kohn–Sham density functional theory are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the localization of the density matrix or accurate embedding approaches, limiting their applicability. In contrast, stochastic density functional theory (sDFT) achieves linear- and sub-linear scaling by statistically sampling the ground state density without relying on embedding or imposing localization. In return, ground state observables, such as the forces on the nuclei, fluctuate in sDFT, making optimizing the nuclear structure a highly non-trivial problem. In this work, we combine the most recent noise-reduction schemes for sDFT with stochastic optimization algorithms to perform structure optimization within sDFT. We compare the performance of the stochastic gradient descent approach and its variations (stochastic gradient descent with momentum) with stochastic optimization techniques that rely on the Hessian, such as the stochastic Broyden–Fletcher–Goldfarb–Shanno algorithm. In conclusion, we further provide a detailed assessment of the computational efficiency and its dependence on the optimization parameters of each method for determining the ground state structure of bulk silicon with varying supercell dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Medium grain niobium SRF cavity production technology for science frontiers and accelerator applications

Herein we present the cost-effective production of superconducting radio frequency (SRF) cavities made of medium grain (MG) niobium (Nb) discs directly sliced from forged and annealed billet. This production method provides clean surface conditions and reliable mechanical characteristics with sub-millimeter average grain size resulting in stable SRF cavity production. We propose to apply this material to particle accelerator in the science and industrial applications. The science applications require high field gradients(≥ 30 MV/m) particularly in pulsed mode. The industrial applications require high $Q_0$ values with moderate gradients (~ 20 MV/m) in CW mode operation. This paper describes the MG Nb disc production recently demonstrated and discusses future prospects for application in advanced particle accelerators in the science and industrial applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Unification of nonequilibrium molecular dynamics and the mode-resolved phonon Boltzmann equation for thermal transport simulations

Nano-size confinement induces many intriguing non-Fourier heat conduction phenomena, such as nonlinear temperature gradients, temperature jumps near the contacts, and size-dependent thermal conductivity. Over the past decades, these effects have been studied and interpreted by nonequilibrium molecular dynamics (NEMD) and phonon Boltzmann transport equation (BTE) simulations separately, but no theory that unifies these two methods has ever been established. In this work, we unify these methods using a quantitative mode-level comparison and demonstrate that they are equivalent for various thermostats. We show that different thermostats result in different non-Fourier thermal transport characteristics due to the different mode-level phonon excitations inside the thermostats, which explains the different size-dependent thermal conductivities calculated using different reservoirs, even though they give the same bulk thermal conductivity. Specifically, the Langevin thermostat behaves like a thermalizing boundary in phonon BTE and provides mode-level thermal-equilibrium phonon outlets, while the Nose-Hoover chain thermostat and velocity rescaling method behave like biased reservoirs, which provide a spatially uniform heat generation and mode-level nonequilibrium phonon outlets. These findings explain why different experimental measurement methods can yield different size-dependent thermal conductivity. They also indicate that the thermal conductivity of materials can be tuned for various applications by specifically designing thermostats. Finally, the unification of NEMD and phonon BTE will largely facilitate the study of thermal transport in complex systems in the future by, e.g., replacing computationally unaffordable first-principles NEMD simulations with computationally less expensive spectral BTE simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Experiments On A Conduction Cooled Superconducting Radio Frequency Cavity With Field Emission Cathode

To achieve Ampere-class electron beam accelerators the pulse delivery rate need to be much higher than the typical photo injector repetition rate of the order of a few kilohertz. We propose here an injector which can, in principle, generate electron bunches at the same rate as the operating RF frequency. A conduction-cooled superconducting radio frequency (SRF) cavity operating in the CW mode and housing a field emission element at its region of high axial electric field can be a viable method of generating high-repetition-rate electron bunches. In this paper, we report the development and experiments on a conduction-cooled Nb3Sn cavity with a niobium rod intended as a field emitter support. The initial experiments demonstrate 0.4 MV/m average accelerating gradient, which is equivalent of peak gradient of 3.2 MV/m. The measured RF cavity quality factor is 1.4 x 10$^8$ slightly above our goal. The achieved field gradient is limited by the relatively low input RF power and by the poor coupling between the external power supply and the RF cavity. With ideal coupling the field gradient can be as high as 0.6 MV/m still below our goal of about 1 MV/m.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Anisotropic thermal-conductivity degradation in the phase-field method accounting for crack directionality

Dynamic loads applied to metals may lead to brittle or ductile fracture depending on the imposed strain rates, material properties, and specimen geometry. With an increase in the applied velocity, brittle to ductile failure mode transition may also be observed. Furthermore, at high strain rates, ductile fracture may be preceded by shear bands, which are narrow bands of intense plastic deformation, typically accompanied by a significant rise in temperature. Reliable models are needed to predict the response of metals subject to dynamic loads. In particular, capturing the interplay between heat conduction and crack propagation using the phase-field fracture method is still an open research field. To accurately capture the heat transfer physics across crack surfaces, damage models degrading thermal-conductivity are necessary. While isotropic thermal-conductivity degradation models were proposed, they may lead to errors as they are indifferent to crack directionality. In our current work, a new anisotropic approach is proposed in which thermal-conductivity, which depends on the phase-field gradient, is degraded solely across the crack. Here, it is shown that this approach improves the near-field approximation of temperature and heat flux compared with isotropic degradation, when taking the discontinuous crack solutions as reference. Additionally, the anisotropic degradation approach is implemented in a unified dynamic fracture model and a couple of examples demonstrate the viability of this approach.

42 ENGINEERING↗