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Results for “Shape Optimization”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Evaluation and comparison of an adaptive method technique for improved performance of linear Fresnel secondary designs

As a line-focus concentrating solar power (CSP) technology, linear Fresnel collectors have the potential to become a low-cost solution for electricity production and a variety of thermal energy applications. However, this technology often suffers from relatively low performance. A secondary reflector is a key component used to improve optical performance of a linear Fresnel collector. The shape of a secondary reflector is particularly critical in determining solar power captured by the absorber tube(s), and thus, the collector's optical performance. However, to the authors' knowledge, no well-established process existed to derive the optimal secondary shape prior to the development of a new adaptive method to optimize the secondary reflector shape. The new adaptive method does not assume any pre-defined analytical form; rather, it constitutes an optimum shape through an adaptive process by maximizing the energy collection onto the absorber tube. In this paper, the adaptive method is compared with popular secondary-reflector designs with respect to a collector's optical performance under various scenarios. For the first time, a comprehensive, in-depth comparison was conducted on all popular secondary designs for CSP applications. In conclusion, it is shown that the adaptive design exhibits the best optical performance.

14 SOLAR ENERGY↗
DOE OSTI2022

Practical guide to understanding goodness-of-fit metrics used in chemical state modeling of x-ray photoelectron spectroscopy data by synthetic line shapes using nylon as an example

Chemical state analysis of a sample surface through fitting bell-shaped curves to x-ray photoelectron spectroscopic polymer data is reviewed using nylon to introduce and discuss aspects of data analysis. Different strategies for modeling chemistry in nylon spectra are presented and in so doing, a case is made to include in published science the design logic and implementation in terms of line shapes and optimization parameter constraints between components in a peak model. Imperfections in line shape relative to the true shape for photoemission lines, when compensated for using constraints to optimization parameters, are shown to provide chemical state information about a sample that justify, for peak models constructed with these limitations, metrics for goodness-of-fit different from those expected for pulse-counted data.

Materials Science↗
DOE OSTI2019

Laser wakefield acceleration with active feedback at 5 Hz

We describe the use of a genetic algorithm to apply active feedback to a laser wakefield accelerator at a higher power (10 TW) and a lower repetition rate (5 Hz) than previous work. The temporal shape of the drive laser pulse was adjusted automatically to optimize the properties of the electron beam. By changing the software configuration, different properties could be improved. This included the total accelerated charge per bunch, which was doubled, and the average electron energy, which was increased from 22 to 27 MeV. Using experimental measurements directly to provide feedback allows the system to work even when the underlying acceleration mechanisms are not fully understood, and, in fact, studying the optimized pulse shape might reveal new insights into the physical processes responsible. Our work suggests that this technique, which has already been applied with low-power lasers, can be extended to work with petawatt-class laser systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Suppressing trapped-electron-mode-driven turbulence via optimization of three-dimensional shaping

Abstract Turbulent transport driven by trapped electron modes (TEMs) is believed to drive significant heat and particle transport in quasihelically symmetric stellarators. Two three-dimensionally-shaped magnetic configurations with suppressed TEM-driven turbulence were generated through optimization that targeted quasihelical symmetry and the available energy of trapped electrons. Initial equilibria have flux surface shapes with a helically rotating negative triangularity (NT) and positive triangularity (PT). In gyrokinetic simulations, TEMs are suppressed in the reduced-TEM NT and PT configurations, showing that NT does not have the same beneficial turbulence properties over PT as seen in tokamaks. Heat fluxes from TEMs are also suppressed. Without temperature gradients and with a strong density gradient, the most unstable modes at low k y were consistent with toroidal universal instabilities (UIs) in the NT case and slab UIs in the PT case. Nonlinear simulations show that UIs drive substantial heat flux in both the NT and PT configurations. A moderate increase in β halves the heat flux in the NT configuration, while suppressing the heat flux in the PT geometry. Based on the present work, future optimizations aimed at reducing electrostatic drift wave-driven turbulent transport will need to consider UIs if β is sufficiently small.

Duff, J. M. (ORCID:0000000153086694)↗
DOE OSTI2020

Fourier Analysis Method for Wireless Power Transfer Coil Design

Wireless power transfer (WPT) systems for Electric Vehicles (EVs) are designed to meet specifications such as stray field, power transfer, efficiency, and ground clearance. Typical design approaches include iterative analysis of predetermined coil geometries to identify candidates that meet these constraints. This work instead directly generates WPT coil shapes and magnetic fields to meet specifications and constraints through the optimization of Fourier basis function coefficients. The proposed Fourier Analysis Method (FAM) applies to arbitrary planar coil geometries and does not rely on iterative finite-element analysis (FEA) simulations. This flexibility allows for rapid design evaluation across a larger range of coil geometries and design specifications. A prototype coil is built to compare FAM outputs to experimental measurements and FEA simulations. The FAM is then used to illustrate the tradeoff of coil current and stray field for a given power level showing that the method is capable of generating optimized coil shapes to meet arbitrary field constraints.

Foote, Andrew↗
DOE OSTI2026

Observable optimization for precision theory: machine learning energy correlators

The practice of collider physics typically involves the marginalization of multi-dimensional collider data to uni-dimensional observables relevant for some physics task. In many cases, such as classification or anomaly detection, the observable can be arbitrarily complicated, such as the output of a neural network. However, for precision measurements, the observable must correspond to something computable systematically beyond the level of current simulation tools. In this work, we demonstrate that precision-theory-compatible observable space exploration can be systematized by using neural simulation-based inference techniques from machine learning. We illustrate this approach by exploring the space of marginalizations of the energy 3-point correlator to optimize sensitivity to the top quark mass. We first learn the energy-weighted probability density from simulation, then search in the space of marginalizations for an optimal triangle shape. Although simulations and machine learning are used in the process of observable optimization, the output is an observable definition which can be then computed to high precision and compared directly to data without any memory of the computations which produced it. We find that the optimal marginalization is isosceles triangles on the sphere with a side ratio approximately $1 : 1 : \sqrt{2}$ (i.e. right triangles) within the set of marginalizations we consider.

Jets and Jet Substructure↗
DOE OSTI2024

Compatibility of divertor detachment and ELM suppression in DIII-D high- β p plasmas with ITER-similar shape

Abstract Integration of transient and steady-state divertor heat fluxes control with a high-performance core is necessary for future fusion reactors. In recent DIII-D high- β p experiments, divertor detachment and simultaneous edge localized mode (ELM) suppression are demonstrated while the plasma confinement quality is maintained high in ITER-similar shape. By optimizing the neon injection in high- β p scenario with ITER-similar shape, deep detachment and ELM suppression are achieved with a high-performance core ( β N ∼ 2.8, β p ∼ 2.3) at q 95 ∼ 7.5. Partial divertor detachment and suppression of large ELMs are achieved at q 95 ∼ 6. The stability analyses suggest that with low neon injection, the density pedestal becomes higher and steeper and the T i profile also increases, therefore the increased edge pressure and higher current density destabilize the Peeling-Ballooning mode (PBM), which would lead to a large ELM collapse. With strong neon gas puffing, the significantly reduced pedestal pressure and current density, due to the degraded T e pedestal, lead to the stabilization of PBM and ELMs are suppressed. For both cases, the coupling between the large radius internal transport barrier (ITB) and edge pedestal is the key reason for maintaining high global performance. The formation of large radius ITB compensates for pedestal degradation. Such results could provide an attractive scenario to well control the transient and steady-state heat flux onto the divertor plates while maintaining good plasma performance, which is an important step toward the steady-state operation of future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Multivariate Bayesian Optimization of CoO Nanoparticles for CO 2 Hydrogenation Catalysis

The hydrogenation of CO 2 holds promise for transforming the production of renewable fuels and chemicals. However, the challenge lies in developing robust and selective catalysts for this process. Transition metal oxide catalysts, particularly cobalt oxide, have shown potential for CO 2 hydrogenation, with performance heavily reliant on crystal phase and morphology. Achieving precise control over these catalyst attributes through colloidal nanoparticle synthesis could pave the way for catalyst and process advancement. Yet, navigating the complexities of colloidal nanoparticle syntheses, governed by numerous input variables, poses a significant challenge in systematically controlling resultant catalyst features. We present a multivariate Bayesian optimization, coupled with a data-driven classifier, to map the synthetic design space for colloidal CoO nanoparticles and simultaneously optimize them for multiple catalytically relevant features within a target crystalline phase. The optimized experimental conditions yielded small, phase-pure rock salt CoO nanoparticles of uniform size and shape. These optimized nanoparticles were then supported on SiO 2 and assessed for thermocatalytic CO 2 hydrogenation against larger, polydisperse CoO nanoparticles on SiO 2 and a conventionally prepared catalyst. The optimized CoO/SiO 2 catalyst consistently exhibited higher activity and CH 4 selectivity (ca. 98%) across various pretreatment reduction temperatures as compared to the other catalysts. This remarkable performance was attributed to particle stability and consistent H* surface coverage, even after undergoing the highest temperature reduction, achieving a more stable catalytic species that resists sintering and carbon occlusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Thermal Shape Stability of fcc Metal Nanocrystals Synthesized with Faceted Nonequilibrium Shapes

Highly refined capabilities of the shape-controlled solution-phase synthesis of metal nanocrystals (NCs) allow the generation of NCs with faceted nonequilibrium shapes, which optimize properties for target applications such as catalysis and plasmonics. Often, for such applications and also for TEM analysis, the NCs are removed from the solution-phase environment. We explore the postsynthesis evolution of these metastable NCs in a high-vacuum TEM environment. Specifically, here we analyze their reshaping toward the equilibrium Wulff shapes mediated by surface diffusion, where such reshaping degrades the above-mentioned optimized properties. Typical sizes for these NCs range from 5 to 30 nm or 10 3 –10 6 atoms, and reshaping often occurs on the time scale of minutes for temperatures around, say, 400 °C. We discuss the development of predictive stochastic atomistic-level models for NC evolution with a realistic description of surface diffusion. These models, in contrast to Molecular Dynamics, can naturally address the relevant time and length scales for these systems. KMC simulation results for the stochastic models are described, focusing on the reshaping of slightly elongated nanorods and of mildly truncated octahedra and nanocubes. In addition, we review appropriate theoretical formulations for reshaping, which involves the nucleation and growth on 2D islands or layers on outer facets of the NC. We note the limitations of classical nucleation theory in some scenarios and demonstrate the successes of a more fundamental and general master equation-based analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Enhanced Data Efficiency Using Deep Neural Networks and Gaussian Processes for Aerodynamic Design Optimization

Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that can then be used in a gradient-based optimizer. This makes them very well suited for high-fidelity simulation based aerodynamic shape optimization of highly parametrized geometries such as aircraft wings. However, the development of adjoint-based solvers involve careful mathematical treatment and their implementation require detailed software development. Furthermore, they can become prohibitively expensive when multiple optimization problems are being solved, each requiring multiple restarts to circumvent local optima. In this work, we propose a machine learning enabled, surrogate-based framework that replaces the expensive adjoint solver, without compromising on predicting predictive accuracy. Specifically, we first train a deep neural network (DNN) from training data generated from evaluating the high-fidelity simulation model on a model-agnostic design of experiments on the geometry shape parameters. The optimum shape may then be computed by using a gradient-based optimizer coupled with the trained DNN. Subsequently, we also perform a gradient-free Bayesian optimization, where the trained DNN is used as the prior mean. We observe that the latter framework (DNN-BO) improves upon the DNN-only based optimization strategy for the same computational cost. Overall, this framework predicts the true optimum with very high accuracy, while requiring far fewer high-fidelity function calls compared to the adjoint-based method. Furthermore, we show that multiple optimization problems can be solved with the same machine learning model with high accuracy, to amortize the offline costs associated with constructing our models. Our methodology finds applications in the early stages of aerospace design. (C) 2021 Published by Elsevier Masson SAS.

Renganathan, S. Ashwin↗
DOE OSTI2022

Design-Space Exploration for Inverse-Design of Wind Turbine Blades Using Data-Driven Methods

The state-of-the-practice aerodynamic design methods for wind turbine blades is typically based on Blade-Element Momentum (BEM) theory using a pre-designed frozen family of airfoils. The airfoils are themselves typically designed using panel methods. The design of the next-generation of large flexible rotors will need to capture the non-linear aerodynamics and three-dimensional flow to reduce the levelized cost of wind energy. Data-driven methods for aerodynamic design using data generated by computational fluid dynamics offer an attractive alternative to BEM-based methods that captures the non-linear aerodynamics of the component airfoils as well as the root and tip sections. In this work, we develop and demonstrate a framework to "smartly" explore the relevant design space in combination with an appropriate automated CFD pipeline to evaluate the aerodynamics of each design. The design-space exploration framework uses appropriate perturbations to the airfoil shape and induction profile from a baseline shape in combination with the inverse-design using BEM. The resulting designs are evaluated using an automated CFD pipeline using the in-house CFD solver framework "Mercury". We perform verification and validation to establish the capability of the Mercury framework to predict the aerodynamic performance of wind turbines. The CFD simulation of the perturbed blade shapes are optimized to restart from the converged baseline simulation to reduce the computational time. Finally, we demonstrate the design-space exploration technique for the design of the outboard section and the full rotor using perturbations to the shape and operating conditions of the NREL 5-MW turbine.

aerodynamic design methods↗
DOE OSTI2019

Optimization of the size and shape of the scanning aperture in autocollimator-based deflectometric profilometers

Deflectometric profilometers based on industrial electronic autocollimators (ACs), as the ELCOMAT-3000, have become indispensable tools for precision form measurements of optical surfaces. A growing number of labs at synchrotron and free electron laser x-ray facilities are going for BESSY-II NOM-like versions of the AC-based profilometers. These tools have proven capable of characterizing state-of-the-art aspherical x-ray optics with an accuracy on the level of 100 nrad (root-mean-square) over the spatial frequency range limited by the size of the aperture used in the profilometer. Normally, a round aperture with a diameter of about 2.5 mm is used. Previous investigations have shown that with the optimally aligned 2.5-mm aperture, the spatial resolution of a NOM-like profilometer corresponding to the first zero-crossing of the optical transform function (OTF) is ~1.2 mm. In this paper, we investigate the performance of an AC ELCOMAT-3000 for a slope profilometer with different aperture sizes and shapes. The results of angular calibration of the AC equipped with circular and rectangular apertures placed at different distances from the AC are discussed. The calibration was performed at the Physikalisch-Technische Bundesanstalt using the original experimental arrangements, also discussed in the paper. The OTF measurements with the specially developed test sample with chirped surface slope profiles were performed at the Advanced Light Source X-Ray Optics Laboratory (XROL) in application to a new optical surface measuring system under development at the XROL. In the OTF measurements, we have shown that application of a rectangular aperture with dimensions of 1.5 mm × 3 mm improves the spatial resolution in the tangential direction by a factor of ~1.4 compared to that of the standard circular aperture of 2.5-mm diameter. We postulate that the conclusions of our investigations are crucial for reaching fundamental metrological limits in deflectometric profilometry utilizing state-of-the-art electronic autocollimators.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Hundreds of weak lensing shear-selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S19A data

Abstract We use the Hyper Suprime-Cam Subaru Strategic Program S19A shape catalog to construct weak lensing shear-selected cluster samples. From aperture mass maps covering ∼510 deg2 created using a truncated Gaussian filter, we construct a catalog of 187 shear-selected clusters that correspond to mass map peaks with signal-to-noise ratio larger than 4.7. Most of the shear-selected clusters have counterparts in optically selected clusters, from which we estimate the purity of the catalog to be higher than 95%. The sample can be expanded to 418 shear-selected clusters with the same signal-to-noise ratio cut by optimizing the shape of the filter function and by combining weak lensing mass maps created with several different background galaxy selections. We argue that dilution and obscuration effects of cluster member galaxies can be mitigated by using background source galaxy samples and adopting a filter function with its inner boundary larger than about 2′. The large samples of shear-selected clusters that are selected without relying on any baryonic tracer are useful for detailed studies of cluster astrophysics and cosmology.

Oguri, Masamune↗
DOE OSTI2022

Single-stage gradient-based stellarator coil design: Optimization for near-axis quasi-symmetry

Here we present a new coil design paradigm for magnetic confinement in stellarators. Our approach directly optimizes coil shapes and coil currents to produce a vacuum quasi-symmetric magnetic field with a target rotational transform on the magnetic axis. This approach differs from the traditional two-stage approach in which first a magnetic configuration with desirable physics properties is found, and then coils to approximately realize this magnetic configuration are designed. The proposed single-stage approach allows us to find a compromise between confinement and engineering requirements, i.e., find easy-to-build coils with good confinement properties. Using forward and adjoint sensitivities, we derive derivatives of the physical quantities in the objective, which is constrained by a nonlinear periodic differential equation. In two numerical examples, we compare different gradient-based descent algorithms and find that incorporating approximate second-order derivative information through a quasi-Newton method is crucial for convergence. We also explore the optimization landscape in the neighborhood of a minimizer and find many directions in which the objective is mostly flat, indicating ample freedom to find simple and thus easy-to-build coils.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An optimization-based approach to tailor the mechanical response of soft metamaterials undergoing rate-dependent instabilities

An optimization-based design framework is proposed to tune the response of soft metamaterials involving both geometric instabilities and nonlinear viscoelastic material behavior. Designing the response of soft metamaterials to harness instabilities and undergo large, tailored configuration changes will enable advancements in soft robotics, shock and vibration mitigation, and flexible electronics. In line with the metamaterial concept, the response of these materials is governed to a large extent by the geometric and topological makeup of their small-scale features. However, the link between structure and response is less intuitive for soft metamaterials due to their reliance upon highly nonlinear responses triggered by geometric instabilities. This is further complicated by the effects of viscoelastic relaxation, which recent studies have shown to alter the emergence of instabilities in non-intuitive ways. Here, these effects are accounted for in our framework to achieve various design objectives, including tailored force–displacement response and maximized energy absorption from both geometric and material effects. To fully automate this process, it is essential to have a completely robust equation solver for forward problems involving instabilities and viscoelastic relaxation. We achieve this by casting the search for stable mechanical equilibrium — i.e. the forward problem — as a minimization problem and utilize a trust region algorithm to robustly handle instabilities and follow energetically-favorable equilibrium paths through critical points.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multi‐Stage Optimization of Pore Size and Shape in Pore‐Space‐Partitioned Metal–Organic Frameworks for Highly Selective and Sensitive Benzene Capture

Abstract Compared to exploratory development of new structure types, pushing the limits of isoreticular synthesis on a high‐performance MOF platform may have higher probability of achieving targeted properties. Multi‐modular MOF platforms could offer even more opportunities by expanding the scope of isoreticular chemistry. However, navigating isoreticular chemistry towards best properties on a multi‐modular platform is challenging due to multiple interconnected pathways. Here on the multi‐modular pacs (partitioned acs) platform, we demonstrate accessibility to a new regime of pore geometry using two independently adjustable modules (framework‐forming module 1 and pore‐partitioning module 2). A series of new pacs materials have been made. Benzene/cyclohexane selectivity is tuned, progressively, from 4.5 to 15.6 to 195.4 and to 482.5 by pushing the boundary of the pacs platform towards the smallest modules known so far. The exceptional stability of these materials in retaining both porosity and single crystallinity enables single‐crystal diffraction studies of different crystal forms (as‐synthesized, activated, guest‐loaded) that help reveal the mechanistic aspects of adsorption in pacs materials.

Chen, Yichong↗
DOE OSTI2024

Multi–Stage Optimization of Pore Size and Shape in Pore–Space–Partitioned Metal–Organic Frameworks for Highly Selective and Sensitive Benzene Capture

Compared to exploratory development of new structure types, pushing the limits of isoreticular synthesis on a high-performance MOF platform may have higher probability of achieving targeted properties. Multi-modular MOF platforms could offer even more opportunities by expanding the scope of isoreticular chemistry. However, navigating isoreticular chemistry towards best properties on a multi-modular platform is challenging due to multiple interconnected pathways. Here on the multi-modular pacs (partitioned acs) platform, we demonstrate accessibility to a new regime of pore geometry using two independently adjustable modules (framework-forming module 1 and pore-partitioning module 2). A series of new pacs materials have been made. Benzene/cyclohexane selectivity is tuned, progressively, from 4.5 to 15.6 to 195.4 and to 482.5 by pushing the boundary of the pacs platform towards the smallest modules known so far. The exceptional stability of these materials in retaining both porosity and single crystallinity enables single-crystal diffraction studies of different crystal forms (as-synthesized, activated, guest-loaded) that help reveal the mechanistic aspects of adsorption in pacs materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗