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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Structural characterization of particle systems using spherical harmonics

Many important properties of particulate materials are heavily influenced by the size and shape of the constituent particles. Thus, in order to control and improve product quality, it is important to develop a good understanding of the shape and size of the particles that make up a given particulate material. In this paper, we show how the spherical harmonics expansion can be used to approximate particles obtained from tomographic 3D images. This yields an analytic representation of the particles which can be used to calculate structural characteristics. We present an estimation method for the optimal length of expansion depending on individual particle shapes, based on statistical hypothesis testing. A suitable choice of this parameter leads to a smooth approximation that preserves the main shape features of the original particle. To show the wide applicability of this procedure, we use it to approximate particles obtained from two different tomographic 3D datasets of particulate materials. The first one describes an anode material from lithium-ion cells that consists of sphere-like particles with different sizes. The second dataset describes a powder of highly non-spherical titanium dioxide particles. - Highlights: • Complex particle shapes are described analytically by spherical harmonics expansion. • The optimal length of the expansion is estimated for each particle individually. • Characteristics like, e.g., particle surface areas can be calculated efficiently. • The method is applied to two tomographic datasets of particulate materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Cyber-Physical System for Freeway Ramp Meter Signal Control Using Deep Reinforcement Learning in a Connected Environment

Freeway bottlenecks such as on-ramp merging areas account for about 40% of recurring freeway congestion. It is generally agreed that building more roads and adding more lanes to existing infrastructure does not solve the congestion problem, and so dynamic traffic control measures offer a more cost-effective alternative. Ramp meters, traffic signal devices that regulate traffic flow entering freeways, are among the most effective measures to mitigate congestion at on-ramp merging areas on freeways. The confluence of deep reinforcement learning (RL) and connectivity provides a possible solution to advance ramp meter signal control. Deep RL is a group of machine-learning methods that enables an agent learning from the environment to improve its performance. In this study, three deep RL methods-proximal policy optimization (PPO), Ape-X deep Q-network (DQN), and asynchronous advantage actor-critic agents (A3C)-are explored for ramp meter signal control to maximize vehicle speed and traffic throughput, as well as to minimize energy consumption and emissions at freeway on-ramp merging areas in a connected environment. The low computational requirement and scalability of deep RL for deployment make it a powerful optimization tool for time-sensitive applications such as ramp meter signal control. The results of this study show that deep RL methods yield superior performance to both a fixed-time controller and ALINE A, a state-of-the-art feedback controller.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2019

Distributed Reinforcement Learning with ADMM-RL

NREL researcher Peter Graf discusses distributed reinforcement learning with ADMM-RL as part of the Innovative Optimization and Control Methods for Highly Distributed Autonomous Systems workshop. NREL hosted the workshop to exchange ideas on state-of-the-art control and optimization strategies as well as get feedback on work being done at NREL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Toward Robustness Guarantees for Feedback-Based Optimization

NREL researcher Andrey Bernstein discusses the move toward robustness guarantees for feedback-based optimization as part of the Innovative Optimization and Control Methods for Highly Distributed Autonomous Systems workshop. NREL hosted the workshop to exchange ideas on state-of-the-art control and optimization strategies as well as get feedback on work being done at NREL.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

3D printed modular centrifugal contactors and method for separating moieties using 3D printed optimized surfaces

The present invention provides an annular centrifugal contactor, having a housing to receive a plurality of liquids; a rotor inside the housing; an annular mixing zone, with a plurality of fluid retention reservoirs; and an adjustable stem that can be raised to restrict the flow of a liquid into the rotor or lowered to increase the flow of liquid into the rotor. The invention also provides a method for transferring moieties from a first liquid to a second liquid, the method having the steps of combining the fluids in a housing whose interior has helically shaped first channels; subjecting the fluids to a spinning rotor to produce a mixture, whereby the channels simultaneously conduct the mixture downwardly and upwardly; and passing the mixture through the rotor to contact second channels, whereby the channels pump the second liquid through a first aperture while the first fluid exits a second aperture.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Room-temperature fabrication of garnet-type solid-electrolyte: Optimizing particle size for high ionic conductivity

Dense and uniform Li 6.25 Al 0.25 La 3 Zr 2 O 12 (Al-doped LLZO) solid-electrolyte film of ~24 µm thickness is successfully fabricated by room temperature aerosol deposition (AD) method. The process optimization study revealed that careful control of particle size and morphology is one of critical determinants in the development of a compact AD membrane. Notably, our method facilitated an impressive ionic conductivity of approximately 10 –5 S cm –1 , bypassing the necessity for post-annealing processes, a milestone in itself. However, it is hypothesized that the attained conductivity is somewhat restrained by factors such as smaller grain size and potential surface degradation due to moisture exposure during fabrication, indicating avenues for further research. Looking forward, detailed investigations into the film's microstructure and its impact on transport properties will be a focal point, alongside potential enhancements through post-annealing and particle coating strategies. Finally, this research hints at a promising trajectory for the development of high-efficiency solid-state battery technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: a tomographic measurement of cosmic structure growth and expansion rate based on optimal redshift weights

We develop a new method, which is based on the optimal redshift weighting scheme, to extract the maximal tomographic information of baryonic acoustic oscillations (BAO) and redshift space distortions (RSD) from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 14 quasar (DR14Q) survey. We validate our method using the Extended Zel’dovich mocks, and apply our pipeline to the eBOSS DR14Q sample in the redshift range of 0.8 < z < 2.2. We report a joint measurement of fσ8 and two-dimensional BAO parameters D A and H at four effective redshifts of z eff = 0.98, 1.23, 1.52, and 1.94, and provide the full data covariance matrix. Using our measurement combined with BOSS DR12, Main Galaxy Sample (MGS), and 6 degree Field Galaxy Survey (6dFGS) BAO measurements, we find that the existence of dark energy is supported by observations at a 7.4σ significance level. Combining our measurement with BOSS DR12 and Planck observations, we constrain the gravitational growth index to be γ = 0.580 ± 0.082, which is fully consistent with the prediction of general relativity. This paper is part of a set that analyses the eBOSS DR14 quasar sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Correlation between DNAPL distribution area and dissolved concentration in surfactant enhanced aquifer remediation effluent: a two-dimensional flow cell study

During the process of surfactant enhanced aquifer remediation (SEAR), free phase dense non-aqueous phase liquid (DNAPL) may be mobilized and spread. The understanding of the impact of DNAPL spreading on the SEAR remediation is not sufficient with its positive effect infrequently mentioned. To evaluate the correlation between DNAPL spreading and remediation efficiency, a two-dimensional sandbox apparatus was used to simulate the migration and dissolution process of 1,2-DCA (1,2-dichloroethane) DNAPL in SEAR. Distribution area of DNAPL in the sandbox was determined by digital image analysis and correlated with effluent DNAPL concentration. The results showed that the effluent DNAPL concentration has significant positive linear correlation with the DNAPL distribution area, indicating the mobilization of DNAPL could improve remediation efficiency by enlarging total NAPL-water interfacial area for mass transfer. Meanwhile, the vertical migration of 1,2-DCA was limited within the boundary of aquifer in all experiments, implying that by manipulating injection parameters in SEAR, optimal remediation efficiency can be reached while the risk of DNAPL vertical migration is minimized. This study provides a convenient visible and quantitative method for the optimization of parameters for SEAR project, and an approach of rapid predicting the extent of DNAPL contaminant distribution based on the dissolved DNAPL concentration in the extraction well.

Wu, Bin↗
DOE OSTI2020

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

SU-F-T-187: Quantifying Normal Tissue Sparing with 4D Robust Optimization of Intensity Modulated Proton Therapy

Purpose: To report an approach to quantify the normal tissue sparing for 4D robustly-optimized versus PTV-optimized IMPT plans. Methods: We generated two sets of 90 DVHs from a patient’s 10-phase 4D CT set; one by conventional PTV-based optimization done in the Eclipse treatment planning system, and the other by an in-house robust optimization algorithm. The 90 DVHs were created for the following scenarios in each of the ten phases of the 4DCT: ± 5mm shift along x, y, z; ± 3.5% range uncertainty and a nominal scenario. A Matlab function written by Gay and Niemierko was modified to calculate EUD for each DVH for the following structures: esophagus, heart, ipsilateral lung and spinal cord. An F-test determined whether or not the variances of each structure’s DVHs were statistically different. Then a t-test determined if the average EUDs for each optimization algorithm were statistically significantly different. Results: T-test results showed each structure had a statistically significant difference in average EUD when comparing robust optimization versus PTV-based optimization. Under robust optimization all structures except the spinal cord received lower EUDs than PTV-based optimization. Using robust optimization the average EUDs decreased 1.45% for the esophagus, 1.54% for the heart and 5.45% for the ipsilateral lung. The average EUD to the spinal cord increased 24.86% but was still well below tolerance. Conclusion: This work has helped quantify a qualitative relationship noted earlier in our work: that robust optimization leads to plans with greater normal tissue sparing compared to PTV-based optimization. Except in the case of the spinal cord all structures received a lower EUD under robust optimization and these results are statistically significant. While the average EUD to the spinal cord increased to 25.06 Gy under robust optimization it is still well under the TD50 value of 66.5 Gy from Emami et al. Supported in part by the NCI U19 CA021239.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities: Preprint

Increased penetration of distributed variable re-newable generation may cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But due to the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network is needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69 node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Anion exchange and extraction chromatography tandem column isolation of zirconium-89 ( 89 Zr) from cyclotron bombarded targets using an automated fluidic platform

The long-lived positron emitter 89 Zr is a highly promising nuclide employed in diagnostic Positron Emission Tomography (PET) imaging. Methods of radiochemical processing to obtain 89 Zr for clinical use are traditionally performed with a single hydroxamate resin column. In this work, we present a tandem column purification method for the preparation of high-purity 89 Zr from cyclotron bombarded Y metal foils. The primary column is a macroporous, strongly basic anion exchange resin on styrene divinylbenzene co-polymer. The secondary microcolumn, with an internal volume of 33 µL, is packed with an extraction chromatography resin (ExCR) loaded with HDEHP. A condition of “inverted selectivity” is presented, wherein the 89 Zr elution from the primary column is synonymous with the load condition on the secondary column. The ability to transfer 89 Zr from one column to the next allows two sequential column clean-up methods to be performed prior to the final elution of the 89 Zr product. This approach assures delivery of very high purity 89 Zr . The tandem column purification process has been implemented into a prototype automated fluidic system. Optimization of the method is presented, followed by evaluation of the process using seven cyclotron bombarded Y metal foil targets. Once optimized, we found that 93.7±2.3% of the 89 Zr present in the foils was recovered in the secondary column elution fraction (0.8 M oxalic acid). Radiochromatograms of the product elution peaks enabled determination of full width at half-maximum (FWHM) and 89 Zr collection yields as a function of volume. Because of the small size of the secondary microcolumn, a 89 Zr product volume of ~0.28 mL is reported, which provides a substantially increased nuclide concentration over traditional methods. Finally, we evaluated the transchelation of the resulting 89 Zr oxalate product to deferoxamine mesylate (DFOM) salt. We observed effective specific activities (ESA) and bindable metals concentrations ([M B ]) that exceed those reported by the traditional single hydroxamate column method.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

A special generalized HSS method for discrete ill-posed problems

In this paper, we use a new special generalized Hermitian and skew-Hermitian splitting (SGHSS) method for solving ill-posed inverse problems. Based on an augmented system formulation, we apply a new splitting for the Hermitian part of the coefficient matrix and discuss on the convergence of this iterative method. Moreover, the optimal parameter minimizing the spectral radius of iteration matrix is derived. Finally, we present some numerical examples to demonstrate the performance of the presented method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Outcomes and Insights From Simplified Analytic Trajectory Optimization for a Tethered Underwater Kite

This letter formulates and solves a periodic trajectory optimization problem for a tethered underwater kite. The goal is to maximize the average mechanical power harvested by the kite. The type of kite considered in this letter extracts electricity from ocean currents by moving cross-current as its reel away from its base station, and consumes electricity to reel back. The problem of optimizing this kite’s trajectory is challenging due to the high dimensionality and nonlinearity of its dynamics. To tackle this challenge, the literature often separates the problem into two subproblems focusing on optimizing the cross-current and the reel-in/reel-out components of the trajectory, respectively, which may be sub-optimal. In contrast, this letter solves for the combined cross-current and reel-in/reel-out trajectory by linearizing the dynamics of the kite around a zero-power reference equilibrium trajectory in spherical coordinates. This allows the trajectory optimization problem to be solved analytically for simple sinusoidal input perturbations from equilibrium. Here we use linear quadratic regulation to enable the nonlinear kite model to track the optimized trajectory. The result is a computationally efficient approach that achieves an attractive Loyd factor of 19.9%, while providing important insights into the nature of the optimal trajectory.

42 ENGINEERING↗
DOE OSTI2016

TH-EF-BRB-05: 4pi Non-Coplanar IMRT Beam Angle Selection by Convex Optimization with Group Sparsity Penalty

Purpose: Integrated beam orientation and fluence map optimization is expected to be the foundation of robust automated planning but existing heuristic methods do not promise global optimality. We aim to develop a new method for beam angle selection in 4π non-coplanar IMRT systems based on solving (globally) a single convex optimization problem, and to demonstrate the effectiveness of the method by comparison with a state of the art column generation method for 4π beam angle selection. Methods: The beam angle selection problem is formulated as a large scale convex fluence map optimization problem with an additional group sparsity term that encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated first-order method, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The beam angle selection and fluence map optimization algorithm is used to create non-coplanar 4π treatment plans for several cases (including head and neck, lung, and prostate cases) and the resulting treatment plans are compared with 4π treatment plans created using the column generation algorithm. Results: In our experiments the treatment plans created using the group sparsity method meet or exceed the dosimetric quality of plans created using the column generation algorithm, which was shown superior to clinical plans. Moreover, the group sparsity approach converges in about 3 minutes in these cases, as compared with runtimes of a few hours for the column generation method. Conclusion: This work demonstrates the first non-greedy approach to non-coplanar beam angle selection, based on convex optimization, for 4π IMRT systems. The method given here improves both treatment plan quality and runtime as compared with a state of the art column generation algorithm. When the group sparsity term is set to zero, we obtain an excellent method for fluence map optimization, useful when beam angles have already been selected. NIH R43CA183390, NIH R01CA188300, Varian Medical Systems; Part of this research took place while D. O’Connor was a summer intern at RefleXion Medical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Practical dose point-based methods to characterize dose distribution in a stationary elliptical body phantom for a cone-beam C-arm CT system

Purpose: To propose new dose point measurement-based metrics to characterize the dose distributions and the mean dose from a single partial rotation of an automatic exposure control-enabled, C-arm-based, wide cone angle computed tomography system over a stationary, large, body-shaped phantom. Methods: A small 0.6 cm{sup 3} ion chamber (IC) was used to measure the radiation dose in an elliptical body-shaped phantom made of tissue-equivalent material. The IC was placed at 23 well-distributed holes in the central and peripheral regions of the phantom and dose was recorded for six acquisition protocols with different combinations of minimum kVp (109 and 125 kVp) and z-collimator aperture (full: 22.2 cm; medium: 14.0 cm; small: 8.4 cm). Monte Carlo (MC) simulations were carried out to generate complete 2D dose distributions in the central plane (z = 0). The MC model was validated at the 23 dose points against IC experimental data. The planar dose distributions were then estimated using subsets of the point dose measurements using two proposed methods: (1) the proximity-based weighting method (method 1) and (2) the dose point surface fitting method (method 2). Twenty-eight different dose point distributions with six different point number cases (4, 5, 6, 7, 14, and 23 dose points) were evaluated to determine the optimal number of dose points and their placement in the phantom. The performances of the methods were determined by comparing their results with those of the validated MC simulations. The performances of the methods in the presence of measurement uncertainties were evaluated. Results: The 5-, 6-, and 7-point cases had differences below 2%, ranging from 1.0% to 1.7% for both methods, which is a performance comparable to that of the methods with a relatively large number of points, i.e., the 14- and 23-point cases. However, with the 4-point case, the performances of the two methods decreased sharply. Among the 4-, 5-, 6-, and 7-point cases, the 7-point case (1.0% [±0.6%] difference) and the 6-point case (0.7% [±0.6%] difference) performed best for method 1 and method 2, respectively. Moreover, method 2 demonstrated high-fidelity surface reconstruction with as few as 5 points, showing pixelwise absolute differences of 3.80 mGy (±0.32 mGy). Although the performance was shown to be sensitive to the phantom displacement from the isocenter, the performance changed by less than 2% for shifts up to 2 cm in the x- and y-axes in the central phantom plane. Conclusions: With as few as five points, method 1 and method 2 were able to compute the mean dose with reasonable accuracy, demonstrating differences of 1.7% (±1.2%) and 1.3% (±1.0%), respectively. A larger number of points do not necessarily guarantee better performance of the methods; optimal choice of point placement is necessary. The performance of the methods is sensitive to the alignment of the center of the body phantom relative to the isocenter. In body applications where dose distributions are important, method 2 is a better choice than method 1, as it reconstructs the dose surface with high fidelity, using as few as five points.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Optimizing Irregular Communication with Neighborhood Collectives and Locality-Aware Parallelism

Irregular communication often limits both the performance and scalability of parallel applications. Typically, applications individually implement irregular communication as point-to-point, and any optimizations are integrated directly into the application. As a result, these optimizations lack portability. It is difficult to optimize point-to-point messages within MPI, as the interface for single messages provides no information on the collection of all communication to be performed. However, the persistent neighbor collective API, released in the MPI 4 standard, provides an interface for portable optimizations of irregular communication within MPI libraries. This paper presents methods for implementing existing optimizations for irregular communication within neighborhood collectives, analyzes the impact of replacing point-to-point communication in existing codebases such as Hypre BoomerAMG with neighborhood collectives, and finally shows up to a 1.38x speedup on sparse matrix-vector multiplication communication within a BoomerAMG solve through the use of our optimized neighbor collectives. Here, the authors analyze three implementations of persistent neighborhood collectives for Alltoallv: an unoptimized wrapper of standard point-to-point communication, and two locality-aware aggregating methods. The second locality-aware implementation exposes an non-standard interface to perform additional optimization, and the authors present the additional 0.07x speedup from the extended interface. All optimizations are available in an open-source codebase, MPI Advance, which sits on top of MPI, allowing for optimizations to be added into existing codebases regardless of the system MPI install.

AMG↗
DOE OSTI2024

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗