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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Inferring fracture dilation and shear slip from surface deformation utilising trained surrogate models

An important task in energy and CO 2 storage (sequestration) in the subsurface is to verify that the surrounding fractures and faults are not activated, acting as leakage pathways. This is achievable through effective and efficient Measurement, Monitoring and Verification (MMV) plans. In this work, two surrogate models are trained to captures dilation (opening) and shear deformation of fractures, and the associated surface deformation. The trained surrogate model, based on conditional Generative-Adversarial Networks (cGAN) receives fracture apertures from dilational fractures together with fracture slips from shear fractures and predicts the combined surface deformation. An inversion algorithm based on Bayesian framework is proposed to identify the geometry of both types of fractures, as well as volume of dilational fractures and deformation moment induced by shear fractures, all from the measured surface deformation data. The inversion algorithm utilises the Differential Evolution (DE) optimisation technique that has the superior performance in finding the global minimum of cost function. The proposed surrogate-assisted inversion successfully inferred the unknown dip, dip direction and the volume of the dilational fractures as well as the induced deformation moment in shear fractures. The model was further tested for the inversion of a field hydraulic fracturing tilt dataset applying different scenarios with varying unknowns to show the model's performance, as well as incorporating shear deformation for better match with the observed data.

Dilation and shear↗
DOE OSTI2017

An enhanced artificial neural network with a shuffled complex evolutionary global optimization with principal component analysis

The classical Back-Propagation (BP) scheme with gradient-based optimization in training Artificial Neural Networks (ANNs) suffers from many drawbacks, such as the premature convergence, and the tendency of being trapped in local optimums. Therefore, as an alternative for the BP and gradient-based optimization schemes, various Evolutionary Algorithms (EAs), i.e., Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), and Differential Evolution (DE), have gained popularity in the field of ANN weight training. This study applied a new efficient and effective Shuffled Complex Evolutionary Global Optimization Algorithm with Principal Component Analysis – University of California Irvine (SP-UCI) to the weight training process of a three-layer feed-forward ANN. A large-scale numerical comparison is conducted among the SP-UCI-, PSO-, GA-, SA-, and DE-based ANNs on 17 benchmark, complex, and real-world datasets. Here the results show that SP-UCI-based ANN outperforms other EA-based ANNs in the context of convergence and generalization. Results suggest that the SP-UCI algorithm possesses good potential in support of the weight training of ANN in real-word problems. In addition, the suitability of different kinds of EAs on training ANN is discussed. The large-scale comparison experiments conducted in this paper are fundamental references for selecting proper ANN weight training algorithms in practice.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments

A multi-rate expression for uranyl [U(VI)] surface complexation reactions has been proposed to describe diffusion-limited U(VI) sorption/desorption in heterogeneous subsurface sediments. An important assumption in the rate expression is that its rate constants follow a certain type probability distribution. In this paper, a Bayes-based, Differential Evolution Markov Chain method was used to assess the distribution assumption and to analyze parameter and model structure uncertainties. U(VI) desorption from a contaminated sediment at the US Hanford 300 Area, Washington was used as an example for detail analysis. The results indicated that: 1) the rate constants in the multi-rate expression contain uneven uncertainties with slower rate constants having relative larger uncertainties; 2) the lognormal distribution is an effective assumption for the rate constants in the multi-rate model to simualte U(VI) desorption; 3) however, long-term prediction and its uncertainty may be significantly biased by the lognormal assumption for the smaller rate constants; and 4) both parameter and model structure uncertainties can affect the extrapolation of the multi-rate model with a larger uncertainty from the model structure. The results provide important insights into the factors contributing to the uncertainties of the multi-rate expression commonly used to describe the diffusion or mixing-limited sorption/desorption of both organic and inorganic contaminants in subsurface sediments.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2024

An ion specific continuum model on ionic surfactant's binary phase diagram in aqueous solution

Here, a continuum aggregation model is proposed to account for specific ion effects, enabling accurate phase diagrams calculations for the micellar, cylindrical and lamellar aggregates of sodium/potassium carboxylate surfactants in aqueous solution across a range of temperatures. Three groups of concentrations at distinctive temperatures are fitted to build empirical temperature dependence given the limited availability of relevant experimental measurements. The specific ion effects are manifested in the aggregates' surface tension as well as in the distributions of counter-ions' concentrations in the vicinity of the aggregates. The aggregates' geometric sizes are well-reproduced. The differential evolution algorithm is applied to address boundary conditions of the electrostatic potential, aggregate size optimization as well as the equilibrium of monomers transferring between the aggregate and aqueous region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms

To improve the marketability of novel microreactor designs, there is a need for automated and optimal control of these reactors. This paper presents a methodology for performing multiobjective optimization of control drum operation for a microreactor under normal and off-nominal conditions. Here, two different case studies are used where the control drum configuration is optimized for the reactor to be critical with some desired power distribution that would satisfy peaking limits. A surrogate model for power distribution is developed based on a feedforward neural network. The process for determining weights for scalarization of the multiobjective optimization problem is also detailed. Six optimization algorithms: evolutionary strategies, differential evolution, grey wolf optimization, Harris hawks optimization, moth flame optimization and particle swarm optimization, are all applied to these cases and the results analyzed. Although all these algorithms will demonstrate optima-seeking behavior, for real-time control it is necessary to identify the best algorithm to efficiently provide reasonable optima without operator interference. The moth flame optimization algorithm was found to perform particularly well on both cases. Overall, it was found that the algorithms capable of supplying the best optima were also the most consistent. Finally, the found optima were verified with the original model used to train surrogates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Periodically multilayered planar optical concentrator for photovoltaic solar cells

A planar optical concentrator comprising a periodic multilayered isotropic dielectric material backed by a metallic surface-relief grating was theoretically examined for silicon photovoltaics. The concentrator was optimized using a differential evolution algorithm for solar-spectrum-integrated power-flux density. Further optimization was carried out for tolerance to variations in the incidence angle, spatial dimensions, and dielectric properties. The average electron-hole pair density in a silicon solar cell can be doubled, and the material costs substantially diminished by this concentrator, whose efficacy is due to the excitation of waveguide modes and multiple surface-plasmon-polariton waves in a broad spectral regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Indirect-to-direct band gap transition in relaxed and strained Ge{sub 1−x−y}Si{sub x}Sn{sub y} ternary alloys

Sn-containing group IV semiconductors create the possibility to independently control strain and band gap thus providing a wealth of opportunities to develop an entirely new class of low dimensional systems, heterostructures, and silicon-compatible electronic and optoelectronic devices. With this perspective, this work presents a detailed investigation of the band structure of strained and relaxed Ge{sub 1−x−y}Si{sub x}Sn{sub y} ternary alloys using a semi-empirical second nearest neighbors tight binding method. This method is based on an accurate evaluation of the deformation potential constants of Ge, Si, and α-Sn using a stochastic Monte-Carlo approach as well as a gradient based optimization method. Moreover, a new and efficient differential evolution approach is also developed to accurately reproduce the experimental effective masses and band gaps. Based on this, we elucidated the influence of lattice disorder, strain, and composition on Ge{sub 1−x−y}Si{sub x}Sn{sub y} band gap energy and directness. For 0 ≤ x ≤ 0.4 and 0 ≤ y ≤ 0.2, we found that tensile strain lowers the critical content of Sn needed to achieve a direct band gap semiconductor with the corresponding band gap energies below 0.76 eV. This upper limit decreases to 0.43 eV for direct gap, fully relaxed ternary alloys. The obtained transition to direct band gap is given by y > 0.605 × x + 0.077 and y > 1.364 × x + 0.107 for epitaxially strained and fully relaxed alloys, respectively. The effects of strain, at a fixed composition, on band gap directness were also investigated and discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Reduction of scattering using thin all-dielectric shells designed by stochastic optimizer

Adaptive differential evolution method has been used for optimization of all-dielectric multilayer coatings in order to reduce total scattering from spherical targets. The optimal refractive index profiles have been found for various sizes of targets and thicknesses of coatings. Few profile types that appear to be optimal for various geometrical parameters have been identified. Scattering of the target with diameter of 0.75 λ has been reduced by 85% using 0.16 λ thick coating formed by isotropic dielectric materials. For larger targets, scattering reduction becomes smaller, but it still reaches 50% for targets with the diameter of 1.5 λ. The obtained designs provide a route to implement cloaking without the use of magnetic and anisotropic metamaterials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Mathematical model of the metal mould surface temperature optimization

The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

A SYSTEMATIC RETRIEVAL ANALYSIS OF SECONDARY ECLIPSE SPECTRA. I. A COMPARISON OF ATMOSPHERIC RETRIEVAL TECHNIQUES

Exoplanet atmosphere spectroscopy enables us to improve our understanding of exoplanets just as remote sensing in our own solar system has increased our understanding of the solar system bodies. The challenge is to quantitatively determine the range of temperatures and molecular abundances allowed by the data, which is often difficult given the low information content of most exoplanet spectra that commonly leads to degeneracies in the interpretation. A variety of spectral retrieval approaches have been applied to exoplanet spectra, but no previous investigations have sought to compare these approaches. We compare three different retrieval methods: optimal estimation, differential evolution Markov chain Monte Carlo, and bootstrap Monte Carlo on a synthetic water-dominated hot Jupiter. We discuss expectations of uncertainties in abundances and temperatures given current and potential future observations. In general, we find that the three approaches agree for high spectral resolution, high signal-to-noise data expected to come from potential future spaceborne missions, but disagree for low-resolution, low signal-to-noise spectra representative of current observations. We also compare the results from a parameterized temperature profile versus a full classical Level-by-Level approach and discriminate in which situations each of these approaches is applicable. Furthermore, we discuss the implications of our models for the inferred C-to-O ratios of exoplanetary atmospheres. Specifically, we show that in the observational limit of a few photometric points, the retrieved C/O is biased toward values near solar and near one simply due to the assumption of uninformative priors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

CHARACTERIZING THE ORBITAL AND DYNAMICAL STATE OF THE HD 82943 PLANETARY SYSTEM WITH KECK RADIAL VELOCITY DATA

We present an updated analysis of radial velocity data of the HD 82943 planetary system based on 10 yr of measurements obtained with the Keck telescope. Previous studies have shown that the HD 82943 system has two planets that are likely in 2:1 mean-motion resonance (MMR), with orbital periods about 220 and 440 days. However, alternative fits that are qualitatively different have also been suggested, with two planets in a 1:1 resonance or three planets in a Laplace 4:2:1 resonance. Here we use χ{sup 2} minimization combined with a parameter grid search to investigate the orbital parameters and dynamical states of the qualitatively different types of fits, and we compare the results to those obtained with the differential evolution Markov chain Monte Carlo method. Our results support the coplanar 2:1 MMR configuration for the HD 82943 system, and show no evidence for either the 1:1 or three-planet Laplace resonance fits. The inclination of the system with respect to the sky plane is well constrained at 20{sup +4.9}{sub -5.5} degrees, and the system contains two planets with masses of about 4.78 M{sub J} and 4.80 M{sub J} (where M{sub J} is the mass of Jupiter) and orbital periods of about 219 and 442 days for the inner and outer planet, respectively. The best fit is dynamically stable with both eccentricity-type resonant angles θ{sub 1} and θ{sub 2} librating around 0°.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A Spitzer five-band analysis of the Jupiter-sized planet TrES-1

With an equilibrium temperature of 1200 K, TrES-1 is one of the coolest hot Jupiters observed by Spitzer. It was also the first planet discovered by any transit survey and one of the first exoplanets from which thermal emission was directly observed. We analyzed all Spitzer eclipse and transit data for TrES-1 and obtained its eclipse depths and brightness temperatures in the 3.6 μm (0.083% ± 0.024%, 1270 ± 110 K), 4.5 μm (0.094% ± 0.024%, 1126 ± 90 K), 5.8 μm (0.162% ± 0.042%, 1205 ± 130 K), 8.0 μm (0.213% ± 0.042%, 1190 ± 130 K), and 16 μm (0.33% ± 0.12%, 1270 ± 310 K) bands. The eclipse depths can be explained, within 1σ errors, by a standard atmospheric model with solar abundance composition in chemical equilibrium, with or without a thermal inversion. The combined analysis of the transit, eclipse, and radial-velocity ephemerides gives an eccentricity of e=0.033{sub −0.031}{sup +0.015}, consistent with a circular orbit. Since TrES-1's eclipses have low signal-to-noise ratios, we implemented optimal photometry and differential-evolution Markov Chain Monte Carlo (MCMC) algorithms in our Photometry for Orbits, Eclipses, and Transits pipeline. Benefits include higher photometric precision and ∼10 times faster MCMC convergence, with better exploration of the phase space and no manual parameter tuning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

IMFIT: A FAST, FLEXIBLE NEW PROGRAM FOR ASTRONOMICAL IMAGE FITTING

I describe a new, open-source astronomical image-fitting program called IMFIT, specialized for galaxies but potentially useful for other sources, which is fast, flexible, and highly extensible. A key characteristic of the program is an object-oriented design that allows new types of image components (two-dimensional surface-brightness functions) to be easily written and added to the program. Image functions provided with IMFIT include the usual suspects for galaxy decompositions (Sérsic, exponential, Gaussian), along with Core-Sérsic and broken-exponential profiles, elliptical rings, and three components that perform line-of-sight integration through three-dimensional luminosity-density models of disks and rings seen at arbitrary inclinations. Available minimization algorithms include Levenberg-Marquardt, Nelder-Mead simplex, and Differential Evolution, allowing trade-offs between speed and decreased sensitivity to local minima in the fit landscape. Minimization can be done using the standard χ{sup 2} statistic (using either data or model values to estimate per-pixel Gaussian errors, or else user-supplied error images) or Poisson-based maximum-likelihood statistics; the latter approach is particularly appropriate for cases of Poisson data in the low-count regime. I show that fitting low-signal-to-noise ratio galaxy images using χ{sup 2} minimization and individual-pixel Gaussian uncertainties can lead to significant biases in fitted parameter values, which are avoided if a Poisson-based statistic is used; this is true even when Gaussian read noise is present.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Thermoeconomic cost optimization of superconducting magnets for proton therapy gantries

A compact gantry delivering 70-220 MeV protons with fixed field in the superconducting magnets could reduce the cost and improve the adoption of proton therapy. While a number of magnet and cryogenics designs have been proposed, the combined capital and operating costs of state-of-the-art superconducting materials have not been analyzed. In response, we develop a thermoeconomic model of a multi-stage, conduction cooled gantry lattice and analyze the cryocooler operating cost, cryocooler capital cost and conductor capital cost for Nb-Ti, Nb 3 Sn, REBCO and Bi-2223 over a continuous range of magnet temperatures, and a differential evolution algorithm is used to identify the optimal combination of thermal intercept temperatures. Although Nb3Sn yields the lowest Net Present Value (NPV) of $111.7k at a magnet temperature of 9.4 K, the optimized Bi-2223 design at 12.8 K approaches the realm of commercial feasibility by offering improved thermal stability and forgoing the need for costly conductor heat treatment and magnet quench training. Furthermore, it was found that Nb3Sn was more cost effective than Nb-Ti and that REBCO was not economically viable for the parameters of this investigation. Overall, the thermoeconomic model developed herein can optimize conductor choices, magnet temperatures and thermal staging which has value for any conduction-cooled superconducting magnet.

BSCCO↗
DOE OSTI2012

New constraints on cosmological parameters and neutrino properties using the expansion rate of the Universe to z ∼ 1.75

We have assembled a compilation of observational Hubble parameter measurements estimated with the differential evolution of cosmic chronometers, in the redshift range 0 < z < 1.75. This sample has been used, in combination with CMB data and with the most recent estimate of the Hubble constant H{sub 0}, to derive new constraints on several cosmological parameters. The new Hubble parameter data are very useful to break some of the parameter degeneracies present in CMB-only analysis, and to constrain possible deviations from the standard (minimal) flat ΛCDM model. The H(z) data are especially valuable in constraining Ω{sub k} and Ω{sub DE} in models that allow a variation of those parameters, yielding constraints that are competitive with those obtained using Supernovae and/or baryon acoustic oscillations. We also find that our H(z) data are important to constrain parameters that do no affect directly the expansion history, by breaking or reducing degeneracies with other parameters. We find that N{sub rel} = 3.45±0.33 using WMAP 7-years data in combination with South Pole Telescope data and our H(z) determinations (N{sub rel} = 3.71±0.45 using Atacama Cosmology Telescope data instead of South Pole Telescope). We exclude N{sub rel} > 4 at 95% CL (74% CL) using the same datasets combinations. We also put competitive limits on the sum of neutrino masses, Σm{sub ν} < 0.24 eV at 68% confidence level. These results have been proven to be extremely robust to many possible systematic effects, such as the initial choice of stellar population synthesis model adopted to estimate H(z) and the progenitor-bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

PyDREAM: high-dimensional parameter inference for biological models in python

Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis [DREAM(ZS)] algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012). PyDREAM achieves excellent performance for complex, parameter-rich models and takes full advantage of distributed computing resources, facilitating parameter inference and uncertainty estimation of CPU-intensive biological models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Integral Field Spectroscopy of the cometary starburst galaxy NGC 4861

ABSTRACT Using the PMAS Integral Field Unit on the Calar Alto 3.5 m telescope, we observed the southern component (Markarian 59) of the ‘cometary’ starburst galaxy NGC 4861. Mrk 59 is centred on a giant nebula and concentration of stars 1 kpc in diameter. Strong $\rm H\,\alpha$ emission points to a star-formation rate (SFR) at least 0.47 $\rm M_{\odot }\, yr^{-1}$. Mrk 59 has a very high [O iii] $\rm \lambda 5007/H\,\beta$ ratio, reaching 7.35 in the central nebula, with a second peak at a star-forming hotspot further north. Fast outflows are not detected but nebular motion and galaxy rotation produce relative velocities up to 40 km $\rm s^{-1}$. Spectral analysis of different regions with ‘Fitting Analysis using Differential evolution Optimization’ (FADO) finds that the stars in the central and ‘spur’ nebulae are very young, $\rm \le 125~Myr$ with a large $\rm \lt 10~Myr$ contribution. Older stars ($\rm \sim 1~Gyr$) make up the northern disk component, while the other regions show mixtures of 1 Gyr age with very young stars. This and the high specific SFR $\rm \sim 3.5~Gyr^{-1}$ imply a bimodal star formation history, with Mrk 59 formed in ongoing starbursts fuelled by a huge gas inflow, turning the galaxy into an asymmetric ‘green pea’ or blue compact dwarf. We map the He ii λ4686 emission, and identify a broad component from the central nebula, consistent with the emission of ∼300 Wolf–Rayet stars. About a third of the He ii λ4686 flux is a narrow line emitted from a more extended area covering the central and spur nebulae, and may have a different origin.

Roche, Nathan (ORCID:0000000319363058)↗
DOE OSTI2020

Assessing three closed-loop learning algorithms by searching for high-quality quantum control pulses

Designing a high-quality control is crucial for reliable quantum computation. Among the existing approaches, closed-loop leaning control is an effective choice. Its efficiency depends on the learning algorithm employed, thus deserving algorithmic comparisons for its practical applications. Here we assess three representative learning algorithms, including GRadient Ascent Pulse Engineering (GRAPE), improved Nelder-Mead (NMplus), and Differential Evolution (DE), by searching for high-quality control pulses to prepare the Bell state. We first implement each algorithm experimentally in a nuclear magnetic resonance system and then conduct a numerical study considering the impact of some possible significant experimental uncertainties. The experiments report the successful preparation of the high-fidelity target state by the three algorithms, while NMplus converges fastest, and these results coincide with the numerical simulations when potential uncertainties are negligible. However, under certain significant uncertainties, these algorithms possess distinct performance with respect to their resulting precision and efficiency, and DE shows the best robustness. Finally, this study provides insight to aid in the practical application of different closed-loop learning algorithms in realistic physical scenarios.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗