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At least 757 records · Page 42

A novel approach to correct the coded aperture misalignment for fast neutron imaging

Aperture alignment is crucial for the diagnosis of neutron imaging because it has significant impact on the coding imaging and the understanding of the neutron source. In our previous studies on the neutron imaging system with coded aperture for large field of view, “residual watermark,” certain extra information that overlies reconstructed image and has nothing to do with the source is discovered if the peak normalization is employed in genetic algorithms (GA) to reconstruct the source image. Some studies on basic properties of residual watermark indicate that the residual watermark can characterize coded aperture and can thus be used to determine the location of coded aperture relative to the system axis. In this paper, we have further analyzed the essential conditions for the existence of residual watermark and the requirements of the reconstruction algorithm for the emergence of residual watermark. A gamma coded imaging experiment has been performed to verify the existence of residual watermark. Based on the residual watermark, a correction method for the aperture misalignment has been studied. A multiple linear regression model of the position of coded aperture axis, the position of residual watermark center, and the gray barycenter of neutron source with twenty training samples has been set up. Using the regression model and verification samples, we have found the position of the coded aperture axis relative to the system axis with an accuracy of approximately 20 μm. Conclusively, a novel approach has been established to correct the coded aperture misalignment for fast neutron coded imaging.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimization of micropillar sequences for fluid flow sculpting

Inertial fluid flow deformation around pillars in a microchannel is a new method for controlling fluid flow. Sequences of pillars have been shown to produce a rich phase space with a wide variety of flow transformations. Previous work has successfully demonstrated manual design of pillar sequences to achieve desired transformations of the flow cross section, with experimental validation. However, such a method is not ideal for seeking out complex sculpted shapes as the search space quickly becomes too large for efficient manual discovery. We explore fast, automated optimization methods to solve this problem. We formulate the inertial flow physics in microchannels with different micropillar configurations as a set of state transition matrix operations. These state transition matrices are constructed from experimentally validated streamtraces for a fixed channel length per pillar. This facilitates modeling the effect of a sequence of micropillars as nested matrix-matrix products, which have very efficient numerical implementations. With this new forward model, arbitrary micropillar sequences can be rapidly simulated with various inlet configurations, allowing optimization routines quick access to a large search space. We integrate this framework with the genetic algorithm and showcase its applicability by designing micropillar sequences for various useful transformations. We computationally discover micropillar sequences for complex transformations that are substantially shorter than manually designed sequences. We also determine sequences for novel transformations that were difficult to manually design. Finally, we experimentally validate these computational designs by fabricating devices and comparing predictions with the results from confocal microscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Controlling the high frequency response of H{sub 2} by ultra-short tailored laser pulses: A time-dependent configuration interaction study

We combine the stochastic pulse optimization (SPO) scheme with the time-dependent configuration interaction singles method in order to control the high frequency response of a simple molecular model system to a tailored femtosecond laser pulse. For this purpose, we use H{sub 2} treated in the fixed nuclei approximation. The SPO scheme, as similar genetic algorithms, is especially suited to control highly non-linear processes, which we consider here in the context of high harmonic generation. Here, we will demonstrate that SPO can be used to realize a “non-harmonic” response of H{sub 2} to a laser pulse. Specifically, we will show how adding low intensity side frequencies to the dominant carrier frequency of the laser pulse and stochastically optimizing their contribution can create a high-frequency spectral signal of significant intensity, not harmonic to the carrier frequency. At the same time, it is possible to suppress the harmonic signals in the same spectral region, although the carrier frequency is kept dominant during the optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computation of energy states of hydrogenic quantum dot with two-electrons

In this study we have investigated the electronic structure of the hydrogenic quantum dot with two electrons inside an impenetrable potential surface. The energy eigenvalues and wavefunctions of the ground and excited states of spherical quantum dot have been calculated by using the Quantum Genetic Algorithm (QGA) and Hartree-Fock Roothaan (HFR) method, and the energies are investigated as a function of dot radius. The results show that as dot radius increases, the energy of quantum dot decreases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An X-band waveguide measurement technique for the accurate characterization of materials with low dielectric loss permittivity

In this work, we present a new X-band waveguide (WR90) measurement method that permits the broadband characterization of the complex permittivity for low dielectric loss tangent material specimens with improved accuracy. An electrically long polypropylene specimen that partially fills the cross-section is inserted into the waveguide and the transmitted scattering parameter (S{sub 21}) is measured. The extraction method relies on computational electromagnetic simulations, coupled with a genetic algorithm, to match the experimental S{sub 21} measurement. The sensitivity of the technique to sample length was explored by simulating specimen lengths from 2.54 to 15.24 cm, in 2.54 cm increments. Analysis of our simulated data predicts the technique will have the sensitivity to measure loss tangent values on the order of 10{sup −3} for materials such as polymers with relatively low real permittivity values. The ability to accurately characterize low-loss dielectric material specimens of polypropylene is demonstrated experimentally. The method was validated by excellent agreement with a free-space focused-beam system measurement of a polypropylene sheet. This technique provides the material measurement community with the ability to accurately extract material properties of low-loss material specimen over the entire X-band range. This technique could easily be extended to other frequency bands.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Atomic, electronic, and magnetic properties of bimetallic ZrCo clusters: A first-principles study

Here, we report the atomic, electronic, and magnetic structures of small Zr{sub m}Co{sub n} (m + n = 2, 4, 6, and 8) alloy clusters based on spin-polarized density functional theory under the plane wave based pseudo-potential approach. The ground state geometry and other low-lying stable isomers of each cluster have been identified using the cascade genetic algorithm scheme. On the basis of the relative energy, it is found that Zr{sub 2}Co{sub 2} (for tetramer), Zr{sub 3}Co{sub 3} (for hexamer), and Zr{sub 4}Co{sub 4} (for octamer) are the most stable isomers than others. In order to underscore the hydrogen storage capacity of these small clusters, the hydrogen adsorption on the stable Zr{sub m}Co{sub n} (m + n = 2, 4, 6, and 8) clusters has also been studied. The electronic structures of Zr{sub m}Co{sub n} clusters with and without adsorbed hydrogen are described in terms of density of states spectra and charge density contours.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fluid dynamic design and experimental study of an aspirated temperature measurement platform used in climate observation

Due to the solar radiation effect, current air temperature sensors inside a thermometer screen or radiation shield may produce measurement errors that are 0.8 °C or higher. To improve the observation accuracy, an aspirated temperature measurement platform is designed. A computational fluid dynamics (CFD) method is implemented to analyze and calculate the radiation error of the aspirated temperature measurement platform under various environmental conditions. Then, a radiation error correction equation is obtained by fitting the CFD results using a genetic algorithm (GA) method. In order to verify the performance of the temperature sensor, the aspirated temperature measurement platform, temperature sensors with a naturally ventilated radiation shield, and a thermometer screen are characterized in the same environment to conduct the intercomparison. The average radiation errors of the sensors in the naturally ventilated radiation shield and the thermometer screen are 0.44 °C and 0.25 °C, respectively. In contrast, the radiation error of the aspirated temperature measurement platform is as low as 0.05 °C. This aspirated temperature sensor allows the radiation error to be reduced by approximately 88.6% compared to the naturally ventilated radiation shield, and allows the error to be reduced by a percentage of approximately 80% compared to the thermometer screen. The mean absolute error and root mean square error between the correction equation and experimental results are 0.032 °C and 0.036 °C, respectively, which demonstrates the accuracy of the CFD and GA methods proposed in this research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Methodology for optimizing composite towers for use on floating wind turbines

In this work, a methodology for the design and optimization of a composite wind turbine tower for use on a floating offshore platform is presented. A composite turbine tower on a floating offshore platform not only has the potential to reduce maintenance and upkeep costs associated with the use of steel offshore but also has potential to reduce the tower mass and subsequently the support platform mass. The optimization problem is formulated to obtain a turbine tower that meets all strength and serviceability criteria and minimizes the tower mass. The optimization and design process link a number of dynamic analyses and finite element routines using a genetic algorithm. This work documents the optimization and design software and illustrates its use in various case studies for a 6 MW floating wind turbine system. Case studies include the optimization of a steel tower as a comparison to a composite material tower and the use of a cored, sandwich panel composite tower versus a solid composite tower. The results demonstrate that significant reductions in the tower mass are likely when comparing a steel tower with a composite tower. Also demonstrated for the platform and turbine configuration considered in this work is that the minimum mass tower design is driven towards a solid shell composite configuration, rather than a sandwich panel tower shell, in the face of reasonable design constraints.

17 WIND ENERGY↗

Genarris: Random generation of molecular crystal structures and fast screening with a Harris approximation

Herein, we present Genarris, a Python package that performs configuration space screening for molecular crystals of rigid molecules by random sampling with physical constraints. For fast energy evaluations, Genarris employs a Harris approximation, whereby the total density of a molecular crystal is constructed via superposition of single molecule densities. Dispersion-inclusive density functional theory is then used for the Harris density without performing a self-consistency cycle. Genarris uses machine learning for clustering, based on a relative coordinate descriptor developed specifically for molecular crystals, which is shown to be robust in identifying packing motif similarity. In addition to random structure generation, Genarris offers three workflows based on different sequences of successive clustering and selection steps: the "Rigorous" workflow is an exhaustive exploration of the potential energy landscape, the "Energy" workflow produces a set of low energy structures, and the "Diverse" workflow produces a maximally diverse set of structures. The latter is recommended for generating initial populations for genetic algorithms. Here, the implementation of Genarris is reported and its application is demonstrated for three test cases. Published by AIP Publishing.

74 ATOMIC AND MOLECULAR PHYSICS↗

Temporal feedback control of high-intensity laser pulses to optimize ultrafast heating of atomic clusters

We describe how active feedback routines can be applied at a limited repetition rate (5 Hz) to optimize high-power (>10 TW) laser interactions with clustered gases. Optimization of x-ray production from an argon cluster jet, using a genetic algorithm, approximately doubled the measured energy through temporal modification of the 150 mJ driving laser pulse. This method achieved an increased radiation yield through exploration of a multi-dimensional parameter space, without requiring detailed a priori knowledge of the complex cluster dynamics. The optimized laser pulses exhibited a slow rising edge to the intensity profile, which enhanced the laser energy coupling into the cluster medium, compared to the optimally compressed FWHM pulse (40 fs). This report suggests that this technique can be more widely utilized for control of intense pulsed secondary radiation from petawatt-class laser systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

On a physics-based model equation for shock-position evolution in PMMA

A governing differential equation for shock position in PMMA was derived from momentum conservation and an experimentally determined decay law for shock pressure. A new multi-diagnostic characterization method for measuring detonator pressure and wave shape output in PMMA witness blocks provided temporally resolved, 1-D, shock-position data that was iteratively fit by solutions to the governing equation via a unique genetic algorithm solver. The goal was to calculate a solution that describes the temporal evolution of shock pressure in PMMA starting at the detonator interface. The empirical decay law was investigated using experimental data, where different regimes were considered for the decay coefficients. A successful solution provides extensive performance information that is directly relevant to the understanding and characterization of detonator function.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Investigation of high X-ray conversion efficiency Kr filled gas sources at the National Ignition Facility

In this work, we report on the performance of high x-ray fluence Kr K-shell sources that are being developed for high energy density experiments. These targets are 4.1 mm in diameter 4.4 mm tall hollow epoxy tubes having a 40 μm thick wall holding 1.5 atm of Kr gas. For these shots, the National Ignition Facility laser delivered a nominally constant total energy of ≈750 kJ of 351 nm (3ω) light at the three power levels [e.g., ≈120 (low), ≈145 (medium), and ≈210 TW (high)]. The Kr K-shell (E photon = 8–20 keV) x-ray radiant intensity and radiant energy (kJ/sr) of these sources were found to increase as a function of laser power but began to plateau at the highest laser power. The Kr K-shell radiant energy increased from ≈1 kJ/sr at ≈120 TW to ≈2 kJ/sr at ≈210 TW. Radiation hydrodynamics simulations predict radiant energies to be always higher than these measurements. The increase in K-shell emission is attributed to its strong dependence on the electron temperature. Electron temperature distributions were inferred from measured Heα and Lyα line emission through the use of a genetic algorithm and Scram modeling. The inferred temperatures from the experiment are 20% to 30% higher than those predicted from modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pt 8 cluster on alumina under a pressure of hydrogen: Support-dependent reconstruction from first-principles global optimization

Alumina supported Pt nano clusters under hydrogen environment play a crucial role for many heterogeneous catalysis applications. As such, we conducted grand canonical genetic algorithm (GCGA) simulations for supported Pt 8 clusters in hydrogen gas environment to study the intra-cluster, cluster-support, and cluster-adsorbate interactions. Two alumina surfaces, α-Al 2 O 3 (0001) and $γ$-Al 2 O 3 (100), and two conditions T=600°C, p H2 = 0.1bar and T=25°C, p H2 = 1.0 bar were considered corresponding to low and high hydrogen chemical potential $μ$ H , respectively. The low free energy ensemble of Pt 8 is decorated by a medium (2–12 H), resp. high (20–30 H), number of hydrogen atoms under equilibrium at low $μ$ H , respectively, high $μ$ H , and undergoes different morphology transformations on the two surfaces. On α-Al2O3(0001), Pt8 is mostly 3D but very fluxional in structure at low μH and converts to open one-layer 2D structures with minimal fluxionality at high μH, whereas on $γ$-Al 2 O 3 (100), the exact opposite occurs, and Pt 8 clusters present one-layer 2D shapes at low $μ$ H and switch into compact 3D shapes under high $μ$ H , during which the Pt 8 cluster preserves moderate fluxionality. Further analysis reveals similar Pt–Pt bond length increase when switching from low $μ$ H to high $μ$ H on both surfaces, though morphology transformations are different. Electronic structure analysis shows the existence of bonding interactions between Pt and Lewis acidic Al 3+ sites along with the Pt – O interaction, which implies the necessity to include Al neighbors to discuss the electronic structure of small Pt clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Augmenting machine learning of energy landscapes with local structural information

We present a machine learning approach for accurately predicting formation energies of binary compounds in the context of crystal structure predictions. The success of any machine learning model depends significantly on the choice of representation used to encode the relevant physical information into machine-learnable data. We test different representation schemes based on partial radial and angular distribution functions (RDF+ADF) on Al–Ni and Cd–Te structures generated using our genetic algorithm for structure prediction. We observe a remarkable improvement in predictive accuracy upon transitioning from global to atom-centered representations, resulting in a threefold decrease in prediction errors. We show that a support vector regression model using a combination of atomic radial and angular distribution functions performs best at the formation energy prediction task, providing small root mean squared errors of 3.9 meV/atom and 10.9 meV/atom for Al–Ni and Cd–Te, respectively. We test the performance of our models against common traditional descriptors and find that RDF- and ADF-based representations significantly outperform many of those in the prediction of formation energies. The high accuracy of predictions makes our machine learning models great candidates for the exploration of energy landscapes.

Honrao, Shreyas J. (ORCID:0000000166155257)↗

Aperiodic optical coatings for neutral-color semi-transparent organic photovoltaics

Semi-transparent organic photovoltaics (ST-OPVs) have the potential for integration with windows for ubiquitous power generating applications. Typically, such applications require that ST-OPVs be neutrally transparent across the visible and exhibit both a high average photopic transmittance (APT) and color rendering index, as well as iso-energetic chromaticity coordinates. In this work, we demonstrate the design and use of optical coatings to achieve ST-OPVs with a neutral visible transmittance of APT = 50%, a power conversion efficiency of 8.3%, and optical properties that are independent of a ± 30° variation in the solar angle of incidence. As a result, these simple optical coatings are rapidly designed using a genetic algorithm and transfer matrix formalism.

14 SOLAR ENERGY↗

A transferable classical force field to describe glyme based lithium solvate ionic liquids

A non-polarizable force field for lithium (Li + ) and bis(trifluoromethanesulfonyl)imide (TFSI – ) ions solvated in diglyme at around 0.2 mol fraction salt concentration was developed based on ab initio molecular dynamics (AIMD) simulations and a modified polymer consistent force field model. A force–torque matching based scheme, in conjunction with a genetic algorithm, was used to determine the Lennard-Jones (LJ) parameters of the ion–ion and ion–solvent interactions. This force field includes a partial charge scaling factor and a scaling factor for the 1–4 interactions. The resulting force field successfully reproduces the radial distribution function of the AIMD simulations and shows better agreement compared to the unmodified force field. The new force field was then used to simulate salt solutions with glymes of increasing chain lengths and different salt concentrations. The comparison of the MD simulations, using the new force field, with experimental data at different salt concentrations and AIMD simulations on equimolar concentrations of the triglyme system demonstrates the transferability of the force field parameters to longer glymes and higher salt concentrations. Furthermore, the force field appears to reproduce the features of the experimental x-ray structure factors, suggesting accuracy beyond the first solvation shell, for equimolar salt solutions using both triglyme and tetraglyme as the solvent. Altogether, the new force field was found to accurately reproduce the molecular descriptions of LiTFSI-glyme systems not only at various salt concentrations but also with glymes of different chain lengths. Thus, the new force field provides a useful and accurate tool to perform in silico studies of this family of systems at the atomistic level.

25 ENERGY STORAGE↗

Enhancing Thomson scattering polychromator performance with multi-pass spectral filters

In photon-deficient, noncollective Thomson scattering diagnostics, filter polychromators are typically employed in the spectral analysis of Thomson-scattered signals to achieve acceptable signal-to-noise performance. Currently, the most common polychromator filter configuration employs a set of single-passband optical filters that define individual spectral channels. Here, we introduce a new spectral analysis method for Thomson scattering based on spectral filters with multiple passbands, referred to as Thomson scattering spectral multiplexing. Implementing multi-bandpass spectral filters on polychromators increases the achievable range of electron temperature measurement for a given number of filters employed. In addition, Thomson scattering spectral multiplexing reduces systematic measurement uncertainty, with fewer required spectral channels, thereby decreasing light loss from reduced optical element interactions. A multi-bandpass filter set, optimized by a genetic algorithm, has been successfully installed and tested on the Helically Symmetric eXperiment (HSX), demonstrating the benefits of the Thomson scattering spectral multiplexing method.

Instruments & Instrumentation↗

An experimentally informed design process for future inertial confinement fusion facilities

The achievement of ignition in the laboratory has renewed interest in defining the requirements for a future high-gain inertial confinement fusion (ICF) facility. Our best chance of predicting future ICF performance is with 3-D radiation hydrodynamic simulations that have been benchmarked against experimental data, but their high computational cost is prohibitive for use in practical design studies. We introduce a hierarchical approach where 3-D simulations are tuned to match experimental measurements and used to train 3-D degradation models in 1-D simulations allowing for accurate predictions over the entire OMEGA direct-drive database. A genetic algorithm was used in combination with the trained 1-D simulations to search for optimal direct-drive implosion designs at driver energies ranging from 20 kJ to 10 MJ. As the fidelity of 3-D codes improves, this approach will provide a viable experimentally informed tool for defining the next ICF facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗