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At least 919 records · Page 51

Identification of subsurface structures using electromagnetic data and shape priors

We consider the inverse problem of identifying large-scale subsurface structures using the controlled source electromagnetic method. To identify structures in the subsurface where the contrast in electric conductivity can be small, regularization is needed to bias the solution towards preserving structural information. We propose to combine two approaches for regularization of the inverse problem. In the first approach we utilize a model-based, reduced, composite representation of the electric conductivity that is highly flexible, even for a moderate number of degrees of freedom. With a low number of parameters, the inverse problem is efficiently solved using a standard, second-order gradient-based optimization algorithm. Further regularization is obtained using structural prior information, available, e.g., from interpreted seismic data. The reduced conductivity representation is suitable for incorporation of structural prior information. Such prior information cannot, however, be accurately modeled with a gaussian distribution. To alleviate this, we incorporate the structural information using shape priors. The shape prior technique requires the choice of kernel function, which is application dependent. We argue for using the conditionally positive definite kernel which is shown to have computational advantages over the commonly applied gaussian kernel for our problem. Numerical experiments on various test cases show that the methodology is able to identify fairly complex subsurface electric conductivity distributions while preserving structural prior information during the inversion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simultaneous reproduction of experimental profiles, fluxes, transport coefficients, and turbulence characteristics via nonlinear gyrokinetic profile predictions in a DIII-D ITER similar shape plasma

Experimental conditions obtained on the DIII-D tokamak in the ITER Similar Shape (ISS) have been compared extensively with nonlinear gyrokinetic simulation using the CGYRO code [Candy et al., J. Comput. Phys. 324, 73–93 (2016)] with comparisons spanning ion and electron heat fluxes, electron and impurity particle transport, and turbulent fluctuation levels and characteristics. Bayesian optimization techniques [Rodriguez-Fernandez et al., Nucl. Fusion 62(7), 076036 (2022)], combined with nonlinear gyrokinetics, have been used to obtain simultaneously Qi, Qe, and Γe flux-matched profiles that are found to be in good agreement with experimental profile measurements. Synthetic diagnostics were used to compare measured beam emission spectroscopy and correlation electron cyclotron emission turbulent fluctuations with nonlinear simulation. Although some disagreements exist, nonlinear simulations are found to be in generally good agreement with measured fluctuation levels, spectral shapes, and measured radial trends in low-k δne/ne and δTe/Te. Low (Li and C) and mid-Z (Ca) impurity transport was also compared with these flux-matched simulations. Fully stripped, low-Z impurities are well reproduced by the gyrokinetic modeling while clear disagreement exists in comparisons with mid-Z impurities. Nonlinear gyrokinetic investigation into the Z dependence of impurity transport in the ISS conditions is also performed, demonstrating clear trends of impurity diffusion with impurity Z (both D∝Z and D∝1/Z) that vary with the radial location studied. These trends are shown to result from the local dominance of ion temperature gradient or ∇n driven trapped electron mode turbulence and may contribute to the disagreement between simulation and experiment in mid-Z impurity transport. The results of this work represent one of the most complete validation studies of the gyrokinetic model performed to date and provide an example of new capabilities for predicting performance in future fusion devices.

Physics↗

Active interlocking metasurfaces enabled by shape memory alloys

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Additive manufacturing↗

Efficient estimation of the modified Gromov–Hausdorff distance between unweighted graphs

Abstract Gromov–Hausdorff distances measure shape difference between the objects representable as compact metric spaces, e.g. point clouds, manifolds, or graphs. Computing any Gromov–Hausdorff distance is equivalent to solving an NP-hard optimization problem, deeming the notion impractical for applications. In this paper we propose a polynomial algorithm for estimating the so-called modified Gromov–Hausdorff (mGH) distance, a relaxation of the standard Gromov–Hausdorff (GH) distance with similar topological properties. We implement the algorithm for the case of compact metric spaces induced by unweighted graphs as part of Python library , and demonstrate its performance on real-world and synthetic networks. The algorithm finds the mGH distances exactly on most graphs with the scale-free property. We use the computed mGH distances to successfully detect outliers in real-world social and computer networks.

Oles, Vladyslav (ORCID:0000000188727463)↗

Extended virtual element method for the Laplace problem with singularities and discontinuities

In this paper, we propose the extended virtual element method (X-VEM) to treat singularities and crack discontinuities that arise in the Laplace problem. The virtual element method (VEM) is a stabilized Galerkin formulation on arbitrary polytopal meshes, wherein the basis functions are implicit (virtual)—they are not known explicitly nor do they need to be computed within the problem domain. In this work, suitable projection operators are used to decompose the bilinear form on each element into two parts: a consistent term that reproduces the first-order polynomial space and a correction term that ensures stability. A similar approach is pursued in the X-VEM with a few notable extensions. To capture singularities and discontinuities in the discrete space, we augment the standard virtual element space with an additional contribution that consists of the product of virtual nodal basis (partition-of-unity) functions with enrichment functions. For discontinuities, basis functions are discontinuous across the crack and for singularities a weakly singular enrichment function that satisfies the Laplace equation is chosen. For the Laplace problem with a singularity, we devise an extended projector that maps functions that lie in the extended virtual element space onto linear polynomials and the enrichment function, whereas for the discontinuous problem, the consistent element stiffness matrix has a block-structure that is readily computed. An adaptive homogeneous numerical integration method is used to accurately and efficiently (no element-partitioning is required) compute integrals with integrands that are weakly singular. Once the element projection matrix is computed, the same steps as in the standard VEM are followed to compute the element stabilization matrix. Numerical experiments are performed on quadrilateral and polygonal (convex and nonconvex elements) meshes for the problem of an $\textit{L}$-shaped domain with a corner singularity and the problem of a cracked membrane under mode III loading, and results are presented that affirm the sound accuracy and demonstrate the optimal rates of convergence in the $\textit{L}^2$ norm and energy of the proposed method.

42 ENGINEERING↗

Synthesis, characterization and rate capability performance of the micro-porous MnO{sub 2} nanowires as cathode material in lithium batteries

Graphical abstract: Translating MnO{sub 2} nanowires as cathode materials in coin cell and studying their discharge behavior and cycling stability at different C-rates. - Highlights: • MnO{sub 2} nanowires have been synthesized via hydrothermal route. • The nanowires were employed as cathode materials in Li-batteries. • Discharge and cycling stability were studied at different C-rates. • Specific capacity and power density of 251 mAh g{sup −1} and 200 W kg{sup −1} were attained. - Abstract: A peculiar architecture of one-dimensional MnO{sub 2} nanowires was synthesized by an optimized hydrothermal route and has been lucratively exploited to fabricate highly efficient microporous electrode overlays for lithium batteries. These fabricated electrodes comprised of interconnected nanoscale units with wire-shaped profile which exhibits high aspect ratio in the order of 10{sup 2}. Their outstanding intercalation/de-intercalation prerogatives have also been studied to fabricate lithium coin cells which revealed a significant specific capacity and power density of 251 mAh g{sup −1} and 200 W kg{sup −1}, respectively. A detailed electrochemical study was performed to elucidate how surface morphology and redox reaction behaviors underlying these electrodes influence the cyclic behavior of the electrode. Rate capability tests at different C-rates were performed to evaluate the capacity and cycling performance of these coin cells.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

An adjoint method for determining the sensitivity of island size to magnetic field variations

An adjoint method to calculate the gradient of island width in stellarators is presented and applied to a set of magnetic field configurations. The underlying method for calculation of the island width is that of Cary & Hanson ( Phys. Fluids B, vol. 3, issue 4, 1991, pp. 1006–1014) (with a minor modification), and requires that the residue of the island centre be small. Therefore, the gradient of the residue is calculated in addition. Both the island width and the gradient calculations are verified using an analytical magnetic field configuration introduced by Reiman & Greenside ( Comput. Phys. Commun. , vol. 43, issue 1, 1986, pp. 157–167). The method is also applied to the calculation of the shape gradient of the width of a magnetic island in a National Compact Stellarator Experiment (NCSX) vacuum configuration with respect to positions on a coil. A gradient-based optimization is applied to a magnetic field configuration studied by Hanson & Cary ( Phys. Fluids , vol. 27, issue 4, 1984, pp. 767–769) to minimize stochasticity by adding perturbations to a pair of helical coils. Although only vacuum magnetic fields and an analytical magnetic field model are considered in this work, the adjoint calculation of the island width gradient could also be applied to a magnetohydrodynamic (MHD) equilibrium if the derivative of the magnetic field, with respect to the equilibrium parameters, is known. Using the island width gradient calculation presented here, more general gradient-based optimization methods can be applied to design stellarators with small magnetic islands. Moreover, the sensitivity of the island size may itself be optimized to ensure that coil tolerances, with respect to island size, are kept as high as possible.

Physics↗

Application of the diagnostic radiological index of protection to protective garments

Purpose: Previously, the diagnostic radiological index of protection (DRIP) was proposed as a metric for quantifying the protective value of radioprotective garments. The DRIP is a weighted sum of the percent transmissions of different radiation beams through a garment. Ideally, the beams would represent the anticipated stray radiation encountered during clinical use. However, it is impractical to expect a medical physicist to possess the equipment necessary to accurately measure transmission of scattered radiation. Therefore, as a proof of concept, the authors tested a method that applied the DRIP to clinical practice. Methods: Primary beam qualities used in interventional cardiology and radiology were observed and catalogued. Based on the observed range of beam qualities, five representative clinical primary beam qualities, specified by kV and added filtration, were selected for this evaluation. Monte Carlo simulations were performed using these primary beams as source definitions to generate scattered spectra from the clinical primary beams. Using numerical optimization, ideal scatter mimicking primary beams, specified by kV and added aluminum filtration, were matched to the scattered spectra according to half- and quarter-value layers and spectral shape. To within reasonable approximation, these theoretical scatter-mimicking primary beams were reproduced experimentally in laboratory x ray beams and used to measure transmission through pure lead and protective garments. For this proof of concept, the DRIP for pure lead and the garments was calculated by assigning equal weighting to percent transmission measurements for each of the five beams. Finally, the areal density of lead and garments was measured for consideration alongside the DRIP to assess the protective value of each material for a given weight. Results: The authors identified ideal scatter mimicking primary beams that matched scattered spectra to within 0.01 mm for half- and quarter-value layers in copper and within 5% for the shape function. The corresponding experimental scatter-mimicking primary beams matched the Monte Carlo generated scattered spectra with maximum deviations of 6.8% and 6.6% for half- and quarter-value layers. The measured DRIP for 0.50 mm lead sheet was 2.0, indicating that it transmitted, on average, 2% of incident radiation. The measured DRIP for a lead garment and one lead-alternative garment closely matched that for pure lead of 0.50 mm thickness. The DRIP for other garments was substantially higher than 0.50 mm lead (3.9–5.4), indicating they transmitted about twice as much radiation. When the DRIP was plotted versus areal density, it was clear that, of the garments tested, none were better than lead on a weight-by-weight basis. Conclusions: A method for measuring the DRIP for protective garments using scatter-mimicking primary beams was developed. There was little discernable advantage in protective value per unit weight for lead-alternative versus lead-only garments. Careful consideration must be given to the balance of protection and weight when choosing a lead-alternative protective garment with a lower specified “lead equivalence,” e.g., 0.35 mm. The DRIP has the potential to resolve this dilemma. Reporting the DRIP relative to areal density is an ideal metric for objective comparisons of protective garment performance, considering both protective value in terms of transmission of radiation and garment weight.

60 APPLIED LIFE SCIENCES↗

Synthetic genetic circuits as a means of reprogramming plant roots

We report the shape of a plant’s root system influences its ability to reach essential nutrients in the soil and to acquire water during drought. Progress in engineering plant roots to optimize water and nutrient acquisition has been limited by our capacity to design and build genetic programs that alter root growth in a predictable manner. We developed a collection of synthetic transcriptional regulators for plants that can be compiled to create genetic circuits. These circuits control gene expression by performing Boolean logic operations and can be used to predictably alter root structure. This work demonstrates the potential of synthetic genetic circuits to control gene expression across tissues and reprogram plant growth.

59 BASIC BIOLOGICAL SCIENCES↗

A Least-Squares-Based Weak Galerkin Finite Element Method for Second Order Elliptic Equations

Here, in this article, we introduce a least-squares-based weak Galerkin finite element method for the second order elliptic equation. This new method is shown to provide very accurate numerical approximations for both the primal and the flux variables. In contrast to other existing least-squares finite element methods, this new method allows us to use discontinuous approximating functions on finite element partitions consisting of arbitrary polygon/polyhedron shapes. We also develop a Schur complement algorithm for the resulting discretization problem by eliminating all the unknowns that represent the solution information in the interior of each element. Optimal order error estimates for both the primal and the flux variables are established. An extensive set of numerical experiments are conducted to demonstrate the robustness, reliability, flexibility, and accuracy of the least-squares-based weak Galerkin finite element method. Finally, the numerical examples cover a wide range of applied problems, including singularly perturbed reaction-diffusion equations and the flow of fluid in porous media with strong anisotropy and heterogeneity.

nite element methods↗

Melt-Pool Temperature and Size Measurement During Direct Laser Sintering

Additive manufacturing has demonstrated the ability to fabricate complex geometries and components not possible with conventional casting and machining. In many cases, industry has demonstrated the ability to fabricate complex geometries with improved efficiency and performance. However, qualification and certification of processes is challenging, leaving companies to focus on certification of material though design allowable based approaches. This significantly reduces the business case for additive manufacturing. Therefore, real time monitoring of the melt pool can be used to detect the development of flaws, such as porosity or un-sintered powder and aid in the certification process. Characteristics of the melt pool in the Direct Laser Sintering (DLS) process is also of great interest to modelers who are developing simulation models needed to improve and perfect the DLS process. Such models could provide a means to rapidly develop the optimum processing parameters for new alloy powders and optimize processing parameters for specific part geometries. Stratonics’ ThermaViz system will be integrated with the Renishaw DLS system in order to demonstrate its ability to measure melt pool size, shape and temperature. These results will be compared with data from an existing IR camera to determine the best approach for the determination of these critical parameters.

42 ENGINEERING↗

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3–20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

42 ENGINEERING↗

Chapter 4 - Mechanical Fractionations of Biomass Feedstocks for Enhanced Pretreatment and Conversion. In the book Biomass Preprocessing and Pretreatments for Production of Biofuels: Mechanical, Chemical and Thermal Methods.

Living plant biomass consists of multiple types of tissues and organs, each performing unique and essential physical or biological functions in the living plant. Because of these differences in form and function, these tissues and organs can retain these unique physical and chemical properties after senescence or harvest. Properties such as ash composition, ash content, carbohydrate content, lignin content, density, and recalcitrance can vary widely between plant parts and tissues. Mechanical fractionation of biomass feedstocks has the potential to take advantage of these naturally occurring differences to produce physically or chemically unique fractions that have higher or lower value within specific biochemical or thermochemical conversion platforms. Mechanical fractionation techniques that have shown promise include density separations in air or liquid, size separations, and automated sorting. Density separations, such as air classification, separate based on particle density, size, and shape. Size separations are highly dependent upon size reduction techniques, however anatomical differences can affect particle size. The chemical and physical properties of the resulting fractions help determine their optimal use. These unique fractions can be used directly or treated as ingredients and blended with other feedstocks or fractions of feedstocks to meet cost, quality, or conversion specifications.

09 BIOMASS FUELS↗

Hydrodynamic Design Optimization and Wave Tank Testing of a Self-Reacting Two-Body Wave Energy Converter

As worldwide energy consumption continues to increase, so does the demand for renewable energy sources. The total available wave energy resource for the United States alone is 2,640 TWh/yr; nearly two thirds of the 4,000 TWh of electricity used in the United States each year. It is estimated that nearly half of that available energy is recoverable through wave energy conversion techniques. In this thesis, a two-body ‘point absorber’ type wave energy converter with a mechanical power-takeoff is investigated. The two-body wave energy converter extracts energy through the relative motion of a floating buoy and a neutrally buoyant submerged body. Using a linear frequency-domain model, analytical solutions of the optimal power and the corresponding power-takeoff components are derived for the two-body wave energy converter. Using these solutions, a case study is conducted to investigate the influence of the submerged body size on the absorbed power of the device in regular and irregular waves. Here it is found that an optimal mass ratio between the submerged body and floating buoy exists where the device will achieve resonance. Furthermore, a case study to investigate the influence of the submerged body shape on the absorbed power is conducted using a time-domain numerical model. Here it is found that the submerged body should be designed to reduce the effects of drag, but to maintain relatively large hydrodynamic added mass and excitation force. To validate the analytical and numerical models, a 1/30th scale model of a two-body wave energy converter is tested in a wave tank. The results of the wave tank tests show that the two-body wave energy converter can absorb nearly twice the energy of a single-body ‘point absorber’ type wave energy converter.

16 TIDAL AND WAVE POWER↗

Concept of a polarized positron source for CEBAF

This thesis focuses on the development of polarized and unpolarized positron beams for the future experimental pro- gram of hadronic physics at the Thomas Jefferson National Accelerator Facility (JLab). The primary challenge is to produce high-duty-cycle and high-intensity polarized positron beams. The JLab positron source, which is based on the PEPPo (Polarized Electrons for Polarized Positrons) technique, aims to use a high intensity (1 mA) and highly polarized (90%) continuous electron beam of moderate energy (120 MeV) to produce either a low intensity (>50 nA), highly polarized (60%) positron beam or a high intensity (>1 ?A), unpolarized positron beam. The optimization of the layout and performance of the positron source is examined in this thesis. The source is designed with a specialized second injector to generate, transport, accelerate, and shape positron beams. It is compatible with acceleration at the Continuous Electron Beam Accelerator Facility (CEBAF), and the investigation results are presented in this document.

Habet, Sami↗

Piston geometry and stroke optimization for high efficiency propane spark ignition engines

Propane has unique properties and offers interesting characteristics for high-efficiency spark ignition engines. Its high volatility reduces or completely eliminates fuel-wall wetting and facilitates fuel air mixing. Furthermore, propane has a research octane number of 112 and a high octane sensitivity of 15. Finally, its laminar flame speed is on the same order as that of conventional gasoline, and it exhibits high dilution tolerance. Modern spark ignition internal combustion engines rely on fast combustion rates and high dilution to achieve high brake thermal efficiencies. To accomplish this, high stroke-to-bore ratios and high geometric compression ratios have been used in new engine designs. Therefore, propane’s relatively high laminar flame speeds, high knock resistance, and dilution tolerance make it an excellent candidate fuel for modern spark ignition engines. The objective of this work is to co-optimize the piston geometry and the engine stroke to maximize the efficiency of a spark-ignition engine fueled with propane. 3D computational fluid dynamics (CFD) simulations employing the extended coherent flamelet model were used to study the parametric effects of piston shape and stroke length. A piston geometry based on high performing pistons was parameterized using four controlling parameters. The piston geometry and engine stroke design space was explored using deterministic and quasi-random sampling techniques. In conclusion, a Gaussian process regression model was built using the simulation data to explain the results observed.

33 ADVANCED PROPULSION SYSTEMS↗

Domain Optimization for an Acoustic Waveguide Scattering Problem

We consider a domain optimization problem of an unbounded domain, which models scattering of a time-harmonic acoustic wave at the junction of two closed waveguides. Solutions of our problem fulfill the Helmholtz equation with a real wavenumber, a modal radiation condition and homogeneous Dirichlet boundary conditions. We derive an a-priori bound for the solution on a certain class of domains (which is compact in the Hausdorff metric topology) and show that within this class the solution depends H{sup 1}-continuously on the domain. Furthermore, we show some numerical examples to illustrate our results, which were calculated using the domain (or shape) derivative of our problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimized dark matter searches in deep observations of Segue 1 with MAGIC

We present the results of stereoscopic observations of the satellite galaxy Segue 1 with the MAGIC Telescopes, carried out between 2011 and 2013. With almost 160 hours of good-quality data, this is the deepest observational campaign on any dwarf galaxy performed so far in the very high energy range of the electromagnetic spectrum. We search this large data sample for signals of dark matter particles in the mass range between 100 GeV and 20 TeV. For this we use the full likelihood analysis method, which provides optimal sensitivity to characteristic gamma-ray spectral features, like those expected from dark matter annihilation or decay. In particular, we focus our search on gamma-rays produced from different final state Standard Model particles, annihilation with internal bremsstrahlung, monochromatic lines and box-shaped signals. Our results represent the most stringent constraints to the annihilation cross-section or decay lifetime obtained from observations of satellite galaxies, for masses above few hundred GeV. In particular, our strongest limit (95% confidence level) corresponds to a ∼500 GeV dark matter particle annihilating into τ{sup +}τ{sup −}, and is of order <σ{sub ann}v>≃ 1.2×10{sup −24} cm{sup 3} s{sup −1} — a factor ∼40 above the <σ{sub ann}v>≃ thermal value.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗