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Among the various aspects of the present disclosure is the provision of systems for producing radioisotopes and improving the specific activity of radioisotopes (e.g., Cu-64 chloride). As described herein, the system includes a target material area or target material shape that matches the proton beam strike area or proton beam strike shape, resulting in optimal thickness with less target material required.
With the ever increased penetration of renewables in power grid, economic power dispatch faces a challenge in terms of min-imizing the generation cost which is increasingly affected by random factors and constraints subjected to random inputs. In this context, the cost functions are random for which the widely used mean value based minimization can only achieve limited profit gain. Indeed, as the probability density function (PDF) is a comprehensive measure of characteristics of any random varia-bles, the desired optimization should address the shaping of the PDF of the generation cost function rather just its mean value. Through a simple case study, this paper firstly reveals the long tail PDF shape of the cost function when the traditional mean-value based optimization is used. This is then followed by the de-velopment of a novel PDF-shaping-based method that optimizes both the mean and variance of the PDF of the cost function. It has been shown that the proposed approach can reshape the PDF of the generation cost function so as to make it as left and as narrow as possible, leading to a significant low risk for high generation cost. Simulation tests have been included to show the effectiveness of the proposed approach and encouraging results have been obtained.
In radiation therapy, x-ray dose must be precisely sculpted to the tumor, while simultaneously avoiding surrounding organs at risk. This requires modulation of x-ray intensity in space and/or time. Typically, this is achieved using a multi leaf collimator (MLC) - a complex mechatronic device comprising over one hundred individually powered tungsten ‘leaves’ that move in or out of the radiation field as required. Here, an all-electronic x-ray collimation concept with no moving parts is presented, termed “SPHINX”: Scanning Pencil-beam High-speed Intensity-modulated X-ray source. SPHINX utilizes a spatially distributed bremsstrahlung target and collimator array in conjunction with magnetic scanning of a high energy electron beam to generate a plurality of small x-ray “beamlets.” A simulation framework was developed in Topas Monte Carlo incorporating a phase space electron source, transport through user defined magnetic fields, bremsstrahlung x-ray production, transport through a SPHINX collimator, and dose in water. This framework was completely parametric, meaning a simulation could be built and run for any supplied geometric parameters. This functionality was coupled with Bayesian optimization to find the best parameter set based on an objective function which included terms to maximize dose rate for a user defined beamlet width while constraining inter-channel cross talk and electron contamination. Designs for beamlet widths of 5, 7, and 10 mm 2 were generated. Each optimization was run for 300 iterations and took approximately 40 h on a 24-core computer. For the optimized 7-mm model, a simulation of all beamlets in water was carried out including a linear scanning magnet calibration simulation. Finally, a back-of-envelope dose rate formalism was developed and used to estimate dose rate under various conditions. The optimized 5–, 7–, and 10-mm models had beamlet widths of 5.1 , 7.2 , and 10.1 mm 2 and dose rates of 3574, 6351, and 10 015 Gy/C, respectively. The reduction in dose rate for smaller beamlet widths is a result of both increased collimation and source occlusion. For the simulation of all beamlets in water, the scanning magnet calibration reduced the offset between the collimator channels and beam centroids from 2.9 ±1.9 mm to 0.01 ±0.03 mm. A slight reduction in dose rate of approximately 2% per degree of scanning angle was observed. Based on a back-of-envelope dose rate formalism, SPHINX in conjunction with next-generation linear accelerators has the potential to achieve substantially higher dose rates than conventional MLC-based delivery, with delivery of an intensity modulated 100 x 100 mm 2 field achievable in 0.9 to 10.6 s depending on the beamlet widths used. Bayesian optimization was coupled with Monte Carlo modeling to generate SPHINX geometries for various beamlet widths. A complete Monte Carlo simulation for one of these designs was developed, including electron beam transport of all beamlets through scanning magnets, x-ray production and collimation, and dose in water. These results demonstrate that SPHINX is a promising candidate for sculpting radiation dose with no moving parts, and has the potential to vastly improve both the speed and robustness of radiotherapy delivery. A multi-beam SPHINX system may be a candidate for delivering magavoltage FLASH RT in humans.
Abstract Complex shapes of gold nanostars (GNS) have been the major obstacle to the comprehensive understanding of the rich plasmonic phenomena of GNS. We conducted extensive, systematic numerical study of far-field and near-field spectral responses of GNS for varying geometrical parameters (e.g., number of spikes, spike tip angle, and spike-to-core ratio) to elucidate the relationship between the optical property and the geometry of GNS. We found that symmetric configurations of GNS spikes generated both dipole and quadrupole localized surface plasmon (LSP) modes, their hybridization resulted in the final near-field intensity at the spike tips, and there existed a specific GNS geometry that optimized the hybridization and thus the E-field intensity for any given wavelength. From these results, we further identified the shapes of GNS that generated the strongest Surface Enhanced Raman Scattering (SERS) enhancement factors in the visible and NIR spectral range. Hence, our results provide guiding principles in determining the optimal geometry of GNS for SERS applications with any choice of excitation wavelength.
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Abstract not provided.
In this letter, we report the experimental demonstration of single-spike hard-X-ray free-electron laser pulses starting from noise with multi-eV bandwidth. Here, this is accomplished by shaping a low-charge electron beam with a slotted emittance spoiler and by adjusting the transport optics to optimize the beam-shaping accuracy. Based on elementary free-electron laser scaling laws, we estimate the pulse duration to be less than 1 fs full-width at half-maximum.
Bose–Einstein condensate (BEC)-based atom interferometry exploits low temperatures and long coherence lengths to facilitate high-precision measurements. Progress in atom interferometry promises improvements in navigational devices like gyroscopes and accelerometers, as well as applications in fundamental physics such as accurate determination of physical constants. Previous work demonstrates that beam splitters and mirrors for coherent manipulation of dilute BEC momentum in atom interferometers can be implemented with sequences of non-resonant standing-wave light pulses. While previous work focuses on the optimization of the optical pulses’ amplitude and duration to produce high-order momentum states with high fidelity, we explore how varying the shape of the optical pulses affects optimal beam-splitter performance, as well as the effect of pulse shape on the sensitivity of optimized parameters in achieving high fidelity in high-momentum states. Here, in simulations of two-pulse beam splitters utilizing optimized square, triangle, and sinc-squared pulse shapes applied to dilute BECs, we, in some cases, reduce parameter sensitivity by an order of magnitude while maintaining fidelity.
Practical applications of synthetic self-propelled nano and microparticles for microrobotics, targeted drug delivery, and manipulation at the nanoscale are rapidly expanding. However, fabrication limitations often hinder progress, resulting in relatively simple shapes and limited functionality. Here, taking advantage of 3D nanoscale printing, chiral micropropellers powered by the hydrogen peroxide reduction reaction are fabricated. Due to their chirality, the propellers exhibit multifunctional behavior controlled by an applied magnetic field: spinning in place (loitering), directed migration in the prescribed direction, capture, and transport of polymer cargo particles. Design parameters of the propellers are optimized by computation modeling based on mesoscale molecular dynamics. It is predicted by computer simulations, and confirmed experimentally, that clockwise rotating propellers attract each other and counterclockwise repel. These results shed light on how chirality and shape optimization enhance the functionality of synthetic autonomous micromachines.
In this paper, different optimal designs of Yagi–Uda nano-antennas (NAs) are introduced and analyzed based on different element shapes to maximize the directivity and radiation efficiency. The studied element shapes include triangular, hexagonal, cube, square, rotated square, rectangular, ellipsoid, and elliptical cylinder shapes. The NAs parameters for each design are optimized using particle swarm optimization algorithm to achieve high directivity at a wavelength of 500 nm for wireless point-to-point applications. The designs are numerically analysed using 3-D finite difference time domain method (3-D FDTD) via Lumerical software package. To illustrate the performance of the proposed antennas, different radiation parameters such as radiation pattern, directivity, and radiation efficiency have been studied. Moreover, a tolerance of ± 5% is calculated to consider the imperfections that may appear in the fabrication process at a nanoscale. The optimized rectangular prism NA achieves the highest directivity of 24.21 with an efficiency of 50.74%. However, the optimized triangular prism NA has the highest efficiency of 73% with a directivity of 20.89. This enhancement is mainly attributed to the efficient coupling between array elements along with low side lobe level. However, a trade-off between directivity and radiation efficiency is obtained by the hexagonal prism NA with directivity of 21.9 and radiation efficiency of 69.1%.
The Report for the 2023 Theory & Simulation Performance Target (TSPT) is presented herein. The 1st, 2nd and 3rd Quarter Reports are given in Sec. I, Sec. II and Sec. III. These are unchanged from those previously submitted, except that in this final document the equations, figures and citations have been automatically renumbered. The 4th Quarter Report is given in Sec. IV. The following material presents verification calculations of several widely used three-dimensional (3D) magnetohydrodynamic (MHD) equilibrium codes in strongly shaped configurations; for both fixed and free-boundary equilibria; for the so-called vacuum case and for the case of high plasma pressure; and, for magnetic fields that have nested magnetic surfaces and for fields that have a magnetic island. The configurations studied includes the recently discovered “precise-QA” case [Phys. Rev. Lett., 128, 035001 (2002)] and other highly optimized configurations. Because of the strong (extreme) shaping, the latter of these pose challenges to the 3D MHD codes. A new method is introduced for constructing coordinates in arbitrarily shaped toroidal domains, and this can improve the robustness of 3D equilibrium calculations. Beyond the equilibrium calculation, this report demonstrates the capability of performing non-linear extended-MHD modelling of optimized stellarator equilibria. This capability allows the assessment not only of linear stability thresholds but also of the nonlinear evolution of unstable equilibria to new configurations that might be far from the original configuration, with significantly different transport properties and magnetic topology. They also enable the self-consistent determination of pressure profiles in non-integrable magnetic topology through the use of highly anisotropic thermal-transport equations. The calculations presented here represent the first demonstration of extended-MHD calculations in strongly-shaped, optimized quasi-symmetric configurations.
Reducing the gap between rotating and stationary parts in gas turbine engines, and mitigating gas leakage via these paths, can significantly increase the performance and attendant efficiency. One approach to reducing such gaps is to deploy abradable coatings on the stationary shroud components as seals, to reduce the blade-tip clearances under operational conditions. Abradable coatings must be able to withstand high temperature oxidation, thermal cycling, and erosion, while providing optimal controlled abrasion and associated shape retention. Existing abradable seals utilized in power generation turbines have generally been optimized for use with natural gas-fired systems; however, preliminary testing of syngas and high-hydrogen-content (HHC) fired turbines has shown that the stability of hot-section materials (and presumably abradable sealing materials) may be substantially altered due to characteristic changes in the combustion by-products (partial pressures of water vapor, etc.) as well as characteristic impurities and particulate matter entrained in the fuel. The primary focus of this research program has been to develop a mechanistic understanding of how the altered combustion environments modify the thermo-mechanical stability and performance of the sealing materials, including the requisite abradable sealing behavior. A key component of the research program carried out has been an exploration of mechanisms underpinning observed degradation processes, and an assessment of connections to the combustion environments and characteristic non-combustible constituents. The ultimate goal of the project has been to advance the goals of the Advanced Turbine Program by developing materials design protocols leading to turbine hot-section components with improved resistance to service lifetime degradation under advanced fuels exposures. This research program has evaluated the performance and degradation of ceramic abradable seals used in the high-temperature turbine sections of gas turbine engines. The focus has been two-fold: (1) to understand performance of such materials in relation to the turbines operating on coal-derived syngas and high hydrogen content (HHC) fuels, ultimately seeking an improved understanding of factors that control performance and durability of abradable seal materials for these combustion environments (and play into materials design protocols); and (2) to evaluate the potential of alternative materials as abradable seals for the higher temperatures expected with IGCC and HHC fueled turbine systems. In particular, we carried out an initial assessment of multi-layered systems of existing abradable seal materials (YSZ) and other ceramics. The research program also investigated several classes of abradable coatings under simulated exposures to syngas-based combustion environments, evaluating the relevant wear behavior, hardness, stability under cyclic oxidation, and general thermo-mechanical behavior. The research also attempted to develop alternatives to carrying out full-scale combustion-based abradability test rig exposures to evaluate materials system performance. The research has been focused on correlating the measured thermo-mechanical behavior, and controlled abrasive wear, with the intrinsic properties of the multilayer coatings and processing-controlled microstructural features that have shown attractive machinability characteristics based on weak interfacial bonding between the constituent phases at elevate temperatures (while maintaining thermochemical stability). This program has resulted in an improved mechanistic understanding of factors governing performance of high temperature abradable seals, and degradation mechanisms unique to IGCC-based power generation turbine systems and the realization of coal-derived syngas and HHC-based combustion environments – ultimately with the goal of developing a knowledge base upon which the design of coatings that retain optimal sealing characteristics and are more resistant to the observed wear/attack mechanisms, important aspects of advancing the goals of the DOE Advanced Turbine Program.
The Advanced Sources and Detectors (ASD) project aims to build Scorpius, a multi pulse linear induction accelerator capable of delivering a 1.4 kA electron beam at energies up to 24 MeV. One of the primary advancements of Scorpius is the use of solid state pulsed power (SSPP) to provide flexibility in pulse shaping by independently triggering 45 individual stages stacked in each of 984 line replaceable units (LRU), with 168 LRUs dedicated to the injector. By leveraging circuit modeling of each LRU stage, a machine learning model of the SSPP will be developed to allow for optimization of the pulse shape, including pulse flattening and reflection mitigation. Particle-in-cell simulations of Scorpius have, for example, demonstrated that reducing reflections during multi-pulse operation mitigates beam spill by preventing the production of off-energy electrons between pulses, thereby abating stimulated ion desorption from the wall and beam charge neutralization. This machine learning model will be validated and tuned with experimental data collected from the Scorpius injector and Integrated Test Stand
The Compact Linear Collider (CLIC) is a study for an electron–positron machine aiming at accelerating and colliding particles at the next energy frontier. The CLIC concept is based on the novel two-beam acceleration scheme, where a high-current low-energy drive beam generates RF in series of power extraction and transfer structures accelerating the low-current main beam. To compensate for the transient beam-loading and meet the energy spread specification requirements for the main linac, the RF pulse shape must be carefully optimized. This was recently modelled by varying the drive beam phase switch times in the sub-harmonic buncher so that, when combined, the drive beam modulation translates into the required voltage modulation of the accelerating pulse. In this paper, the control over the RF pulse shape with the phase switches, that is crucial for the success of the developed compensation model, is studied. The results on the experimental verification of this control method are presented and a good agreement with the numerical predictions is demonstrated. Implications for the CLIC beam-loading compensation model are also discussed.
This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on prevalent applications in computational mechanics and design optimization. We leverage Matérn-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental influences, variating material properties, and geometric ambiguities. Our focus lies on delivering practical GRF realizations that accurately capture imperfections and variations and understanding how they impact the predictions of computational models as well as the shape and topology of optimized designs. Here we describe a numerical algorithm based on solving a generalized SPDE to sample GRFs on arbitrary meshed domains. The algorithm leverages established techniques and integrates seamlessly with the open-source finite element library MFEM and associated scientific computing workflows, like those found in industrial and national laboratory settings. Our solver scales efficiently for large-scale problems and supports various domain types, including surfaces and embedded manifolds. We showcase its versatility through biomechanics and topology optimization applications, emphasizing the potential to influence these domains. The flexibility and efficiency of SPDE-based GRF generation empowers us to run large-scale optimization problems on 2D and 3D domains, including finding optimized designs on embedded surfaces, and to generate design features and topologies beyond the reach of conventional techniques. Moreover, these capabilities allow us to model and quantify geometric uncertainties on reconstructed submanifolds, such as the interpolated surfaces of cerebral aneurysms provided by postprocessing CT scans. In addition to offering benefits in these specific domains, the proposed techniques transcend specific applications and generalize to arbitrary forward and backward problems in uncertainty quantification involving finite elements.
We describe our implementation of a global-parameter optimizer and Square Root Information Filter into the asteroid-modeling software shape. We compare the performance of our new optimizer with that of the existing sequential optimizer when operating on various forms of simulated data and actual asteroid radar data. In all cases, the new implementation performs substantially better than its predecessor: it converges faster, produces shape models that are more accurate, and solves for spin axis orientations more reliably. We discuss potential future changes to improve shape's fitting speed and accuracy.
The leaf economic traits such as leaf area, maximum carbon assimilation rate, and venation are all correlated and related to water availability. Furthermore, leaves are often broad and large in humid areas and narrower in arid/semiarid and hot and cold areas. We use optimization theory to explain these patterns. We have created a constrained optimization leaf model linking leaf shape to vein structure that is integrated into coupled transpiration and carbon assimilation processes. The model maximizes net leaf carbon gain (NPPleaf) over the loss of xylem water potential. Modeled relations between leaf traits are consistent with empirically observed patterns. As the results of the leaf shape-venation relation, our model further predicts that a broadleaf has overall higher NPPleaf compared to a narrowleaf. In addition, a broadleaf has a lower stomatal resistance compared to a narrowleaf under the same level of constraint. With the same leaf area, a broadleaf will have, on average, larger conduits and lower total leaf xylem resistance and thus be more efficient in water transportation but less resistant to cavitation. By linking venation structure to leaf shape and using water potential as the constraint, our model provides a physical explanation for the general pattern of the covariance of leaf traits through the safety-efficiency trade-off of leaf hydraulic design.