Target Geometry Research Articles

Feature Extraction and Classification of Simulated Monostatic Acoustic Echoes from Spherical Targets of Various Materials Using Convolutional Neural Networks

Active sonar target classification remains an ongoing area of research due to the unique challenges associated with the problem (unknown target parameters, dynamic oceanic environment, different scattering mechanisms, etc.). Many feature extraction and classification techniques have been proposed, but there remains a need to relate and explain the classifier results in the physical domain. This work examines convolutional neural networks trained on simulated data with a known ground truth projected onto two time-frequency representations (spectrograms and scalograms). The classifiers were trained to discriminate the target material type, geometry, and internal fluid filling, while the hyperparameters were tuned to the classification task using Bayesian optimization. The trained networks were examined using an explainable artificial intelligence technique, gradient-weighted class activation mapping, to uncover the informative features used in discrimination. This analysis resulted in visual representations that allowed the CNN choices to be related to the physical domain. It was found that the scalogram representation provided a negligible classification accuracy increase compared with the spectrograms. Networks trained to discriminate between target geometries resulted in the highest accuracy, and the networks trained to discriminate the internal fluid of the target resulted in the lowest accuracy.

Investigating 99Mo output changes in high-sustainability uranium targets by modifying target volume and geometry

Introduction: The most common current uranium target type for 99Mo production uses plate geometry. This paper investigates the effects of geometry on 99Mo output and target sustainability.Methods: MCNP6.2 was used to model rectangular, spherical, and cylindrical targets ranging from 12.03 cm3 to 120.34 cm3 to determine the target geometry and volume effects on 99Mo output, sustainability, proliferation concerns, and heating. 4-7 days irradiation was used with a consistent target density of 2 g/cm3 UO2 for all target types.Results and Discussion: The cylindrical target was found to have the best performance due to having the second highest sustainability, the highest 99Mo output and produce the lowest amounts of 239Pu compared to the other target geometries. The heating comparison showed that there were negligible heating concerns for all target volumes and geometries.

Comparison of manifold representations of sonar data

There are many challenges in active sonar target recognition due to the dynamic nature of the environment, unknown target geometries, and various clutter present within the ocean. These factors combine and entangle the target features within the received response. This research assumes the informative and discriminatory acoustic target features lie on a low dimensional manifold and can be extracted using statistical and machine learning techniques. Linear techniques, such as principal component analysis and linear discriminant analysis, are useful for dimension reduction but will typically not accurately capture the underlying non-linearity within a dataset. Non-linear manifold learning techniques, such as T-distributed stochastic neighbor embedding and uniform manifold approximation and projection, are relatively recent techniques that create low-dimensional embeddings in an unsupervised fashion and can capture the non-linearity. Previously, persistent braid features have been reported in real sonar data1. Our objective here is to do comparison between these different manifold representations for both simulated data with a known ground truth and experimental active sonar data. [1] A. Sen Gupta, B. Kubicek, A. Christensen, and I. Kirsteins, “Geometric feature representation in active sonar signal processing,” OCEANS 2022—Chennai, 2022, pp. 1–5. [Work supported by NDSEG 2021 and ONR Grant No. N00014-21-1-2420].

Dissolution of Molybdenum in Hydrogen Peroxide: A Thermodynamic, Kinetic and Microscopic Study of a Green Process for 99mTc Production.

99mTc-based radiopharmaceuticals are the most commonly used medical radioactive tracers in nuclear medicine for diagnostic imaging. Due to the expected global shortage of 99Mo, the parent radionuclide from which 99mTc is produced, new production methods should be developed. The SORGENTINA-RF (SRF) project aims at developing a prototypical medium-intensity D-T 14-MeV fusion neutron source specifically designed for production of medical radioisotopes with a focus on 99Mo. The scope of this work was to develop an efficient, cost-effective and green procedure for dissolution of solid molybdenum in hydrogen peroxide solutions compatible for 99mTc production via the SRF neutron source. The dissolution process was extensively studied for two different target geometries: pellets and powder. The first showed better characteristics and properties for the dissolution procedure, and up to 100 g of pellets were successfully dissolved in 250-280 min. The dissolution mechanism on the pellets was investigated by means of scanning electron microscopy and energy-dispersive X-ray spectroscopy. After the procedure, sodium molybdate crystals were characterized via X-ray diffraction, Raman and infrared spectroscopy and the high purity of the compound was established by means of inductively coupled plasma mass spectroscopy. The study confirmed the feasibility of the procedure for production of 99mTc in SRF as it is very cost-effective, with minimal consumption of peroxide and controlled low temperature.

Simulation of DNA damage using Geant4‐DNA: an overview of the “molecularDNA” example application

AbstractPurposeThe scientific community shows great interest in the study of DNA damage induction, DNA damage repair, and the biological effects on cells and cellular systems after exposure to ionizing radiation. Several in silico methods have been proposed so far to study these mechanisms using Monte Carlo simulations. This study outlines a Geant4‐DNA example application, named “molecularDNA”, publicly released in the 11.1 version of Geant4 (December 2022).MethodsIt was developed for novice Geant4 users and requires only a basic understanding of scripting languages to get started. The example includes two different DNA‐scale geometries of biological targets, namely “cylinders” and “human cell”. This public version is based on a previous prototype and includes new features, such as: the adoption of a new approach for the modeling of the chemical stage, the use of the standard DNA damage format to describe radiation‐induced DNA damage, and upgraded computational tools to estimate DNA damage response.ResultsSimulation data in terms of single‐strand break and double‐strand break yields were produced using each of the available geometries. The results were compared with the literature, to validate the example, producing less than 5% difference in all cases. Conclusion: “molecularDNA” is a prototype tool that can be applied in a wide variety of radiobiology studies, providing the scientific community with an open‐access base for DNA damage quantification calculations. New DNA and cell geometries for the “molecularDNA” example will be included in future versions of Geant4‐DNA.

Novel SOLPS-ITER simulations of X-point target and snowflake divertors

The design and understanding of alternative divertor configurations may be crucial for achieving acceptable steady-state heat and particle material loads for magnetic confinement fusion reactors. Multiple X-point alternative divertor geometries such as snowflakes and X-point targets have great potential in reducing power loads, but have not yet been simulated widely in codes with kinetic neutrals. This paper discusses recent changes made to the SOLPS-ITER code to allow for the simulation of X-point target and low-field side snowflake divertor geometries. Snowflake simulations using this method are presented, in addition to the first SOLPS-ITER simulation of the X-point target. Analysis of these results show reasonable consistency with the simple modelling and theoretical predictions, supporting the validity of the methodology implemented.

Enhanced electron acceleration by high-intensity lasers in extended (confined) preplasma in cone targets

We report on experimental results from a high-intensity laser interaction with cone targets that increase the number (×3) and temperature (×3) of the measured hot electrons over a traditional planar target. This increase is caused by a substantial increase in the plasma density within the cone target geometry, which was induced by 17 ± 9 mJ prepulse that arrived 1.5 ns prior to the main high intensity (>1019 W/cm2). Three-dimensional hydrodynamic simulations are conducted using hydra which show that the cone targets create substantially longer and denser plasma than planar targets due to the geometric confinement of the expanding plasma. The density within the cone is a several hundred-micron plasma “shelf” with a density of approximately 1020 ne/cc. The hydra simulated plasma densities are used as the initial conditions for two-dimensional particle-in-cell simulations using EPOCH. These simulations show that the main acceleration mechanism is direct-laser-acceleration, with close agreement between experimentally measured and simulated electron temperatures. Further analysis is conducted to investigate the acceleration of the electrons within the long plasma generated within a compound parabolic concentrator by the prepulse.

Stokes–Mueller polarization-based analysis of model SARS-CoV-2 virions

Understanding the virology of the coronavirus at the structural level has gained utmost importance to overcome the constant and long-term health complications induced by them. In this work, the light scattering properties of SARS-CoV-2 of size 140 nm were simulated by using discrete dipole approximation (DDA) for two incident wavelengths 200 nm and 350 nm, respectively. Three different 3-dimensional (3D) models of SARS-CoV-2 corresponding to 15, 20, and 40 numbers of spike proteins on the viral capsid surface were constructed as target geometries for the DDA calculations. These models were assessed by employing Stokes–Mueller polarimetry to obtain individual polarization properties such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP). Irrespective of its spike numbers, all the coronavirus models were found to display higher DOP and DOCP values and negligibly small DOLP values for circularly polarized incident light, indicating the presence of chiral structures. On the other hand, the lack of understanding about the dependence of the Mueller matrix on its microstructural properties was overcome by transforming 16 Mueller elements into sub-matrices with specific structural and physical properties using Lu–Chipman-based Mueller matrix polar decomposition method. The obtained properties such as retardance, diattenuation, and depolarization were used for investigating the composition and microstructural information. The approach presented in this work has the potential to understand the virology of the coronavirus at the structural level and, therefore, will be beneficial in developing effective detection strategies by exploiting their characteristic electromagnetic scattering signatures.

Correlation between plasma characteristics, morphology, and microstructure of sputtered CuAl alloy films with varied target geometry

The effect of target geometry on coating microstructure and morphology is correlated to changes in deposition conditions, plasma characteristics, and film growth during planar and hollow cathode sputtering. The sputtering plasma properties for the two target geometries were characterized via Langmuir probe analysis as a function of power density and Ar pressure to determine the evolution of ion density for each configuration. Films were then synthesized at the low (0.4 W cm−2) and high (1.2 W cm−2) power densities and characterized using x-ray diffraction, scanning electron microscopy, and electron backscatter diffraction to link changes in texturing, morphology, and microstructure with variations in ion density and sputtering deposition conditions caused by target geometry. It was observed that varying target geometry led to an over threefold increase in deposition rate, homologous temperature, and ion density, which altered the morphology and texture of the film without significant changes to the grain size.

Future facilities at PSI, the High-Intensity Muon Beams (HIMB) project

Currently, PSI delivers the most intense continuous muon beam in the world with up to a few 108 µ+/s. The High-Intensity Muon Beams (HIMB) project is developing a new target station and muon beamlines able to deliver 1010 µ+/s, with a huge impact for low-energy, high-precision muon experiments. While the next generation of proton drivers with beam powers in excess of the currently achieved 1.4 MW still require significant research and development, the focus of HIMB is to improve the surface muon yield with a new target geometry and to increase capture and transmission with a solenoid-based beamline in order to reach a total efficiency of approximately 10 %. We present the current status of the HIMB project.

The PSI meson target facility and its upgrade IMPACT-HIMB

The high intensity proton accelerator complex (HIPA) at the Paul Scherrer Institute (PSI) delivers a 590 MeV CW proton beam with currents up to 2.4 mA (1.4 MW). Besides two spallation targets for thermal/cold neutrons (SINQ) and for ultracold neutrons (UCN), the beam feeds two meson production targets Target M and Target E. The targets consist of graphite wheels of effective thickness 5 mm (M) and 40/60 mm (E). The target stations M and E are of quite different design; however, both of them rotate at 1 Hz to dissipate the heat (20 kW/mA for the 40 mm target E) efficiently. Recent progress was made by a new type of bearings and a new target geometry able to increase the rate of surface muons by up to 50 %. This is also foreseen for the upgrade of the target station M within the High Intensity Muon Beam (HIMB) initiative aiming to increase the surface muons available for experiment by two orders of magnitude. HIMB is part of IMPACT (Isotope and Muon Production with Advanced Cyclotron and Target Technology), an application for the Swiss Roadmap of Research Infrastructure.

Guided electromagnetic discharge pulses driven by short intense laser pulses: Characterization and modeling

Strong electromagnetic pulses (EMPs) are generated from intense laser interactions with solid-density targets and can be guided by the target geometry, specifically through conductive connections to the ground. We present an experimental characterization by time- and spatial-resolved proton deflectometry of guided electromagnetic discharge pulses along wires including a coil, driven by 0.5 ps, 50 J, 1019 W/cm2 laser pulses. Proton-deflectometry allows us to time-resolve first the EMP due to the laser-driven target charging and then the return EMP from the ground through the conductive target stalk. Both EMPs have a typical duration of tens of ps and correspond to currents in the kA-range with electric-field amplitudes of multiple GV/m. The sub-mm coil in the target rod creates lensing effects on probing protons due to both magnetic- and electric-field contributions. This way, protons of the 10 MeV-energy range are focused over cm-scale distances. Experimental results are supported by analytical modeling and high-resolution numerical particle-in-cell simulations, unraveling the likely presence of a surface plasma, in which parameters define the discharge pulse dispersion in the non-linear propagation regime.

Analytical method for elastic recovery prediction of air bending sheet

The estimation of the elastic recovery is of great importance during the planning of plastic deformation processes, because this estimation could reduce the number of required steps to reach the target geometry. The sheet bending process is one of the most widely used industrial processes, and that is why this paper seeks to provide an analytical model based on an elastic behavior with potential hardening of the material that could be combined with the geometric information of the process to estimate the degree of recovery of the components. The potential hardening model was selected due to its simplicity and good fit with the experimental data observed in steel sheets in this application. The effectiveness of the model was compared with the results obtained by several authors. The effectiveness of the model is significantly influenced by the parameters of the bending process and the method used to estimate the radius of curvature.

Fully automated tool path planning for turbine blade repair

The recontouring process of aircraft engine parts like turbine blades is a manual or in best-case semi-automated process due to high individuality of the workpiece. This leads to in-process scrap because of low process stability and high process times. An automation of process planning reduces both. This paper introduces a method for a fully automated and individual tool path planning using 3D-scan data. Geometric parameters of the degenerated blade were considered to find best-suitable target geometry in a robust way. For turbine blade repair, the process stability is increased while meeting the dimensional tolerances required for the international aviation certifications.

Multibeam laser–plasma interaction at the Gekko XII laser facility in conditions relevant for direct-drive inertial confinement fusion

Abstract Laser–plasma interaction and hot electrons have been characterized in detail in laser irradiation conditions relevant for direct-drive inertial confinement fusion. The experiment was carried out at the Gekko XII laser facility in multibeam planar target geometry at an intensity of approximately $3\times {10}^{15}$ W/cm2. Experimental data suggest that high-energy electrons, with temperatures of 20–50 keV and conversion efficiencies of $\eta <1\%$ , were mainly produced by the damping of electron plasma waves driven by two-plasmon decay (TPD). Stimulated Raman scattering (SRS) is observed in a near-threshold growth regime, producing a reflectivity of approximately $0.01\%$ , and is well described by an analytical model accounting for the convective growth in independent speckles. The experiment reveals that both TPD and SRS are collectively driven by multiple beams, resulting in a more vigorous growth than that driven by single-beam laser intensity.

Robot-guided Pre-machining for Repair by Cold Spray

Cold spraying is currently developing as a high potential technique for the repair of metallic components, particularly for the deposition of heat-and oxidation-sensitive materials. However, for the appropriate application, it is essential to prepare the component surface suitably to ensure optimum prerequisites for the subsequent material deposition by cold spray. Thus, this work proposes a concept for robot-guided pre-machining for repair by cold spray that includes removal of the damaged volume while considering the requirements for subsequent material deposition. In this concept, digital component and damage data define the dimensions and boundary conditions for material removal. This involves designing a parametric pre-machining target geometry for the damaged component by computer-aided design software that can handle variable surface types. The pre-machining target geometry is adapted to the damage characteristics by considering length, width, depth and orientation. To produce the pre-machining target geometry by machining tools, the adjusted component is exported to computer-aided manufacturing software. The applicability of this concept has been successfully demonstrated on digital use cases with exemplary components and damages as well as by practical application with a milling robot in a laboratory environment. The results demonstrate the capability of this concept for preparing damaged components and promise a high potential to ensure the required prerequisites for high-quality component repair by cold spray.

Modelling cyclotron-based production of radioisotopes via TOPAS

Objective. In this work, the irradiation of natural titanium foils in the beam-stop of a compact medical cyclotron, an IBA CYCLONE 18/9, is simulated to assess the efficacy of using a beam-stop as a target holder, and using two different target geometries, in the production of vanadium-48, a positron-emitting radioisotope with potential utility as a cancer imaging agent in positron emission tomography. Approach. TOPAS, the TOol for PArticle Simulation, a Geant4-based Monte Carlo program, was used to model the cyclotron beam parameters, choose an appropriate physics list, and simulate the irradiation of targets made from foils of 12 or 12.5 μm thickness. These simulation yields were compared to theoretical yields calculated using cross section data from the literature, as well as assayed yields from experimental irradiations. Main results. We found that most physics lists in TOPAS overestimate the cross section in the desired energy range (16–20 MeV) by at least 136%, with the exception of those using the Bertini Cascade Model. Compared to assayed yields, TOPAS provided a minimum of 0.4% error for cup-shaped targets and at least a 12% overestimation for sphere-shaped targets. Significance. These simulations provide a tool to help explain irregularities in radioisotope production yield and motivate modifications to increase target yield.

Simultaneous parametric estimation of shape and impedance of a scattering surface using a multi-frequency fast indirect boundary element method

Characterization of rough surface properties, such as surface shape or surface impedance, is relevant in many applications. Previous work has been done for characterizing these two aspects separately. This paper proposes a framework for characterizing rough surfaces of finite size in terms of their roughness shape and surface impedance in a single setup. The surface properties are estimated indirectly using a superposition of spatial sinusoidal components for the surface shape and a porous material model for the surface impedance. A fast multipole indirect boundary element method is employed to model the acoustic scattering problem. With the modeling flexibility from the indirect formulation, the target geometry can be simplified as a thin shell representation, which significantly improves computational efficiency. A subtraction method is proposed to mitigate the modeling error of this representation and enable the use of low driving frequencies (e.g. acoustic wavelength is comparable to or larger than the roughness scale) in the characterization. Considering the modeling accuracy of surface shape representation, a discretization criterion concerning both acoustic and spatial aspects is defined. The inverse problem is solved by means of a general-purpose optimizer, minimizing the difference between the simulated and reference acoustic field at multiple driving frequencies. Various numerical examples show that by using reference data with sufficient quality, the proposed framework can retrieve the surface shape and impedance separately, and also simultaneously.

Experimental Study on the Target–Receiver Formation Problem with the Exploitation of Coherent and Non-Coherent Bearing Information

Localization of emitting sources is a fundamental task in sonar applications. One of the most important factors that affect the localization performance is the sensor–target geometry. The sensor formation problem is usually addressed in related work assuming that the target is static and the location is known to a certain degree, but this is not the case for many underwater surveillance problems. In this paper, we deal with the target–receiver formation problem from a different perspective, and propose to investigate the effect of target–receiver geometry on localization performance by exploiting the spatial spectrum of the direct position determination (DPD) methods. For a given multi-array system, the transformation of geometrical patterns can be explicitly demonstrated as the target moves along the track. Meaningful characteristics of the DPD methods are obtained from the experimental results, where coherent and non-coherent bearing information is used and compared. The feasibility of the DPD approaches in the ocean environments is also investigated by comparing with a matched filter processing (MFP)-based multi-array processor in order to validate the credibility of the results in this paper.

Monte Carlo N-Particle forward modeling for density reconstruction of double shell capsule radiographs.

In the Double Shell Inertial Confinement Fusion concept, characterizing the shape asymmetry of imploding metal shells is vital for understanding energy-efficient compression and radiative losses of the thermonuclear fuel. The Monte Carlo N-Particle MCNP® code forward models radiography of Double Shell capsule implosions using the Advanced Radiographic Capability at the National Ignition Facility. A procedure is developed for using MCNP to reconstruct density profiles from the radiograph image intensity. For a given Double Shell imploding target geometry, MCNP radiographs predict image contrast, which can help guide experimental design. In future work, the calculated MCNP synthetic radiographs will be compared with experimental radiographs to determine the radial and azimuthal density profiles of the Double Shell capsules.