Specific Geometry Research Articles

Из опыта преподавания. XII. Зарождение кристалла и принцип равного ближайшего окружения

The article is devoted to the search for a concise answer to the question: how does the nucleus of a crystal arise? Although a simple and complete answer is impossible at the same time, an attempt has been made to clarify the problem in three aspects: according to which principle particles are combined into a nucleus, which nucleus have a chance to become crystal, and from which atomic configuration it can be recognized. To model the small polyhedral clusters, the principle of equal immediate environment is proposed. It is shown that such clusters with an odd number of atoms are impossible. Small polyhedral clusters should grow by attaching pairs of atoms. Previously, this was known for fullerenes because of their specific geometry. The topic is important because of the coverage of various quasi- and non-crystalline structures by crystallography and mineralogy.

A novel parameter for the prediction of rupture risk of cerebral aneurysms based on morphology.

Neurosurgeons often encounter dilemmas in the clinical management of cerebral aneurysms owing to an uncertainty of their rupture status and rupture risk. This study evaluates the influence of natural frequency of an aneurysm, as a novel morphological parameter to understand and analyze rupture status and risk prediction. In this work, we employ the natural frequency of 20 idealized and 50 patient specific aneurysms. The natural frequency of patient specific aneurysms is then compared against their rupture status. A strong correlation was observed between various morphological indicators and natural frequency for ideal and patient specific geometries. A statistical analysis with both Mann Whitney U test and T-test for rupture status against natural frequency has given a p-value less than 0.01 indicating a strong correlation between them. The correlation of morphological parameters with natural frequency from Pearson correlation coefficient and T-test suggests a holistic reflection of their effects on the natural frequency of an aneurysm. Thus, natural frequency could be a good indicator to discern the rupture potential of an aneurysm. The correlation between rupture status and natural frequency makes it a novel parameter that can differentiate between ruptured and unruptured patient specific aneurysms.

Vat polymerization 3D printing of composite acrylate photopolymer-based coated glass beads

Vat photopolymerization-based three-dimensional (3D) printing techniques have been used as an efficient method for complex and special geometries in various applications. Composites are also a group of polymer materials that are obtained by adding a reinforcing component such as filler, fibres with different origins. Therefore, the development of 3D printable composites is paramount due to their high precision and speed of production. Glass beads (GBs) have been favorites as economical reinforcement agents for their chemical stability, water resistance in acidic environments, dimensional stability, and eco-friendly properties. In this study, 3D printable composites based on coated glass beads (CGBs) have been prepared. First, the beads are coated with ultraviolet (UV) curable resins to improve the interface with the polymer matrix. Then, CGBs are mixed with 3D printing resin and formulated for digital light processing (DLP) printing. The coating process is checked by scanning electron microscopy (SEM), and the mechanical properties of the 3D-printed composite structures have been evaluated by bending and compression tests. Also, the fracture behavior of cured resin has been checked with SEM. Mechanical property investigations have shown the success of the 3D printing of the CGBs into a photopolymer resin (PR) composite with behavior modification and compatibility of the interface with the matrix in practice.

Compact Efficient and Frequency Tunable Relativistic Magnetron With Reducing Coaxial Section and Tilted Tuners

In this article, we present a compact efficient and frequency tunable relativistic magnetron (RM) with what we have named a reducing coaxial section (RCS) and with tilted tuners. The RCS is a conical-shaped part inserted in front of the output window. The design is adapted to the compact Marx generator of the Concept Léger Aéroporté d’Illuminateur RadioElectrique (CEA)-Gramat demonstrator—Commissariat à l’Energie Atomique et aux Energies Alternatives (CLAIRE)—and meets technical requirements such as input impedance (specifically during frequency shifting), mechanical dimensions, power handling capacity, and electromagnetic (EM) mode. Special care has been taken to lower the EM mode competition, which occurs with specific geometry, extraction waveguide with high dimensions, and/or frequency shifting. To mitigate this effect, the output waveguide diameter was decreased by means of the RCS design. Another challenge was to operate frequency shifting by adding tuners while maintaining high power handling. The premise is that cathode endcap spheres and tilted tuners theoretically reduce the electric field strength from 600 to 280 kV/cm. Particle-in-cell (PIC) simulation exhibits an output power (averaged over the pulse duration) that reaches 680 MW at 1.85 GHz. The corresponding maximum power efficiency is about 50% when the applied voltage is 380 kV, and the current intensity is about 3.8 kA. The frequency operating range is above 19% from 1.85 to 2.25 GHz.

Automatic Methods for Ultrasonic Scanning Paths Generation

This paper presents the last evolutions of a program developed in 2020 for the automated generation of optimal scanning paths for 0°LW ultrasonic inspections of complex parts. After summarizing the overall concepts of the path generation method, the paper presents two new algorithms (side following path and side/radius interpolating path) recently developed for specific geometries such as long and thin parts, or parts including nonparallel radii. Trajectories automatically generated by the software are then presented for a collection of various aerospace and industrial CFRP components. The results show that the software was able to generate optimal paths for all the tested geometries, using the part’s 3D surface CAD and the probe’s characteristics as only inputs. In particular, the addition of the new algorithms allows for the generation of satisfactory trajectories even for the parts that were previously problematic.

Evaluation of blast mitigation performance of cylindrical explosion containment vessels based on water containers

Using liquid materials with specific geometries can enhance the explosion-proof properties of confined structures. This approach is promising because bulk water has multiple blast mitigation mechanisms and adds almost no extra mass. In this study, a method of using water-filled containers to reduce both the peak and permanent deformation of cylindrical explosion containment vessels (CECVs) is investigated through experiments and numerical simulations. Several explosion experiments were performed to evaluate the blast mitigation of the empty containers and the bulk water with multiple thicknesses and heights in terms of dynamic deformation and afterburning suppression. The experimental results indicated that the bulk water with a larger thickness and a smaller height had better protective performance, which provided up to an 80.1% reduction in permanent deformation compared with no mitigant. Numerical models were established using LS-DYNA and verified by the deformation-time history curves measured in the experiments. The energy conversion process during the explosion was analyzed through the numerical simulations, and the results showed that water absorbed most of the detonation energy that should have been transferred to the steel shell, proving that momentum extraction of water was a significant mitigation mechanism for the internal blast in CECVs. Another significant mitigation mechanism was the shadowing effect of water, which changed the spatial distribution of the blast loading acting on the steel shell, especially for water containers with larger thickness and smaller height.

Seiberg-Witten Geometry of Four-Dimensional $\mathcal N=2$ Quiver Gauge Theories

Seiberg-Witten geometry of mass deformed $\mathcal N=2$ superconformal ADE quiver gauge theories in four dimensions is determined. We solve the limit shape equations derived from the gauge theory and identify the space $\mathfrak M$ of vacua of the theory with the moduli space of the genus zero holomorphic (quasi)maps to the moduli space ${\rm Bun}_{\mathbf G} (\mathcal E)$ of holomorphic $G^{\mathbb C}$-bundles on a (possibly degenerate) elliptic curve $\mathcal E$ defined in terms of the microscopic gauge couplings, for the corresponding simple ADE Lie group $G$. The integrable systems $\mathfrak P$ underlying the special geometry of $\mathfrak M$ are identified. The moduli spaces of framed $G$-instantons on ${\mathbb R}^{2} \times {\mathbb T}^{2}$, of $G$-monopoles with singularities on ${\mathbb R}^{2} \times {\mathbb S}^{1}$, the Hitchin systems on curves with punctures, as well as various spin chains play an important role in our story. We also comment on the higher-dimensional theories.

Electrically Detected Magnetic Resonance on a Chip (EDMRoC) for Analysis of Thin-Film Silicon Photovoltaics

Electrically detected magnetic resonance (EDMR) is a spectroscopic technique that provides information about the physical properties of materials through the detection of variations in conductivity induced by spin-dependent processes. EDMR has been widely applied to investigate thin-film semiconductor materials in which the presence of defects can induce the current limiting processes. Conventional EDMR measurements are performed on samples with a special geometry that allows the use of a typical electron paramagnetic resonance (EPR) resonator. For such measurements, it is of utmost importance that the geometry of the sample under assessment does not influence the results of the experiment. Here, we present a single-board EPR spectrometer using a chip-integrated, voltage-controlled oscillator (VCO) array as a planar microwave source, whose geometry optimally matches that of a standard EDMR sample, and which greatly facilitates electrical interfacing to the device under assessment. The probehead combined an ultrasensitive transimpedance amplifier (TIA) with a twelve-coil array, VCO-based, single-board EPR spectrometer to permit EDMR-on-a-Chip (EDMRoC) investigations. EDMRoC measurements were performed at room temperature on a thin-film hydrogenated amorphous silicon (a-Si:H) pin solar cell under dark and forward bias conditions, and the recombination current driven by the a-Si:H dangling bonds (db) was detected. These experiments serve as a proof of concept for a new generation of small and versatile spectrometers that allow in situ and operando EDMR experiments.

Reinforcement learning based UAV formation control in GPS-denied environment

Highly accurate positioning is a crucial prerequisite of multi Unmanned Aerial Vehicle close-formation flight for target tracking, formation keeping, and collision avoidance. Although the position of a UAV can be obtained through the Global Positioning System (GPS), it is difficult for a UAV to obtain highly accurate positioning data in a GPS-denied environment (e.g., a GPS jamming area, suburb, urban canyon, or mountain area); this may cause it to miss a tracking target or collide with another UAV. In particular, UAV close-formation control in GPS-denied environments faces difficulties owing to the low-accuracy position, close distance between vehicles, and nonholonomic dynamics of a UAV. In this paper, on the one hand, we develop an innovative UAV formation localization method to address the formation localization issues in GPS-denied environments; on the other hand, we design a novel reinforcement learning based algorithm to achieve the high-efficiency and robust performance of the controller. First, a novel Lidar-based localization algorithm is developed to measure the localization of each aircraft in the formation flight. In our solution, each UAV is equipped with Lidar as the position measurement sensor instead of the GPS module. The k-means algorithm is implemented to calculate the center point position of UAV. A novel formation position vector matching method is proposed to match center points with UAVs in the formation and estimate their position information. Second, a reinforcement learning based UAV formation control algorithm is developed by selecting the optimal policy to control UAV swarm to start and keep flying in a close formation of a specific geometry. Third, the innovative collision risk evaluation module is proposed to address the collision-free issues in the formation group. Finally, a novel experience replay method is also provided in this paper to enhance the learning efficiency. Experimental results validate the accuracy, effectiveness, and robustness of the proposed scheme.

Analysis of PlanetScope Dove Digital Surface Model Accuracy Using Geometrically Simulated Images

Many objectives in geoscience and engineering require Earth surface elevations at greater temporospatial resolution and coverage than are currently available. This may be achieved with stereo imagery from large constellations of “small sats”, such as PlanetScope Doves. Obtaining Digital Surface Models (DSMs) of sufficient quality from these images is challenging due to their lower resolution and weaker stereo geometry relative to stereo mode satellites such as WorldView. The quality can be improved by utilizing their much larger numbers of repeat images, but this requires effective stereopair selection. To determine the stereo geometries required for obtaining quality DSMs from PlanetScope Dove imagery, we apply a new methodology for generating simulated stereo images of varying geometries using adjusted orientation parameters obtained by a self-calibrating bundle adjustment and validated by comparing the resulting rigorous sensor and rational function models. The accuracies of simulated stereo and multi-pair DSMs are then assessed through comparison to a reference DSM, providing the relationship between specific imaging geometries and DSM quality. Our results provide a basis for automated stereo imagery selection to enable large-scale DSM production from PlanetScope Dove imagery. Our methodology can be applied to other sources of stereo imagery and designing future satellite missions. In the future, we will further develop multi-pair matching algorithms for generating DSMs with Dove Classic images to improve both accuracy and quality that are otherwise limited by the weak stereo geometry of single stereo pairs.

Overall protein structure quality assessment using hydrogen-bonding parameters.

Atomic model refinement at low resolution is often a challenging task. This ismostly because the experimental data are not sufficiently detailed to be described by atomic models. To make refinement practical and ensure that a refined atomic model is geometrically meaningful, additional information needs to be used such as restraints on Ramachandran plot distributions or residue side-chain rotameric states. However, using Ramachandran plots or rotameric states as refinement targets diminishes the validating power of these tools. Therefore, finding additional model-validation criteria that are not used or are difficult to use as refinement goals is desirable. Hydrogen bonds are one of the important noncovalent interactions that shape and maintain protein structure. These interactions can be characterized by a specific geometry of hydrogen donor and acceptor atoms. Systematic analysis of these geometries performed for quality-filtered high-resolution models of proteins from the Protein Data Bank shows that they have a distinct and a conserved distribution. Here, it is demonstrated how this information can be used for atomic model validation.

Understanding the piezoelectric response of ZnO nanotetrapods: Detailed numerical calculations

The complex tetrapod shape of zinc oxide nanostructure, which is constructed from four one-dimensional arms interconnected together via a central core, is a special 3D geometry with multifunctional applications in advanced technologies. The ZnO hexagonal wurtzite crystal lattice with a non-centrosymmetric structure introduces interesting piezoelectric property in nanorods in the bent state, which has been well reported and utilized in piezo- and tribo-electric nanogenerator applications. Considering the broad technological relevance of tetrapods, it is important to understand the piezoelectric response of zinc oxide tetrapods under different conditions. In this study, we explicate the fundamental mechanical and electrical properties of ZnO nanotetrapods (ZnO NTs) through a detailed finite element method analysis. On this basis, the effects of shape factors (including length, height, and aspect ratio) as well as connection strength and packing density on the deformation and piezoelectric potential of ZnO NTs are examined, offering guidance for the fabrication of ZnO NTs. This theoretical model and numerical simulation provide an avenue for further piezoelectric and piezotronic research of ZnO NTs.

Tsallis Entropy applied to microfluidic channels analysis

This work investigated the possibility to describe the fluid flow in a microchannel from a thermodynamic point of view, exploring the possibility to evaluate the presence of obstacles (or, more in general, geometry imperfection) and their influence on the fluid. Tsallis entropy concept was employed. This form of entropy was introduced in 1988 by Costantino Tsallis as a basis for generalizing the standard statistical mechanics and as a generalization of the standard Boltzmann-Gibbs entropy. Inspired by nature, where storing information is an intrinsic ability of natural systems, here we investigate the capability of interacting systems to transport/store the information generated/exchanged in the interaction process in the form of energy or matter, preserving it over time. In detail, here we test the possibility to consider a fluid as a carrier of information, speculating about how to use such information. The final goal is to demonstrate that information theory can be used to illuminate physical observations, even in those cases where the equations describing the phenomenon under investigation are intractable, are affected by a budget of uncertainty that makes their solution not affordable or may not even be known. In this exploratory work, an information theory-based approach is applied to microfluidic data. In detail, the classical study of the fluid flow in a microchannel with an obstacle of a specific geometry is faced by integrating fluid mechanics theory with Tsallis entropy. Technically, computational fluid dynamics simulations at Reynolds’ numbers (Re) equal to 1 were carried out in fluidic channels presenting a rectangular obstacle and on the simulated flow fields.

An approach to study recruitment/derecruitment dynamics in a patient-specific computational model of an injured human lung.

We present a new approach for physics-based computational modeling of diseased human lungs. Our main object is the development of a model that takes the novel step of incorporating the dynamics of airway recruitment/derecruitment into an anatomically accurate, spatially resolved model of respiratory system mechanics, and the relation of these dynamics to airway dimensions and the biophysical properties of the lining fluid. The importance of our approach is that it potentially allows for more accurate predictions of where mechanical stress foci arise in the lungs, since it is at these locations that injury is thought to arise and propagate from. We match the model to data from a patient with acute respiratory distress syndrome (ARDS) to demonstrate the potential of the model for revealing the underlying derangements in ARDS in a patient-specific manner. To achieve this, the specific geometry of the lung and its heterogeneous pattern of injury are extracted from medical CT images. The mechanical behavior of the model is tailored to the patient's respiratory mechanics using measured ventilation data. In retrospective simulations of various clinically performed, pressure-driven ventilation profiles, the model adequately reproduces clinical quantities measured in the patient such as tidal volume and change in pleural pressure. The model also exhibits physiologically reasonable lung recruitment dynamics and has the spatial resolution to allow the study of local mechanical quantities such as alveolar strains. This modeling approach advances our ability to perform patient-specific studies in silico, opening the way to personalized therapies that will optimize patient outcomes.

Microvibration simulation of reaction wheel ball bearings

Microvibrations on board satellites are a well-known problem affecting their pointing accuracy by inducing oscillations to the line-of-sight. Fast rotating devices, such as reaction wheel assemblies (RWAs) are a major cause of these onboard mechanical disturbances. Imbalances in the flywheel, as well as imperfections in the ball-bearing components yield low-amplitude vibrations that are transmitted to the satellite structure, adversely affecting the performance of sensitive onboard instruments. This research focuses on the RWA’s ball bearing microvibration frequency and amplitude characterization. This is achieved by introducing specific geometry imperfections on the ball bearing rotating elements. In addition, variables such as the ball bearing preload, the number of balls and their dimensions are altered to understand how the bearing microvibration changes in order to minimize it. Finally, available physical microvibration test data is used to compare and cross-correlate the microvibration waterfall plots obtained from the transient FEA of the parametrized bearing models introduced herein. This work provides a better understanding of the relation between the main structural ball bearing parameters and the microvibration disturbances emitted by the RWA to minimize its mechanical noise.

An Overview of Active Control Techniques for Vortex Rope Mitigation in Hydraulic Turbines

This review addresses the current state of research into active control and suppression of vortex rope in hydroturbines under off-design operating conditions. Only active control methods that can be “switched on” when required under off-design operating conditions are considered in this work. The review focuses on air addition into the flow, as well as various auxiliary fluid jets. It includes all the best practices for vortex rope suppression in numerical and experimental studies. It can be inferred from the review that a modern flow control system should be comprehensive, designed for a specific hydroturbine geometry, and obtain feedback from the flow. Injecting ~2% of air from the impeller fairing cone appears optimal for suppressing pressure pulsations without significant efficiency loss. The cost of air injection is rarely estimated, but the use of an automatic venting system can minimize overheads and potentially improve efficiencies at low gas contents. Fluid jets ranging from 3% to 12% of the main flow rate can efficiently suppress pressure pulsations, but their high energy requirements limit their use. Azimuthal perturbation of the flow appears promising as it does not require significant energy loss, but practical implementation remains challenging as one needs to accurately know the system dynamics and be capable of real-time manipulation of the flow.

Failures of Minimum Variance Analysis in Diagnosing Planar Structures in Space

Minimum variance analysis of the magnetic field (MVAB), among various techniques of planar structure analysis, is most widely used for its numerical simplicity and loose requirements for data. Through a large number of studies based on MVAB, a global picture of the solar wind intermittency has been established. However, the huge discrepancy between the results from MVAB and other techniques like timing/triangulation implies that the uncertainty of MVAB is a crucial issue that is not fully understood. Utilizing Cluster data, we establish a data set comprised of 6752 discontinuities, whose orientations are precisely determined by timing, as a benchmark for testing MVAB. We find that the scatter of the MVAB normals around the timing normal can be reduced by elevating the threshold for the eigenvalue ratio λ 2/λ 3 and narrowing the data window to which MVAB is applied. The misidentification of discontinuities with < 0.4, Δ∣ B ∣/∣ B ∣ < 0.2 as rotational discontinuities (RDs, identified by > 0.4, Δ∣ B ∣/∣ B ∣ < 0.2) is proved to be a major and inherent defect of MVAB, which can occur even when λ 2/λ 3 is large. Such a misidentification process is revealed to be related to a special discontinuity geometry. It also explains the false RD predominance reported by previous studies based on MVAB. Finally, we provide advice for the application of MVAB and discuss the possibility of obtaining the real statistical properties of interplanetary discontinuities by using MVAB.

Grasses exploit geometry to achieve improved guard cell dynamics.

Stomata are controllable micropores formed between two adjacent guard cells (GCs) that regulate gas flow across the plant surface.1 Grasses, among the most successful organisms on the planet and the main food crops for humanity, have GCs flanked by specialized lateral subsidiary cells (SCs).2,3,4 SCs improve performance by acting as a local pool of ions and metabolites to drive changes in turgor pressure within the GCs that open/close the stomatal pore.4,5,6,7,8 The 4-celled complex also involves distinctive changes in geometry, having dumbbell-shaped GCs compared with typical kidney-shaped stomata.2,4,9 However, the degree to which this distinctive geometry contributes to improved stomatal performance, and the underlying mechanism, remains unclear. To address this question, we created a finite element method (FEM) model of a grass stomatal complex that successfully captures experimentally observed pore opening/closure. Exploration of the model, including in silico and experimental mutant analyses, supports the importance of a reciprocal pressure system between GCs and SCs for effective stomatal function, with SCs functioning as springs to restrain lateral GC movement. Our results show that SCs are not essential but lead to a more responsive system. In addition, we show that GC wall anisotropy is not required for grass stomatal function (in contrast to kidney-shaped GCs10) but that a relatively thick GC rod region is needed to enhance pore opening. Our results demonstrate that a specific cellular geometry and associated mechanical properties are required for the effective functioning of grass stomata.

Target-Conformal Optimization-Based Actuator Placement for Ultrasound-Mediated Hyperthermia in Cancer Treatments

In hyperthermia for cancer treatments, tumors are heated to improve the outcome of radio-and chemotherapies. Using extracorporeal high-intensity focused ultrasound (HIFU) transducers, the heating can be applied noninvasively, accurately, and with high acoustic power. The heating location can be changed by electronic beam steering, within the transducer’s small local heating range, and by mechanically repositioning the transducer, which effectively shifts the local range to enable the treatment of larger tumors. An important problem is the selection of the sonication points, i.e., the discrete locations reachable by electronic beam steering, and the admissible mechanical transducer positions, which must be performed prior to treatment, and can be seen as an actuator selection problem. Clearly, the selected sonication points and transducer positions have a major impact on the achievable tumor temperatures, and their number is directly related to the controller’s complexity and, thereby, real-time feasibility. To address this challenging problem, this brief presents a target-conformal optimization-based actuator placement procedure, designed to assist the clinician in enabling maximum treatment quality using only a limited number of sonication points and transducer positions. The method is computationally tractable, and takes into account the specific tumor geometry and tissue properties.

Anatomical predictors of difficult left internal carotid artery navigation in transradial access for neurointervention.

Transradial access (TRA) has received considerable attention in the field of neurointervention owing to its advantages over transfemoral access. However, the difficulty of left internal carotid artery (ICA) navigation under certain anatomical conditions of the aortic arch and its branches is a limitation of right TRA. In this study the authors aimed to investigate the anatomical predictors that impede navigation of the left ICA in right TRA. From January to October 2020, 640 patients underwent transradial angiography at a single institute. Among them, 263 consecutive patients who were evaluated by contrast-enhanced MRA before transradial angiography were included in the study and assigned to success or failure groups according to whether left ICA navigation was possible or not. Several anatomical predictors were investigated to evaluate the correlation of the success of left ICA navigation in right TRA. A higher grade of the aortic arch type (type I vs type III: OR 6.323, p = 0.0171), higher height of the right subclavian artery (OR 1.071, p = 0.0068), narrower turnoff angle of the left common carotid artery (CCA) (OR 0.953, p = 0.0017), wider distance between the innominate artery and the left CCA (OR 1.784, p < 0.0001), steeper angulation of the right subclavian artery (tortuous vs kinking: OR 6.323, p = 0.0066), and steeper angulation of the left CCA (normal vs tortuous: OR 7.453, p = 0.0087; normal vs kinking: OR 51.65, p < 0.0001) were significantly associated with successful navigation of the left ICA. The cutoff value of the height of the right subclavian artery, distance between the innominate artery and the left CCA, turnoff angle of the left CCA, and diameter of the left CCA were 54.83 mm, 4.25 mm, 17°, and 6.05 mm, respectively. Successful left ICA navigation in right TRA was related to the specific vascular geometry of the aortic arch and its branches. Preprocedural evaluation of the anatomical predictors identified in this study may enhance the success rate of left ICA navigation in right TRA.