On the applicability of numerical tools for simulating wave-ports close to the cutoff frequency

This paper focuses on a common drawback in electromagnetic numerical computer aided design computer aided design (CAD) tools: high frequency structure simulator (HFSS), computer simulation technology (CST) and FEKO, where the excitation by using a wave-port below and close to the cutoff frequency has unreliable values for the reflection coefficient. An example for such problem is presented in the design of a dual horn antenna fed by two different waveguide sections. To overcome this numerical error in the results of these CAD tools, a tapered waveguide section is used in the simulation as an excitation mechanism to the feeding waveguide. The cross section of the input port at this tapered waveguide section is designed to have a cutoff frequency smaller than the lowest frequency under investigation for the original problem. Then, by extracting the effect of the tapered section from the obtained reflection coefficient, it would be possible to obtain the reflection coefficient of the original problem.

Approaches for FPGA Design Assurance

Field-Programmable Gate Arrays (FPGAs) are widely used for custom hardware implementations, including in many security-sensitive industries, such as defense, communications, transportation, medical, and more. Compiling source hardware descriptions to FPGA bitstreams requires the use of complex computer-aided design (CAD) tools. These tools are typically proprietary and closed-source, and it is not possible to easily determine that the produced bitstream is equivalent to the source design. In this work, we present various FPGA design flows that leverage pre-synthesizing or pre-implementing parts of the design, combined with open-source synthesis tools, bitstream-to-netlist tools, and commercial equivalence-checking tools, to verify that a produced hardware design is equivalent to the designer’s source design. We evaluate these different design flows on several benchmark circuits and demonstrate that they are effective at detecting malicious modifications made to the design during compilation. We compare our proposed design flows with baseline commercial design flows and measure the overheads to area and runtime.

CFD-CAA Method for Prediction of Pseudosound and Emitted Noise in Quadcopter Propeller

Subsonic flow air blade machines like UAV propellers generate intensive noise thus the prediction of acoustic impact, optimization of these machines in order to reduce the level of emitted noise is an urgent engineering task. Currently, the development of calculation methods for determining the amplitudes of pressure pulsations and noise characteristics by CFD-CAA methods is a necessary requirement for the development of computer-aided design methods for blade machines, where the determining factors are the accuracy and speed of calculations. The main objective is to provide industrial computer-aided design systems with a highly efficient domestic software to create optimal designs of UAV blade machines that provide a given level of pressure pulsations in the flow part and radiated noise. It comprises: 1) creation of a method for the numerical simulation of sound generation using the correct decomposition of the initial equations of hydrodynamics of a compressible medium and the selection of the source of sound waves in a three-dimensional definition, taking into account the rotation of blades and their interaction with the stator part of the UAV; 2) decomposition of the boundary conditions accounting pseudo-sound disturbances and the complex acoustic impedance at the boundaries of the computational domain 3) development of an effective SLAE solver for solving the acoustic-vortex equation in complex arithmetic (taking into account the boundary conditions in the form of complex acoustic impedance); 4) testing of a new method at all stages of development using experimental data on the generation of pressure pulsations and aerodynamic noise, including a propeller noise measurements.

1.3 kV Vertical GaN-Based Trench MOSFETs on 4-Inch Free Standing GaN Wafer

In this work, a vertical gallium nitride (GaN)-based trench MOSFET on 4-inch free-standing GaN substrate is presented with threshold voltage of 3.15 V, specific on-resistance of 1.93 mΩ·cm2, breakdown voltage of 1306 V, and figure of merit of 0.88 GW/cm2. High-quality and stable MOS interface is obtained through two-step process, including simple acid cleaning and a following (NH4)2S passivation. Based on the calibration with experiment, the simulation results of physical model are consistent well with the experiment data in transfer, output, and breakdown characteristic curves, which demonstrate the validity of the simulation data obtained by Silvaco technology computer aided design (Silvaco TCAD). The mechanisms of on-state and breakdown are thoroughly studied using Silvaco TCAD physical model. The device parameters, including n−-GaN drift layer, p-GaN channel layer and gate dielectric layer, are systematically designed for optimization. This comprehensive analysis and optimization on the vertical GaN-based trench MOSFETs provide significant guide for vertical GaN-based high power applications.

Computer-aided design of reversible hybridization chain reaction (CAD-HCR) enables multiplexed single-cell spatial proteomics imaging

Cyclic imaging of multiple proteins in a single cell is realized through CAD-HCR.

ImageMech: From Image to Particle Spring Network for Mechanical Characterization

The emerging demand for advanced structural and biological materials calls for novel modeling tools that can rapidly yield high-fidelity estimation on materials properties in design cycles. Lattice spring model , a coarse-grained particle spring network, has gained attention in recent years for predicting the mechanical properties and giving insights into the fracture mechanism with high reproducibility and generalizability. However, to simulate the materials in sufficient detail for guaranteed numerical stability and convergence, most of the time a large number of particles are needed, greatly diminishing the potential for high-throughput computation and therewith data generation for machine learning frameworks. Here, we implement CuLSM, a GPU-accelerated compute unified device architecture C++ code realizing parallelism over the spring list instead of the commonly used spatial decomposition, which requires intermittent updates on the particle neighbor list. Along with the image-to-particle conversion tool Img2Particle, our toolkit offers a fast and flexible platform to characterize the elastic and fracture behaviors of materials, expediting the design process between additive manufacturing and computer-aided design. With the growing demand for new lightweight, adaptable, and multi-functional materials and structures, such tailored and optimized modeling platform has profound impacts, enabling faster exploration in design spaces, better quality control for 3D printing by digital twin techniques, and larger data generation pipelines for image-based generative machine learning models.

Engineering working operations based on parameters of product manufacturability using a computer-aided design algorithm

The study aimed to develop an algorithm for computer-aided design (CAD) of working operations. A processing route for machining components was developed based on the criteria of production manufacturability, industrial data and a digital model of the product. The process of machining a workpiece was analysed using a method of theoretical separation. The machining process of a frame workpiece was used as a model. The identified formal parameters formed a basis for developing a CAD algorithm and a model of manufacturing route associated with the mechanical processing of a work-piece applying a condition-action rule, as well as mathematical logic. The research afforded a scheme for selecting process operations, given the manufacturability parameters of a product design. The concept of CAD algorithm was developed to design a production process of engineering products with given manufacturability parameters, including industrial data. The principle of forming a route and selecting a machining process was proposed. Several criteria of production manufacturability (labour intensity, consumption of materials, production costs) were selected to evaluate mechanical processing. A CAD algorithm for designing technological operations considering the parameters of manufacturability was developed. The algorithm was tested by manufacturing a frame workpiece. The developed algorithm can be used for reducing labour costs and development time, at the same time as improving the quality of production processes. The formalisation of process design is a crucial stage in digitalisation and automation of all production processes.

Design of a robot for inspection and diagnostic operations of rail track facilities

PurposeThe need to examine the integrity of infrastructure in the rail industry in order to improve its reliability and reduce the chances of breakdown due to defects has brought about development of an inspection and diagnostic robot.Design/methodology/approachIn this study, an inspection robot was designed for detecting crack, corrosion, missing clips and wear on rail track facilities. The robot is designed to use infrared and ultrasonic sensors for obstacles avoidance and crack detection, two 3D-profilometer for wear detection as well as cameras with high resolution to capture real time images and colour sensors for corrosion detection. The robot is also designed with cameras placed in front of it with colour sensors at each side to assist in the detection of corrosion in the rail track. The image processing capability of the robot will permit the analysis of the type and depth of the crack and corrosion captured in the track. The computer aided design and modeling of the robot was carried out using the Solidworks software version 2018 while the simulation of the proposed system was carried out in the MATLAB 2020b environment.FindingsThe results obtained present three frameworks for wear, corrosion and missing clips as well as crack detection. In addition, the design data for the development of the integrated robotic system is also presented in the work. The confusion matrix resulting from the simulation of the proposed system indicates significant sensitivity and accuracy of the system to the presence and detection of fault respectively. Hence, the work provides a design framework for detecting and analysing the presence of defects on the rail track.Practical implicationsThe development and the implementation of the designed robot will bring about a more proactive way to monitor rail track conditions and detect rail track defects so that effort can be geared towards its restoration before it becomes a major problem thus increasing the rail network capacity and availability.Originality/valueThe novelty of this work is based on the fact that the system is designed to work autonomously to avoid obstacles and check for cracks, missing clips, wear and corrosion in the rail tracks with a system of integrated and coordinated components.

Effect of Thermocycling on the Bond Strength of Self-Adhesive Resin Cements Used for Luting CAD/CAM Ceramics to Human Dentin

The aim of the study was to evaluate the influence of thermocycling on the shear bond strength of self-adhesive, self-etching resin cements luted to human dentin and computer-aided design/computer-aided manufacturing (CAD/CAM) ceramics. Three modern self-adhesive dental cements (Maxcem Elite, RelyX U200, Panavia SA) were used to lute three CAD/CAM ceramics (IPS Empress CAD, IPS e.max CAD, IPS e.max ZirCAD) onto the dentin. One conventional cement (Panavia V5) served as a control. After preparation, the samples were subjected to thermocycling as a method of artificial aging of dental materials applied to simulate long-term use in oral conditions. Shear bond strength was evaluated according to PN-EN ISO 29022:2013-10 and failure modes were observed under a light microscope. Statistical analysis was performed. The study demonstrated that a combination of ceramics and cements directly impacts the bond strength. The highest bond strength was observed in Panavia V5, lower in Panavia SA and Maxcem Elite and the lowest–in RelyX U200. Adhesive failure between human dentin and cements was the most common failure mode. Moreover, thermocycling highly decreased bond strength of self-adhesive, self-etching cements.