High-speed Simulation Research Articles

Study on Aerodynamic Characteristics and Stability of a Vehicle with Inverted Dihedral and Momentum Lift Augmentation

Abstract Inspired by the wave-rider idea and momentum principle, the vehicle with inverted dihedral and momentum lift augmentation is a new aerodynamic configuration of high-speed gliding vehicle in the near-space, which has achieved a high lift-to-drag ratio and long-distance sliding. Numerical simulation of aerodynamic characteristics and stability of the aircraft are carried out in this paper. The lift-to-drag characteristics, longitudinal-directional stability and lateral-directional stability are evaluated based on the National Numerical Wind tunnel’s high-speed simulation software, named NNW-HyFLOW. An unstructured/hybrid grid is used in the calculation at the typical ballistic points of altitude of 10-75km and Mach number of 3-25. The results shows that the lift-to-drag ratio reaches a peak value of 4.11 at the altitude of 30km and attack angle of 8°. This value is decreased when the altitude raises. The usable lift-to-drag ratio is over 3 in the glide phase range from 30 to 50 kilometres. This vehicle shows better longitudinal-directional stability at large angles of attack than at small in the reentry phase and glide phase, which can be optimized by adjusting the center of mass or pitching rudder. It has a weak instability in the lateral direction at small angle of attack in the glide phase. Therefore, it is suggested to avoid to work at the high altitude with a small angle of attack. Or, the lateral-directional stability can be strengthened at this altitude by improving the V-tail.

Fast Loosely-Timed Deep Neural Network Models with Accurate Memory Contention

The emergence of data-intensive applications, such as Deep Neural Networks (DNN), exacerbates the well-known memory bottleneck in computer systems and demands early attention in the design flow. Electronic System-Level (ESL) design using SystemC Transaction Level Modeling (TLM) enables effective performance estimation, design space exploration (DSE), and gradual refinement. However, memory contention is often only detectable after detailed TLM-2.0 approximately-timed or cycle-accurate RTL models are developed. A memory bottleneck detected at such a late stage can severely limit the available design choices or even require costly redesign. In this work, we propose a novel TLM-2.0 loosely-timed contention-aware (LT-CA) modeling style that offers high-speed simulation close to traditional loosely-timed (LT) models, yet shows the same accuracy for memory contention as low-level approximately-timed (AT) models. Thus, our proposed LT-CA modeling breaks the speed/accuracy tradeoff between regular LT and AT models and offers fast and accurate observation and visualization of memory contention. Our extensible SystemC model generator automatically produces desired TLM-1 and TLM-2.0 models from a DNN architecture description for design space exploration focusing on memory contention. We demonstrate our approach with a real-world industry-strength DNN application, GoogLeNet. The experimental results show that the proposed LT-CA modeling is 46× faster in simulation than equivalent AT models with an average error of less than 1% in simulated time. Early detection of memory contentions also suggests that local memories close to computing cores can eliminate memory contention in such applications.

Design and Simulation of New High Speed, Low Power D-Flip-Flops, Implemented Using Graphene Nanoribbon and Carbon Nanotube Field Effect Transistors

Design and Simulation of New High Speed, Low Power D-Flip-Flops, Implemented Using Graphene Nanoribbon and Carbon Nanotube Field Effect Transistors

Designing ultra-broadband terahertz polarization converters based on the transformer model

Polarization, a fundamental property of terahertz (THz) waves, can be controlled using metasurfaces for signal transmission and sensitive measurements. However, conventional methods for designing polarization-conversion metasurfaces require numerous numerical simulation iterations and trial and error attempts that are computationally intensive and time-consuming, necessitating a more rapid and efficient approach. This study proposes a transformer-based method for the inverse design of terahertz polarization converters; the approach can accurately design the corresponding metasurface based on the target spectrum. The model also comprises a forward network that can precisely and intuitively predict the meta-atoms spectra with high simulation speed and reduced computational cost. Using this approach, two ultra-broadband polarization conversion devices were designed in approximately 0.006 s within a target frequency range of 0.5–4 THz, with polarization conversion ratios greater than 90% within 1.23–3.19 THz and 1.18–3.24 THz. Additionally, the average cross-polarization ratio was greater than 50%. This study provides insights into designing terahertz polarization converters, which are applicable in terahertz communications, polarization imaging, and biomedical procedures.

MOTION CONTROLLED GAMING INTERFACE

The motion game controller project based on OpenCV technology enhances gaming experience. Also, it works with OpenCV where computer vision used in translating human hands movement to game plays. This one-of-a- kind controller has some degree of flexibility. The product lets you adjust the intensity of emotions to your individual needs and type of audio experience. A customized commodity promises a complete response tailored for different levels of skills available in the marketplace. Motion detection is reliable owing to OpenCV integration which ensures proper management in the game. The control center is suitable for any type of gaming whether it involves exploration of virtual worlds high-speed simulation or just mere playing.

Exploration of the mechanical properties of carbon-incorporated amorphous silica using a universal neural network potential

C-incorporated amorphous silica (a-SiOC) is expected to be a significant dielectric film for miniaturized semiconductor devices. However, information on the relationship among its composition, atomic structures, and material properties remains insufficient. This study investigated the dependence of the elastic modulus on the C content in a-SiOC, employing a universal neural network interatomic potential to realize a high-accuracy and high-speed simulation of multicomponent systems. The relationship between elastic modulus and atomic network structures was explored by fabricating 480 amorphous structures through the melt-quenching method without predetermined structure assumptions. The bulk modulus increased from 45 to 60 GPa by incorporating 10% C atoms under O-poor conditions and 20% C atoms under O-rich conditions, respectively. This result is attributed to the formation of denser crosslinking atomic network structures. In particular, the C atoms bonded with the Si atoms with higher coordination under O-poor conditions, whereas they tend to bond with O atoms under O-rich conditions, breaking the SiO2 network. Large C clusters precipitated as the C fraction was increased under O-rich conditions. Gas molecules, such as CO and CO2, were also generated. These results are consistent with reported ab initio calculation results of the formation energies of C defects and gas molecules in SiO2. The findings suggest that realizing O-poor conditions during deposition is crucial for fabricating stronger dielectric films. Therefore, this work contributes to understanding the fabrication of stronger dielectric films and elucidating the underlying mechanism of C cluster formation.

High-Speed Simulator of Numerical Controller Considering Axis Dynamics for Realizing High Precision Digital Twin of Machine Tools

High-Speed Simulator of Numerical Controller Considering Axis Dynamics for Realizing High Precision Digital Twin of Machine Tools

UMC-PET: a fast and flexible Monte Carlo PET simulator

Objective. The GPU-based Ultra-fast Monte Carlo positron emission tomography simulator (UMC-PET) incorporates the physics of the emission, transport and detection of radiation in PET scanners. It includes positron range, non-colinearity, scatter and attenuation, as well as detector response. The objective of this work is to present and validate UMC-PET as a a multi-purpose, accurate, fast and flexible PET simulator. Approach. We compared UMC-PET against PeneloPET, a well-validated MC PET simulator, both in preclinical and clinical scenarios. Different phantoms for scatter fraction (SF) assessment following NEMA protocols were simulated in a 6R-SuperArgus and a Biograph mMR scanner, comparing energy histograms, NEMA SF, and sensitivity for different energy windows. A comparison with real data reported in the literature on the Biograph scanner is also shown. Main results. NEMA SF and sensitivity estimated by UMC-PET where within few percent of PeneloPET predictions. The discrepancies can be attributed to small differences in the physics modeling. Running in a 11 GB GeForce RTX 2080 Ti GPU, UMC-PET is ∼1500 to ∼2000 times faster than PeneloPET executing in a single core Intel(R) Xeon(R) CPU W-2155 @ 3.30 GHz. Significance. UMC-PET employs a voxelized scheme for the scanner, patient adjacent objects (such as shieldings or the patient bed), and the activity distribution. This makes UMC-PET extremely flexible. Its high simulation speed allows applications such as MC scatter correction, faster SRM estimation for complex scanners, or even MC iterative image reconstruction.

Efficient robust project schedule method based on iterated local search with high-speed simulations

Efficient robust project schedule method based on iterated local search with high-speed simulations

Design and verification of a hybrid electrostatic discharge model for Gate-Controlled silicon controlled rectifier

The DC breakdown characteristic of electrostatic discharge (ESD) protection device, which is an important indicator of its transparency and circuit compatibility, has received widespread attention. Currently, methods such as Verilog-A hardware description language, circuit-level SPICE simulation, and process-level device modeling cannot simultaneously achieve high accuracy, good convergence, and fast simulation speed. Therefore, in this paper, a hybrid ESD model based on Technology Computer Aided Design (TCAD) device-level simulation, Monte Carlo numerical modeling and Verilog-A behavioral modeling is proposed to characterize the ESD characteristics of gate-controlled silicon-controlled rectifier (GCSCR). A device-level model of GCSCR was established using TCAD, and the working mechanism was simulated. By extracting the electric field from TCAD and using the Monte Carlo modeling method, the DC characteristic of GCSCR was accurately characterized. In addition, the snapback characteristic of the device was successfully simulated by Verilog-A. The effectiveness of the above approaches was further verified based on the 0.18 μm standard BCD (Bipolar-CMOS-DMOS) process. Comparison results indicate that the hybrid model exhibits high simulation accuracy, good convergence and good universality and scalability, providing a simple and effective modeling solution for ESD devices of different structures and sizes.1This work is supported by the National Natural Science Foundation of China (Grant No. 62174052, 61827812), Hunan Science and Technology Department Huxiang High-level Talent Gathering Project (Grant No. 2019RS1037) and Innovation Project of Science and Technology Department of Hunan Province (Grant No. 2020GK2018).

The effect of PCM on mitigating thermal runaway propagation in lithium-ion battery modules

The main safety issue of lithium-ion batteries (LIBs) is thermal runaway (TR), which has greatly hindered the application of LIBs. Phase change materials (PCM) have been used in battery modules as a thermal management method due to the heat absorption function during the phase change process. However, the role of PCM in TR propagation mitigation has not been carefully examined. In this paper, a 1D heat transfer model was developed to predict the mitigation effect of PCM on TR propagation of a battery array, which shows the superiority of high simulation speed and accuracy. The effects of thermo-physical parameters of PCM on cascading cell-to-cell thermal runaway propagation behavior were investigated. In addition, we gave an optimal range of key parameters of PCM based on safe regulations of China and the United Nations regarding to the TR in electric vehicle LIBs. It was found that the latent heat, density and heat capacity of PCM have similar effects on TR propagation behavior. With the increase of the three PCM parameters, the time duration between cell-to-cell failure propagation increases linearly, which shows a slower TR propagation rate. The optimal ranges for density, heat capacity and latent heat of PCM are over 2150 kg·m−3, over 4100 J·kg−1·K−1 and over 9 × 105 J·kg−1, respectively. What’s more, the TR propagation will exacerbate with the increase of thermal conductivity of PCM, which reminds us to notice a balance between thermal management and TR mitigation in PCM-based thermal management system. Generally, through analyzing the effect of thermal diffusivity of PCM in TR inhibition, we found higher thermal diffusivity will speed up the propagation of TR. And the TR propagation speed is more sensitive to the change of density of PCM. The thermal diffusivity of PCM should be less than 9 × 10−7 m2·s−1 to satisfy the safety standards. The PCM manifests great performance in retarding TR propagation with the phase transition temperature in the range from 318.15 to 518.15 K. Moreover, we found that there exists a critical PCM thickness over which TR propagation will not occur. As the battery thickness increases from 8.8 to 56.5 mm, the critical PCM thickness shows a non-monotonic variation trend (increasing at first and decreasing later). This study demonstrates the feasibility of using PCM as a thermal runaway mitigation strategy and provides a guideline for the optimization of physical parameters of PCM.

Modeling of battery energy storage systems for AGC performance analysis in wind power systems

Battery energy storage system (BESS) is being widely integrated with wind power systems to provide various ancillary services including automatic generation control (AGC) performance improvement. For AGC performance studies, it is crucial to accurately describe BESS’s power regulation behavior and provide a correct state of charge (SOC). In addition, BESS model is required to maintain a sufficiently high simulation speed, since it usually is involved in hour- or day-scale simulations. Different from existing models, this paper develops a new BESS model which considers DC-AC converter control, DC link circuit and switching loss, thus providing an accurate power regulation behavior. In addition, it also considers the nonlinear relationship between open-circuit voltage and SOC of battery so that it provides a correct SOC. As a whole, the BESS is simplified as a controlled current source with fundamental frequency (50/60 Hz) and described by algebraic phasor equations to reduce computational burden. This makes the proposed model capable of finishing hour- or day-scale simulations within a few minutes. Time-domain simulations are used to validate and compare the simulation accuracy with the classical first-order transfer function model and electromagnetic model. Based on the proposed model, this paper also introduces and verifies a new BESS-based strategy to improve the AGC performance of wind farms.

The Effect of ICT in Education and Teaching: Student Evaluation Based Verification

ICT, Information Communication Technology, is a course that is being taught in several different institutions. The role of this course is crucial in the teaching and grading process. The significance of this course is based on several different factors. ICT increases the mental capabilities of the students. In this study we have shown that IT based knowledge and accessibility to the internet increase the capability of students for rapid absorbing of information, fast processing, and achievement of smart conclusions. High speed modeling and simulation by digital techniques enable students to learn by doing, leading to actual and real implementation of the invented models and IT obtained knowledge. Quantified knowledge, by numerically represented data and their smart distribution, leads to deterministic and logical decision. The tests we have performed, in addition to this work, methodology we have applied, by using temporal based distribution of data and information, have shown the advantage of IT and internet, for a better and faster understanding process of absorbing and incubating the knowlage by the students, during the learning and teaching process, leading to the optimal conclusion. Our study is based on three possibilties, modes or cases: First case: The tests are performed to the studens with no IST education. Second case: The test is introduced to the groupe of students with superfisial or lack of proper ICT education or training. Third case: A group of students trained in a proper way, where thoroughly professional manner is applied. A correct representation of the data is verified by Fourier Transform Technique and frequency representation of information. Knowing how to manipulate with the computer models and platforms or prograns accesible at internet, that can be used for primary and secondary school teaching, is a very important approach and possibility that is being used today in different teaching sessions.
 
 Received: 13 April 2023 / Accepted: 10 August 2023 / Published: 5 September 2023

Machine Learning and IoT Trends for Intelligent Prediction of Aircraft Wing Anti-Icing System Temperature

Airplane manufacturers are frequently faced with formidable challenges to improving both aircraft performance and customer safety. Ice accumulation on the wings of aircraft is one of the challenges, which could result in major accidents and a reduction in aerodynamic performance. Anti-icing systems, which use the hot bleed airflow from the engine compressor, are considered one of the most significant solutions utilized in aircraft applications to prevent ice accumulation. In the current study, a novel approach based on machine learning (ML) and the Internet of Things (IoT) is proposed to predict the thermal performance characteristics of a partial span wing anti-icing system constructed using the NACA 23014 airfoil section. To verify the proposed strategy, the obtained results are compared with those obtained using computational ANSYS 2019 software. An artificial neural network (ANN) is used to build a forecasting model of wing temperature based on experimental data and computational fluid dynamics (CFD) data. In addition, the ThingSpeak platform is applied in this article to realize the concept of the IoT, collect the measured data, and publish the data in a private channel. Different performance metrics, namely, mean square error (MSE), maximum relative error (MAE), and absolute variance (R2), are used to evaluate the prediction model. Based on the performance indices, the results prove the efficiency of the proposed approach based on ANN and the IoT in designing a forecasting model to predict the wing temperature compared to the numerical CFD method, which consumes a lot of time and requires high-speed simulation devices. Therefore, it is suggested that the ANN-IoT approach be applied in aviation.

Accuracy of high resolution coastal flow speed simulations during and outside of wind, wave and stratification events (Gulf of Lion, NW Mediterranean)

Accuracy of high resolution coastal flow speed simulations during and outside of wind, wave and stratification events (Gulf of Lion, NW Mediterranean)

An Algorithm for Fast Simulation of CW Illuminator

The continuous wave (CW) illuminator is aimed to simulate high-altitude nuclear electromagnetic pulse. In this article, a simulation algorithm is proposed covering the method of moments and finite difference method (FDM), with the high-speed simulation of the CW illuminator with arbitrary ellipse size, arbitrary loading, and arbitrary polarization direction. Based on the surface electric field equation of the CW illuminator, the mathematical model is established with the vector potential equation and the boundary conditions. In this model, the pulse function and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> function are set as the basis function and the weight function, respectively, for the establishment of the current equation, with the current distribution determined by the simplification equation with image theory and nonuniform FDM. Finally, as the field distribution is determined by the superposition theorem. The simulation algorithm is verified by the self-built CW illuminator.

Predicting Geometrical Variation in Fabricated Assemblies Using a Digital Twin Approach Including a Novel Non-Nominal Welding Simulation

The aerospace industry faces constantly increasing demands on performance and reliability, especially within the vital area of engine development. New technologies are needed in order to push the limits of high precision manufacturing processes for the next generation of aircraft engines. An increased use of in-line data collection in manufacturing is creating an opportunity to individualize each assembly operation rather than treating them identically. Welding is common in this context, and the interaction between welding distortion and variation in part geometries is difficult to predict and manage in products with tight tolerances. This paper proposes an approach based on the Digital Twin paradigm, aiming to increase geometrical quality by combining the novel SCV (Steady-state Convex hull Volumetric shrinkage) method for non-nominal welding simulation with geometrical data collected from 3D scanning of parts. A case study is presented where two parts are scanned and then welded together into an assembly. The scan data is used as input for a non-nominal welding simulation, and the result of the simulation is compared directly to scan data from the real welded assembly. Three different welding simulation methods are used and assessed based on simulation speed and ability to predict the real welding result. The segmented SCV method for welding simulation shows promising potential for this implementation, delivering good prediction accuracy and high simulation speed.

High Speed Simulation and Freeform Optimization of Nanophotonic Devices with Physics-Augmented Deep Learning

High Speed Simulation and Freeform Optimization of Nanophotonic Devices with Physics-Augmented Deep Learning

Simulation of high speed rotating dynamics in constrained mechanical systems

High-speed rotating motion is an important issue in mechanical systems such as propellers or turbine blades. Difficulties occurs in the simulation of high-speed rotating dynamics, resulting in unexpected and unreliable numerical results. For example, the calculated angular velocity usually doesn’t increase linearly but grows until reaching a saturation value under a constant torque. This phenomenon will be more complex in constrained mechanical systems, especially in a flexible system. This work aims to address this issue that arises in the simulation of high-speed rotating dynamics, where a new formulation of non-linear floating frame of reference formulation is proposed to solve constrained flexible system. Pros and cons of various numerical techniques in the field of multibody system dynamics are compared and discussed here. These techniques involve the Euler parameter formulation, local rotational parameters, minimal coordinate set approach and the nonlinear elastic formulation. Cases with constrained rigid or flexible system are studied here. This work provides an insight into practical simulations of high-speed rotating mechanical systems.

High-Speed Penetration Test and Numerical Simulation of Ceramic-Reactive Powder Concrete Composite Target

To study the protective performance of ceramic materials against the high-speed penetration of projectiles, seven ceramic-reactive powder concrete (C-RPC) composite targets were designed. Using a 100/30 mm two-stage light-gas gun, penetration tests were performed at 1.4–2.0 km/s. The results showed that the penetration depth of the C-RPC target body first increased and then decreased as the target speed increased, and the corresponding reverse penetration speed was between 1743.2 m/s and 1803.9 m/s. LS-DYNA software was used to perform a wide-speed numerical simulation study of a projectile’s high-speed penetration of the composite target, focusing on the analysis of the deformation, mass loss, passivation, and penetration depth of the projectile. Changes in the parameters were compared with the experimental results of a C-RPC penetration test, which together revealed the changes in the damaging effect of the missile’s high-speed penetration of the C-RPC composite target. It provided a damage analysis of the high-speed/super-high-speed penetration of the projectile, which provides a reference for targeted protection research.