Large-scale Real-time Simulation Research Articles

Discrete differential geometry-based model for nonlinear analysis of axisymmetric shells

In this paper, we propose a novel one-dimensional (1D) discrete differential geometry (DDG)-based numerical method for geometrically nonlinear mechanics analysis (e.g., buckling and snapping) of axisymmetric shell structures. Our numerical model leverages differential geometry principles to accurately capture the complex nonlinear deformation patterns exhibited by axisymmetric shells. By discretizing the axisymmetric shell into interconnected 1D elements along the meridional direction, the in-plane stretching and out-of-bending potentials are formulated based on the geometric principles of 1D nodes and edges under the Kirchhoff–Love hypothesis, and elastic force vector and associated Hessian matrix required by equations of motion are later derived based on symbolic calculation. Through extensive validation with available theoretical solutions and finite element method (FEM) simulations in literature, our model demonstrates high accuracy in predicting the nonlinear behavior of axisymmetric shells. Importantly, compared to the classical theoretical model and three-dimensional (3D) FEM simulation, our model is highly computationally efficient, making it suitable for large-scale real-time simulations of nonlinear problems of shell structures such as instability and snap-through phenomena. Moreover, our framework can easily incorporate complex loading conditions, e.g., boundary nonlinear contact and multi-physics actuation, which play an essential role in the use of engineering applications, such as soft robots and flexible devices. This study demonstrates that the simplicity and effectiveness of the 1D discrete differential geometry-based approach render it a powerful tool for engineers and researchers interested in nonlinear mechanics analysis of axisymmetric shells, with potential applications in various engineering fields.

NYUS.2: an automated machine learning prediction model for the large-scale real-time simulation of grapevine freezing tolerance in North America.

Accurate and real-time monitoring of grapevine freezing tolerance is crucial for the sustainability of the grape industry in cool climate viticultural regions. However, on-site data are limited due to the complexity of measurement. Current prediction models underperform under diverse climate conditions, which limits the large-scale deployment of these methods. We combined grapevine freezing tolerance data from multiple regions in North America and generated a predictive model based on hourly temperature-derived features and cultivar features using AutoGluon, an automated machine learning engine. Feature importance was quantified by AutoGluon and SHAP (SHapley Additive exPlanations) value. The final model was evaluated and compared with previous models for its performance under different climate conditions. The final model achieved an overall 1.36°C root-mean-square error during model testing and outperformed two previous models using three test cultivars at all testing regions. Two feature importance quantification methods identified five shared essential features. Detailed analysis of the features indicates that the model has adequately extracted some biological mechanisms during training. The final model, named NYUS.2, was deployed along with two previous models as an R shiny-based application in the 2022-23 dormancy season, enabling large-scale and real-time simulation of grapevine freezing tolerance in North America for the first time.

GAMMA: A General Agent Motion Model for Autonomous Driving

This letter presents GAMMA, a general motion prediction model that enables large-scale real-time simulation and planning for autonomous driving. GAMMA models <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">heterogeneous</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">interactive</i> traffic agents that operate under diverse road conditions, with various geometric and kinematic constraints. GAMMA treats the prediction task as constrained optimization in traffic agents’ velocity space. The objective is to optimize an agent’s driving performance, while obeying all the constraints resulting from the agent’s kinematics, collision avoidance with other agents, and the environmental context. Further, GAMMA explicitly conditions the prediction on human behavioral states as parameters of the optimization model, in order to account for versatile human behaviors. We evaluated GAMMA on a set of real-world benchmark datasets. The results show that GAMMA achieves high prediction accuracy on both homogeneous and heterogeneous traffic datasets, with sub-millisecond execution time. Further, the computational efficiency and the flexibility of GAMMA enable (i) simulation of mixed urban traffic at many locations worldwide and (ii) planning for autonomous driving in dense traffic with uncertain driver behaviors, both in real-time. The open-source code of GAMMA is available <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">online</uri> .

Research on real time simulation modeling method of large scale MMC electromagnetic transient

Modular multilevel converter (MMC) contains a large number of power electronic switching devices. The modeling method based on switching circuit model needs a lot of resources and the simulation speed is slow, so it is difficult to realize large-scale real-time simulation of electromagnetic transient. A MMC electromagnetic transient numerical modeling method based on ideal transformer model (ITM) is presented. Firstly, the MMC system is divided into the main circuit network and the sub module group network by ITM method, and the error caused by decoupling delay in serial and parallel real time simulation is compensated respectively by interpolation prediction and advanced interpolation prediction. Secondly, the capacitor in sub module is discreted respectively by trapezoidal integration method, backward Euler method and Gear-2 method. Based on the above numerical integration, the difference equations of capacitance voltage, capacitance current and output voltage of half bridge and full bridge sub modules are derived. Then, in order to improve the calculation speed, a simplified numerical model of half bridge and full bridge sub module based on switching function is proposed. Finally, the MMC based on switching circuit model runs off-line simulation in the simulation software, and the above MMC numerical modeling method runs real-time simulation in Speedgoat real-time simulator. The off-line and real-time simulation results of the MMC numerical modeling method and the switching circuit model are compared. And the simulation results verify the feasibility and effectiveness of the above MMC numerical modeling method in real time simulation.

Simulations of a bubble wall interacting with an electroweak plasma

We perform large-scale real-time simulations of a bubble wall sweeping through an out-of-equilibrium plasma. The scenario we have in mind is the electroweak phase transition, which may be first order in extensions of the Standard Model, and produce such bubbles. The process may be responsible for baryogenesis and can generate a background of primordial cosmological gravitational waves. We study thermodynamic features of the plasma near the advancing wall, the generation of Chern-Simons number/Higgs winding number and consider the potential for CP-violation at the wall generating a baryon asymmetry. A number of technical details necessary for a proper numerical implementation are developed.

Dynamic performance testing and implementation for static var compensator controller via hardware-in-the-loop simulation under large-scale power system with real-time simulators

Recently, the number of electric-power facilities, including high-voltage direct current (HVDC) and flexible AC current transmission system (FACTS), has rapidly increased, owing to restrictions regarding the expansion of existing AC networks. Traditionally, a final site acceptance test (SAT) is conducted following controller performance verification in a factory acceptance test (FAT), based on an equivalent small network or voltage sources. Furthermore, several standards and guidelines related to the FAT and SAT of HVDC and FACTS have been published. Meanwhile, as the number of power electronic devices and the complexity of power systems increase, controller performance tests reflecting the wide area dynamic characteristics and control operation of adjacent devices should be required. However, a wide-area dynamic performance test (DPT) requires a large-scale real-time simulator and high-level operational technology. Owing to these difficulties, the definition, standard, procedure, and test protocol of hardware-in-the-loop simulation (HILS)-DPT, based on a large-scale power system, have not yet been established systematically, and only a few applications have been reported. This study aims to establish and propose procedures, a test protocol, and a methodology of HILS-DPT and large-scale power system modeling for testing. To this end, a case study was conducted to demonstrate the necessity of the DPT procedures and methodologies for the static VAR compensator controller installed at the Shin-Jecheon substation, an ongoing project undertaken the by Korea Electric Power Corporation, as of 2019.

Hardware-in-the-Loop Simulation Using Real-Time Hybrid-Simulator for Dynamic Performance Test of Power Electronics Equipment in Large Power System

This paper presents the hardware-in-the-loop simulation for dynamic performance test (HILS-DPT) of power electronic equipment replicas using a real-time hybrid simulator (RTHS). The authors developed the procedure of HILS-DPT, and as an actual case example, the results of HILS-DPT of Static VAR Compensator (SVC) replica using RTHS is presented. RTHS is a co-simulation tool that synthesizes real-time simulator (RTS) with transient stability program to perform real-time dynamic simulation of a large power system. As power electronics applications have been increasing, the electric utilities have performed HILS-DPT of the power electronics equipment to validate the performance and investigate interactions. Because inspection tests are limited in their ability to validate its impact on the power system during various contingencies, all power electronics equipment newly installed in the Korean power system should take HILS-DPT using large-scale RTS with replicas since 2018. Although large-scaled RTS offers an accuracy improvement, it requires lots of hardware resources, time, and effort to model and simulate the equipment and power systems. Therefore, the authors performed SVC HILS-DPT using RTHS, and the result of the first practical application of RTHS present feasibility comparing the result of HILS-DPT using large-scale RTS. The authors will discuss the test results and share lessons learned from the industrial experience of HILS-DPT using RTHS.

Application of the First Replica Controller in Korean Power Systems

The purpose of this paper is to introduce, examine, and evaluate the industrial experiences and effectiveness of a Thyristor Controlled Series Compensator (TCSC) replica controller installed in Korea in 2019 through a review of its configuration, test platform, and practical application, and further to propose operational guidelines for replica controllers. Four representative practical cases were conducted: a Dynamic Performance Test (DPT) under a sufficiently large-scale power system prior to the Site Acceptance Test (SAT), pre-verification for on-site controller modification during operation stage, parameter tuning to mitigate the control interaction, and time domain simulation for Sub-Synchronous Torsional Interaction (SSTI). None of these four cases can be performed in a Factory Acceptance Test (FAT) or on-site. Therefore, TCSC control performance was accurately verified under the entire Korean power system based on a large-scale real-time simulator, which demonstrated its effectiveness as a powerful tool for operations including multiple power electronics devices. Our review herein of these four practical cases is expected to show the usefulness of replica controllers, to demonstrate their strength to deal with practical field events, and to contribute to the further expansion of the application area from a perspective of electric utility.

NeuroSpike viewer: A graphical environment for efficient control, communication and display of large-scale real-time simulation of Spiking Neural Networks on embedded systems

In recent years, the scientific community's interest for developing software or hardware tools capable of processing and displaying real-time simulations of large-scale Spiking Neural Networks (SNN) has been growing exponentially. Visualization of the simulations is crucial to observe and study the dynamics of the SNN, because these models involve high level of biological realism by encoding spatial-temporal information into action potentials or spikes like biological neurons do. Existing tools are based on supercomputers or customized neuromorphic architectures to compute large-scale SNN models. However, many of them are unsuitable to carry out real-time analysis of large scale SNN with minimal cost as large amount of complex data needs to be processed and displayed at the same time. This work intends to provide an efficient cost effective and power efficient emulation tool based on hardware-software hybrid to process, control, and display large-scale SNN network behavior in real time. The solution consists of a customized hardware architecture that computes the neural-synaptic parameters and a software environment that displays the same on the screen of a general purpose computer (Host). The data to be visualized is transferred to the host through high speed Ethernet link. The proposed solution tailors the use of the Ethernet link bandwidth to an optimum such that the customized neuromorphic architecture and the host computer duo can be used to visualize the dynamics of SNN network of any size in real-time. The hardware and software platforms are scalable in terms of number of neurons and synapses. This solution gives flexibility to the user to visualize and analyze SNN network of any size avoiding saturation of the high-speed serial Ethernet link while supporting the visualization of SNN dynamics with a good screen resolution.

Social Effects on Real-Time ATC Simulation

Large-scale Real-Time simulations are accepted as the preferred method for the validation of Air Traffic Control systems. They are generally accepted as valid representations of the ‘real world’. Controllers participating in such simulations are considered to be both objective evaluators and representative participants. A study by a social anthropologist suggests that the success or failure of a simulation may depend on social factors unknown to, or ignored by, simulation staff, illustrating this from experience of two contrasting simulations.