Showing papers on "Verification and validation of computer simulation models published in 2020"

Hybrid broadband ground motion simulation validation of small magnitude earthquakes in Canterbury, New Zealand:

Abstract: Ground motion simulation validation is an important and necessary task toward establishing the efficacy of physics-based ground motion simulations for seismic hazard analysis and earthquake enginee...

Gaussian-Process-Based Surrogate for Optimization-Aided and Process-Variations-Aware Analog Circuit Design

Abstract: Optimization algorithms have been successfully applied to the automatic design of analog integrated circuits. However, many of the existing solutions rely on expensive circuit simulations or use fully customized surrogate models for each particular circuit and technology. Therefore, the development of an easily adaptable low-cost and efficient tool that guarantees resiliency to variations of the resulting design, remains an open research area. In this work, we propose a computationally low-cost surrogate model for multi-objective optimization-based automated analog integrated circuit (IC) design. The surrogate has three main components: a set of Gaussian process regression models of the technology’s parameters, a physics-based model of the MOSFET device, and a set of equations of the performance metrics of the circuit under design. The surrogate model is inserted into two different state-of-the-art optimization algorithms to prove its flexibility. The efficacy of our surrogate is demonstrated through simulation validation across process corners in three different CMOS technologies, using three representative circuit building-blocks that are commonly encountered in mainstream analog/RF ICs. The proposed surrogate is 69 X to 470 X faster at evaluation compared with circuit simulations.

Development of an Asymmetric Car-Following Model and Simulation Validation

Abstract: Numerous car-following models have been developed since the 1950s. However, there still exist many traffic phenomena that cannot be demonstrated using the existing models. Therefore, this research proposed a new car-following model, the Asymmetric car-following (ACF) model based on the understanding of driver’s asymmetric behavior, which can explain complex traffic phenomena. We established the asymmetric car-following (ACF) rule under the vehicle’s safety constraints using eight parameters that indicate the driver’s characteristics and vehicle’s performances. To evaluate the ACF model, we performed the simulation for car-following pairs and conducted a comparison analysis with the existing models: Newell, Gipps, GM, and IDM. As a result, the proposed ACF model showed good fitness with the empirical trajectory and the apparent asymmetric behavior compared to others. For further investigation in the congested traffic stream, we simulated a group of vehicles by adding an error term to represent the driver’s unexpected behavior. The simulation showed growth, propagation, and dissipation of the stop-and-go traffic. These results proved that the ACF model has the strength to elaborate on various traffic phenomena, such as traffic hysteresis and stop-and-go traffic.

Model-Less Feedback Control for Soft Manipulators with Jacobian Adaptation

Abstract: In this paper we propose a novel closed-loop model-less feedback control scheme for soft manipulators with Jacobian matrix adaptation. As the major merit, this approach does not rely on a specific kinematic model and thus has wide applicability and portability for different kinds of soft manipulators. We make use of closed-loop control, convex optimization and adaptation strategy to estimate the Jacobian matrix for trajectory tracking tasks. In the simulation validation, we adapt the algorithm to a two-section soft manipulator of piece-wise constant curvature to track a desired trajectory. Furthermore, we compare our algorithm with two other model-less algorithms and a model-based algorithm with noise on their tracking performances. Validation results prove the feasibility of this simple yet effective model-less feedback control scheme.

Intelligent Fault-Tolerant Control System Design and Semi-Physical Simulation Validation of Aero-Engine

Abstract: In order to improve the reliability and real-time of the control system of aero-engine, an intelligent fault-tolerant control system based on the online sequential extreme learning machine (OS-ELM) is proposed against the sensor faults. This system can realize the online fault diagnosis and signal reconstruction without a system model. And while considering the traditional PID control robustness and poor anti-interference ability and other shortcomings, an improved global fast non-singular terminal sliding mode control method is used to obtain better control effects, effectively solve the uncertainty problem in aero-engine, and give full play to aero-engine performance. To verify the feasibility and effectiveness of this system based on the above method, a turbofan engine is taken as the research object and semi-physical simulation experiments on fault-tolerant control are conducted on a semi-physical simulation test platform. Results show that the controller of this system can safely and reliably control the aero-engine without losing its control performance under the circumstance that there are faults in engine sensors. The purpose of fault-tolerant control is reached.

A novel evaluation method for vehicle and traffic performance of different decision control of automatic lane change based on miniature model

Abstract: Research on automatic lane-change decision is mainly limited to simulation validation and lacks real vehicle validation methods because it is limited by experimental site and automatic driving tech...

Test Results of an Innovative and Modular Sensor Design for Fission Chamber Studies

Abstract: Since many years, the Instrumentation, Sensors and Dosimetry laboratory at CEA Cadarache has been working to propose innovative and robust design of fission chambers. In this framework, few simulation tools like Chester or PyFc were developed to make detector prototyping and optimisation possible. Up to now, the code experimental validations are scarce mainly because of the lack of flexibility of regular fission chambers. In order to set up an experimental database for code validation, an innovative modular twin fission chamber, the CFTM, was designed. It allows to set with precision the inter-electrode gap, the filling gas pressure as well as the fissile deposit used. This detector was irradiated in Minerve zero power reactor in order to gather results for code validation. Thanks to a calibration procedure, a bank of experimental results is available for simulation validation.