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A Simulator for NSA-DEVS in Matlab Matlab 中的 NSA-DEVS 模拟器
Pub Date : 2023-12-01 DOI: 10.11128/sne.33.sw.10661
David Jammer, P. Junglas, T. Pawletta, S. Pawletta
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引用次数: 0
Fit for Duty Assessment of Driver Fatigue based on Statistical Modelling of Cardiovascular Parameters 基于心血管参数统计建模的驾驶员疲劳适合度评估
Pub Date : 2023-12-01 DOI: 10.11128/sne.33.tn.10663
Ciara Picher, M. Bachler, Christer Ahlström, Christopher C. Mayer, Berhard Hametner
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引用次数: 0
Modeling and Simulation of a Real-world Application using NSA-DEVS 使用 NSA-DEVS 对真实世界的应用进行建模和仿真
Pub Date : 2023-12-01 DOI: 10.11128/sne.33.tn.10662
David Jammer, P. Junglas, T. Pawletta, S. Pawletta
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引用次数: 0
A Use Case for Digital Tools in Crafts: Simulation and Virtual Reality for Carpentries 数字工具在手工艺中的应用案例:木工行业的模拟和虚拟现实技术
Pub Date : 2023-12-01 DOI: 10.11128/sne.33.tn.10667
Bastian Prell, J. Reiff-Stephan
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引用次数: 0
Simplified Mechanistic Model of the Multiple Hearth Furnace for Control Development 用于控制开发的多底炉简化机理模型
Pub Date : 2018-09-01 DOI: 10.11128/sne.28.sn.10426
J. V. Gomez Fuentes, Sirkka-Liisa Jämsä-Jounela
This paper presents the simplified mechanistic model of a Multiple Hearth Furnace (MHF), developed for process control implementation. The detailed mechanistic model of the MHF and its solving procedure are introduced. Based on the detailed model, the simplified model is developed in the nonlinear Hammerstein-Wiener form, which defines a specific type of nonlinear state space models suitable for example for Model Predictive Control (MPC) implementation. The simplified model aims to preserve the key physicalchemical phenomena taking place in the furnace and to reproduce the nonlinear dependencies between the input and output variables. Finally, the paper presents the simulation results to compare the mechanistic and the simplified models. The comparison confirms that the dynamics of the simplified model accurately follows the mechanistic model outputs. Introduction Furnaces, such as the rotary kilns and multiple hearth furnaces, are widely used in industry for the calcination of clay minerals, such as kaolin. However, these processes continue to provide challenges in maintaining efficient process operations. In particular, it is hard to control the final product quality, due to the difficulty in measuring the product characteristics, the solid temperature profile in the furnace, and the rates of the calcination reactions. Instead, the existing control systems mostly rely on the gas temperature measurements and traditional control implementations, such as PID. This strategy, however, does not allow achieving stable solid phase temperature profile and uniform product quality. In contrast, a Model Predictive Control (MPC), based on a model describing the physicalchemical phenomena in the furnace, would be able to stabilize the solid temperature and minimize the product quality variations. 1 Process Description This paper considers a multiple hearth furnace used for kaolin calcination, having the counter-current solid and gas flows. The furnace has eight hearths, and eight burners, combusting natural gas to provide the heat necessary for the calcination reactions, are located in hearths 4 and 6. The amount of air flow, supplied to the burners for the gas combustion, is calculated based on the stoichiometric ratio. The burners are placed with a tangential alignment. Kaolin is supplied to the first hearth located at the top of the furnace. In the calciner, the material is moved by the metal plates, called blades, which are attached to the rotating rabble arms, designed with the intention of transporting the material outwards on even-numbered hearths and inwards on odd-numbered hearths. The kaolin traversing the even numbered hearths moves outward to descend through the holes at the outside border of the hearth, while in the odd-numbered hearths kaolin falls to the next hearth through a single annulus located around the shaft carrying the rabble arms. The temperature of the solid increases as it travels down through the furnace and reaches its maximum in
。本文介绍了为实现过程控制而开发的多底炉(MHF)简化机理模型。介绍了该模型的详细机理模型及其求解过程。在详细模型的基础上,以非线性Hammerstein-Wiener形式建立了简化模型,定义了一种特定类型的非线性状态空间模型,适用于模型预测控制(MPC)的实现。简化模型旨在保留炉内发生的关键物理化学现象,并再现输入和输出变量之间的非线性依赖关系。最后给出了力学模型和简化模型的仿真结果。通过比较,证实了简化模型的动力学特性与机械模型的输出结果是一致的。
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引用次数: 2
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SNE Simulation Notes Europe
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