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A multi-objective optimization of methylcyclohexane dehydrogenation via microwave-enhanced process: 3D multiphysics simulation and response surface methodology

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 112卷 322-332页

作者： Sun, Jianchen Shang, Hui Fan, Xiayu Li, Keying Li, Jun China Univ Petr State Key Lab Heavy Oil Proc Beijing 102249 Peoples R China Petrochina Planning & Engn Inst Zhixin West Rd 3 Beijing 100083 Peoples R China

Microwave enhancement technology has been explored to improve methylcyclohexane (MCH) dehydrogenation. However, comprehensive studies on multiphysics coupling and parameter optimization of these systems remain limited. In this paper, a 3D multiphysics coupling model, integrating chemical reactions, heat transfer, electromagnetic waves, and porous media flow, was developed using COMSOL multiphysics to study MCH dehydrogenation. Response Surface Methodology (RSM) and Box-Behnken Design (BBD) were used to analyze the influence of parameters and optimize the operating conditions. The results showed that the conversion rate of microwave heating was nearly 70% higher than that of conventional heating, and the feed rate and temperature had the greatest influence on the conversion rate. Under the optimal conditions (623 K, 0.1 bar, carrier-gas ratio 1, feed rate 0.173 g/min), the conversion rate was 86.3%, and the hydrogen production rate was 1820 mmol/gPt/ min. This study provides a theoretical basis for the development of efficient microwave enhanced MCH dehydrogenation reactor.

关键词： Microwave-enhanced Methylcyclohexane dehydrogenation Response surface methodology multiphysics simulation model Multi-objective optimization

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Automated generation of multiphysics simulation models to support multidisciplinary design optimization

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ADVANCED ENGINEERING INFORMATICS 2015年第4期29卷 1110-1125页

作者： Tian, Fengnian Voskuijl, Mark Delft Univ Technol Fac Aerosp Engn Delft Netherlands

To ensure a consistent design representation for serving multidisciplinary analysis, this research study proposes an intelligent modeling system to automatically generate multiphysics simulation models to support multidisciplinary design optimization processes by using a knowledge based engineering approach. A key element of this system is a multiphysics information model (MIM), which integrates the design and simulation knowledge from multiple engineering domains. The intelligent modeling system defines classes with attributes to represent various aspects of physical entities. Moreover, it uses functions to capture the non-physical information, such as control architecture, simulation test maneuvers and simulation procedures. The challenge of system coupling and the interactions among the disciplines are taken into account during the process of knowledge acquisition. Depending on the domain requirements, the intelligent modeling system extracts the required knowledge from the MIM and uses this first to instantiate submodels and second to construct the multiphysics simulation model by combining all submodels. The objective of this research is to reduce the time and effort for modeling complex systems and to provide a consistent and concurrent design environment to support multidisciplinary design optimization. The development of an unstable and unmanned aerial vehicle, a multirotor UAV, is selected as test case. The intelligent modeling system is demonstrated by modeling thirty-thousand multirotor UAV designs with different topologies and by ensuring the automatic development of a consistent control system dedicated for each individual design. Moreover, the resulting multiphysics simulation model of the multirotor UAV is validated by comparing with the flight data of an actual quadrotor UAV. The results show that the multiphysics simulation model matches test data well and indicate that high fidelity models can be generated with the automatic model generation proces

关键词： multiphysics simulation model Knowledge based engineering Multidisciplinary design optimization Multirotor UAV

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Mechatronic Design and Optimization Using Knowledge-Based Engineering Applied to an Inherently Unstable and Unmanned Aerial Vehicle

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2016年第1期21卷 542-554页

作者： Tian, Fengnian Voskuijl, Mark Delft Univ Technol Fac Aerosp Engn NL-2629 HS Delft Netherlands

A novel design method for mechatronic systems, based on knowledge-based engineering techniques, is proposed in this research study. The method is particularly suited for mechatronic vehicles which are inherently unstable and require control systems for stabilization. The method is implemented in a dedicated software tool in which physical entities of the product are defined as classes with attributes. Nonphysical elements of the system and procedures for the design and analysis of the system are defined as functions with variables. The method has two key features. First, multiphysics simulation models and associated analysis functions are generated automatically within a multidisciplinary analysis and optimization framework. These models are not restricted to geometrical aspects for mechanical design, but also include the system architecture, dynamics, aerodynamics, electronic control systems and associated software codes. Second, for each representation of a design, a dedicated control system is developed completely automatically, based on the multiphysics simulation model, using model inversion control. These two features make it possible to analyze the dynamics and performance of inherently unstable mechatronic vehicles already in the early design phases when the vehicle is still subject to large configuration design changes. The method is demonstrated for the design of a multirotor unmanned aerial vehicle. Thirty thousand possible design solutions are evaluated by the system without manual interference. For each design, a dedicated control system is created and five flight test maneuvers are simulated in order to assess the aircraft performance and flying qualities. A global optimization process is applied for two conflicting requirements and the process is convergent at two optimum solutions.

关键词： Electronic control system knowledge-based engineering mechatronics multiphysics simulation model unmanned aerial vehicle

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