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Optimization Of Self-repairing Structures And Microtuble Network Carrier Based On MMC And NSGA-Ⅱ

Posted on:2024-08-26Degree:MasterType:Thesis
Country:ChinaCandidate:C Y ZhangFull Text:PDF
GTID:2531307133993519Subject:Mechanics (Professional Degree)
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As a new type of intelligent material,self-repairing materials will eventually be made into various complex structures(i.e.,self-repairing structures),and the optimization of complex structures will inevitably lead to higher optimization time,Therefore,it is urgent to carry out research on microtubule network optimization with complex structures as the design domain,and to reduce the impact of structural complexity on the time cost of microtubule network topology optimization.Aiming at this problem,a stepwise optimization strategy of macro structure and micro tubular network carrier was adopted;The feasibility of the optimization method was verified by making samples and conducting mechanical experiments.The details were as follows:(1)Topology optimization of self-repair structures with built-in single-layer micropipe network carriers.Taking MBB beam as an example,the influence of structural complexity(number of components)on the calculation speed of topology optimization is verified by increasing the number of different components under the same design domain size and operating conditions based on MMC method,and the explicit expression of optimal macrostructure is obtained.Then,in order to ensure the flow efficiency of the repair agent and the mechanical properties of the self-repairing structure,the micro-pipe network carrier was implanted into the macro-structure as the design domain,and the head loss of the micro-pipe network carrier was solved as the objective function 1 based on Hardy-Cross iteration.The macro-structure flexibility of the micro-pipe network carrier was calculated as the objective function 2 based on the stiffness matrix and the total length of the micro-pipe network carrier as the objective function 3.NSGA-Ⅱ algorithm is used to obtain the non-inferior solution set based on the three objective function values.The research shows: 1)In the MMC method,with the increase of the number of components,the optimized macrostructure becomes more delicate and complex,the contour presented is smoother and the compliance value decreases;2)Compared with the macro structure without microtubular network,the mechanical properties of self-repairing structure with built-in single/double-layer carrier decreased to some extent within acceptable range;3)Under the same conditions,the mechanical properties of self-repairing structure of double-layer carrier are slightly worse than that of single-layer carrier,but generally,the head loss and pipe network length are better.(2)Experimental verification of self-repairing structures and topological optimization of micro-pipe network carrier.In order to prove the validity of the optimization results,MBB beam specimens without microtubular network and MBB beam specimens with built-in single-layer microtubular network were prepared respectively,and the experimental platform was designed and built.Mechanical test experiments were carried out on the two structures.The experimental results show that under the same load and constraints,the average strain of MBB beam without microtubular network is 3593.76,the average strain of MBB beam with built-in single-layer microtubular network is 3802.32,and the mechanical properties of MBB beam model with built-in single-layer microtubular network can reach94.5% of that without microtubular network.Compared to the flexibility 0.0248 of the MBB beam optimization results(see Table 2-2 for details),the flexibility 0.0255 of the built-in single-layer microtubule network MBB beam(see Section 2.7.2 for details)only decreased by 2.8%.Obviously,the experiment is in good agreement with the optimization results.It verifies the effectiveness of the optimization methods for self-repairing structures and their micro-pipe network carrier.
Keywords/Search Tags:Self-repair, Microtubule network carrier, Moving morphable components method, NSGA-Ⅱ
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