Design optimization of a newly developed aluminum-steel multi-material electric bus body structure

Fu, Chuanliang; Bai, Yuchen; Lin, Cheng; Wang, W. W.

doi:10.1007/s00158-019-02292-w

Cited by 19 publications

(8 citation statements)

References 27 publications

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“…What motivates this research is to reproduce such failure by performing testings in a laboratory." Using computational analysis in recent research, the most loaded structural details in bus structures have been identified [6], which show coincidence with the failure prone critical points studied in this research.…”

Section: Methodssupporting

confidence: 64%

Experimental Analysis of a Bus Structure Section

Cruz¹,

Rabiela²,

González³

et al. 2021

IRJIET

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The objective of this research work is to reproduce in a test specimen, the fatigue failure that occurs in a damaged section of a structure. There is a structural problem, that is, the presence of a fracture at a certain point in the structure of the bus, starting at this point and growing progressively, causing damage. The steps of a methodology were applied to physically reproduce the fatigue failure in a representative specimen of a section of the bus structure, where the failure is located and up to the instrumentation of the testing machine and performance of the fatigue test. Subsequently, the results are analyzed and conclusions are made based on the results obtained in the laboratory test.

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Section: Methodssupporting

confidence: 64%

Experimental Analysis of a Bus Structure Section

Cruz¹,

Rabiela²,

González³

et al. 2021

IRJIET

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show abstract

“…Some uncertain factors, such as the processing error of the sensor split and the assembly error between the sensor splits, are inevitable to encounter during the execution of the actual rotor blade wind tunnel test project. Without considering the influence of these uncertain factors in the deterministic optimization of the sensor split, the optimization result may present lower reliability or robustness and greater technical risks in practice [16,17].…”

Section: Robustness Analysis and Optimizationmentioning

confidence: 99%

Multiobjective Optimization of Structure and Robustness of a Split Parallel Multicomponent Strain Sensor

Kong

Peng

Lian

2022

Wireless Communications and Mobile Computing

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A novel split parallel multicomponent strain sensor structure layout is proposed based on the special requirements of the helicopter rotor airfoil wind tunnel test for measuring aerodynamic sensors. The sensor consists of two splits with the same configuration; the performance of the sensor not only depends on the split structure of the sensor but also depends on the assembly relationship between the splits. Three steps have been performed so as to enhance the technical performance of the sensor. First, the RBF neural network approximate model and the second-generation nondominated sorting genetic algorithm are used to optimize the split of sensor deterministically; secondly, the rotor airfoil wind tunnel test model and the sensor finite element system model are established, and the 6 σ robustness analysis is carried out; finally, the 6 σ robust multiobjective optimization has been carried out considering the sensor split processing errors and the assembly errors. The results show that, compared to initial designed sensors, the sensitivity of the three components of the sensor is increased by 285.46%, 284.95%, and 151.5%, respectively, and the maximum equivalent stress is reduced by 28.4%; the interference to the three components is reduced by 97.82%, 92.83%, and 99.8%, respectively, and the quality is reduced by 25.74%. Meanwhile, the quality level of the sensor was promoted, and the sensitivity of the response to assembly and manufacturing errors were reduced. These results exhibit that the structural layout, optimized path, and method in this strain sensor are suitable for the needs of helicopter rotor airfoil wind tunnel test.

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“…Multi-material automobile designs have been proposed as a strategy to improve fuel efficiency and, therefore, significantly reduce CO 2 emissions. Among light materials, which include Mg alloys and carbon fiber-reinforced plastics (CFRPs), the lower cost, better moldability, and higher specific strength of Al alloys make them the most promising material for the Al alloy/steel-based design of multi-material automobiles 1,2) . However, to implement the widespread use of multi-material automobiles, several technical issues need to be addressed, such as the challenges of joining dissimilar materials 3,4) , lack of life cycle assessments of multi-material structures for recycling 5,6) , and galvanic corrosion between dissimilar materials [7][8][9][10][11][12] .…”

Section: Introductionmentioning

confidence: 99%

Role of KMnO<sub>4</sub>–NaF Treatment in Galvanic Corrosion Resistance of AA5083 Coupled to Steel

et al. 2023

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The role of KMnO 4 -NaF conversion treatment in the galvanic corrosion resistance of AA5083 aluminum alloy coupled to AISI 1045 carbon steel in synthetic seawater (diluted 100 times) was investigated. The 10 min-treated AA5083 was observed to reduce the period of high current density during the early stage of coupling and decrease the number of localized corrosion damages on the AA5083. The 10 min conversion treatment significantly reduced the electrode potential of bulk Al 6 (Fe, Mn), and it was concluded that the Al 6 (Fe, Mn) particles on the conversion-treated AA5083 no longer acted as a local cathode at the electrode potential when the AA5083 was in contact with AISI 1045 carbon steel. The decrease in cathodic activity of Al 6 (Fe, Mn) was attributed to the removal of Fe from the surface film of Al 6 (Fe, Mn), addition of Mn by the conversion treatment, and thickening of the film.

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Design optimization of a newly developed aluminum-steel multi-material electric bus body structure

Cited by 19 publications

References 27 publications

Experimental Analysis of a Bus Structure Section

Experimental Analysis of a Bus Structure Section

Multiobjective Optimization of Structure and Robustness of a Split Parallel Multicomponent Strain Sensor

Role of KMnO<sub>4</sub>–NaF Treatment in Galvanic Corrosion Resistance of AA5083 Coupled to Steel

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