Dukui Zheng¹, Jingfa Li^1,*, Bo Yu¹, Zhiqiang Huang¹, Yindi Zhang¹, Cuiwei Liu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.011669

Abstract In the low and medium pressure urban gas pipe network, transporting the hydrogen-blended natural gas through polyethylene pipe is an important means to realize the large-scale delivery and utilization of hydrogen-blended natural gas. However, due to the characteristics of polymer material, polyethylene pipes will experience aging phenomenon, which will lead to the deterioration of performance and eventually result in brittle damage and failure. Therefore, it is of great significance to analyze and predict the lifetime of polyethylene pipe due to the aging in the hydrogen-blended natural gas environment to ensure the safe transportation. In this… More >

Borui Yang¹, Jun Luo², Bo Wan^1,*, Yutai Su^1,3, Guicui Fu¹, Xu Long^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1113-1134, 2022, DOI:10.32604/cmes.2022.018037 - 13 December 2021

Abstract A thermal fatigue lifetime prediction model of ceramic ball grid array (CBGA) packages is proposed based on the Darveaux model. A finite element model of the CBGA packages is established, and the Anand model is used to describe the viscoplasticity of the CBGA solder. The average viscoplastic strain energy density increment ΔWave of the CBGA packages is obtained using a finite element simulation, and the influence of different structural parameters on the ΔWave is analyzed. A simplified analytical model of the ΔWave is established using the simulation data. The thermal fatigue lifetime of CBGA packages More >

Muhammad Haris^1,*, Muhammad Noman Hasan¹ , Abdul Basit², Shiyin Qin¹

Journal of Quantum Computing, Vol.3, No.3, pp. 89-95, 2021, DOI:10.32604/jqc.2021.016390 - 21 December 2021

Abstract This article presents a multilayer hybrid classical-quantum classifier for predicting the lifetime of LiFePO4 batteries using early degradation data. The multilayer approach uses multiple variational quantum circuits in cascade, which allows more parameters to be used as weights in a single run hence increasing accuracy and provides faster cost function convergence for the optimizer. The proposed classifier predicts with an accuracy of 92.8% using data of the first four cycles. The effectiveness of the hybrid classifier is also presented by validating the performance using untrained data with an accuracy of 84%. We also demonstrate More >