M.A. Waheed^a, C.A. Komolafe^b,*

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-7, 2019, DOI:10.5098/hmt.12.8

Abstract The drying kinetics of three varieties of cocoa beans (N38, F and WA) at 40, 50 and 60 degree centigrade was investigated experimentally. The three different varieties were dried using laboratory air oven UF Memmert and the moisture content determined according to AOAC standards. The results show that drying processes occur mainly in the range of the falling-rate period and the drying rates were observed to be faster at higher drying temperature. The effective diffusivities of the three cocoa beans varieties determined at 40, 50 and 60 degree centigrade ranged between 9.9269 x 10^-11 and 4.4671 More >

Haiyang Zhang^1,*, Qian He¹, Xiaoning Lu¹, A. Pizzi^2,3, Changtong Mei¹, Xianxu Zhan⁴

Journal of Renewable Materials, Vol.6, No.5, pp. 450-456, 2018, DOI:10.7569/JRM.2017.634180

Abstract Double cantilever beam tests were used to measure the energy release rates of linear vibrational welded moso bamboo joints. The influence of the length of the preserved cracks, the different combinations of the inner and outer bamboo surfaces and the moisture content is studied herein. The experimental compliance method, which is based on linear elastic fracture mechanics and has been shown to be an ideal method, was used to analyze data with the power equation. The results show that the preserved initial crack length does not have a significant effect on the final measured energy More >

Shurong Li^1,*, Yulei Ge², Renlin Zang²

CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.1, pp. 95-116, 2018, DOI:10.3970/cmes.2018.114.095

Abstract In this paper, an interacting multiple-model (IMM) method based on data-driven identification model is proposed for the prediction of nonlinear dynamic systems. Firstly, two basic models are selected as combination components due to their proved effectiveness. One is Gaussian process (GP) model, which can provide the predictive variance of the predicted output and only has several optimizing parameters. The other is regularized extreme learning machine (RELM) model, which can improve the over-fitting problem resulted by empirical risk minimization principle and enhances the overall generalization performance. Then both of the models are updated continually using meaningful… More >