Dynamic stress response and fatigue life of cantilever beam under non-Gaussian base excitation

The stress response of cantilever beam to non-Gaussian random base excitation is investigated based on Monte-Carlo simulation. First, the statistical properties and spectral characteristics of non-Gaussian random vibrations are analyzed qualitatively; and the conclusion is that spectral method based on power spectrum density (PSD) is not applicable for non-Gaussian random vibrations. Second, the stress response formula of cantilever beam under non-Gaussian random base excitations is established in the time-domain, and the factors influencing the output kurtosis are subsequently determined. Two numerical examples representing different practical situations are analyzed in detail. The discrepancies of the stress responses to Gaussian, steady non-Gaussian and burst non-Gaussian base excitations are analyzed in terms of root mean square (RMS), kurtosis and fatigue damage. The transmissibility of RMS and high-kurtosis of steady non-Gaussian random base excitation is different from that of burst non-Gaussian case. Finally, the fatigue life corresponding to every base excitation is calculated using the rainflow method in conjunction with the Palmgren-Miner rule. Finite element analysis is also carried out for validation. The predicted fatigue lives corresponding to Gaussian, steady non-Gaussian and burst non-Gaussian base excitations are compared quantitatively. Finally, in the fatigue damage point of view, the discrepancies among the three kinds of random base excitations are summarized

A spectral method to estimate fatigue life under broadband non-Gaussian random vibration loading

The aim of this study is to propose a spectral method for assessing the fatigue lives of mechanical components under non-Gaussian random vibration loadings. Efforts are made to extend the Dirlik’s method to non-Gaussian vibration field by introducing the Gaussian mixture model. A symmetric non-Gaussian random vibration can be decomposed into a series of Gaussian components through Gaussian mixture model. Then the rainflow cycle distributions of the Gaussian components can be obtained using Dirlik’s method. The cycle distribution of the underlying non-Gaussian process is derived by compounding the distributions of Gaussian components together. The non-Gaussian cycle distribution, combined with Palmgren-Miner rule is used to predict the fatigue lives of specimens. Comparisons among the proposed method, Dirlik’s solution, nonlinear model in literature, and the experimental data, are carried out extensively. The results have confirmed good accuracy of the proposed method

Determination of Camellia oleifera Abel. Germplasm Resources of Genetic Diversity in China using ISSR Markers

Camellia oleifera is one of the four woody oil plants in the world, which is widely cultivated in South China. To examine the genetic diversity of C. oleifera in China, the diversity and genetic relationships among and within major populations of 109 varieties of C. oleifera were analyzed using ISSR markers. Twenty-three ISSR primers out of 49 primers yielded approximately 487 legible bands. A total of 335 of these bands were polymorphic markers, and the ratio of polymorphism was 68.86%. From the results, Zhejiang province showed the highest populations genetic diversity (H value 0.18), while Guangxi population showed the lowest genetic diversity (H 0.0851). Base on the bands, the genetic similarity coefficient ranged from 0.61 to 0.93 using NTSYS2.10e software. When coefficient was 0.75, 109 cultivars were divided into 11 categories and categories I contain 79 varieties by UPGMA cluster analysis. The test varieties divided into 7 sub-groups when categories were 0.75, which show a close genetic relationship. Results advised that Hunan is the main producing area of C. oleifera, with enriched C. oleifera variety and complex topography, and therefore has a high genetic diversity. Meanwhile, the main varieties of C. oleifera in Hubei are imported from Hunan, which results in fewer varieties and reduces the genetic diversity of C. oleifera. The ISSR profiles can improve C. oleifera germplasm management and provide potential determine correlations between different varieties and its distribution in different province

Formulation of locational marginal electricity-carbon price in power systems

Decarbonisation of power systems is essential for realising carbon neutrality, in which the economic cost caused by carbon is needed to be qualified. Based on the formulation of locational marginal price (LMP), this paper proposes a locational marginal electricity-carbon price (EC-LMP) model to reveal carbon-related costs caused by power consumers. A carbon-price-integrated optimal power flow (C-OPF) is then developed to maximise the economic efficiency of the power system considering the costs of electricity and carbon. Case studies are presented to demonstrate the new formulation and the results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy

Formulation of Locational Marginal Electricity-Carbon Price in Power Systems

Decarbonisation of power systems is essential for realising carbon neutrality, in which the economic cost caused by carbon is needed to be qualified. Based on the formulation of locational marginal price (LMP), this paper proposes a locational marginal electricity-carbon price (EC-LMP) model to reveal carbon-related costs caused by power consumers. A carbon-price-integrated optimal power flow (C-OPF) is then developed to maximise the economic efficiency of the power system considering the costs of electricity and carbon. Case studies are presented to demonstrate the new formulation and the results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy