In order to improve the prediction accuracy of the photovoltaic power prediction model, this paper presents a novel forecasting model, which is the combination between Principal Component Analysis (PCA) and Support Vector Machine (SVM) intelligent algorithm. PCA statistical method used to extract less principal components instead of the original meteorological factor. Then that is as the input of the SVM model. The proposed prediction model verify its validity by the data of a roof grid-connected PV system located at Huazhong University of Science and Technology. The results show that the forecasting model can not only improve the prediction accuracy of the photovoltaic power output also reduce the computational model to meet real-time requirements for forecasting. The prediction of the accuracy is better than that of the currently used photovoltaic power forecast by comparing other model.

Failure characteristics of rocks under different loading and unloading conditions have been an important subject of laboratory tests. This study aims to investigate the influence of the height to diameter (H/D) ratio on the failure characteristics of marble specimens under unloading conditions. Conventional triaxial unloading (TU) tests were performed on marble specimens of 50 mm diameter with different H/D ratios from 0.5 to 3.0. Moreover, for comparison, uniaxial compression (UC) tests and conventional triaxial compression (TC) tests were conducted on marble specimens with different H/D ratios. The results indicate that the failure strengths of the specimens, including the UC strength, TC strength, and TU strength decrease with the increase in specimen height, and the decreasing trend can be fitted with a function that is deduced from Weibull's theory. The specimens with lower H/D ratios (0.5 and 1.0) underwent tensile failures in the TU tests, whereas the specimens with higher H/D ratios (2.0 and 3.0) showed shear failures in the TU tests. In addition, the analyses of strain energy evolutions indicate that the unloading failures of the specimens with lower H/D ratios are an ongoing process and the unloading failures of the specimens with higher H/D ratios present a sudden process.

Excavation unloading is a primary stress condition for engineering rock mass in deep underground. Based on the unloading stress condition during the excavation operation, this paper employed a distinct element method (DEM) to simulate the unloading responses of intact and preflawed rock specimens. The simulation results revealed that the unloading failure strength, unloading damage thresholds, and cracking characteristics were largely dependent on the inclination angle α of the preflaws. With the increase in the flaw inclination angle, the unloading failure strength of a preflawed specimen exhibited a sigmoidal curve increasing trend, and it decreased by 5.5%-20% compared to the unloading failure strength of an intact specimen. Based on the crack accumulation in specimens, three damage thresholds were identified under unloading condition and two damage thresholds σci and σdi were found to be increased with the increase in the flaw inclination angle. Furthermore, when the flaw inclination angle was smaller, cracks were initiated around the preflaws, and there were obvious axial splitting cracks in the failure modes of preflawed specimens, while axial splitting cracks were few in the preflawed specimen with a larger flaw inclination angle and none in the intact specimen. These unloading responses indicate that inducing preflaws can reliably reduce the unloading failure strength and promote the cracking process of hard rock during an excavation unloading process. Moreover, inducing preflaws with a smaller inclination angle (e.g., vertical to the unloading direction) will be more helpful for the unloading failure and rock cracking during an excavation unloading process.

Soil can be amended with cement, lime, fly ash and other curing agents after diesel contamination. In this study, a diesel-contaminated granite residual soil with an oil content of 9% was selected and amended with cement, lime and fly ash as curing agents and their incorporation levels were varied. A straight shear test showed that 6% lime resulted in the best improvement in the contaminated soil, with a cohesive force of 122.1 kPa and an internal friction angle of 27.1°. A disintegration test revealed that the disintegration resistance of the contaminated soil was improved by 6% cement, 20% fly ash and 10% lime, with 10% lime being the most effective. SEM tests revealed that diesel fuel acted as a constant pore fluid to cause significant fragmentation and separation of the granite residual soil from flakes and blocks to smaller agglomerates and fragments. The curing agent, by increasing the physical reaction products, causes the particles to agglomerate, filling the soil pores and enhancing the integrity of the soil, thus improving the soil properties.