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A novel conductive heating method using solar energy for soil remediation was introduced in this work. Contaminated industrial heritage sites will affect the sustainable development of the local ecological environment and the surrounding air environment, and frequent exposure will have a negative impact on human health. Soil thermal desorption is an effective means to repair contaminated soil, but thermal desorption is accompanied by a large amount of energy consumption and secondary pollution. Therefore, a trough solar heat collection desorption system (TSHCDS) is proposed, which is applied to soil thermal desorption technology. The effects of different water inlet temperature, water inlet velocity and soil porosity on the evolution of soil temperature field were discussed. The temperature field of contaminated soil can be numerically simulated, and a small experimental platform is built to verify the accuracy of the numerical model for simulation research. It is concluded that the heating effect is the best when the water entry temperature is the highest, at 70 °C, and the temperature of test point 4 is increased by 50.71% and 1.42%, respectively. When the inlet water flow rate is increased from 0.1 m/s to 0.2 m/s, the heating effect is significantly improved; when the inlet water flow rate is increased from 0.5 m/s to 1.5 m/s, the heating effect is not significantly improved. Therefore, when the flow rate is greater than a certain value, the heating effect is not significantly improved. The simulation analysis of soil with different porosity shows that larger porosity will affect the thermal diffusivity, which will make the heat transfer effect worse and reduce the heating effect. The effects of soil temperature distribution on the removal of petroleum hydrocarbon C6–C9 and trichloroethylene (TCE) were studied. The results showed that in the thermal desorption process of petroleum hydrocarbon C6–C9-contaminated soil, the removal rate of pollutants increased significantly when the average soil temperature reached 80 °C. In the thermal desorption of trichloroethylene-contaminated soil, when the thermal desorption begins, the soil temperature rises rapidly and reaches the target temperature, and a large number of pollutants are removed. At the end of thermal desorption, the removal of both types of pollutants reached the target repair value. This study provides a new feasible method for soil thermal desorption. [ABSTRACT FROM AUTHOR]

Progressive collapse is a phenomenon where initial local failure of a component spreads to surrounding components, resulting in the collapse of the entire structure or most of it. This research is based on the component method (joint simplification model) and the hierarchical shell element macromodeling approach (composite floor simplification model). A three-dimensional spatial composite structural model was established using the finite-element (FE) software ANSYS/LS-DYNA. Experimental results were used to validate the reliability of the FE model. Based on these methods, a typical prototype structural model designed by the National Institute of Standards and Technology (NIST) was established, and a computational analysis of progressive collapse due to component removal was conducted. The results showed that the occurrence of structural collapse depends on the type of beam-column connection, floor level, and type of component removed. Also, it was found that structural collapse is more likely to occur when interior columns, gravity columns (nonresisting lateral column), and low-floor columns are removed. After column failure, the path of vertical loads is mainly transmitted to the columns within the area of direct collapse effect. The area within the potential collapse effect is also exposed to a severe impact phenomenon due to falling floors. Based on the collapse modes and internal force transfer path, an innovative collapse-prevention design method (structural response-based design, or SRBD) is proposed. The SRBD method predicts the collapse response of structure at a theoretical level and avoids redundant modeling and nonlinear calculations in collapse-prevention design. A comparison with collapse response of the NIST model shows that the prediction accuracy is approximately 90%. The SRBD method provides guidance for structural engineers in progressive collapse-prevention design. [ABSTRACT FROM AUTHOR]