Eng

Flexible photovoltaic (PV) support systems, referring to cable-supported structural systems that carry conventional rigid PV modules rather than flexible thin-film modules, have attracted increasing attention as a promising solution for photovoltaic construction in complex terrains due to their advantages of broad-span design and simplified installation. However, the deformation behavior of flexible PV supports remains insufficiently understood, which restricts its application and engineering optimization. To address this issue, a three-dimensional finite element model of a flexible PV support system was developed using an in-house Python code to investigate its deformation characteristics. The model discretizes the structure into beam and cable elements according to their mechanical properties, and the coupling relationship between their degrees of freedom is established by means of a multi-point constraint. The validation of the proposed model is confirmed by comparison with theoretical solutions. Simulation results reveal that the deformation of flexible PV supports is more sensitive to horizontal loads, indicating that their overall deformation performance is primarily governed by lateral rather than vertical loading. Furthermore, dynamic analyses show that higher loading frequencies induce noticeable torsional de-formation of the structure, which may compromise the stability of the PV panels. These findings provide valuable theoretical guidance for the design and optimization of flexible PV support systems deployed in complex terrains.

Understanding the flow characteristics of tight sandstone reservoirs is crucial for improving resource recovery efficiency. During fluid flow in porous media, surfactant components in the fluid can adsorb onto solid surfaces, forming a boundary layer. This boundary layer has a pronounced impact on fluid movement within tight sandstone formations. In this study, digital core analysis is employed to investigate how the boundary layer influences non-Darcy flow behavior. A computational model is first developed to quantify the thickness and viscosity of the boundary layer, followed by the construction of a mathematical flow model based on the Navier–Stokes equations that incorporates boundary layer effects. Using CT scan data from actual core samples, a pore network model is then built to represent the reservoir’s complex pore structure. The impact of boundary layer development on microscale flow is subsequently analyzed under varying pore conditions. The results indicate that both boundary layer thickness and viscosity significantly influence fluid transport in microscopic pores. When the relative boundary layer thickness is 0.5, and the relative viscosity reaches 10, the actual outlet flow rate drops to only 12.89% of the value obtained without considering boundary layer effects. Furthermore, in tight reservoirs with smaller pore throat sizes, the boundary layer introduces considerable flow resistance. When boundary layer effects are incorporated into the pore network model, permeability initially increases with pressure gradient and then stabilizes.

The present research demonstrates the utility of the linear canonical transform (LCT) in constructing the characteristic function of real random variables. We refer to this construction as the linear canonical characteristic function (LCCF). The proposed LCCF aims to address the limitations of the classical characteristic function in both theoretical and applied aspects. Using this approach, we investigate its properties, such as Hermitian symmetry, continuity, convolution, and derivatives, which are generalized forms of the classical characteristic function in the literature. Finally, we implement the obtained results by calculating several probability density functions in the LCCF domains.