[PERSON] and [PERSON] [16] proposed a boundary search method for pressure loading for the first time, and they obtained loading surfaces by identifying equal-density nodes. [PERSON] and [PERSON] [17] improved their method by representing loading surfaces with straight-line segments instead of a B-spline, which made the loading surface identification process more robust. [PERSON] et al. [18] proposed a direct element loading method that uses a density threshold to classify boundary elements. In their method, the load was directly applied to the finite element boundary. The advantage of this method was that it was easy to implement, and load sensitivity analysis could be easily avoided. In addition, when using the above method for boundary search, it is necessary to determine the endpoint of the loading surface before optimization, which does not apply to the design of asymmetric structures under internal pressure. To solve this issue, [PERSON] and [PERSON] [19] introduced a void region to apply pressure, avoiding the pre-definition of endpoints. In addition, [PERSON]'s work analytically deduced the sensitivity of the load. Recently, many researchers have solved mechanical problems through image processing [20; 21]. In 2015, [PERSON] and [PERSON] [22] adopted an image segmentation technique based on Distance Regularized Level Set Evolution [23] (DRLSE: Distance Regularized Level Set Evolution) for boundary recognition, and they successfully applied this method to the design of an underwater pressure hull. In 2018, [PERSON] et al. [24] proposed a simple algorithm based on digital image processing and area contour tracking technology that could generate suitable loading surfaces in the process of topology evolution. Since the endpoints of the loading boundary were determined semi-automatically, the scheme could handle both the loading from outside the domain and the pressure completely contained within the domain while avoiding the calculation of the load sensitivity. The second category involves tracking changes in pressure loads by constructing multi-physics models. [PERSON] and [PERSON] [25], as well as [PERSON] and [PERSON] [26], applied a fluid-solid-void model to identify a loading surface. [PERSON] and [PERSON] [27] suggested that a hybrid finite element could be used to simulate incompressible fluid structural regions. Some scholars have used the evolutionary structure method to study topology optimization problems with design-dependent loads. In 2014, [PERSON] et al. [28; 29] extended the Bidirectional Evolutionary Structural Optimization (BESO) method using binary {0,1} design variables to solve design-dependent loads, acoustics, and fluid-structure coupling problems. In 2018, [PERSON] and [PERSON] [30] invented a binary structure topology optimization method using design variables 0 and 1 and integer mathematical programming, and they used this method to solve the fluid pressure load problem. The binary structure topology optimization method does not have the problem of blurred boundaries, which is its advantage over the SIMP method. Some scholars have also studied the loading surface search algorithm using the level set method. [PERSON] and [PERSON] [31] and [PERSON] and [PERSON] [32] used level set evolution technology to propose a search method for designing the boundary of a load. When appropriating mathematical transformation, it is convenient to deal with the design-dependent loads imposed on the structure, avoiding tedious boundary extraction work in the density method. In 2015, [PERSON] et al. [33] used two-level set functions to represent the free boundary and pressure. In 2018, [PERSON] et al. [34] adopted the level set method based on the reaction-diffusion equation to mark the pressure load boundary by tracking the level set function of the pressure load boundary. In 2019, based on the level-set method, [PERSON] et al. [35] adopted the Laplace equation to solve the pressure field of a fluid. Recently, [PERSON] [36] used [PERSON]'s law in rock mechanics to deal with design-dependent loads.