## 1 Introduction  
The discrete element method (DEM) was first introduced by [PERSON] in 1971 [1]. Since this time, the DEM has been widely applied in fields, such as mining and geotechnical engineering [2; 3; 4; 5; 6; 7; 8; 9]. Particle flow code (PFC) is one of the widely used particle DEMs. The PFC is convenient for dealing with problems in non-continuous media and can effectively simulate non-continuous phenomena (e.g., cracking, media separation), which has greatly aided research into the damage, fracture evolution, and failure mechanism of rocks [10; 11; 12; 13; 14]. The first step in a PFC simulation is to select rational micro-parameters according to the material macro-responses. The accuracy of the simulation results depends on the selection of micro-parameters [15; 16]. Many studies have explored the relationship between micro- and macro-parameters and achieved substantial success. [PERSON] and [PERSON] [17] analyzed the sensitivity of the results of biaxial, triaxial, and Brazilian splitting tests of the PFC model to micro-parameters. [PERSON] et al. [18; 19] proposed the calibration and optimization method of PFC micro-parameters based on the design of experiments method. [PERSON] et al. [20; 21] analyzed the quantitative relationship between the macro-properties and micro-parameters of the calculation model by using a two-dimensional particle flow code (PFC2D) parallel-bond model. [PERSON] [22] combined the triaxial loading and unloading test of marble to study the micro-parameters applicable to the mechanical analysis of rock materials. [PERSON] et al. [23; 24; 25] established a two-dimensional discrete element model, which could reflect the mineral components of rocks, and studied the influence of mineral components and microdamage distribution on the macro-properties of rocks. [PERSON] et al. [26; 27] studied the influence of model scale and particle size distribution on PFC simulation results. However, most of these studies are based on PFC2D, and few are based on a three-dimensional particle flow code (PFC3D). Substantial differences have been shown to exist between PFC2D and PFC3D simulation results [17; 20; 27; 28; 29]. Additionally, plane strain and plane stress conditions can be applied to a wide variety of applications [30; 31; 32; 33], but some engineering and experiment problems in the field cannot be simplified into plane stress or plane strain problems [19; 26; 34; 35]. The research on the relationship between macro-properties and micro-parameters generally only considers the relationship between macro-properties and a single micro-parameter, while the research on the influence of multi-parameter coupling on macro-properties is insufficient. However, limited research shows that the coupling of multiple parameters has a more significant impact on the macro characteristics of the model [21; 36]. In the PFC bond model, the contact-bond model (CBM) and parallel-bond model (PBM) are widely used. CBM can be regarded as a spring with certain normal and shear stiffness, which binds the particle element at the contact. PBM can be regarded as a series of springs with normal and shear stiffness, which are evenly distributed on a certain width of the contact surface and can resist the action of force and moment at the same time [19; 37]. In PBM, the bond failure will immediately reduce the macro-stiffness, which is more in line with the brittle failure characteristics of rock [10; 19; 37]. Therefore, PBM is selected to simulate the mechanical behavior of hard rock in the process of failure. In this study, the parallel-bond model in PFC was applied to investigate the effects and effect mechanisms of bond normal strength, shear strength, and stiffness ratio on the macro-properties of the PFC3D model of rocks. Section 2 briefly reviews the relationships between micro-parameters and macro-properties in the parallel-bond model. Section 3 describes the test scheme, Section 4 presents the test results, and the key problems found in this study are discussed in Section 5.