## 1 Introduction
Although initially defined, many researchers do have their own understandings for lattice structure, based upon the definition by [PERSON] and [PERSON], as lattice structure does not rely completely on the dimensions and connecting style of the struts and nodes. In general, lattice structure is defined as being composed of interconnected cells, arranged in a repeated manner, to build a three dimensional structure, whereas the cells are an assembly of struts and nodes [20; 21; 22; 23]. Based upon the placement pattern of unit cells in three dimensional Euclidean space, lattice structures are divided into three categories [24]:  
Figure 1: Process Schematic diagram for FDM Process. 1. Disordered lattice structure: The distribution of unit cells within the defined space do not follow any pattern, and is arbitrary and unplanned, as shown by Figure 2a. 2. Periodic lattice structure: Here, the distribution of unit cells is repeated periodically, having the same topology, geometry, and size, as shown in Figure 2b. 3. Pseudo-periodic lattice structure: Also known as conformal lattice structure, as depicted in Figure 2c, each unit cell holds the same topology with variations in shape and size. Modeling of cellular lattice structure depends on traditional approaches related to surfaces: boundary representation and voxels (discrete volume representation). It is observed that these approaches are successful, up to some extent, and limited by design complexities of regular cellular lattice structure. The problems intensify further when modeling irregular cellular lattice structure. For such cases, each representation requires time to render the object and larger processing power, which mostly exceeds the processing power of computing machines. Qualitative problems are related to precision, operability, and manufacturability. Surface generated through boundary and voxel representation are problematic to manufacture due to defects (cracks, self-intersection, false and residual polygons) created during modeling, which produces an approximate instead of an exact geometry. Both representations are not supported for parametrization. If parameters are changed, the user needs to regenerate using a high-level procedure [25]. Most of the associated problems of the traditional approach to modeling, as stated above, are addressed by the function-based approach. Some recent research claims that implicit functions are markedly suitable for porous as well, as it can successfully be used for geometric modelling of objects, including cellular lattice structure [25; 26; 27; 28]. To investigate properties of cellular lattice structure, several different geometries of unit cells are used by researchers to construct them. [PERSON] et al. utilized a unit truss with five strut members to generate an octet truss conformal cellular lattice structure [29; 30]. A complete design and experimental analysis study were conducted by [PERSON] for cellular lattice structure [31]. Three different types of structures: square pyramidal, tetrahedral, and kagome sourced structure are produced and tested for compressive and flexural strengths. The experimental results were analyzed and compared with the corresponding strengths of the solid structure, which shows the strengths are close to the solid structure. The research findings from [PERSON] triggered researchers to investigate the potential of truss lattice structures and surface network structures, in compression, to extend their application areas. The study performed by [PERSON] et al. compares network structures based on truss-lattices and periodic surfaces. The structures were designed and analyzed by Finite element software Abaqus, and the findings show the periodic surface networks are much stiffer than truss lattice structures [32]. Several lattice structures are generated through periodic octet cell, including Octet, Cross, FrameCross, InsideCross, and OctetFramed to measure their performance in compression [21]. Experimental study, by [PERSON] et al. and [PERSON] et al.