## 1 Introduction  
Design of lightweight structures, which have both low mass and good mechanical properties, became a crucial part of the mechanical design process. It is achieved not only by using advanced lightweight materials, but mainly by using the advanced design process. The leading industrial approach is the use of structural optimization to design both the stiffest and lightweight design. Combined with Additive Manufacturing techniques [1; 2; 3], structural optimization is an excellent method for achieving solutions greatly exceeding what is possible to create using traditional techniques of design and manufacturing. Structural optimization software, by design, is based on the structural analysis numerical methods. Those methods, with the Finite Elements Method as the dominant approach, require discretization of the analyzed area. This leads to discretized results of structural optimization--a surface or volumetric finite element mesh. Additive manufacturing production methods may reduce the post-processing of structural optimization results to the mesh surface smoothing only. In many practical cases, in particular when after optimization further design requires a parametric model, there is a need for transferring structural optimization results to the CAD system. This requires building a parametric model. This paper describes the approach of building CAD parametric models using cylindrical structural elements--the result is truss. The entry point for the presented approach is an output mesh obtained by optimization performed using the biometric approach to structural optimization [4; 5; 6] which utilizes a new paradigm of ultralight constructions considering material properties and enables solving optimization problems for multiple load scenarios. The presented features recognition algorithm works properly for truss structures appearing in a broad variety of structural optimization results. The algorithm is based on the skeletonization of a mesh directly obtained from the biomimetic structural optimization system. The skeleton is used to determine the topology of the initial solution, which is refined using a heuristic optimization approach. The final solution is transformed into a parametric model, which can be imported into the CAD system. An important feature of the presented approach is a fully automated method of operation. The proper operation of the reconstruction algorithm is proved using typical topology optimization problems, which are well described in the literature. Detailed analysis is performed using two case studies. First is an optimized cantilever bar and second is an industrial application--the optimization of a box corner. For both case studies, structural analysis was performed and the results are discussed. The approach is validated and future directions of research are proposed. The efficiency of the algorithm is demonstrated in the second case study--the industrial use of biomimetic optimization in the BioniAMoto project. The aim of the BioniAMoto project is to develop a cost-effective method for manufacturing lightweight and efficient structural nodes for the automotive industry using additive manufacturing (AM) technologies and structural optimization. The project aims to create a new concept for manufacturing 3D structural nodes for vehicle frames using topology-optimized aluminum alloys that are joined together with readily available and commonly used extruded profiles. One of the parts manufactured as a part of the project is an aluminum box corner used in truck cars. The use of the presented approach enables the conversion of the results of the structural optimization to the parametric model, which simplifies the post-processing steps required to prepare the model for the manufacturing process. Two additive manufacturing processes are considered. The direct method, Laser Metal Powder Bed Fusion (LM-PBF) technology, uses a laser beam to fuse metal powder.