## 3 Results
### Analysis of Thin-Walled Tubular Structures  
For a more accurate and complete characterization of the TWB thin-walled structure's behaviour, the effect of these geometries on designs made of homogeneous steel sheets was analysed. The thin-walled tubular structures used for the analyses had optimized U parts. Figure 10 presents the cross-section of the U parts and the geometry of the resulted tubular structure. The thin-walled tubular structures made of homogeneous steel sheets had a specific height of 200 mm and are shown in Figure 11. To construct these tubular structures, gluing with an adhesive solution with modified polymers was used. To analyse the crashing behaviour and the parameters regarding the energy absorption developed at impact, axial crushing tests were performed. Figure 11: Thin-walled tubular structures made of homogeneous steel sheets and TWB. Figure 10: Cross-section of individual U parts and geometry of the tubular structures. Figure 9: Equipment used for experimental testing on dynamic impact load applications. Use of Genetic Algorithms to Improve the Behavior of TWB Tubular Structures at Dynamic Impact Loading  
A Genetic Algorithm is an iterative global searching procedure to optimize the evaluation function. The algorithm works parallel on a population of potential solutions (chromosomes) distributed throughout the search space. Typically, the performance value of a chromosome is independent of the performance of other individuals in the population. Another possibility is to consider a function of implicit adequacy, whose values also depend on the rest of the population through specific interactions between individuals. It refers to an intrinsic adaptation that ensures the co-evolution of individuals [24; 25; 26]. A new population is created at each iteration of the algorithm, called a generation, with all generations the same number of individuals. It is accepted that, in general, the new generation is made up of better performing individuals, better adapted to the environment represented by the adequacy function. With the succession of generations, individuals will tend to evolve towards the global optimum of the adequacy function. Achieving a new generation, starting from the previous one, takes place in the following stages [27; 28]:  
* Evaluation is when the Genetic Algorithm calculates the value of the adequacy function for each individual of the old population. * Selection is when the Genetic Algorithm selects individuals from a population-based on their performance. The chosen individuals will represent an intermediate population. Thus, the chromosomes of the intermediate population become the parents of the new generation. * Recombination and modification: the Genetic Algorithm recombines and modifies selected individuals. For this purpose, the operators' genetics of crossbreeding (re-combination), mutation, and inversion are used. From an algorithmic point of view, genetic operators are methods of locally changing the solutions represented by the parents (conversion or inversion) or combining these solutions (crossover) by a gene transfer between two chromosomes. The technique used to estimate the optimal amount of material needed to construct TWB tubular structures is based on the principles of Genetic Algorithms. Also, the OPTIMIZATION TOOL software module within the MATLAB 9.12.0 R2022a software (The MathWorks, Inc., Natick, MA, USA) platform was used to run the steps necessary for the optimization with Genetic Algorithms in the best possible conditions. The analysis of the experimental results established the factors that decisively influence the behaviour of TWB tubular structures subjected to dynamic impact loadings. These factors are the energy absorbed \(\mathrm{E_{a}}\) and the absorption of specific energy \(\mathrm{A_{es}}\) (which must have the highest values) and stroke efficiency \(\mathrm{E_{cd}}\) (which must have average values characteristic of the strain level accepted for the structure in question).