Along with the advantages provided by the material and ease of assembly/disassembly, the ease of repair provided by minimum deformation after a collision and its sustainability highlight the preference of concrete barriers for roadside safety. However, concrete barriers, as rigid systems, are highly risky in case of a collision. Because the top priority of the application purpose is safety, it is desirable to have designs that provide the necessary safety criteria in the relevant standards and which are highly safe in terms of environment, especially for drivers. In this study, the optimum safety design of the New Jersey (NJ) concrete barrier which reduces injury levels up to the acceleration severity index (ASI) and meets safety criteria for the EN1317/2 standard, is achieved by simulation-based design optimization. For this purpose, the critical design points of the NJ type barrier have been determined. Then the critical design points were taken as variables and the safety criteria in EN1317 were taken as the objective function for multi-objective optimization (MOO). Once the variables and objective functions were determined, data was prepared with finite elements (FE) and the surrogate model was constructed using an optimal weighted pointwise of radial basis function (OWPE-RBF). Afterward, the multi-objective genetic algorithm was employed to solve the MOO problem. The optimum safety design that was obtained was compared with the validated original design, i.e. full-size modeling in the finite element (FE) environment. As a result, both the critical design points of NJ type barriers and important determinations regarding the OWPE-RBF model were obtained. Above all, a design has been achieved with an ASI/injury level which is 22–23% safer by way of the proposed analytical model and the monitored path.

除了由材料提供的优点和易于组装/拆卸的功能外，碰撞后最小变形提供的易于维修性及其可持续性突出了混凝土路障对路边安全性的偏爱。但是，混凝土屏障作为刚性系统，在发生碰撞时具有很高的风险。因为应用目的的首要任务是安全，所以希望设计提供相关标准中必要的安全标准，并且在环境方面（特别是对于驾驶员）非常安全。在这项研究中，通过基于仿真的设计优化来实现新泽西州（NJ）混凝土路障的最佳安全设计，该设计可将伤害等级降低到加速严重程度指数（ASI）并符合EN1317 / 2标准的安全标准。以此目的，NJ型屏障的关键设计点已经确定。然后将关键设计点作为变量，并将EN1317中的安全标准作为多目标优化（MOO）的目标函数。一旦确定了变量和目标函数，就可以使用有限元（FE）准备数据，并使用径向基函数的最佳加权点向（OWPE-RBF）构建替代模型。之后，采用多目标遗传算法求解MOO问题。将获得的最佳安全设计与经过验证的原始设计进行了比较，即在有限元（FE）环境中进行全尺寸建模。结果，既获得了NJ型屏障的关键设计要点，又获得了有关OWPE-RBF模型的重要决定。首先，