Determining the components of the structural-automatic model of firing a single target in armor protection with fragmentation-beam projectiles of directed action in a series of three shots based on the reference graph of states

Abstract

The problem of determining the components of the structural-automatic model is solved by creating a graph of states and transitions. The purpose of the process is to form a formalized expression of the object of study in the form of a structural-machine model of the process of firing a mobile armored vehicle with a series of three shots with fragmentation-beam projectiles of directional action. This model can be further practically implemented during the development of the latest samples of fire resistance in order to reduce errors at the stage of system design. This approach reduces the cost of design and production of prototypes by up to 25 %. This paper considers the process involving interrelated elements of the components of a system while accounting for all possible variants of its behavior from the moment of detection to the failure of a single target in armor protection to perform tasks as intended. The execution of a fire task is considered as a set of certain procedures characterized by the average value of their duration. The explosive destruction of the hull of each fragmentation-beam projectile is characterized by the self-propagation of the reaction of explosive transformations based on tabular data on an armored combat vehicle. Appropriate procedures (phases) of firing a single target in armor protection are advisable to formalize to create preconditions for obtaining the value of a statistical indicator of the effectiveness of causing damage to the target and to study further alternative options for this process. For the proposed structural-automatic model of the process of firing a single target in armor protection with a series of fragmentation-beam projectiles of directional action, validation and verification were carried out, which demonstrated the convergence of the results that exceeded 60 %. The use of the structural-automatic model's components proposed in this work increases the probability of performing a fire task for the first shot from 0.23 to 0.88, for the second – from 0.35 to 0.95, for the third – from 0.45 to 0.98