SOLUTION TO THE PROBLEM OF OPTIMAL DESIGN OF AN ELEVATOR WORKING TOWER UNDER DYNAMIC LOADS

Abstract

Purpose. The purpose of the paper is to develop and substantiate an approach to the optimal design of steel–reinforced concrete floors in elevator working towers subjected to dynamic loads generated by grain-cleaning machines. The study aims to formulate a mathematical model of the optimization problem, define a system of generalized design parameters, and establish a methodology for their rational selection under strength and serviceability constraints. Particular attention is given to the application of the Hooke–Jeeves direct search method in combination with limit state design principles for optimizing key structural parameters, including slab thickness, floor beam spacing, stud connector characteristics, and reinforcement configuration. The research also focuses on accounting for dynamic effects arising from different operating modes of separator machines within the overall design framework of composite floor systems. Methodology. The research is based on a combined approach that integrates limit state design calculations with the Hooke–Jeeves direct search method for optimizing the structural configuration of steel–reinforced concrete floors. A mathematical model of the optimization problem is formulated, including an objective function based on bending stresses and constraints defined by nonlinear equilibrium equations, strength conditions, and permissible ranges of design parameters. The set of generalized design variables includes slab thickness, floor beam spacing, stud connector diameter, and reinforcement characteristics, while key geometric parameters of the structure are treated as fixed inputs. The optimization procedure involves iterative variation of individual parameters with subsequent evaluation of the structural response under combined permanent, variable, and dynamic loads generated by grain-cleaning machines operating in different modes. Results. The application of the proposed optimization methodology enabled the formulation of a structured procedure for determining rational parameters of steel–reinforced concrete floors in elevator working towers. A base point of the optimization process was established, along with permissible ranges for variation of the main design parameters, including slab thickness, floor beam spacing, stud connector diameter, and reinforcement characteristics. Scientific novelty. The scientific novelty of the study lies in the development of an integrated approach to the optimal design of steel–reinforced concrete floors in elevator working towers, which combines limit state design principles with the Hooke–Jeeves direct search optimization method. A distinctive feature of the proposed approach is the explicit consideration of dynamic loads generated by grain-cleaning machines operating in different modes, which are incorporated into the optimization framework. This allows for a more accurate representation of real operating conditions compared to conventional static design methods. The study also establishes a structured procedure for parameter variation and search direction identification within the design space, forming a basis for further development of optimization techniques for composite steel–reinforced concrete systems. Practical relevance. The proposed approach can be applied in the design of steel–reinforced concrete floors in elevator working towers and similar industrial structures subjected to dynamic loads from technological equipment. The developed methodology provides engineers with a systematic tool for selecting rational design parameters, including slab thickness, beam spacing, stud connector characteristics, and reinforcement layout, in accordance with strength and serviceability requirements. Its implementation enables a more reliable consideration of dynamic effects during the design stage, contributing to improved structural safety, durability, and operational performance. The approach can be integrated into existing engineering practice and adapted for use in numerical modeling environments, facilitating more efficient decision-making in the design and modernization of grain processing facilities.