Scholarly record

ADVANCED DRY MIX SOLUTIONS FOR CORROSION PROTECTION AND IMPROVED DURABILITY OF CONCRETE IN AGRO-INDUSTRIAL ENVIRONMENTS USING D-OPTIMAL DESIGN OF EXPERIMENTS FOR MULTI-FACTOR OPTIMIZATION

Ion Rusu, L. JUDELE, Ana-Raluca ROSU, Eduard Proaspat, Daniel Lepadatu

Abstract

The paper presents the results of investigations on the in-service behavior of concrete structures used in fruit and vegetable processing facilities, where environmental conditions are characterized by high chemical and biological aggressiveness. In such environments, concrete surfaces are continuously or periodically exposed to liquid media containing organic acids and microorganisms, as well as to significant variations in temperature and humidity. These factors lead to accelerated degradation processes, manifested by corrosion, cracking, and increased material porosity. The analysis of current practices and the technical condition of existing structures indicates that surface degradation is strongly influenced by characteristics such as high roughness, open porosity, and the presence of cracks, as well as by the material’s water absorption capacity. In this context, proper surface preparation such as cleaning, leveling, and sealing of pores and cracks is essential for the effective application of protective systems. The study focuses on optimizing the properties of dry mixes used for the protection of concrete surfaces by adapting their composition and functional parameters to specific operating conditions, using a Design of Experiments (DOE) approach for systematic evaluation and optimization. The key properties investigated include chemical resistance, water retention capacity, stability during application on vertical surfaces, tensile behavior, adhesion to the substrate, and self-leveling capability on horizontal surfaces. The experimental results demonstrate the effectiveness of the proposed solutions in mitigating degradation phenomena and enhancing the durability and reliability of concrete structures operating in aggressive agro-industrial environments, contributing to extended service life and reduced maintenance costs. The study was based on a D-optimal Design of Experiments (DOE) with five factors, including thixotropic additive, polymer additive, filler additive, biocide additive, and water-to-cement ratio, while regression analysis was employed to determine the optimal composition and functional performance of the dry mix. This approach enables the identification of the individual and interaction effects of multiple factors on the performance of the dry mix. Furthermore, it supports a multi-factor optimization strategy aimed at achieving an optimal balance between functional properties and application requirements.

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