CO2 and cost optimization of reinforced concrete footings over a lime-treated soil using modified simulated annealing algorithm

Abstract

Introduction: The design of spread footings over a lime-treated soil is studied as an important topic in geotechnical and environmental engineering. With the emergence and use of algorithms, it is possible to solve optimization problems in engineering, leading, for example, to decreased amounts of materials, time, energy, and work.
 Objective: This research aims to optimize the CO2 emission and cost of building spread footings over a treated soil with hydrated lime using the modified simulated annealing algorithm (MSAA).
 Method: The parameters for shear strength (cohesion and friction angle) was calculated of a silty soil of the Guabirotuba geological formation of Curitiba (Brazil) stabilized with different lime contents (3, 5, 7 and 9%) at different curing times (30, 90, and 180 days). Then with these parameters, the geometry of the spread footings was optimized with MSAA minimizing the cost and CO2 emissions of their construction. For the design constraint of the structures the ultimate bearing capacity of the soil was used as criteria, the settlements produced by the service load, and the base safety factor
 Results: The results show that most of the problems converge to the same solution for costs and CO2 emissions without depending on curing time and lime content used, due to the solutions being restricted primarily by the maximum permissible settlements.
 Conclusions: With the increase in lime content, the cohesion of the mixtures increased for all curing times studied ant the friction angle had no major variations in relation to the amount of lime administered or to the curing time employed. Costs and carbon dioxide emissions for spread footing construction converge to the same results. In this sense, 9% lime can be avoided, and small percentages of lime (i.e. 3-5%) are appropriated to ground improvement and reduce the costs of this procedure. On the other hand, the MSAA can be designated as a robust algorithm due to having achieved almost equal results and, in some cases, better results compared with other algorithms to solve problems reported in the literature.