An optimum mix design of high strength concrete using genetic algorithms
High-strength concrete (HSC) is a highly complex material which makes modeling its behavior a very difficult task. Careful selection of constituent materials must be employed to successfully proportion HSC mixtures. Moreover, while strength may be of primary concern in HSC, workability requirements...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2011
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/7937 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Language: | English |
| Summary: | High-strength concrete (HSC) is a highly complex material which makes modeling its behavior a very difficult task. Careful selection of constituent materials must be employed to successfully proportion HSC mixtures. Moreover, while strength may be of primary concern in HSC, workability requirements must also be satisfied in order to be applied in actual practice. In order to obtain concrete of high strength and high workability by the conventional method, a large number of trial mixes are required to select to desired combination of materials. Therefore, in this paper, genetic algorithm is used as an optimization technique to find the optimal solution to a problem with many possible combinations of solutions. This study shows that the results from genetic algorithm modified to be applicable in actual practice suggested a reduction in the number of trial mixtures with desired results in the field test and lesser incurred overall material cost of HSC compared to the current HSC mixture of the company which granted us the trial mix data. Experimental and analytic investigations were carried out to physically show the applicability of genetic algorithm in optimizing high-strength concrete performance as well. The results of the series of test showed that indeed genetic algorithm finds the optimum HSC mix design parameters with less material wastage and other resources. |
|---|