Prediction of Mechanical Properties of Frozen Soils Using Response Surface Method: An Optimization Approach

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Vahdani M.; Ghazavi M.; Roustaei M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: International Journal of Engineering Year:2020 | Volume:33 | Issue:10 Page(s): 1826-1841

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

Prediction of Mechanical Properties of Frozen Soils Using Response Surface Method: An Optimization Approach

Author(s)

Vahdani M. | Ghazavi M. | Roustaei M. | Issue Writer Certificate

Keywords

Frozen soil

Mechanical properties

Prediction models

response surface method

Statistical optimization

Abstract

The present study was based on a promoting statistical method known as response surface method (RSM). RSM has been applied as an efficient method to optimize many physical applications in industry for more than two decades. In the current study, the RSM was utilized as a platform to develop models as a function of some prescribed input factors to predict Mechanical properties (responses) of Frozen soils (i.e. peak tensile/compressive strength, elasticity modulus). Besides, RSM makes it possible to find significant factors and probable interactions as well. A widespread literature review was conducted and three case studies were chosen to evaluate the performance of the RSM in developing precise models and finally an optimum experiment. For each case study, less than half of the available data (an average of 40.8%) was employed to develop models and the remaining part was employed to evaluate the validity of derived models. A comparison between predicted and measured data showed a good agreement with a significant level of 0.05. This indicates that upon using the model a hundred times to predict an specific property for different input factors, the maximum five predictions may diverge from the measured values with ± confidence interval. In addition, some contours were plotted to give a comprehensive presentation of any probable correlations between investigated properties and input factors. Based on the developed models with an average correlation coefficients (R2) of 93.69, temperature was found to be the most significant factor affecting the Mechanical properties of frozen fine soil, while the dry density was not as effective as the temperature.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans