AUB ScholarWorks

Reliability-Based Design of Rammed Earth Structures using Machine Learning Models

Show simple item record

dc.contributor.advisor Najjar, Shadi Mustapha, Anas 2024-05-14T11:47:16Z 2024-05-14T11:47:16Z 2024-05-14 2024-04-25
dc.description.abstract Rammed earth construction is becoming popular since it successfully integrates eco-friendliness, sustainability, and the possibility of cost-effective construction. Rammed earth is comprised of clay, gravel, sand, silt, and may or may not include a stabilizer like cement or lime. Since the mechanical properties of stabilized rammed earth vary with properties of the soil and the type and level of cementation, a great deal of experimental and theoretical research has been done on the subject. The rigorous design considerations found in structures constructed using conventional building materials (such as concrete or masonry) are absent from structures created with rammed earth. The absence of rigorous design practices for rammed earth poses a critical need for a systematic evaluation of the uncertainties inherent in the material properties of rammed earth and their impact on the reliability levels that characterize the likelihood of failure of structures built with these mixtures. The objective of this thesis is to use a data-driven approach to utilize a large database of experimental data on the unconfined compressive strength (UCS) of stabilized rammed earth mixtures to develop machine learning (ML) models that can predict the UCS as a function of the characteristics of the rammed earth mixture. The ML models will then be used within a reliability-based design framework to quantify the reliability levels that are inherent in the design of structural members which are constructed with rammed earth, and then compare the reliability levels to those currently enforced in conventional design codes. The results of this study could be used to inform the reliability-based design of rammed earth construction and to offer valuable insights into the design of sustainable and efficient construction materials. By combining traditional knowledge with modern methodologies, this thesis aims to empower architects, engineers, and builders to harness the potential of rammed earth construction while meeting contemporary standards of safety and durability.
dc.language.iso en
dc.subject Rammed earth
dc.subject Reliability-based design
dc.subject Machine learning
dc.subject Soil stabilization
dc.subject Sustainable construction
dc.title Reliability-Based Design of Rammed Earth Structures using Machine Learning Models
dc.type Thesis
dc.contributor.department Department of Civil and Environmental Engineering
dc.contributor.faculty Maroun Semaan Faculty of Engineering and Architecture
dc.contributor.commembers Mabsout, Mounir
dc.contributor.commembers Yeretzian, Aram ME
dc.contributor.AUBidnumber 201901215

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search AUB ScholarWorks


My Account