SOIL SENSIBILITY CHARACTERIZATION OF GRANULAR SOILS DUE TO SUFFUSION
Published In: 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND CONSTRUCTION ENGINEERING
Author(s): ABDUL ROCHIM , DIDIER MAROT , LUC SIBILLE
Abstract: This paper studies the characterization of soil sensibility due to suffusion process by carrying out a series of one-dimensional downward seepage flow tests realized with an erodimeter. Tests were performed under controlled hydraulic gradients in sandy gravel soils. We propose the analysis based on energy induced by the seepage flow to characterize the hydraulic loading and the cumulative eroded dry mass to characterize the soil response. With this approach, the effect of hydraulic loading histories and initial fines contents to soil sensibility are presented. It is found that for given soils, erosion coefficients are different if tests are performed under different hydraulic loading histories. For given initial fines fraction contents, the sensibility may be grouped in the same classification. The lower fines content soils tend to require larger flow energy to the development of erosion. These results demonstrate that this approach is effective to characterize suffusion sensibility fo
- Publication Date: 19-Apr-2015
- DOI: : 10.15224/978-1-63248-042-2-123
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COMPARISON BETWEEN FUZZY RISK ASSESSMENT METHODS
Published In: 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN CIVIL, STRUCTURAL AND CONSTRUCTION ENGINEERING
Author(s): A. SAMER EZELDIN , KHALED NASSAR , RANIA FAYED
Abstract: Contracting for construction services is an inherently risky venture for the owner, design agent and contractor. All of these parties are exposed to unanticipated risks, exposure to economic loss and unforeseen contract liability while performing under the contract. Project risk management, therefore, has been recognised critical for the construction industry to improve their performance and secure the success of projects. Risk assessment is the most important step in risk management. Classical methods for risk assessment are no longer accurate and effective, therefore, many papers introduced fuzzy logic as a more accurate and effective technique in risk assessment. In this paper, a comparison between two fuzzy risk assessment methods; Nieto-Morote and Ruz-Vila [1] and Kuo and Lu [2] is done using the same input parameters which are risk probability (RP), risk impact (RI) and risk discrimination (RD) to determine if these methods give the same risk ranking or not. Actually, the compari
- Publication Date: 19-Apr-2015
- DOI: 10.15224/978-1-63248-042-2-142
- Views: 0
- Downloads: 0