23 research outputs found

    Support of Deep Excavation in Soft Clay: A Case History Study

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    The innovative analysis, design, and construction of the temporary support of excavation (SOE) system for an underground garage will be presented in this paper. The site of the project is blanketed with a 10 to 18 feet thick layer of fill material, underlain with about 5 feet of soft organic deposits. The main soil deposit at the site consists of 65 to 90 feet deep marine clay, known as the “Boston Blue Clay”. The upper 10 to 12 feet of this clay is weathered and hardened to form a stiff crust that softens with depth. The majority of the excavation within the project site removed the stiff clay crust to expose the soft clay layer. In order to excavate to the required depth of about 44 feet, the contractor had to address a major challenge of controlling the basal heave as well as the lateral support of the excavation. Reinforced concrete slurry walls were installed along the perimeter of the underground garage to serve as structural wall and water cut-off for the parking garage. The slurry wall was toed in the soft clay layer at about 12 to 20 feet below the bottom of excavation. Finite element models that accounted for soil non-linearity were used to analyze the staged excavation and construction of the garage structure. Based on the finite element analyses, two temporary bracing levels were used to provide lateral support for the slurry walls. Because of the geometry of the underground garage and the variation of the bottom of excavation, the design and installation of the temporary bracing system was a challenging task. A close correlation between the predicted and the measured lateral deflection of the slurry wall was observed

    Estimation of stature from the foot and its segments in a sub-adult female population of North India

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    <p>Abstract</p> <p>Background</p> <p>Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population.</p> <p>Methods</p> <p>The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques.</p> <p>Results</p> <p>The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (<it>p-value </it>< 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements.</p> <p>Conclusions</p> <p>The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults.</p
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