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The San Jacinto Monument was built in 1936 to celebrate the 100 year anniversary of the battlefield victory that gave Texas its freedom. Ray Dawson was in charge of the foundation design and decided to instrument the foundation to monitor the settlement of the Monument. The settlement has been recorded since 1936 and provides a very valuable long-term record. This settlement and other geotechnical data were studied and reported by Briaud and his co-authors in 2007. That study was based on data available at the time, which was primarily from a 61-m-deep boring in 1953. In 2007, Fugro and Texas A&M University drilled a new boring with sampling to a depth of 78 m, conducted in situ tests to 36 m, and laboratory tests on the samples recovered. Updated settlement calculations are provided using this new data; they show reasonably good agreement with modern settlement techniques. One of the issues possibly affecting the settlement readings is the subsidence of the ground surface, which can reach 3 m in that area of Houston. A second part of this article presents calculations and numerical simulations to evaluate the influence of subsidence on the recorded settlement of the Monument. It is shown that the true settlement of the SJM is 295 mm while the measured settlement is 328 mm. The reduction is due to the different influence of the subsidence on the settlement of the shallow benchmark and of the Monument. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study on the thermal conductivity of a soft saturated clay (Bangkok clay) carried out in relation to an investigation into thermal ground improvement using prefabricated vertical drains. The thermal conductivity of clay specimens was measured, at different porosities and temperature levels, using a simple nondestructive steady-state test method. In addition, a theoretical mixture model to simulate the evolution of thermal conductivity of saturated fine-grained soils has been introduced. It is formulated in terms of thermal conductivity and volume fraction of each soil phase (solid and water), and a morphological parameter controlled by the soil fabric condition. The proposed model has been validated against thermal conductivity results reported in the literature and results obtained from the present investigation. Reasonable agreement has been obtained between the predicted and measured thermal conductivity values. [ABSTRACT FROM AUTHOR]

Over the years, many methods have been developed to predict the settlement of shallow foundations on cohesionless soils. However, methods for making such predictions with the required degree of accuracy and consistency have not yet been developed. Accurate prediction of settlement is essential since settlement, rather than bearing capacity, generally controls foundation design. In this paper, artificial neural networks (ANNs) are used in an attempt to obtain more accurate settlement prediction. A large database of actual measured settlements is used to develop and verify the ANN model. The predicted settlements found by utilizing ANNs are compared with the values predicted by three of the most commonly used traditional methods. The results indicate that ANNs are a useful technique for predicting the settlement of shallow foundations on cohesionless soils, as they outperform the traditional methods. [ABSTRACT FROM AUTHOR]

Considers the probabilistic measures of foundation settlement on spatially random soil. Description of random field and finite element models of soil layer; Discussion of the single footing case; Analysis of the two footing case.