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The estimation of the compressibility of normally and overconsolidated granular soils was the main aim of the research. A model screw plate instrument was designed and developed and various plate geometries and plate advancement mechanisms were studied with a view to assessing soil disturbance during installation. Screw plate loading tests were conducted by means of a plate 50 mm in diameter 3 mm thick and 5 mm pitch. All the tests were conducted in a calibration chamber under stress controlled conditions on normally and overconsolidated saturated Leighton Buzzard sand along Ko and isotropic stress paths. Stress path triaxial tests were performed on normally and overconsolidated sand specimens. The stress-strain responses observed from such tests were compared with the pressure-settlement curves obtained from screw plate tests. The CRISP Finite Element Program was utilised to model the embedded plate and the chamber. Stress distributions and induced settlements beneath the plate were studied. Finally the effect of plate rigidity on the distribution of stresses was investigated and the validity of dimensions of the calibration chamber for the purpose of screw plate testing was proven.

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Many software systems must be load tested to ensure that they can scale up under high load while maintaining functional and non-functional requirements. Studies show that field problems are often related to systems not scaling to field workloads instead of feature bugs. To assure the quality of these systems, load testing is a required testing procedure in addition to conventional functional testing procedures, such as unit and integration testing. Current industrial practices for checking the results of a load test remain ad-hoc, involving high-level manual checks. Few research efforts are devoted to the automated analysis of load testing results, mainly due to the limited access to large scale systems for use as case studies. Approaches for the automated and systematic analysis of load tests are needed, as many services are being offered online to an increasing number of users. This dissertation proposes automated approaches to assess the quality of a system under load by mining some of the recorded load testing data (execution logs). Execution logs, which are readily available yet rarely used, are generated by output statements which developers insert into the source code. Execution logs are hard to parse and analyze automatically due to their free-form structure. We first propose a log abstraction approach that uncovers the internal structure of each log line. Then we propose automated approaches to assess the quality of a system under load by deriving various models (functional, performance and reliability models) from the large set of execution logs. Case studies show that our approaches scale well to large enterprise and open source systems and output high precision results that help load testing practitioners effectively analyze the quality of the system under load. / Thesis (Ph.D, Computing) -- Queen's University, 2013-01-26 22:58:29.881

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