Bridges and buildings are often supported on deep foundations. These foundations consist of groups of piles coupled together by concrete pile caps. These pile caps, which are often massive and deeply buried, would be expected to provide significant resistance to lateral loads. However, practical procedures for computing the resistance of pile caps to lateral loads have not been developed, and, for this reason, cap resistance is usually ignored. Neglecting cap resistance results in estimates of pile group deflections and bending moments under load that may exceed the actual deflections and bending moments by 100 % or more. Advances could be realized in the design of economical pile-supported foundations, and their behavior more accurately predicted, if the cap resistance can be accurately assessed. This research provides a means of assessing and quantifying many important aspects of pile group and pile cap behavior under lateral loads. The program of work performed in this study includes developing a full-scale field test facility, conducting approximately 30 lateral load tests on pile groups and pile caps, performing laboratory geotechnical tests on natural soils obtained from the site and on imported backfill materials, and performing analytical studies. A detailed literature review was also conducted to assess the current state of practice in the area of laterally loaded pile groups. A method called the "group-equivalent pile" approach (abbreviated GEP) was developed for creating analytical models of pile groups and pile caps that are compatible with established approaches for analyzing single laterally loaded piles. A method for calculating pile cap resistance-deflection curves (p-y curves) was developed during this study, and has been programmed in the spreadsheet called PYCAP. A practical, rational, and systematic procedure was developed for assessing and quantifying the lateral resistance that pile caps provide to pile groups. Comparisons between measured and calculated load-deflection responses indicate that the analytical approach developed in this study is conservative, reasonably accurate, and suitable for use in design. The results of this research are expected to improve the current state of knowledge and practice regarding pile group and pile cap behavior. / Ph. D.

This master thesis is about providing the implementation of synthesis, detection of spiral symbols and estimating the pan/tilt angle and position by using camera calibration. The focus is however on the latter, the estimation of parameters of localization. Spiral symbols are used to be able to give an object an identity as well as to locate it. Due to the spiral symbol´s characteristic shape, we can use the generalized structure tensor (GST) algorithm which is particularly efficient to detect different members of the spiral family. Once we detect spirals, we know the position and identity parameters of the spirals within an apriori known geometric configuration (on a sheet of paper). In turn, this information can be used to estimate the 3D-position and orientation of the object on which spirals are attached using a camera calibration method.   This thesis provides an insight into how automatic detection of spirals attached on a sheet of paper, and from this, automatic deduction of position and pose parameters of the sheet, can be achieved by using a network camera. GST algorithm has an advantage of running the processes of detection of spirals efficiently w.r.t detection performance and computational resources because it uses a spiral image model well adapted to spiral spatial frequency characteristic. We report results on how detection is affected by zoom parameters of the network camera, as well as by the GST parameters; such as filter size. After all spirals centers are located and identified w.r.t. their twist/bending parameter, a flexible technique for camera calibration, proposed by Zhengyou Zhang implemented in Matlab within the present study, is performed. The performance of the position and pose estimation in 3D is reported. The main conclusion is, we have reasonable surface angle estimations for images which were taken by a WLAN network camera in different conditions such as different illumination and different distances.

The angle of arrival estimation of multiple sources plays a vital role in the field of array signal processing as MIMO systems can be employed at both the transmitter and the receiver end and the system capacity, reliability and throughput can be significantly increased by using array signal processing. Almost all applications require accurate direction of arrival (DOA) estimation to localize the sources of the signals. Another important parameter of localization systems is the array geometry and sensor design which can be application specific and is used to estimate the DOA. In this work, various array geometries and arrival estimation algorithms are studied and then a new scheme for multiple source estimation is proposed and evaluated based on the performance of subspace and non-subspace decomposition methods. The proposed scheme has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation and Bartlett estimation techniques. The new scheme has a better performance advantage at low and high signal to noise ratio values (SNRs). The research work also studies different array geometries for both single and multiple incident sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna array elements. This research also considers the shape of the ground plane and its effects on the angle of arrival estimation and in addition it shows how the mutual couplings between the elements effect the overall estimation and how this error can be minimised by using a decoupling matrix. At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver base station is designed and tested. The antenna radiation patterns in the azimuth angle are almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral with striplines feeding network and biased components to improve the impedance bandwidth. The antenna provides the benefit of small size, and re-configurability and is very well suited for the asset tracking applications.