The use of composite structures in engineering applications has proliferated over the past few decades due to its distinct advantages namely: high structural performance, corrosion resistance, and high strength/weight ratio. However, they also come with a set of disadvantages, i.e. they are prone to fibre breakage, matrix cracking and delaminations. These types of damage are often invisible and if undetected, could lead to catastrophic failures of structures. Although there are systems to detect such damage, the criticality assessment and prognosis of the damage is often much more difficult to achieve. The research study conducted here resulted in the development of a Structural Health Monitoring (SHM) system for a 2D polymeric composite T-joint, used in maritime structures. The SHM system was found to be capable of not only detecting the presence of multiple delaminations in a composite structure, but also capable of determining the location and extent of all t he delaminations present in the T-joint structure, regardless of the load (angle and magnitude) acting on the structure. The system developed relies on the examination of the strain distribution of the structure under operational loading. This SHM system necessitated the development of a novel pre-processing algorithm - Damage Relativity Assessment Technique (DRAT) along with a pattern recognition tool, Artificial Neural Network (ANN), to predict and estimate the damage. Another program developed - the Global Neural network Algorithm for Sequential Processing of Internal sub Networks (GNAISPIN) uses multiple ANNs to render the SHM system independent to variations in structural loading and capable of estimating multiple delaminations in composite T-joint structures. Upto 82% improvement in detection accuracy was observed when GNAISPIN was invoked. The Finite Element Analysis (FEA) was also conducted by placing delaminations of different sizes at various locations in two structures, a composite beam and a T-joint. Glass Fibre Reinforced Polymer T-joints were then manufactured and tested, thereby verifying the accuracy of the FEA results experimentally. The resulting strain distribution from the FEA was pre-processed by the DRAT and used to trai n the ANN to predict and estimate damage in the structures. Finally, on testing the SHM system developed with strain signatures of composite T-joint structures, subjected to variable loading, embedded with all possible damage configurations (including multiple damage scenarios), an overall damage (location & extent) prediction accuracy of 94.1% was achieved. These results are presented and discussed in detail in this study.

Adaptability is one of the reasons for the success of bacteria, allowing them to survive in conditions where no other organisms would be able to thrive. Nitrogen deficiency, for example, can be a limiting factor for the growth of micro-organisms, as this element is an essential part of almost all types of biomolecules. As such, some bacteria have evolved specific mechanisms to overcome nitrogen limitation. Nitrogen fixing bacteria, or diazotrophs, use a specific enzyme complex, nitrogenase, in order to harness this element from the enormous reservoir that is the Earth’s atmosphere. However, nitrogen fixation is a demanding process for the cells, requiring vast amounts of energy and tight regulation. In this thesis we explore the mechanisms regulating nitrogen fixation in Rhodospirillum rubrum, a purple non-sulphur photosynthetic bacterium. Using proteomics tools, we show how the regulation of both the nitrogen and carbon fixation processes is interconnected, possibly in order to maintain the intracellular redox balance. Using a new detergent molecule, we also demonstrate how nitrogen availability affects the chromatophore membrane proteome. Our studies have revealed the crucial role of the cellular pool of 2-oxoglutarate (2OG) for adequate signaling through the PII proteins and the effects resulting from artificially manipulating this metabolite’s concentration. In R. rubrum nitrogenase is also subjected to post-translational control (the “switch-off” effect) and this work shows for the first time that the enzyme modifying nitrogenase (Dinitrogenase Reductase ADP-ribsosyl Transferase or DRAT) forms a complex with the PII protein GlnB. This complex allows DRAT activation and its formation – and, therefore, DRAT activity – is regulated by binding of ADP:ATP and 2OG to GlnB. Upon light withdrawal, nitrogenase activity anaerobically in the dark is also here demonstrated to be dependent on the activity of the pathway starting in pyruvate formate-lyase and we show how different nitrogen sources influence the switch-off response. This response can, in some conditions, be modified by addition of pyruvate and we have studied how this metabolite influences nitrogenase activity and switch-off regulation. This study allows a better understanding of the underlying processes controlling the metabolic routes in R. rubrum and also provides new insights into regulation of enzyme activity, paving the road for the complete establishment of the mechanisms regulating nitrogenase switch-off. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: In press. Paper 3: Submitted. Paper 4: Manuscript. Paper 5: Submitted.</p>