Probabilistic verification of satellite systems for mission critical applications

In this thesis, we present a quantitative approach using probabilistic verification techniques for the analysis of reliability, availability, maintainability, and safety (RAMS) properties of satellite systems. The subject of our research is satellites used in mission critical industrial applications. A strong case for using probabilistic model checking to support RAMS analysis of satellite systems is made by our verification results. This study is intended to build a foundation to help reliability engineers with a basic background in model checking to apply probabilistic model checking to small satellite systems. We make two major contributions. One of these is the approach of RAMS analysis to satellite systems. In the past, RAMS analysis has been extensively applied to the field of electrical and electronics engineering. It allows system designers and reliability engineers to predict the likelihood of failures from the indication of historical or current operational data. There is a high potential for the application of RAMS analysis in the field of space science and engineering. However, there is a lack of standardisation and suitable procedures for the correct study of RAMS characteristics for satellite systems. This thesis considers the promising application of RAMS analysis to the case of satellite design, use, and maintenance, focusing on its system segments. Data collection and verification procedures are discussed, and a number of considerations are also presented on how to predict the probability of failure. Our second contribution is leveraging the power of probabilistic model checking to analyse satellite systems. We present techniques for analysing satellite systems that differ from the more common quantitative approaches based on traditional simulation and testing. These techniques have not been applied in this context before. We present the use of probabilistic techniques via a suite of detailed examples, together with their analysis. Our presentation is done in an incremental manner: in terms of complexity of application domains and system models, and a detailed PRISM model of each scenario. We also provide results from practical work together with a discussion about future improvements.

An investigation into the properties of non-digestible carbohydrates that selectively promote colonic propionate production

Short chain fatty acids (SCFA), including propionate, are produced by the bacterial fermentation of carbohydrates in the colon. Propionate has many potential roles in health, including inhibiting cholesterol synthesis, de novo lipogenesis and increasing satiety. The profile of SCFA produced is determined by both the substrate available and the bacteria present and may be influenced by environmental conditions within the lumen of the colon. Whilst it may be beneficial to increase colonic propionate production, dietary strategies to achieve this are unproven. Adding propionate to food leads to poorer organoleptic properties, and oral propionate is absorbed in the small intestine. The optimum way to selectively increase colonic propionate would be to select fermentable carbohydrates that selectively promote propionate production. To date, few studies have undertaken a systematic assessment of the factors leading to increased colonic propionate production making the selection of propiogenic carbohydrates challenging. The aim of this thesis was to identify the best carbohydrates for selectively increasing propionate production, and to explore the factors which control propionate production. This work started with a systematic review of the literature for evidence of candidate carbohydrates, which led to a screen of ‘propiogenic’ substrates using in vitro batch fermentations and mechanistic analysis of the impact of pH, bond linkage and orientation using a range of sugars, polysaccharides and fibre sources. A new unit for SCFA production was developed to allow comparison of results from in vitro studies encompassing a range different methodologies found in the literature. The systematic review found that rhamnose yielded the highest rate and proportion of propionate production whereas, for polysaccharides, β-glucan ranked highest for rate and guar gum ranked highest for molar production, but this was not replicated across all studies. Thus, no single NDC was established as highly propiogenic. Some substrates appeared more propiogenic than others and when these were screened in vitro. Laminarin, and other β-glucans ranked highest for propionate production. Legume fibre and mycoprotein fibre were also propiogenic. A full complement of glucose disaccharides were tested to examine the role glycosidic bond orientation and position on propionate production. Of the glucose disaccharides tested, β(1-4) bonding was associated with increased proportion of propionate and α(1-1) and β(1-4) increased the rate and proportion of butyrate production. In conclusion, it appears that for fibre to affect satiety, high intakes of fibre are needed, and which a major mechanism is thought to occur via propionate. Within this thesis it was identified that rather than selecting specific fibres, increasing overall intakes of highly fermentable carbohydrates is as effective at increasing propionate production. Selecting carbohydrates with beta-bonding, particularly laminarin and other β(1-4) fermentable carbohydrates leads to marginal increases in propionate production. Compared with targeted delivery of propionate to the colon, fermentable carbohydrates examined in this thesis have lesser and variable effects on propionate production. A more complete understanding of the impact of bond configurations in polysaccharides, rather than disaccharides, may help selection or design of dietary carbohydrates which selectively promote colonic propionate production substrates for inclusion in functional foods. Overall this study has concluded that few substrates are selectively propiogenic and the evidence suggests that similar changes in propionate production may be achieved by modest changes in dietary fibre intake

Physicochemical complexity in complex chemical systems

Self-replication and compartmentalization are two central properties thought to be essential for minimal life, and understanding how such processes interact in the emergence of complex reaction networks is crucial to exploring the development of complexity in chemistry and biology. Autocatalysis can emerge from multiple different mechanisms such as formation of an initiator, template self-replication and physical autocatalysis (where micelles formed from the reaction product solubilize the reactants, leading to higher local concentrations and therefore higher rates). Amphiphiles are also used in artificial life studies to create protocell models such as micelles, vesicles and oil-in-water droplets, and can increase reaction rates by encapsulation of reactants. So far, no template self-replicator exists which is capable of compartmentalization, or transferring this molecular scale phenomenon to micro or macro-scale assemblies. Here a system is demonstrated where an amphiphilic imine catalyses its own formation by joining a non-polar alkyl tail group with a polar carboxylic acid head group to form a template, which was shown to form reverse micelles by Dynamic Light Scattering (DLS). The kinetics of this system were investigated by 1H NMR spectroscopy, showing clearly that a template self-replication mechanism operates, though there was no evidence that the reverse micelles participated in physical autocatalysis. Active oil droplets, composed from a mixture of insoluble organic compounds in an aqueous sub-phase, can undergo processes such as division, self-propulsion and chemotaxis, and are studied as models for minimal cells, or protocells. Although in most cases the Marangoni effect is responsible for the forces on the droplet, the behaviour of the droplet depends heavily on the exact composition. Though theoretical models are able to calculate the forces on a droplet, to model a mixture of oils on an aqueous surface where compounds from the oil phase are dissolving and diffusing through the aqueous phase is beyond current computational capability. The behaviour of a droplet in an aqueous phase can only be discovered through experiment, though it is determined by the droplet's composition. By using an evolutionary algorithm and a liquid handling robot to conduct droplet experiments and decide which compositions to test next, entirely autonomously, the composition of the droplet becomes a chemical genome capable of evolution. The selection is carried out according to a fitness function, which ranks the formulation based on how well it conforms to the chosen fitness criteria (e.g. movement or division). Over successive generations, significant increases in fitness are achieved, and this increase is higher with more components (i.e. greater complexity). Other chemical processes such as chemiluminescence and gelation were investigated in active oil droplets, demonstrating the possibility of controlling chemical reactions by selective droplet fusion. Potential future applications for this might include combinatorial chemistry, or additional fitness goals for the genetic algorithm. Combining the self-replication and the droplet protocells research, it was demonstrated that the presence of the amphiphilic replicator lowers the interfacial tension between droplets of a reaction mixture in organic solution and the alkaline aqueous phase, causing them to divide. Periodic sampling by a liquid handling robot revealed that the extent of droplet fission increased as the reaction progressed, producing more individual protocells with increased self-replication. This demonstrates coupling of the molecular scale phenomenon of template self-replication to a macroscale physicochemical effect.