La biomasse lignocellulosique est considérée comme une ressource de carbone renouvelable possédant un grand potentiel pour la une valorisation énergétique et chimique. La torréfaction de la biomasse sèche (de type bois) est un procédé de transformation thermique s’effectuant à des températures comprises entre 200°C et 300°C, et un temps de séjour compris entre quelques minutes et plusieurs heures, opérant sous pression atmosphérique et en défaut d’air. Le produit principal de la torréfaction est un combustible solide hydrophobe et stable. Cette opération génère des coproduits gazeux à haute température qui sont habituellement considérés comme des effluents pénalisants, apportant au mieux un appoint d’énergie pour le procédé. Pourtant, de nombreux constituants présents dans les condensats – récupérés par condensation des coproduits de torréfaction – pourraient être valorisés comme produits chimiques bio-sourcés. L'objectif de la thèse est de proposer un procédé de séparation-purification pour les composés condensables présents dans ces effluents gazeux. Ces condensats constituent une phase majoritairement aqueuse, contenant plus de 150 espèces organiques identifiées. Les espèces minoritaires sont présentes dans des proportions variables suivant le bois torréfié. Enfin il s’agit d’un mélange réactif et thermiquement instable, où différents équilibres chimiques sont présents. Une analyse des caractéristiques physico-chimiques des condensats a permis de proposer un milieu modèle limité à une dizaine de composés. Un modèle représentatif du comportement thermodynamique de ce mélange réactif à large spectre de masse moléculaire a été sélectionné et les paramètres d’interaction binaire identifiés. Des données expérimentales d’équilibres liquide-vapeur ont été acquises pour valider en partie ce modèle. Les composés cibles et les objectifs du procédé de valorisation ont été choisis et plusieurs stratégies de valorisation ont été élaborées et simulées sous Prosim+ sur la base de la modélisation thermodynamique. Cette étude a permis d’évaluer ces différentes stratégies en termes d’efficacité énergétique et de pureté des produits finaux pour une potentielle mise en place à l’échelle industrielle de cette filière. / Lignocellulosic biomass is considered as a renewable carbon resource with great potential for the energy and chemical recovery. Torrefaction is a thermal process carried out at temperatures below 300°C, under inert atmosphere, at atmospheric pressure, and with residence times for the solid biomass ranging from few minutes to several hours. Torrefied wood is a solid product constituted by more than 70% of the initial mass with properties close to those of coal. The 30% remaining part is a gaseous effluent, composed of about one third of non-condensable gases – carbon monoxide and carbon dioxide – and two thirds of condensable species. Currently, torrefied wood is the main product of interest and is usually transformed into energetic gases by the gasification process or directly used as coal for combustion. Conversely, gaseous by-products are considered at present time as a waste and in the best case are burned to provide energy to the process. Yet, the recovery and valorization of the condensable fraction as bio-sourced chemicals is worth considering. The aim of the thesis is to propose a separation-purification process for condensable chemicals of the waste gas. This condensable fraction is a predominantly aqueous phase, containing more than 150 identified organic species. Minority species are present in varying proportions depending on torrefied wood. Finally, it is a reactive and thermally unstable mixture, where different chemical equilibria are present. An analysis of the physicochemical characteristics of the condensable fraction allowed selecting a limited number of compounds to model the mixture. A representative model of the thermodynamic behavior of the reactive mixture has been selected and the binary interaction parameters identified. Experimental vapor-liquid equilibria data were acquired in part to validate this model. The target compounds and objectives of the recovery process were selected and several development strategies were developed and simulated in ProSim+ on the basis of thermodynamic modeling. This study assessed these different strategies in terms of energy efficiency and purity of the products for potential implementation on an industrial scale of this sector.

Survival analytic methods help to analyze lifetime data arising from medical and reliability experiments. The popular proportional hazards model, proposed by Cox (1972), is widely used in survival analysis to study the effect of risk factors on lifetimes. An important assumption in regression type analysis is that all relative risk factors should be included in the model. However, not all relative risk factors are observed due to measurement difficulty, inaccessibility, cost considerations, and so on. These unobservable risk factors can be modelled by the so-called frailty model, originally introduced by Vaupel et al. (1979). Furthermore, the frailty model is also applicable to clustered data. Cluster data possesses the feature that observations within the same cluster share similar conditions and environment, which are sometimes difficult to observe. For example, patients from the same family share similar genetics, and patients treated in the same hospital share the same group of profes- sionals and same environmental conditions. These factors are indeed hard to quantify or measure. In addition, this type of similarity introduces correlation among subjects within clusters. In this thesis, a semi-parametric frailty model is proposed to address aforementioned issues. The baseline hazards function is approximated by a piecewise constant function and the frailty distribution is assumed to be a Birnbaum-Saunders distribution. Due to the advancement in modern medical sciences, many diseases are curable, which in turn leads to the need of incorporating cure proportion in the survival model. The frailty model discussed here is further extended to a mixture cure rate frailty model by integrating the frailty model into the mixture cure rate model proposed originally by Boag (1949) and Berkson and Gage (1952). By linking the covariates to the cure proportion through logistic/logit link function and linking observable covariates and unobservable covariates to the lifetime of the uncured population through the frailty model, we obtain a flexible model to study the effect of risk factors on lifetimes. The mixture cure frailty model can be reduced to a mixture cure model if the effect of frailty term is negligible (i.e., the variance of the frailty distribution is close to 0). On the other hand, it also reduces to the usual frailty model if the cure proportion is 0. Therefore, we can use a likelihood ratio test to test whether the reduced model is adequate to model the given data. We assume the baseline hazard to be that of Weibull distribution since Weibull distribution possesses increasing, constant or decreasing hazard rate, and the frailty distribution to be Birnbaum-Saunders distribution. D ́ıaz-Garc ́ıa and Leiva-Sa ́nchez (2005) proposed a new family of life distributions, called generalized Birnbaum-Saunders distribution, including Birnbaum-Saunders distribution as a special case. It allows for various degrees of kurtosis and skewness, and also permits unimodality as well as bimodality. Therefore, integration of a generalized Birnbaum-Saunders distribution as the frailty distribution in the mixture cure frailty model results in a very flexible model. For this general model, parameter estimation is carried out using a marginal likelihood approach. One of the difficulties in the parameter estimation is that the likelihood function is intractable. The current technology in computation enables us to develop a numerical method through Monte Carlo simulation, and in this approach, the likelihood function is approximated by the Monte Carlo method and the maximum likelihood estimates and standard errors of the model parameters are then obtained numerically by maximizing this approximate likelihood function. An EM algorithm is also developed for the Birnbaum-Saunders mixture cure frailty model. The performance of this estimation method is then assessed by simulation studies for each proposed model. Model discriminations is also performed between the Birnbaum-Saunders frailty model and the generalized Birnbaum-Saunders mixture cure frailty model. Some illustrative real life examples are presented to illustrate the models and inferential methods developed here. / Thesis / Doctor of Science (PhD)

Deep Mixing involves the introduction of cementitious or specially formulated solutions directly into the ground through the use of purpose built blending injection augers. The system is mainly designed to increase strength and reduce compressibility of treated soil. In the first stage of the research effective mixture ratios and mixture types of stabilizing agents were investigated for soft clays (CL form Eymir lake and kaolinite) by means of unconfined compression (UC) tests on stabilized soils. The unconfined compressive strength (UCS) values were obtained for 7,28,90 and 365 days of curing time. The ratio of elastic modulus at 50% failure load (E50) to (UCS) of the stabilizing agents were also investigated. In the second part of the research programme, deep mixed model columns with the three column materials and four different column spacings are formed within the large scale consolidation tanks, and the consolidation characteristics of deep mixed improved clay were investigated. Based on the results of large scale consolidation tests on deep mixed columnar improved soft clay, compressibility characteristics of improved soft clay were determined in relation to spacing of columns namely, effective replacement ratio and binder content. The cement content (also UCS) of the column material was found to be the most important parameter for the improvement effects of DMM applications. Validity of the relations for the estimation of bulk compression modulus of soilcrete were discussed. The use of constrained modulus of the soil and the column material were found to be effective in predicting the compression modulus of the soilcrete. Settlement reduction factor versus replacement ratio and cement content relations were determined which may be used for preliminary design works. The stresses on the soil and the columns were backcalculated from the settlement values. The stress ratios were obtained.