Le stockage de grains est une problématique qui date du développement de l’agriculture afin de répondre au besoin de conservation des céréales. Afin de faciliter la vidange de silos, l’entreprise Vibrafloor propose une solution de vidange automatisée basée sur l’agitation du contenu par vibration d’un plancher flexible. L’objectif de cette thèse est de développer un modèle numérique robuste qui puisse prédire le comportement du système vibrant sous charge, au cours d’un cycle de vidange. Ces travaux peuvent être décomposés en trois parties principales : - Le développement d’un modèle numérique fiable d’un module vibrant ; - Le développement d’un modèle numérique du milieu granulaire ; - La mise en interaction de ces deux modèles. Enfin, l’exploitation de ces modèles numériques a permis de proposer des règles d’utilisation du système à l’industriel et de proposer les prémisses d’un outil d’étude du procédé de vidange dans sa globalité. / The grain storage is an issue that dates agricultural development to address the need for cereal preservation. In order to facilitate the emptying silos process, Vibrafloor provides an automated emptying solution based on the agitation of the contents by vibration of a flexible floor. The objective of this thesis is to develop a reliable numerical model that can predict the behavior of the vibrating system under load during a drain cycle. These works can be divided into three main parts: - The development of a reliable digital model of a vibrating module - The development of a numerical model of the granular media - The interaction of these two models. Finally, the exploitation of these numerical models helped provide system usage rules for industrial and the beginnings of a study tool for the entire automatic drain process.

Cette thèse porte sur la modélisation, l'analyse et la réduction de modèles biologiques, notamment de réseaux de régulation génique chez la bactérie E. coli. Différentes approches mathématiques sont utilisées. Dans la 1ère partie de la thèse, on modélise, analyse et réduit avec des outils classiques un modèle de transcription-traduction de grande dimension de l'ARN polymérase (RNAP) chez E. coli. Dans la 2de partie, l'introduction d'une nouvelle méthode appelée Analyse de Processus Principaux (PPA) nous permet d'analyser des modèles de haute dimension, en les décomposant en processus biologiques dont l'activité est évaluée pendant l'évolution du système. L'exclusion des processus inactifs réduit la dynamique du modèle à ses principaux mécanismes. La méthode est appliquée à des modèles d'horloge circadienne, de toxicologie endocrine et de voie de signalisation ; on teste également sa robustesse aux variations des conditions initiales et des paramètres. Dans la 3ème partie, on présente un modèle ODE de la machinerie d'expression génique de cellules d'E. coli dont la croissance est contrôlée par un inducteur de la synthèse de RNAP. On décrit notre contribution au développement du modèle et analyse par PPA les mécanismes essentiels du réseau de régulation. Dans une dernière partie, on modélise spécifiquement la réponse de RNAP à l'ajout d'inducteur et estime les paramètres du modèle à partir de données de cellules individuelles. On discute l'importance de considérer la variabilité entre cellules pour modéliser ce processus : ainsi, la moyenne des calibrations sur chaque cellule apparaît mieux représenter les données moyennes observées que la calibration de la cellule moyenne. / This thesis deals with modeling, analysis and reduction of various biological models, with a focus on gene regulatory networks in the bacterium E. coli. Different mathematical approaches are used. In the first part of the thesis, we model, analyze and reduce, using classical tools, a high-dimensional transcription-translation model of RNA polymerase in E. coli. In the second part, we introduce a novel method called Principal Process Analysis (PPA) that allows the analysis of high-dimensional models, by decomposing them into biologically meaningful processes, whose activity or inactivity is evaluated during the time evolution of the system. Exclusion of processes that are always inactive, and inactive in one or several time windows, allows to reduce the complex dynamics of the model to its core mechanisms. The method is applied to models of circadian clock, endocrine toxicology and signaling pathway; its robustness with respect to variations of the initial conditions and parameter values is also tested. In the third part, we present an ODE model of the gene expression machinery of E. coli cells, whose growth is controlled by an external inducer acting on the synthesis of RNA polymerase. We describe our contribution to the design of the model and analyze with PPA the core mechanisms of the regulatory network. In the last part, we specifically model the response of RNA polymerase to the addition of external inducer and estimate model parameters from single-cell data. We discuss the importance of considering cell-to-cell variability for modeling this process: we show that the mean of single-cell fits represents the observed average data better than an average-cell fit.

Unlike the traditional two-stage methods, a conditional and inverse-conditional simulation approach may directly generate independent, identically distributed realizations to honor both static data and state data in one step. The Markov chain Monte Carlo (McMC) method was proved a powerful tool to perform such type of stochastic simulation. One of the main advantages of the McMC over the traditional sensitivity-based optimization methods to inverse problems is its power, flexibility and well-posedness in incorporating observation data from different sources. In this work, an improved version of the McMC method is presented to perform the stochastic simulation of reservoirs and aquifers in the framework of multi-Gaussian geostatistics. First, a blocking scheme is proposed to overcome the limitations of the classic single-component Metropolis-Hastings-type McMC. One of the main characteristics of the blocking McMC (BMcMC) scheme is that, depending on the inconsistence between the prior model and the reality, it can preserve the prior spatial structure and statistics as users specified. At the same time, it improves the mixing of the Markov chain and hence enhances the computational efficiency of the McMC. Furthermore, the exploration ability and the mixing speed of McMC are efficiently improved by coupling the multiscale proposals, i.e., the coupled multiscale McMC method. In order to make the BMcMC method capable of dealing with the high-dimensional cases, a multi-scale scheme is introduced to accelerate the computation of the likelihood which greatly improves the computational efficiency of the McMC due to the fact that most of the computational efforts are spent on the forward simulations. To this end, a flexible-grid full-tensor finite-difference simulator, which is widely compatible with the outputs from various upscaling subroutines, is developed to solve the flow equations and a constant-displacement random-walk particle-tracking method, which enhances the com / Fu, J. (2008). A markov chain monte carlo method for inverse stochastic modeling and uncertainty assessment [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1969 / Palancia

This master thesis focuses on a scaled fuselage design made from composite material. The first part deals with a description of composite materials and used material models in an explicit FEM simulation. Two types of scaled structures were designed that were subjected to drop test. Test results were compared with FEM simulation. Finally the calibration of models was carried out.

Winter cover crops grown in rotation with grain crops can be an efficient integrated pest management tool (IPM). However, cover crop biomass production and thus successful provisioning of ecosystem services depend on a timely planting and cover crop establishment after harvest of a cash crop in the fall. One potential management adaptation is the use of short-season soybeans to advance cover crop planting date in the fall. Cover crops planted earlier in the fall may provide a greater percentage of ground cover early in the season because of higher biomass accumulation that may improve weed suppression. However, adapting to short-season soybeans could have a yield penalty compared to full-season soybeans. In addition, it is unclear if further increasing cover crop growing season and biomass production under environmental conditions in Kentucky could limit nitrogen and water availability for the next cash crop. This thesis combines the use of field trials and a crop simulation model to address the research questions posed. In Chapter 1, field trials evaluating yield and harvest date of soybean maturity group (MG) cultivars from 0 to 4 in 13 site-years across KY, NE, and OH, were used to calibrate and evaluate the DSSAT crop modeling software (v 4.7). The subsequent modeling analysis showed that planting shorter soybean maturity groups (MG) would advance date of harvest maturity (R8) by 6.6 to 11 days per unit decrease in MG for May planting or by 1 to 7.3 days for July planting. The earliest MG cultivar that maximized yield ranged from MG 0 to 3 depending on the location, allowing a winter-killed cover crop to accumulate between 257 to 270 growing degree days (GDD) before the first freeze occurrence when soybean was planted in May, and between 280 to 296 GDD when soybean was planted in July. Winter-hardy cover crops could accumulate 701 to 802 GDD following soybean planted in May and 329 to 416 GDD after soybean planted in July. In Chapter 2, a two-year field trial was conducted at Lexington, KY to evaluate the effect of a soybean – cover crop rotation with soybean cultivars MG 1, 2, 3 or 4 on cover crop biomass and canopy cover, and on weed biomass in the fall and the following spring. Results showed that having cover crops was an efficient management strategy to reduce weed biomass in the fall and spring compared to no cover treatment. Planting cover crops earlier in the fall after a short-season soybean increased cover crop biomass production and percentage of ground cover in the fall, but not the following spring. Planting cover crop earlier after a short-season soybean did not improve weed suppression in the fall or spring compared to a fallow control with full-season soybean. Having a fall herbicide application improved weed control when there was a high pressure of winter annual weeds. By the spring, delaying cover crop termination increased cover crop biomass but also did weed biomass. In Chapter 3, a soybean – cover crop – corn rotation was simulated to evaluate the effect of different soybean MG and cover crop termination, as well as year to year variability on water and nitrogen availability for the next corn crop in Lexington, KY. Simulations showed that when cover crops were terminated early, they did not reduced soil available water at corn planting. However, introducing a non-legume cover crop reduced total inorganic nitrogen content in the soil profile by 21 to 34 kg ha-1 implying 15 to 30 kg ha-1 less in corn nitrogen uptake. Cover crop management that was able to maintain similar available water values than fallow treatment while minimizing nitrogen uptake differences was cover crops planted after soybean MG 4 with an early termination. However, the best management strategies that will maximize ecosystem services from cover crops as well as cash crop productivity may need to be tailored to each environment, soil type, irrigation management, and must consider year-to-year variability.

This diploma thesis describes the design and implementation of appropriate procedure photogrammetry processing of technical documentation of selected historical artifacts gauges. This thesis deals with finding the most suitable evaluation of the calibration of the camera used for metric artifacts documentation, processing documentation and model visualization.

Die Arbeit widmet sich der Entwicklung und numerischen Implementierung eines nichtlokalen kontinuumsmechanischen Schädigungsmodells zur Beschreibung des duktilen Versagens eines austenitischen TRIP-Stahlgusses. Dieser weist eine martensitische Phasenumwandlung während der Verformung auf. Das Umwandlungs- und Verfestigungsverhalten des Untersuchungswerkstoffs hängt stark von Temperatur und Spannungszustand ab. Deshalb wird ein vollständig thermomechanisch gekoppeltes Viskoplastizitätsmodell zugrunde gelegt, welches die temperaturabhängige Zug-Druck-Asymmetrie von Verfestigung und verformungsinduzierter Martensitentwicklung abbildet. Bei erhöhter Dehnrate können experimentell beobachtete Kreuzungseffekte der Fließkurven vorhergesagt werden. Die Schädigungsmodellierung baut auf dem viskoplastischen Grundmodell auf, wobei das netzunabhängige Verhalten durch eine Gradientenerweiterung im Rahmen der mikromorphen Theorie erreicht wird. Im Modell können verschiedene Ansätze für Schädigungsinitiierung und -entwicklung kombiniert werden. Die Einflüsse der Modellparameter auf die Ergebnisse von Risswachstumssimulationen werden für ausgewählte Modellvarianten untersucht und bewertet. Mithilfe erarbeiteter Kalibrierungsstrategien können die qualifizierten Varianten erfolgreich an experimentelle Ergebnisse von Kerbzugversuchen und bruchmechanischen Kompaktzugproben angepasst werden. / The present thesis comprises the development and numerical implementation of a non-local damage model in order to describe ductile failure of a cast austenitic TRIP-steel. The TRIP-steel shows a martensitic phase transformation during deformation. The transformation and strain hardening behavior is strongly dependent on temperature and stress state. For this reason, a fully thermomechanically coupled viscoplasticity model is proposed, which exhibits the temperature dependent tension-compression-asymmetry of strain hardening and deformation-induced martensite evolution. Experimentally observed crossing effects of the flow curves can be predicted at increased strain rates. The damage modeling is based on the viscoplastic basic model, whereby the mesh-independent behavior is achieved by a gradient extension within the framework of micromorphic theory. Different approaches for damage initiation and evolution can be combined within the model. The influences of the model parameters on results of crack growth simulations are investigated and evaluated for selected model variants. With the help of developed calibration strategies the qualified variants can be successfully adapted to experimental results of notched tensile tests and compact tension tests.

Agent-based simulation models are an important tool to study the effectiveness of policy interventions on the uptake of residential photovoltaic systems by households, a cornerstone of sustainable energy system transition. In order for these models to be trustworthy, they require rigorous validation. However, the canonical approach of validating emulation models through calibration with parameters that minimize the difference of model results and reference data fails when the model is subject to many stochastic influences. The residential photovoltaic diffusion model PVact features numerous stochastic influences that prevent straightforward optimization-driven calibration. From the analysis of the results of a case-study on the cities Dresden and Leipzig (Germany) based on three error metrics (mean average error, root mean square error and cumulative average error), this research identifies a parameter range where stochastic fluctuations exceed differences between results of different parameterization and a minimization-based calibration approach fails. Based on this observation, an approach is developed that aggregates model behavior across multiple simulation runs and parameter combinations to compare results between scenarios representing different future developments or policy interventions of interest.

Cette thèse porte sur les questions d'évaluation et de couverture des options dans un modèle exponentiel-Lévy avec changements de régime. Un tel modèle est construit sur un processus additif markovien un peu comme le modèle de Black- Scholes est basé sur un mouvement Brownien. Du fait de l'existence de plusieurs sources d'aléa, nous sommes en présence d'un marché incomplet et ce fait rend inopérant les développements théoriques initiés par Black et Scholes et Merton dans le cadre d'un marché complet. Nous montrons dans cette thèse que l'utilisation de certains résultats de la théorie des processus additifs markoviens permet d'apporter des solutions aux problèmes d'évaluation et de couverture des options. Notamment, nous arrivons à caracté- riser la mesure martingale qui minimise l'entropie relative à la mesure de probabilit é historique ; aussi nous dérivons explicitement sous certaines conditions, le portefeuille optimal qui permet à un agent de minimiser localement le risque quadratique associé. Par ailleurs, dans une perspective plus pratique nous caract érisons le prix d'une option Européenne comme l'unique solution de viscosité d'un système d'équations intégro-di érentielles non-linéaires. Il s'agit là d'un premier pas pour la construction des schémas numériques pour approcher ledit prix. / This thesis focuses on the pricing and hedging problems of financial derivatives in a Markov-modulated exponential-Lévy model. Such model is built on a Markov additive process as much as the Black-Scholes model is based on Brownian motion. Since there exist many sources of randomness, we are dealing with an incomplete market and this makes inoperative techniques initiated by Black, Scholes and Merton in the context of a complete market. We show that, by using some results of the theory of Markov additive processes it is possible to provide solutions to the previous problems. In particular, we characterize the martingale measure which minimizes the relative entropy with respect to the physical probability measure. Also under some conditions, we derive explicitly the optimal portfolio which allows an agent to minimize the local quadratic risk associated. Furthermore, in a more practical perspective we characterize the price of a European type option as the unique viscosity solution of a system of nonlinear integro-di erential equations. This is a rst step towards the construction of e ective numerical schemes to approximate options price.

Agricultural system models integrate many different processes that cannot all be measured in field experiments and help quantify soil water dynamics, crop evapotranspiration, and crop growth with high temporal resolution. Understanding soil water dynamics and crop evapotranspiration is essential to improve agricultural management of field crops. For example, the interaction between nitrogen application rate and water dynamics is not sufficiently understood. In most cases, model simulations deviate from field measurements, especially when model input parameters are indirectly and unspecifically derived. The extent to which measured soil hydraulic property inputs decrease the discrepancy between measured and simulated soil water status is not well understood. Consequently, this study: (i) investigated thr use of measured soil hydraulic properties as Root Zone Water Quality Model (RZWQM2) inputs compared to indirectly derived inputs; (ii) explored the capability of calibrating measured soil hydraulic property input parameters for one crop and using them for other crops without further calibration; (iii) studied the effect of the nitrogen application rate on the behavior of soil water dynamics and crop evapotranspiration using RZWQM2 under different rainfall amounts. To evaluate the model in different field management conditions, a field experiment with soybean, corn, wheat, and fallow soil was conducted from 2015 – 2017 to collect field data to calibrate and validate the RZWQM2 model. The model presented a satisfactory response to using measured soil hydraulic property inputs and a satisfactory capability to quantify the effect of nitrogen rates on daily crop evapotranspiration, soil water dynamics, and crop growth. With sufficient measurements of soil hydraulic parameters, it was possible to build a RZWQM2 model that produced reasonable results even without calibration.