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1	Applications of Contact Length Models in Grinding Processes Qi, Hong Sheng, Mills, B., Xu, X.P. January 2009 (has links) yes / The nature of the contact behaviour between a grinding wheel and a workpiece in the grinding process has a great effect on the grinding temperature and the occurrence of thermal induced damage on the ground workpiece. It is found that the measured contact length le in grinding is considerably longer than the geometric contact length lg and the contact length due to wheel-workpiece deflection lf. The orthogonal relationship among the contact lengths, i.e. lc2 = (Rrlf)2 + lg2, reveals how the grinding force and grinding depth of cut affect the overall contact length between a grinding wheel and a workpiece in grinding processes. To make the orthogonal contact length model easy to use, attempts on modification of the model are carried out in the present study, in which the input variable of the model, Fn’, is replaced by a well-established empirical formula and specific grinding power. By applying the modified model in this paper, an analysis on the contributions of the individual factors, i.e. the wheel/workpiece deformation and the grinding depth of cut, on the overall grinding contact length is conducted under a wide range of grinding applications, i.e. from precise/shallow grinding to deep/creep-feed grinding. Finally, using a case study, the criterion of using geometric contact length lg to represent the real contact length lc, in terms of convenience versus accuracy, is discussed.
2	Parameter Estimation of Complex Systems from Sparse and Noisy Data Chu, Yunfei 2010 December 1900 (has links) Mathematical modeling is a key component of various disciplines in science and engineering. A mathematical model which represents important behavior of a real system can be used as a substitute for the real process for many analysis and synthesis tasks. The performance of model based techniques, e.g. system analysis, computer simulation, controller design, sensor development, state filtering, product monitoring, and process optimization, is highly dependent on the quality of the model used. Therefore, it is very important to be able to develop an accurate model from available experimental data. Parameter estimation is usually formulated as an optimization problem where the parameter estimate is computed by minimizing the discrepancy between the model prediction and the experimental data. If a simple model and a large amount of data are available then the estimation problem is frequently well-posed and a small error in data fitting automatically results in an accurate model. However, this is not always the case. If the model is complex and only sparse and noisy data are available, then the estimation problem is often ill-conditioned and good data fitting does not ensure accurate model predictions. Many challenges that can often be neglected for estimation involving simple models need to be carefully considered for estimation problems involving complex models. To obtain a reliable and accurate estimate from sparse and noisy data, a set of techniques is developed by addressing the challenges encountered in estimation of complex models, including (1) model analysis and simplification which identifies the important sources of uncertainty and reduces the model complexity; (2) experimental design for collecting information-rich data by setting optimal experimental conditions; (3) regularization of estimation problem which solves the ill-conditioned large-scale optimization problem by reducing the number of parameters; (4) nonlinear estimation and filtering which fits the data by various estimation and filtering algorithms; (5) model verification by applying statistical hypothesis test to the prediction error. The developed methods are applied to different types of models ranging from models found in the process industries to biochemical networks, some of which are described by ordinary differential equations with dozens of state variables and more than a hundred parameters. parameter estimation systems identification parameter selection design of experiments ill-conditioned problems mathematical modeling sensitivity analysis model simplification
3	A Systems Biology Approach to Develop Models of Signal Transduction Pathways Huang, Zuyi 2010 August 1900 (has links) Mathematical models of signal transduction pathways are characterized by a large number of proteins and uncertain parameters, yet only a limited amount of quantitative data is available. The dissertation addresses this problem using two different approaches: the first approach deals with a model simplification procedure for signaling pathways that reduces the model size but retains the physical interpretation of the remaining states, while the second approach deals with creating rich data sets by computing transcription factor profiles from fluorescent images of green-fluorescent-protein (GFP) reporter cells. For the first approach a model simplification procedure for signaling pathway models is presented. The technique makes use of sensitivity and observability analysis to select the retained proteins for the simplified model. The presented technique is applied to an IL-6 signaling pathway model. It is found that the model size can be significantly reduced and the simplified model is able to adequately predict the dynamics of key proteins of the signaling pathway. An approach for quantitatively determining transcription factor profiles from GFP reporter data is developed as the second major contribution of this work. The procedure analyzes fluorescent images to determine fluorescence intensity profiles using principal component analysis and K-means clustering, and then computes the transcription factor concentration from the fluorescence intensity profiles by solving an inverse problem involving a model describing transcription, translation, and activation of green fluorescent proteins. Activation profiles of the transcription factors NF-κB, nuclear STAT3, and C/EBPβ are obtained using the presented approach. The data for NF-κB is used to develop a model for TNF-α signal transduction while the data for nuclear STAT3 and C/EBPβ is used to verify the simplified IL-6 model. Finally, an approach is developed to compute the distribution of transcription factor profiles among a population of cells. This approach consists of an algorithm for identifying individual fluorescent cells from fluorescent images, and an algorithm to compute the distribution of transcription factor profiles from the fluorescence intensity distribution by solving an inverse problem. The technique is applied to experimental data to derive the distribution of NF-κB concentrations from fluorescent images of a NF-κB GFP reporter system. Fluorescent microscopy image analysis IL-6 signaling pathway Inverse problem K-means clustering Model simplification Mathematical modeling Observability analysis Principal component analysis Sensitivity analysis TNF-α signal transduction Transcription factor profiles
4	Modélisation d'un robot manipulateur en vue de la commande robuste en force utilisé en soudage FSW / Robot manipulator modeling for robust force control used in Friction Stir Welding (FSW) Wang, Ke 28 January 2016 (has links) Le travail présenté dans cette thèse concerne la modélisation et la commande robuste en force de robots manipulateurs industriels à articulations flexibles utilisés pour le procédé FSW. Afin de réduire les temps de calcul et l'occupation de la mémoire, une approche basée sur la méthode par intervalle est proposée en vue de la simplification des modèles dynamiques des robots industriels, et contribue à identifier les paramètres d'inertie qui sont négligeables. Des études de cas sur trois types de trajectoires de test et l’analyse des couples moteurs ont démontré l'efficacité et les bonnes performances de la méthode de simplification. Ensuite, la modélisation dynamique et l'identification des paramètres du procédé FSW ont été effectuées. Les paramètres des modèles linéaires et non-linéaires de forces axiales sont identifiés. Sur la base de la modélisation du procédé FSW qui considère simultanément la cinématique du système complet, le modèle de déplacement du robot rigide, les flexibilités des articulations et le modèle dynamique de la force axiale, un contrôleur robuste en force est obtenu par la méthode de réglage fréquentielle. En outre, un simulateur du procédé FSW robotique est développé et les résultats de simulation montrent les bonnes performances du contrôleur en force. L'oscillation de la force axiale dans le procédé FSW peut être simulée en utilisant un modèle de perturbation de la position verticale de référence. / The work presented in this thesis focuses on the modeling and robust force control of flexible joints industrial robot manipulators used for FSW process. In order to reduce computation time and memory occupation, a novel interval-based approach for dynamic model simplification of industrial robots is proposed, which applies to arbitrary trajectories of whole robot workspace and contributes to obtaining negligible inertia parameters. Cases studies have been carried out on three kinds of test trajectories and torques analysis of robot dynamic equation, demonstrating the effectiveness and good performance of the simplification method. Then, the dynamic modeling and identification of robotic FSW process is performed, and the parameters of linear and nonlinear dynamic axial force process models are identified by using the plunge depth and its derivative. On the basis of the modeling of robotic FSW process which simultaneously considers the complete kinematics, the rigid robot displacement model, the joint flexibility and the dynamic axial force process model, a robust force controller can be obtained by using the frequency response approach. Besides, a simulator of robotic FSW process is developed and simulation results show good performance of the force controller. The oscillation of axial force in FSW process can be simulated when a disturbance model of initial vertical reference position is proposed and used in the simulation. Commande robuste en force Simplification de modèles dynamiques Robust force control Dynamic model simplification Robot Cartesian model identification
5	Birds, bats and arthropods in tropical agroforestry landscapes: Functional diversity, multitrophic interactions and crop yield Maas, Bea 20 November 2013 (has links) No description available. 630 birds bats arthropods multitrophic interactions agroforestry tropical landscape forest margin landscape functional diversity crop yield exclosure experiments experimental exclusion arthropod suppression avian predation ecosystem services mist netting point counts artificial plasticine caterpillar dummy experiment biological control monitoring mapping Lemon-bellied White-eye Grosbeak Starling Zosterops chloris Scissiostrum dubium Theobroma cacao cacao agroforestry cacao diseases cacao harvest cacao pests flying vertebrates aerial insectivores volant vertebrates logging breeding colony flower herbivory mesopredator release predatory insects ants spiders aphids Lepidoptera Coleoptera Lepidopteran larvae sustainable agriculture sustainable agroforestry management implications management recommendations applied managament extensive land use management landscape management conservation biodiversity-friendly dbh distance to forest forest proximity habitat conversion herbivory Indonesia insectivorous bats insectivorous birds invertebrates Central Sulawesi Napu valley leaf gleaning leaf herbivory pests insects phytophagous insects plant productivity remnant forest trees shade tree managament South-east Asia Paleotropics tropical landscape tree height landscape gradient local shade management Cacao Pod Borer Cherelle Wilt fruit abortion Helopeltis sulawesi deforestation habitat fragmentation land use intensification forest margin species critical decline predation experiment species-specific functions Southeast Asia biodiversity conservation mesopredators food security human welfare human well-being poverty alleviation poverty reduction smallholder cacao smallholder plantation cacao farmers sustainable cacao management landscape perspective landscape scale large scale field experiment long term field experiment human wellbeing economic importance economic value valuation ecosystem services landscape matrix yield quality yield quantity fruit productivity species identity species diversity species richness ecosystem functioning pesticide use chemical compounds complex food web tritrophic interactions wildlife-friendly rural livelihoods endangered bird species endangered bat species endemic endemic birds endemic bats beneficial impact IUCN Lore Lindu National Park bioindicator indicator species forest margin agricultural habitat agroforestry systems population density predation activity species activity cacao flower cacao pod Orthoptera linear mixed effect models Tukey Post Hoc Test AICc model selection generalized least squares restricted maximum likelihood model simplification species richness estimator species accumulation linear mixed-effects models Likelihood Ratio Test Maximum Likelihood nocturnal insects diurnal arthropods nocturnal arthropods diurnal insects landscape context Land- und Forstwirtschaft (PPN621302791)

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