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Management strategies for sustainable sugarcane production need to deal with the increasing complexity and variability of the whole sugar system. Moreover, they need to accommodate the multiple goals of different industry sectors and the wider community. Traditional disciplinary approaches are unable to provide integrated management solutions, and an approach based on whole systems analysis is essential to bring about beneficial change to industry and the community. The application of this approach to water management, environmental management and cane supply management is outlined, where the literature indicates that the application of extreme learning machine (ELM) has never been explored in this realm. Consequently, the leading objective of the current research was set to filling this gap by applying ELM to launch swift and accurate model for crop production data-driven. The key learning has been the need for innovation both in the technical aspects of system function underpinned by modelling of sugarcane growth. Therefore, the current study is an attempt to establish an integrate model using ELM to predict the concluding growth amount of sugarcane. Prediction results were evaluated and further compared with artificial neural network (ANN) and genetic programming models. Accuracy of the ELM model is calculated using the statistics indicators of Root Means Square Error (RMSE), Pearson Coefficient (r), and Coefficient of Determination (R2) with promising results of 0.8, 0.47, and 0.89, respectively. The results also show better generalization ability in addition to faster learning curve. Thus, proficiency of the ELM for supplementary work on advancement of prediction model for sugarcane growth was approved with promising results.
Polymer-modified cement concrete (PCC) is a heterogeneous building material with a hierarchically organized microstructure. Therefore, continuum micromechanics-based multiscale models represent a promising method to estimate the mechanical properties. By means of a bottom-up approach, homogenized properties at the macroscopic scale are derived considering microstructural characteristics. The extension of existing multiscale models for the application to PCC is the main objective of this work. For that, cross-scale experimental studies are required. Both macroscopic and microscopic mechanical tests are performed to characterize the elastic and viscoelastic properties of different PCC. The comparison between experiment and model prediction illustrates the success of the modeling approach.
Polymeric nanocomposites (PNCs) are considered for numerous nanotechnology such as: nano-biotechnology, nano-systems, nanoelectronics, and nano-structured materials. Commonly , they are formed by polymer (epoxy) matrix reinforced with a nanosized filler. The addition of rigid nanofillers to the epoxy matrix has offered great improvements in the fracture toughness without sacrificing other important thermo-mechanical properties. The physics of the fracture in PNCs is rather complicated and is influenced by different parameters. The presence of uncertainty in the predicted output is expected as a result of stochastic variance in the factors affecting the fracture mechanism. Consequently, evaluating the improved fracture toughness in PNCs is a challenging problem.
Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have been employed to predict the fracture energy of polymer/particle nanocomposites. The ANN and ANFIS models were constructed, trained, and tested based on a collection of 115 experimental datasets gathered from the literature. The performance evaluation indices of the developed ANN and ANFIS showed relatively small error, with high coefficients of determination (R2), and low root mean square error and mean absolute percentage error.
In the framework for uncertainty quantification of PNCs, a sensitivity analysis (SA) has been conducted to examine the influence of uncertain input parameters on the fracture toughness of polymer/clay nanocomposites (PNCs). The phase-field approach is employed to predict the macroscopic properties of the composite considering six uncertain input parameters. The efficiency, robustness, and repeatability are compared and evaluated comprehensively for five different SA methods.
The Bayesian method is applied to develop a methodology in order to evaluate the performance of different analytical models used in predicting the fracture toughness of polymeric particles nanocomposites. The developed method have considered the model and parameters uncertainties based on different reference data (experimental measurements) gained from the literature. Three analytical models differing in theory and assumptions were examined. The coefficients of variation of the model predictions to the measurements are calculated using the approximated optimal parameter sets. Then, the model selection probability is obtained with respect to the different reference data.
Stochastic finite element modeling is implemented to predict the fracture toughness of polymer/particle nanocomposites. For this purpose, 2D finite element model containing an epoxy matrix and rigid nanoparticles surrounded by an interphase zone is generated. The crack propagation is simulated by the cohesive segments method and phantom nodes. Considering the uncertainties in the input parameters, a polynomial chaos expansion (PCE) surrogate model is construed followed by a sensitivity analysis.
Increasing structural robustness is the goal which is of interest for structural engineering community. The partial collapse of RC buildings is subject of this dissertation. Understanding the robustness of RC buildings will guide the development of safer structures against abnormal loading scenarios such as; explosions, earthquakes, fine, and/or long-term accumulation effects leading to deterioration or fatigue. Any of these may result in local immediate structural damage, that can propagate to the rest of the structure causing what is known by the disproportionate collapse.
This work handels collapse propagation through various analytical approaches which simplifies the mechanical description of damaged reinfoced concrete structures due to extreme acidental event.
Die hier vorliegende Arbeit befasst sich mit dem Modifizieren von Computerspielen (Modding). Die Annäherung an das Modding geschieht aus zwei unterschiedlichen Blickrichtungen: Zum einen wird mit einem analytischen Blick auf das Themenfeld geschaut, der das bereits Erforschte mit den eigenen Suchbewegungen kombiniert. Zum anderen wird die Perspektive der Handlung eingenommen, die sich in der Widerständigkeit des Materials, der Werkzeuge und der Spieltechnologie äußert. Im Mittelpunkt der Auseinandersetzung stehen das Modding als Praxis, die Mods als Derivate und die Erforschung des Computerspiels mit den Praktiken und Derivaten des Modifizierens. Das Modding wird so zu einer epistemischen Praxis des Computerspiels.
Die hier formulierten Überlegungen zum Modding, als eine forschende Praxis des Computerspiels, präsentieren eine Vorgehensweise, die ästhetische, widerständige und stabilisierende Aspekte in sich vereint. Sie dient der Erforschung des Computerspiels entlang seiner Diskussionen, Materialien, Technologien und Praktiken und fokussiert hierbei auf das Abseitige, dass als integraler Bestandteil des Computerspiels verstanden wird. Mit diesem Blick auf die Grenzen des Computerspielens werden Dinge sichtbar, die zwar Teil der synthetischen Computerspielwelten sind, durch dessen Inszenierungen und Atmosphären jedoch verschleiert werden. Der hier entwickelte Ansatz ermöglicht einen Perspektivenwechsel innerhalb dieser Welten und die Erforschung des Computerspiels unter besonderer Berücksichtigung seiner eingeschriebenen Normen und Machtverhältnissen. Das Modding dient hierbei als eine kritische Praxis zur Entschlüsselung dieser medial vermittelten Konstellationen.
This cumulative dissertation discusses - by the example of four subsequent publications - the various layers of a tangible interaction framework, which has been developed in conjunction with an electronic musical instrument with a tabletop tangible user interface. Based on the experiences that have been collected during the design and implementation of that particular musical application, this research mainly concentrates on the definition of a general-purpose abstraction model for the encapsulation of physical interface components that are commonly employed in the context of an interactive surface environment. Along with a detailed description of the underlying abstraction model, this dissertation also describes an actual implementation in the form of a detailed protocol syntax, which constitutes the common element of a distributed architecture for the construction of surface-based tangible user interfaces. The initial implementation of the presented abstraction model within an actual application toolkit is comprised of the TUIO protocol and the related computer-vision based object and multi-touch tracking software reacTIVision, along with its principal application within the Reactable synthesizer. The dissertation concludes with an evaluation and extension of the initial TUIO model, by presenting TUIO2 - a next generation abstraction model designed for a more comprehensive range of tangible interaction platforms and related application scenarios.
Long-span bridges are prone to wind-induced vibrations. Therefore, a reliable representation of the aerodynamic forces acting on a bridge deck is of a major significance for the design of such structures. This paper presents a systematic study of the two-dimensional (2D) fluid-structure interaction of a bridge deck under smooth and turbulent wind conditions. Aerodynamic forces are modeled by two approaches: a computational fluid dynamics (CFD) model and six semi-analytical models. The vortex particle method is utilized for the CFD model and the free-stream turbulence is introduced by seeding vortex particles upstream of the deck with prescribed spectral characteristics. The employed semi-analytical models are based on the quasi-steady and linear unsteady assumptions and aerodynamic coefficients obtained from CFD analyses.
The underlying assumptions of the semi-analytical aerodynamic models are used to interpret the results of buffeting forces and aeroelastic response due to a free-stream turbulence in comparison with the CFD model. Extensive discussions are provided to analyze the effect of linear fluid memory and quasi-steady nonlinearity from a CFD perspective. The outcome of the analyses indicates that the fluid memory is a governing effect in the buffeting forces and aeroelastic response, while the effect of the nonlinearity is overestimated by the quasi-steady models. Finally, flutter analyses are performed and the obtained critical velocities are further compared with wind tunnel results, followed by a brief examination of the post-flutter behavior. The results of this study provide a deeper understanding of the extent of which the applied models are able to replicate the physical processes for fluid-structure interaction phenomena in bridge aerodynamics and aeroelasticity.
The accurate representation of aerodynamic forces is essential for a safe, yet reasonable design of long-span bridges subjected to wind effects. In this paper, a novel extension of the Pseudo-three-dimensional Vortex Particle Method (Pseudo-3D VPM) is presented for Computational Fluid Dynamics (CFD) buffeting analysis of line-like structures. This extension entails an introduction of free-stream turbulent fluctuations, based on the velocity-based turbulence generation. The aerodynamic response of a long-span bridge is obtained by subjecting the 3D dynamic representation of the structure to correlated free-stream turbulence in two-dimensional (2D) fluid planes, which are positioned along the bridge deck. The span-wise correlation of the free-stream turbulence between the 2D fluid planes is established based on Taylor's hypothesis of frozen turbulence. Moreover, the application of the laminar Pseudo-3D VPM is extended to a multimode flutter analysis. Finally, the structural response from the Pseudo-3D flutter and buffeting analyses is verified with the response, computed using the semi-analytical linear unsteady model in the time-domain. Meaningful merits of the turbulent Pseudo-3D VPM with respect to the linear unsteady model are the consideration of the 2D aerodynamic nonlinearity, nonlinear fluid memory, vortex shedding and local non-stationary turbulence effects in the aerodynamic forces. The good agreement of the responses for the two models in the 3D analyses demonstrates the applicability of the Pseudo-3D VPM for aeroelastic analyses of line-like structures under turbulent and laminar free-stream conditions.