4 resultados para Choice under complete uncertainty
em AMS Tesi di Laurea - Alm@DL - Università di Bologna
Resumo:
The aim of this work is to present a general overview of state-of-the-art related to design for uncertainty with a focus on aerospace structures. In particular, a simulation on a FCCZ lattice cell and on the profile shape of a nozzle will be performed. Optimization under uncertainty is characterized by the need to make decisions without complete knowledge of the problem data. When dealing with a complex problem, non-linearity, or optimization, two main issues are raised: the uncertainty of the feasibility of the solution and the uncertainty of the objective value of the function. In the first part, the Design Of Experiments (DOE) methodologies, Uncertainty Quantification (UQ), and then Uncertainty optimization will be deepened. The second part will show an application of the previous theories on through a commercial software. Nowadays multiobjective optimization on high non-linear problem can be a powerful tool to approach new concept solutions or to develop cutting-edge design. In this thesis an effective improvement have been reached on a rocket nozzle. Future work could include the introduction of multi scale modelling, multiphysics approach and every strategy useful to simulate as much possible real operative condition of the studied design.
Resumo:
In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.
Resumo:
In recent years, global supply chains have increasingly suffered from reliability issues due to various external and difficult to-manage events. The following paper aims to build an integrated approach for the design of a Supply Chain under the risk of disruption and demand fluctuation. The study is divided in two parts: a mathematical optimization model, to identify the optimal design and assignments customer-facility, and a discrete-events simulation of the resulting network. The first one describes a model in which plant location decisions are influenced by variables such as distance to customers, investments needed to open plants and centralization phenomena that help contain the risk of demand variability (Risk Pooling). The entire model has been built with a proactive approach to manage the risk of disruptions assigning to each customer two types of open facilities: one that will serve it under normal conditions and a back-up facility, which comes into operation when the main facility has failed. The study is conducted on a relatively small number of instances due to the computational complexity, a matheuristic approach can be found in part A of the paper to evaluate the problem with a larger set of players. Once the network is built, a discrete events Supply Chain simulation (SCS) has been implemented to analyze the stock flow within the facilities warehouses, the actual impact of disruptions and the role of the back-up facilities which suffer a great stress on their inventory due to a large increase in demand caused by the disruptions. Therefore, simulation follows a reactive approach, in which customers are redistributed among facilities according to the interruptions that may occur in the system and to the assignments deriving from the design model. Lastly, the most important results of the study will be reported, analyzing the role of lead time in a reactive approach for the occurrence of disruptions and comparing the two models in terms of costs.
Resumo:
Bone is continually being removed and replaced through the actions of basic multicellular units (BMU). This constant upkeep is necessary to remove microdamage formed naturally due to fatigue and thus maintain the integrity of the bone. The repair process in bone is targeted, meaning that a BMU travels directly to the site of damage and repairs it. It is still unclear how targeted remodelling is stimulated and directed but it is highly likely that osteocytes play a role. A number of theories have been advanced to explain the microcrack osteocyte interaction but no complete mechanism has been demonstrated. Osteocytes are connected to each other by dendritic processes. The “scissors model" proposed that the rupture of these processes where they cross microcracks signals the degree of damage and the urgency of the necessary repair. In its original form it was proposed that under applied compressive loading, microcrack faces will be pressed together and undergo relative shear movement. If this movement is greater than the width of an osteocyte process, then the process will be cut in a “scissors like" motion, releasing RANKL, a cytokine known to be essential in the formation of osteoclasts from pre-osteoclasts. The main aim of this thesis was to investigate this theoretical model with a specific focus on microscopy and finite element modelling. Previous studies had proved that cyclic stress was necessary for osteocyte process rupture to occur. This was a divergence from the original “scissors model" which had proposed that the cutting of cell material occurred in one single action. The present thesis is the first study to show fatigue failure in cellular processes spanning naturally occurring cracks and it's the first study to estimate the cyclic strain range and relate it to the number of cycles to failure, for any type of cell. Rupture due to shear movement was ruled out as microcrack closing never occurred, as a result of plastic deformation of the bone. Fatigue failure was found to occur due to cyclic tensile stress in the locality of the damage. The strain range necessary for osteocyte process rupture was quantified. It was found that the lower the process strain range the greater the number of cycles to cell process failure. FEM modelling allowed to predict stress in the vicinity of an osteocyte process and to analyse its interaction with the bone surrounding it: simulations revealed evident creep effects in bone during cyclic loading. This thesis confirms and dismisses aspects of the “scissors model". The observations support the model as a viable mechanism of microcrack detection by the osteocyte network, albeit in a slightly modified form where cyclic loading is necessary and the method of rupture is fatigue failure due to cyclic tensile motion. An in depth study was performed focusing on microscopy analysis of naturally occurring cracks in bone and FEM simulation analysis of an osteocyte process spanning a microcrack in bone under cyclic load.