4 resultados para process optimization

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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In a world focused on the need to produce energy for a growing population, while reducing atmospheric emissions of carbon dioxide, organic Rankine cycles represent a solution to fulfil this goal. This study focuses on the design and optimization of axial-flow turbines for organic Rankine cycles. From the turbine designer point of view, most of this fluids exhibit some peculiar characteristics, such as small enthalpy drop, low speed of sound, large expansion ratio. A computational model for the prediction of axial-flow turbine performance is developed and validated against experimental data. The model allows to calculate turbine performance within a range of accuracy of ±3%. The design procedure is coupled with an optimization process, performed using a genetic algorithm where the turbine total-to-static efficiency represents the objective function. The computational model is integrated in a wider analysis of thermodynamic cycle units, by providing the turbine optimal design. First, the calculation routine is applied in the context of the Draugen offshore platform, where three heat recovery systems are compared. The turbine performance is investigated for three competing bottoming cycles: organic Rankine cycle (operating cyclopentane), steam Rankine cycle and air bottoming cycle. Findings indicate the air turbine as the most efficient solution (total-to-static efficiency = 0.89), while the cyclopentane turbine results as the most flexible and compact technology (2.45 ton/MW and 0.63 m3/MW). Furthermore, the study shows that, for organic and steam Rankine cycles, the optimal design configurations for the expanders do not coincide with those of the thermodynamic cycles. This suggests the possibility to obtain a more accurate analysis by including the computational model in the simulations of the thermodynamic cycles. Afterwards, the performance analysis is carried out by comparing three organic fluids: cyclopentane, MDM and R245fa. Results suggest MDM as the most effective fluid from the turbine performance viewpoint (total-to-total efficiency = 0.89). On the other hand, cyclopentane guarantees a greater net power output of the organic Rankine cycle (P = 5.35 MW), while R245fa represents the most compact solution (1.63 ton/MW and 0.20 m3/MW). Finally, the influence of the composition of an isopentane/isobutane mixture on both the thermodynamic cycle performance and the expander isentropic efficiency is investigated. Findings show how the mixture composition affects the turbine efficiency and so the cycle performance. Moreover, the analysis demonstrates that the use of binary mixtures leads to an enhancement of the thermodynamic cycle performance.

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Globalization has increased the pressure on organizations and companies to operate in the most efficient and economic way. This tendency promotes that companies concentrate more and more on their core businesses, outsource less profitable departments and services to reduce costs. By contrast to earlier times, companies are highly specialized and have a low real net output ratio. For being able to provide the consumers with the right products, those companies have to collaborate with other suppliers and form large supply chains. An effect of large supply chains is the deficiency of high stocks and stockholding costs. This fact has lead to the rapid spread of Just-in-Time logistic concepts aimed minimizing stock by simultaneous high availability of products. Those concurring goals, minimizing stock by simultaneous high product availability, claim for high availability of the production systems in the way that an incoming order can immediately processed. Besides of design aspects and the quality of the production system, maintenance has a strong impact on production system availability. In the last decades, there has been many attempts to create maintenance models for availability optimization. Most of them concentrated on the availability aspect only without incorporating further aspects as logistics and profitability of the overall system. However, production system operator’s main intention is to optimize the profitability of the production system and not the availability of the production system. Thus, classic models, limited to represent and optimize maintenance strategies under the light of availability, fail. A novel approach, incorporating all financial impacting processes of and around a production system, is needed. The proposed model is subdivided into three parts, maintenance module, production module and connection module. This subdivision provides easy maintainability and simple extendability. Within those modules, all aspect of production process are modeled. Main part of the work lies in the extended maintenance and failure module that offers a representation of different maintenance strategies but also incorporates the effect of over-maintaining and failed maintenance (maintenance induced failures). Order release and seizing of the production system are modeled in the production part. Due to computational power limitation, it was not possible to run the simulation and the optimization with the fully developed production model. Thus, the production model was reduced to a black-box without higher degree of details.

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Nowadays the number of hip joints arthroplasty operations continues to increase because the elderly population is growing. Moreover, the global life expectancy is increasing and people adopt a more active way of life. For this reasons, the demand of implant revision operations is becoming more frequent. The operation procedure includes the surgical removal of the old implant and its substitution with a new one. Every time a new implant is inserted, it generates an alteration in the internal femur strain distribution, jeopardizing the remodeling process with the possibility of bone tissue loss. This is of major concern, particularly in the proximal Gruen zones, which are considered critical for implant stability and longevity. Today, different implant designs exist in the market; however there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. The aim of the study is to investigate the stress shielding effect generated by different implant design parameters on proximal femur, evaluating which ranges of those parameters lead to the most physiological conditions.