Ângela Silva

Thermal-economic optimisation of a CHP gas turbine system by applying a fit-problem genetic algorithm

ABSTRACT Cogeneration allows the optimal use of the primary energy sources and significant reductions in carbon emissions. Its use has great potential for applications in the residential sector. This study aims to develop a methodology for thermal-economic optimisation of small-scale micro-gas turbine for cogeneration purposes, able to fulfil domestic energy needs with a thermal power out of 125 kW. A constrained non-linear optimisation model was built. The objective function is the maximisation of the annual worth from the combined heat and power, representing the balance between the annual incomes and the expenditures subject to physical and economic constraints. A genetic algorithm coded in the java programming language was developed. An optimal micro-gas turbine able to produce 103.5 kW of electrical power with a positive annual profit (i.e. 11,925 €/year) was disclosed. The investment can be recovered in 4 years and 9 months, which is less than half of system lifetime expectancy.

Reverse Logistics Companies’ Perspective: A Qualitative Analysis

Reverse Logistics has been object of great interest essentially in the consumer’s culture change, in the competitiveness and in the increased environmental, and obviously due to its economic potential. In Portugal, Reverse Logistics is an unfamiliar word in the business world, specifically in SMEs. The present research focus to describe the Portuguese companies’ standpoint and knowledge based on two aspects: the concept and the return of products. To verify the different companies’ perspectives, semi structured interviews were applied in ten Portuguese Companies, of different size and in diverse industrial sectors. The qualitative data analysis was developed with the support of the webQDA software. The interviews analysis gave the opportunity to understand that large companies are aware of Reverse Logistics, in contrast to the SMEs’ scarce knowledge. Related to the Reverse Logistics strategies applied to the product returns, this research has showed that the reuse of the products or their sale to the scrap or recycling industries as the most common strategies, although some particularities depending on the type of industry.

CFD Simulation of Two-Phase Flow in a Large Scale Venturi Scrubber

Venturi scrubbers are very attractive devices for gas cleaning in industrial facilities, from small scale textile plants to large scale power plants. They may also be used combining the cleaning capabilities with cooling and humidification process.The difficulty in studying venturi scrubbers arises from the complexity of its flow. It is a multiphase mixture of gas, droplets, and dust particles with multiple interactions between the various phases including: liquid atomization, droplet breakup, collision and coalescence, in addition to interactions between liquid droplets and dust particles.Amongst the various (phenomenological) models that have been proposed, the authors have developed an integral boundary layer model, applicable to the diverging section of the venturi. This has proved to be very successful in predicting the pressure drop for a wide range of venturis.Because phenomenological methods have limits on the performance prediction when the venturi geometry or the operation condition changes, attempts have been made to implement other computational models in venturi scrubbers. Computational Fluid Dynamics techniques can provide detailed information of the flow pattern in the venturi. The present paper reports the development of an Eulerian-Lagrangian model for the two phase flow in a large-scale venturi with a diameter ratio of 122.5/250 mm and the half angles for the converging and diverging sections are 17° and 5°, respectively.The experimental data are published elsewhere and are used in the present work to validate the CFD model presented.© 2013 ASME