- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Heat transfer between different processes or inter-plant heat integration can be seen as an efficient way to cost-efficiently improve the energy efficiency of a system of different processes. Nanofluids are a new type of heat transfer fluids, in which particles with size of 1-100 nm are suspended in a liquid. Nanosized particles can cause considerable enhancement in convective heat transfer performance of the base fluid, although at the same time they increase the viscosity of the fluid, thus enhancing the needed pumping power. In this work we study the effect of using nanofluids in streams transferring heat from different processes by optimizing the total annual cost of a heat exchanger network. These costs include the cost of hot and cold utilities, heat exchanger investment costs and pumping costs. A modified version of the well-known Synheat superstructure is used as the optimization model in comparing the different fluids (water and five nanofluids) in two examples. Some key parameters (electricity price and annuity factor) are varied in these two examples. The results show that nanofluids can in some cases save total annual costs and especially if electricity prices are low compared to other factors. This is true especially for MgO 1.0% which outperformed water and the other nanofluids in normal price conditions. But altogether it is evident that most, and in some cases all, of the benefits provided by nanofluids to improved heat transfer is canceled out by the increased pressure drops.
Inter-plant heat exchanging is a means to improve the energy efficiency of a system of different processes in a cost-efficient manner so that the inter-plant heat exchange can be prioritized. In this work the effect of using nanofluids in streams transferring heat from different processes by optimizing the total cost of a heat exchanger network is studied. A superstructure approach is used in the model where te objective is to minimize the total annual cost (energy and investments) of the network. In the model used for this analysis heat can be transferred directly between process streams in the same process and using intermediate streams for heat transfer between different processes. The intermediate streams are process streams, but these are the only streams whose heat can be transferred to other processes. These intermediate streams are the ones were different fluids are tested.
The model has been used to solve two problems. Additionally some key parameters (electricity cost and annuity factor) are varied to analyze their effect on the solution. The results show that nanofluids, especially MgO 1.0% can improve total annual costs when used as intermediate streams, especially if electricity costs are small compared to other costs. With normal electricity prices and when investment cost (money costs) are normal, most, or even, all of the benefits of saving heat transfer area goes into increased pumping costs. But when electricity is cheap, nanofluids seem to provide cost savings. All together it is clear that the choice of an optimal nanofluid is case dependent. As a future work, it would be interesting to see are there any benefits to mix nano materials with special fluids intended for heat transfer and to optimize these mixtures for specific applications.