Techno-Economic Analysis and Multi-Objective Optimization of Cross-Flow Wind Turbines for Smart Building Energy Systems.

This work reports a technical, economic, and environmental investigation of the possibility of using a recently developed smallscale crossflow wind turbine (CFWT) to supply the energy demand of buildings for different integration scenarios. For this purpose, three CFWT-assisted building energy system configurations with heat pumps, with and without batteries, and two-way interaction with the local grid in two residential building models in Iran and Germany are investigated. Triobjective optimization with a Nondominated Sorting Genetic Algorithm (NSGA-II) is performed for finding the optimal configuration of the energy system in different configurations. For economic assessment, the Capital Budgeting Analysis method is used with four indicators, namely, payback period (PP), net present value (NPV), internal rate of return (IRR), and profitability index (PI). The results show that due to different energy market regulations and prices, different integration scenarios and system configurations can outperform others in Germany and Iran. Overall, due to the exchange rate instability and low energy tariff in Iran, in order for the project to be feasible, either the CFWT cost must fall to below 30% of its current cost or the local electricity price should increase significantly to get a Levelized cost of energy of as low as 0.6 $ kWh-1.

A numerical study on thermal ablation of brain tumor with intraoperative focused ultrasound.

Focused ultrasound surgery (FUS) is a non-invasive thermal therapeutic method which has been emerged in the field of brain tumors treatment. During intraoperative brain surgery, application of FUS can significantly increase the accuracy of thermal ablation of tumor while reducing undesirable damage to healthy brain tissue. The main objective of this study is acquiring acoustic transducer specifications to achieve optimum thermal treatment in the tumoral tissue. 2D and 3D models are constructed from patient-specific brain MRI images which consist of a malignant vascular tumor. Acoustic pressure and temperature are obtained by using homogenous Helmholtz and bio-heat transfer equations according to insignificant nonlinear effect. Besides that, thermal lesion induced by FUS is obtained by the thermal dose function. Results show the significance of blood vessels' cooling effect on the temperature profile. Moreover, correlation between temperature profile and transducer's operating parameter including power, frequency and duty cycle is obtained. Artificial neural network analysis is conducted to estimate required transducer parameters for optimum temperature rise.

A Patient-Specific Three-Dimensional Hemodynamic Model of the Circle of Willis.

Circle of Willis (CoW) is one of the most important cerebral arteries in the human body and various attempts have been made to study the hemodynamic of blood flow in this vital part of the brain. In the present study, blood flow in a patient specific CoW is numerically modeled to predict disease-prone regions of the CoW. Medical images and computer aided design software are used to construct a realistic three-dimensional model of the CoW for this particular case. The arteries are considered as elastic conduits and the interactions between arterial walls and the blood flow are taken into account. Mooney-Rivlin hyperelastic model is used to describe the behavior of arterial walls and blood is considered as a non-Newtonian fluid obeying the Carreau model. An available experimental-based pulsatile velocity profile is used at the entrance of the CoW. The finite element-based commercial software, ADINA, is used to solve the governing equations. Blood pressure and velocity and arterial wall shear stress are calculated in different regions of the CoW. A simplified form of the model is also compared with the available published data. Results affirmed that the proposed computational model has the potential to capture the hemodynamic characteristics of the CoW. The computational results can be used to determine disease-prone locations for a given CoW.