A Rudimentary Computational Assessment of Low Tip Speed Ratio Asymmetrical Wind Turbine Blades

This paper presents a computational study of novel drag type vertical axis wind turbine inspired by three design elements from nature. The aim of this study is to analyze the aerodynamic performance of the proposed design. The design is simulated in FLUENT using SST k-ω transport model via URANS turbulent model. The model is simulated in 2D in order to save computational time. The design is simulated under the influence of freestream velocity of U∞=8m/s at multiple tip speed ratios. The proposed wind turbine is composed of drag induced novel cavity vane turbine blade for energy capturing. The proposed wind turbine generated low power coefficient, Cp = 0.029 and Cp=0.025 at λ=0.2 and λ=0.3 respectively. tip speed ratio λ=0.4, λ=0.6 and λ=0.9 indicated high instability in moment generation and high negative power extraction.  Computational result indicated that the geometry of the cavity vane has impacted the performance of the turbine due to its sharp-edged corner. the proposed geometry resulted in unstable moment generation and torque deliverance which impacted the power extraction. The lack of symmetrical and streamline properties of the blades has affected one another as in terms of rotation. The cavity vane experiences high adverse pressure due to its sharp cornered geometry in returning blade which consequently impacted the rotation of the advancing blade

Modelling and Optimization of Energy Efficient Assembly Line Balancing Using Modified Moth Flame Optimizer

Energy utilization is a global issue due to the reduction of fossil resources and also negative environmental effect. The assembly process in the manufacturing sector needs to move to a new dimension by taking into account energy utilization when designing the assembly line. Recently, researchers studied assembly line balancing (ALB) by considering energy utilization. However, the current works were limited to robotic assembly line problem. This work has proposed a model of energy efficient ALB (EE-ALB) and optimize the problem using a new modified moth flame optimizer (MMFO). The MMFO introduces the best flame concept to guide the global search direction. The proposed MMFO is tested by using 34 cases from benchmark problems. The numerical experiment results showed that the proposed MMFO, in general, is able to optimize the EE-ALB problem better compared to five comparison algorithms within reasonable computational time.  Statistical test indicated that the MMFO has a significant performance in 75% of the cases. The proposed model can be a guideline for manufacturer to set up a green assembly line in future

Novel bio-hybrid drag induced wind turbine

In the world of rapid growing economy, energy consumption by power industry and human are drastically rising which is leading to an energy crisis situation. Today several countries are investing their resources on the development of renewable energy; wind power generation. 1. Pollution Increasing carbon emission by industry and humans activities had impacted global climate which lead to increasing greenhouse gases at the atmosphere year by year regardless the campaign and regulations initiated by the government and NGO. 2. Wind turbine's design for low-wind speed Design modification were done on wind turbine by engineers in order to adapt the wind speed of the desired geographical area. Researches indicates that, drag driven wind turbines such as Savonius and Darrieus VAWTs are suitable in harvesting wind energy in low wind speed potential

Novel compact fin and tube heat exchanger made of reinforced composite plate fins

Most fin and tube heat exchangers are affected by external factors over time, leading to a decrease in their efficiency. Among the most important reasons for this problem are the materials used in the manufacture of the heat exchanger. Heat exchangers are made of materials with high conductivity and are able to withstand the harsh conditions, but most of these materials are affected by corrosion such as iron, or the occurrence of electrochemical reactions that form layers with heat resistance at the surface of the material such as aluminium and copper, which negatively affects the performance of the heat exchanger. In addition, these materials have heavy weights that are difficult to use in small applications, and sometimes their prices are high for use in projects with a limited budget. To solve aforementioned problems, it possible to be a good option to use materials which have high corrosive resistance and light weight, few research work have suggested to use polymer as a material to product the heat exchanger, due to its characteristics which may limit the problems those occur in iron, copper and aluminium

Thermal conductivity and dynamic viscosity of mono and hybrid organic- and synthetic-based nanofluids: A critical review

Thermal conductivity and dynamic viscosity are two critical properties of nanofluids that indicate their heat transfer performance and flow. Nanofluids are prepared by dispersing mono or several organic or synthetic nanoparticles in selected base fluids to form mono or hybrid nanofluids. The qualitative and quantitative stability measurement of nanofluids will then be addressed, followed by a detailed discussion on how the dispersion of nanoparticles in water (W), ethylene glycol (EG), and themixture of W:EG 60:40%by volume affects the thermal conductivity and dynamic viscosity ratio. The data comparison demonstrated that the thermal conductivity ratio increases with increasing normalized concentrations, the bulk temperature of nanofluids, and the smaller nanoparticle size. The dynamic viscosity ratio is multiplied by the normalized concentration increase. Nevertheless, as the bulk temperature climbed from 0 to 80°C, the dynamic viscosity ratio was scattered, and the dynamic viscosity ratio trend dropped with increasing particle size. While the majority of nanofluids enhanced thermal conductivity ratio by 20%, adding carbon-based nanoparticles to synthetic nanofluid increased it by less than 10%. The disadvantage of nanofluids is that they multiply the dynamic viscosity ratio of all nanofluids, which increase power consumption and reduces the efficiency of any mechanical system

Modelling and optimization of energy efficient assemblyline balancing using modified moth flame optimizer

Energy utilization is a global issue due to the reduction of fossil resources and also negative environmental effect. The assembly process in the manufacturing sector needs to move to a new dimension by taking into account energy utilization when designing the assembly line. Recently, researchers studied assembly line balancing (ALB) by considering energy utilization. However, the current works were limited to robotic assembly line problem. This work has proposed a model of energy efficient ALB (EE-ALB) and optimize the problem using a new modified moth flame optimizer (MMFO). The MMFO introduces the best flame concept to guide the global search direction. The proposed MMFO is tested by using 34 cases from benchmark problems. The numerical experiment results showed that the proposed MMFO, in general, is able to optimize the EE-ALB problem better compared to five comparison algorithms within reasonable computational time. Statistical test indicated that the MMFO has a significant performance in 75% of the cases. The proposed model can be a guideline for manufacturer to set up a green assembly line in future

Exploratory, Phase II Controlled Trial of Shiunko Ointment Local Application Twice a Day for 4 Weeks in Ethiopian Patients with Localized Cutaneous Leishmaniasis

The clinical efficacy and safety of Shiunko ointment (phase II clinical trial) was investigated in 40 Ethiopian patients with cutaneous leishmaniasis. Patients were randomized to receive treatment with Shiunko ointment or placebo (n=20, each), applied on the lesion twice a day for 4 weeks. Clinicoparasitological assessments were performed before treatment, weekly for 4 weeks, and then 4, 8, and 12 weeks after the end of treatment. A marked reduction in lesion size was observed on week 16 of treatment in the Shiunko compared with placebo group (69% and 22% reduction, resp.). The overall rate of lesion reduction during the four weeks of treatment was significantly faster in the Shiunko group. Shiunko provided significant effect on wound closure in patients with ulcerated lesion. The clinical efficacy and tolerability of Shiunko were comparable to placebo with regard to its clinicoparasitological response (cure rate and parasitological clearance). Results of this preliminary study may suggest that Shiunko could be useful as adjuvant or as complementary treatment, not as alternatives to current treatment. Its attractive action includes fast lesion healing with a significantly smaller lesion at week 16 of treatment compared with placebo. In addition, its action was promoted in ulcerative lesions

THREE DIMENSIONAL SIMULATION OF SUSPENSION FLOW IN A MOLD CAVITY

ABSTRACT This paper presents three-dimensional simulation of fiber suspension flows in a cavity using the Finite Volume Method (FVM). The numerical simulation model described makes it possible to predict the propagation of the fiber-polymer solution and fiber orientation during the filling phase. Therefore, the objective of the work is to develop a Computational Fluid Dynamics (CFD) model to simulate and characterize the fiber suspension flow in three dimensional cavities. The model is intended to describe the fiber orientation distribution in three dimensional mold cavities. The continuity, momentum, energy and the fiber orientation equations are solved using the FVM. The flow is considered to be incompressible, non-isothermal, transient, and to behave as non-Newtonian fluid. A numerical analysis is presented to illustrate the application of the FVM to dilute suspension flows in injection molding processes. The volume-of-fluid method is employed to describe the flow of the two incompressible, immiscible phases, i.e., liquid suspension and air. Since the flow is a non-Newtonian, the Cross model is used to describe the shear-thinning behavior of the suspension. The governing equations of the flow and the fiber are implemented and solved by means of the open source code OpenFOAM. The evolution equation of the fiber orientation contains a fourth order orientation tensor which is approximated in terms of second order tensor through the use of appropriate closure rules. In this study the Hybrid closure model of Advani and Tucker is used to approximate the fourth order orientation tensor. To validate the numerical algorithm, test cases of suspension flow in a rectangular cavity are modeled for different fiber-polymer matrices. The numerical results are compared with available experimental findings and with those of Newtonian flows

Development of brain tissue swelling predictive tools for ischaemic stroke patient post-treatment

Ischaemic stroke is one of the causes of death worldwide. Treatments such as thrombolysis and catheterisation must be given within 3 hours after stroke onset, in which treatments beyond this time may pose risk of brain tissue swelling. Thus, a prediction system must be made to determine the suitability of a stroke treatment to avoid the risk of failure. In this report, a mathematical model based on poroelastic theory and asymptotic expansion homogenization has been developed to study the formation of brain tissue swelling after ischaemia-reperfusion treatment. Firstly, the mathematical model of brain tissue swelling after ischaemia-reperfusion treatment is investigated using an ideal 2D brain geometry. The objective here is to observe the effect of infarct size and location towards the formation and severity of brain herniation, which will form due to brain tissue swelling. However, this model assumed that the blood pressure is constant and homogeneous throughout the brain, while in fact, the blood capillaries vary in sizes and shapes. Therefore, asymptotic expansion homogenization technique is applied to allow for the inclusion of capillaries sizes into the initial model. This method transforms the initial model into two types of equations: (1) macroscale governing equations; and (2) microscale cell problems. In order to solve for the macroscale governing equations, the microscale cell problems must first be solved on a brain tissue geometry to calculate the effective parametric tensors, which later be used in the macroscale governing equations. Lastly, the mathematical model is solved in a realistic brain geometry to evcaluate the effect of different mechanical properties of the brain towards brain tissue swelling formation