State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

IDENTIFICATION OF CHATTER VIBRATIONS AND ACTIVE VIBRATION CONTROL BY USING THE SLIDING MODE CONTROLLER ON DRY TURNING OF TITANIUM ALLOY (TI6AL4V)

In recent years, with the development of sensor technologies, communication platforms, cyber-physical systems, storage technologies, internet applications and controller infrastructures, the way has been opened to produce competitive products with high quality and low cost. In turning, which is one of the important processes of machining, chatter vibrations are among the biggest problems affecting product quality, productivity and cost. There are many techniques proposed to reduce chatter vibrations for which the exact cause cannot be determined. In this study, an active vibration control based on the Sliding Mode Control (SMC) has been implemented in order to reduce and eliminate chatter vibration, which is undesirable for the turning process. In this context, three-axis acceleration data were collected from the cutting tool during the turning of Ti6Al4V. Finite Impulse Response (FIR) filtering, Fast Fourier Transform (FFT) analysis and integral process were carried out in order to use the raw acceleration data collected over the system in control. The system is modeled mathematically and an active control block diagram is created. It is observed that chattering decreased significantly after the application of active vibration control. The surface quality formed by the amplitude of the graph obtained after active control has been compared and verified with the data obtained from the actual manufacturing result

In Vitro and Computational Analyses of Blood Flow at Aortoiliac Bifurcation for Patients with Atherosclerotic Plaque Treated with Endovascular Procedures

This research has developed an appropriate approach allowing for more accurate assessment of haemodynamic changes following implantation of endovascular stent graft to treat patients with occlusive aortoiliac disease. Two different endovascular techniques involving the use of different types of stent grafts were analysed and compared with regard to haemodynamics associated with these techniques. Results improved understanding of the flow characteristics of these endovascular techniques

CFD Modeling and Optimization of Magneto-rheological Abrasive Flow Finishing (MRAFF) Process

A modern nano finishing technique called magnetorheological abrasive flow finishing (MRAFF), which is simply a combined hybrid form of abrasive flow machining (AFM) process and magnetorheological finishing (MRF) process, has been designed for micro finishing of parts even with difficult geometry for a broad range of industrial purposes. In the present work, a model for the prediction of removal of material and surface roughness has been estimated. An effort has been made to study the flow passing through the stainless steel workpiece by CFD modeling in ANSYS 15.0 FLUENT. By assuming the medium as Bingham plastic various parameters affecting the surface roughness has been calculated. Also a theoretical calculation is made for the model if no magnetic field is applied and then comparative study of the two models is proposed. An optimization of the process has also been carried out. With the help of SN Ratio plot and Means plot optimized value of input parameters has been found out to achieve better surface finish

CFD Modeling and Optimization of Magneto-rheological Abrasive Flow Finishing (MRAFF) Process

A modern nano finishing technique called magnetorheological abrasive flow finishing (MRAFF), which is simply a combined hybrid form of abrasive flow machining (AFM) process and magnetorheological finishing (MRF) process, has been designed for micro finishing of parts even with difficult geometry for a broad range of industrial purposes. In the present work, a model for the prediction of removal of material and surface roughness has been estimated. An effort has been made to study the flow passing through the stainless steel workpiece by CFD modeling in ANSYS 15.0 FLUENT. By assuming the medium as Bingham plastic various parameters affecting the surface roughness has been calculated. Also a theoretical calculation is made for the model if no magnetic field is applied and then comparative study of the two models is proposed. An optimization of the process has also been carried out. With the help of SN Ratio plot and Means plot optimized value of input parameters has been found out to achieve better surface finish

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

PREDICTION OF RESPONSES IN A CNC MILLING OPERATION USING RANDOM FOREST REGRESSOR

In the present-day manufacturing environment, the modeling of a machining process with the help of statistical and machine learning techniques in order to understand the material removal mechanism and study the influences of the input parameters on the responses has become essential for cost optimization and effective resource utilization. In this paper, using a past CNC face milling dataset with 27 experimental observations, a random forest (RF) regressor is employed to effectively predict the response values of the said process for given sets of input parameters. The considered milling dataset consists of four input parameters, i.e. cutting speed, feed rate, depth of cut and width of cut, and three responses, i.e. material removal rate, surface roughness and active energy consumption. The RF regressor is an ensemble learning method where multiple decision trees are combined together to provide better prediction results with minimum variance and overfitting of data. Its prediction performance is validated using five statistical metrics, i.e. mean absolute percentage error, root mean squared percentage error, root mean squared logarithmic error, correlation coefficient and root relative squared error. It is observed that the RF regressor can be deployed as an effective prediction tool with minimum feature selection for any of the machining processes

Advancements in Flux Switching Machine Optimization : Applications and Future Prospects

This work was supported by the Commonwealth Scholarship Commission, U. K., under Grant Number: NGCN-180-2021Peer reviewe