In this paper, Pythagorean-hodograph (PH) quantic spline curves constructed by several connected PH curves with C2 continuity are used to designing the tool path in machining operation. To generate the tool path commands, the acceleration/deceleration phase of motion and the middle regions of the tool path are devised by time-dependent and constant velocity interpolation algorithms, respectively. In the aforementioned interpolation algorithm, the exponential functions are employed to modify the FEEDRATE PROFILE and subsequently using the Pattern Search algorithm (PSA), the proposed FEEDRATE PROFILE is optimized to maintain the maximum jerk within allowable physical limits. Finally, high speed CNC machining for two cases of open and closed C2 PH quantic spline curves along with the commonly used feed forward/feedback controller is simulated in Simulink Matlab software and the contouring error is studied and analyzed.

In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex OPTIMIZATION problem that guarantees the global optimal solution. The convex OPTIMIZATION problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

One of the main concerns in flight performance is to determine the highest level of capabilities for flying vehicles to perform the assigned missions. The objective of the current research is to utilize the maximum aerodynamic and propulsive capabilities of a flying robot. In this regard, the problem of optimal performance during all phases of a mission PROFILE is proposed. By integrating a multi objective heuristic OPTIMIZATION algorithm with constrained OPTIMIZATION approaches, all phases of a typical mission PROFILE have been optimized. The major advantage of the proposed approach is that it provides the optimal time history for all state variables as well as the optimal flight path and the amount of required fuel.

In this research, successfully joint of dissimilar 5050 Al alloy to 304stainless steel by friction Stir Welding (FSW) has been studied. In FSW many parameters on the microstructure and mechanical properties is effective. Therefore, to achieve the highest strength possible, the important process parameters such as tool rotational speed, FEEDRATE tool offset and pin PROFILE have been investigated. Considering the results of the mechanical properties, the best condition to obtain the highest strength in weld nugget was 80mm/min FEEDRATE, 500rpm tool rotational speed, with a conical pin PROFILE and 1.8mm tool offset respectivly. In this case the strength of the 94/203MPa is obtained that this value is equal to 97% strength aluminum alloy base metal.

In this paper, multi-objective OPTIMIZATION of railway wheel web PROFILE using bidirectional evolutionary structural OPTIMIZATION (BESO) algorithm is investigated. Using a finite element software, static analysis of the wheel based on a standard load case, and its modal analysis for finding the fundamental natural frequency is performed. The von Mises stress and critical frequency as the problem objectives are combined using different weight factors in order to find the sensitivity number in the method, which specifies which elements to be omitted and which to be added. The iterative process is continued until convergence to an a priori specified material volume. The resulted web PROFILEs show that when the stress is important, material removal is from the middle part of the web, while for frequency as the important objective, the removal is from near the rim part of the web. The suggested PROFILE, corresponding to equal weight factor for the objectives, has a better volume and stress state compared to a standard web PROFILE, and has a more uniform stress distribution. However, higher natural frequency, compared to that of the standard PROFILE, are obtained for larger frequency weight factors, although with a bigger volume. In the end, considering manufacturability of the wheel, the jagged PROFILE resulted from BESO is replaced with a fitted smooth curve and performing the finite element analysis on it. It is seen that there is an improvement in the obtained objectives for the smoothened PROFILE, with no significant change in volume.

This study pertains to the design OPTIMIZATION of a four-blade ceiling fan to enhance air circulation and energy efficiency. The sweep angle of the blade PROFILE is nonlinear. The design of experiment (DOE) computational fluid dynamics (CFD) and response surface method (RSM) methods were used in parallel to find the optimal design solution. The design variables considered were inboard angle of attack, outboard angle of attack, blade sweep, and tip-chord length. Numerical simulations were conducted using steady state Reynolds-averaged Navier– Stokes (RANS) equations and the Spalart– Allmaras turbulence model. The baseline results were validated through experimental data. Subsequently, the DOE method was employed to generate the blade design which reduce the number of simulations without losing the influence of different geometric parameter interactions. The response variables studied were volume flow rate, mass flow rate, torque, and energy efficiency. The simulations exhibited that flow pattern has a distinct feature and is further classified into three groups. In the end, the optimal blade design was identified using response surface methodology (RSM).

Trajectory OPTIMIZATION is a familiar method for most of re-entry and Re-usable vehicles. This is because of the ability to include almost all of the problem constraints without facing restrictions such as time & Calculation issues. Adding or removing constraints in trajectory OPTIMIZATION problem has significant effects on overall OPTIMIZATION performance which even can upgrade the method to an on-line process. Most of OPTIMIZATION Algorithms such as nonlinear-programming need an initial guess and are also sensitive to it. Hence in this research management of initial guess is done to remove some constraints from OPTIMIZATION problem and transfer them to initial phase. Accordingly an effort is conducted through using a classic guidance method to satisfy constraints of distance error and angle of impact command. The output of guidance initial guess is then fed to the OPTIMIZATION problem. 6Dof Simulation results show the increase of OPTIMIZATION performance via reduced number of iterations and OPTIMIZATION time and increased solution accuracy.