Shape Optimization of Pin Fin Arrays Using Gaussian Process Surrogate Models Under Design Constraints

Internal cooling channels with pin-fin arrays are an important part of gas turbine blade trailing edge design. Short pin-fins act as turbulators in high aspect ratio channels to increase heat transfer and provide structural support to the trailing edge of the blade. Such pin fins however also result in a high pressure drop owing to chaotic flow phenomenon in these highly turbulent flows. High pressure-drop results in higher compressor work due to increased power consumption to push the coolant through these passages. Hence, optimizing the design of pin fin arrays is key to increasing the efficiency of real gas turbine cycles by handling higher turbine inlet temperature and increasing blade life. Moreover, the design process of such pin fin arrays can be computationally very expensive, since it typically involves high-fidelity CFD simulations. The optimization problem involves maximizing Nusselt number, while keeping the friction factor as a constraint. To address this problem, a computationally efficient approach involving Gaussian Processes (GP) surrogate modeling and constrained Bayesian Optimization (BO) has been carried out for optimizing the thermal performance of the pin fin arrays. The multidimensional search space of design parameters includes pin-fin dimensions and shape of the resulting pin-fins. The optimization problem is solved under computational budget limitations and design constraints. A ‘drop’ like optimal design is obtained which has a lower pressure drop and higher Nu compared to the baseline.

Insight into bubble nucleation at high-pressure drop rate

This paper presents insight in bubble nucleation in polymer foaming with physical blowing agent using a batch foaming technique. In our experiments the bubble nucleation is triggered by a sudden pressure drop that causes the supersaturation in the polymer gas solution. In fact, the pressure drop rate is an important process variable since it plays a role in both bubble nucleation and growth. Herein, we investigated very high pressure drop rates, and confirmed the great importance of the pressure drop rate as foaming process variable. The results show that the number of nucleated bubbles increases of one order of magnitude and the foam density is reduced if the pressure drop rate is increased from 50 to 500 MPa/s. Interestingly, the number of nucleated bubble increases linearly in a bi-logarithmic scale as function of pressure drop rate at all the investigated temperatures. Moreover, in the current paper, it is discussed how talc used as nucleating agent plays a role in cooperation with pressure drop rate on bubble nucleation at different foaming temperatures.