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This paper aims to investigate numerical solution of transonic flow around NACA0012 airfoil under sinusoidal pitch oscillation. Accordingly, effects of the amplitude and frequency of oscillations on aerodynamic coefficients are evaluated and the efficiency of the turbulent models, K-ω shear-stress transport (SST), scale adaptive simulation (SAS) and delayed detached eddy simulation (DDES), in simulation of the nonlinear phenomena – i.e. the interaction between shock and boundary layer and the shock oscillations – is studied.

K-ω SST, SAS and DDES models are used as turbulence approaches. The numerical results are compared with available experimental and numerical information.

According to the results inside the buffet boundaries, the DDES turbulent model expresses results that are more appropriate; however, SAS and SST models are not efficient enough in evaluating the characteristics of nonlinear flow.

In this research study, hybrid RANS-LES turbulence model is engaged to simulate transonic flow around pitching NACA0012 airfoil, and results are compared to the SAS and Reynolds Average Navier–Stocks simulations as well as available numerical and experimental data. In addition, effects of the amplitude and frequency of oscillations on aerodynamic coefficients are evaluated in buffet regions.

In this paper, the applicability of shear stress transport k-ω model along with the intermittency concept has been investigated over pitching airfoils to capture the laminar separation bubble (LSB) position and the boundary layer transition movement. The effect of reduced frequency of oscillations on boundary layer response is also examined.

A two-dimensional computational fluid dynamic code was developed to compute the effects of unsteadiness on LSB formation, transition point movement, pressure distribution and lift force over an oscillating airfoil using transport equation of intermittency accompanied by the k-ω model.

The results indicate that increasing the angle of attack over the stationary airfoil causes the LSB size to shorten, leading to a rise in wall shear stress and pressure suction peak. In unsteady cases, both three- and four-equation models are capable of capturing the experimentally measured transition point well. The transition is delayed for an unsteady boundary layer in comparison with that for a static airfoil at the same angle of attack. Increasing the unsteadiness of flow, i.e. reduced frequency, moves the transition point toward the trailing edge of the airfoil. This increment also results in lower static pressure suction peak and hence lower lift produced by the airfoil. It was also found that the fully turbulent k-ω shear–stress transport (SST) model cannot capture the so-called figure-of-eight region in lift coefficient and the employment of intermittency transport equation is essential.

Boundary layer transition and unsteady flow characteristics owing to airfoil motion are both important for many engineering applications including micro air vehicles as well as helicopter blade, wind turbine and aircraft maneuvers. In this paper, the accuracy of transition modeling based on intermittency transport concept and the response of boundary layer to unsteadiness are investigated.

As a conclusion, the contribution of this paper is to assess the ability of intermittency transport models to predict LSB and transition point movements, static pressure distribution and aerodynamic lift variations and boundary layer flow pattern over dynamic pitching airfoils with regard to oscillation frequency effects for engineering problems.

The purpose of this paper is to identify the factors influencing Indonesian students’ choice of university by estimating the trade-off students make in selecting a university.

Conjoint analysis was used to examine the relative importance and the part-worth scores of the attributes that influence students’ public university preferences in Indonesia.

High-school leavers in Indonesia trade off university preferences and view advice from family, friends, and/or teachers, reputation, and job prospects as important factors for selecting a public university. Two different preference-based segments of prospective students were identified from cluster analysis, and classified as either a “social networks-based decision” or a “rational decision” segment. A choice simulator was employed with three propositions, and the segments were found to have dissimilar preferences.

While this paper provides insights on higher-education consumer choice, more research is needed that includes samples from different types of higher-education institutions and fields of study.

A greater understanding of student choice can help to inform marketing practices and customize marketing strategies for each segment by providing important information to principal parties involved in making university choice decisions.

This paper demonstrates the relevance and value of conjoint analysis as an effective analytical tool for the identification of important choice criteria and its potential contribution to the development of more effective marketing strategies.