Modeling the unsteadiness owing to body motion is essential for accurately simulating ice accretion on a moving object. For an oscillating airfoil, high-frequency oscillations have been assumed to occur in slow motion to apply a quasi-steady approach to numerical analysis. The method raised arbitrariness in the number of data exchanges and the initial angle of attack. Simultaneously, the oscillation owing to a change in the angle of attack was considered for each step. Subsequently, the quasi-unsteady approach was proposed, the results from which exhibited good agreement for a few ice shapes, unlike that of the extended quasi-steady approach. However, whether a quasi-unsteady approach is sufficiently accurate for simulating ice accretion on a two-dimensional oscillating airfoil under various conditions still remains unknown. This study analyzed the unsteady effect on collection efficiency and convective heat transfer using the quasi-unsteady approach. Furthermore, as the static case, this approach demonstrated that the roughness and laminar-turbulent transition model for the oscillating airfoil can improve the prediction of the ice shape. The results obtained from this approach using the improved model exhibited good agreement with previously reported experimental results.Fig. 11 compared predicted ice shape with different roughness height. Fig. 11(a) is Run 61 with a reduced frequency of 0.044 at an LWC = 1 g/m3, and Fig. 11(b) is Run 50 with a reduced frequency of 0.027 at an LWC =.55 g/m3 The dotted line indicates the experimental ice shape and the dashed line indicates the numerical results applied to the empirical roughness model. The solid line indicates ice shape with the roughness size when the direction and size of the ice horn closely match the experimental values. When an empirical roughness model is applied, the ice horns are usually concentrated near the leading edge. Roughness increases convective heat transfer and premature laminar turbulence in ice accretion. The convective heat transfer peaks near the leading edge with a high roughness value; therefore, the ice horn gathers near the leading edge. Low roughness delayed the formation of the ice horn due to the decreased heat transfer rate, which balances the latent heat of icing, thereby allowing the droplets to freeze before moving to the trailing edge. In Run 61, the ice shape was predicted accurately at 20 % of the empirical roughness and 40 % roughness height of Run 55. When the roughness height was reduced, such as in the case of Run 61 with 10 % empirical roughness, the primary horn reduced, whereas the secondary horns increased.