In the present work, the particle agglomeration in shear flows is investigated in the framework of a hard sphere model with deterministic collision detection employing two different modeling approaches: the energy-based and the momentum-based agglomeration models. The former is further improved concerning the agglomeration conditions. Moreover, the application area of both models is extended towards fully three-dimensional turbulent flows applying the large-eddy simulation technique. Here, the particles are assumed to be rigid, dry and electrostatically neutral and hence only the cohesion due to the van-der-Waals forces is considered. First, the energy-based and the momentum-based agglomeration models are successfully validated based on theoretical results using an existing laminar test case. The numerical results are found to be in close agreement with the theory. Then, both agglomeration approaches are used to investigate the dynamic process of the particle agglomeration in a vertical fully developed turbulent channel flow. A detailed comparison of the results obtained using both agglomeration models is reported. Additionally, the performance of both techniques is examined under the influence of varying normal restitution coefficients of the inter-particle collisions. Furthermore, the influence of the inclusion of three sub-models (the feedback effect of the particles on the fluid, the lift forces and the subgrid-scale model for the particles) on the agglomeration process is studied. The results show that a significantly lower agglomeration rate is observed if the sub-models are considered. Next, the agglomeration models are applied to evaluate the effect of the diameter of the primary particles and the wall roughness on the agglomeration behavior. The reduction of the diameter of the particles leads to a stronger cohesive impulse and hence to a higher agglomeration rate. The wall roughness enhances the particle-particle collisions and slightly increases the number of agglomeration processes leading to higher agglomeration rates. The comparative study clearly indicates that both models predict similar trends of the physical behavior of the agglomeration process, but their results deviate slightly from each other. The most important reasons for the differences observed between the numerical results of both models are discussed. Based on the advantages and drawbacks of both models highlighted in this study, it can be concluded that owing to the reduced necessity of empirical parameters and the slightly more accurate results the momentum-based agglomeration model is superior to the energy-based model. (C) 2016 Elsevier B.V. All rights reserved.