Abstract: Visualizing characteristics of blood flow in the human body is essential for accurate diagnosis of cardiovascular diseases, analysis of pathological mechanisms, and optimization of personalized treatment. However, traditional medical methods, relying primarily on imaging observations and empirical analysis, face significant limitations in directly observing blood flow states and lack sufficient quantitative assessment of the coupled effects of blood components. Therefore, in this study, we propose a blood flow characteristics simulation method based on a multicomponent non-Newtonian fluid model, integrating rheological modeling, multiphase coupling, and fluid–solid interaction mechanisms to address these problems. The proposed method takes three pivotal advancements into consideration. First, the Walburn–Schneck model is employed to describe the shear-thinning behavior of non-Newtonian fluids, wherein the viscosity is characterized as a function of shear rate. Second, the Walburn–Schneck model is extended to multicomponent application scenarios by introducing volume fractions, enabling the modeling of interaction mechanisms between different components and their collective influence on bulk viscosity. This extension allows for accurate simulation of multicomponent non-Newtonian fluid dynamics, including the complex deformation and flow patterns that traditional single-component models struggle to capture. Third, a solid–liquid interaction force model at the blood vessel wall is constructed using an improved smoothed particle hydrodynamics framework. The model incorporates wall shear stress and adhesive forces, effectively mitigating computational inaccuracies near the fluid-solid boundary caused by particle truncation. As a result, the model achieves robust simulations in complex vascular geometries. To verify the effectiveness of the proposed method for blood flow simulation, a series of experiments were performed. The drop and deformation experiments of non-Newtonian fluids were first conducted. The results demonstrated that the Walburn–Schneck model can accurately capture the shear rate-dependent viscosity changes, outperforming the Carreau model in reproducing fluid extension and thinning effects. To further assess the model’s adaptability to high-viscosity fluids, experiments on the coiling and folding phenomena exhibited by non-Newtonian fluids with high-viscosity characteristics were also carried out. The extended Walburn–Schneck model effectively captured and maintained the complex crease effects generated by fluid curling and folding, thereby verifying the model’s accuracy and applicability in high-viscosity scenarios. Then, simulations of multicomponent non-Newtonian fluids with varying volume fractions of high-viscosity components were carried out, and the stability of the multicomponent non-Newtonian fluid model was verified through the three-phase dam break experiment. Finally, simulations across diverse vascular scenarios were conducted to verify the efficacy of the solid-liquid interaction force model and the multicomponent non-Newtonian fluid model in the blood flow scenario. The model effectively reproduced mixing-diffusion behaviors in complex vascular structures, including straight, bifurcated, and stenotic vessels. Stable fluid–solid coupling and no particle penetration were observed, highlighting the robustness and accuracy of the proposed method. The research results provide a new technical pathway for digital and intelligent medical diagnosis, holding promise to assist in deepening the understanding of pathological mechanisms related to hemodynamic abnormalities. By integrating the fluid viscosity of the multicomponent with non-Newtonian rheology, the method improves the accuracy of hemodynamic simulations. Future work will focus on integrating microscale cellular interactions and dynamic vascular elasticity to further bridge the gap between simulation and clinical reality.