Integration Approaches and Development Status of Experimental Mechanics and Numerical Simulation Methods

Abstract: This paper discusses the basic pathways, respective advantages and disadvantages, and the latest collaborative development trends of the combination of experimental mechanics and numerical simulation methods.

In modern solid mechanics research, experimental mechanics and numerical simulation have long been regarded as two major pillars. Experimental mechanics is based on real physical testing, with results that are intuitive and close to reality, but it is often limited by measurement point constraints and environmental interference; numerical simulation, with theoretical equations and computer algorithms at its core, possesses efficient, full-field predictive capabilities, yet it is extremely dependent on the accuracy of constitutive models and boundary conditions. How to organically integrate the two to achieve complementary advantages has become a key approach for the mechanics community to solve complex engineering and scientific problems.

Performance Comparison and Complementary Logic of Experimental Mechanics and Numerical Simulation

To understand the integration of the two, one must first clarify their respective advantages and disadvantages. The advantage of experimental mechanics lies in "authenticity"; it directly reflects the response of materials under real loads and can capture unprejudiced physical phenomena (such as local damage and micro-crack initiation). However, traditional point-based measurement methods make it difficult to obtain high-resolution deformation information inside complex three-dimensional components and across the full field. Numerical simulation (such as the finite element method and the discrete element method) excels in "completeness" and "depth," capable of high-density calculations of full-field stress and strain evolution for complex geometric components. Nevertheless, the risk of numerical model distortion always exists; if the input material constitutive parameters are inaccurate, the calculation results will be "off by a millimeter, leading to an error of a thousand miles." Combining experimental "real observation" with simulated "full-field prediction" to form a closed-loop feedback is the inevitable logic to eliminate their respective blind spots.

Integration Pathways of Data-Driven Methods and Boundary Condition Correction

The preliminary integration of the two is commonly seen in the correction of boundary conditions and material parameters. In actual engineering structural analysis, true load boundaries and initial conditions are often difficult to accurately specify. By deploying experimental measurement points at key locations to obtain measured physical quantities and using them as boundary inputs or constraint conditions for numerical models, the authenticity of finite element calculations can be significantly enhanced. In addition, aiming at the establishment of material constitutive models, researchers often use experimental data to identify and invert unknown parameters in numerical simulations. This alternating iterative process of "experiments measure initial values, simulations solve for the full field, and experiments re-verify" enables the numerical model to progressively approximate the real physical system.

Collaborative Development Dynamics in Cross-Scale and Multi-Physics Coupling

Currently, with the development of fields such as aerospace and advanced manufacturing, mechanics problems are increasingly evolving toward extremization, multi-scale, and multi-physics directions. In frontier fields such as micro-nano scale materials and composite material damage evolution, a single method is no longer sufficient. The latest development trends indicate that experimental mechanics is evolving toward microscopic and full-field approaches, while numerical simulation is developing toward multi-scale parallel computing. The collaboration between the two is reflected in: the mesoscopic deformation mechanisms revealed by micro-experiments directly guide the construction of macro-meso multi-scale numerical models; conversely, the high-stress gradient regions predicted by numerical simulations guide experimental mechanics to focus high-precision full-field measurement equipment on critical hazardous locations. This deep two-way interaction greatly promotes the accuracy and depth of research on the multi-scale mechanical behavior of complex materials.

Conclusion and Future Outlook

• The integration of experimental mechanics and numerical simulation methods is essentially a deep dialogue between the physical world and the digital world. From early unidirectional validation to today's deep coupling and data assimilation, the combination of the two has not only resolved many bottlenecks in traditional mechanical analysis but also laid a solid foundation for intelligent design and digital twin technology. With the introduction of artificial intelligence and machine learning algorithms, future integration pathways will become even more efficient, continuously evolving toward real-time, dynamic, and omnidirectional directions.