Mechanicsdriven

Mechanicsdriven is a term used to describe modeling, analysis, or design approaches guided primarily by fundamental mechanics and physics rather than by empirical data alone. It emphasizes governing equations, constitutive laws, and physical constraints as the primary source of information.

The term may be written mechanics-driven or mechanicsdriven. It is common in fields such as computational mechanics, solid and fluid mechanics, robotics, and materials science to distinguish from data-driven methods. The idea is to build models that respect physics from the outset.

In practice, mechanicsdriven modeling uses differential equations, such as conservation laws, Navier–Stokes for fluids or elasticity for solids, with appropriate boundary and initial conditions, solved by numerical methods like finite element analysis, finite volume, or multibody dynamics. It relies on material constitutive models, fracture criteria, and sometimes multiscale coupling to capture behavior across scales. It can be hybridized with data to calibrate parameters but keeps physics as the governing core.

Relationship to data-driven approaches: mechanics-driven models provide interpretability, stability, and extrapolation beyond observed data. Data-driven methods may be used to calibrate parameters or model phenomena not captured by first principles, to yield physics-informed machine learning approaches.

In summary, mechanicsdriven denotes a design and analysis philosophy that foregrounds mechanics and physics in modeling, simulation, and decision-making, distinguishing it from approaches driven primarily by data.