The present application relates to the technical field of water conservancy and
hydropower engineering design, and discloses a dam multi-
physical field coupling design method, device, equipment and medium, the present application constructs a heterogeneous
hybrid solution architecture of embedding a
machine learning model and a numerical solution model which is constrained by a
physical control equation, and differentiates
model selection based on the difference in the rate of change of each
physical field in space and time, fundamentally solving the core contradiction between the low efficiency of traditional pure numerical
simulation and the lack of physical constraints in pure data-driven
machine learning models which are prone to non-physical solutions; at the same time, through mutual feedback type two-way
coupling iteration of the response results of each
physical field, the solution efficiency and solution accuracy are simultaneously considered; on this basis, combined with the adaptive screening mechanism of the multi-working-condition differentiated response weight strategy, the design scheme can dynamically adapt to the core needs of different service working conditions, significantly improving the
engineering practicability of the design scheme.