Abstract: A method, an apparatus, and a system for generating a neural network model, a device, a medium, and a program product are provided. In an embodiment, a first device sends an indication about a structure of a subnetwork model to a second device, where the subnetwork model is determined by adjusting a structure of a hypernetwork model. The first device receives a parameter of the subnetwork model from the second device, where the parameter of the subnetwork model is determined by the second device based on the indication and the hypernetwork model. The first device trains the subnetwork model based on the received parameter of the subnetwork model. The first device sends a parameter of the trained subnetwork model to the second device for the second device to update the hypernetwork model. In the foregoing manner, an efficient federated learning scheme between a plurality of devices is provided.

Abstract: A laser shock peening method and device for a bottom surface of a tenon groove of an aircraft blade. During the laser shock peening process, according to geometric characteristics of the bottom surface of a tenon groove, a circular facula of a laser beam is changed into a strip-shaped facula, at the same time as a flow-guiding injection device and a water pumping device are respectively arranged at two end surfaces of the bottom surface of the tenon groove to ensure the stability of a water confinement layer.

Abstract: A laser shock peening method and device for a bottom surface of a tenon groove of an aircraft blade. During the laser shock peening process, according to geometric characteristics of the bottom surface of a tenon groove, a circular facula of a laser beam is changed into a strip-shaped facula, at the same time as a flow-guiding injection device and a water pumping device are respectively arranged at two end surfaces of the bottom surface of the tenon groove to ensure the stability of a water confinement layer.