7 results about "Block modeling" patented technology

Aspects of the present disclosure provide for eliminating or reducing block uniqueness in a chip-level graph of a computer chip, reducing the size of the graph while still encoding block-specific information. For each group of blocks in the graph generated from a multiple instantiation block (MIB), a block in the group is selected as a base block. The physical location of the base block is encoded in the reduced graph, and the physical locations of the remaining blocks are encoded as linear transformations of the physical locations of the base block across the face of the chip. Each group of blocks instantiated from the same MIB is represented as a single instance. The reduced graph can be provided to a device configured to perform a circuit component placement process to identify placement of circuit components for blocks in the chip according to one or more objectives.

Aspects of the disclosure provide for eliminating or reducing uniquification of blocks in a chip-level graph of a computer chip, to reduce the size of the graph while still encoding block-specific information. For each group of blocks in the graph generated from a multiply-instantiated block (MIB), a block in the group is selected as a base block. The physical position of the base block is encoded in a reduced graph, and the physical positions of the remaining blocks are encoded as a linear transformation of the physical position of the base block across the face of the chip. Each group of blocks instantiated from the same MIB is represented as a single instance. The reduced graph can be fed into a device configured to perform a circuit component placement process, to identify the placement of circuit components for blocks in the chip in accordance with one or more objectives.

The invention relates to the technical field of civil engineering and artificial intelligence, in particular to an automatic modeling method and system for a bridge finite element model. Comprising an interaction module, a large model cascade engine, a compiler and a modeling program language grammar error debugging module. The large model cascade engine comprises a natural language pseudo code generation and check module, a modeling program language cue word generation module and a bridge structure parameter generation module; the technical threshold of finite element modeling in the field of civil engineering is greatly reduced, modeling personnel do not need to have a firm computer programming capability, an operable finite element program and a calculation result can be quickly obtained only through input requirements, and the bridge finite element modeling efficiency is remarkably improved.

The invention belongs to the technical field of metal additive manufacturing numerical simulation, and particularly relates to a method for establishing an efficient LPBF block-by-block finite element model based on thermal-mechanical coupling, which comprises the following steps of: establishing an LPBF block-by-block finite element model on the basis of ANSYS software; constructing a three-dimensional heat transfer calculation model and a three-dimensional stress calculation model of the metal LPBF by utilizing an APDL language; the ANSYS software program is used for carrying out grid division on the target workpiece according to a block-by-block modeling strategy, and temperature distribution calculation is carried out according to thermophysical parameters of a target workpiece material; and applying the calculated temperature distribution as a load to the three-dimensional stress calculation model, and performing stress field distribution calculation according to the temperature distribution and the mechanical property parameters of the target workpiece material at different temperatures to obtain stress distribution. The method provided by the invention realizes the prediction of the temperature field and the stress field, can reduce the time cost, and improves the simulation efficiency and the simulation precision.

The invention discloses a psychological state assessment method based on emotion labeling and multi-expert integration, and the method comprises the steps: carrying out the continuous emotion labeling of an input video, and obtaining an emotion score of each video frame; enhancing a video frame feature sequence extracted from the video, dynamically distributing the enhanced feature to a plurality of expert networks for processing according to the emotion score, and integrating the output of each expert network into a final sequence representation; in each expert network, dimension mapping and preprocessing are carried out on input features distributed to each expert network, in-block modeling and inter-block modeling are executed, information fusion and pooling are carried out on modeling output and preprocessed input, and output features of each expert network are generated. The problems that in the prior art, emotion information utilization is insufficient, diversified emotion data cannot be effectively processed through a single model, and fixed-scale modeling cannot adapt to psychological state dynamic expression are solved.