![]() To verify the effectiveness of the proposed method, an experimental study on a hierarchical stiffened plate is carried out. Finally, a digital twin model can be built, which is capable of visualizing the full-field strength information of the stiffened plate structure. Then, the pre-trained DNN model is fine-tuned based on the target dataset using a lower learning rate and fewer training epochs. First, a pre-trained deep neural network (DNN) model is established based on the source dataset. In transfer learning, simulation data and sensor data are utilized as the source dataset and the target dataset, respectively. To this end, a digital twin modeling method of multi-source data fusion based on transfer learning is proposed in this paper. On the other hand, data from the sensors cannot provide the full-field strength information of the structure, which may result in the misjudgment of the structural state. On the one hand, the simulation results are sometimes inaccurate, due to the simplification of the true loading conditions and modeling details. ![]() Since DADOS is a cloud-based system, anyone can access DADOS at using their web browser without the need for installation or powerful hardware.Īs the key load-bearing component of spacecraft, the strength evaluation of stiffened plate structures faces two challenges. Two examples were employed to demonstrate how to use DADOS to conduct data-driven design optimization. This paper also details the architecture and the user interface of DADOS. In addition, DADOS allows users to visualize the results to gain more insights into the design problems, allows multi-person collaborating on a project at the same time, and supports multi-disciplinary optimization. To improve ease of use, DADOS provides a user-friendly graphical user interface and employed flow-based programming so that users can conduct design optimization just by dragging, dropping, and connecting algorithm blocks into a workflow instead of writing massive code. Moreover, it also includes an exclusive ensemble surrogate modeling technique, the extended hybrid adaptive function, which can make use of the advantages of each surrogate and eliminate the effort of selecting the appropriate individual surrogate. DADOS has nearly 30 key algorithms, including the design of experiments, surrogate models, model validation and selection, prediction, optimization, and sensitivity analysis. This paper presents a cloud-based data-driven design optimization system, named DADOS, to help engineers and researchers improve a design or product easily and efficiently. This paper provides a new approach for intelligent sensing and feedback of corrugated compensators in the piping system. The important state information hidden in the multi-source data obtained by limited sensors is effectively mined to achieve the real-time prediction of the stress field. The single prediction time of the digital twin is 0.76% of the time spent on finite element analysis, and the prediction result has good consistency with the true response under dynamic input, indicating that the digital twin can achieve fast and accurate stress field prediction. The results show that the values of performance metrics correlation of determination R2 and standardized average leave-one-out cross-validation CVavg of the digital twin satisfy the recommended threshold, which indicates that the digital twin has excellent predictive performance. The sensing data of three types of displacements are used as the associated information of a finite element model with 19,800 elements and its digital twin. Therefore, this paper proposes a digital twin construction method for global mechanical response sensing of corrugated compensators, combining Gaussian process regression in machine learning and finite element analysis. ![]() However, the stress monitoring method of corrugated compensators with limited localized sensors lack real-time and full-domain sensing. To reduce the risk of the piping system with corrugated compensators and improve the safety and stability of industrial equipment, condition monitoring and fault diagnosis of bellows is necessary. The corrugated compensators are important components in the piping system, absorbing mechanical deformation flexibly.
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