In this work, we have developed a data-driven artificial intelligence (AI) solution to assist the ship hull design process. Specifically, we have developed and implemented an AI-based multiple-input neural network mod...
详细信息
In this work, we have developed a data-driven artificial intelligence (AI) solution to assist the ship hull design process. Specifically, we have developed and implemented an AI-based multiple-input neural network model to realize the real-time prediction of the total resistance of the ship hull structure while avoiding the inconsistent estimates from different types of design input parameters. It is demonstrated that the developed AI-based machine learning algorithm as a prediction tool can assist the ship hull design process by accurately providing the total resistance of ship hulls in real time. Moreover, we have conducted design tasks to validate the proposed method, and the validation results show that a well-trained artificial neural network model can avoid the problem of different sensitivities due to the different degrees of influence of the input parameters on the output parameter. The proposed AI-based data-driven solution provides a real-time hydrodynamic performance calculation, which can predict the hyperdynamic performances of ship hulls based on their geometry modification parameters. This approach gives a consistent prediction in terms of accuracy when facing different geometry modification parameters, and it in turn provides a fast and accurate AI-based method to assist ship hull design to achieve an optimum forecast accuracy in the entire design space, making an advance to artificial intelligence assist design in naval architecture engineering.
The components of complex systems such as automobiles or ships communicate via connectors, including wires, hoses, or pipes whose weight could substantially increase the total weight of the system. Hence, it is of par...
详细信息
The components of complex systems such as automobiles or ships communicate via connectors, including wires, hoses, or pipes whose weight could substantially increase the total weight of the system. Hence, it is of paramount importance to lay out these connectors such that their overall weight is minimized. In this paper, a computationally efficient approach is proposed to optimize the layout of flexible connectors (e.g., cable harnesses) by minimizing their overall length while maximizing their common length. The approach provides a framework to mathematically model the cable harness layout optimization problem. A Multiobjective Genetic Algorithm (MOGA) solver is then applied to solve the optimization problem, which outputs a set of non-dominated solutions to the bi-objective problem. Finally, the effects of the workspace's geometric structure on the optimal layouts of cable harnesses are discussed using sample test cases. The overarching objective of this study is to provide insight for designers of cable harnesses when deciding on the final layout of connectors considering aspects such as accessibility to and maintainability of these connectors.
A novel hybrid six-bar mechanism with non-circular gear constraints and its optimal synthesis method for complex multi-pose rigid body guidance tasks are proposed. An innovative optimization module is proposed to opti...
详细信息
A novel hybrid six-bar mechanism with non-circular gear constraints and its optimal synthesis method for complex multi-pose rigid body guidance tasks are proposed. An innovative optimization module is proposed to optimize the non-circularity and smoothness of non-circular gear pitch curves. The optimization synthesis of this mechanism is divided into two steps. The first step is to conduct multi-objective constraint optimization with pose error and non-circular gear pitch curve as optimization objectives to obtain the required diversified non-inferior solution set. Second, a set of solutions are selected from the solution set to construct the optimization function of non-circular gear pitch curves. The non-circularity and smoothness of the pitch curve are optimized to the maximum extent, and the pose change is ensured to be small. Finally, the multi-pose picking and planting of vegetable pot seedlings were realized using the proposed mechanism and optimization synthesis method. The final optimization design results show that the error between the actual pose and the required pose of the compact hybrid mechanism is small. The optimization effect of non-circularity and smoothness of non-circular gear pitch curves is pronounced. The effectiveness of the mechanism is verified via kinematic simulation.
Multi-objective optimization (MOO) problems with computationally expensive constraints are commonly seen in real-world engineering design. However, metamodel-baseddesign optimization (MBDO) approaches for MOO are oft...
详细信息
Multi-objective optimization (MOO) problems with computationally expensive constraints are commonly seen in real-world engineering design. However, metamodel-baseddesign optimization (MBDO) approaches for MOO are often not suitable for high-dimensional problems and often do not support expensive constraints. In this work, the situational adaptive Kreisselmeier and Steinhauser (SAKS) method was combined with a new multi-objective trust region optimizer (MTRO) strategy to form the SAKS-MTRO method for MOO problems with expensive black-box constraint functions. The SAKS method is an approach that hybridizes the modeling and aggregation of expensive constraints and adds an adaptive strategy to control the level of hybridization. The MTRO strategy uses a combination of objective decomposition and K-means clustering to handle MOO problems. SAKS-MTRO was benchmarked against four popular multi-objective optimizers and demonstrated superior performance on average. SAKS-MTRO was also applied to optimize the design of a semiconductor substrate and the design of an industrial recessed impeller.
暂无评论