The influence of thermal circuit parameters on a buried underground cable is investigated using an ANFIS （adaptive neuro-fuzzy inference system）. Finite element solution of the heat conduction equation is used, comb...The influence of thermal circuit parameters on a buried underground cable is investigated using an ANFIS （adaptive neuro-fuzzy inference system）. Finite element solution of the heat conduction equation is used, combined with artificial intelligence methods. The cable temperature depends on several parameters, such as the ambient temperature, the currents flowing through the conductor and the resistivity of the surrounding soil. In this paper, ANFIS is used to simulate the problem of the thermal field of underground cables under various parameters variation and climatic conditions. The developed model was trained using data generated from FEM （finite element method） for different configurations （training set） of the thermal field problem. After training, the system is tested for several scenarios, differing significantly from the training cases. It is shown that the proposed method is very time efficient and accurate in calculating the thermal fields compared to the relatively time consuming finite element method; thus ANFIS provides a potential computationally efficient and inexpensive predictive tool for more effective thermal design of underground cable systems.展开更多
The waveguide to coaxial cable adapter is very important to the cavity beam position monitor （CBPM） because it determines how much of the energy in the cavity could be coupled outside. In this paper, the waveguide t...The waveguide to coaxial cable adapter is very important to the cavity beam position monitor （CBPM） because it determines how much of the energy in the cavity could be coupled outside. In this paper, the waveguide to coaxial cable adapter of a CBPM is designed and experiments are conducted. The curve shapes of experiments and simulations are very similar and the difference in reflection is less than 0.1. This progress provides a reliable method for designing the adapter.展开更多
文摘The influence of thermal circuit parameters on a buried underground cable is investigated using an ANFIS （adaptive neuro-fuzzy inference system）. Finite element solution of the heat conduction equation is used, combined with artificial intelligence methods. The cable temperature depends on several parameters, such as the ambient temperature, the currents flowing through the conductor and the resistivity of the surrounding soil. In this paper, ANFIS is used to simulate the problem of the thermal field of underground cables under various parameters variation and climatic conditions. The developed model was trained using data generated from FEM （finite element method） for different configurations （training set） of the thermal field problem. After training, the system is tested for several scenarios, differing significantly from the training cases. It is shown that the proposed method is very time efficient and accurate in calculating the thermal fields compared to the relatively time consuming finite element method; thus ANFIS provides a potential computationally efficient and inexpensive predictive tool for more effective thermal design of underground cable systems.
文摘The waveguide to coaxial cable adapter is very important to the cavity beam position monitor （CBPM） because it determines how much of the energy in the cavity could be coupled outside. In this paper, the waveguide to coaxial cable adapter of a CBPM is designed and experiments are conducted. The curve shapes of experiments and simulations are very similar and the difference in reflection is less than 0.1. This progress provides a reliable method for designing the adapter.
