In this paper,a discrete element model for collapse simulation of RC frame structure is constructed by discretizing the structure into a few elements and spring groups.This model introduces special hysteretic models o...In this paper,a discrete element model for collapse simulation of RC frame structure is constructed by discretizing the structure into a few elements and spring groups.This model introduces special hysteretic models of connected springs for arbitrary loading path and also takes into account reasonable failure criteria for springs considering coupling effect of shear and axial force.Based on the discrete element model,a computer program is developed to simulate the whole process of RC frame structures from initial state to collapse under earthquakes.Particularly,the contact-impact problem between discrete elements has been treated with effective measures.Then,the program is employed to study the collapse mechanism of a real building in Wenchuan earthquake-hit area;the result of which shows that the simulation program developed based on the new model can realistically simulate the seismic collapse process of RC frame structures.展开更多
Quantum machine learning based on quantum algorithms may achieve an exponential speedup over classical algorithms in dealing with some problems such as clustering.In this paper,we use the method of training the lower ...Quantum machine learning based on quantum algorithms may achieve an exponential speedup over classical algorithms in dealing with some problems such as clustering.In this paper,we use the method of training the lower bound of the average log likelihood function on the quantum Boltzmann machine(QBM)to recognize the handwritten number datasets and compare the training results with classical models.We find that,when the QBM is semi-restricted,the training results get better with fewer computing resources.This shows that it is necessary to design a targeted algorithm to speed up computation and save resources.展开更多
文摘In this paper,a discrete element model for collapse simulation of RC frame structure is constructed by discretizing the structure into a few elements and spring groups.This model introduces special hysteretic models of connected springs for arbitrary loading path and also takes into account reasonable failure criteria for springs considering coupling effect of shear and axial force.Based on the discrete element model,a computer program is developed to simulate the whole process of RC frame structures from initial state to collapse under earthquakes.Particularly,the contact-impact problem between discrete elements has been treated with effective measures.Then,the program is employed to study the collapse mechanism of a real building in Wenchuan earthquake-hit area;the result of which shows that the simulation program developed based on the new model can realistically simulate the seismic collapse process of RC frame structures.
基金supported by the National Natural Science Foundation of China under Grant No.11725524the Hubei Provincal Natural Science Foundation of China under Grant No.2019CFA003
文摘Quantum machine learning based on quantum algorithms may achieve an exponential speedup over classical algorithms in dealing with some problems such as clustering.In this paper,we use the method of training the lower bound of the average log likelihood function on the quantum Boltzmann machine(QBM)to recognize the handwritten number datasets and compare the training results with classical models.We find that,when the QBM is semi-restricted,the training results get better with fewer computing resources.This shows that it is necessary to design a targeted algorithm to speed up computation and save resources.
