Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the...Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the soil thermal conductivity had been known in the simulation of thermal response test.The thermal response curve was firstly obtained through numerical calculation.Then,the accuracy of the numerical model was verified with measured data obtained through a thermal response test.Based on the numerical and experimental thermal response curves,the thermal conductivity of the soil was calculated by different parameter identification methods.The calculated results were compared with the assumed value and then the accuracy of these methods was evaluated.Furthermore,the effects of test time,variable data quality,borehole radius,initial ground temperature,and heat injection rate were analyzed.The results show that the method based on cylinder-source model has a low precision and the identified thermal conductivity decreases with an increase in borehole radius.For parameter estimation,the measuring accuracy of the initial temperature of the deep ground soil has greater effect on identified thermal conductivity.展开更多
In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata...In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata model is established based on function analysis of the zone controller, and the correctness of the model is verified by UPPAAL. Then by parsing the timed automata model files, state information and transition conditions can be extracted to generate test case sets. Finally, according to the serialization conditions of test cases, the test cases are serialized into test sequences by using the improved depth first search algorithm. A case, the ZC controls the train running within its jurisdiction, shows that the method is correct and can effectively improve the efficiency of test sequence generation.展开更多
Early warning model of debris flow is important for providing local residents with reliable and accurate warning information to escape from debris flow hazards. This research studied the debris flow initiation in the ...Early warning model of debris flow is important for providing local residents with reliable and accurate warning information to escape from debris flow hazards. This research studied the debris flow initiation in the Yindongzi gully in Dujiangyan City, Sichuan province, China with scaled-down model experiments. We set rainfall intensity and slope angle as dominating parameters and carried out 20 scaled-down model tests under artificial rainfall conditions. The experiments set four slope angles(32°, 34°, 37°, 42°) and five rainfall intensities(60 mm/h, 90 mm/h, 120 mm/h, 150 mm/h, and 180 mm/h) treatments. The characteristic variables in the experiments, such as, rainfall duration, pore water pressure, moisture content, surface inclination, and volume were monitored. The experimental results revealed the failure mode of loose slope material and the process of slope debris flow initiation, as well as the relationship between the surface deformation and the physical parameters of experimental model. A traditional rainfall intensity-duration early warning model(I-D model) was firstly established by using a mathematical regression analysis, and it was then improved into ISD model and ISM model(Here, I is rainfall Intensity, S is Slope angle, D is rainfall Duration, and M is Moisture content). The warning model can provide reliable early warning of slope debris flow initiation.展开更多
基金Project(xjj20100078) supported by the Fundamental Research Funds for the Central Universities in China
文摘Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the soil thermal conductivity had been known in the simulation of thermal response test.The thermal response curve was firstly obtained through numerical calculation.Then,the accuracy of the numerical model was verified with measured data obtained through a thermal response test.Based on the numerical and experimental thermal response curves,the thermal conductivity of the soil was calculated by different parameter identification methods.The calculated results were compared with the assumed value and then the accuracy of these methods was evaluated.Furthermore,the effects of test time,variable data quality,borehole radius,initial ground temperature,and heat injection rate were analyzed.The results show that the method based on cylinder-source model has a low precision and the identified thermal conductivity decreases with an increase in borehole radius.For parameter estimation,the measuring accuracy of the initial temperature of the deep ground soil has greater effect on identified thermal conductivity.
文摘In order to solve the problem of artificial generation and low efficiency of test sequences for zone controller (ZC), a model-based automatic generation method of test sequence is proposed. Firstly, the timed automata model is established based on function analysis of the zone controller, and the correctness of the model is verified by UPPAAL. Then by parsing the timed automata model files, state information and transition conditions can be extracted to generate test case sets. Finally, according to the serialization conditions of test cases, the test cases are serialized into test sequences by using the improved depth first search algorithm. A case, the ZC controls the train running within its jurisdiction, shows that the method is correct and can effectively improve the efficiency of test sequence generation.
基金financially supported by the CAS Pioneer Hundred Talents Programpthe Institute of Mountain Hazards and Environment(Grant No.SDS-135-1705)+1 种基金support from the National Natural Science Foundation of China(Grant No.41771021,41471429,and 41790443)the National Key Research and Development Program of China(Grant No.2017YFD0800501)
文摘Early warning model of debris flow is important for providing local residents with reliable and accurate warning information to escape from debris flow hazards. This research studied the debris flow initiation in the Yindongzi gully in Dujiangyan City, Sichuan province, China with scaled-down model experiments. We set rainfall intensity and slope angle as dominating parameters and carried out 20 scaled-down model tests under artificial rainfall conditions. The experiments set four slope angles(32°, 34°, 37°, 42°) and five rainfall intensities(60 mm/h, 90 mm/h, 120 mm/h, 150 mm/h, and 180 mm/h) treatments. The characteristic variables in the experiments, such as, rainfall duration, pore water pressure, moisture content, surface inclination, and volume were monitored. The experimental results revealed the failure mode of loose slope material and the process of slope debris flow initiation, as well as the relationship between the surface deformation and the physical parameters of experimental model. A traditional rainfall intensity-duration early warning model(I-D model) was firstly established by using a mathematical regression analysis, and it was then improved into ISD model and ISM model(Here, I is rainfall Intensity, S is Slope angle, D is rainfall Duration, and M is Moisture content). The warning model can provide reliable early warning of slope debris flow initiation.
