Thermo-mechanical coupling analysis of APSE using submodels and neural networks

The ,Aspoe Pillar Stability Experiment （APSE） is an in situ experiment for investigating the spalling mechanism under mechanical and thermal loading conditions in a crystalline rock. In this study, the thermo-mechanical behaviors in the APSE were investigated with three models： （1） a Full model with rough meshes for calculating the influence of tunnel excavation; （2） a Submodel with fine meshes for predicting the thermo-mechanical behavior in the pillar during the borehole drilling, heating, and cool- ing phases; and （3） a Thin model for modeling the effect of slot cutting for de-stressing around the pillar. In order to import the stresses calculated from the Full model to the Submodel and to define the complex thermal boundary conditions, artificial neural networks （NNs） were utilized. From this study, it was pos- sible to conclude that the stepwise approach with the application of NNs was useful for predicting the complex response of the pillar under severe thermo-mechanical loading conditions.

Research on Digital and Analog Electronic Experiment Teaching Course Management based on UltraLab Network Experiment Platform

Digital circuit and analog circuit courses are basic courses for students of science and engineering universities. Among them,the practical courses are of great significance for students to master the knowledge of electronics. In order to make teachers teaching more efficiently and students studying more quickly,how to update the experimental course in teaching reform is the key point. This paper analyzing the present situation of teaching in the digital circuit and analog circuit courses,the teaching questions in universities. On the basis of it,the innovation measures of experimental teaching methods and contents are discussed. Our school tries to introduce the UltraLab network experiment platform,reform and optimize the teaching methods of related courses.And it’ s accelerating the construction and development of emerging engineering education’ s process,reducing effectively the teacher’s time for managing in equipment,improving the students’ ability to use instruments.

Modeling, analysis, and screening of cyclic pressure pulsing with nitrogen in hydraulically fractured wells

Cyclic pressure pulsing with nitrogen is studied for hydraulically fractured wells in depleted reservoirs.A compositional simulation model is constructed to represent the hydraulic fractures through local-grid refinement.The process is analyzed from both operational and reservoir/hydraulic-fracture perspectives.Key sensitivity parameters for the operational component are chosen as the injection rate,lengths of injection and soaking periods and the economic rate limit to shut-in the well.For the reservoir/hydraulic fracturing components,reservoir permeability,hydraulic fracture permeability,effective thickness and half-length are used.These parameters are varied at five levels.A full-factorial experimental design is utilized to run 1250 cases.The study shows that within the ranges studied,the gas-injection process is applied successfully for a 20-year project period with net present values based on the incremental recoveries greater than zero.It is observed that the cycle rate limit,injection and soaking periods must be optimized to maximize the efficiency.The simulation results are used to develop a neural network based proxy model that can be used as a screening tool for the process.The proxy model is validated with blind-cases with a correlation coefficient of 0.96.