In practical applications,noble metal doping is often used to prepare high performance gas sensors,but more noble metal doping will lead to higher preparation costs.In this study,CeO_(2)/ZnO-Pd with low palladium cont...In practical applications,noble metal doping is often used to prepare high performance gas sensors,but more noble metal doping will lead to higher preparation costs.In this study,CeO_(2)/ZnO-Pd with low palladium content was prepared by ultrasonic method with fast response and high selectivity for acetone sensing.With the same amount of palladium added,the selectivity coefficient of CeO_(2)/ZnO-Pd is 1.88 times higher than that of the stirred sensor.Compared with the pure PdO-doped CeO_(2)/ZnO-PdO material,the content of Pd in CeO_(2)/ZnO-PdO is about 30%of that in CeO_(2)/ZnO-PdO,but the selectivity coefficient for acetone is 2.56 times higher.The CeO_(2)/ZnO-Pd sensor has a higher response(22.54)to 50×10^(−6) acetone at 300℃and the selectivity coefficient is 2.57 times that of the CeO_(2)/ZnO sensor.The sensor has a sub-second response time(0.6 s)and still has a 2.36 response to 330×10^(−9) of acetone.Ultrasonic doping makes Pd particles smaller and increases the contact area with gas.Meanwhile,the composition of n-p-n heterojunction and the synergistic effect of Pd/PdO improve the sensor performance.It shows that ultrasonic Pd doping provides a way to improve the utilization rate of doped metals and prepare highly selective gas sensors.展开更多
When the geological environment of rock masses is disturbed,numerous non-persisting open joints can appear within it.It is crucial to investigate the effect of open joints on the mechanical properties of rock mass.How...When the geological environment of rock masses is disturbed,numerous non-persisting open joints can appear within it.It is crucial to investigate the effect of open joints on the mechanical properties of rock mass.However,it has been challenging to generate realistic open joints in traditional experimental tests and numerical simulations.This paper presents a novel solution to solve the problem.By utilizing the stochastic distribution of joints and an enhanced-fractal interpolation system(IFS)method,rough curves with any orientation can be generated.The Douglas-Peucker algorithm is then applied to simplify these curves by removing unnecessary points while preserving their fundamental shape.Subsequently,open joints are created by connecting points that move to both sides of rough curves based on the aperture distribution.Mesh modeling is performed to construct the final mesh model.Finally,the RB-DEM method is applied to transform the mesh model into a discrete element model containing geometric information about these open joints.Furthermore,this study explores the impacts of rough open joint orientation,aperture,and number on rock fracture mechanics.This method provides a realistic and effective approach for modeling and simulating these non-persisting open joints.展开更多
The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establis...The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.展开更多
In this paper,a new strategy for a sub-element-based shock capturing for discontinuous Galerkin(DG)approximations is presented.The idea is to interpret a DG element as a col-lection of data and construct a hierarchy o...In this paper,a new strategy for a sub-element-based shock capturing for discontinuous Galerkin(DG)approximations is presented.The idea is to interpret a DG element as a col-lection of data and construct a hierarchy of low-to-high-order discretizations on this set of data,including a first-order finite volume scheme up to the full-order DG scheme.The dif-ferent DG discretizations are then blended according to sub-element troubled cell indicators,resulting in a final discretization that adaptively blends from low to high order within a single DG element.The goal is to retain as much high-order accuracy as possible,even in simula-tions with very strong shocks,as,e.g.,presented in the Sedov test.The framework retains the locality of the standard DG scheme and is hence well suited for a combination with adaptive mesh refinement and parallel computing.The numerical tests demonstrate the sub-element adaptive behavior of the new shock capturing approach and its high accuracy.展开更多
基金Project(2023JJ10005)supported by the Natural Science Foundation of Hunan Province,ChinaProjects(51772082,51804106)supported by the National Natural Science Foundation of China。
文摘In practical applications,noble metal doping is often used to prepare high performance gas sensors,but more noble metal doping will lead to higher preparation costs.In this study,CeO_(2)/ZnO-Pd with low palladium content was prepared by ultrasonic method with fast response and high selectivity for acetone sensing.With the same amount of palladium added,the selectivity coefficient of CeO_(2)/ZnO-Pd is 1.88 times higher than that of the stirred sensor.Compared with the pure PdO-doped CeO_(2)/ZnO-PdO material,the content of Pd in CeO_(2)/ZnO-PdO is about 30%of that in CeO_(2)/ZnO-PdO,but the selectivity coefficient for acetone is 2.56 times higher.The CeO_(2)/ZnO-Pd sensor has a higher response(22.54)to 50×10^(−6) acetone at 300℃and the selectivity coefficient is 2.57 times that of the CeO_(2)/ZnO sensor.The sensor has a sub-second response time(0.6 s)and still has a 2.36 response to 330×10^(−9) of acetone.Ultrasonic doping makes Pd particles smaller and increases the contact area with gas.Meanwhile,the composition of n-p-n heterojunction and the synergistic effect of Pd/PdO improve the sensor performance.It shows that ultrasonic Pd doping provides a way to improve the utilization rate of doped metals and prepare highly selective gas sensors.
基金supported by the National Key R&D Program of China (2018YFC0407004)the Fundamental Research Funds for the Central Universities (Nos.B200201059,2021FZZX001-14)the National Natural Science Foundation of China (Grant No.51709089)and 111 Project.
文摘When the geological environment of rock masses is disturbed,numerous non-persisting open joints can appear within it.It is crucial to investigate the effect of open joints on the mechanical properties of rock mass.However,it has been challenging to generate realistic open joints in traditional experimental tests and numerical simulations.This paper presents a novel solution to solve the problem.By utilizing the stochastic distribution of joints and an enhanced-fractal interpolation system(IFS)method,rough curves with any orientation can be generated.The Douglas-Peucker algorithm is then applied to simplify these curves by removing unnecessary points while preserving their fundamental shape.Subsequently,open joints are created by connecting points that move to both sides of rough curves based on the aperture distribution.Mesh modeling is performed to construct the final mesh model.Finally,the RB-DEM method is applied to transform the mesh model into a discrete element model containing geometric information about these open joints.Furthermore,this study explores the impacts of rough open joint orientation,aperture,and number on rock fracture mechanics.This method provides a realistic and effective approach for modeling and simulating these non-persisting open joints.
基金supported by the National Key R&D Program of China(Grant No.2022YFB3303500).
文摘The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.
文摘In this paper,a new strategy for a sub-element-based shock capturing for discontinuous Galerkin(DG)approximations is presented.The idea is to interpret a DG element as a col-lection of data and construct a hierarchy of low-to-high-order discretizations on this set of data,including a first-order finite volume scheme up to the full-order DG scheme.The dif-ferent DG discretizations are then blended according to sub-element troubled cell indicators,resulting in a final discretization that adaptively blends from low to high order within a single DG element.The goal is to retain as much high-order accuracy as possible,even in simula-tions with very strong shocks,as,e.g.,presented in the Sedov test.The framework retains the locality of the standard DG scheme and is hence well suited for a combination with adaptive mesh refinement and parallel computing.The numerical tests demonstrate the sub-element adaptive behavior of the new shock capturing approach and its high accuracy.
