In order to study the variation o f the asphalt pavement water film thickness influenced by multi-factors,anew method for predicting water film thickness was developed by the combination o f the artificial neural netw...In order to study the variation o f the asphalt pavement water film thickness influenced by multi-factors,anew method for predicting water film thickness was developed by the combination o f the artificial neural network(ANN)a d two-dimensional shallow water equations based on hydrodynamic theory.Multi-factors included the rainfall intensity,pavement width,cross slope,longitudinal slope a d pavement roughness coefficient.The two-dimensional hydrodynamic method was validated by a natural rainfall event.Based on the design scheme o f Shen-Sha expressway engineering project,the limited training data obtained by the two-dimensional hydrodynamic simulation model was used to predict water film thickness.Furthermore,the distribution of the water film thickness influenced by multi-factors on the pavement was analyzed.The accuracy o f the ANN model was verified by the18sets o f data with a precision o f0.991.The simulation results indicate that the water film thickness increases from the median strip to the edge o f the pavement.The water film thickness variation is obviously influenced by rainfall intensity.Under the condition that the pavement width is20m and t e rainfall intensity is3m m/h,t e water film thickness is below10mm in the fast lane and20mm in t e lateral lane.Athough there is fluctuation due to the amount oftraining data,compared with the calculation on the basis o f the existing criterion and theory,t e ANN model exhibits a better performance for depicting the macroscopic distribution of the asphalt pavement water film.展开更多
[ Objective] The aim was to study the optimum extraction condition of dietary fiber of wheat bran and to discuss its influence on viscosity-elasticity of noodle dough with added extracts. [ Methed] Influences of a-amy...[ Objective] The aim was to study the optimum extraction condition of dietary fiber of wheat bran and to discuss its influence on viscosity-elasticity of noodle dough with added extracts. [ Methed] Influences of a-amylase, alkaline concentration, alkaline hydrolysis time and temperature on water holding capability and swelling capacity of dietary fiber were evaluated using single-factor test and orthogonal test. Effects of added dietary fiber from wheat bran on dough absorption ratio, rupture stress of dough and creep resistance were studied. [ Result] When the hydrolysis condi-tions of wheat bran were 0.4% a-amylase at 75 ℃ for 60 rain, further alkaline conditions were 5% sodium hydroxide for 60 min at 65 ℃, dietary fi-ber exhibited fine water holding capability and swelling capacity. The addition of 3%-5% dietary fiber from wheat bran into dough had little influence on the water absorption ratio of noodle, rupture stress of dough, creep resistance and can make functional noodle with rich dietary fiber from wheat bran. [Coonclusion] The study provided reference for the comprehensive utilization of wheat bran and development of functional product.展开更多
A leak detection method based on Bayesian theory and Fisher’s law was developed for water distribution systems. A hydraulic model was associated with the parameters of leaks (location, extent). The randomness of para...A leak detection method based on Bayesian theory and Fisher’s law was developed for water distribution systems. A hydraulic model was associated with the parameters of leaks (location, extent). The randomness of parameter values was quantified by probability density function and updated by Bayesian theory. Values of the parameters were estimated based on Fisher’s law. The amount of leaks was estimated by back propagation neural network. Based on flow characteristics in water distribution systems, the location of leaks can be estimated. The effectiveness of the proposed method was illustrated by simulated leak data of node pressure head and flow rate of pipelines in a test pipe network, and the leaks were spotted accurately and renovated on time.展开更多
一种改善抗拉强度的尼龙缝合线在美国新泽西州Ethicon of Somerville登记,专利号为U S Patent 5843574。 缝合线是用融熔挤压、并在控制温湿度条件下骤冷形成的细旦尼龙长丝,然后经过3.0-5.5倍的拉伸处理。长丝在均匀的张力下卷绕在架子...一种改善抗拉强度的尼龙缝合线在美国新泽西州Ethicon of Somerville登记,专利号为U S Patent 5843574。 缝合线是用融熔挤压、并在控制温湿度条件下骤冷形成的细旦尼龙长丝,然后经过3.0-5.5倍的拉伸处理。长丝在均匀的张力下卷绕在架子上,然后用120℃-185℃的温度进行热定型处理至少30分钟。这种热定型最长可到8小时,但以2至4小时为首选条件。 缝合线经过下列试验: 打结强力 抗拉强力 结构稳定性 热定型工序的目的是使纤维结晶度达到最佳化。展开更多
Fracking is one of the kernel technologies in the remarkable shale gas revolution. The extended finite element method is used in this paper to numerically investigate the interaction between hydraulic and natural frac...Fracking is one of the kernel technologies in the remarkable shale gas revolution. The extended finite element method is used in this paper to numerically investigate the interaction between hydraulic and natural fractures, which is an important issue of the enigmatic fracture network formation in fracking. The criteria which control the opening of natural fracture and crossing of hydraulic fracture are tentatively presented. Influence factors on the interaction process are systematically analyzed, which include the approach angle, anisotropy of in-situ stress and fluid pressure profile.展开更多
In this paper, the effect of pre-existing discrete fracture network(DFN) connectivity on hydraulic fracturing is numerically investigated in a rock mass subjected to in-situ stress. The simulation results show that DF...In this paper, the effect of pre-existing discrete fracture network(DFN) connectivity on hydraulic fracturing is numerically investigated in a rock mass subjected to in-situ stress. The simulation results show that DFN connectivity has a significant influence on the hydraulic fracture(HF) & DFN interaction and hydraulic fracturing effectiveness, which can be characterized by the total interaction area, stimulated DFN length, stimulated HF length, leak-off ratio, and stimulated total length. In addition, even at the same fluid injection rate, simulation models exhibit different responses that are strongly affected by the DFN connectivity. At a low injection rate, total interaction area decreases with increasing DFN connectivity; at a high injection rate, total interaction area increases with the increase of DFN connectivity. However, for any injection rate, the stimulated DFN length increases and stimulated HF length decreases with the increase of connectivity. Generally, this work shows that the DFN connectivity plays a crucial role in the interaction between hydraulic fractures, the pre-existing natural fractures and hydraulic fracturing effectiveness; in return, these three factors affect treating pressure, created microseismicity and corresponding stimulated volume. This work strongly relates to the production technology and the evaluation of hydraulic fracturing effectiveness. It is helpful for the optimization of hydraulic fracturing simulations in naturally fractured formations.展开更多
基金The National Natural Science Foundation of China(No.51478114,51778136)the Transportation Science and Technology Program of Liaoning Province(No.201532)
文摘In order to study the variation o f the asphalt pavement water film thickness influenced by multi-factors,anew method for predicting water film thickness was developed by the combination o f the artificial neural network(ANN)a d two-dimensional shallow water equations based on hydrodynamic theory.Multi-factors included the rainfall intensity,pavement width,cross slope,longitudinal slope a d pavement roughness coefficient.The two-dimensional hydrodynamic method was validated by a natural rainfall event.Based on the design scheme o f Shen-Sha expressway engineering project,the limited training data obtained by the two-dimensional hydrodynamic simulation model was used to predict water film thickness.Furthermore,the distribution of the water film thickness influenced by multi-factors on the pavement was analyzed.The accuracy o f the ANN model was verified by the18sets o f data with a precision o f0.991.The simulation results indicate that the water film thickness increases from the median strip to the edge o f the pavement.The water film thickness variation is obviously influenced by rainfall intensity.Under the condition that the pavement width is20m and t e rainfall intensity is3m m/h,t e water film thickness is below10mm in the fast lane and20mm in t e lateral lane.Athough there is fluctuation due to the amount oftraining data,compared with the calculation on the basis o f the existing criterion and theory,t e ANN model exhibits a better performance for depicting the macroscopic distribution of the asphalt pavement water film.
基金Supported by National Science and Technology Fund(31171753)International Science and Technology Cooperation Program of Anhui Province(10080703035)Natural Scientific Research Fund of Universities in Anhui Province(KJ2009A109)
文摘[ Objective] The aim was to study the optimum extraction condition of dietary fiber of wheat bran and to discuss its influence on viscosity-elasticity of noodle dough with added extracts. [ Methed] Influences of a-amylase, alkaline concentration, alkaline hydrolysis time and temperature on water holding capability and swelling capacity of dietary fiber were evaluated using single-factor test and orthogonal test. Effects of added dietary fiber from wheat bran on dough absorption ratio, rupture stress of dough and creep resistance were studied. [ Result] When the hydrolysis condi-tions of wheat bran were 0.4% a-amylase at 75 ℃ for 60 rain, further alkaline conditions were 5% sodium hydroxide for 60 min at 65 ℃, dietary fi-ber exhibited fine water holding capability and swelling capacity. The addition of 3%-5% dietary fiber from wheat bran into dough had little influence on the water absorption ratio of noodle, rupture stress of dough, creep resistance and can make functional noodle with rich dietary fiber from wheat bran. [Coonclusion] The study provided reference for the comprehensive utilization of wheat bran and development of functional product.
基金Supported by National Natural Science Foundation of China (No. 50278062 and 50578108)Science and Technology Innovation Funds Project of Tianjin, China (No. 08FDZDSF03200)
文摘A leak detection method based on Bayesian theory and Fisher’s law was developed for water distribution systems. A hydraulic model was associated with the parameters of leaks (location, extent). The randomness of parameter values was quantified by probability density function and updated by Bayesian theory. Values of the parameters were estimated based on Fisher’s law. The amount of leaks was estimated by back propagation neural network. Based on flow characteristics in water distribution systems, the location of leaks can be estimated. The effectiveness of the proposed method was illustrated by simulated leak data of node pressure head and flow rate of pipelines in a test pipe network, and the leaks were spotted accurately and renovated on time.
基金supported by the National Natural Science Foundation of China (Grant No. 11372157)the Special Research Grant for Doctor Discipline by Ministry of Education of China (Grant No. 20120002110075)the Foundation for the Author of National Excellent Doctoral Dissertation of China (FANEDD) (Grant No. 201326)
文摘Fracking is one of the kernel technologies in the remarkable shale gas revolution. The extended finite element method is used in this paper to numerically investigate the interaction between hydraulic and natural fractures, which is an important issue of the enigmatic fracture network formation in fracking. The criteria which control the opening of natural fracture and crossing of hydraulic fracture are tentatively presented. Influence factors on the interaction process are systematically analyzed, which include the approach angle, anisotropy of in-situ stress and fluid pressure profile.
基金the National Natural Science Foundation of China(Grant Nos.41227901,41502294&41330643)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grants Nos.XDB10030000,XDB10030300&XDB10050400)
文摘In this paper, the effect of pre-existing discrete fracture network(DFN) connectivity on hydraulic fracturing is numerically investigated in a rock mass subjected to in-situ stress. The simulation results show that DFN connectivity has a significant influence on the hydraulic fracture(HF) & DFN interaction and hydraulic fracturing effectiveness, which can be characterized by the total interaction area, stimulated DFN length, stimulated HF length, leak-off ratio, and stimulated total length. In addition, even at the same fluid injection rate, simulation models exhibit different responses that are strongly affected by the DFN connectivity. At a low injection rate, total interaction area decreases with increasing DFN connectivity; at a high injection rate, total interaction area increases with the increase of DFN connectivity. However, for any injection rate, the stimulated DFN length increases and stimulated HF length decreases with the increase of connectivity. Generally, this work shows that the DFN connectivity plays a crucial role in the interaction between hydraulic fractures, the pre-existing natural fractures and hydraulic fracturing effectiveness; in return, these three factors affect treating pressure, created microseismicity and corresponding stimulated volume. This work strongly relates to the production technology and the evaluation of hydraulic fracturing effectiveness. It is helpful for the optimization of hydraulic fracturing simulations in naturally fractured formations.
