A computational mass transfer model is proposed for predicting the concentration profile and Murphree efficiency of sieve tray distillation column. The proposed model is based on using modified c＇2 -εc＇ two equatio...A computational mass transfer model is proposed for predicting the concentration profile and Murphree efficiency of sieve tray distillation column. The proposed model is based on using modified c＇2 -εc＇ two equations formulation for closing the differential turbulent mass transfer equation with improvement by considering the vapor injected from the sieve hole to be three dimensional. The predicted concentration distributions by using proposed model were checked by experimental work conducted on a sieve tray simulator of 1.2 meters in diameter for desorbing the dissolved oxygen in the feed water by blowing air. The model predictions were confirmed by the experimental measurement. The validation of the proposed model was further tested by comparing the simulated result with the performance of an industrial scale sieve tray distillation column reported by Kunesh et al. for the stripping of toluene from its water solution. The predicted outlet concentration of each tray and the Murphree tray efficiencies under different operating conditions were in agreement with the published data. The simulated turbulent mass transfer diffusivity on each tray was within the range of the experimental result in the same sieve column reported by Cai et al. In addition, the prediction of the influence of sieve tray structure on the tray efficiency by using the proposed model was demonstrated.展开更多
This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-E...This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R^2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.展开更多
A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a n...A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.展开更多
The comparative study between unsteady flow models in alluvial streams shows a chaotic residue as for the choices of a forecasting model. The difficulty resides in the choice of the expressions of friction resistance ...The comparative study between unsteady flow models in alluvial streams shows a chaotic residue as for the choices of a forecasting model. The difficulty resides in the choice of the expressions of friction resistance and sediment transport. Three types of mathematical models were selected. Models of type one and two are fairly general, but require a considerable number of boundary conditions, which related to each size range of sediments. It can be a handicap during rivers studies which are not very well followed in terms of experimental measurements. Also, the use of complex models is not always founded. But then, the model of type three requires a limited number of boundary conditions and solves only a system of three equations at each time step. It allows a considerable saving in calculating times.展开更多
High Frequency(HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation(OI) method. The purpose of this work is to develop a real-time computationally highly efficient as...High Frequency(HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation(OI) method. The purpose of this work is to develop a real-time computationally highly efficient assimilation method to improve the forecast of shelf current. Since the true state of the ocean is not known, the specification of background error covariance is arduous. Usually, it is assumed or calculated from an ensemble of model states and is kept in constant. In our method, the spatial covariances of model forecast errors are derived from differences between the adjacent model forecast fields, which serve as the forecast tendencies. The assumption behind this is that forecast errors can resemble forecast tendencies, since variances are large when fields change quickly and small when fields change slowly. The implementation of HF radar data assimilation is found to yield good information for analyses. After assimilation, the root-mean-square error of model decreases significantly. Besides, three assimilation runs with variational observation density are implemented. The comparison of them indicates that the pattern described by observations is much more important than the amount of observations. It is more useful to expand the scope of observations than to increase the spatial interval. From our tests, the spatial interval of observation can be 5 times bigger than that of model grid.展开更多
In order to minimize the harm caused by the instability of a planing craft, a motion prediction model is essential. This paper analyzed the feasibility of using an MGM（1,N） model in grey system theory to predict pla...In order to minimize the harm caused by the instability of a planing craft, a motion prediction model is essential. This paper analyzed the feasibility of using an MGM（1,N） model in grey system theory to predict planing craft motion and carried out the numerical simulation experiment. According to the characteristics of planing craft motion, a recurrence formula was proposed of the parameter matrix of an MGMfl,N） model. Using this formula, data can be updated in real-time without increasing computational complexity significantly. The results of numerical simulation show that using an MGM（1,N） model to predict planing motion is feasible and useful for prediction. So the method proposed in this study can reflect the planing craft motion mechanism successfully, and has rational and effective functions of forecasting and analyzing trends.展开更多
In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and ...In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and flexible model to predict overheads of these mechanisms. This model is based on overheads of basic operations frequently used in cryptography algorithms, which are essential elements of security mechanisms. Several popular cryptography algorithms and security mechanisms are evaluated using this model. According to simulation results, relative prediction errors are less than 7% for most cryptography algorithms and security mechanisms.展开更多
The mesoscopic modeling developed rapidly in the past three decades is a promising tool for predicting and understanding the microstructure evolution at grain scale.In this paper,the recent development of mesoscopic m...The mesoscopic modeling developed rapidly in the past three decades is a promising tool for predicting and understanding the microstructure evolution at grain scale.In this paper,the recent development of mesoscopic modeling and its application to microstructure evolution in steels is reviewed.Firstly,some representative computational models are briefly introduced,e.g.,the phase field model,the cellular automaton model and the Monte Carlo model.Then,the emphasis is put on the application of mesoscopic modeling of the complex features of microstructure evolution,including solidification,solid-state phase transformation,recrystallization and grain growth.Finally,some issues in the present mesoscopic modeling and its perspective are discussed.展开更多
Bispyribac is a widely used herbicide that targets the acetohydroxyacid synthase （AHAS） enzyme. Mutations in AHAS have caused serious herbicide resistance that threatened the continued use of the herbicide. So far, ...Bispyribac is a widely used herbicide that targets the acetohydroxyacid synthase （AHAS） enzyme. Mutations in AHAS have caused serious herbicide resistance that threatened the continued use of the herbicide. So far, a unified model to decipher herb- icide resistance in molecular level with good prediction is still lacking. In this paper, we have established a new QSAR method to construct a prediction model for AHAS mutation resistance to herbicide Bispyribac. A series of AHAS mutants concerned with the herbicide resistance were constructed, and the inhibitory properties of Bispyribac against these mutants were meas- ured. The 3D-QSAR method has been transformed to process the AHAS mutants and proposed as mutation-dependent biom- acromolecular QSAR （MB-QSAR）. The excellent correlation between experimental and computational data gave the MB-QSAR/CoMFA model （q2 = 0.615, P = 0.921, F2pred = 0.598） and the MB-QSAR/CoMSIA model （q2 = 0.446, r2 = 0.929, r2pred = 0.612）, which showed good prediction for the inhibition properties of Bispyribac against AHAS mutants. Such MB-QSAR models, containing the three-dimensional molecular interaction diagram, not only disclose to us for the first time the detailed three-dimensional information about the structure-resistance relationships, but may also provide further guidance to resistance mutation evolution. Also, the molecular interaction diagram derived from MB-QSAR models may aid the resistance-evading herbicide design.展开更多
基金Supported by the National lqatural Science Foundation of China （20736005）.
文摘A computational mass transfer model is proposed for predicting the concentration profile and Murphree efficiency of sieve tray distillation column. The proposed model is based on using modified c＇2 -εc＇ two equations formulation for closing the differential turbulent mass transfer equation with improvement by considering the vapor injected from the sieve hole to be three dimensional. The predicted concentration distributions by using proposed model were checked by experimental work conducted on a sieve tray simulator of 1.2 meters in diameter for desorbing the dissolved oxygen in the feed water by blowing air. The model predictions were confirmed by the experimental measurement. The validation of the proposed model was further tested by comparing the simulated result with the performance of an industrial scale sieve tray distillation column reported by Kunesh et al. for the stripping of toluene from its water solution. The predicted outlet concentration of each tray and the Murphree tray efficiencies under different operating conditions were in agreement with the published data. The simulated turbulent mass transfer diffusivity on each tray was within the range of the experimental result in the same sieve column reported by Cai et al. In addition, the prediction of the influence of sieve tray structure on the tray efficiency by using the proposed model was demonstrated.
文摘This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R^2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.
基金Project(9140A18010210KG01) supported by the Departmental Pre-Research Fund of China
文摘A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.
文摘The comparative study between unsteady flow models in alluvial streams shows a chaotic residue as for the choices of a forecasting model. The difficulty resides in the choice of the expressions of friction resistance and sediment transport. Three types of mathematical models were selected. Models of type one and two are fairly general, but require a considerable number of boundary conditions, which related to each size range of sediments. It can be a handicap during rivers studies which are not very well followed in terms of experimental measurements. Also, the use of complex models is not always founded. But then, the model of type three requires a limited number of boundary conditions and solves only a system of three equations at each time step. It allows a considerable saving in calculating times.
基金supported by the State Oceanic Administration Young Marine Science Foundation (No. 2013201)the Shandong Provincial Key Laboratory of Marine Ecology and Environment & Disaster Prevention and Mitigation Foundation (No. 2012007)+1 种基金the Marine Public Foundation (No. 201005018)the North China Sea Branch Scientific Foundation (No. 2014B10)
文摘High Frequency(HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation(OI) method. The purpose of this work is to develop a real-time computationally highly efficient assimilation method to improve the forecast of shelf current. Since the true state of the ocean is not known, the specification of background error covariance is arduous. Usually, it is assumed or calculated from an ensemble of model states and is kept in constant. In our method, the spatial covariances of model forecast errors are derived from differences between the adjacent model forecast fields, which serve as the forecast tendencies. The assumption behind this is that forecast errors can resemble forecast tendencies, since variances are large when fields change quickly and small when fields change slowly. The implementation of HF radar data assimilation is found to yield good information for analyses. After assimilation, the root-mean-square error of model decreases significantly. Besides, three assimilation runs with variational observation density are implemented. The comparison of them indicates that the pattern described by observations is much more important than the amount of observations. It is more useful to expand the scope of observations than to increase the spatial interval. From our tests, the spatial interval of observation can be 5 times bigger than that of model grid.
基金Supported by the Foundation of State Key Laboratory of Autonomous Underwater Vehicle, Harbin Engineering Universitythe Fundamental Research Funds for the Central Universities (HEUCFL20101113)
文摘In order to minimize the harm caused by the instability of a planing craft, a motion prediction model is essential. This paper analyzed the feasibility of using an MGM（1,N） model in grey system theory to predict planing craft motion and carried out the numerical simulation experiment. According to the characteristics of planing craft motion, a recurrence formula was proposed of the parameter matrix of an MGMfl,N） model. Using this formula, data can be updated in real-time without increasing computational complexity significantly. The results of numerical simulation show that using an MGM（1,N） model to predict planing motion is feasible and useful for prediction. So the method proposed in this study can reflect the planing craft motion mechanism successfully, and has rational and effective functions of forecasting and analyzing trends.
基金Supported by 863 Project of China (No.2006AA01Z224)
文摘In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and flexible model to predict overheads of these mechanisms. This model is based on overheads of basic operations frequently used in cryptography algorithms, which are essential elements of security mechanisms. Several popular cryptography algorithms and security mechanisms are evaluated using this model. According to simulation results, relative prediction errors are less than 7% for most cryptography algorithms and security mechanisms.
基金supported by the National Natural Science Foundation of China (Grant Nos. 50871109 and 51001096)
文摘The mesoscopic modeling developed rapidly in the past three decades is a promising tool for predicting and understanding the microstructure evolution at grain scale.In this paper,the recent development of mesoscopic modeling and its application to microstructure evolution in steels is reviewed.Firstly,some representative computational models are briefly introduced,e.g.,the phase field model,the cellular automaton model and the Monte Carlo model.Then,the emphasis is put on the application of mesoscopic modeling of the complex features of microstructure evolution,including solidification,solid-state phase transformation,recrystallization and grain growth.Finally,some issues in the present mesoscopic modeling and its perspective are discussed.
文摘Bispyribac is a widely used herbicide that targets the acetohydroxyacid synthase （AHAS） enzyme. Mutations in AHAS have caused serious herbicide resistance that threatened the continued use of the herbicide. So far, a unified model to decipher herb- icide resistance in molecular level with good prediction is still lacking. In this paper, we have established a new QSAR method to construct a prediction model for AHAS mutation resistance to herbicide Bispyribac. A series of AHAS mutants concerned with the herbicide resistance were constructed, and the inhibitory properties of Bispyribac against these mutants were meas- ured. The 3D-QSAR method has been transformed to process the AHAS mutants and proposed as mutation-dependent biom- acromolecular QSAR （MB-QSAR）. The excellent correlation between experimental and computational data gave the MB-QSAR/CoMFA model （q2 = 0.615, P = 0.921, F2pred = 0.598） and the MB-QSAR/CoMSIA model （q2 = 0.446, r2 = 0.929, r2pred = 0.612）, which showed good prediction for the inhibition properties of Bispyribac against AHAS mutants. Such MB-QSAR models, containing the three-dimensional molecular interaction diagram, not only disclose to us for the first time the detailed three-dimensional information about the structure-resistance relationships, but may also provide further guidance to resistance mutation evolution. Also, the molecular interaction diagram derived from MB-QSAR models may aid the resistance-evading herbicide design.
