A unified constitutive modeling approach is highly desirable to characterize a wide range of engineeringmaterials subjected simultaneously to the effect of a number of factors such as elastic, plastic and creepdeforma...A unified constitutive modeling approach is highly desirable to characterize a wide range of engineeringmaterials subjected simultaneously to the effect of a number of factors such as elastic, plastic and creepdeformations, stress path, volume change, microcracking leading to fracture, failure and softening,stiffening, and mechanical and environmental forces. There are hardly available such unified models. Thedisturbed state concept （DSC） is considered to be a unified approach and is able to provide materialcharacterization for almost all of the above factors. This paper presents a description of the DSC, andstatements for determination of parameters based on triaxial, multiaxial and interface tests. Statementsof DSC and validation at the specimen level and at the boundary value problem levels are also presented.An extensive list of publications by the author and others is provided at the end. The DSC is considered tobe a unique and versatile procedure for modeling behaviors of engineering materials and interfaces. 2016 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. This is an open access article under the CC BY-NC-ND license展开更多
A new generic reaction in the form of PC_i→PC_m+[i,m]→PC_m+λi,m coke+surplusage has been proposed for describing the catalytic cracking behavior of petroleum narrow cuts or pseudo-components(PCs),where the rate con...A new generic reaction in the form of PC_i→PC_m+[i,m]→PC_m+λi,m coke+surplusage has been proposed for describing the catalytic cracking behavior of petroleum narrow cuts or pseudo-components(PCs),where the rate constant formula is derived from the transition state theory and the coking amount is correlated to the properties of the intermediate substance [i,m].In composing the cracking reaction network for feedstock and product oils,only the product PC m of the proposed generic reaction is used,which together with a criterion for excluding exothermic reactions,distinctly reduces the number of reactions in the network.With the proposed cracking reaction scheme coupled with special pseudo-components,a predictive one-dimensional steady state model for fluid catalytic cracking risers is formulated in the sense that for a given riser and given catalyst,the model parameters are independent of stock oils,product schemes and other operational conditions.The great correlating and predicting capability of the resulted model is tested with production data in different scenarios of four commercial risers.展开更多
It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to har...It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter "pseudo" transfer functions.The models are identified using supervisory control and data acquisition(SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.展开更多
文摘A unified constitutive modeling approach is highly desirable to characterize a wide range of engineeringmaterials subjected simultaneously to the effect of a number of factors such as elastic, plastic and creepdeformations, stress path, volume change, microcracking leading to fracture, failure and softening,stiffening, and mechanical and environmental forces. There are hardly available such unified models. Thedisturbed state concept （DSC） is considered to be a unified approach and is able to provide materialcharacterization for almost all of the above factors. This paper presents a description of the DSC, andstatements for determination of parameters based on triaxial, multiaxial and interface tests. Statementsof DSC and validation at the specimen level and at the boundary value problem levels are also presented.An extensive list of publications by the author and others is provided at the end. The DSC is considered tobe a unique and versatile procedure for modeling behaviors of engineering materials and interfaces. 2016 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting byElsevier B.V. This is an open access article under the CC BY-NC-ND license
基金Supported by the National Natural Science Foundation of China(21676012)the Fundamental Research Funds for the Central Universities(Project YS1404)the National High Technology Research and Development Program of China(2007AA04Z191)
文摘A new generic reaction in the form of PC_i→PC_m+[i,m]→PC_m+λi,m coke+surplusage has been proposed for describing the catalytic cracking behavior of petroleum narrow cuts or pseudo-components(PCs),where the rate constant formula is derived from the transition state theory and the coking amount is correlated to the properties of the intermediate substance [i,m].In composing the cracking reaction network for feedstock and product oils,only the product PC m of the proposed generic reaction is used,which together with a criterion for excluding exothermic reactions,distinctly reduces the number of reactions in the network.With the proposed cracking reaction scheme coupled with special pseudo-components,a predictive one-dimensional steady state model for fluid catalytic cracking risers is formulated in the sense that for a given riser and given catalyst,the model parameters are independent of stock oils,product schemes and other operational conditions.The great correlating and predicting capability of the resulted model is tested with production data in different scenarios of four commercial risers.
基金supported by the UK Engineering and Physical Sciences Research Council(EPSRC)(No.EP/I037326/1)
文摘It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter "pseudo" transfer functions.The models are identified using supervisory control and data acquisition(SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.
