Based on the monitoring and discovery service 4 （MDS4） model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of comput...Based on the monitoring and discovery service 4 （MDS4） model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of computing resources in the monitoring model are analyzed. Then, a time-series autoregressive prediction model is devised. And an autoregressive support vector regression（ ARSVR） monitoring method is put forward to predict the node load of the data grid. Finally, a model for historical observations sequences is set up using the autoregressive （AR） model and the model order is determined. The support vector regression（SVR） model is trained using historical data and the regression function is obtained. Simulation results show that the ARSVR method can effectively predict the node load.展开更多
MapReduce has emerged as a popular computing model used in datacenters to process large amount of datasets.In the map phase,hash partitioning is employed to distribute data that sharing the same key across data center...MapReduce has emerged as a popular computing model used in datacenters to process large amount of datasets.In the map phase,hash partitioning is employed to distribute data that sharing the same key across data center-scale cluster nodes.However,we observe that this approach can lead to uneven data distribution,which can result in skewed loads among reduce tasks,thus hamper performance of MapReduce systems.Moreover,worker nodes in MapReduce systems may differ in computing capability due to(1) multiple generations of hardware in non-virtualized data centers,or(2) co-location of virtual machines in virtualized data centers.The heterogeneity among cluster nodes exacerbates the negative effects of uneven data distribution.To improve MapReduce performance in heterogeneous clusters,we propose a novel load balancing approach in the reduce phase.This approach consists of two components:(1) performance prediction for reducers that run on heterogeneous nodes based on support vector machines models,and(2) heterogeneity-aware partitioning(HAP),which balances skewed data for reduce tasks.We implement this approach as a plug-in in current MapReduce system.Experimental results demonstrate that our proposed approach distributes work evenly among reduce tasks,and improves MapReduce performance with little overhead.展开更多
A new support vector machine （SVM） optimized by an improved particle swarm optimization （PSO） combined with simulated annealing algorithm （SA） was proposed. By incorporating with the simulated annealing method, ...A new support vector machine （SVM） optimized by an improved particle swarm optimization （PSO） combined with simulated annealing algorithm （SA） was proposed. By incorporating with the simulated annealing method, the global searching capacity of the particle swarm optimization（SAPSO） was enchanced, and the searching capacity of the particle swarm optimization was studied. Then, the improyed particle swarm optimization algorithm was used to optimize the parameters of SVM （c,σ and ε）. Based on the operational data provided by a regional power grid in north China, the method was used in the actual short term load forecasting. The results show that compared to the PSO-SVM and the traditional SVM, the average time of the proposed method in the experimental process reduces by 11.6 s and 31.1 s, and the precision of the proposed method increases by 1.24% and 3.18%, respectively. So, the improved method is better than the PSO-SVM and the traditional SVM.展开更多
Designers are required to plan for future expansion and also to estimate the grid's future utilization. This means that an effective modeling and forecasting technique, which will use efficiently the information c...Designers are required to plan for future expansion and also to estimate the grid's future utilization. This means that an effective modeling and forecasting technique, which will use efficiently the information contained in the available data, is required, so that important data properties can be extracted and projected into the future. This study proposes an adaptive method based on the multi-model partitioning algorithm (MMPA), for short-term electricity load forecasting using real data. The grid's utilization is initially modeled using a multiplicative seasonal ARIMA (autoregressive integrated moving average) model. The proposed method uses past data to learn and model the normal periodic behavior of the electric grid. Either ARMA (autoregressive moving average) or state-space models can be used for the load pattern modeling. Load anomalies such as unexpected peaks that may appear during the summer or unexpected faults (blackouts) are also modeled. If the load pattern does not match the normal be-havior of the load, an anomaly is detected and, furthermore, when the pattern matches a known case of anomaly, the type of anomaly is identified. Real data were used and real cases were tested based on the measurement loads of the Hellenic Public Power Cooperation S.A., Athens, Greece. The applied adaptive multi-model filtering algorithm identifies successfully both normal periodic behavior and any unusual activity of the electric grid. The performance of the proposed method is also compared to that produced by the ARIMA model.展开更多
An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learnin...An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Based on the operational data provided by a regional power grid in the south of China, the method was used in the actual short term load forecasting. The results show that the average time cost of the proposed method in the experiment process is reduced by 12.2 s, and the precision of the proposed method is increased by 3.43% compared to the traditional wavelet network. Consequently, the improved wavelet neural network forecasting model is better than the traditional wavelet neural network forecasting model in both forecasting effect and network function.展开更多
Achieving simultaneous reduction of NOx,CO and unburned hydrocarbon(UHC) emissions without compromising engine performance at part loads is the current focus of dual fuel engine research.The present work focuses on an...Achieving simultaneous reduction of NOx,CO and unburned hydrocarbon(UHC) emissions without compromising engine performance at part loads is the current focus of dual fuel engine research.The present work focuses on an experimental investigation conducted on a dual fuel(diesel-natural gas) engine to examine the simultaneous effect of inlet air pre-heating and exhaust gas recirculation(EGR) ratio on performance and emission characteristics at part loads.The use of EGR at high levels seems to be unable to improve the engine performance at part loads.However,it is shown that EGR combined with pre-heating of inlet air can slightly increase thermal efficiency,resulting in reduced levels of both unburned hydrocarbon and NOx emissions.CO and UHC emissions are reduced by 24% and 31%,respectively,The NOx emissions decrease by 21% because of the lower combustion temperature due to the much inert gas brought by EGR and decreased oxygen concentration in the cylinder.展开更多
Cellular-based Machine-Type Communication (MTC) will become more and more important in the near future for the advantage of the long-distance wireless communication.However,a large number of MTC applications introduce...Cellular-based Machine-Type Communication (MTC) will become more and more important in the near future for the advantage of the long-distance wireless communication.However,a large number of MTC applications introduce heavy load to cellular network.MTC traffic scheduling schemes are proposed to avoid congestion in this paper.Our approaches are based on the delay-tolerance of MTC traffic.Some MTC traffic is postponed until the network load becomes light.Moreover,our scheme efficiently utilizes the bandwidth resources reserved for handover in traditional cellular network.Simulation results show that the utility usage of radio resources is improved and the congestion probability is reduced.展开更多
The catalytic oxidation of toluene over Ag/SBA‐15synthesized under different pretreatment conditions,including O2at500°C(denoted O500),H2at500°C(H500),and O2at500°C followed by H2at300°C(O500‐H30...The catalytic oxidation of toluene over Ag/SBA‐15synthesized under different pretreatment conditions,including O2at500°C(denoted O500),H2at500°C(H500),and O2at500°C followed by H2at300°C(O500‐H300)was studied.The pretreated samples were investigated by N2physisorption,X‐ray diffraction,and ultraviolet‐visible diffuse reflectance.The pretreatment atmosphere greatly influences the status of the Ag and O species,which in turn significantly impacts the adsorption and catalytic removal of toluene.Ag2O and amorphous Ag particles,as well as a large amount of subsurface oxygen species,are formed on O500,and the subsurface oxygen enhances the interaction between Ag species and toluene,so O500shows good activity at higher temperature.However,its activity at lower temperature is not as high as expected,with a reduced presence of Ag2O and lower adsorption capacity for toluene.H2pretreatment at500°C is conducive to the formation of large Ag particles and yields the largest adsorption capacity for toluene,so H500exhibits the best activity at lower temperatures;however,because of poor interaction between Ag and toluene,its activity at higher temperature is modest.The O500‐H300sample exhibits excellent catalytic activity during the whole reaction process,which can be attributed to the small and highly dispersed Ag nanoparticles as well as the existence of subsurface oxygen.展开更多
Transformers are normally designed and built for use at rated frequency and sinusoidal load current. A non-linear load on a transformer leads to harmonic power losses which cause increased operational costs and additi...Transformers are normally designed and built for use at rated frequency and sinusoidal load current. A non-linear load on a transformer leads to harmonic power losses which cause increased operational costs and additional heating in transformer parts. It leads to higher losses, early fatigue of insulation, premature failure and reduction of the useful life of the transformer. To prevent these problems, the rated capacity of transformer which supplies harmonic loads must be reduced. In this work, a typical 50 kVA three-phase distribution transformer with real practical parameters is taken under non-linear loads generated due to domestic loads. The core losses is evaluated using the three dimensional model of the transformer developed in FEM （finite element method） program based on valid model of transformer under high harmonic conditions. And finally a relation associated with core losses and amplitude of high harmonic order are reviewed ＆ analyzed and then a comparison is being carried out on the results obtained by different excitation current in transformer windings.展开更多
The most conventional vehicle pretensioner system consists of an internal gear pair with involute teeth. However, it has been well known that the corresponding gear pairs are relatively weak under the situation of imp...The most conventional vehicle pretensioner system consists of an internal gear pair with involute teeth. However, it has been well known that the corresponding gear pairs are relatively weak under the situation of impact loadings. To improve this phenomenon, a new pretensioning gear system with cycloid teeth rather than the involute ones was proposed, and dual cycloidal gear mechanisms were designed for satisfying geometric constraints and dynamic loading conditions. The simulations of the prototypes were conducted by LS-DYNA program and the experiments for a prototype were performed for a dynamic model with impact loading devices. The results show that the better operation and the smoother motion are confirmed in the proposed cycloidal gear system rather than the conventional one without interferences between gear teeth under the impact of a crash.展开更多
The widely used cascade speed and torque controllers have a limited control performance in most high power applications due to the low switching frequency of power electronic converters and the convenience to avoid sp...The widely used cascade speed and torque controllers have a limited control performance in most high power applications due to the low switching frequency of power electronic converters and the convenience to avoid speed overshoots and oscillations for lifetime considerations. Model Predictive Direct Current Control （MPDCC） leads to an increase of torque control performance taking into account the discrete nature of inverters but temporary offsets and poor responses to load torque variations are still issues in speed control. A load torque estimator is proposed in this paper in order to further improve dynamic behavior. It compensates the load torque influence on the speed control setting a feed forward torque reference value. The benefits are twice; the speed controller reaches the speed reference value without offsets which would need to be compensated by an integrator and a better response to load torque variations is obtained since they are detected and compensated leading to small speed variations. Moreover, the influence of pararneter errors and disturbances has been analyzed and limited so that they play a minor role in operation.展开更多
In this paper a numerical investigation has been presented on the stall mechanism of a highly loaded Single Stage Low Speed Fan designed for the research test facility to be installed at North Western Polytechnic Univ...In this paper a numerical investigation has been presented on the stall mechanism of a highly loaded Single Stage Low Speed Fan designed for the research test facility to be installed at North Western Polytechnic University (NWPU) Xi’an, China. The results presented are for the design point, near stall and just stall operating conditions at design speed. Design point studies have been found to be an indicative of stall area. Unsteady method of domain scaling has been used to compute the results at near stall and just stall conditions. It has been found that unlike the conventional tip leakage flow of the rotor, stator hub section is mainly responsible for the stall of the fan. The flow mechanism has been discussed with correlation to the design variables and previous investigations. Commercial CFD code NUMECA FINE/Turbo has been used for computations; results have been compared with results obtained from commercial CFD code ANSYS-CFX. The loss prediction of latter code is conservative than the former. The stall mechanism predicted by both codes is analogous.展开更多
This paper investigates the transverse vibration of a simply supported nanobeam with an initial axial tension based on the nonlocal stress field theory with a nonlocal size parameter. Considering an axial elongation d...This paper investigates the transverse vibration of a simply supported nanobeam with an initial axial tension based on the nonlocal stress field theory with a nonlocal size parameter. Considering an axial elongation due to transverse vibration, the internal axial tension is not precisely equal to the external initial tension. A sixth-order nonlinear partial differential equation that governs the transverse vibration for such nonlocal nanobeam is derived. Using a perturbation method, the relation between natural frequency and nonlocal nanoscale parameter is derived and the transverse vibration mode is solved. The external axial tension and nonlocal nanoscale parameter are proven to play significant roles in the nonlinear vibration behavior of nonlocal nanobeams. Such effects enhance the natural frequency and stiffness as compared to the predictions of the classical continuum mechanics models. Additionally, the frequency is higher if the precise internal axial load is considered with respect to that when only the approximate internal axial tension is assumed.展开更多
基金The National High Technology Research and Development Program of China (863 Program) (No2007AA01Z404)
文摘Based on the monitoring and discovery service 4 （MDS4） model, a monitoring model for a data grid which supports reliable storage and intrusion tolerance is designed. The load characteristics and indicators of computing resources in the monitoring model are analyzed. Then, a time-series autoregressive prediction model is devised. And an autoregressive support vector regression（ ARSVR） monitoring method is put forward to predict the node load of the data grid. Finally, a model for historical observations sequences is set up using the autoregressive （AR） model and the model order is determined. The support vector regression（SVR） model is trained using historical data and the regression function is obtained. Simulation results show that the ARSVR method can effectively predict the node load.
基金The authors would like to thank the reviewers for their detailed reviews and constructive comments, which have helped improve the quality of this paper. This work is support- ed by National High-Tech Research and Development Plan of China under grants NO.2011AA01A204, and 2012AA01A306, National Natural Science Foundation of China under grant NO. 61202041, and NO.91330117.
文摘MapReduce has emerged as a popular computing model used in datacenters to process large amount of datasets.In the map phase,hash partitioning is employed to distribute data that sharing the same key across data center-scale cluster nodes.However,we observe that this approach can lead to uneven data distribution,which can result in skewed loads among reduce tasks,thus hamper performance of MapReduce systems.Moreover,worker nodes in MapReduce systems may differ in computing capability due to(1) multiple generations of hardware in non-virtualized data centers,or(2) co-location of virtual machines in virtualized data centers.The heterogeneity among cluster nodes exacerbates the negative effects of uneven data distribution.To improve MapReduce performance in heterogeneous clusters,we propose a novel load balancing approach in the reduce phase.This approach consists of two components:(1) performance prediction for reducers that run on heterogeneous nodes based on support vector machines models,and(2) heterogeneity-aware partitioning(HAP),which balances skewed data for reduce tasks.We implement this approach as a plug-in in current MapReduce system.Experimental results demonstrate that our proposed approach distributes work evenly among reduce tasks,and improves MapReduce performance with little overhead.
基金Project(50579101) supported by the National Natural Science Foundation of China
文摘A new support vector machine （SVM） optimized by an improved particle swarm optimization （PSO） combined with simulated annealing algorithm （SA） was proposed. By incorporating with the simulated annealing method, the global searching capacity of the particle swarm optimization（SAPSO） was enchanced, and the searching capacity of the particle swarm optimization was studied. Then, the improyed particle swarm optimization algorithm was used to optimize the parameters of SVM （c,σ and ε）. Based on the operational data provided by a regional power grid in north China, the method was used in the actual short term load forecasting. The results show that compared to the PSO-SVM and the traditional SVM, the average time of the proposed method in the experimental process reduces by 11.6 s and 31.1 s, and the precision of the proposed method increases by 1.24% and 3.18%, respectively. So, the improved method is better than the PSO-SVM and the traditional SVM.
文摘Designers are required to plan for future expansion and also to estimate the grid's future utilization. This means that an effective modeling and forecasting technique, which will use efficiently the information contained in the available data, is required, so that important data properties can be extracted and projected into the future. This study proposes an adaptive method based on the multi-model partitioning algorithm (MMPA), for short-term electricity load forecasting using real data. The grid's utilization is initially modeled using a multiplicative seasonal ARIMA (autoregressive integrated moving average) model. The proposed method uses past data to learn and model the normal periodic behavior of the electric grid. Either ARMA (autoregressive moving average) or state-space models can be used for the load pattern modeling. Load anomalies such as unexpected peaks that may appear during the summer or unexpected faults (blackouts) are also modeled. If the load pattern does not match the normal be-havior of the load, an anomaly is detected and, furthermore, when the pattern matches a known case of anomaly, the type of anomaly is identified. Real data were used and real cases were tested based on the measurement loads of the Hellenic Public Power Cooperation S.A., Athens, Greece. The applied adaptive multi-model filtering algorithm identifies successfully both normal periodic behavior and any unusual activity of the electric grid. The performance of the proposed method is also compared to that produced by the ARIMA model.
基金Project(50579101) supported by the National Natural Science Foundation of China
文摘An improved wavelet neural network algorithm which combines with particle swarm optimization was proposed to avoid encountering the curse of dimensionality and overcome the shortage in the responding speed and learning ability brought about by the traditional models. Based on the operational data provided by a regional power grid in the south of China, the method was used in the actual short term load forecasting. The results show that the average time cost of the proposed method in the experiment process is reduced by 12.2 s, and the precision of the proposed method is increased by 3.43% compared to the traditional wavelet network. Consequently, the improved wavelet neural network forecasting model is better than the traditional wavelet neural network forecasting model in both forecasting effect and network function.
文摘Achieving simultaneous reduction of NOx,CO and unburned hydrocarbon(UHC) emissions without compromising engine performance at part loads is the current focus of dual fuel engine research.The present work focuses on an experimental investigation conducted on a dual fuel(diesel-natural gas) engine to examine the simultaneous effect of inlet air pre-heating and exhaust gas recirculation(EGR) ratio on performance and emission characteristics at part loads.The use of EGR at high levels seems to be unable to improve the engine performance at part loads.However,it is shown that EGR combined with pre-heating of inlet air can slightly increase thermal efficiency,resulting in reduced levels of both unburned hydrocarbon and NOx emissions.CO and UHC emissions are reduced by 24% and 31%,respectively,The NOx emissions decrease by 21% because of the lower combustion temperature due to the much inert gas brought by EGR and decreased oxygen concentration in the cylinder.
基金supported by the National Science Foundation(60972047,60972048,60832001)National S&T Major Project(2011ZX03005-003-03,2008ZX03005-001,2010ZX03005-003)+4 种基金National Science Fund for Distinguished Young Scholars(60725105)National Basic Research Program of China(No.2009CB320404)Program for Changjiang Scholars and Innovative Research Team in University(IRT0852)the 111 Project(B08038)State Key Laboratory Foundation(ISN090305,ISN1002005)
文摘Cellular-based Machine-Type Communication (MTC) will become more and more important in the near future for the advantage of the long-distance wireless communication.However,a large number of MTC applications introduce heavy load to cellular network.MTC traffic scheduling schemes are proposed to avoid congestion in this paper.Our approaches are based on the delay-tolerance of MTC traffic.Some MTC traffic is postponed until the network load becomes light.Moreover,our scheme efficiently utilizes the bandwidth resources reserved for handover in traditional cellular network.Simulation results show that the utility usage of radio resources is improved and the congestion probability is reduced.
基金supported by the National Natural Science Foundation of China(21377016,21577014)Program for Changjiang Scholars and Innovative Research Team in University(IRT_13R05)~~
文摘The catalytic oxidation of toluene over Ag/SBA‐15synthesized under different pretreatment conditions,including O2at500°C(denoted O500),H2at500°C(H500),and O2at500°C followed by H2at300°C(O500‐H300)was studied.The pretreated samples were investigated by N2physisorption,X‐ray diffraction,and ultraviolet‐visible diffuse reflectance.The pretreatment atmosphere greatly influences the status of the Ag and O species,which in turn significantly impacts the adsorption and catalytic removal of toluene.Ag2O and amorphous Ag particles,as well as a large amount of subsurface oxygen species,are formed on O500,and the subsurface oxygen enhances the interaction between Ag species and toluene,so O500shows good activity at higher temperature.However,its activity at lower temperature is not as high as expected,with a reduced presence of Ag2O and lower adsorption capacity for toluene.H2pretreatment at500°C is conducive to the formation of large Ag particles and yields the largest adsorption capacity for toluene,so H500exhibits the best activity at lower temperatures;however,because of poor interaction between Ag and toluene,its activity at higher temperature is modest.The O500‐H300sample exhibits excellent catalytic activity during the whole reaction process,which can be attributed to the small and highly dispersed Ag nanoparticles as well as the existence of subsurface oxygen.
文摘Transformers are normally designed and built for use at rated frequency and sinusoidal load current. A non-linear load on a transformer leads to harmonic power losses which cause increased operational costs and additional heating in transformer parts. It leads to higher losses, early fatigue of insulation, premature failure and reduction of the useful life of the transformer. To prevent these problems, the rated capacity of transformer which supplies harmonic loads must be reduced. In this work, a typical 50 kVA three-phase distribution transformer with real practical parameters is taken under non-linear loads generated due to domestic loads. The core losses is evaluated using the three dimensional model of the transformer developed in FEM （finite element method） program based on valid model of transformer under high harmonic conditions. And finally a relation associated with core losses and amplitude of high harmonic order are reviewed ＆ analyzed and then a comparison is being carried out on the results obtained by different excitation current in transformer windings.
基金supported by the Changwon National University in 2011-2012,Korea
文摘The most conventional vehicle pretensioner system consists of an internal gear pair with involute teeth. However, it has been well known that the corresponding gear pairs are relatively weak under the situation of impact loadings. To improve this phenomenon, a new pretensioning gear system with cycloid teeth rather than the involute ones was proposed, and dual cycloidal gear mechanisms were designed for satisfying geometric constraints and dynamic loading conditions. The simulations of the prototypes were conducted by LS-DYNA program and the experiments for a prototype were performed for a dynamic model with impact loading devices. The results show that the better operation and the smoother motion are confirmed in the proposed cycloidal gear system rather than the conventional one without interferences between gear teeth under the impact of a crash.
文摘The widely used cascade speed and torque controllers have a limited control performance in most high power applications due to the low switching frequency of power electronic converters and the convenience to avoid speed overshoots and oscillations for lifetime considerations. Model Predictive Direct Current Control （MPDCC） leads to an increase of torque control performance taking into account the discrete nature of inverters but temporary offsets and poor responses to load torque variations are still issues in speed control. A load torque estimator is proposed in this paper in order to further improve dynamic behavior. It compensates the load torque influence on the speed control setting a feed forward torque reference value. The benefits are twice; the speed controller reaches the speed reference value without offsets which would need to be compensated by an integrator and a better response to load torque variations is obtained since they are detected and compensated leading to small speed variations. Moreover, the influence of pararneter errors and disturbances has been analyzed and limited so that they play a minor role in operation.
文摘In this paper a numerical investigation has been presented on the stall mechanism of a highly loaded Single Stage Low Speed Fan designed for the research test facility to be installed at North Western Polytechnic University (NWPU) Xi’an, China. The results presented are for the design point, near stall and just stall operating conditions at design speed. Design point studies have been found to be an indicative of stall area. Unsteady method of domain scaling has been used to compute the results at near stall and just stall conditions. It has been found that unlike the conventional tip leakage flow of the rotor, stator hub section is mainly responsible for the stall of the fan. The flow mechanism has been discussed with correlation to the design variables and previous investigations. Commercial CFD code NUMECA FINE/Turbo has been used for computations; results have been compared with results obtained from commercial CFD code ANSYS-CFX. The loss prediction of latter code is conservative than the former. The stall mechanism predicted by both codes is analogous.
基金supported by a collaboration scheme from University of Science and Technology of China-City University of Hong Kong Joint Advanced Research Institute and by City University of Hong Kong of China (Grant No. 7002699 (BC))
文摘This paper investigates the transverse vibration of a simply supported nanobeam with an initial axial tension based on the nonlocal stress field theory with a nonlocal size parameter. Considering an axial elongation due to transverse vibration, the internal axial tension is not precisely equal to the external initial tension. A sixth-order nonlinear partial differential equation that governs the transverse vibration for such nonlocal nanobeam is derived. Using a perturbation method, the relation between natural frequency and nonlocal nanoscale parameter is derived and the transverse vibration mode is solved. The external axial tension and nonlocal nanoscale parameter are proven to play significant roles in the nonlinear vibration behavior of nonlocal nanobeams. Such effects enhance the natural frequency and stiffness as compared to the predictions of the classical continuum mechanics models. Additionally, the frequency is higher if the precise internal axial load is considered with respect to that when only the approximate internal axial tension is assumed.
