Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, ...Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, if a distributed parameter system is described by ordinary differential equations （ODE） during the analysis and the design of distributed parameter system, the reliability of the system description will be reduced, and the systemic errors will be introduced. Studies on working condition real-time monitoring can improve the security because the rechargeable LIBs are widely used in many electronic systems and electromechanical equipment. Single particle model （SPM） is the simplification of LIB under some approximations, and can estimate the working parameters of a LIB at the faster simulation speed. A LIB modelling algorithm based on PDEs and SPM is proposed to monitor the working condition of LIBs in real time. Although the lithium ion concentration is an unmeasurable distributed parameter in the anode of LIB, the working condition monitoring model can track the real time lithium ion concentration in the anode of LIB, and calculate the residual which is the difference between the ideal data and the measured data. A fault alarm can be triggered when the residual is beyond the preset threshold. A simulation example verifies that the effectiveness and the accuracy of the working condition real-time monitoring model of LIB based on PDEs and SPM.展开更多
observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting(WRF)model simulations using four microphysics schemes(Morrison,WSM6,P3,SBM)with different complexities.The ma...observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting(WRF)model simulations using four microphysics schemes(Morrison,WSM6,P3,SBM)with different complexities.The main purpose of this paper is to assess the performance of the microphysics ensemble in terms of cloud microphysical properties.Results show that although the vertical distributions of liquid water content(LWC)and ice water content(IWC)simulated by the four members are quite different in the convective cloud region,they are relatively uniform in the stratiform cloud region.Overall,the results of the Morrison scheme are very similar to the ensemble average,and both of them are closer to the observations compared to the other schemes.Besides,the authors also note that all members still overpredict the LWC by a factor of 2–8 in some regions,resulting in large deviation between the observation and ensemble average.展开更多
The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science.However,given the uncertainties in the initial and boundary conditions a...The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science.However,given the uncertainties in the initial and boundary conditions and imperfections of microphysical schemes,the accurate prediction of these microphysical properties of cloud is still a big challenge.The ensemble approach may be a viable way to reduce forecast uncertainties.In this paper,a large-scale stratiform cloud precipitation process is studied by comparing results of a 10-member ensemble forecast model with aircraft observation data.By means of the ensemble average,the prediction of bulk parameters such as liquid water content and ice water content can be improved in comparison with the control member,but the particle number concentrations are still one to two orders of magnitude less than those from observations.Intercomparison of raindrop size spectra reveals a big distinction between observations and predictions for particles with a diameter less than 1000μm.展开更多
The number concentrations in the radius range of 0.06 – 5 μm of aerosol particles and meteorological parameters were measured on board during a cruise in the South China Sea from August 25 to October 12, 2012. Effec...The number concentrations in the radius range of 0.06 – 5 μm of aerosol particles and meteorological parameters were measured on board during a cruise in the South China Sea from August 25 to October 12, 2012. Effective fluxes in the reference height of 10 m were estimated by steady state dry deposition method based on the observed data, and the influences of different air masses on flux were discussed in this paper. The number size distribution was characterized by a bimodal mode, with the average total number concentration of（1.50 ± 0.76）×10~3 cm^（-3）. The two mode radii were 0.099 μm and 0.886 μm, both of which were within the scope of accumulation mode. A typical daily average size distribution was compared with that measured in the Bay of Bengal. In the whole radius range, the number concentrations were in agreement with each other; the modes were more distinct in this study than that abtained in the Bay of Bengal. The size distribution of the fluxes was fitted with the sum of log-normal and power-law distribution. The impact of different air masses was mainly on flux magnitude, rather than the shape of spectral distribution. A semiempirical source function that is applicable in the radius range of 0.06 μm展开更多
Nano fluid is considered to be a class of high efficient heat transfer fluid created by dispersing some special solid nanoparticles (normally less than 100 nm) in traditional heat transfer fluid. The present experimen...Nano fluid is considered to be a class of high efficient heat transfer fluid created by dispersing some special solid nanoparticles (normally less than 100 nm) in traditional heat transfer fluid. The present experiment was conducted aiming at investigating the forced heat transfer characteristics of aqueous copper (Cu) nanofluid at varying concentration of Cu nano-particles in different flow regimes (300<Re≤16 000). The forced convective heat transfer enhancement is available both in the laminar and turbulent flow with increasing the concentration. Especially, the enhancement rate increases dramatically in laminar flow regime, for instance, the heat transfer coefficient of Cu/water nanofluid increases by two times at around Re=2 000 compared with that of base fluid water, and averagely increases by 62% at 1% volume fraction. However, the heat transfer coefficient of Cu/water decreases sharply in the transition flow regime. Furthermore, it has the trend that the heat transfer coefficient displays worse with increasing the concentration.展开更多
During the last decade, many variants of the original particle swarm optimization （PSO） algorithm have been proposed for global numerical optimization, hut they usually face many challenges such as low solution qual...During the last decade, many variants of the original particle swarm optimization （PSO） algorithm have been proposed for global numerical optimization, hut they usually face many challenges such as low solution quality and slow convergence speed on multimodal function optimization. A composite particle swarm optimization （CPSO） for solving these difficulties is presented, in which a novel learning strategy plus an assisted search mechanism framework is used. Instead of simple learning strategy of the original PSO, the proposed CPSO combines one particle＇s historical best information and the global best information into one learning exemplar to guide the particle movement. The proposed learning strategy can reserve the original search information and lead to faster convergence speed. The proposed assisted search mechanism is designed to look for the global optimum. Search direction of particles can be greatly changed by this mechanism so that the algorithm has a large chance to escape from local optima. In order to make the assisted search mechanism more efficient and the algorithm more reliable, the executive probability of the assisted search mechanism is adjusted by the feedback of the improvement degree of optimal value after each iteration. According to the result of numerical experiments on multimodal benchmark functions such as Schwefel, Rastrigin, Ackley and Griewank both with and without coordinate rotation, the proposed CPSO offers faster convergence speed, higher quality solution and stronger robustness than other variants of PSO.展开更多
We investigate a coupled quintessence scenario, which can provide a natural solution to the cosmic coincidence problem. We assume that the mass of dark matter particles depends on a power law function of the scalar fi...We investigate a coupled quintessence scenario, which can provide a natural solution to the cosmic coincidence problem. We assume that the mass of dark matter particles depends on a power law function of the scalar field associated to dark energy and meanwhile the scalar field evolves in a power law potential. Since the dynamics of this system is dominated by an attractor solution, the mass of dark matter particles is forced to change with time as to ensure that the ratio between the energy densities of dark matter and dark energy becomes a constant at late times,and one thus solves the cosmic coincidence problem naturally. We then apply a statefinder diagnostic to this coupled quintessence scenario. It is shown that the evolving trajectory of this scenario in the s-r diagram is quite different from those of other dark energy models.展开更多
文摘Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, if a distributed parameter system is described by ordinary differential equations （ODE） during the analysis and the design of distributed parameter system, the reliability of the system description will be reduced, and the systemic errors will be introduced. Studies on working condition real-time monitoring can improve the security because the rechargeable LIBs are widely used in many electronic systems and electromechanical equipment. Single particle model （SPM） is the simplification of LIB under some approximations, and can estimate the working parameters of a LIB at the faster simulation speed. A LIB modelling algorithm based on PDEs and SPM is proposed to monitor the working condition of LIBs in real time. Although the lithium ion concentration is an unmeasurable distributed parameter in the anode of LIB, the working condition monitoring model can track the real time lithium ion concentration in the anode of LIB, and calculate the residual which is the difference between the ideal data and the measured data. A fault alarm can be triggered when the residual is beyond the preset threshold. A simulation example verifies that the effectiveness and the accuracy of the working condition real-time monitoring model of LIB based on PDEs and SPM.
基金supported by the National Key R&D Program of Chinagrant number 2018YFC1507900the Demonstration Project of Artificial Precipitation Enhancement and Hail Suppression Operation Technology at the Eastern Side of the Taihang Mountains grant number hbrywcsy-2017-2sponsored by the National Natural Science Foundation of China grant numbers 41530427 and 41875172。
文摘observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting(WRF)model simulations using four microphysics schemes(Morrison,WSM6,P3,SBM)with different complexities.The main purpose of this paper is to assess the performance of the microphysics ensemble in terms of cloud microphysical properties.Results show that although the vertical distributions of liquid water content(LWC)and ice water content(IWC)simulated by the four members are quite different in the convective cloud region,they are relatively uniform in the stratiform cloud region.Overall,the results of the Morrison scheme are very similar to the ensemble average,and both of them are closer to the observations compared to the other schemes.Besides,the authors also note that all members still overpredict the LWC by a factor of 2–8 in some regions,resulting in large deviation between the observation and ensemble average.
基金supported by the National Key R&D Program of China grant number 2018YFC1507900the Demonstration Project of Artificial Precipitation Enhancement and Hail Suppression Operation Technology at the Eastern Side of the Taihang Mountains grant number hbrywcsy-2017-2sponsored by the National Natural Science Foundation of China grant numbers 41530427 and 41875172。
文摘The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science.However,given the uncertainties in the initial and boundary conditions and imperfections of microphysical schemes,the accurate prediction of these microphysical properties of cloud is still a big challenge.The ensemble approach may be a viable way to reduce forecast uncertainties.In this paper,a large-scale stratiform cloud precipitation process is studied by comparing results of a 10-member ensemble forecast model with aircraft observation data.By means of the ensemble average,the prediction of bulk parameters such as liquid water content and ice water content can be improved in comparison with the control member,but the particle number concentrations are still one to two orders of magnitude less than those from observations.Intercomparison of raindrop size spectra reveals a big distinction between observations and predictions for particles with a diameter less than 1000μm.
基金supported by the National Natural Science Foundation of China under Grant NO.41276009
文摘The number concentrations in the radius range of 0.06 – 5 μm of aerosol particles and meteorological parameters were measured on board during a cruise in the South China Sea from August 25 to October 12, 2012. Effective fluxes in the reference height of 10 m were estimated by steady state dry deposition method based on the observed data, and the influences of different air masses on flux were discussed in this paper. The number size distribution was characterized by a bimodal mode, with the average total number concentration of（1.50 ± 0.76）×10~3 cm^（-3）. The two mode radii were 0.099 μm and 0.886 μm, both of which were within the scope of accumulation mode. A typical daily average size distribution was compared with that measured in the Bay of Bengal. In the whole radius range, the number concentrations were in agreement with each other; the modes were more distinct in this study than that abtained in the Bay of Bengal. The size distribution of the fluxes was fitted with the sum of log-normal and power-law distribution. The impact of different air masses was mainly on flux magnitude, rather than the shape of spectral distribution. A semiempirical source function that is applicable in the radius range of 0.06 μm
基金supported by Basic Science Research Program through the National Research Foundation of Korea (NRF)funded by the Ministry of Education, Science and Technology (No.2012-0004544)
文摘Nano fluid is considered to be a class of high efficient heat transfer fluid created by dispersing some special solid nanoparticles (normally less than 100 nm) in traditional heat transfer fluid. The present experiment was conducted aiming at investigating the forced heat transfer characteristics of aqueous copper (Cu) nanofluid at varying concentration of Cu nano-particles in different flow regimes (300<Re≤16 000). The forced convective heat transfer enhancement is available both in the laminar and turbulent flow with increasing the concentration. Especially, the enhancement rate increases dramatically in laminar flow regime, for instance, the heat transfer coefficient of Cu/water nanofluid increases by two times at around Re=2 000 compared with that of base fluid water, and averagely increases by 62% at 1% volume fraction. However, the heat transfer coefficient of Cu/water decreases sharply in the transition flow regime. Furthermore, it has the trend that the heat transfer coefficient displays worse with increasing the concentration.
基金Projects(50275150,61173052)supported by the National Natural Science Foundation of China
文摘During the last decade, many variants of the original particle swarm optimization （PSO） algorithm have been proposed for global numerical optimization, hut they usually face many challenges such as low solution quality and slow convergence speed on multimodal function optimization. A composite particle swarm optimization （CPSO） for solving these difficulties is presented, in which a novel learning strategy plus an assisted search mechanism framework is used. Instead of simple learning strategy of the original PSO, the proposed CPSO combines one particle＇s historical best information and the global best information into one learning exemplar to guide the particle movement. The proposed learning strategy can reserve the original search information and lead to faster convergence speed. The proposed assisted search mechanism is designed to look for the global optimum. Search direction of particles can be greatly changed by this mechanism so that the algorithm has a large chance to escape from local optima. In order to make the assisted search mechanism more efficient and the algorithm more reliable, the executive probability of the assisted search mechanism is adjusted by the feedback of the improvement degree of optimal value after each iteration. According to the result of numerical experiments on multimodal benchmark functions such as Schwefel, Rastrigin, Ackley and Griewank both with and without coordinate rotation, the proposed CPSO offers faster convergence speed, higher quality solution and stronger robustness than other variants of PSO.
文摘We investigate a coupled quintessence scenario, which can provide a natural solution to the cosmic coincidence problem. We assume that the mass of dark matter particles depends on a power law function of the scalar field associated to dark energy and meanwhile the scalar field evolves in a power law potential. Since the dynamics of this system is dominated by an attractor solution, the mass of dark matter particles is forced to change with time as to ensure that the ratio between the energy densities of dark matter and dark energy becomes a constant at late times,and one thus solves the cosmic coincidence problem naturally. We then apply a statefinder diagnostic to this coupled quintessence scenario. It is shown that the evolving trajectory of this scenario in the s-r diagram is quite different from those of other dark energy models.
