Optical imaging methods have been widely applied in combustion diagnostics due to their high sensitivity, versatility, non-intrusiveness, and amenability for implementation in harsh environment [1,2]. Compared with tr...Optical imaging methods have been widely applied in combustion diagnostics due to their high sensitivity, versatility, non-intrusiveness, and amenability for implementation in harsh environment [1,2]. Compared with traditional intrusive diagnostics, such as thermometry with thermocouples and manometry with pressure transducers, planar imaging methods provide richer insights into fluid dynamics and complex combustion phenomena.展开更多
The fluid flow around a bio-inspired airfoil with corrugated surfaces and its smooth counterpart at chord Reynolds number Re = 2.0×10^3. and different Angle-Of-Attack (AOA = 0°, 4°, 8° and 12...The fluid flow around a bio-inspired airfoil with corrugated surfaces and its smooth counterpart at chord Reynolds number Re = 2.0×10^3. and different Angle-Of-Attack (AOA = 0°, 4°, 8° and 12°) were measured by using Particle Image Velocimetry (PIV). The global characteristics of the fluid flow around two airfoils were analyzed by ensemble-averaged velocity field, distribution of reverse flow intermittency, and time-series flow visualizations. At AOA = 0°, no significant variation of the global flow patterns was recognized for both configurations. The statistical results of reverse flow intermittency results demonstrated that the protruding peaks of the corrugated airfoil delay flow separation occur at AOA = 4°. At large AOAs (8° and 12°), however, the flow is massively separated in both configurations, the combination of large separation bubble above the corrugated airfoil and small recirculation zones in the upstream upper valley results in earlier separation of the flow. At AOA=8°, the wake region behind the corrugated airfoil is considerably shortened in comparison to the smooth one, indicating a remarkable reduction of the time-mean lift and drag forces, however, at AOA - 12°, the wake region behind the corrugated one is slightly larger than that behind the smooth one. For the case of AOA = 8° and 12°, the time-series flow visualizations demonstrate the intensified vortex shedding process of the corrugated airfoil, which would give rise to enhanced dynamic loading. Due to the fact that dragonfly wing is practically flexible, it is speculated that the wing structure of a gliding dragonfly might be sophisticatedly deformed in response to the periodic loading to reduce the drag.展开更多
The monitoring of Li-ion battery temperatures is essential to ensure high efficiency and safety.In this work,two types of recurrent neural networks (RNNs),which are long short-term memory-RNN (LSTM-RNN) and gated recu...The monitoring of Li-ion battery temperatures is essential to ensure high efficiency and safety.In this work,two types of recurrent neural networks (RNNs),which are long short-term memory-RNN (LSTM-RNN) and gated recurrent unit-RNN(GRU-RNN),are proposed to estimate the surface temperature of 18650 Li-ion batteries during the discharging processes under different ambient temperatures.The datasets acquired from the Prognostics Center of Excellence (PCo E) of NASA are used to train,validate and test the networks.In previous work,temperature has been set as the output of the networks;however,here the temperature difference along the time axis is adopted as the output.The net heat generated results in net temperature change,which is more closely aligned with electrochemical and thermodynamic laws.Extensive simulation results show that the two RNNs can achieve accurate real-time battery temperature estimation.The maximum absolute error in temperature estimation is approximately 0.75°C and the correlation coefficient between the estimated and measured temperature curves is greater than 0.95.The influences of three crucial parameters,which are the number of hidden neurons,initial learning rate and maximum number of iterations,are also assessed in terms of training time,root mean square error and mean absolute error.展开更多
Optical combustion diagnostics are indispensable tools to investigate flame dynamics and excavate in-situ quantities of flames,such as velocity,temperature,concentration of key intermediates and pressure without intro...Optical combustion diagnostics are indispensable tools to investigate flame dynamics and excavate in-situ quantities of flames,such as velocity,temperature,concentration of key intermediates and pressure without introducing probe perturbation.For example,velocity and flame temperature can be obtained using techniques such as particle image velocimetry,coherent anti-Stokes Raman scattering spectroscopy,Rayleigh scattering and tunable diode laser absorption spectroscopy,respectively.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 51706141 and 51976122)Foundation of Science and Technology on Combustion and Explosion Laboratory (Grant No.6142603200508)National Science and Technology Major Project(Grant No. 2017-Ⅲ-0007-0033)。
文摘Optical imaging methods have been widely applied in combustion diagnostics due to their high sensitivity, versatility, non-intrusiveness, and amenability for implementation in harsh environment [1,2]. Compared with traditional intrusive diagnostics, such as thermometry with thermocouples and manometry with pressure transducers, planar imaging methods provide richer insights into fluid dynamics and complex combustion phenomena.
基金supported by the National Natural Science Foundation of China(Grant Nos.51106096,51176108)
文摘The fluid flow around a bio-inspired airfoil with corrugated surfaces and its smooth counterpart at chord Reynolds number Re = 2.0×10^3. and different Angle-Of-Attack (AOA = 0°, 4°, 8° and 12°) were measured by using Particle Image Velocimetry (PIV). The global characteristics of the fluid flow around two airfoils were analyzed by ensemble-averaged velocity field, distribution of reverse flow intermittency, and time-series flow visualizations. At AOA = 0°, no significant variation of the global flow patterns was recognized for both configurations. The statistical results of reverse flow intermittency results demonstrated that the protruding peaks of the corrugated airfoil delay flow separation occur at AOA = 4°. At large AOAs (8° and 12°), however, the flow is massively separated in both configurations, the combination of large separation bubble above the corrugated airfoil and small recirculation zones in the upstream upper valley results in earlier separation of the flow. At AOA=8°, the wake region behind the corrugated airfoil is considerably shortened in comparison to the smooth one, indicating a remarkable reduction of the time-mean lift and drag forces, however, at AOA - 12°, the wake region behind the corrugated one is slightly larger than that behind the smooth one. For the case of AOA = 8° and 12°, the time-series flow visualizations demonstrate the intensified vortex shedding process of the corrugated airfoil, which would give rise to enhanced dynamic loading. Due to the fact that dragonfly wing is practically flexible, it is speculated that the wing structure of a gliding dragonfly might be sophisticatedly deformed in response to the periodic loading to reduce the drag.
基金the National Natural Science Foundation of China(Grant Nos.52061135108 and 51976122)the National Science and Technology Major Project(Grant No.2017-III-0007-0033)。
文摘The monitoring of Li-ion battery temperatures is essential to ensure high efficiency and safety.In this work,two types of recurrent neural networks (RNNs),which are long short-term memory-RNN (LSTM-RNN) and gated recurrent unit-RNN(GRU-RNN),are proposed to estimate the surface temperature of 18650 Li-ion batteries during the discharging processes under different ambient temperatures.The datasets acquired from the Prognostics Center of Excellence (PCo E) of NASA are used to train,validate and test the networks.In previous work,temperature has been set as the output of the networks;however,here the temperature difference along the time axis is adopted as the output.The net heat generated results in net temperature change,which is more closely aligned with electrochemical and thermodynamic laws.Extensive simulation results show that the two RNNs can achieve accurate real-time battery temperature estimation.The maximum absolute error in temperature estimation is approximately 0.75°C and the correlation coefficient between the estimated and measured temperature curves is greater than 0.95.The influences of three crucial parameters,which are the number of hidden neurons,initial learning rate and maximum number of iterations,are also assessed in terms of training time,root mean square error and mean absolute error.
基金the National Natural Science Foundation of China(Grant Nos.51606123,51706141,51976122 and 91541201)。
文摘Optical combustion diagnostics are indispensable tools to investigate flame dynamics and excavate in-situ quantities of flames,such as velocity,temperature,concentration of key intermediates and pressure without introducing probe perturbation.For example,velocity and flame temperature can be obtained using techniques such as particle image velocimetry,coherent anti-Stokes Raman scattering spectroscopy,Rayleigh scattering and tunable diode laser absorption spectroscopy,respectively.