The evaporation ofmicrometer and millimeter liquid drops,involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through the liquid-vapor interface,is encountered in many natural and indus...The evaporation ofmicrometer and millimeter liquid drops,involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through the liquid-vapor interface,is encountered in many natural and industrial processes as well as in numerous engineering applications.Therefore,understanding and predicting the dynamics of evaporating flows have become of primary importance.Recent efforts have been addressed using the method of Smoothed Particle Hydrodynamics(SPH),which has proven to be very efficient in correctly handling the intrinsic complexity introduced by the multiscale nature of the evaporation process.This paper aims to provide an overview of published work on SPH-based simulations related to the evaporation of drops suspended in static and convective environments and impacting on heated solid surfaces.After a brief theoretical account of the main ingredients necessary for the modeling of drop evaporation,the fundamental aspects of SPH are revisited along with the various existing formulations that have been implemented to address the challenges imposed by the physics of evaporating flows.In the following sections,the paper summarizes the results of SPH-based simulations of drop evaporation and ends with a few comments on the limitations of the current state-of-the-art SPHsimulations and future lines of research.展开更多
In laser systems requiring a flat-top distribution of beam intensity,beam smoothing is a critical technology for enhancing laser energy deposition onto the focal spot.The continuous phase modulator(CPM)is a key compon...In laser systems requiring a flat-top distribution of beam intensity,beam smoothing is a critical technology for enhancing laser energy deposition onto the focal spot.The continuous phase modulator(CPM)is a key component in beam smoothing,as it introduces high-frequency continuous phase modulation across the laser beam profile.However,the presence of the CPM makes it challenging to measure and correct the wavefront aberration of the input laser beam effectively,leading to unwanted beam intensity distribution and bringing difficulty to the design of the CPM.To address this issue,we propose a deep learning enabled robust wavefront sensing(DLWS)method to achieve effective wavefront measurement and active aberration correction,thereby facilitating active beam smoothing using the CPM.The experimental results show that the average wavefront reconstruction error of the DLWS method is 0.04μm in the root mean square,while the Shack–Hartmann wavefront sensor reconstruction error is 0.17μm.展开更多
Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retr...Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.展开更多
Cycle slip detection and repair is one of the key technologies for GNSS high-precision positioning.We introduce an enhanced methodology for detecting and repairing BDS four-frequency cycle slips,utilizing fuzzy cluste...Cycle slip detection and repair is one of the key technologies for GNSS high-precision positioning.We introduce an enhanced methodology for detecting and repairing BDS four-frequency cycle slips,utilizing fuzzy clustering analysis.Firstly,based on fuzzy clustering analysis,the optimal combinations for the BDS four-frequency,including extra-wide lane(EWL),wide lane(WL),and narrow lane(NL),were selected.Secondly,the feasibility of this method was verified using actual static and dynamic observation data,and different types of cycle slips were simulated for further validation.Meanwhile,the proposed method was compared with the classical Turbo-Edit method through experiments.Finally,cycle slips were repaired using the least squares method.According to the experimental results,the optimal geometry-free phase combinations(-2,2,1,-1),(1,-1,1,-1),(3,2,-2,-3),and the pseudo-range phase combination(-1,1,1,-1),selected based on fuzzy clustering analysis,were used for cycle slip detection.The proposed method accurately detected small,large,and specific cycle slips simulated in the actual data.Compared with the Turbo-Edit method,the proposed methodwas able to detect specific cycle slips that Turbo-Edit could not.It is worth noting that during the repair process,the coefficients of the combined observation values are integers,preserving the integer cycle characteristic of the observation values,which allows cycle slips to be fixed directly,eliminating the need for complex searching procedures.Consequently,by enhancing the precision and reliability of the detection of BDS four-frequency cycle slips,our proposed method provides the support for the high-precision localization of BDS multi-frequency observations.展开更多
文摘The evaporation ofmicrometer and millimeter liquid drops,involving a liquid-to-vapor phase transition accompanied by mass and energy transfer through the liquid-vapor interface,is encountered in many natural and industrial processes as well as in numerous engineering applications.Therefore,understanding and predicting the dynamics of evaporating flows have become of primary importance.Recent efforts have been addressed using the method of Smoothed Particle Hydrodynamics(SPH),which has proven to be very efficient in correctly handling the intrinsic complexity introduced by the multiscale nature of the evaporation process.This paper aims to provide an overview of published work on SPH-based simulations related to the evaporation of drops suspended in static and convective environments and impacting on heated solid surfaces.After a brief theoretical account of the main ingredients necessary for the modeling of drop evaporation,the fundamental aspects of SPH are revisited along with the various existing formulations that have been implemented to address the challenges imposed by the physics of evaporating flows.In the following sections,the paper summarizes the results of SPH-based simulations of drop evaporation and ends with a few comments on the limitations of the current state-of-the-art SPHsimulations and future lines of research.
基金supported by the National Natural Science Foundation of China(Grant No.61775112).
文摘In laser systems requiring a flat-top distribution of beam intensity,beam smoothing is a critical technology for enhancing laser energy deposition onto the focal spot.The continuous phase modulator(CPM)is a key component in beam smoothing,as it introduces high-frequency continuous phase modulation across the laser beam profile.However,the presence of the CPM makes it challenging to measure and correct the wavefront aberration of the input laser beam effectively,leading to unwanted beam intensity distribution and bringing difficulty to the design of the CPM.To address this issue,we propose a deep learning enabled robust wavefront sensing(DLWS)method to achieve effective wavefront measurement and active aberration correction,thereby facilitating active beam smoothing using the CPM.The experimental results show that the average wavefront reconstruction error of the DLWS method is 0.04μm in the root mean square,while the Shack–Hartmann wavefront sensor reconstruction error is 0.17μm.
基金supported by the National Natural Science Foundation of China(6157138861601398)the National Natural Science Foundation of Hebei Province(F2016203251)
文摘Traditional inverse synthetic aperture radar(ISAR)imaging methods for maneuvering targets have low resolution and poor capability of noise suppression. An ISAR imaging method of maneuvering targets based on phase retrieval is proposed,which can provide a high-resolution and focused map of the spatial distribution of scatterers on the target. According to theoretical derivation, the modulus of raw data from the maneuvering target is not affected by radial motion components for ISAR imaging system, so the phase retrieval algorithm can be used for ISAR imaging problems. However, the traditional phase retrieval algorithm will be not applicable to ISAR imaging under the condition of random noise. To solve this problem, an algorithm is put forward based on the range Doppler(RD) algorithm and oversampling smoothness(OSS) phase retrieval algorithm. The algorithm captures the target information in order to reduce the influence of the random phase on ISAR echoes, and then applies OSS for focusing imaging based on prior information of the RD algorithm. The simulated results demonstrate the validity of this algorithm, which cannot only obtain high resolution imaging for high speed maneuvering targets under the condition of random noise, but also substantially improve the success rate of the phase retrieval algorithm.
基金supported by the National Natural Science Foundation of China(42174003)the Gansu Provincial Department of Education:Innovation Fund Project for College Teachers(2023A-035)+1 种基金Gansu Provincial Science and Technology Program(Joint Research Fund),24JRRA856the Lanzhou Talent Innovation Project,2023-RC-31.
文摘Cycle slip detection and repair is one of the key technologies for GNSS high-precision positioning.We introduce an enhanced methodology for detecting and repairing BDS four-frequency cycle slips,utilizing fuzzy clustering analysis.Firstly,based on fuzzy clustering analysis,the optimal combinations for the BDS four-frequency,including extra-wide lane(EWL),wide lane(WL),and narrow lane(NL),were selected.Secondly,the feasibility of this method was verified using actual static and dynamic observation data,and different types of cycle slips were simulated for further validation.Meanwhile,the proposed method was compared with the classical Turbo-Edit method through experiments.Finally,cycle slips were repaired using the least squares method.According to the experimental results,the optimal geometry-free phase combinations(-2,2,1,-1),(1,-1,1,-1),(3,2,-2,-3),and the pseudo-range phase combination(-1,1,1,-1),selected based on fuzzy clustering analysis,were used for cycle slip detection.The proposed method accurately detected small,large,and specific cycle slips simulated in the actual data.Compared with the Turbo-Edit method,the proposed methodwas able to detect specific cycle slips that Turbo-Edit could not.It is worth noting that during the repair process,the coefficients of the combined observation values are integers,preserving the integer cycle characteristic of the observation values,which allows cycle slips to be fixed directly,eliminating the need for complex searching procedures.Consequently,by enhancing the precision and reliability of the detection of BDS four-frequency cycle slips,our proposed method provides the support for the high-precision localization of BDS multi-frequency observations.
