High-energy density lithium-ion batteries(LIBs)with layered high-nickel oxide cathodes(LiNi_(x)Co_(y)Mn_(1-x-y)O_(2),x≥0.8)show great promise in consumer electronics and vehicular applications.However,LiNi_(x)Co_(y)M...High-energy density lithium-ion batteries(LIBs)with layered high-nickel oxide cathodes(LiNi_(x)Co_(y)Mn_(1-x-y)O_(2),x≥0.8)show great promise in consumer electronics and vehicular applications.However,LiNi_(x)Co_(y)Mn_(1-x-y)O_(2)faces challenges related to capacity decay caused by residual alkalis owing to high sensitivity to air.To address this issue,we propose a hazardous substances upcycling method that fundamentally mitigates alkali content and concurrently induces the emergence of an anti-air-sensitive layer on the cathode surface.Through the neutralization of polyacrylic acid(PAA)with residual alkalis and then coupling it with 3-aminopropyl triethoxysilane(KH550),a stable and ion-conductive cross-linked polymer layer is in situ integrated into the LiNi_(0.89)Co_(0.06)Mn_(0.05)O_(2)(NCM)cathode.Our characterization and measurements demonstrate its effectiveness.The NCM material exhibits impressive cycling performance,retaining 88.4%of its capacity after 200 cycles at 5 C and achieving an extraordinary specific capacity of 170.0 mA h g^(-1) at 10 C.Importantly,this layer on the NCM efficiently suppresses unfavorable phase transitions,severe electrolyte degradation,and CO_(2)gas evolution,while maintaining commendable resistance to air exposure.This surface modification strategy shows widespread potential for creating air-stable LiNi_(x)Co_(y)Mn_(1-x-y)O_(2)cathodes,thereby advancing high-performance LIBs.展开更多
Transition metal chalcogenides(TMCs)are recognized as pre-catalysts,and their(oxy)hydroxides derived from electrochemical reconstruction are the active species in the water oxidation.However,understanding the role of ...Transition metal chalcogenides(TMCs)are recognized as pre-catalysts,and their(oxy)hydroxides derived from electrochemical reconstruction are the active species in the water oxidation.However,understanding the role of the residual chalcogen in the reconstructed layer is lacking in detail,and the corresponding catalytic mechanism remains controversial.Here,taking Cu_(1-x)Co_(x)S as a platform,we explore the regulating effect and existence form of the residual S doped into the reconstructive layer for oxygen evolution reaction(OER),where a dual-path OER mechanism is proposed.First-principles calculations and operando~(18)O isotopic labeling experiments jointly reveal that the residual S in the reconstructive layer of Cu_(1-x)Co_(x)S can wisely balance the adsorbate evolution mechanism(AEM)and lattice oxygen oxidation mechanism(LOM)by activating lattice oxygen and optimizing the adsorption/desorption behaviors at metal active sites,rather than change the reaction mechanism from AEM to LOM.Following such a dual-path OER mechanism,Cu_(0.4)Co_(0.6)S-derived Cu_(0.4)Co_(0.6)OSH not only overcomes the restriction of linear scaling relationship in AEM,but also avoids the structural collapse caused by lattice oxygen migration in LOM,so as to greatly reduce the OER potential and improved stability.展开更多
A numerical model based on measured fictive temperature distributions is explored to evaluate the residual stress fields of CO_(2)laser-annealed mitigated fused silica damage sites.The proposed model extracts the resi...A numerical model based on measured fictive temperature distributions is explored to evaluate the residual stress fields of CO_(2)laser-annealed mitigated fused silica damage sites.The proposed model extracts the residual strain from the differences in thermoelastic contraction of fused silica with different fictive temperatures from the initial frozen-in temperatures to ambient temperature.The residual stress fields of mitigated damage sites for the CO_(2)laser-annealed case are obtained by a finite element analysis of equilibrium equations and constitutive equations.The simulated results indicate that the proposed model can accurately evaluate the residual stress fields of laser-annealed mitigated damage sites with a complex thermal history.The calculated maximum hoop stress is in good agreement with the reported experimental result.The estimated optical retardance profiles from the calculated radial and hoop stress fields are consistent with the photoelastic measurements.These results provide sufficient evidence to demonstrate the suitability of the proposed model for describing the residual stresses of mitigated fused silica damage sites after CO_(2)laser annealing.展开更多
Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the ...Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.展开更多
In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intr...In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intra-pulse modulation signal type based on deep residual network.The basic principle of the recognition method is to obtain the transformation relationship between the time and frequency of complex radar intra-pulse modulation signal through short-time Fourier transform(STFT),and then design an appropriate deep residual network to extract the features of the time-frequency map and complete a variety of complex intra-pulse modulation signal type recognition.In addition,in order to improve the generalization ability of the proposed method,label smoothing and L2 regularization are introduced.The simulation results show that the proposed method has a recognition accuracy of more than 95%for complex radar intra-pulse modulation sig-nal types under low SNR(2 dB).展开更多
Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Dop...Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.展开更多
A new experimental measurement of residual stresses around Vickers′ indentations on the surface of the SiC/Al 2O 3 nanocomposites is proposed with the aid of a Raman microprobe. Results s how that the shifts of R...A new experimental measurement of residual stresses around Vickers′ indentations on the surface of the SiC/Al 2O 3 nanocomposites is proposed with the aid of a Raman microprobe. Results s how that the shifts of R lines in the fluorescence spectra va ry with the distance from the centre of indentation. The magnitude of load appli ed on the surface of the materials through the indenter influences the shifts of R lines to great extent. The luminescence of R lines of the materials before indenting is used to determine the residual stresses around the indentation in the materials, assuming that the stress tensor is transversely isotropic. Final ly, the term of hydrostatic stress is adopted to explain and compare different residual stresses around indentations with the increase of the indenting load an d the distance from the centre of indentations. <展开更多
A new experimental measurement of residual stresses around Vickers′ indentations on the surface of the SiC/Al 2O 3 nanocomposites is proposed with the aid of a Raman microprobe. Results s how that the shifts of R...A new experimental measurement of residual stresses around Vickers′ indentations on the surface of the SiC/Al 2O 3 nanocomposites is proposed with the aid of a Raman microprobe. Results s how that the shifts of R lines in the fluorescence spectra va ry with the distance from the centre of indentation. The magnitude of load appli ed on the surface of the materials through the indenter influences the shifts of R lines to great extent. The luminescence of R lines of the materials before indenting is used to determine the residual stresses around the indentation in the materials, assuming that the stress tensor is transversely isotropic. Final ly, the term of hydrostatic stress is adopted to explain and compare different residual stresses around indentations with the increase of the indenting load an d the distance from the centre of indentations. 【展开更多
To evaluate the coal burst proneness more precisely,a new energy criterion namely the residual elastic energy index was proposed.This study begins by performing the single-cyclic loading-unloading uniaxial compression...To evaluate the coal burst proneness more precisely,a new energy criterion namely the residual elastic energy index was proposed.This study begins by performing the single-cyclic loading-unloading uniaxial compression tests with five pre-peak unloading stress levels to explore the energy storage characteristics of coal.Five types of coals from different mines were tested,and the instantaneous destruction process of the coal specimens under compression loading was recorded using a high speed camera.The results showed a linear relationship between the elastic strain energy density and input energy density,which confirms the linear energy storage law of coal.Based on this linear energy storage law,the peak elastic strain energy density of each coal specimen was obtained precisely.Subsequently,a new energy criterion of coal burst proneness was established,which was called the residual elastic energy index(defined as the difference between the peak elastic strain energy density and post peak failure energy density).Considering the destruction process and actual failure characteristics of coal specimens,the accuracy of evaluating coal burst proneness based on the residual elastic energy index was examined.The results indicated that the residual elastic energy index enables reliable and precise evaluations of the coal burst proneness.展开更多
The efficiency of water flooding in heavy oil reservoirs would be improved by increasing the viscosity of the displacing phase, but the sweep efficiency is not of significance due to the low mobility of the vicious oi...The efficiency of water flooding in heavy oil reservoirs would be improved by increasing the viscosity of the displacing phase, but the sweep efficiency is not of significance due to the low mobility of the vicious oil. On the basis of mobility control theory, increasing the residual resistance factor not only reduces the water-oil mobility ratio but also decreases the requirement for viscosity enhancement of the polymer solution. The residual resistance factor caused by hydrophobic associating polymer solution is higher than that caused by polyacrylamide solution in brine containing high concentrations of calcium and magnesium ions. The results of numerical simulations show that the polymer flooding efficiency improved by increasing the residual resistance factor is far better than that by only increasing solution viscosity. The recovery factor of heavy oil reservoirs （70 mPa·s） can be enhanced by hydrophobic associating polymer solution of high residual resistance factor （more than 3） and high effective viscosity （24 mPa·s）. Therefore, increasing the residual resistance factor of the polymer solution not only decreases the requirement for the viscosity of polymer solution injected into heavy oil reservoirs but also is favorable to enhanced oil recovery during polymer flooding.展开更多
In low signal-to-noise ratio(SNR)environments,the traditional radar emitter recognition(RER)method struggles to recognize multiple radar emitter signals in parallel.This paper proposes a multi-label classification and...In low signal-to-noise ratio(SNR)environments,the traditional radar emitter recognition(RER)method struggles to recognize multiple radar emitter signals in parallel.This paper proposes a multi-label classification and recognition method for multiple radar-emitter modulation types based on a residual network.This method can quickly perform parallel classification and recognition of multi-modulation radar time-domain aliasing signals under low SNRs.First,we perform time-frequency analysis on the received signal to extract the normalized time-frequency image through the short-time Fourier transform(STFT).The time-frequency distribution image is then denoised using a deep normalized convolutional neural network(DNCNN).Secondly,the multi-label classification and recognition model for multi-modulation radar emitter time-domain aliasing signals is established,and learning the characteristics of radar signal time-frequency distribution image dataset to achieve the purpose of training model.Finally,time-frequency image is recognized and classified through the model,thus completing the automatic classification and recognition of the time-domain aliasing signal.Simulation results show that the proposed method can classify and recognize radar emitter signals of different modulation types in parallel under low SNRs.展开更多
The disintegration of granite residual soil is especially affected by variations in physical and chemical properties. Serious geologic hazards or engineering problems are closely related to the disintegration of grani...The disintegration of granite residual soil is especially affected by variations in physical and chemical properties. Serious geologic hazards or engineering problems are closely related to the disintegration of granite residual soil in certain areas. Research on the mechanical properties and controlling mechanisms of disintegration has become a hot issue in practical engineering. In this paper, the disintegration characteristics of improved granite residual soil are studied by using a wet and dry cycle disintegration instrument, and the improvement mechanism is analyzed. The results show that the disintegration amounts and disintegration ratios of soil samples treated with different curing agents are obviously different. The disintegration process of improved granite residual soil can be roughly divided into 5 stages:the forcible water intrusion stage, microcrack and fissure development stage, curing and strengthening stage, stable stage, and sudden disintegration stage. The disintegration of granite residual soil is caused by the weakening of the cementation between soil particles under the action of water. When the disintegration force is greater than the anti-disintegration force of soil, the soil will disintegrate. Cement and lime mainly rely on ion exchange agglomeration, the inclusion effect of curing agents on soil particles, the hard coagulation reaction and carbonation to strengthen granite residual soil. Kaolinite mainly depends on the reversibility of its own cementation to improve and strengthen granite residual soil. The reversibility of kaolinite cementation is verified by investigating pure kaolinite with a tensile, soaking, drying and tensile test cycle. Research on the disintegration characteristics and disintegration mechanism of improved granite residual soil is of certain reference value for soil modification.展开更多
We explore the （2＋l）-dimensional dispersive long-wave （DLW） system. From the standard truncated Painleve expansion, the Baicklund transformation （BT） and residual symmetries of this system are derived. The intr...We explore the （2＋l）-dimensional dispersive long-wave （DLW） system. From the standard truncated Painleve expansion, the Baicklund transformation （BT） and residual symmetries of this system are derived. The introduction to an appropriate auxiliary dependent variable successfully localizes the residual symmetries to Lie point symmetries. In particular, it is verified that the （2＋l）-dimensional DLW system is consistent Riccati expansion （CRE） solvable. If the special form of （CRE）-consistent tanh-function expansion （CTE） is taken, the soliton-cnoidal wave solutions and corresponding images can be explicitly given. Furthermore, the conservation laws of the DLW system are investigated with symmetries and Ibragimov theorem.展开更多
Residual stresses can have a strong effect on the usability of machined parts,and the X-ray diffraction(XRD)measuring equipment,which is commonly used to measure residual stresses,is very expensive.This paper presents...Residual stresses can have a strong effect on the usability of machined parts,and the X-ray diffraction(XRD)measuring equipment,which is commonly used to measure residual stresses,is very expensive.This paper presents a method of measuring the residual stresses induced by boring in the internal surface of a tube with much cheaper equipment.The method,called the strain-based method is mainly based on the strains measured on the external surface of the tube.It is proposed on the basis of the very long tube assumption.The finite element method(FEM)analysis is thus used to validate the length of the tube.Guided by the FEM results,an appropriate length of the tube is chosen,and the residual stresses are obtained from both the strain-based method and the XRD method.Stress profiles obtained from both two methods are compared.The comparison result indicates that the profiles of the two methods agree well with each other.Therefore,it can be concluded that the accuracy of the strain-based method is high enough,and it can be applied to residual stress measurement in practice.展开更多
A multi-residual module stacked hourglass network(MRSH)was proposed to improve the accuracy and robustness of human body pose estimation.The network uses multiple hourglass sub-networks and three new residual modules....A multi-residual module stacked hourglass network(MRSH)was proposed to improve the accuracy and robustness of human body pose estimation.The network uses multiple hourglass sub-networks and three new residual modules.In the hourglass sub-network,the large receptive field residual module(LRFRM)and the multi-scale residual module(MSRM)are first used to learn the spatial relationship between features and body parts at various scales.Only the improved residual module(IRM)is used when the resolution is minimized.The final network uses four stacked hourglass sub-networks,with intermediate supervision at the end of each hourglass,repeating high-low(from high resolution to low resolution)and low-high(from low resolution to high resolution)learning.The network was tested on the public datasets of Leeds sports poses(LSP)and MPII human pose.The experimental results show that the proposed network has better performance in human pose estimation.展开更多
The additive manufacturing(AM)of Ni-based superalloys has attracted extensive interest from both academia and industry due to its unique capabilities to fabricate complex and high-performance components for use in hig...The additive manufacturing(AM)of Ni-based superalloys has attracted extensive interest from both academia and industry due to its unique capabilities to fabricate complex and high-performance components for use in high-end industrial systems.However,the intense temperature gradient induced by the rapid heating and cooling processes of AM can generate high levels of residual stress and metastable chemical and structural states,inevitably leading to severe metallurgical defects in Ni-based superalloys.Cracks are the greatest threat to these materials’integrity as they can rapidly propagate and thereby cause sudden and non-predictable failure.Consequently,there is a need for a deeper understanding of residual stress and cracking mechanisms in additively manufactured Ni-based superalloys and ways to potentially prevent cracking,as this knowledge will enable the wider application of these unique materials.To this end,this paper comprehensively reviews the residual stress and the various mechanisms of crack formation in Ni-based superalloys during AM.In addition,several common methods for inhibiting crack formation are presented to assist the research community to develop methods for the fabrication of crack-free additively manufactured components.展开更多
The integrated structure parts are widely used in aircraft. The distortion caused by residual stresses in thick pre-stretched aluminum plates during machining integrated parts is a common and serious problem. To predi...The integrated structure parts are widely used in aircraft. The distortion caused by residual stresses in thick pre-stretched aluminum plates during machining integrated parts is a common and serious problem. To predict and control the machining distortion, the residual stress distribution in the thick plate must be measured firstly. The modified removal method for measuring residual stress in thick pre-stretched aluminum plates is proposed and the stress-strain relation matrix is deduced by elasticity theory. The residual stress distribution in specimen of 7050T7451 plate is measured by using the method, and measurement results are analyzed and compared with data obtained by other methods. The method is effective to measure the residual stress.展开更多
High frequency(HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising technique to facilitate the working frequency selection and...High frequency(HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising technique to facilitate the working frequency selection and enhance the function of automatic link establishment. Most of the existing spectrum prediction algorithms focus on predicting spectrum values in a slot-by-slot manner and therefore are lack of timeliness. Deep learning based spectrum prediction is developed in this paper by simultaneously predicting multi-slot ahead states of multiple spectrum points within a period of time. Specifically, we first employ supervised learning and construct samples depending on longterm and short-term HF spectrum data. Then, advanced residual units are introduced to build multiple residual network modules to respectively capture characteristics in these data with diverse time scales. Further, convolution neural network fuses the outputs of residual network modules above for temporal-spectral prediction, which is combined with residual network modules to construct the deep temporal-spectral residual network. Experiments have demonstrated that the approach proposed in this paper has a significant advantage over the benchmark schemes.展开更多
Because of the growing concern over the radiation dose delivered to patients, X-ray cone-beam CT(CBCT) imaging of low dose is of great interest. It is difficult for traditional reconstruction methods such as Feldkamp ...Because of the growing concern over the radiation dose delivered to patients, X-ray cone-beam CT(CBCT) imaging of low dose is of great interest. It is difficult for traditional reconstruction methods such as Feldkamp to reduce noise and keep resolution at low doses. A typical method to solve this problem is using optimizationbased methods with careful modeling of physics and additional constraints. However, it is computationally expensive and very time-consuming to reach an optimal solution. Recently, some pioneering work applying deep neural networks had some success in characterizing and removing artifacts from a low-dose data set. In this study,we incorporate imaging physics for a cone-beam CT into a residual convolutional neural network and propose a new end-to-end deep learning-based method for slice-wise reconstruction. By transferring 3D projection to a 2D problem with a noise reduction property, we can not only obtain reconstructions of high image quality, but also lower the computational complexity. The proposed network is composed of three serially connected sub-networks: a cone-to-fan transformation sub-network, a 2D analytical inversion sub-network, and an image refinement sub-network. This provides a comprehensive solution for end-to-end reconstruction for CBCT. The advantages of our method are that the network can simplify a 3D reconstruction problem to a 2D slice-wise reconstruction problem and can complete reconstruction in an end-to-end manner with the system matrix integrated into the network design. Furthermore, reconstruction can be less computationally expensive and easily parallelizable compared with iterative reconstruction methods.展开更多
Specific emitter identification can distin-guish individual transmitters by analyzing received signals and extracting inherent features of hard-ware circuits.Feature extraction is a key part of traditional machine lea...Specific emitter identification can distin-guish individual transmitters by analyzing received signals and extracting inherent features of hard-ware circuits.Feature extraction is a key part of traditional machine learning-based methods,but manual extrac-tion is generally limited by prior professional knowl-edge.At the same time,it has been noted that the per-formance of most specific emitter identification meth-ods degrades in the low signal-to-noise ratio(SNR)environments.The deep residual shrinkage network(DRSN)is proposed for specific emitter identification,particularly in the low SNRs.The soft threshold can preserve more key features for the improvement of performance,and an identity shortcut can speed up the training process.We collect signals via the receiver to create a dataset in the actual environments.The DRSN is trained to automatically extract features and imple-ment the classification of transmitters.Experimental results show that DRSN obtains the best accuracy un-der different SNRs and has less running time,which demonstrates the effectiveness of DRSN in identify-ing specific emitters.展开更多
基金supported by the National Natural Science Foundation of China(52162030)the Yunnan Major Scientific and Technological Projects(202202AG050003)+4 种基金the Key Research and Development Program of Yunnan Province(202103AA080019)the Scientific Research Foundation of Kunming University of Science and Technology(20220122)the Graduate Student Top Innovative Talent Program of Kunming University of Science and Technology(CA23107M139A)the Analysis and Testing Foundation of Kunming University of Science and Technology(2023T20220122)the Shenzhen Science and Technology Program(KCXST20221021111201003)。
文摘High-energy density lithium-ion batteries(LIBs)with layered high-nickel oxide cathodes(LiNi_(x)Co_(y)Mn_(1-x-y)O_(2),x≥0.8)show great promise in consumer electronics and vehicular applications.However,LiNi_(x)Co_(y)Mn_(1-x-y)O_(2)faces challenges related to capacity decay caused by residual alkalis owing to high sensitivity to air.To address this issue,we propose a hazardous substances upcycling method that fundamentally mitigates alkali content and concurrently induces the emergence of an anti-air-sensitive layer on the cathode surface.Through the neutralization of polyacrylic acid(PAA)with residual alkalis and then coupling it with 3-aminopropyl triethoxysilane(KH550),a stable and ion-conductive cross-linked polymer layer is in situ integrated into the LiNi_(0.89)Co_(0.06)Mn_(0.05)O_(2)(NCM)cathode.Our characterization and measurements demonstrate its effectiveness.The NCM material exhibits impressive cycling performance,retaining 88.4%of its capacity after 200 cycles at 5 C and achieving an extraordinary specific capacity of 170.0 mA h g^(-1) at 10 C.Importantly,this layer on the NCM efficiently suppresses unfavorable phase transitions,severe electrolyte degradation,and CO_(2)gas evolution,while maintaining commendable resistance to air exposure.This surface modification strategy shows widespread potential for creating air-stable LiNi_(x)Co_(y)Mn_(1-x-y)O_(2)cathodes,thereby advancing high-performance LIBs.
基金supported by the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202200550)the Natural Science Foundation Joint Fund for Innovation and Development of Chongqing Municipal Education Commission(CSTB2022NSCQ-LZX0077)+4 种基金the National Natural Science Foundation of China(No.52100065)the Science and Technology Research Program of Natural Science Foundation of Chongqing(cstc2021ycjh-bgzxm0037)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJZD-M202200503)the Chongqing Innovation Research Group Project(No.CXQT21015)the Doctor Start/Talent Introduction Program of Chongqing Normal University(No.02060404/2020009000321)。
文摘Transition metal chalcogenides(TMCs)are recognized as pre-catalysts,and their(oxy)hydroxides derived from electrochemical reconstruction are the active species in the water oxidation.However,understanding the role of the residual chalcogen in the reconstructed layer is lacking in detail,and the corresponding catalytic mechanism remains controversial.Here,taking Cu_(1-x)Co_(x)S as a platform,we explore the regulating effect and existence form of the residual S doped into the reconstructive layer for oxygen evolution reaction(OER),where a dual-path OER mechanism is proposed.First-principles calculations and operando~(18)O isotopic labeling experiments jointly reveal that the residual S in the reconstructive layer of Cu_(1-x)Co_(x)S can wisely balance the adsorbate evolution mechanism(AEM)and lattice oxygen oxidation mechanism(LOM)by activating lattice oxygen and optimizing the adsorption/desorption behaviors at metal active sites,rather than change the reaction mechanism from AEM to LOM.Following such a dual-path OER mechanism,Cu_(0.4)Co_(0.6)S-derived Cu_(0.4)Co_(0.6)OSH not only overcomes the restriction of linear scaling relationship in AEM,but also avoids the structural collapse caused by lattice oxygen migration in LOM,so as to greatly reduce the OER potential and improved stability.
基金Project supported by the National Natural Science Foundation of China(Grant No.62275235).
文摘A numerical model based on measured fictive temperature distributions is explored to evaluate the residual stress fields of CO_(2)laser-annealed mitigated fused silica damage sites.The proposed model extracts the residual strain from the differences in thermoelastic contraction of fused silica with different fictive temperatures from the initial frozen-in temperatures to ambient temperature.The residual stress fields of mitigated damage sites for the CO_(2)laser-annealed case are obtained by a finite element analysis of equilibrium equations and constitutive equations.The simulated results indicate that the proposed model can accurately evaluate the residual stress fields of laser-annealed mitigated damage sites with a complex thermal history.The calculated maximum hoop stress is in good agreement with the reported experimental result.The estimated optical retardance profiles from the calculated radial and hoop stress fields are consistent with the photoelastic measurements.These results provide sufficient evidence to demonstrate the suitability of the proposed model for describing the residual stresses of mitigated fused silica damage sites after CO_(2)laser annealing.
基金National Natural Science Foundation of China under Grant No.61973037China Postdoctoral Science Foundation under Grant No.2022M720419。
文摘Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.
文摘In view of low recognition rate of complex radar intra-pulse modulation signal type by traditional methods under low signal-to-noise ratio(SNR),the paper proposes an automatic recog-nition method of complex radar intra-pulse modulation signal type based on deep residual network.The basic principle of the recognition method is to obtain the transformation relationship between the time and frequency of complex radar intra-pulse modulation signal through short-time Fourier transform(STFT),and then design an appropriate deep residual network to extract the features of the time-frequency map and complete a variety of complex intra-pulse modulation signal type recognition.In addition,in order to improve the generalization ability of the proposed method,label smoothing and L2 regularization are introduced.The simulation results show that the proposed method has a recognition accuracy of more than 95%for complex radar intra-pulse modulation sig-nal types under low SNR(2 dB).
基金supported in part by the National Natural Foundation of China(No.62027801).
文摘Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.
文摘A new experimental measurement of residual stresses around Vickers′ indentations on the surface of the SiC/Al 2O 3 nanocomposites is proposed with the aid of a Raman microprobe. Results s how that the shifts of R lines in the fluorescence spectra va ry with the distance from the centre of indentation. The magnitude of load appli ed on the surface of the materials through the indenter influences the shifts of R lines to great extent. The luminescence of R lines of the materials before indenting is used to determine the residual stresses around the indentation in the materials, assuming that the stress tensor is transversely isotropic. Final ly, the term of hydrostatic stress is adopted to explain and compare different residual stresses around indentations with the increase of the indenting load an d the distance from the centre of indentations. <
文摘A new experimental measurement of residual stresses around Vickers′ indentations on the surface of the SiC/Al 2O 3 nanocomposites is proposed with the aid of a Raman microprobe. Results s how that the shifts of R lines in the fluorescence spectra va ry with the distance from the centre of indentation. The magnitude of load appli ed on the surface of the materials through the indenter influences the shifts of R lines to great extent. The luminescence of R lines of the materials before indenting is used to determine the residual stresses around the indentation in the materials, assuming that the stress tensor is transversely isotropic. Final ly, the term of hydrostatic stress is adopted to explain and compare different residual stresses around indentations with the increase of the indenting load an d the distance from the centre of indentations. 【
基金This work was supported by the National Natural Science Foundation of China(No.41877272)the Fundamental Research Funds for the Central Universities of Southeast University(No.2242021R10080).
文摘To evaluate the coal burst proneness more precisely,a new energy criterion namely the residual elastic energy index was proposed.This study begins by performing the single-cyclic loading-unloading uniaxial compression tests with five pre-peak unloading stress levels to explore the energy storage characteristics of coal.Five types of coals from different mines were tested,and the instantaneous destruction process of the coal specimens under compression loading was recorded using a high speed camera.The results showed a linear relationship between the elastic strain energy density and input energy density,which confirms the linear energy storage law of coal.Based on this linear energy storage law,the peak elastic strain energy density of each coal specimen was obtained precisely.Subsequently,a new energy criterion of coal burst proneness was established,which was called the residual elastic energy index(defined as the difference between the peak elastic strain energy density and post peak failure energy density).Considering the destruction process and actual failure characteristics of coal specimens,the accuracy of evaluating coal burst proneness based on the residual elastic energy index was examined.The results indicated that the residual elastic energy index enables reliable and precise evaluations of the coal burst proneness.
基金supported by the National High Technology Research and Development Program of China (863 Program: 2006AA09Z315 and 2007AA090701-3)
文摘The efficiency of water flooding in heavy oil reservoirs would be improved by increasing the viscosity of the displacing phase, but the sweep efficiency is not of significance due to the low mobility of the vicious oil. On the basis of mobility control theory, increasing the residual resistance factor not only reduces the water-oil mobility ratio but also decreases the requirement for viscosity enhancement of the polymer solution. The residual resistance factor caused by hydrophobic associating polymer solution is higher than that caused by polyacrylamide solution in brine containing high concentrations of calcium and magnesium ions. The results of numerical simulations show that the polymer flooding efficiency improved by increasing the residual resistance factor is far better than that by only increasing solution viscosity. The recovery factor of heavy oil reservoirs （70 mPa·s） can be enhanced by hydrophobic associating polymer solution of high residual resistance factor （more than 3） and high effective viscosity （24 mPa·s）. Therefore, increasing the residual resistance factor of the polymer solution not only decreases the requirement for the viscosity of polymer solution injected into heavy oil reservoirs but also is favorable to enhanced oil recovery during polymer flooding.
基金The authors would like to acknowledge National Natural Science Foundation of China under Grant 61973037 and Grant 61673066 to provide fund for conducting experiments.
文摘In low signal-to-noise ratio(SNR)environments,the traditional radar emitter recognition(RER)method struggles to recognize multiple radar emitter signals in parallel.This paper proposes a multi-label classification and recognition method for multiple radar-emitter modulation types based on a residual network.This method can quickly perform parallel classification and recognition of multi-modulation radar time-domain aliasing signals under low SNRs.First,we perform time-frequency analysis on the received signal to extract the normalized time-frequency image through the short-time Fourier transform(STFT).The time-frequency distribution image is then denoised using a deep normalized convolutional neural network(DNCNN).Secondly,the multi-label classification and recognition model for multi-modulation radar emitter time-domain aliasing signals is established,and learning the characteristics of radar signal time-frequency distribution image dataset to achieve the purpose of training model.Finally,time-frequency image is recognized and classified through the model,thus completing the automatic classification and recognition of the time-domain aliasing signal.Simulation results show that the proposed method can classify and recognize radar emitter signals of different modulation types in parallel under low SNRs.
基金supported by the National Natural Science Foundation of China (Nos. 41877228, 41877229 and 42102303)Guangdong Basic and Applied Basic Research Foundation (Nos. 2018B030311066 and 2019A1515010554)+1 种基金China Postdoctoral Science Foundation (No. 2019M663241)Science and Technology Program of Guangzhou, China (No. 201904010136)。
文摘The disintegration of granite residual soil is especially affected by variations in physical and chemical properties. Serious geologic hazards or engineering problems are closely related to the disintegration of granite residual soil in certain areas. Research on the mechanical properties and controlling mechanisms of disintegration has become a hot issue in practical engineering. In this paper, the disintegration characteristics of improved granite residual soil are studied by using a wet and dry cycle disintegration instrument, and the improvement mechanism is analyzed. The results show that the disintegration amounts and disintegration ratios of soil samples treated with different curing agents are obviously different. The disintegration process of improved granite residual soil can be roughly divided into 5 stages:the forcible water intrusion stage, microcrack and fissure development stage, curing and strengthening stage, stable stage, and sudden disintegration stage. The disintegration of granite residual soil is caused by the weakening of the cementation between soil particles under the action of water. When the disintegration force is greater than the anti-disintegration force of soil, the soil will disintegrate. Cement and lime mainly rely on ion exchange agglomeration, the inclusion effect of curing agents on soil particles, the hard coagulation reaction and carbonation to strengthen granite residual soil. Kaolinite mainly depends on the reversibility of its own cementation to improve and strengthen granite residual soil. The reversibility of kaolinite cementation is verified by investigating pure kaolinite with a tensile, soaking, drying and tensile test cycle. Research on the disintegration characteristics and disintegration mechanism of improved granite residual soil is of certain reference value for soil modification.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11371293 and 11505090)the Natural Science Foundation of Shaanxi Province,China(Grant No.2014JM2-1009)+1 种基金the Research Award Foundation for Outstanding Young Scientists of Shandong Province,China(Grant No.BS2015SF009)the Science and Technology Innovation Foundation of Xi’an,China(Grant No.CYX1531WL41)
文摘We explore the （2＋l）-dimensional dispersive long-wave （DLW） system. From the standard truncated Painleve expansion, the Baicklund transformation （BT） and residual symmetries of this system are derived. The introduction to an appropriate auxiliary dependent variable successfully localizes the residual symmetries to Lie point symmetries. In particular, it is verified that the （2＋l）-dimensional DLW system is consistent Riccati expansion （CRE） solvable. If the special form of （CRE）-consistent tanh-function expansion （CTE） is taken, the soliton-cnoidal wave solutions and corresponding images can be explicitly given. Furthermore, the conservation laws of the DLW system are investigated with symmetries and Ibragimov theorem.
基金Supported by the National Defense Program of China(C152012C002)the Specialized Research Fund for the Doctoral Program of Higher Education of China(20123218120025)
文摘Residual stresses can have a strong effect on the usability of machined parts,and the X-ray diffraction(XRD)measuring equipment,which is commonly used to measure residual stresses,is very expensive.This paper presents a method of measuring the residual stresses induced by boring in the internal surface of a tube with much cheaper equipment.The method,called the strain-based method is mainly based on the strains measured on the external surface of the tube.It is proposed on the basis of the very long tube assumption.The finite element method(FEM)analysis is thus used to validate the length of the tube.Guided by the FEM results,an appropriate length of the tube is chosen,and the residual stresses are obtained from both the strain-based method and the XRD method.Stress profiles obtained from both two methods are compared.The comparison result indicates that the profiles of the two methods agree well with each other.Therefore,it can be concluded that the accuracy of the strain-based method is high enough,and it can be applied to residual stress measurement in practice.
基金Supported by the National Natural Science Foundation of China(61401001,61501003,61672032)。
文摘A multi-residual module stacked hourglass network(MRSH)was proposed to improve the accuracy and robustness of human body pose estimation.The network uses multiple hourglass sub-networks and three new residual modules.In the hourglass sub-network,the large receptive field residual module(LRFRM)and the multi-scale residual module(MSRM)are first used to learn the spatial relationship between features and body parts at various scales.Only the improved residual module(IRM)is used when the resolution is minimized.The final network uses four stacked hourglass sub-networks,with intermediate supervision at the end of each hourglass,repeating high-low(from high resolution to low resolution)and low-high(from low resolution to high resolution)learning.The network was tested on the public datasets of Leeds sports poses(LSP)and MPII human pose.The experimental results show that the proposed network has better performance in human pose estimation.
基金This work was supported by Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone Shenzhen Park Project:HZQB-KCZYB-2020030the National Natural Science Foundation of China(No.91860131and No.52074157)+2 种基金Guangdong Provincial Department of Science and Technology,Key-Area Research and Development Program of Guangdong Province(No.2020B090923002)the National Key Research and Development Program of China(No.2017YFB0702901)the Shenzhen Science and Technology Innovation Commission(No.JCYJ20170817111811303,No.KQTD20170328154443162and No.ZDSYS201703031748354).
文摘The additive manufacturing(AM)of Ni-based superalloys has attracted extensive interest from both academia and industry due to its unique capabilities to fabricate complex and high-performance components for use in high-end industrial systems.However,the intense temperature gradient induced by the rapid heating and cooling processes of AM can generate high levels of residual stress and metastable chemical and structural states,inevitably leading to severe metallurgical defects in Ni-based superalloys.Cracks are the greatest threat to these materials’integrity as they can rapidly propagate and thereby cause sudden and non-predictable failure.Consequently,there is a need for a deeper understanding of residual stress and cracking mechanisms in additively manufactured Ni-based superalloys and ways to potentially prevent cracking,as this knowledge will enable the wider application of these unique materials.To this end,this paper comprehensively reviews the residual stress and the various mechanisms of crack formation in Ni-based superalloys during AM.In addition,several common methods for inhibiting crack formation are presented to assist the research community to develop methods for the fabrication of crack-free additively manufactured components.
文摘The integrated structure parts are widely used in aircraft. The distortion caused by residual stresses in thick pre-stretched aluminum plates during machining integrated parts is a common and serious problem. To predict and control the machining distortion, the residual stress distribution in the thick plate must be measured firstly. The modified removal method for measuring residual stress in thick pre-stretched aluminum plates is proposed and the stress-strain relation matrix is deduced by elasticity theory. The residual stress distribution in specimen of 7050T7451 plate is measured by using the method, and measurement results are analyzed and compared with data obtained by other methods. The method is effective to measure the residual stress.
基金supported in part by the National Natural Science Foundation of China (Grants No. 61501510 and No. 61631020)Natural Science Foundation of Jiangsu Province (Grant No. BK20150717)+2 种基金China Postdoctoral Science Foundation Funded Project (Grant No. 2016M590398 and No.2018T110426)Jiangsu Planned Projects for Postdoctoral Research Funds (Grant No. 1501009A)Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province (Grant No. BK20160034)
文摘High frequency(HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising technique to facilitate the working frequency selection and enhance the function of automatic link establishment. Most of the existing spectrum prediction algorithms focus on predicting spectrum values in a slot-by-slot manner and therefore are lack of timeliness. Deep learning based spectrum prediction is developed in this paper by simultaneously predicting multi-slot ahead states of multiple spectrum points within a period of time. Specifically, we first employ supervised learning and construct samples depending on longterm and short-term HF spectrum data. Then, advanced residual units are introduced to build multiple residual network modules to respectively capture characteristics in these data with diverse time scales. Further, convolution neural network fuses the outputs of residual network modules above for temporal-spectral prediction, which is combined with residual network modules to construct the deep temporal-spectral residual network. Experiments have demonstrated that the approach proposed in this paper has a significant advantage over the benchmark schemes.
基金supported by the National Natural Science Foundation of China(Nos.61771279,11435007)the National Key Research and Development Program of China(No.2016YFF0101304)
文摘Because of the growing concern over the radiation dose delivered to patients, X-ray cone-beam CT(CBCT) imaging of low dose is of great interest. It is difficult for traditional reconstruction methods such as Feldkamp to reduce noise and keep resolution at low doses. A typical method to solve this problem is using optimizationbased methods with careful modeling of physics and additional constraints. However, it is computationally expensive and very time-consuming to reach an optimal solution. Recently, some pioneering work applying deep neural networks had some success in characterizing and removing artifacts from a low-dose data set. In this study,we incorporate imaging physics for a cone-beam CT into a residual convolutional neural network and propose a new end-to-end deep learning-based method for slice-wise reconstruction. By transferring 3D projection to a 2D problem with a noise reduction property, we can not only obtain reconstructions of high image quality, but also lower the computational complexity. The proposed network is composed of three serially connected sub-networks: a cone-to-fan transformation sub-network, a 2D analytical inversion sub-network, and an image refinement sub-network. This provides a comprehensive solution for end-to-end reconstruction for CBCT. The advantages of our method are that the network can simplify a 3D reconstruction problem to a 2D slice-wise reconstruction problem and can complete reconstruction in an end-to-end manner with the system matrix integrated into the network design. Furthermore, reconstruction can be less computationally expensive and easily parallelizable compared with iterative reconstruction methods.
基金the National Natural Science Foundation of China(No.U20B2038,No.61871398,NO.61901520 and No.61931011)the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province(No.BK20190030)the National Key R&D Program of China under Grant 2018YFB1801103.
文摘Specific emitter identification can distin-guish individual transmitters by analyzing received signals and extracting inherent features of hard-ware circuits.Feature extraction is a key part of traditional machine learning-based methods,but manual extrac-tion is generally limited by prior professional knowl-edge.At the same time,it has been noted that the per-formance of most specific emitter identification meth-ods degrades in the low signal-to-noise ratio(SNR)environments.The deep residual shrinkage network(DRSN)is proposed for specific emitter identification,particularly in the low SNRs.The soft threshold can preserve more key features for the improvement of performance,and an identity shortcut can speed up the training process.We collect signals via the receiver to create a dataset in the actual environments.The DRSN is trained to automatically extract features and imple-ment the classification of transmitters.Experimental results show that DRSN obtains the best accuracy un-der different SNRs and has less running time,which demonstrates the effectiveness of DRSN in identify-ing specific emitters.
