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| 1 | Creep behavior of EPS composite soil显示文摘EPS composite soil is one type of premixed lightweight fills studied by numerous researchers.However,one aspect that has not been fully understood is the creep behaviors which may have significant effect on the design and application of EPS composite soil.In this paper,the results of a series of oedometer creep tests and triaxial undrained creep tests on EPS composite soil were presented.Four main influencing factors were identified and their effects on the creep behaviors of EPS composite soil were studied.Three well established creep models,namely,Findley model,Singh & Mitchell model,and Mesri model,were used to simulate the creep behavior of EPS composite soil.This study shows that the Findley creep model fits the test results the best.A semi-empirical creep model was also proposed to model the creep behavior under axisymmetric conditions.In this model,the creep strain was divided into instant and viscous elastic strain as well as instant and viscous plastic strain which were simulated by element models and empirical equations,respectively.It was shown that the proposed creep model was able to precisely predict the creep strain of EPS composite soil. | GAO HongMei CHEN YuMin LIU HanLong LIU JinYuan CHU Jian | 2012 | Science China(Technological Sciences)2012，55，11： | 7 |
| 2 | A constitutive model for the state-dependent behaviors of rockfill material considering particle breakage显示文摘The particle breakage during specimen compaction had more significant influence on the position of the breakage critical-state line(BCSL)of Tacheng rockfill material(TRM)in the e-lnp’plane than the particle breakage during shearing,based on the large-scale triaxial compression tests on TRM in a wide range of densities and pressures.The state-dependent dilatancy and the plastic modulus were correlated to the breakage index,based on the formulations of the BCSL of TRM in the e-lnp’plane.The state-dependent model considering particle breakage was proposed for TRM within the framework of the generalized plasticity theory.The proposed model contained fourteen material constants.The test data of TRM from Group A were adopted to determine these material constants,while the test data from Group B were used independently to validate the model predictive capacity.The comparisons between model simulations and test data illustrated that the model with consideration of particle breakage could well represent the stress-strain behaviors of TRM,e.g.,the strain hardening and volumetric contraction behaviors at a loose state and the strain softening and volumetric expansion behaviors at a dense state,and also the particle breakage behaviors of TRM. | XIAO Yang LIU HanLong YANG Gui CHEN YuMin JIANG JingShan | 2014 | Science China(Technological Sciences)2014，57，8： | 6 |
| 3 | Recurrent neural network-based volumetric fluorescence microscopy显示文摘Volumetric imaging of samples using fluorescence microscopy plays an important role in various fields including physical,medical and life sciences.Here we report a deep learning-based volumetric image inference framework that uses 2D images that are sparsely captured by a standard wide-field fluorescence microscope at arbitrary axial positions within the sample volume.Through a recurrent convolutional neural network,which we term as Recurrent-MZ,2D fluorescence information from a few axial planes within the sample is explicitly incorporated to digitally reconstruct the sample volume over an extended depth-of-field.Using experiments on C.elegans and nanobead samples,Recurrent-MZ is demonstrated to significantly increase the depth-of-field of a 63×/1.4NA objective lens,also providing a 30-fold reduction in the number of axial scans required to image the same sample volume.We further illustrated the generalization of this recurrent network for 3D imaging by showing its resilience to varying imaging conditions,including e.g.,different sequences of input images,covering various axial permutations and unknown axial positioning errors.We also demonstrated wide-field to confocal cross-modality image transformations using Recurrent-MZ framework and performed 3D image reconstruction of a sample using a few wide-field 2D fluorescence images as input,matching confocal microscopy images of the same sample volume.Recurrent-MZ demonstrates the first application of recurrent neural networks in microscopic image reconstruction and provides a flexible and rapid volumetric imaging framework,overcoming the limitations of current 3D scanning microscopy tools. | Luzhe Huang Hanlong Chen Yilin Luo Yair Rivenson Aydogan Ozcan | 2021 | Light(Science & Applications)2021，10，4： | 4 |
| 4 | Analysis and Comparison of Two Jumping Leg Models for Bioinspired Locust Robot显示文摘 | Ziqiang Zhang Diansheng Chen Kewei Chen Hanlong Chen | 2016 | Journal of Bionic Engineering2016，13，4： | 4 |
| 5 | Seismic behaviors of utility tunnel-soil system: With and without joint connections显示文摘Seismic responses of utility tunnel-soil system were studied via shaking table model tests with considerations of two kinds of double box utility tunnels:with and without joint connections.These two testing utility tunnel models were made of galvanized iron wire and micro-concrete,and the ground was simulated by the dry standard sand through layered tamping treatment.The utility tunnel-soil system was subjected to horizontal vibration in uniaxial direction perpendicular to the longitudinal direction of tunnel model.Via instrumentations of earth pressure gauges,accelerometers and strain gauges,the earth pressure response,acceleration response and bending moment response were measured.The testing results show that the joint connections in the utility tunnel along the longitudinal direction play an important role in determining the characteristic of earth pressure response and bending moment response,whereas the effect of joint connections on acceleration response is less significant.In addition,the partition wall exhibits the consistent acceleration response with the side-wall of double box utility tunnel model under seismic condition.Based on the testing results,it is suggested that the joint connection should be taken reasonably into consideration during design and construction for engineering practice. | Liang Han Hanlong Liu Wengang Zhang Xuanming Ding Zhixiong Chen Li Feng Zhenyu Wang | 2022 | Underground Space2022，7，5： | 3 |
| 6 | Behavior of large post-liquefaction deformation in saturated Nanjing fine sand显示文摘Laboratory tests on the large post-liquefaction deformation of saturated Nanjing fine sand were performed by using a hollow cylinder apparatus. The stress-strain responses and the characteristics of excess pore water pressure after liquefaction were studied. It was found that the relationship between deviatoric stress and axial strain presented a sigmoid curve, and there was a good linearity relationship between normalized pore water pressure and deviatoric stress. On this basis, a constitutive model of stress-strain responses and a dissipation model of excess pore water pressure were established. It was found that the results predicted by the two models were in good agreement with the experimental data. The influence of relative densities and confi ning pressure on the characteristics of liquef ied soil were studied. The results showed the relative densities and initial effective confining pressure all had an important influence on the stress-strain responses of liquefi ed saturated Nanjing fine sand. However, the dissipation model of excess pore water pressure after liquefaction was only affected by the confining pressure. | Pan Hua Chen Guoxing Liu Hanlong Wang Binghui | 2011 | Earthquake Engineering and Engineering Vibration2011，10，2： | 3 |
| 7 | Fourier Imager Network(FIN):A deep neural network for hologram reconstruction with superior external generalization显示文摘Deep learning-based image reconstruction methods have achieved remarkable success in phase recovery and holographic imaging.However,the generalization of their image reconstruction performance to new types of samples never seen by the network remains a challenge.Here we introduce a deep learning framework,termed Fourier Imager Network(FIN),that can perform end-to-end phase recovery and image reconstruction from raw holograms of new types of samples,exhibiting unprecedented success in external generalization.FIN architecture is based on spatial Fourier transform modules that process the spatial frequencies of its inputs using learnable filters and a global receptive field.Compared with existing convolutional deep neural networks used for hologram reconstruction,FIN exhibits superior generalization to new types of samples,while also being much faster in its image inference speed,completing the hologram reconstruction task in~0.04 s per 1 mm^(2) of the sample area.We experimentally validated the performance of FIN by training it using human lung tissue samples and blindly testing it on human prostate,salivary gland tissue and Pap smear samples,proving its superior external generalization and image reconstruction speed.Beyond holographic microscopy and quantitative phase imaging,FIN and the underlying neural network architecture might open up various new opportunities to design broadly generalizable deep learning models in computational imaging and machine vision fields. | HANLONG CHEN LUZHE HUANG TAIRAN LIU AYDOGAN OZCAN | 2022 | Light(Science & Applications)2022，11，9： | 3 |
| 8 | Study of the seismic performance of hybrid A-frame micropile/MSE (mechanically stabilized earth) wall显示文摘The Hybrid A-Frame Micropile/MSE(mechanically stabilized earth) Wall suitable for mountain roadways is put forward in this study: a pair of vertical and inclined micropiles goes through the backfill region of a highway MSE Wall from the road surface and are then anchored into the foundation. The pile cap and grade beam are placed on the pile tops, and then a road barrier is connected to the grade beam by connecting pieces. The MSE wall's global stability, local stability and impact resistance of the road barrier can be enhanced simultaneously by this design. In order to validate the serviceability of the hybrid A-frame micropile/MSE wall and the reliability of the numerical method, scale model tests and a corresponding numerical simulation were conducted. Then, the seismic performance of the MSE walls before and after reinforcement with micropiles was studied comparatively through numerical methods. The results indicate that the hybrid A-frame micropile/MSE wall can effectively control earthquake-induced deformation, differential settlement at the road surface, bearing pressure on the bottom and acceleration by means of a rigid-soft combination of micropiles and MSE. The accumulated displacement under earthquakes with amplitude of 0.1-0.5g is reduced by 36.3%-46.5%, and the acceleration amplification factor on the top of the wall is reduced by 13.4%, 15.7% and 19.3% based on 0.1, 0.3 and 0.5g input earthquake loading, respectively.In addition, the earthquake-induced failure mode of the MSE wall in steep terrain is the sliding of the MSE region along the backslope, while the micropiles effectively control the sliding trend. The maximum earthquake-induced pile bending moment is in the interface between MSE and slope foundation, so it is necessary to strengthen the reinforcement of the pile body in the interface. Hence, it is proven that the hybrid A-frame micropile/MSE wall system has good seismic performance. | Chen Yumin Zhang Zhichao Liu Hanlong | 2017 | Earthquake Engineering and Engineering Vibration2017，16，2： | 2 |
| 9 | Enhancement of biochemical methane potential from excess sludge with low organic content by mild thermal pretreatment显示文摘 | YAN Yuanyuan CHEN Hanlong XU Wenying | 2013 | Biochemical Engineering Journal2013，70，： | 1 |
| 10 | Tunneling and deep excavations in spatially variable soil and rock masses:A short review显示文摘In an urbanization process,infrastructure elements such as tunnels and deep excavations are widely used to service the development of cities.Owing to the lengthy geological processes of geomaterials and the limited availability of site-specific test data,soil and rock properties exhibiting spatial variability are frequently encountered in geological and geotechnical engineering.This paper presents a comprehensive review of the application of spatial variability in tunneling and deep excavation over the past 20 years.It is found that the spatial variability is generally modeled as a random field(RF)in finite element software,based on random field theory(RFT).This model has been widely used in the design,stability evaluation,and probabilistic analysis of tunnels and excavations.Previous works have proven that the performance of tunnels and deep excavations can be better captured by considering the spatial variability,as compared with conventional deterministic analysis methods.Nonetheless,current research still faces many factual scientific problems.Therefore,this paper also identifies some research gaps,as well as recommendations for further investigations. | Wengang Zhang Liang Han Xin Gu Lin Wang Fuyong Chen Hanlong Liu | 2022 | Underground Space2022，7，3： | 1 |
| 11 | Enhancement of biochemical methane potential from excess sludge with low organic content by mild thermal pretreatment 显示文摘 | YAN Yuanyuan CHEN Hanlong XU Wenying | 2013 | Biochemical Engineering Journal2013，70，： | 1 |
| 12 | ToMFIR-based fault detection approach in frequency domain显示文摘This paper is to explore further results for total measurable fault information-based residual(ToMFIR) approach to fault detection in dynamic systems.The ToMFIR contains the essential fault information and remains unaffected by control actions in a closed-loop system.It is composed of controller residual and output residual and some of further results are developed in frequency domain.Besides the ability of detecting actuator and sensor faults,it is able to detect faults/failures resulting from the computer used for control purpose that generates control signals.Currently,all of existing fault detection schemes cannot achieve the same task at all.A practical DC motor example,with a PID controller,is used to demonstrate the effectiveness of the ToMFIR-based fault detection.A comparison with the standard observer-based technique is also provided. | Wen Chen Chih Ping Yeh Hanlong Yang | 2011 | Journal of Systems Engineering and Electronics2011，22，1： | 0 |
| 13 | Numerical investigation of pile responses induced by adjacent tunnel excavation in spatially variable clays显示文摘The pile responses induced by adjacent tunnel excavation have been a hot research topic in geotechnical engineering.Tunnel excavation may exert disturbance to the surrounding soil mass and then influence the adjacent pile foundations.In this paper,the random finite difference analysis considering the spatial variations of soil properties is conducted to explore the effect of tunnel excavation on the adjacent pile response by varying the distance of pile away from the tunnel centerline(D),the pile length(L),the pile diameter(d_(p)),the tunnel depth(h),and the anisotropic ratio between the horizontal and the vertical scales of fluctuation(δ_(x)/δ_(y)).A set of pile response curves are developed to assess the influence of tunnel excavation on the adjacent passive pile foundations in spatially variable clays and provide guidelines for the tunnel excavation in the complex constructed environment. | Xin Gu Fuyong Chen Wengang Zhang Qi Wang Hanlong Liu | 2022 | Underground Space2022，7，5： | 0 |
| 14 | All-optical image denoising using a diffractive visual processor显示文摘Image denoising,one of the essential inverse problems,targets to remove noise/artifacts from input images.In general,digital image denoising algorithms,executed on computers,present latency due to several iterations implemented in,e.g.,graphics processing units(GPUs).While deep learning-enabled methods can operate non-iteratively,they also introduce latency and impose a significant computational burden,leading to increased power consumption.Here,we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images–implemented at the speed of light propagation within a thin diffractive visual processor that axially spans<250×λ,whereλis the wavelength of light.This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features,causing them to miss the output image Field-of-View(FoV)while retaining the object features of interest.Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of~30–40%.We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum.Owing to their speed,power-efficiency,and minimal computational overhead,all-optical diffractive denoisers can be transformative for various image display and projection systems,including,e.g.,holographic displays. | Çağatay Işıl Tianyi Gan Fazil Onuralp Ardic Koray Mentesoglu Jagrit Digani Huseyin Karaca Hanlong Chen Jingxi Li Deniz Mengu Mona Jarrahi Kaan Akşit Aydogan Ozcan | 2024 | Light(Science & Applications)2024，13，3： | 0 |
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