Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced tran...Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.展开更多
Optogenetic has been widely applied in various pathogenesis investigations of neuropathic diseases since its accurate and targeted regulation of neuronal activity.However,due to the mismatch between the soft tissues a...Optogenetic has been widely applied in various pathogenesis investigations of neuropathic diseases since its accurate and targeted regulation of neuronal activity.However,due to the mismatch between the soft tissues and the optical waveguide,the long-term neural regulation within soft tissue(such as brain and spinal cord)by implantable optical fibers is a large challenge.Herein,we designed a modulus selfadaptive hydrogel optical fiber(MSHOF)with tunable mechanical properties(Young’modulus was tunable in the range of 0.32-10.56MPa)and low light attenuation(0.12-0.21 dB/cm,472nm laser light),which adapts to light transmission under soft tissues.These advantages of MSHOF can ensure the effectiveness of optogenetic stimulation meanwhile safeguarding the safety of the brain/materials interaction interface.In addition,this work provides more design possibilities of MSHOF for photogenetic stimuli and has significant application prospects in photomedical therapy.展开更多
In this paper,a double-effect DNN-based Digital Back-Propagation(DBP)scheme is proposed and studied to achieve the Integrated Communication and Sensing(ICS)ability,which can not only realize nonlinear damage mitigatio...In this paper,a double-effect DNN-based Digital Back-Propagation(DBP)scheme is proposed and studied to achieve the Integrated Communication and Sensing(ICS)ability,which can not only realize nonlinear damage mitigation but also monitor the optical power and dispersion profile over multi-span links.The link status information can be extracted by the characteristics of the learned optical fiber parameters without any other measuring instruments.The efficiency and feasibility of this method have been investigated in different fiber link conditions,including various launch power,transmission distance,and the location and the amount of the abnormal losses.A good monitoring performance can be obtained while the launch optical power is 2 dBm which does not affect the normal operation of the optical communication system and the step size of DBP is 20 km which can provide a better distance resolution.This scheme successfully detects the location of single or multiple optical attenuators in long-distance multi-span fiber links,including different abnormal losses of 2 dB,4 dB,and 6 dB in 360 km and serval combinations of abnormal losses of(1 dB,5 dB),(3 dB,3 dB),(5 dB,1 dB)in 360 km and 760 km.Meanwhile,the transfer relationship of the estimated coefficient values with different step sizes is further investigated to reduce the complexity of the fiber nonlinear damage compensation.These results provide an attractive approach for precisely sensing the optical fiber link status information and making correct strategies timely to ensure optical communication system operations.展开更多
Soft polymer optical fiber(SPOF)has shown great potential in optical-based wearable and implantable biosensors due to its excellent mechanical properties and optical guiding characteristics.However,the multimodality c...Soft polymer optical fiber(SPOF)has shown great potential in optical-based wearable and implantable biosensors due to its excellent mechanical properties and optical guiding characteristics.However,the multimodality characteristics of SPOF limit their integration with traditional fiber optic sensors.This article introduces for the first time a flexible fiber optic vibration sensor based on laser interference technology,which can be applied to vibration measurement under high stretch conditions.This sensor utilizes elastic optical fibers made of polydimethylsiloxane(PDMS)as sensing elements,combined with phase generating carrier technology,to achieve vibration measurement at 50−260 Hz within the stretch range of 0−42%.展开更多
This paper examines the design and optimization of optical fibers for high-speed data transmission, emphasizing advancements that maximize efficiency in modern communication networks. Optical fibers, core components o...This paper examines the design and optimization of optical fibers for high-speed data transmission, emphasizing advancements that maximize efficiency in modern communication networks. Optical fibers, core components of global communication infrastructure, are capable of transmitting data over long distances with minimal loss through principles like total internal reflection. This study explores single-mode and multi-mode fiber designs, providing an overview of key parameters such as core diameter, refractive index profile, and numerical aperture. Mathematical modeling using Maxwell’s equations plays a central role in optimizing fiber performance, helping engineers mitigate challenges like attenuation and dispersion. The paper also discusses advanced techniques, including dense wavelength division multiplexing (DWDM), which enables terabit-per-second data rates. Case studies in practical applications, such as fiber-to-the-home (FTTH) networks and transoceanic cables, highlight the impact of optimized designs on network performance. Looking forward, innovations in photonic crystal fibers and hollow-core fibers are expected to drive further improvements, enabling ultra-high-speed data transmission. The paper concludes by underscoring the significance of continuous research and development to address challenges in optical fiber technology and support the increasing demands of global communication systems.展开更多
We proposed a fiber optic high temperature sensor based on the Mach-Zehnder interference(MZI)structure,which is composed of two lengths of multi-mode fibers(MMFs),a length of few-mode fiber(FMF)and two sections of sin...We proposed a fiber optic high temperature sensor based on the Mach-Zehnder interference(MZI)structure,which is composed of two lengths of multi-mode fibers(MMFs),a length of few-mode fiber(FMF)and two sections of single-mode fibers(SMFs).Firstly,the two sections of MMFs were spliced with two sections of SMFs.Then,the MMFs were fused to two ends of FMF to form a symmetrically structured fiber-optic MZI structure.In this structure,the MMF served as the optical mode field coupling element,and the cladding and core of the FMF are the interference arm and the reference arm of the MZI structure,respectively.We investigated the sensor's response characteristics of the temperature and strain.The experimental results indicate that the sensor is sensitive to temperature variation,and the temperature response sensitivity is up to 61.4 pm/℃ in the range of 40-250℃,while the sensor has weak strain sensitivity,its strain sensitivity is only-0.72 pm/μe in the strain range of 0-1400μe.Moreover,the sensor has good stability and repeatability.In brief,the proposed fiber optic high temperature sensor has good properties,such as high sensitivity,compact structure,good stability and repeatability,which can be used for monitoring the temperature of submerged oil electric pump units under oil wells.展开更多
Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fib...Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers,and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear.This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers.By constructing representative volume elements(RVEs)with randomly distributed reinforcing fibers,the optical fiber,the matrix,and the interface phase,the micromechanical behavior and damage evolution under transverse tensile and compressive loads are explored.The study finds that the presence of embedded optical fibers significantly influences the initiation and propagation of microscopic damage within the composites.Under transverse tension,the fiber-matrix interface cracks first,followed by plastic cracking in the matrix surrounding the fibers,forming micro-cracks.Eventually,these cracks connect with the debonded areas at the fiber-matrix interface to form a dominant crack that spans the entire model.Under transverse compression,plastic cracking first occurs in the resin surrounding the optical fibers,connecting with the interface debonding areas between the optical fibers and the matrix to form two parallel shear bands.Additionally,it is observed that the strength of the interface between the optical fiber and the matrix critically affects the simulation results.The simulated damage morphologies align closely with those observed using scanning electron microscopy(SEM).These findings offer theoretical insights that can inform the design and fabrication of smart composite materials with embedded optical fiber sensors for advanced structural health monitoring.展开更多
As a laser passes through a scattering medium,the light interacts with the irregular reflections within the medium,resulting in light scattering and the formation of speckles.In this paper,an image sensor based on the...As a laser passes through a scattering medium,the light interacts with the irregular reflections within the medium,resulting in light scattering and the formation of speckles.In this paper,an image sensor based on the combination of a coreless optical fiber and a digital camera is proposed for liquid refractive index sensing applications.The coreless fiber is used as a sensing unit,and the change in the speckle pattern is measured using the digital correlation method to detect the magnitude of the liquid's refractive index.The experimental results indicate that the laser image sensing technique is capable of effectively distinguishing liquid samples with refractive indices ranging from 1.332 8 to1.390 8,with a sensing sensitivity of-1.306 RIU-l.Moreover,the laser image sensing technique,with its advantages of high experimental reproducibility,simple system design,remote over-control,holds great research significance and potential application in laser communication and sensor integration.展开更多
To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase n...To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.展开更多
Vibration detection using sensors with both wide working frequency range,good sensitivity,and other good performances is a topic of great interest in fields such as inertial navigation,deep-sea fishing boat engines co...Vibration detection using sensors with both wide working frequency range,good sensitivity,and other good performances is a topic of great interest in fields such as inertial navigation,deep-sea fishing boat engines condition monitoring,seismic monitoring,attitude,and heading reference system,etc.This paper investigates two 6H-SIC MEMS diaphragms,one triangular and the other square,used in a fiber optic Fabry–Perot(FP)accelerometer in an experimental scenario.The triangular chip shows a wide working frequency range of 630 Hz–5300 Hz,a natural frequency of 44.3 k Hz,and a mechanical sensitivity of 0.154 nm/g.An optimal structure of the square chip used in a probe such as a fiber optic FP accelerometer also shows a wide working frequency range of 120 Hz–2300 Hz;a good sensitivity of 31.5 m V/g,a resonance frequency of7873 Hz,an accuracy of 0.96%F.S.,a frequency measurement error of 1.15%,and an excellent linearity of 0.9995.展开更多
The rapid expansion of urban development has led to the extensive construction of civil infrastructures.However,these urban development zones frequently face potential geohazards,primarily due to the lack of detailed ...The rapid expansion of urban development has led to the extensive construction of civil infrastructures.However,these urban development zones frequently face potential geohazards,primarily due to the lack of detailed site investigations and long-term monitoring of subsurface geological conditions.Understanding the temporal and spatial distributions of underground multi-field information is vital for successful engineering construction and effective utilization of urban underground space.In this study,a fiber optic nerve system(FONS)was utilized in the Tianfu New Area,Sichuan Province,China,to obtain comprehensive subsurface multi-physical information,including geological deformation,temperature,and surface hydrological data.The FONS incorporates three advanced fiber optic sensing techniques,i.e.fiber Bragg grating(FBG),Brillouin optical time domain reflectometry(BOTDR),and Raman optical time domain reflectometry(ROTDR).Fully-and quasi-distributed strain/temperature sensing cables have been installed in nine monitoring boreholes,covering various geological features such as plains,terraces,and areas within active fault zones.The field monitoring results confirm the feasibility of employing FONS for geological investigations within urban development zones,offering a valuable reference for future applications of this cost-effective technology in geohazard mitigation.展开更多
Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).C...Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.展开更多
The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibratio...The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibration signals induced by external events and to effectively provide early warnings of potential intrusion activities.Due to the complexity and diversity of external intrusion events,traditional deep learning methods can achieve event recognition with an average accuracy exceeding 90%.However,these methods rely on large-scale datasets,leading to significant time and labor costs during the data collection process.Additionally,traditional methods perform poorly when faced with the scarcity of low-frequency event samples,making it challenging to address these rare occurrences.To address this issue,this paper proposes a small-sample learning model based on triplet learning for intrusion event recognition.The model employs a 6-way 20-shot support set configuration and utilizes the KNN clustering algorithm to assess the model's performance.Experimental results indicate that the model achieves an average accuracy of 91.6%,further validating the superior performance of the triplet learning model in classifying external intrusion events.Compared to traditional methods,this approach not only effectively reduces the dependence on large-scale datasets but also better addresses the classification of low-frequency event samples,demonstrating significant application potential.展开更多
With the rapid development of lithium batteries,it’s of great significance to ensure the safe use of it.An ultrasound imaging system based on fiber optic ultrasound sensor has been developed to monitor the internal c...With the rapid development of lithium batteries,it’s of great significance to ensure the safe use of it.An ultrasound imaging system based on fiber optic ultrasound sensor has been developed to monitor the internal changes of lithium batteries.Based on Fabry-Perot interferometer(FPI)structure which is made of a glass plate and an optical fiber pigtail,the ultrasound imaging system possesses a high sensitivity of 558 mV/kPa at 500 kHz with the noise equivalent pressure(NEP)of only 63.5 mPa.For the frequency response,the ultrasound sensitivity is higher than 13.1 mV/kPa within the frequency range from 50 kHz to 1 MHz.Meanwhile,the battery imaging system based on the proposed sensor has a superior resolution as high as 0.5 mm.The performance of battery safety monitoring is verified,in which three commercial lithium-ion ferrous phosphate/graphite(LFP||Gr)batteries are imaged and the state of health(SOH)for different batteries is obtained.Besides,the wetting process of an anode-free lithium metal batteries(AFLMB)is clearly observed via the proposed system,in which the formation process of the pouch cell is analyzed and the gas-related"unwetting"condition is discovered,representing a significant advancement in battery health monitoring field.In the future,the commercial usage can be realized when sensor array and artificial intelligence technology are adopted.展开更多
The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system ...The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system with kilometer-level sensing distance and submeter spatial resolution.Based on this,we propose a Raman distributed optical fiber sensing scheme based on chaotic pulse cluster demodulation.Chaotic pulse clusters are used as the probe signal,in preference to conventional pulsed or chaotic single-pulse lasers.Furthermore,the accurate positioning of the temperature variety region along the sensing fiber can be realized using chaotic pulse clusters.The proposed demodulation scheme can enhance the signal-to-noise ratio by improving the correlation between the chaotic reference and the chaotic Raman anti-Stokes scattering signals.The experiment achieved a sensing spatial resolution of 30 cm at a distributed temperature-sensing distance of∼6.0 km.Furthermore,we explored the influence of chaotic pulse width and detector bandwidth on the sensing spatial resolution.In addition,the theoretical experiments proved that the sensing spatial resolution in the proposed scheme was independent of the pulse width and sensing distance.展开更多
Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has seve...Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision FOGs.The conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under vibration.In this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put forward.Particularly,the loop gain is extracted out by adding a gain-monitoring wave.By demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation depth.The experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 Hz.This technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.展开更多
As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely...As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields.展开更多
Despite the extensive use of distributed fiber optic sensing(DFOS)in monitoring underground structures,its potential in detecting structural anomalies,such as cracks and cavities,is still not fully understood.To contr...Despite the extensive use of distributed fiber optic sensing(DFOS)in monitoring underground structures,its potential in detecting structural anomalies,such as cracks and cavities,is still not fully understood.To contribute to the identification of defects in underground structures,this study conducted a four-point bending test of a reinforced concrete(RC)beam and uniaxial loading tests of an RC specimen with local cavities.The experimental results revealed the disparity in DFOS strain spike profiles between these two structural anomalies.The effectiveness of DFOS in the quantification of crack opening displacement(COD)was also demonstrated,even in cases where perfect bonding was not achievable between the cable and structures.In addition,DFOS strain spikes observed in two diaphragm wall panels of a twin circular shaft were also reported.The most probable cause of those spikes was identified as the mechanical behavior associated with local concrete contamination.With the utilization of the strain profiles obtained from laboratory tests and field monitoring,three types of multi-classifiers,based on support vector machine(SVM),random forest(RF),and backpropagation neural network(BP),were employed to classify strain profiles,including crack-induced spikes,non-crack-induced spikes,and non-spike strain profiles.Among these classifiers,the SVM-based classifier exhibited superior performance in terms of accuracy and model robustness.This finding suggests that the SVM-based classifier holds promise as a potential solution for the automatic detection and classification of defects in underground structures during long-term monitoring.展开更多
The commonly used method for estimating crack opening displacement(COD)is based on analytical models derived from strain transferring.However,when large background noise exists in distributed fiber optic sensing(DFOS)...The commonly used method for estimating crack opening displacement(COD)is based on analytical models derived from strain transferring.However,when large background noise exists in distributed fiber optic sensing(DFOS)data,estimating COD through an analytical model is very difficult even if the DFOS data have been denoised.To address this challenge,this study proposes a machine learning(ML)-based methodology to complete rock's COD estimation from establishment of a dataset with one-to-one correspondence between strain sequence and COD to the optimization of ML models.The Bayesian optimization is used via the Hyperopt Python library to determine the appropriate hyper-parameters of four ML models.To ensure that the best hyper-parameters will not be missing,the configuration space in Hyperopt is specified by probability distribution.The four models are trained using DFOS data with minimal noise while being examined on datasets with different noise levels to test their anti-noise robustness.The proposed models are compared each other in terms of goodness of fit and mean squared error.The results show that the Bayesian optimization-based random forest is promising to estimate the COD of rock using noisy DFOS data.展开更多
A series of laboratory pull-out tests was conducted to study the effects of temperature on the performance and behaviours of fully grouted rock bolt specimens cured within a specific temperature range,as well as for d...A series of laboratory pull-out tests was conducted to study the effects of temperature on the performance and behaviours of fully grouted rock bolt specimens cured within a specific temperature range,as well as for different durations.Each specimen consisted of a 20M rebar bolt at 1300 mm embedment length grouted inside a Schedule 80 steel pipe using Portland cement grout at a 0.4 water-to-cement ratio.Two temperatures(20℃and 45℃)were explored to investigate the effects of geothermally active temperature conditions on fully grouted rock bolts.Distributed fiber optic sensors were employed to provide continuous strain profiles along the entire embedment length to observe micro-mechanisms and monitor internal specimen temperature change during testing.The specimens cured at 45℃generally resulted in higher grout UCS(in certain cases 25%e50%higher)compared to those at 20℃;the ultimate capacity was not significantly impacted as the specimens'embedment length allowed full development of the rock bolt's capacity.The resulting strain profile trends showed generally higher strains experienced by the shorter(i.e.3-d)curing duration specimens under both curing temperatures compared to long-term curing.The 45℃specimens generally experienced lower strains and faster strain profile attenuation compared to specimens cured at 20℃.Understanding these effects and further analysis of FGRB specimen behaviours over time provide insights for mobilized and critical embedment lengths,capacity development,and support system stabilization.This paper highlights the results of this study and aims to bridge selected gaps in existing literature with a view to aid practitioners.展开更多
基金research was funded by Science and Technology Project of State Grid Corporation of China under grant number 5200-202319382A-2-3-XG.
文摘Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.
基金supported by the National Key Research and Development Program of China(Nos.2021YFA1201302 and 2021YFA1201300)the National Natural Science Foundation of China(Nos.52303033,52173029)+1 种基金Shanghai Sailing Program(No.23YF1400400)the Natural Science Foundation of Shanghai(No.21ZR1400500).
文摘Optogenetic has been widely applied in various pathogenesis investigations of neuropathic diseases since its accurate and targeted regulation of neuronal activity.However,due to the mismatch between the soft tissues and the optical waveguide,the long-term neural regulation within soft tissue(such as brain and spinal cord)by implantable optical fibers is a large challenge.Herein,we designed a modulus selfadaptive hydrogel optical fiber(MSHOF)with tunable mechanical properties(Young’modulus was tunable in the range of 0.32-10.56MPa)and low light attenuation(0.12-0.21 dB/cm,472nm laser light),which adapts to light transmission under soft tissues.These advantages of MSHOF can ensure the effectiveness of optogenetic stimulation meanwhile safeguarding the safety of the brain/materials interaction interface.In addition,this work provides more design possibilities of MSHOF for photogenetic stimuli and has significant application prospects in photomedical therapy.
基金supported by the National Key Research and Development Program of China (2019YFB1803905)the National Natural Science Foundation of China (No.62171022)+2 种基金Beijing Natural Science Foundation (4222009)Guangdong Basic and Applied Basic Research Foundation (2021B1515120057)the Scientific and Technological Innovation Foundation of Shunde Graduate School,USTB (No.BK19AF005)。
文摘In this paper,a double-effect DNN-based Digital Back-Propagation(DBP)scheme is proposed and studied to achieve the Integrated Communication and Sensing(ICS)ability,which can not only realize nonlinear damage mitigation but also monitor the optical power and dispersion profile over multi-span links.The link status information can be extracted by the characteristics of the learned optical fiber parameters without any other measuring instruments.The efficiency and feasibility of this method have been investigated in different fiber link conditions,including various launch power,transmission distance,and the location and the amount of the abnormal losses.A good monitoring performance can be obtained while the launch optical power is 2 dBm which does not affect the normal operation of the optical communication system and the step size of DBP is 20 km which can provide a better distance resolution.This scheme successfully detects the location of single or multiple optical attenuators in long-distance multi-span fiber links,including different abnormal losses of 2 dB,4 dB,and 6 dB in 360 km and serval combinations of abnormal losses of(1 dB,5 dB),(3 dB,3 dB),(5 dB,1 dB)in 360 km and 760 km.Meanwhile,the transfer relationship of the estimated coefficient values with different step sizes is further investigated to reduce the complexity of the fiber nonlinear damage compensation.These results provide an attractive approach for precisely sensing the optical fiber link status information and making correct strategies timely to ensure optical communication system operations.
文摘Soft polymer optical fiber(SPOF)has shown great potential in optical-based wearable and implantable biosensors due to its excellent mechanical properties and optical guiding characteristics.However,the multimodality characteristics of SPOF limit their integration with traditional fiber optic sensors.This article introduces for the first time a flexible fiber optic vibration sensor based on laser interference technology,which can be applied to vibration measurement under high stretch conditions.This sensor utilizes elastic optical fibers made of polydimethylsiloxane(PDMS)as sensing elements,combined with phase generating carrier technology,to achieve vibration measurement at 50−260 Hz within the stretch range of 0−42%.
文摘This paper examines the design and optimization of optical fibers for high-speed data transmission, emphasizing advancements that maximize efficiency in modern communication networks. Optical fibers, core components of global communication infrastructure, are capable of transmitting data over long distances with minimal loss through principles like total internal reflection. This study explores single-mode and multi-mode fiber designs, providing an overview of key parameters such as core diameter, refractive index profile, and numerical aperture. Mathematical modeling using Maxwell’s equations plays a central role in optimizing fiber performance, helping engineers mitigate challenges like attenuation and dispersion. The paper also discusses advanced techniques, including dense wavelength division multiplexing (DWDM), which enables terabit-per-second data rates. Case studies in practical applications, such as fiber-to-the-home (FTTH) networks and transoceanic cables, highlight the impact of optimized designs on network performance. Looking forward, innovations in photonic crystal fibers and hollow-core fibers are expected to drive further improvements, enabling ultra-high-speed data transmission. The paper concludes by underscoring the significance of continuous research and development to address challenges in optical fiber technology and support the increasing demands of global communication systems.
基金supported by the Scientific Research Program Funded by Shaanxi Provincial Education Department (No.15JK1573)the Postgraduate Innovation and Practice Ability Development Fund of Xi’an Shiyou University (No.YCS21211084)。
文摘We proposed a fiber optic high temperature sensor based on the Mach-Zehnder interference(MZI)structure,which is composed of two lengths of multi-mode fibers(MMFs),a length of few-mode fiber(FMF)and two sections of single-mode fibers(SMFs).Firstly,the two sections of MMFs were spliced with two sections of SMFs.Then,the MMFs were fused to two ends of FMF to form a symmetrically structured fiber-optic MZI structure.In this structure,the MMF served as the optical mode field coupling element,and the cladding and core of the FMF are the interference arm and the reference arm of the MZI structure,respectively.We investigated the sensor's response characteristics of the temperature and strain.The experimental results indicate that the sensor is sensitive to temperature variation,and the temperature response sensitivity is up to 61.4 pm/℃ in the range of 40-250℃,while the sensor has weak strain sensitivity,its strain sensitivity is only-0.72 pm/μe in the strain range of 0-1400μe.Moreover,the sensor has good stability and repeatability.In brief,the proposed fiber optic high temperature sensor has good properties,such as high sensitivity,compact structure,good stability and repeatability,which can be used for monitoring the temperature of submerged oil electric pump units under oil wells.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3402500)the National Natural Science Foundation of China(Grant No.12372129).
文摘Embedding optical fiber sensors into composite materials offers the advantage of real-time structural monitoring.However,there is an order-of-magnitude difference in diameter between optical fibers and reinforcing fibers,and the detailed mechanism of how embedded optical fibers affect the micromechanical behavior and damage failure processes within composite materials remains unclear.This paper presents a micromechanical simulation analysis of composite materials embedded with optical fibers.By constructing representative volume elements(RVEs)with randomly distributed reinforcing fibers,the optical fiber,the matrix,and the interface phase,the micromechanical behavior and damage evolution under transverse tensile and compressive loads are explored.The study finds that the presence of embedded optical fibers significantly influences the initiation and propagation of microscopic damage within the composites.Under transverse tension,the fiber-matrix interface cracks first,followed by plastic cracking in the matrix surrounding the fibers,forming micro-cracks.Eventually,these cracks connect with the debonded areas at the fiber-matrix interface to form a dominant crack that spans the entire model.Under transverse compression,plastic cracking first occurs in the resin surrounding the optical fibers,connecting with the interface debonding areas between the optical fibers and the matrix to form two parallel shear bands.Additionally,it is observed that the strength of the interface between the optical fiber and the matrix critically affects the simulation results.The simulated damage morphologies align closely with those observed using scanning electron microscopy(SEM).These findings offer theoretical insights that can inform the design and fabrication of smart composite materials with embedded optical fiber sensors for advanced structural health monitoring.
文摘As a laser passes through a scattering medium,the light interacts with the irregular reflections within the medium,resulting in light scattering and the formation of speckles.In this paper,an image sensor based on the combination of a coreless optical fiber and a digital camera is proposed for liquid refractive index sensing applications.The coreless fiber is used as a sensing unit,and the change in the speckle pattern is measured using the digital correlation method to detect the magnitude of the liquid's refractive index.The experimental results indicate that the laser image sensing technique is capable of effectively distinguishing liquid samples with refractive indices ranging from 1.332 8 to1.390 8,with a sensing sensitivity of-1.306 RIU-l.Moreover,the laser image sensing technique,with its advantages of high experimental reproducibility,simple system design,remote over-control,holds great research significance and potential application in laser communication and sensor integration.
基金supported in part by National Natural Science Foundation of China(No.62271080)in part by Fund of State Key Laboratory of IPOC(BUPT)(No.IPOC2022ZT06)in part by BUPT Excellent Ph.D Students Foundation(No.CX2022102).
文摘To achieve a low-complexity nonlinearity compensation(NLC)in high-symbol-rate(HSR)systems,we propose a modified weighted digital backpropagation(M-W-DBP)by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP.Based on this model,with the aid of neural network optimization,a learned version of M-W-DBP(M-W-LDBP)is also proposed and explored.Furthermore,enough technical details are revealed for the first time,including the principle of our proposed M-W-DBP and M-W-LDBP,the training process,and the complexity analysis of different DBPclass NLC algorithms.Evaluated numerically with QPSK,16QAM,and PS-64QAM modulation formats,1-step-per-span(1-StPS)M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation(CDC)in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems,respectively.Moreover,1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60%of the complexity.The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-WDBP is also discussed.This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.
基金Project supported by the National Natural Science Foundation of China(Grant No.32473216)Ningbo Youth Science and Technology Innovation Leading Talent Project(Grant No.2023QL004)。
文摘Vibration detection using sensors with both wide working frequency range,good sensitivity,and other good performances is a topic of great interest in fields such as inertial navigation,deep-sea fishing boat engines condition monitoring,seismic monitoring,attitude,and heading reference system,etc.This paper investigates two 6H-SIC MEMS diaphragms,one triangular and the other square,used in a fiber optic Fabry–Perot(FP)accelerometer in an experimental scenario.The triangular chip shows a wide working frequency range of 630 Hz–5300 Hz,a natural frequency of 44.3 k Hz,and a mechanical sensitivity of 0.154 nm/g.An optimal structure of the square chip used in a probe such as a fiber optic FP accelerometer also shows a wide working frequency range of 120 Hz–2300 Hz;a good sensitivity of 31.5 m V/g,a resonance frequency of7873 Hz,an accuracy of 0.96%F.S.,a frequency measurement error of 1.15%,and an excellent linearity of 0.9995.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.42225702 and 42077235).
文摘The rapid expansion of urban development has led to the extensive construction of civil infrastructures.However,these urban development zones frequently face potential geohazards,primarily due to the lack of detailed site investigations and long-term monitoring of subsurface geological conditions.Understanding the temporal and spatial distributions of underground multi-field information is vital for successful engineering construction and effective utilization of urban underground space.In this study,a fiber optic nerve system(FONS)was utilized in the Tianfu New Area,Sichuan Province,China,to obtain comprehensive subsurface multi-physical information,including geological deformation,temperature,and surface hydrological data.The FONS incorporates three advanced fiber optic sensing techniques,i.e.fiber Bragg grating(FBG),Brillouin optical time domain reflectometry(BOTDR),and Raman optical time domain reflectometry(ROTDR).Fully-and quasi-distributed strain/temperature sensing cables have been installed in nine monitoring boreholes,covering various geological features such as plains,terraces,and areas within active fault zones.The field monitoring results confirm the feasibility of employing FONS for geological investigations within urban development zones,offering a valuable reference for future applications of this cost-effective technology in geohazard mitigation.
基金the financial supports of the National Natural Science Foundation of China(No.52372200)a project supported by the State Key Laboratory of Mechanics and Control for Aerospace Structures(No.MCAS-S-0324G01)。
文摘Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.
基金Supported by the Scientific Research and Technology Development Project of Petrochina Southwest Oil and Gas Field Company(20230307-02)。
文摘The distributed fiber optic sensing system,known for its high sensitivity and wide-ranging measurement capabilities,has been widely used in monitoring underground gas pipelines.It primarily serves to perceive vibration signals induced by external events and to effectively provide early warnings of potential intrusion activities.Due to the complexity and diversity of external intrusion events,traditional deep learning methods can achieve event recognition with an average accuracy exceeding 90%.However,these methods rely on large-scale datasets,leading to significant time and labor costs during the data collection process.Additionally,traditional methods perform poorly when faced with the scarcity of low-frequency event samples,making it challenging to address these rare occurrences.To address this issue,this paper proposes a small-sample learning model based on triplet learning for intrusion event recognition.The model employs a 6-way 20-shot support set configuration and utilizes the KNN clustering algorithm to assess the model's performance.Experimental results indicate that the model achieves an average accuracy of 91.6%,further validating the superior performance of the triplet learning model in classifying external intrusion events.Compared to traditional methods,this approach not only effectively reduces the dependence on large-scale datasets but also better addresses the classification of low-frequency event samples,demonstrating significant application potential.
基金supports from China National Funds for Distinguished Young Scientists(62425505)National Natural Science Foundation of China(U22A20206)+1 种基金the China Postdoctoral Science Foundation(2023M731188)the Fundamental Research Funds for the Central Universities(2024BRA012).
文摘With the rapid development of lithium batteries,it’s of great significance to ensure the safe use of it.An ultrasound imaging system based on fiber optic ultrasound sensor has been developed to monitor the internal changes of lithium batteries.Based on Fabry-Perot interferometer(FPI)structure which is made of a glass plate and an optical fiber pigtail,the ultrasound imaging system possesses a high sensitivity of 558 mV/kPa at 500 kHz with the noise equivalent pressure(NEP)of only 63.5 mPa.For the frequency response,the ultrasound sensitivity is higher than 13.1 mV/kPa within the frequency range from 50 kHz to 1 MHz.Meanwhile,the battery imaging system based on the proposed sensor has a superior resolution as high as 0.5 mm.The performance of battery safety monitoring is verified,in which three commercial lithium-ion ferrous phosphate/graphite(LFP||Gr)batteries are imaged and the state of health(SOH)for different batteries is obtained.Besides,the wetting process of an anode-free lithium metal batteries(AFLMB)is clearly observed via the proposed system,in which the formation process of the pouch cell is analyzed and the gas-related"unwetting"condition is discovered,representing a significant advancement in battery health monitoring field.In the future,the commercial usage can be realized when sensor array and artificial intelligence technology are adopted.
基金supported by the National Natural Science Foundation of China(Grant Nos.U23A20375 and 62075151)the National Key Research and Development Program of China(Grant No.202103021223042).
文摘The principle of optical time-domain reflection localization limits the sensing spatial resolution of Raman distributed optical fiber sensing.We provide a solution for a Raman distributed optical fiber sensing system with kilometer-level sensing distance and submeter spatial resolution.Based on this,we propose a Raman distributed optical fiber sensing scheme based on chaotic pulse cluster demodulation.Chaotic pulse clusters are used as the probe signal,in preference to conventional pulsed or chaotic single-pulse lasers.Furthermore,the accurate positioning of the temperature variety region along the sensing fiber can be realized using chaotic pulse clusters.The proposed demodulation scheme can enhance the signal-to-noise ratio by improving the correlation between the chaotic reference and the chaotic Raman anti-Stokes scattering signals.The experiment achieved a sensing spatial resolution of 30 cm at a distributed temperature-sensing distance of∼6.0 km.Furthermore,we explored the influence of chaotic pulse width and detector bandwidth on the sensing spatial resolution.In addition,the theoretical experiments proved that the sensing spatial resolution in the proposed scheme was independent of the pulse width and sensing distance.
基金Fundamental Research Funds for the Central Universities(YWF-23-L-1225)National Natural Science Foundation of China(62201025)Chinese Aeronautical Establishment(2022Z037051001)。
文摘Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision FOGs.The conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under vibration.In this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put forward.Particularly,the loop gain is extracted out by adding a gain-monitoring wave.By demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation depth.The experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 Hz.This technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.
基金supported by the National Natural Science Foundation of China(62375013).
文摘As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields.
基金support from the Open Research Project Programme of the State Key Laboratory of Internet of Things for Smart City,University of Macao (Grant No.SKL-IoTSC (UM)-2021-2023/ORPF/A19/2022)the General Research Fund project from Research Grants Council of Hong Kong Special Administrative Region Government of China (Grant No.15214722)the Start-up Fund from The Hong Kong Polytechnic University (Grant No.BD88).
文摘Despite the extensive use of distributed fiber optic sensing(DFOS)in monitoring underground structures,its potential in detecting structural anomalies,such as cracks and cavities,is still not fully understood.To contribute to the identification of defects in underground structures,this study conducted a four-point bending test of a reinforced concrete(RC)beam and uniaxial loading tests of an RC specimen with local cavities.The experimental results revealed the disparity in DFOS strain spike profiles between these two structural anomalies.The effectiveness of DFOS in the quantification of crack opening displacement(COD)was also demonstrated,even in cases where perfect bonding was not achievable between the cable and structures.In addition,DFOS strain spikes observed in two diaphragm wall panels of a twin circular shaft were also reported.The most probable cause of those spikes was identified as the mechanical behavior associated with local concrete contamination.With the utilization of the strain profiles obtained from laboratory tests and field monitoring,three types of multi-classifiers,based on support vector machine(SVM),random forest(RF),and backpropagation neural network(BP),were employed to classify strain profiles,including crack-induced spikes,non-crack-induced spikes,and non-spike strain profiles.Among these classifiers,the SVM-based classifier exhibited superior performance in terms of accuracy and model robustness.This finding suggests that the SVM-based classifier holds promise as a potential solution for the automatic detection and classification of defects in underground structures during long-term monitoring.
基金The Young Scientists Fund of the National Natural Science Foundation of China(Grant No.42407250)the Fund from Research Centre for Resources Engineering towards Carbon Neutrality(RCRE)of The Hong Kong Polytechnic University(Grant No.No.1-BBEM)the Fund from Natural Science Foundation of Jiangsu Province(Grant No.BK20241211)。
文摘The commonly used method for estimating crack opening displacement(COD)is based on analytical models derived from strain transferring.However,when large background noise exists in distributed fiber optic sensing(DFOS)data,estimating COD through an analytical model is very difficult even if the DFOS data have been denoised.To address this challenge,this study proposes a machine learning(ML)-based methodology to complete rock's COD estimation from establishment of a dataset with one-to-one correspondence between strain sequence and COD to the optimization of ML models.The Bayesian optimization is used via the Hyperopt Python library to determine the appropriate hyper-parameters of four ML models.To ensure that the best hyper-parameters will not be missing,the configuration space in Hyperopt is specified by probability distribution.The four models are trained using DFOS data with minimal noise while being examined on datasets with different noise levels to test their anti-noise robustness.The proposed models are compared each other in terms of goodness of fit and mean squared error.The results show that the Bayesian optimization-based random forest is promising to estimate the COD of rock using noisy DFOS data.
基金funded by the Canadian Department of National Defence(DND),the RMC Green Team Military GeoWorks Lab,and the National Sciences and Engineering Research Council(NSERC)of Canada.
文摘A series of laboratory pull-out tests was conducted to study the effects of temperature on the performance and behaviours of fully grouted rock bolt specimens cured within a specific temperature range,as well as for different durations.Each specimen consisted of a 20M rebar bolt at 1300 mm embedment length grouted inside a Schedule 80 steel pipe using Portland cement grout at a 0.4 water-to-cement ratio.Two temperatures(20℃and 45℃)were explored to investigate the effects of geothermally active temperature conditions on fully grouted rock bolts.Distributed fiber optic sensors were employed to provide continuous strain profiles along the entire embedment length to observe micro-mechanisms and monitor internal specimen temperature change during testing.The specimens cured at 45℃generally resulted in higher grout UCS(in certain cases 25%e50%higher)compared to those at 20℃;the ultimate capacity was not significantly impacted as the specimens'embedment length allowed full development of the rock bolt's capacity.The resulting strain profile trends showed generally higher strains experienced by the shorter(i.e.3-d)curing duration specimens under both curing temperatures compared to long-term curing.The 45℃specimens generally experienced lower strains and faster strain profile attenuation compared to specimens cured at 20℃.Understanding these effects and further analysis of FGRB specimen behaviours over time provide insights for mobilized and critical embedment lengths,capacity development,and support system stabilization.This paper highlights the results of this study and aims to bridge selected gaps in existing literature with a view to aid practitioners.
