Estimation of Displacement and Extension due to Reverse Drag of Normal Faults: Forward Method

In the case of reverse drag of normal faulting, the displacement and horizontal extension are determined based on the established equations for the three mechanisms: rigid body, vertical shear and inclined shear. There are three sub-cases of basal detachment for the rigid body model: horizontal detachment, antithetic detachment and synthetic detachment. For the rigid body model, the established equations indicate that the total displacement on the synthetic base (Dt2) is the largest, that on the horizontal base (Dt1) is moderate, and that on the antithetic base (Dt3) is the smallest. On the other hand, the value of (Dt1) is larger than the displacement for the vertical shear (Dt4). The value of (Dt1) is larger than or less than the displacement for the inclined shear (Dt5) depending on the original fault dip δ0, bedding angle θ, and the angle of shear direction β. For all original parameters, the value of Dt5 is less than the value of Dt4. Also, by comparing three rotation mechanisms, we find that the inclined shear produces largest extension, the rigid body model with horizontal detachment produces the smallest extension, and the vertical shear model produces moderate extension.

Development of a 2D spatial displacement estimation method for turbulence velocimetry of the gas puff imaging system on EAST

A gas puff imaging(GPI)diagnostic has been developed and operated on EAST since 2012,and the time-delay estimation(TDE)method is used to derive the propagation velocity of fluctuations from the two-dimensional GPI data.However,with the TDE method it is difficult to analyze the data with fast transient events,such as edge-localized mode(ELM).Consequently,a method called the spatial displacement estimation(SDE)algorithm is developed to estimate the turbulence velocity with high temporal resolution.Based on the SDE algorithm,we make some improvements,including an adaptive median filter and super-resolution technology.After the development of the algorithm,a straight-line movement and a curved-line movement are used to test the accuracy of the algorithm,and the calculated speed agrees well with preset speed.This SDE algorithm is applied to the EAST GPI data analysis,and the derived propagation velocity of turbulence is consistent with that from the TDE method,but with much higher temporal resolution.

Direct scaling of residual displacements for bilinear and pinching oscillators

The estimation of residual displacements in a structure due to an anticipated earthquake event has increasingly become an important component of performance-based earthquake engineering because controlling these displacements plays an important role in ensuring cost-feasible or cost-effective repairs in a damaged structure after the event.An attempt is made in this study to obtain statistical estimates of constant-ductility residual displacement spectra for bilinear and pinching oscillators with 5%initial damping,directly in terms of easily available seismological,site,and model parameters.None of the available models for the bilinear and pinching oscillators are useful when design spectra for a seismic hazard at a site are not available.The statistical estimates of a residual displacement spectrum are proposed in terms of earthquake magnitude,epicentral distance,site geology parameter,and three model parameters for a given set of ductility demand and a hysteretic energy capacity coefficient in the case of bilinear and pinching models,as well as for a given set of pinching parameters for displacement and strength at the breakpoint in the case of pinching model alone.The proposed scaling model is applicable to horizontal ground motions in the western U.S.for earthquake magnitudes less than 7 or epicentral distances greater than 20 km.

A technique for enhancing tight oil recovery by multi-field reconstruction and combined displacement and imbibition

A seepage-geomechanical coupled embedded fracture flow model has been established for multi-field coupled simulation in tight oil reservoirs,revealing the patterns of change in pressure field,seepage field,and stress field after long-term water injection in tight oil reservoirs.Based on this,a technique for enhanced oil recovery(EOR)combining multi-field reconstruction and combination of displacement and imbibition in tight oil reservoirs has been proposed.The study shows that after long-term water flooding for tight oil development,the pressure diffusion range is limited,making it difficult to establish an effective displacement system.The variation in geostress exhibits diversity,with the change in horizontal minimum principal stress being greater than that in horizontal maximum principal stress,and the variation around the injection wells being more significant than that around the production wells.The deflection of geostress direction around injection wells is also large.The technology for EOR through multi-field reconstruction and combination of displacement and imbibition employs water injection wells converted to production and large-scale fracturing techniques to restructure the artificial fracture network system.Through a full lifecycle energy replenishment method of pre-fracturing energy supplementation,energy increase during fracturing,well soaking for energy storage,and combination of displacement and imbibition,it effectively addresses the issue of easy channeling of the injection medium and difficult energy replenishment after large-scale fracturing.By intensifying the imbibition effect through the coordination of multiple wells,it reconstructs the combined system of displacement and imbibition under a complex fracture network,transitioning from avoiding fractures to utilizing them,thereby improving microscopic sweep and oil displacement efficiencies.Field application in Block Yuan 284 of the Huaqing Oilfield in the Ordos Basin has demonstrated that this technology increases the recovery factor by 12 percentage points,enabling large scale and efficient development of tight oil.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

Effect of Articular Cavity Injection Combined with Bite Splint Treatment on Anterior Disc Displacement Without Reduction

Objective:To observe the clinical effect of articular cavity injection combined with bite splint therapy for the treatment of anterior disc displacement without reduction(ADDWoR).Methods:The research subjects for this study were 30 patients with ADDWoR treated in the temporomandibular joint specialist outpatient clinic from November 2018 to November 2019,with a disease duration of 1 to 6 months.The treatment group was treated with an articular cavity injection of sodium hyaluronate+bite splint.The control group was treated with a simple articular cavity injection of sodium hyaluronate.The two groups were followed up once every 2 weeks to evaluate the treatment effect and observe the clinical efficacy of the two groups.Statistical analysis was carried out using SPSS 24.0.t-test and general linear regression analysis were carried out to compare the data of both groups,andχ^(2)-test and binary logistic regression analysis were performed for pain index comparison.Results:There was no significant difference in terms of the efficacy of the treatment received by both groups.The mouth opening and joint pain of patients in both groups were significantly improved after treatment(P<0.001).Conclusion:Articular cavity injection of sodium hyaluronate and occlusal splint therapy are both effective and safe methods for treating ADDWoR.

Analytical solutions for the restraint effect of isolation piles against tunneling-induced vertical ground displacements

This paper presents a simplified elastic continuum method for calculating the restraint effect of isolation piles on tunneling-induced vertical ground displacement,which can consider not only the relative sliding of the pile‒soil interface but also the pile rowesoil interaction.The proposed method is verified by comparisons with existing theoretical methods,including the boundary element method and the elastic foundation method.The results reveal the restraining mechanism of the isolation piles on vertical ground displacements due to tunneling,i.e.the positive and negative restraint effects exerted by the isolation piles jointly drive the ground vertical displacement along the depth direction from the original tunneling-induced nonlinear variation situation to a relatively uniform situation.The results also indicate that the stiffness of the pile‒soil interface,including the pile shaft‒surrounding soil interface and pile tip-supporting soil interface,describes the strength of the pile‒soil interaction.The pile rows can confine the vertical ground displacement caused by the tunnel excavation to the inner side of the isolation piles and effectively prevent the vertical ground displacement from expanding further toward the outer side of the isolation piles.

Landslide displacement prediction based on the ICEEMDAN,ApEn and the CNN-LSTM models

Landslide deformation is affected by its geological conditions and many environmental factors.So it has the characteristics of dynamic,nonlinear and unstable,which makes the prediction of landslide displacement difficult.In view of the above problems,this paper proposes a dynamic prediction model of landslide displacement based on the improvement of complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN),approximate entropy(ApEn)and convolution long short-term memory(CNN-LSTM)neural network.Firstly,ICEEMDAN and Ap En are used to decompose the cumulative displacements into trend,periodic and random displacements.Then,the least square quintic polynomial function is used to fit the displacement of trend term,and the CNN-LSTM is used to predict the displacement of periodic term and random term.Finally,the displacement prediction results of trend term,periodic term and random term are superimposed to obtain the cumulative displacement prediction value.The proposed model has been verified in Bazimen landslide in the Three Gorges Reservoir area of China.The experimental results show that the model proposed in this paper can more effectively predict the displacement changes of landslides.As compared with long short-term memory(LSTM)neural network,gated recurrent unit(GRU)network model and back propagation(BP)neural network,CNN-LSTM neural network had higher prediction accuracy in predicting the periodic displacement,with the mean absolute percentage error(MAPE)reduced by 3.621%,6.893% and 15.886% respectively,and the root mean square error(RMSE)reduced by 3.834 mm,3.945 mm and 7.422mm respectively.Conclusively,this model not only has high prediction accuracy but also is more stable,which can provide a new insight for practical landslide prevention and control engineering.

Analysis of displacement damage effects on the charge-coupled device induced by neutrons at Back-n in the China Spallation Neutron Source

Displacement damage effects on the charge-coupled device(CCD)induced by neutrons at the back-streaming white neutron source(Back-n)in the China Spallation Neutron Source(CSNS)are analyzed according to an online irradiation experiment.The hot pixels,random telegraph signal(RTS),mean dark signal,dark current and dark signal non-uniformity(DSNU)induced by Back-n are presented.The dark current is calculated according to the mean dark signal at various integration times.The single-particle displacement damage and transient response are also observed based on the online measurement data.The trends of hot pixels,mean dark signal,DSNU and RTS degradation are related to the integration time and irradiation fluence.The mean dark signal,dark current and DSNU2 are nearly linear with neutron irradiation fluence when nearly all the pixels do not reach saturation.In addition,the mechanisms of the displacement damage effects on the CCD are demonstrated by combining the experimental results and technology computer-aided design(TCAD)simulation.Radiation-induced traps in the space charge region of the CCD will act as generation/recombination centers of electron-hole pairs,leading to an increase in the dark signal.

Analyis on the indirect tension displacement and strain field of asphalt mixture based on ABAQUS and DICM

In order to study the damage mechanism of asphalt mixture,it is important to obtain the distribution of displacement and strain of its sample in the indirect tension mode.As a result,the digital image correlation method (DICM) was used to evaluate the displacement field and strain field of asphalt mixture.The results showed that the displacement fields under DICM and ABAQUS are similarly;the strain fields are different due to the different modulus of mastic and aggregate;and DICM is an practical method to study the indirect tension displacement and stain.

Assessment of strain effect of strong-motion (focus) zones of earthquakes on earth＇s surface displacement

Strain effect of focal zones on fore-seismic displacements of earth's surface is studied in the paper for real conditions of focus zones of the earthquakes.The width of the interval of maximum displacements is determined by the conditions of potential focus of tectonic earthquake.The solution of elastic problem for half-space with soft inclusion is used.Calculations are conducted also by empirical formulas,obtained for similar stress states.Possible radius of the zone of maximum revelation of strain anomaly is determined on the basis of the growth of rupture scale and change in heterogeneity volume.It is shown that obtained expression covers a wider range of magnitude variations with consideration of the interval of scale change in upcoming rupture-forming zone.In the example of Tashkent(1966) and Gazli(1984) strong ground motions,an analysis of possible strains occurrence on the Earth's surface was conducted.

Inelastic displacement ratio of low-to mid-rise BRBFs designed under variable levels of seismicity

Buckling-restrained braces(BRBs)have shown their capability to provide building structures with stiffness,strength,and ductility.Estimating the seismic drifts of buckling-restrained braced frames(BRBFs)is an important design step to control structural and non-structural damage.In current practice of seismic design,the estimation of seismic drifts of BRBFs is performed by using empirical calculations that are independent upon either the type of the structural system or the design level of seismicity.In these empirical calculations,the seismic drifts are estimated by amplifying the reduced elastic drifts obtained under design lateral loading with a displacement amplification factor(DAF).The value of DAF is considered equal to the product of the response modification factor R and the inelastic displacement ratioρ.The goal of the current research is to assess the value ofρfor low-to mid-rise BRBFs designed under low and high levels of seismicity.This goal has been achieved by conducting a series of elastic and inelastic time-history analyses pertaining to an ensemble of earthquake records on 3-,6-and 9-story BRBFs.The results indicate that theρ-ratio increases with an increase in design seismic intensity and an increase in experienced inelasticity.The range ofρfor low seismicity designs ranges from 0.63 to 0.9,while for high seismicity designs this range stretches from 0.83 to 1.29.It has been found that the consideration of a generalρ-ratio of 1.0 is a reasonable estimation for the design of the BRBFs considered in this study.

Improved calibration method for displacement transformation coefficient in optical and visual measurements

Optical and visual measurement technology is used widely in fields that involve geometric measurements,and among such technology are laser and vision-based displacement measuring modules(LVDMMs).The displacement transformation coefficient(DTC)of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process,and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view(FFOV).To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands,a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV.First,an image coordinate system,a pixel measurement coordinate system,and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM.In addition,marker spots in the FFOV are selected,and the DTCs at the marker spots are obtained from calibration experiments.Also,a fitting method based on locally weighted scatterplot smoothing(LOWESS)is selected,and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots.Finally,the calibrated distribution functions of the DTCs are applied to the LVDMM,and experiments conducted to verify the displacement measurement accuracies are reported.The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than±15μm and±19μm,respectively,and that for oblique displacement is better than±24μm.Compared with the traditional calibration method,the displacement measurement error in the FFOV is now 90%smaller.This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV,and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.

Anomaly detection on displacement rates and deformation pattern features using tree-based algorithm in Japan and Indonesia

Research on strain anomalies and large earthquakes based on temporal and spatial crustal activities has been rapidly growing due to data availability, especially in Japan and Indonesia. However, many research works used local-scale case studies that focused on a specific earthquake characteristic using knowledgedriven techniques, such as crustal deformation analysis. In this study, a data-driven-based analysis is used to detect anomalies using displacement rates and deformation pattern features extracted from daily global navigation satellite system(GNSS) data using a machine learning algorithm. The GNSS data with188 and 1181 continuously operating reference stations from Indonesia and Japan, respectively, are used to identify the anomaly of recent major earthquakes in the last two decades. Feature displacement rates and deformation patterns are processed in several window times with 2560 experiment scenarios to produce the best detection using tree-based algorithms. Tree-based algorithms with a single estimator(decision tree), ensemble bagging(bagging, random forest and Extra Trees), and ensemble boosting(AdaBoost, gradient boosting, LGBM, and XGB) are applied in the study. The experiment test using realtime scenario GNSSdailydatareveals high F1-scores and accuracy for anomaly detection using slope windowing 365 and 730 days of 91-day displacement rates and then 7-day deformation pattern features in tree-based algorithms. The results show the potential for medium-term anomaly detection using GNSS data without the need for multiple vulnerability assessments.

Ensemble Model for Spindle Thermal Displacement Prediction of Machine Tools

Numerous factors affect the increased temperature of a machine tool, including prolonged and high-intensity usage,tool-workpiece interaction, mechanical friction, and elevated ambient temperatures, among others. Consequently,spindle thermal displacement occurs, and machining precision suffers. To prevent the errors caused by thetemperature rise of the Spindle fromaffecting the accuracy during themachining process, typically, the factory willwarm up themachine before themanufacturing process.However, if there is noway to understand the tool spindle’sthermal deformation, the machining quality will be greatly affected. In order to solve the above problem, thisstudy aims to predict the thermal displacement of the machine tool by using intelligent algorithms. In the practicalapplication, only a few temperature sensors are used to input the information into the prediction model for realtimethermal displacement prediction. This approach has greatly improved the quality of tool processing.However,each algorithm has different performances in different environments. In this study, an ensemble model is used tointegrate Long Short-TermMemory (LSTM) with Support VectorMachine (SVM). The experimental results showthat the prediction performance of LSTM-SVM is higher than that of other machine learning algorithms.

Robust vision-based displacement measurement and acceleration estimation using RANSAC and Kalman filter

Computer vision(CV)-based techniques have been widely used in the field of structural health monitoring(SHM)owing to ease of installation and cost-effectiveness for displacement measurement.This paper introduces computer vision based method for robust displacement measurement under occlusion by incorporating random sample consensus(RANSAC).The proposed method uses the Kanade-Lucas-Tomasi(KLT)tracker to extract feature points for tracking,and these feature points are filtered through RANSAC to remove points that are noisy or occluded.With the filtered feature points,the proposed method incorporates Kalman filter to estimate acceleration from velocity and displacement extracted by the KLT.For validation,numerical simulation and experimental validation are conducted.In the simulation,performance of the proposed RANSAC filtering was validated to extract correct displacement out of group of displacements that includes dummy displacement with noise or bias.In the experiment,both RANSAC filtering and acceleration measurement were validated by partially occluding the target for tracking attached on the structure.The results demonstrated that the proposed method successfully measures displacement and estimates acceleration as compared to a reference displacement sensor and accelerometer,even under occluded conditions.

Visualization of real-time displacement time history superimposed with dynamic experiments using wireless smart sensors and augmented reality

Wireless smart sensors(WSS)process field data and inform inspectors about the infrastructure health and safety.In bridge engineering,inspectors need reliable data about changes in displacements under loads to make correct decisions about repairs and replacements.Access to displacement information in the field and in real-time remains a challenge as inspectors do not see the data in real time.Displacement data from WSS in the field undergoes additional processing and is seen at a different location.If inspectors were able to see structural displacements in real-time at the locations of interest,they could conduct additional observations,creating a new,information-based,decision-making reality in the field.This paper develops a new,human-centered interface that provides inspectors with real-time access to actionable structural data during inspection and monitoring enhanced by augmented reality(AR).It summarizes and evaluates the development and validation of the new human-infrastructure interface in laboratory experiments.The experiments demonstrate that the interface that processes all calculations in the AR device accurately estimates dynamic displacements in comparison with the laser.Using this new AR interface tool,inspectors can observe and compare displacement data,share it across space and time,visualize displacements in time history,and understand structural deflection more accurately through a displacement time history visualization.

Displacement fields denoising and strains extraction by finite element method

Optical full-field measurement methods are now widely applied in various domains. In general,the displacement fields can be directly obtained from the measurement,however in mechanical analysis strain fields are preferred.To extract strain fields from noisy displacement fields is always a challenging topic.In this study,a finite element method for smoothing displacement fields and calculating strain fields is proposed.An experimental test case on a holed aluminum specimen under tension is applied to vali...

Molecular insight into the oil displacement mechanism of CO_(2) flooding in the nanopores of shale oil reservoir

With the increasing demand for petroleum,shale oil with considerable reserves has become an important part of global oil resources.The shale oil reservoir has a large number of nanopores and a complicated mineral composition,and the effect of nanopore confinement and pore type usually makes the effective development of shale oil challenging.For a shale oil reservoir,CO_(2) flooding can effectively reduce the oil viscosity and improve the reservoir properties,which can thus improve the recovery performance.In this study,the method of non-equilibrium molecular dynamics(NEMD)simulation is used to simulate the CO_(2) flooding process in the nanoscale pores of shale oil reservoir.The performance difference between the organic kerogen slit nanopore and four types of inorganic nanopores is discussed.Thus,the effects of nanopore type and displacement velocity on the nanoscale displacement behavior of CO_(2) are analyzed.Results indicate that the CO_(2) flooding process of different inorganic pores is different.In comparison,the displacement efficiency of light oil components is higher,and the transport distance is longer.The intermolecular interaction can significantly affect the CO_(2) displacement behavior in nanopores.The CO_(2) displacement efficiency is shown as montmorillonite,feldspar>quartz>calcite>kerogen.On the other hand,it is found that a lower displacement velocity can benefit the miscibility process between alkane and CO_(2),which is conducive to the overall displacement process of CO_(2).The displacement efficiency can significantly decrease with the increase in displacement velocity.But once the displacement velocity is very high,the strong driving force can promote the alkane to move forward,and the displacement efficiency will recover slightly.This study further reveals the microscopic oil displacement mechanism of CO_(2) in shale nanopores,which is of great significance for the effective development of shale oil reservoirs by using the method of CO_(2) injection.

Inverse design and realization of an optical cavity-based displacement transducer with arbitrary responses

Optical cavity has long been critical for a variety of applications ranging from precise measurement to spectral analysis.A number of theories and methods have been successful in describing the optical response of a stratified optical cavity,while the inverse problem,especially the inverse design of a displacement sensitive cavity,remains a significant challenge due to the cost of computation and comprehensive performance requirements.This paper reports a novel inverse design methodology combining the characteristic matrix method,mixed-discrete variables optimization algorithm,and Monte Carlo method-based tolerance analysis.The material characteristics are indexed to enable the mixed-discrete variables optimization,which yields considerable speed and efficiency improvements.This method allows arbitrary response adjustment with technical feasibility and gives a glimpse into the analytical characterization of the optical response.Two entirely different light-displacement responses,including an asymmetric sawtooth-like response and a highly symmetric response,are dug out and experimentally achieved,which fully confirms the validity of the method.The compact Fabry-Perot cavities have a good balance between performance and feasibility,making them promising candidates for displacement transducers.More importantly,the proposed inverse design paves the way for a universal design of optical cavities,or even nanophotonic devices.