Cumulative Displacement Research Articles

Forecasting of landslide displacements using a chaos theory based wavelet analysis-Volterra filter model

Landslide displacement time series can directly reflects landslide deformation and stability characteristics. Hence, forecasting of the non-linear and non-stationary displacement time series is necessary and significant for early warning of landslide failure. Traditionally, conventional machine learning methods are adopted as forecasting models, these forecasting models mainly determine the input and output variables experientially and does not address the non-stationary characteristics of displacement time series. However, it is difficult for these conventional machine learning methods to obtain appropriate input-output variables, to determine appropriate model parameters and to acquire satisfied prediction performance. To deal with these drawbacks, this study proposes the wavelet analysis (WA) to decompose the displacement time series into low- and high-frequency components to address the non-stationary characteristics; then proposes thee chaos theory to obtain appropriate input-output variables of forecasting models, and finally proposes Volterra filter model to construct the forecasting model. The GPS monitoring cumulative displacement time series, recorded on the Shuping and Baijiabao landslides, distance measuring equipment monitoring displacements on the Xintan landslide in Three Gorges Reservoir area of China, are used as test data of the proposed chaotic WA-Volterra model. The chaotic WA-support vector machine (SVM) model and single chaotic Volterra model without WA method, are used as comparisons. The results show that there are chaos characteristics in the GPS monitoring displacement time series, the non-stationary characteristics of landslide displacements are captured well by the WA method, and the model input-output variables are selected suitably using chaos theory. Furthermore, the chaotic WA-Volterra model has higher prediction accuracy than the chaotic WA-SVM and single chaotic Volterra models.

Design and experimental performance of an inertial giant magnetostrictive linear actuator

In order to meet the requirements of large stroke and high precision linear displacement, an inertial impact type giant magnetostrictive linear actuator was designed according to the principle of the inchworm motion. The stepwise cumulative displacement motion can be realized by applying a sawtooth wave signal to the excitation coil. The superimposed flexible hinge effectively improves the force of the system. The equivalent stiffness is calculated by simplifying the flexible hinge into a cantilever beam, and the strength of the flexible hinge is checked, the modal analysis is carried out. The displacement model of inertial actuator is established according to voltage law, magnetoresistance theory, linear piezomagnetic model and dynamic theory. The experimental platform is built and the prototype is designed for test. The experimental and simulation results show that the operating voltage range of the inertial actuator is 3 V–9 V, the maximum operating frequency is 60 Hz, the minimum and maximum single step displacement are 2.41 μm and 7.49 μm, and the maximum speed is 449.4 μm/s. The displacement output is stable, the maximum relative error of the single step displacement is 3.97 %. In the working voltage range, the maximum error between the simulated and experimental values is 4.84 %. And the maximum error between the simulated and experimental values is 2.96 % in the working frequency range. So the design scheme and the displacement model have certain reference significance for the application of large stroke actuator.

Surface Deformation from Sentinel-1A InSAR: Relation to Seasonal Groundwater Extraction and Rainfall in Central Taiwan

Extracting groundwater for agricultural, aquacultural, and industrial use in central Taiwan has caused large-scale land subsidence that poses a threat to the operation of the Taiwan High Speed Railway near Yunlin County. We detected Yunlin subsidence using the Sentinel-1A Synthetic Aperture Radar (SAR) by the Small BAseline Subset (SBAS) method from April 2016 to April 2017. We calibrated the initial InSAR-derived displacement rates using GPS measurements and reduced the velocity difference between the two sensors from 15.0 to 8.5 mm/a. In Yunlin’s severe subsidence regions, cumulative displacements from InSAR and GPS showed that the dry-season subsidence contributed 60%–74% of the annual subsidence. The InSAR-derived vertical velocities matched the velocities from leveling to better than 10 mm/a. In regions with few leveling measurements, InSAR increased the spatial resolution of the vertical velocity field and identified two previously unknown subsidence spots over an industrial zone and steel factory. Annual significant subsidence areas (subsidence rate > 30 mm/a) from leveling from 2011 to 2017 increased with the declining dry-season rainfalls, suggesting that the dry-season rainfall was the deciding factor for land subsidence. A severe drought in 2015 (an El Niño year) dramatically increased the significant subsidence area to 659 km2. Both InSAR and leveling detected similarly significant subsidence areas in 2017, showing that InSAR was an effective technique for assessing whether a subsidence mitigation measure worked. The newly opened Hushan Reservoir can supply surface water during dry seasons and droughts to counter rain shortage and can thereby potentially reduce land subsidence caused by groundwater extraction.

Landslide displacement prediction based on variational mode decomposition and WA-GWO-BP model

Many models have been widely used in landslide displacement prediction. However, few studies have proposed quantitative prediction formulas. Thus, the variational mode decomposition (VMD) theory was applied to decompose the “step-like” displacement of landslides into trend displacement, periodic displacement, and random displacement. Then, a novel prediction model based on wavelet analysis (WA) and a back-propagation neural network (BPNN) optimized by the grey wolf optimizer (GWO) algorithm was proposed (the GWO-BP model) to obtain a prediction formula. In this model, a polynomial function was first used to predict the trend displacement. All the hidden periods of periodic displacement were calculated using the WA method, and a trigonometric function was applied to predict the periodic displacement. In addition, based on an analysis of the grey relational degree (GRD), the main triggering factors, which can affect the random displacement, were determined. Then, the mathematical connection between random displacement and triggering factors was obtained with the GWO-BP model. Finally, all the predicted values were superposed to achieve the prediction cumulative displacement based on the time series model. The Outang landslide in the Three Gorges Reservoir area, China, was taken as an example, and the displacement data of monitoring sites MJ01 and MJ02 from December 2010 to December 2016 were selected for analysis. The results indicated that the root mean square errors (RMSE) between the real displacement values and the prediction values obtained using the formula were 14.79 mm and 12.59 mm, respectively. The correlation coefficient R values were 0.99 and 0.93, respectively. This model can be used to obtain the landslide displacement formula and provide a solid basis for developing early warning systems for landslides.

The Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Time Series

AbstractAutomated systems for detecting deformation in satellite interferometric synthetic aperture radar (InSAR) imagery could be used to develop a global monitoring system for volcanic and urban environments. Here, we explore the limits of a convolutional neural networks for detecting slow, sustained deformations in wrapped interferograms. Using synthetic data, we estimate a detection threshold of 3.9 cm for deformation signals alone and 6.3 cm when atmospheric artifacts are considered. Overwrapping reduces this to 1.8 and 5.2 cm, respectively, as more fringes are generated without altering signal to noise ratio. We test the approach on time series of cumulative deformation from Campi Flegrei and Dallol, where overwrapping improves classification performance by up to 15%. We propose a mean‐filtering method for combining results of different wrap parameters to flag deformation. At Campi Flegrei, deformation of 8.5 cm/year was detected after 60 days and at Dallol, deformation of 3.5 cm/year was detected after 310 days. This corresponds to cumulative displacements of 3 and 4 cm consistent with estimates based on synthetic data.

Measurements error propagation and its sensitivity analysis in the aero-engine multistage rotor assembling process.

The purpose of this paper is to research the measurements error propagation principle about the measurement-assembly equipment of aero engine multistage rotor, besides analyze the effect of guide linear motion and turntable rotational motion on the final alignment error. Furthermore, we can improve the measurement and assembly accuracy of the aero engine multistage rotor. In this paper, a novel error analysis method related to measurement-assembly equipment was proposed. First, the topology of the measuring equipment was established based on the multibody system theory, the error propagation path was constructed by using the low order body sorting method. Second, the error transfer model of the linear motion and the rotational motion were established by using the homogeneous coordinate transformation matrix, and the total measurement terminal errors introduced by the equipment were calculated. Finally, through numerical simulation, the magnitude of the measurement terminal offset error was obtained, sensitivity analysis was performed to calculate key error sources. Measurement accuracy not only depended on the accuracy of the sensor but also closely related to the accuracy of the measurement-assembly equipment. Through the simulation verification, when the linearity error is 0.1 μm and the angular error is 0.1″, the final cumulative offset displacement error is about -0.1002 μm to -0.0998 μm with a probability of 97%. Different type errors have different effects on the results. We can give a conclusion that linear guide alignment error and verticality error are the primary error sources, and the angle error of the turntable need to be improved.

Lateral spreading of ports in the 2014 Cephalonia, Greece, earthquakes

A case history is presented of lateral spreading in two reclaimed port areas of the Cephalonia island, Greece, in the 2014 earthquake doublet (Mw 6.1 & 6). Lateral ground displacements along 24 transects perpendicular to the quay walls in the two port areas were directly measured by ground surveys. Liquefaction of gravel-size fills was observed throughout the ports and was more pronounced in Lixouri port where ground motions were higher. The maximum cumulative horizontal ground displacements ranged from 3 cm to 152 cm, depending on the transect location and height of free face, whereas the inland extent of lateral ground movement ranged from 10 m to 90 m. Lateral movement of the quay walls in Argostoli Port was lower compared to Lixouri Port. Strong motion recordings in the two port areas as well as pertinent seismotectonic data are also presented along with the available geotechnical data compiled by integrating information from exploratory borings, trial pits, site geology and eye-witness accounts of the reclamation history of the areas. Average cumulative lateral displacements for groups of transects, characterized by similar height of quay wall and field conditions were derived and compared to lateral spreading predictions using an empirical relationship for free field conditions. It was found that the magnitude of lateral spreading behind the gravity-type quay walls was significantly lower compared to empirical predictions based on the assumption of free field conditions. The reduction of lateral ground movement depends on the height of quay wall and may even be an order of magnitude lower for wall heights of 6 m or greater. The findings of this study contribute in assessing quay wall movement in port areas especially when liquefaction has occurred behind the wall.

Real-time imaging of brain displacement during FUS neuromodulation in rodents in vivo

Focused ultrasound (FUS) is capable of modulating the central and peripheral nervous system. Temperature increase, cavitation, and acoustic radiation force have been proposed as potential mechanisms. Thus, tissue displacement imaging during FUS modulation is critical to understanding its physical mechanism. A cranial window was formed to perform imaging during FUS neuromodulation in C57BL/6 mice. FUS sonications were performed with a 4 MHz single-element transducer with a focal volume 0.2 × 0.9 mm (Sonic Concepts, WA), an applied tone burst of 0.5 ms and peak positive pressures varying from 1.9 to 6.7 MPa. Real-time channel data using plane wave sequences were acquired with an 18 MHz linear array (Vermon, France) and axial displacements throughout the entire brain were estimated using 1D cross-correlation (9λ window, 99% overlap) at 1 kHz frame rate. Downward displacements were only detected during FUS within the focal region. During modulation, the cumulative displacement ranged from 0.021 ± 0.017 μm (n = 3) at 3.1 MPa to 0.24 ± 0.004 μm at 6.7 MPa (n = 3). Displacement decreased post-FUS and returned to null within 1–2 ms. Unlike in a preliminary phantom study, no shear waves were detected. Real-time displacement imaging could thus provide effective targeting and monitoring as well as unveil the mechanism during FUS modulation.Focused ultrasound (FUS) is capable of modulating the central and peripheral nervous system. Temperature increase, cavitation, and acoustic radiation force have been proposed as potential mechanisms. Thus, tissue displacement imaging during FUS modulation is critical to understanding its physical mechanism. A cranial window was formed to perform imaging during FUS neuromodulation in C57BL/6 mice. FUS sonications were performed with a 4 MHz single-element transducer with a focal volume 0.2 × 0.9 mm (Sonic Concepts, WA), an applied tone burst of 0.5 ms and peak positive pressures varying from 1.9 to 6.7 MPa. Real-time channel data using plane wave sequences were acquired with an 18 MHz linear array (Vermon, France) and axial displacements throughout the entire brain were estimated using 1D cross-correlation (9λ window, 99% overlap) at 1 kHz frame rate. Downward displacements were only detected during FUS within the focal region. During modulation, the cumulative displacement ranged from 0.021 ± 0.017 μm (n ...

Displacement characteristics and prediction of Baishuihe landslide in the Three Gorges Reservoir

In order to reach the designated final water level of 175 m, there were three impoundment stages in the Three Gorges Reservoir, with water levels of 135 m, 156 m and 175 m. Baishuihe landslide in the Reservoir was chosen to analyze its displacement characteristics and displacement variability at the different stages. Based on monitoring data, the landslide displacement was mainly influenced by rainfall and drawdown of the reservoir water level. However, the magnitude of the rise and drawdown of the water level after the reservoir water level reached 175 m did not accelerate landslide displacement. The prediction of landslide displacement for active landslides is very important for landslide risk management. The time series of cumulative displacement was divided into a trend term and a periodic term using the Hodrick-Prescott (HP) filter method. The polynomial model was used to predict the trend term. The extreme learning machine (ELM) and least squares support vector machine (LS-SVM) were chosen to predict the periodic term. In the prediction model for the periodic term, input variables based on the effects of rainfall and reservoir water level in landslide displacement were selected using grey relational analysis. Based on the results, the prediction precision of ELM is better than that of LS-SVM for predicting landslide displacement. The method for predicting landslide displacement could be applied by relevant authorities in making landslide emergency plans in the future.

Using a kernel extreme learning machine with grey wolf optimization to predict the displacement of step-like landslide

Landslide displacement prediction is an important aspect of landslide hazard research. In this paper we assess the characteristics of landslide deformation in the Three Gorges Reservoir Area of China and propose and apply a step-like displacement prediction model based on a kernel extreme learning machine with grey wolf optimization (GWO-KELM) to the Baishuihe landslide. In this model, the cumulative displacement is first decomposed into trend displacement and periodic displacement by time series. The trend displacement is then predicted by a cubic polynomial model, and the periodic displacement is predicted by the proposed model after the displacement data have been statistically analyzed. A hybrid model is then established for the prediction of landslide displacement. We then compare the performance of this hybrid model with that of the extreme learning machine with GWO (GWO-ELM), support vector machine with GWO (GWO-SVM) and extreme learning machine (ELM) models. The results show that the proposed hybrid model outperforms the other models and that the GWO-KELM model achieves excellent performance in predicting landslide displacement with a step-like behavior.

PREDICTION OF DEEP DISPLACEMENT OF MAJIAGOU LANDSLIDE BASED ON OPTICAL FIBER MONITORING AND PSO-SVM MODEL

There are two main factors that influence the accuracy of landslide displacement prediction. One is the reliability of the prediction model and the other is the quality of field monitoring data. Currently, conventional landslide monitoring technology and evaluation methods have many limitations and shortcomings. In this paper, we propose a new evaluation methodology of the combination of fiber-optic monitoring technology, monitoring data and PSO-SVM prediction model. We use it to predict the deep displacement of Majiagou No. 1 landslide in the Three Gorges Reservoir. Firstly, by analyzing 320 fiber-optics monitoring data of landslide deep displacement, we decompose accumulative displacement into trend and fluctuant components based on the time series method. Then, the trend displacement is predicted with the fitting method. The fluctuant displacement is predicted with the PSO-SVM model. Lastly, the prediction of cumulative displacement is computed with the predicted periodic and fluctuant displacement values. Research results show that the root mean square error is 0.51mm and an average absolute percentage error is 0.37mm, which demonstrate this model has a preferable prediction effect. The predicted total displacement show great consistency with the measured total displacement, with the RSME of 0.54mm and the correlation coefficient of 0.98, respectively. This method can be used to make short-term predictions of landslide deep displacement.

Quantifying Vertical Deformation in the Tigris–Euphrates Basin Due to the Groundwater Abstraction: Insights from GRACE and Sentinel-1 Satellites

This study explores the occurrences of land subsidence in response to dropping groundwater levels in the central part of the Tigris–Euphrates basin. We estimated the groundwater depletion related to human and climate drivers between 2003 and 2017 based on estimates from the Gravity Recovery and Climate Experiment (GRACE) and two global hydrological models (NOAH-3.3 and WGHM-2.2d). The cumulative displacement was calculated using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) for 96 interferograms, which were generated by 31 images acquired by the Sentinel-1 satellite. The results show that the basin is experiencing a decline in groundwater storage at a rate of −7.56 km3/year with a total loss of 106.81 km3. This depletion rate has led to inelastic compaction and has resulted in subsidence near the city of Baghdad at a rate of −10 mm/year. The measured coherence phase between the two signals is ~0.67, and the depletion precedes the subsidence by ~1.5 months. The new data from GRACE-Follow on, Sentinel-1, and the piezometric water level could help to constrain the rate of depletion and displacements in the basin. Combining these remote sensing techniques provides an independent tool for water management in areas where in-situ data are scarce.

New Amorphous Iron-Based Oxyfluorides as Cathode Materials for High-Capacity Lithium-Ion Batteries

A novel two-step strategy to prepare amorphous oxyfluorides, containing both divalent and trivalent 3d-metals, as cathode materials for lithium batteries is presented. The first step involves the preparation of hydrated fluorides M2+M3+2F8(H2O)2 (M2+ = Mn, Fe, Co, Ni, Cu; M3+ = V, Fe) by microwave-assisted solvothermal synthesis. Besides the MnFe2F8(H2O)2 and CuFe2F8(H2O)2 phases, three new compounds, Fe1.3V1.7F8(H2O)2, CoFe2F8(H2O)2, and NiFe2F8(H2O)2, which are isostructural with Fe3F8(H2O)2, have been unraveled. The second step consists in the decomposition of M2+M3+2F8(H2O)2 into amorphous oxyfluorides M2+M3+2F8–2xOx via suitable thermal treatments.. The amorphous materials show a greater electrochemical activity toward Li than their parent phases, among them being CuFe2F6O, which displays the best performance as a cathode material with a first discharge capacity of 310 mAh·g–1. We show that such a large capacity results from cumulative insertion and displacement reactions.

Earthquake rupture characteristics along a developing transform boundary

SUMMARYThe 280-km-long San Cristobal Trough (SCT), created by the tearing of the Australia plate as it subducts under the Pacific Plate near the Solomon and Vanuatu subduction zones, has hosted strike-slip earthquake sequences in 1993 and 2015. Both sequences, which likely represent a complete seismic cycle, began along the oldest section of the SCT—the portion farthest from the tear that has experienced the most cumulative displacement—and migrated to the younger sections closer to the tear. The SCT's abundant seismicity allows us to study transform boundary development—a process rarely observed along a single fault system—through observations of earthquake rupture properties. Using the spectral ratio method based on empirical Green's functions (EGFs), we calculate the corner frequencies of three Mw ∼7 2015 earthquakes and colocated smaller earthquakes. We utilize two different spectral ratio stacking methods and fit both Brune and Boatwright models to the stacked spectral ratios. Regardless of stacking methods and spectral models, we find that the corner frequencies of the 2015 Mw ∼7 earthquakes decrease slightly with distance from the tear. Assuming a constant rupture velocity and an omega-square spectral model, this corner frequency decrease may be due to an increase in rupture length with distance from the tear. The spectrum of the 2015 earthquake farthest from the tear also deviates from the omega-square model, which may indicate rupture complexity. Stress drop estimates from the corner frequencies of the 2015 Mw ∼7 earthquakes range between 1 and 7 MPa, whereas stress drop estimates of their EGFs range from ∼0.05 to 10 MPa with most values between 0.1 and 1 MPa. Independent evidence from a second moments analysis of the 2015 earthquake sequence also indicates a possible increase in rupture length with distance from the tear, confirming the results from the spectral ratio analysis. We also observe an increase in normalized centroid time-delay values, a first-order proxy for rupture behaviour, with distance from the tear for the 2015 sequence. A similar trend for the 1993 sequence suggests that earthquake rupture varies systematically along the SCT. Since distance from the tear corresponds to cumulative fault displacement, these along-strike rupture variations may be due to a displacement-driven fault maturation process.

Micromechanical Behavior of DNA‐1A Lunar Regolith Simulant in Comparison to Ottawa Sand

AbstractIn this study, the micromechanical interparticle contact behavior of “De NoArtri” (DNA‐1A) grains is investigated, which is a lunar regolith simulant, using a custom‐built micromechanical loading apparatus, and the results on the DNA‐1A are compared with Ottawa sand which is a standard quartz soil. Material characterization is performed through several techniques. Based on microhardness intender and surface profiler analyses, it was found that the DNA‐1A grains had lower values of hardness and higher values of surface roughness compared to Ottawa sand grains. In normal contact micromechanical tests, the results showed that the DNA‐1A had softer behavior compared with Ottawa sand grains and that cumulative plastic displacements were observed for the DNA‐1A simulant during cyclic compression, whereas for Ottawa sand grains elastic displacements were dominant in the cyclic sequences. In tangential contact micromechanical tests, it was shown that the interparticle friction values of DNA‐1A were much greater than that of Ottawa sand grains, which was attributed to the softer contact response and greater roughness of the DNA‐1A grains. Widely used theoretical models both in normal and tangential directions were fitted to the experimental data to obtain representative parameters, which can be useful as input in numerical analyses which use the discrete element method.

Unifying theories for nonequilibrium statistical mechanics

The question of deriving general force/flux relationships that apply out of the linear response regime is a central topic of theories for nonequilibrium statistical mechanics. This work applies an information theory perspective to compute approximate force/flux relations and compares the result with traditional alternatives. If it can be said that there is a consensus on the form of response theories in driven, nonequilibrium transient dynamics, then that consensus is consistent with maximizing the entropy of a distribution over transition space. This agreement requires the problem of force/flux relationships to be described entirely in terms of such transition distributions, rather than steady-state properties (such as near-equilibrium works) or distributions over trajectory space (such as maximum caliber). Within the transition space paradigm, it is actually simpler to work in the fully nonlinear regime without relying on any assumptions about the steady-state or long-time properties. Our results are compared to extensive numerical simulations of two very different systems. The first is the periodic Lorentz gas under constant external force, extended with angular velocity and physically realistic inelastic scattering. There, we compare predicted and simulated distributions of the cumulative horizontal displacement after falling through 10 rows of fixed scatterers. The second is an -Fermi–Pasta–Ulam–Tsingou (FPUT) chain, extended with a Langevin thermostat that couples to just two of its harmonic modes. This system tests whether the known long-time correlations in the FPUT system alter the properties of cumulative heat conduction away from the maximum entropy prediction. Although both systems are simulated for short, fixed times under physically realistic dynamical models, the maximum entropy structure of the time-integrated flows are clearly evident. The result encourages further development of empirical laws for nonequilibrium statistical mechanics by employing analogies with standard maximum entropy techniques—even in cases where large deviation principles cannot be rigorously proven from an underlying model.

Spatiotemporal deformation characteristics and triggering factors of Baijiabao landslide in Three Gorges Reservoir region, China

Variations of reservoir water level and seasonal precipitation have resulted in significant movement and destabilization of landslides in the Three Gorges Reservoir (TGR) region of China since reservoir impoundment in 2003. An example is the Baijiabao landslide, a large, actively creeping landslide located in the steep lower valley of the Xiangxi River, about 55 km upstream of the TGR dam in the Yangtze River. Twelve years of monthly monitoring at four GPS stations and routine, monthly field observations show cumulative GPS displacements as large as >1.5 m and widely developed ground cracks. GPS monitoring results show that most movement takes place in rapid steps that coincide with the rainy season and the period of annual reservoir drawdown, with particularly large steps in 2009, 2012 and 2015. This step-like pattern of displacement is also shown by daily data from an automatic monitoring system installed in 2017. The total period of acceleration shown by these daily data was about six weeks long, with rapid movement starting during rapid reservoir drawdown, and terminating when the reservoir began to rise again. In particular, most of the 2018 displacement occurred in only two weeks. Different subzones of the landslide move at different rates and exhibit different features of deformation. The neighborhood rough set theory is used to identify the triggering factors responsible for landslide deformation. The most important triggering factors vary between different sites, data types and the time interval used to define them. The surface deformation and ground crack widening are controlled by the combination of rainfall and variations in the reservoir water levels, whereas the deformation of the sliding zone is most sensitive to the latter. The results show that daily data are needed to capture important, short-term landslide responses. The neighborhood rough set theory for determination of triggering factors is suggested for deformation prediction, stability evaluation, and prevention and control of reservoir landslides in this and other regions.

3D ESTIMATION OF SLOW GROUND MOTION USING INSAR AND THE SLOPE ASPECT ASSUMPTION, A CASE STUDY: THE PUNCAK PASS LANDSLIDE, INDONESIA

Abstract. The Indonesian Centre of Volcanology and Geological Hazard Mitigation classified the Ciloto district as one of the most landslide prone areas in Indonesia. Some evidence of ground movement and the landslide failures occurred in recent years. Thus, continuous monitoring is necessary for supporting the precautions of an upcoming landslide. This study applies Small Baselines - Slowly Decorrelated Phase Filter (SDPF) for InSAR processing both for the ascending and the descending data. The primary objective is to generate horizontal and vertical components of InSAR results from two different tracks and slope aspect information in order to retrieve a projection to the northward direction. We used the available Sentinel-1 SAR data from 2014 until 2018. Combination of two orbits is approached by the surface and the nearest-neighbor gridding method. The 3D components were examined at the Puncak Pass, Ciloto, an active landslide area. For the case study area, it appeared that soil materials transferred slowly from the top of main body landslide to the accumulated zone near to the buildings owned by a local resort. The cumulative 3D displacements for three years were computed for the depleted zone: it moved −47, 23, −10 mm for dU, dE and dN, respectively. Meanwhile, the accumulated zone was considered having the up-lift motion to maximum 43, −13, 7 mm, respectively.

Thermo-mechanical ratcheting in soil–structure interfaces

This paper proposes and validates a thermo-mechanical ratcheting mechanism that explains the cumulative displacement of soil–continuum interfaces when subjected to temperature cycles and bias forces. The study provides experimental evidence of the mechanism from a physical model consisting of a rectangular, solid prism, that is subjected to temperature cycles and a static bias force aligned parallel to the interface, while resting on a horizontal granular material bed. The experimental results show that the thermally driven displacement accumulates with the number of temperature cycles in the direction of the bias axial force application. In addition, the displacement accumulation rate decreases with the static factor of safety against sliding of the interface and increases with the amplitude of the temperature cycles. FEM thermo-mechanical simulations of the physical model confirm the experimental findings. Finally, the governing equations of the mechanism are captured in a numerical algorithm that solves the load transfer of the prismatic element and reproduces the trend of displacement accumulation.

Biomechanical evaluation of patellar tendon repair using Krackow suture technique

BackgroundPatellar tendon rupture is a potentially devastating injury. Surgical repair is the primary treatment recommended for the patients with patellar tendon ruptures. Given the tendon properties, the suture technique is critical for proper tissue repair. Providing adequate loading during early mobilization is essential to prevent tendon suture repair failure. Therefore, the current study evaluated the mechanical characteristics of various applied loadings on patellar tendon repair using Krackow suture via a porcine model.MethodsTwelve fresh porcine hindlimbs with patellar tendon rupture were repaired by Krackow method using synthetic and non-absorbable No. 5 Ethibond sutures. Loadings of 100 and 200 N were applied during the cyclic loading test. A three-dimensional optical motion capture system was used to record the gap formation at the initial, 50th, 100th, 150th, 200th, 250th, 500th, 750th, and 1000th cycle. After cyclic loading, the specimen was loaded to failure under displacement control at a rate of 1 mm/s.ResultsSuture breakage was the primary failure mode in both loading conditions. After 1000 cyclic loadings of 100 N, the ultimate failure strength was 243.6 ± 25.8 N. However, the specimens tested under 200 N of loading failed before reaching 200 cycles. Under the 100 N loading, the largest gap deformation (1.89 ± 0.23 mm) and residual deformation (0.213 ± 0.183 mm) were found in the initial cycle. The average cumulative displacement was 5.13 mm from the initial cycle to the 100th cycle and 4.5 mm from the 250th to the 1000th cycle.ConclusionsOur findings can serve as reference values for further comparisons with various repair techniques or materials. This study suggests that the initially applied load after patellar tendon repair is an important risk factor of re-rupture.