Sinkhole collapse propagation studies through instrumented small-scale physical models

Abstract. Sinkholes are common geohazards, frequently responsible for sudden catastrophic ground collapse. Thus, effective monitoring would allow for further understanding of the mechanism of occurrence of sinkholes and lead to the development of a potential early warning system to provide an alarm or a warning of incipient col-lapse. In the current study, fiber Bragg gratings (FBGs) were used to instrument reduced scale models, simulating a sinkhole event. The tests were conducted by embedding optic fiber sensors in the soil and inducing failure until critical conditions were reached. FBG sensors were manufactured in a single optic fiber cable. The measurements of small horizontal strains were recorded simultaneously and in various positions. Failure mechanism was found to relate to the backfill density, and compaction.

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Application of additive technology for the study of resonance oscillations in structures

MATEC Web of Conferences ◽

10.1051/matecconf/201825104001 ◽

2018 ◽

Vol 251 ◽

pp. 04001 ◽

Cited By ~ 1

Author(s):

Konstantin Makarov ◽

Evgeny Yurchenko ◽

Elena Yurchenko

Keyword(s):

Physical Modeling ◽

Physical Models ◽

Small Scale ◽

Additive Technology ◽

Harmonic Oscillations ◽

Resonance Frequencies ◽

Scale Models ◽

Concrete Building ◽

Resonance Oscillations

The methodic of studying the vibrations of small-sized physical models using additive technology has been developed. The results of the experimental determination of the resonance frequencies for harmonic oscillations and the calculation of the phase shift for two small-scale models of a three-story reinforced concrete building with a nonrigel frame has been presented. It has been shown that the production of models on a 3-D printer makes it possible to reduce the laboriousness of their manufacture, and also to expand the possibilities for accounting of operational defects in buildings and structures derived from seismic, vibrational and other types of vibrational influences based on physical modeling.

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Fiber Optic Displacement Monitoring in Laboratory Physical Model Testing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.143-144.1081 ◽

2010 ◽

Vol 143-144 ◽

pp. 1081-1085

Author(s):

Hong Hu Zhu ◽

Jian Hua Yin ◽

Hua Fu Pei ◽

Lin Zhang ◽

Wei Shen Zhu

Keyword(s):

Fiber Optic ◽

Physical Models ◽

Displacement Sensor ◽

Small Scale ◽

Sensing Technology ◽

Laboratory Calibration ◽

Scale Models ◽

Displacement Profile ◽

Displacement Transducers ◽

Good Agreement

For physical models, conventional techniques have difficulties in monitoring internal displacements during laboratory testing. In this paper, based on fiber Bragg grating (FBG) sensing technology, a bar-type fiber optic displacement sensor is developed for small-scale models. When the model deforms due to loading or unloading, the embedded displacement sensor can capture the displacement profile along the bar length using the strain data from quasi-distributed FBGs. Laboratory calibration tests have showed that the displacements measured by the FBG sensing bar are in good agreement with those from conventional displacement transducers. For the physical models of a gravity dam and a cavern group, the FBG sensing bars were successfully installed in predefined holes, together with conventional gauges. During testing, the FBG sensing bars measured the displacement distributions within the models. The fiber optic monitoring results demonstrate the deformation characteristics of surrounding rock masses induced by overloading and underground excavation and indicate the overall stability conditions of these two geo-structures.

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Casing Pipe Damage Detection with Optical Fiber Sensors: A Case Study in Oil Well Constructions

Advances in Civil Engineering ◽

10.1155/2010/638967 ◽

2010 ◽

Vol 2010 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Zhi Zhou ◽

Jianping He ◽

Minghua Huang ◽

Jun He ◽

Genda Chen

Keyword(s):

Optical Fiber ◽

Relative Error ◽

Warning System ◽

Optical Fiber Sensors ◽

Time Domain Reflectometry ◽

Oil Well ◽

In Situ Tests ◽

Fiber Sensors ◽

Casing Pipe ◽

Fbg Sensors

Casing pipes in oil well constructions may suddenly buckle inward as their inside and outside hydrostatic pressure difference increases. For the safety of construction workers and the steady development of oil industries, it is critically important to measure the stress state of a casing pipe. This study develops a rugged, real-time monitoring, and warning system that combines the distributed Brillouin Scattering Time Domain Reflectometry (BOTDR) and the discrete fiber Bragg grating (FBG) measurement. The BOTDR optical fiber sensors were embedded with no optical fiber splice joints in a fiber-reinforced polymer (FRP) rebar and the FBG sensors were wrapped in epoxy resins and glass clothes, both installed during the segmental construction of casing pipes. In situ tests indicate that the proposed sensing system and installation technique can survive the downhole driving process of casing pipes, withstand a harsh service environment, and remain intact with the casing pipes for compatible strain measurements. The relative error of the measured strains between the distributed and discrete sensors is less than 12%. The FBG sensors successfully measured the maximum horizontal principal stress with a relative error of 6.7% in comparison with a cross multipole array acoustic instrument.

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Cognitive map formation through haptic and visual exploration of tactile city-like maps

Scientific Reports ◽

10.1038/s41598-021-94778-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Loes Ottink ◽

Marit Hoogendonk ◽

Christian F. Doeller ◽

Thea M. Van der Geest ◽

Richard J. A. Van Wezel

Keyword(s):

Visual Information ◽

Spatial Information ◽

Cognitive Map ◽

Visual Exploration ◽

Distinct Advantage ◽

Small Scale ◽

Map Learning ◽

Scale Models ◽

Spatial Tasks ◽

Tactile Maps

AbstractIn this study, we compared cognitive map formation of small-scale models of city-like environments presented in visual or tactile/haptic modalities. Previous research often addresses only a limited amount of cognitive map aspects. We wanted to combine several of these aspects to elucidate a more complete view. Therefore, we assessed different types of spatial information, and consider egocentric as well as allocentric perspectives. Furthermore, we compared haptic map learning with visual map learning. In total 18 sighted participants (9 in a haptic condition, 9 visuo-haptic) learned three tactile maps of city-like environments. The maps differed in complexity, and had five marked locations associated with unique items. Participants estimated distances between item pairs, rebuilt the map, recalled locations, and navigated two routes, after learning each map. All participants overall performed well on the spatial tasks. Interestingly, only on the complex maps, participants performed worse in the haptic condition than the visuo-haptic, suggesting no distinct advantage of vision on the simple map. These results support ideas of modality-independent representations of space. Although it is less clear on the more complex maps, our findings indicate that participants using only haptic or a combination of haptic and visual information both form a quite accurate cognitive map of a simple tactile city-like map.

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Roughness Lengths for Momentum and Heat Derived from Outdoor Urban Scale Models

Journal of Applied Meteorology and Climatology ◽

10.1175/jam2500.1 ◽

2007 ◽

Vol 46 (7) ◽

pp. 1067-1079 ◽

Cited By ~ 112

Author(s):

M. Kanda ◽

M. Kanega ◽

T. Kawai ◽

R. Moriwaki ◽

H. Sugawara

Keyword(s):

Wind Direction ◽

Roughness Length ◽

Scale Dependence ◽

Scale Model ◽

Small Scale ◽

Physical Scale ◽

Scale Models ◽

Roughness Lengths ◽

Urban Sites ◽

Obstacle Height

Abstract Urban climate experimental results from the Comprehensive Outdoor Scale Model (COSMO) were used to estimate roughness lengths for momentum and heat. Two different physical scale models were used to investigate the scale dependence of the roughness lengths; the large scale model included an aligned array of 1.5-m concrete cubes, and the small scale model had a geometrically similar array of 0.15-m concrete cubes. Only turbulent data from the unstable boundary layers were considered. The roughness length for momentum relative to the obstacle height was dependent on wind direction, but the scale dependence was not evident. Estimated values agreed well with a conventional morphometric relationship. The logarithm of the roughness length for heat relative to the obstacle height depended on the scale but was insensitive to wind direction. COSMO data were used successfully to regress a theoretical relationship between κB−1, the logarithmic ratio of roughness length for momentum to heat, and Re*, the roughness Reynolds number. Values of κB−1 associated with Re* for three different urban sites from previous field experiments were intercompared. A surprising finding was that, even though surface geometry differed from site to site, the regressed function agreed with data from the three urban sites as well as with the COSMO data. Field data showed that κB−1 values decreased as the areal fraction of vegetation increased. The observed dependency of the bulk transfer coefficient on atmospheric stability in the COSMO data could be reproduced using the regressed function of Re* and κB−1, together with a Monin–Obukhov similarity framework.

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Methodology for Developing Hydrological Models Based on an Artificial Neural Network to Establish an Early Warning System in Small Catchments

Advances in Meteorology ◽

10.1155/2016/9125219 ◽

2016 ◽

Vol 2016 ◽

pp. 1-14 ◽

Cited By ~ 2

Author(s):

Ivana Sušanj ◽

Nevenka Ožanić ◽

Ivan Marović

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Early Warning ◽

Early Warning System ◽

Warning System ◽

Small Scale ◽

Ann Model ◽

Data Value ◽

The Mean ◽

Artificial Neural

In some situations, there is no possibility of hazard mitigation, especially if the hazard is induced by water. Thus, it is important to prevent consequences via an early warning system (EWS) to announce the possible occurrence of a hazard. The aim and objective of this paper are to investigate the possibility of implementing an EWS in a small-scale catchment and to develop a methodology for developing a hydrological prediction model based on an artificial neural network (ANN) as an essential part of the EWS. The methodology is implemented in the case study of the Slani Potok catchment, which is historically recognized as a hazard-prone area, by establishing continuous monitoring of meteorological and hydrological parameters to collect data for the training, validation, and evaluation of the prediction capabilities of the ANN model. The model is validated and evaluated by visual and common calculation approaches and a new evaluation for the assessment. This new evaluation is proposed based on the separation of the observed data into classes based on the mean data value and the percentages of classes above or below the mean data value as well as on the performance of the mean absolute error.

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Fine-Scale Fire Spread in Pine Straw

Fire ◽

10.3390/fire4040069 ◽

2021 ◽

Vol 4 (4) ◽

pp. 69

Author(s):

Daryn Sagel ◽

Kevin Speer ◽

Scott Pokswinski ◽

Bryan Quaife

Keyword(s):

Fire Spread ◽

Small Scale ◽

Natural Setting ◽

Fine Scale ◽

Prescribed Burn ◽

Fire Dynamics ◽

Rate Of Spread ◽

Scale Models ◽

Fire Front ◽

Visible Images

Most wildland and prescribed fire spread occurs through ground fuels, and the rate of spread (RoS) in such environments is often summarized with empirical models that assume uniform environmental conditions and produce a unique RoS. On the other hand, representing the effects of local, small-scale variations of fuel and wind experienced in the field is challenging and, for landscape-scale models, impractical. Moreover, the level of uncertainty associated with characterizing RoS and flame dynamics in the presence of turbulent flow demonstrates the need for further understanding of fire dynamics at small scales in realistic settings. This work describes adapted computer vision techniques used to form fine-scale measurements of the spatially and temporally varying RoS in a natural setting. These algorithms are applied to infrared and visible images of a small-scale prescribed burn of a quasi-homogeneous pine needle bed under stationary wind conditions. A large number of distinct fire front displacements are then used statistically to analyze the fire spread. We find that the fine-scale forward RoS is characterized by an exponential distribution, suggesting a model for fire spread as a random process at this scale.

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Geomechanical modelling of sinkhole development using distinct elements: model verification for a single void space and application to the Dead Sea area

Solid Earth ◽

10.5194/se-9-1341-2018 ◽

2018 ◽

Vol 9 (6) ◽

pp. 1341-1373 ◽

Cited By ~ 13

Author(s):

Djamil Al-Halbouni ◽

Eoghan P. Holohan ◽

Abbas Taheri ◽

Martin P. J. Schöpfer ◽

Sacha Emam ◽

...

Keyword(s):

Distinct Element ◽

Cavity Growth ◽

Dead Sea ◽

Model Verification ◽

Void Space ◽

Ground Collapse ◽

Biaxial Tests ◽

Sinkhole Collapse ◽

The Dead ◽

Element Method

Abstract. Mechanical and/or chemical removal of material from the subsurface may generate large subsurface cavities, the destabilisation of which can lead to ground collapse and the formation of sinkholes. Numerical simulation of the interaction of cavity growth, host material deformation and overburden collapse is desirable to better understand the sinkhole hazard but is a challenging task due to the involved high strains and material discontinuities. Here, we present 2-D distinct element method numerical simulations of cavity growth and sinkhole development. Firstly, we simulate cavity formation by quasi-static, stepwise removal of material in a single growing zone of an arbitrary geometry and depth. We benchmark this approach against analytical and boundary element method models of a deep void space in a linear elastic material. Secondly, we explore the effects of properties of different uniform materials on cavity stability and sinkhole development. We perform simulated biaxial tests to calibrate macroscopic geotechnical parameters of three model materials representative of those in which sinkholes develop at the Dead Sea shoreline: mud, alluvium and salt. We show that weak materials do not support large cavities, leading to gradual sagging or suffusion-style subsidence. Strong materials support quasi-stable to stable cavities, the overburdens of which may fail suddenly in a caprock or bedrock collapse style. Thirdly, we examine the consequences of layered arrangements of weak and strong materials. We find that these are more susceptible to sinkhole collapse than uniform materials not only due to a lower integrated strength of the overburden but also due to an inhibition of stabilising stress arching. Finally, we compare our model sinkhole geometries to observations at the Ghor Al-Haditha sinkhole site in Jordan. Sinkhole depth ∕ diameter ratios of 0.15 in mud, 0.37 in alluvium and 0.33 in salt are reproduced successfully in the calibrated model materials. The model results suggest that the observed distribution of sinkhole depth ∕ diameter values in each material type may partly reflect sinkhole growth trends.

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