Warning Value Research Articles

Early Warning Value of ASL-MRI to Estimate Premorbid Variations in Patients With Early Postoperative Cognitive Dysfunctions.

Background: Postoperative cognitive dysfunction (POCD) is a general complication following cardiac and major non-cardiac surgery amongst the elderly, yet its causes and mechanisms are still unknown. The present study aimed to detect whether regional cerebral blood flow (CBF) is altered in the brain before surgery in POCD patients compared with non-POCD (NPOCD) patients, thus, CBF variation may potentially predict the occurrence of early POCD.Methods: Fifty patients scheduled for spinal stenosis surgery were enrolled in the study. All study participants completed a battery of neuropsychological tests (NPTs) by a well-trained neuropsychologist before the surgery and 1 week after the surgery. POCD was defined when the preoperative to postoperative difference of at least two of the NPTs’ |Z|-scores with reference to a control group exceeded 1.96. Pulsed arterial spin-labeling (ASL) MRI was scanned at least 1 day before surgery. The ASLtbx toolkit and SPM12 were applied to preprocess and correct the images, which were then normalized to the MNI brain template space to obtain standardized cerebral perfusion images.Results: POCD was identified in 11 out of 50 patients (22%). The CBF of the right superior temporal lobe, right and left middle cingulate gyrus, and the right hippocampus, and parahippocampal gyrus in POCD group was lower than that in NPOCD group (P < 0.001). The CBF of the pars triangularis of inferior frontal gyrus in POCD group was higher than that in NPOCD group (P < 0.001).Conclusions: These preliminary findings suggest that CBF premorbid alterations may happen in cognitively intact elderly patients that develop early POCD. Alterations of preoperative CBF might be a bio-marker for early POCD that can be detected by noninvasive MRI scans.

Investigation of Dominant Plants and Analysis of Ecological Restoration Potential in Lailishan Tin Tailings

To investigate the dominant plants in ecological restoration of tin mining areas, field investigations were conducted in a tin tailings area in Lailishan, Yunnan Provence, and 15 dominant plants and corresponding rhizosphere soils were collected. The plant root mycorrhizal infection rate; the copper (Cu), cadmium (Cd), arsenic (As), nickel (Ni), lead (Pb), and tin (Sn) contents; and the chemical properties of the rhizosphere tailings were determined. The transfer and enrichment coefficients of six heavy metals were calculated for each of the 15 plants to comprehensively evaluate the application potential of native plants. The rhizophere tailings had an average pH value of 3.13, which was acidic. The organic matter, total nitrogen, total phosphorus, total potassium, alkaline hydrolyzed nitrogen, and available phosphorus content of the soils was 6.07 g ·kg-1, 5.74 g ·kg-1, 0.62 g ·kg-1, 8.66 g ·kg-1, 30.84 mg ·kg-1, and 2.08 mg ·kg-1 respectively, indicating relatively nutrient-poor soil. The average Cu, Cd, Ni, Pb, As, and Sn contents of the soils were 347.40, 1.02, 1.34, 168.47, 25.81, and 2299.02 mg ·kg-1, respectively. Among the heavy metals, the Cd content reached a third-level pollution warning value. The soil also contained a large amount of Cu and Pb which exhibited a different spatial distribution. This area appears to have a high risk of Cu, Pb, and Cd pollution. In addition, the roots of Olea europaea L. and Eurya japonica Thunb. had a high rate of mycorrhizal infection. Alnus cremastogyne Burk., Bambusa multiplex (Lour.) Raeusch. ex Schult. 'Alphonse-Kar' R. A. Young, Juncus effusus L., and Cyperus rotundus L. var. had a strong ability to absorb and transport heavy metals. The other plants were also adapted to the growth environment of the tin tailings, with the potential to restore the mining area.

Near-Realtime Quantitative Precipitation Estimation and Prediction (RealPEP)

Flash floods in small- to medium-sized catchments and intense precipitation over cities caused by severe local storms pose increasing threats to our society. For the timely prediction of such events, the value of high-resolution and high-quality QPE and corresponding forecasts cannot be overrated. Seamless predictions harmonizing nowcasting and numerical weather prediction (NWP) across forecast lead times from minutes to days would greatly help to improve the value and efficiency of warnings. Organized by the Research Unit on Near-Realtime Precipitation Estimation and Prediction (RealPEP, www2.meteo.uni-bonn.de/realpep) and supported by the Project on Seamless Integrated Forecasting System (SINFONY, www.dwd .de/DE/forschung/forschungsprogramme/sinfony_iafe/sinfony_node.html) of the German Meteorological Service (DWD), an international 3-day online conference was held from 5 to 7 October 2020, dedicated to Precipitation and Flash-Flood Predictions from Minutes to Days (https://indico .scc.kit.edu/event/883/). Most speakers agreed to have their presentations recorded, which we uploaded to YouTube for further distribution (see, e.g., on the conference homepage, https:// indico.scc.kit.edu/event/883/page/588-recorded-talks). The speakers were both invited experts in the respective research fields and researchers from the RealPEP and SINFONY projects. Talks and discussions could be followed on video stream. Interaction between the about 250 participants was enabled by entering written questions and comments via a dedicated tool, which allowed for voting and thus also ranking questions. Registered participants could enter chat rooms from where they could be moved to the speaker room for posing the questions directly to the speakers and the auditorium. On the last day of the conference podium discussions with selected speakers summarized talks and discussions and elaborated on overarching problems, ideas, and developments in the fields of quantitative precipitation estimation (QPE), quantitative precipitation nowcasting (QPN), quantitative precipitation forecasting (QPF), flash-flood prediction (FFP), and their organization into seamless prediction systems, which also constituted the topics of the five sessions during the conference. We report here in particular on the outcomes of the panel discussions.

P-IM003. The utility of intraoperative Neurophysiological monitoring in surgical correction for spinal arteriovenous shunts: A historical control study

Introduction . This study aimed to investigate the utility of intraoperative neurophysiological monitoring (IONM) in surgical correction for spinal arteriovenous shunts (SAVSs). Methods . We retrospectively reviewed 42 patients underwent surgical correction for SAVSs. 29 patients who underwent multimodal IONM (transcranial electrical motor-evoked potentials [tcMEP], somatosensory-evoked potentials [SSEP], continuous electromyography, and bulbocavernosus reflex [BCR]) from 2011 to 2020 were compared to 13 historical controls (non-IONM groups) from 2003 to 2009. The rates of postoperative neurological deficits, neurophysiological warnings, and their characteristics were analyzed. Postoperative neurological deficits were evaluated at one month, six months, and one year after surgery, respectively. Results . Among 42 patients, postoperative neurological deficit rates were 13.8% and 46.2% in the IONM and non-IONM groups, respectively (p = 0.046). In total, 5 warnings were observed during IONM (3 tcMEP; 1 tcMEP and SSEP; 1 BCR). Three cases were true-positive. The amplitude of right abductor halluces MEP decreased during surgery in patient 1 who had no weakness of the right leg previously. After surgery, weakness of right leg was newly observed in patient 1. Patient 2 who had both leg weakness previously got worse both leg weakness than before surgery. Her left abductor halluces MEP disappeared and never recovered during surgery. Patient 3 had normal bladder function before surgery. His baseline BCR was successfully recorded but the end of the surgery, the bilateral BCR was completely disappeared. He had severe urinary retention after surgery. Sensitivity, specificity, positive predictive value, and negative predictive value of IONM warnings for detecting postoperative neurological complications were 75.0%, 92.0%, 60.0%, and 95.8% respectively. Conclusion . The utility of IONM in surgical correction for SAVSs has not been evaluated due to its rarity. This is the first study to provide results revealing that IONM helps to improve postoperative neurological outcome through comparison with non-IONM group in surgical correction for SAVSs.

Extreme-rainfall Data as a Basis for Landslide Warnings: a Case Study of a Road in Central Taiwan

In recent years, an increase in extreme rainfall events linked to global warming has led to increases in the number and intensity of disasters such as landslides, landslips, and debris flows in Taiwan. This study focuses on the impact of such events, especially during typhoons, on County Road 89: the main traffic artery in Renai Township, Nantou County. Specifically, it will use an inverse distance weighting method (IDW) to analyze how rainfall at the four rainfall stations in Nantou, located at Renai, Ruiyan, Cuiluan and Cuihua, may related to damage events at the 12.3k, 22.53k, 32.5k, 46.3k, and 49k points on County Road 89. Then, landslide road-damage warning ranges will be drawn up using various combinations of data, including cumulative rainfall, maximum rainfall within a 24-hour period, and I-R alert model (I: rainfall intensity, R: cumulative rainfall), with an I-T alert model (I: rainfall intensity, T: rainfall duration) for comparison. This will yield an optimal warning value for the landslide-prone area of the focal road. Finally, data from County Road 89 will be compared against data from the Lishan landslide area, to ascertain whether/how such warning values should differ across geographic areas. The results are expected to usefully inform follow-up disaster prevention planning as well as further academic research on this topic.

Framework of Emergency Response System for Potential Large-Scale Landslide in Taiwan

In order to lower the risks of large-scale landslides and improve community resilience in Taiwan, a long-term project has been promoted by the Soil and Water Conservation Bureau since 2017. In this study, methods to build an emergency response framework including hazard mapping and early warning system establishment were introduced. For hazard mapping, large-scale landslides were categorized into a landslide, debris flow, or landslide dam type based on the movement of unstable materials and topography. Each disaster type has different hazard zone delineation methods to identify the affected areas. After establishing the possible effected areas, early warning mechanisms, including warning value using rainfall as the indicator and evacuation procedures, should be created for emergency response. To set the warning value, analysis of the occurrence thresholds of previous existing large-scale landslides was conducted to determine the critical rainfall and further utilized to set the warning value considering the evacuation time for the locals. Finally, for integration with the current debris flow emergency response system, potential large-scale landslide areas were further divided into two types based on their spatial relationship with debris flows. For those overlapping with existing debris flow protected targets, the current emergency response system was upgraded considering the impact of large-scale landslides, while the others were suggested for use in building a new emergency response procedure. This integrated framework could provide a feasible risk avoidance method for local government and residents.

Analysis of High Slope Seepage Influence Based on Multi-scale Measurement Data

In order to study the influence of seepage on high slope stability, the impact of drainage hole blockage on slope stability is analyzed by in-situ test technology, near-field photogrammetry and indoor test and numerical simulation.According to the groundwater monitoring of the water meter and pore pressure meter, when the drainage hole blockage exceeds 80%, the pore water pressure increases by about 13m, by 25kPa; is monitored by the steel gauge and anchor gauge. When the drainage hole blockage exceeds 80%, the shear force of the slope anti-sliding pile increases by 20%, about 30kN; analyzes the slope deformation by the near-view photography technique, when the drainage hole blockage exceeds 80%, and the slope deformation of 44mm, exceeds the slope deformation warning value of 30mm,.After theoretical calculation and numerical simulation analysis, the groundwater level and support structure under different blockage conditions. Numerical simulation results show that when the drainage hole is less than 60%, the supporting structure and slope deformation grow linearly, while when the blockage degree exceeds 80%, the support structure increases sharply, and according to the finite element strength, when the blockage degree exceeds 60%, the slope stability coefficient decreases sharply and the risk of instability.

Research on Underground Chemical Gas Monitoring and Target Location Based on an Improved Moth Flame Algorithm

The danger of downhole work is mainly due to the chemical toxic gases and flammable gases NO2, CO, SO2, H2S, CH4, CO2, etc. When the concentration reaches a certain value, it will produce very great harm. With the continuous development of sensor technology and communication technology, it is necessary to monitor the relevant geographic features below the ground. Because of the complex environmental parameters of the coal mine roadway and the interference caused by various electrical equipment, the transmission of mine electromagnetic signals will be affected, resulting in low positioning accuracy. However, the underground chemical gas leakage leads to the life of underground workers which cannot be guaranteed, so it is necessary to effectively monitor the concentration of chemical gas components in underground mines. In this paper, a moth flame algorithm based on optimized inertia weights is proposed. By continuously improving the local inertia weights, the global optimum is determined by using the change of inertia weights in the iterative process of the algorithm. By testing the convergence and optimal value of several algorithms under common test functions, IMFO can obtain the global optimal solution. Finally, the concentrations of chemical gases NO2, CO, SO2, H2S, CH4, and CO2 are monitored by setting specific areas to see if they reach the early warning values. Then, 16 coordinates in the region are used to predict the above method, and the IMFO algorithm can achieve the best prediction effect.

Quantitative Assessment of Damage in Buried Polyethylene Pipe Subjected to Land Subsidence

AbstractTraditional investigation of polyethylene pipe (PE) subjected to external loads focused only on the study of mechanical behavior or the failure judgment, but could not predict the damage evolution process. In this paper, a quantitative assessment was conducted for the damage of PE pipe subjected to land subsidence. Specifically, a static damage model was proposed based on failure pressure. Then, a finite element model of the buried PE pipe was established to calculate the failure pressure of smooth or notched pipe. Finally, the damage of the buried PE pipes suffering from land subsidence was computed by the damage model. The results show that the failure pressure and damage curves of smooth PE pipe can be divided into increased, steady, and reducing stages. For notched PE pipe, the damage curve can be divided into initial, middle, and late stages when the notch depth coefficient A (notch depth/thickness) equals to 0.1. But when A surpasses 0.2, the damage curve loses its middle stage and rapid damage follows. The threshold of the late stage of damage can be regarded as the last warning value of the damage of PE pipe under land subsidence, which indicates the maintenance measures should be taken immediately. The defects on the pipe accelerated the speed of damage and the late stage of damage evolution.

Study on Early Warning Method of Cylinder Block's Off-Center Position and Swing Failure for 50 MW Steam Turbine

Due to the special structure of the cylinder block, there is an off-center position and swing fault in the process of start-up and operation of the 50 MW extraction unit. Moreover, the lack of effective monitoring and early warning means seriously affects the safety of the unit operation. Therefore, it is very important to forewarn the fault of cylinder off-center position and swing. First of all, through the design of cylinder block offset amplifying mechanism for fault monitoring, the data of eccentric swing required for establishing mathematical model is obtained. Then, neural network is selected for data-driven modeling, two time series prediction models are obtained, and the influence of input and output parameters on the prediction accuracy is studied. Finally, by selecting reasonable early warning value and decision rules, an effective early warning of off-center position and swing fault is realized, and a monitoring device for real-time monitoring and fault early warning is developed. The actual application effect shows that this early warning method has important engineering value to avoid equipment damage caused by the swing fault for 50 MW unit.

Implement an Emergency Rescue Device for Vehicles

The purpose of this study is to design a device that can handle emergency situations when the vehicle is overturned, abnormal gas is generated, or it is accidentally flooded by water. The device is fixed in the corner of the front passenger seat, uses the vehicle power supply as the device power, and uses Bluetooth to connect to the mobile phone. Once one of the above three situations occurs, the device will open the window glass and urgently call for rescue operations. The sensor is divided into two stages to prevent errors in detecting the water level or abnormal gas concentration. The first alarm is a basic judgment that enables the personnel in the car to react to the situation. Once the second alarm occurs, the system will determine that the signal has reached the warning value, the personnel in the vehicle are in danger and the window glass should be opened immediately. This design ensures the safety of the people in the car in the event of a dangerous or unexpected situation, and also prevents unnecessary damage to the car.

Research in placement of measuring sensors on hexagonal idler housing with regard to requirements of pipe conveyor failure analysis

In order to ensure ecological transport without failure requirements for the transport of bulk materials by continuous conveyor systems, careful attention should be given to the proper shape of the conveyor belt which is provided by positioning the idler rolls in the idler housing of the pipe conveyor. This paper presents the research on idler housing contact forces (CF) at the cross-section of the loaded conveyor belt filled up to 37.5% and 75%, resulting in a multiple linear regression model in the form: CF = β0 + β1TF + β2M + ε, where TF is the tension force and M is the material filling volume. Based on it, the relative changes of the contact forces were subsequently processed. From the analysis obtained, the position of the most suitable placement of the strain gauge contact force sensors on the idler rolls is proposed, in view of the timely detection of the warning values for failure analysis.

Differentiated warning rule of power transformer health status based on big data mining

Accurate on-line monitoring of transformer operation status is essential to ensure the reliability of power system. The dissolved gas analysis (DGA) method, which compares the gas concentration to the pre-set threshold, is most widely used for transformer status warning. However, existing standards apply either single threshold value or rough classification to diversified transformers with different properties, which therefore affects the accuracy of status warning. This paper establishes a differentiated warning rule through big data analysis mining. The Fuzzy C -means method is applied to identify optimal transformer properties, which can reflect the individualized characteristics of transformer to the best extent. As verified by the probability plot, the full sets of dissolved gas data under the selected properties conform to the Weibull Model. Association analysis is then carried out between the dissolved gas distribution characteristics and defect/ fault rate, and the warning thresholds are accordingly calculated. Correlating the gas concentration and gas increase rates with established warning values, the transformer operation status can be identified. The verification test indicates that the differentiated warning rule shows better performance than conventional methods and demonstrates an accuracy as high as 98.21%.

A kernel principal component analysis-based approach for determining the spatial warning domain of dam safety

It is important to determine the warning value of structural behavior for evaluating the service safety, identifying the potential risk and preventing the failure of dam engineering. However, more attention was paid to determining the security warning value of a single observation point on deformation, seepage or stress. And the correlation between the adjacent points or among all points in one dam section is usually lack of consideration. In this paper, the monitoring data of multi-points are taken to determine the spatial warning domain of dam safety. The warning mode of abnormal structural behavior is changed from the single point into the linked multi-points. First, the kernel principal component analysis method is adopted to identify the inherent characteristics among observation points in a dam section. Second, considering the correlation among observation points, the implementation process is proposed to determine the spatial warning domain of dam safety. Finally, an actual concrete gravity dam is taken as an example. The proposed approach is used to determine the spatial warning domains of deformation and seepage. The results, which are obtained by the proposed approach, the traditional method and the qualitative analysis for monitoring data, are compared. It is indicated that the proposed multi-points correlation-based approach is feasible and superior to determine the spatial warning domain of dam safety.

Analysis of Early Warning Spatial and Temporal Differences of Tourism Carrying Capacity in China’s Island Cities

Tourism is the leading industry of island cities and the tourism carrying capacity is of great significance to the sustainable development of cities. This paper adopts the state-space model to construct an early warning indicator system for tourism carrying capacity from three aspects: nature, economy, and society, explores the early warning status, and spatial and temporal differences of tourism carrying capacity in Chinese island cities, and makes use of the BP(Back Propagation) neural network model to predict the development trend of early warnings. The results show that (1) from 2012 to 2018, the early warning status of China’s island cities’ tourism carrying capacity is generally on the rise, the natural carrying capacity system’s early warning situation has deteriorated, which is in a state of severe warning interval. The economic carrying capacity and social carrying capacity are on the rise, and the warning degree is from the super warning interval to the severe warning interval and then to the moderate warning degree. The forecast of the overall tourism carrying capacity early warning index from 2019 to 2021 presents an upward trend and is in the moderate warning interval. (2) The tourism carrying capacity early warning in China’s island cities shows a large spatial and temporal difference and the early warning values of each island city are different. The early warning value of Putuo tourism carrying capacity always ranks first, and Changdao has the worst performance. (3) In accordance with the contribution status of the subsystem to the total system, the Chinese island cities show regional differences in the northern, central, and southern area, showing two forms of pressure cities and pressure-carrying cities. The government can adopt different policies and measures in accordance with different characteristics of human environmental activities.

Construction monitoring on the unloading process of steel roof for Guilin Liangjiang International Airport Terminal T2

The main building of Guilin Liangjiang International Airport Terminal T2 adopts the steel reinforced concrete frame structure, the central roof uses the spatial solid web arch support and single-shell steel structural system with the largest supporting arch span of 120 meters, and the single-shell steel structural system is connected with the spatial solid web arch through diagonal bracing. The large-span space steel structure of the roof had a large building area, and more than 300 lattice columns were used for temporary support in construction. In the unloading process of steel structure, the deformation and stress of the structure changed greatly. Simulation for all construction steps of the main steel structure, the key steel members and structural locations with large deformations were found out, and the monitoring scheme of deformation and stress of steel structure were determined. The stress monitoring of steel structural was completed by the self-developed wireless stress monitoring system. The deformation monitoring points were automatically searched by the deformation robot, and the three-dimensional coordinates of each monitoring points were measured. The measured results were compared with the initial data, and the deformation of structure was obtained. In the whole process of stress and deformation monitoring, the early warning values were set according to structural analysis and material properties, which could help engineers to make decisions on the structural safety. After the smooth construction of the project, we would find that the monitoring system meted the monitoring requirement during the construction stage, and the result was an important evaluation index for the structure. The research methods used in this paper could be seen as useful reference for construction of similar projects.

Design and implementation of a CPS‐based predictive maintenance and automated management platform

The concept of cyber-physical systems (CPSs) is a core technology indispensable to Industry 4.0. The development of an intelligent automatic operational management platform is presented in this study. The platform is used to collect on-site data, provide predictive maintenance, and monitor and control the mobile robots. For predictive maintenance, it is targeted at products from manufacturing big data to cloud computing, and predictive maintenance for all factories around the world. The efficiency of the management system is improved by the performance evaluation strategy. In the experiments, the authors implement and discuss the predictive maintenance platform with generated synthetic data and real-world data collected from a gearbox plant. The results show that the important variables possess large drops according to mean decrease Gini. A warning generation for battery simulation and manufacturing execution is also presented to demonstrate the proposed system design. The results show that the discharge curve drops sharply at the last stage, and the warning value can be set accordingly.

Cascading disasters risk modeling based on linear uncertainty distributions

Cascading disasters are a critical part of the disaster study. However, due to problems such as information incompleteness and small-sample, probability distribution functions cannot be derived based on the frequency approach. Fortunately, the uncertainty theory, designated for treating the above situations, provides a way for dealing with the problem through subjective estimations achieved by simulating uncertainty variables. This paper studies the cascading disasters risk modeling with the uncertainty theory and simulates inducing risk by using linear uncertainty distributions. To obtain the minimum early warning value and the maximum belief degree of a disaster system, a cascading disaster risk model is proposed in this paper with the characteristics of the series, parallel, and mixed risk. In addition, the early warning value represents the risk threshold of the cascading disaster system, while the belief degree represents the possibility of the cascading disaster system in a safe state under a certain early warning value level.

SoCalGas and Electrochaea commission new biomethanation reactor in US

Field studies have found that, generally, a roof fall takes place after certain amount of roof strata sagging. Recent applications of auto warning tell-tale (AWTT) instrument as an early warning system at different depillaring panels found it to be simple, economical and efficient during the coal pillar extraction (called depillaring). AWTT is able to watch the set value of roof sagging continuously in time. However, the application of AWTT experienced two practical issues: (i) fixing roof sagging warning value before the fall of overlying strata and (ii) deciding horizon above which its anchorage point of AWTT needs to be installed. Different field experiences noticed that an anchorage horizon at 10 m depth from the ceiling of a gallery works satisfactorily for goaf edge. But fixation of the roof sagging warning value, before the fall of overlying strata, is found to be complex. Generally, the warning value for a given site conditions is determined by extensive field monitoring and correlation of the roof sagging value at the goaf edge with corresponding roof falls. Field studies found that modulus of elasticity and thicknesses of immediate roof are important parameters in deciding the warning value of the roof sagging. These studies also indicated that the variation in size of the left-out ribs and goaf span influence the warning value. These observed facts about the warning value for an AWTT are studied in laboratory using a numerical modelling approach in FLAC3D. The results obtained through developed simulated models are found to be in close agreement with those of the field studies. Attempts are also made to quantify the influence of above-mentioned parameters over the warning value through collated results of different studied models. The obtained results of field and laboratory investigations are presented and discussed in this paper for strata control in a depillaring panel.

Roof sagging limit in an early warning system for safe coal pillar extraction

Field studies have found that, generally, a roof fall takes place after certain amount of roof strata sagging. Recent applications of auto warning tell-tale (AWTT) instrument as an early warning system at different depillaring panels found it to be simple, economical and efficient during the coal pillar extraction (called depillaring). AWTT is able to watch the set value of roof sagging continuously in time. However, the application of AWTT experienced two practical issues: (i) fixing roof sagging warning value before the fall of overlying strata and (ii) deciding horizon above which its anchorage point of AWTT needs to be installed. Different field experiences noticed that an anchorage horizon at 10 m depth from the ceiling of a gallery works satisfactorily for goaf edge. But fixation of the roof sagging warning value, before the fall of overlying strata, is found to be complex. Generally, the warning value for a given site conditions is determined by extensive field monitoring and correlation of the roof sagging value at the goaf edge with corresponding roof falls. Field studies found that modulus of elasticity and thicknesses of immediate roof are important parameters in deciding the warning value of the roof sagging. These studies also indicated that the variation in size of the left-out ribs and goaf span influence the warning value. These observed facts about the warning value for an AWTT are studied in laboratory using a numerical modelling approach in FLAC3D. The results obtained through developed simulated models are found to be in close agreement with those of the field studies. Attempts are also made to quantify the influence of above-mentioned parameters over the warning value through collated results of different studied models. The obtained results of field and laboratory investigations are presented and discussed in this paper for strata control in a depillaring panel.