A Structural Failure Model for the Rock Mass with a Discontinuous Weak Structural Plane

2012 ◽  
Vol 204-208 ◽  
pp. 135-138
Author(s):  
Xi Hua Chu ◽  
Qing Hui Jiang ◽  
Bin Wang
Keyword(s):  
Rock Mass ◽  
Present Model ◽  
Particle Flow Code ◽  
Failure Model ◽  
Structural Failure ◽  
Structural Plane ◽  
Proposed Model ◽  
Coulomb Model ◽  
And Performance ◽  
Mass Rock

A structural failure model is presented for the rock mass with a discontinuous weak structural plane. The present model takes into account the effect of weakening of both deformation and strength parameters. And it can degenerates into classical Mohr-Coulomb model or Jaeger model according to corresponding conditions. The numerical tests by Particle Flow Code demonstrate that the capability and performance of the proposed model in capturing behaviors of the mass rock.

The Influence of Cognitive and Affective Reactions to Feedback on Subsequent Goals

2010 ◽  
Vol 15 (2) ◽  
pp. 121-131 ◽  
Author(s):  
Remus Ilies ◽  
Timothy A. Judge ◽  
David T. Wagner
Keyword(s):  
Performance Feedback ◽  
Business School ◽  
Structural Equation ◽  
Emotional Reactions ◽  
Equation Model ◽  
Proposed Model ◽  
And Performance ◽  
Dispositional Measure ◽  
The Relationship ◽  
Reactions To Feedback

This paper focuses on explaining how individuals set goals on multiple performance episodes, in the context of performance feedback comparing their performance on each episode with their respective goal. The proposed model was tested through a longitudinal study of 493 university students’ actual goals and performance on business school exams. Results of a structural equation model supported the proposed conceptual model in which self-efficacy and emotional reactions to feedback mediate the relationship between feedback and subsequent goals. In addition, as expected, participants’ standing on a dispositional measure of behavioral inhibition influenced the strength of their emotional reactions to negative feedback.

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

Application of an Element-free Galerkin Method to Water Wave Propagation Problems

2014 ◽  
Vol 60 (1-4) ◽  
pp. 87-105 ◽  
Author(s):  
Ryszard Staroszczyk
Keyword(s):  
Wave Propagation ◽  
Galerkin Method ◽  
Present Model ◽  
Free Surface Elevation ◽  
Element Free Galerkin Method ◽  
Plane Flow ◽  
Element Free Galerkin ◽  
Proposed Model ◽  
Sloping Bed ◽  
Element Free

Abstract The paper is concerned with the problem of gravitational wave propagation in water of variable depth. The problem is solved numerically by applying an element-free Galerkin method. First, the proposed model is validated by comparing its predictions with experimental data for the plane flow in water of uniform depth. Then, as illustrations, results of numerical simulations performed for plane gravity waves propagating through a region with a sloping bed are presented. These results show the evolution of the free-surface elevation, displaying progressive steepening of the wave over the sloping bed, followed by its attenuation in a region of uniform depth. In addition, some of the results of the present model are compared with those obtained earlier by using the conventional finite element method.

scholarly journals Finite-difference based response surface methodology to optimize tailgate support systems in longwall coal mining

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Satar Mahdevari ◽  
Mohammad Hayati
Keyword(s):  
Compressive Strength ◽  
Response Surface Methodology ◽  
Rock Mass ◽  
Finite Difference ◽  
Longwall Mining ◽  
Support Systems ◽  
Rock Mass Rating ◽  
Slake Durability Index ◽  
Proposed Model ◽  
Durability Index

AbstractDesigning a suitable support system is of great importance in longwall mining to ensure the safe and stable working conditions over the entire life of the mine. In high-speed mechanized longwall mining, the most vulnerable zones to failure are roof strata in the vicinity of the tailgate roadway and T-junctions. Severe roof displacements are occurred in the tailgate roadway due to the high-stress concentrations around the exposed roof span. In this respect, Response Surface Methodology (RSM) was utilized to optimize tailgate support systems in the Tabas longwall coal mine, northeast of Iran. The nine geomechanical parameters were obtained through the field and laboratory studies including density, uniaxial compressive strength, angle of internal friction, cohesion, shear strength, tensile strength, Young’s modulus, slake durability index, and rock mass rating. A design of experiment was developed through considering a Central Composite Design (CCD) on the independent variables. The 149 experiments are resulted based on the output of CCD, and were introduced to a software package of finite difference numerical method to calculate the maximum roof displacements (dmax) in each experiment as the response of design. Therefore, the geomechanical variables are merged and consolidated into a modified quadratic equation for prediction of the dmax. The proposed model was executed in four approaches of linear, two-factor interaction, quadratic, and cubic. The best squared correlation coefficient was obtained as 0.96. The prediction capability of the model was examined by testing on some unseen real data that were monitored at the mine. The proposed model appears to give a high goodness of fit with the accuracy of 0.90. These results indicate the accuracy and reliability of the developed model, which may be considered as a reliable tool for optimizing or redesigning the support systems in longwall tailgates. Analysis of variance (ANOVA) was performed to identify the key variables affecting the dmax, and to recognize their pairwise interaction effects. The key parameters influencing the dmax are respectively found to be slake durability index, Young’s modulus, uniaxial compressive strength, and rock mass rating.

scholarly journals Natural Disasters Intensity Analysis and Classification Based on Multispectral Images Using Multi-Layered Deep Convolutional Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2648
Author(s):  
Muhammad Aamir ◽  
Tariq Ali ◽  
Muhammad Irfan ◽  
Ahmad Shaf ◽  
Muhammad Zeeshan Azam ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Natural Disasters ◽  
Deep Convolutional Neural Network ◽  
Multispectral Images ◽  
Learning Techniques ◽  
Proposed Model ◽  
Disaster Intensity ◽  
And Performance

Natural disasters not only disturb the human ecological system but also destroy the properties and critical infrastructures of human societies and even lead to permanent change in the ecosystem. Disaster can be caused by naturally occurring events such as earthquakes, cyclones, floods, and wildfires. Many deep learning techniques have been applied by various researchers to detect and classify natural disasters to overcome losses in ecosystems, but detection of natural disasters still faces issues due to the complex and imbalanced structures of images. To tackle this problem, we propose a multilayered deep convolutional neural network. The proposed model works in two blocks: Block-I convolutional neural network (B-I CNN), for detection and occurrence of disasters, and Block-II convolutional neural network (B-II CNN), for classification of natural disaster intensity types with different filters and parameters. The model is tested on 4428 natural images and performance is calculated and expressed as different statistical values: sensitivity (SE), 97.54%; specificity (SP), 98.22%; accuracy rate (AR), 99.92%; precision (PRE), 97.79%; and F1-score (F1), 97.97%. The overall accuracy for the whole model is 99.92%, which is competitive and comparable with state-of-the-art algorithms.

scholarly journals Study of Rock Mass Rating (RMR) and Geological Strength Index (GSI) Correlations in Granite, Siltstone, Sandstone and Quartzite Rock Masses

2021 ◽  
Vol 11 (8) ◽  
pp. 3351
Author(s):  
Gabor Somodi ◽  
Neil Bar ◽  
László Kovács ◽  
Marco Arrieta ◽  
Ákos Török ◽  
...  
Keyword(s):  
Rock Mass ◽  
Linear Equations ◽  
Geological Strength Index ◽  
Gold Mine ◽  
Strength Index ◽  
Comprehensive Understanding ◽  
Rock Types ◽  
Mass Classification ◽  
Waste Repository ◽  
And Performance

A comprehensive understanding of geological, structural geological, hydrogeological and geotechnical features of the host rock are essential for the design and performance evaluation of surface and underground excavations. The Hungarian National Radioactive Waste Repository (NRWR) at Bátaapáti is constructed in a fractured granitic formation, and Telfer Gold Mine in Australia is excavated in stratified siltstones, sandstones and quartzites. This study highlights relationships between GSI chart ratings and calculated GSI values based on RMR rock mass classification data. The paper presents linear equations for estimating GSI from measured RMR89 values. Correlations between a and b constants were analyzed for different rock types, at surface and subsurface settings.

Leader–follower narcissism and subgroup formation in teams: a conceptual model

2019 ◽  
Vol 34 (6) ◽  
pp. 429-442 ◽  
Author(s):  
Manuel London
Keyword(s):  
Team Performance ◽  
Team Identification ◽  
Goal Congruence ◽  
Content Type ◽  
Team Outcomes ◽  
Performance Pressure ◽  
Proposed Model ◽  
Leaders And Followers ◽  
Trait Activation ◽  
And Performance

Purpose Drawing on existing theory, a model is developed to illustrate how the interaction between leaders and followers similarity in narcissism and goal congruence may influence subgroup formation in teams, and how this interaction influences team identification and team performance. Design/methodology/approach The proposed model draws on dominance complementary, similarity attraction, faultline formation and trait activation theories. Findings Leader–follower similarity in narcissism and goal congruence may stimulate subgroup formation, possibly resulting in conformers, conspirators, outsiders and victims, especially when performance pressure on a team is high. Followers who are low in narcissism and share goals with a leader who is narcissistic are likely to become conformers. Followers who are high in narcissism and share goals with a narcissistic leader are likely to become confederates. Followers who do not share goals with a narcissistic leader will be treated by the leader and other members as outsiders if they are high in narcissism, and victimized if they are low in narcissism. In addition, the emergence of these subgroups leads to reduced team identification and lower team performance. Practical implications Higher level managers, coaches and human resource professions can assess and, if necessary, counteract low team identification and performance resulting from the narcissistic personality characteristics of leaders and followers. Originality/value The model addresses how and under what conditions narcissistic leaders and followers may influence subgroup formation and team outcomes.

Modeling and performance analysis of diesel engine considering the heating effect of blow-by on cylinder intake gas

2021 ◽  
pp. 146808742110692
Author(s):  
Zhenyu Shen ◽  
Yanjun Li ◽  
Nan Xu ◽  
Baozhi Sun ◽  
Yunpeng Fu ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Engine Performance ◽  
Marine Diesel Engine ◽  
Heating Effect ◽  
Shipping Industry ◽  
Low Speed ◽  
Proposed Model ◽  
International Regulations ◽  
Marine Diesel ◽  
And Performance

Recently, the stringent international regulations on ship energy efficiency and NOx emissions from ocean-going ships make energy conservation and emission reduction be the theme of the shipping industry. Due to its fuel economy and reliability, most large commercial vessels are propelled by a low-speed two-stroke marine diesel engine, which consumes most of the fuel in the ship. In the present work, a zero-dimensional model is developed, which considers the blow-by, exhaust gas bypass, gas exchange, turbocharger, and heat transfer. Meanwhile, the model is improved by considering the heating effect of the blow-by gas on the intake gas. The proposed model is applied to a MAN B&W low-speed two-stroke marine diesel engine and validated with the engine shop test data. The simulation results are in good agreement with the experimental results. The accuracy of the model is greatly improved after considering the heating effect of blow-by gas. The model accuracy of most parameters has been improved from within 5% to within 2%, by considering the heating effect of blow-by gas. Finally, the influence of blow-by area change on engine performance is analyzed with considering and without considering the heating effect of blow-by.

ARRHYTHMIA DIAGNOSIS FROM ECG SIGNAL ANALYSIS USING STATISTICAL FEATURES AND NOVEL CLASSIFICATION METHOD

2021 ◽  
pp. 2150025
Author(s):  
SAURAV MANDAL ◽  
NABANITA SINHA
Keyword(s):  
Cardiac Arrhythmia ◽  
Present Model ◽  
Fluctuation Analysis ◽  
Statistical Features ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Ecg Signals ◽  
Proposed Model ◽  
Electrocardiogram Ecg ◽  
Detrended Fluctuation ◽  
Heart Condition

This study aims to present an efficient model for autodetection of cardiac arrhythmia by the diagnosis of self-affinity and identification of governing processes of a number of Electrocardiogram (ECG) signals taken from MIT-BIH database. In this work, the proposed model includes statistical methods to find the diagnosis pattern for detecting cardiac abnormalities which is useful for the computer aided system for arrhythmia detection. First, the Rescale Range (R/S) analysis has been employed for ECG signals to understand the scaling property of ECG signals. The value of Hurst exponent identifies the presence of abnormality in ECG signals taken for consideration with 92.58% accuracy. In this study, Higuchi method which deals with unifractality or monofractality of signals has been applied and it is found that unifractality is sufficient to detect arrhythmia with 91.61% accuracy. The Multifractal Detrended Fluctuation Analysis (MFDFA) has been used over the present signals to identify and confirm the multifractality. The nature of multifractality is different for arrhythmia patients and normal heart condition. The multifractal analysis is useful to detect abnormalities with 93.75% accuracy. Finally, the autocorrelation analysis has been used to identify the prevalent governing process in the present arrhythmic ECG signals and study confirms that all the signals are governed by stationary autoregressive methods of certain orders. In order to increase the overall efficiency, this present model deals with analyzing all the statistical features extracted from different statistical techniques for a large number of ECG signals of normal and abnormal heart condition. Finally, the result of present analysis altogether possibly indicates that the proposed model is efficient to detect cardiac arrhythmia with 99.3% accuracy.

Performance measurement and resource sharing among business sub-units in the presence of non-discretionary factors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rita Shakouri ◽  
Maziar Salahi
Keyword(s):  
Resource Sharing ◽  
Content Type ◽  
Development Level ◽  
Proposed Model ◽  
Decision Making Unit ◽  
Efficiency Estimation ◽  
Overall Efficiency ◽  
And Performance ◽  
The Right ◽  
The Impact

Purpose This paper aims to apply a new approach for resource sharing and efficiency estimation of subunits in the presence of non-discretionary factors and partial impacts among inputs and outputs in the data envelopment analysis (DEA) framework. Design/methodology/approach First, inspired by the Imanirad et al.’s model (2013), the authors consider that each decision-making unit (DMU) may consist of several subunits, that each of which can be affected by non-discretionary inputs. After that, the Banker and Morey’s model (1996) is used for modeling non-discretionary factors. For measuring performance of several subunits, which can be considered as DMUs, the aggregate efficiency is suggested. At last, the overall efficiency is computed and compared with each other. Findings One of the important features of proposed model is that each output in this model applies discretionary input according to its need; therefore, the result of this study will make it easier for the managers to make better decisions. Also, it indicates that significant predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the influence of non-discretionary input. Therefore, the proposed model provides a more reasonable and encompassing measure of performance in participating non-discretionary and discretionary inputs to better efficiency. An application of the proposed model for gaining efficiency of 17 road patrols is provided. Research limitations/implications More non-discretionary and discretionary inputs can be taken into consideration for a better analysis. This study provides us with a framework for performance measures along with useful managerial insights. Focusing upon the right scope of operations may help out the management in improving their overall efficiency and performance. In the recent highway maintenance management systems, the environmental differences exist among patrols and other geotechnical services under the climate diverse. Further, in some cases, there might exist more than one non-discretionary factor that can have different effects on the subunits’ performance. Practical implications The purpose of this paper was to measure the performance of a set of the roadway maintenance crews and to analyze the impact of non-discretionary inputs on the efficiency of the roadway maintenance. The application of the proposed model, on the one hand, showed that each output in this model uses discretionary input according to its requirement, and on the other hand, the result showed that meaningful predictions of the development of the overall efficiency of DMUs can be based on observing the development level of subunits because of the impact of non-discretionary input. Originality/value Providing information on resource sharing by taking into account non-discretionary factors for each subunit can help managers to make better decisions to increase the efficiency.

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