A smart priority-based traffic control system for emergency vehicles
- Authors: Karmakar, Gour , Chowdhury, Abdullahi , Kamruzzaman, Joarder , Gondal, Iqbal
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 21, no. 14 (2021), p. 15849-15858
- Full Text: false
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- Description: Unwanted events on roads, such as incidents and increased traffic jams, can cause human lives and economic loss. For efficient incident management, it is essential to send Emergency Vehicles (EVs) to the incident place as quickly as possible. To reduce incidence clearance time, several approaches exist to provide a clear pathway to EVs mainly fitted with RFID sensors in the urban areas. However, they neither assign priority to the EVs based on the type and severity of an incident nor consider the effect on other on-road traffic. To address this issue, in this paper, we introduce an Emergency Vehicle Priority System (EVPS) by determining the priority level of an EV based on the type and the severity of an incident, and estimating the number of necessary signal interventions while considering the impact of those interventions on the traffic in the roads surrounding the EV's travel path. We present how EVPS determines the priority code and a new algorithm to estimate the number of green signal interventions to attain the quickest incident response while concomitantly reducing impact on others. A simulation model is developed in Simulation of Urban Mobility (SUMO) using the real traffic data of Melbourne, Australia, captured by various sensors. Results show that our system recommends appropriate number of intervention that can reduce emergency response time significantly. © 2001-2012 IEEE.
ADMM-based adaptive sampling strategy for nonholonomic mobile robotic sensor networks
- Authors: Le, Viet-Anh , Nguyen, Linh , Nghiem, Truong
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 21, no. 13 (2021), p. 15369-15378
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- Description: This paper discusses the adaptive sampling problem in a nonholonomic mobile robotic sensor network for efficiently monitoring a spatial field. It is proposed to employ Gaussian process to model a spatial phenomenon and predict it at unmeasured positions, which enables the sampling optimization problem to be formulated by the use of the log determinant of a predicted covariance matrix at next sampling locations. The control, movement and nonholonomic dynamics constraints of the mobile sensors are also considered in the adaptive sampling optimization problem. In order to tackle the nonlinearity and nonconvexity of the objective function in the optimization problem we first exploit the linearized alternating direction method of multipliers (L-ADMM) method that can effectively simplify the objective function, though it is computationally expensive since a nonconvex problem needs to be solved exactly in each iteration. We then propose a novel approach called the successive convexified ADMM (SC-ADMM) that sequentially convexify the nonlinear dynamic constraints so that the original optimization problem can be split into convex subproblems. It is noted that both the L-ADMM algorithm and our SC-ADMM approach can solve the sampling optimization problem in either a centralized or a distributed manner. We validated the proposed approaches in 1000 experiments in a synthetic environment with a real-world dataset, where the obtained results suggest that both the L-ADMM and SC-ADMM techniques can provide good accuracy for the monitoring purpose. However, our proposed SC-ADMM approach computationally outperforms the L-ADMM counterpart, demonstrating its better practicality. © 2001-2012 IEEE.
Effect of reactant types (steam, CO2 and steam + CO2) on the gasification performance of coal using entrained flow gasifier
- Authors: Shahabuddin, M. , Bhattacharya, Sankar
- Date: 2021
- Type: Text , Journal article
- Relation: International Journal of Energy Research Vol. 45, no. 6 (2021), p. 9492-9501
- Full Text: false
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- Description: This study investigates the gasification behaviour of bituminous coal using different reactants of CO2, steam and a mixture of CO2 and steam under entrained flow gasification conditions at temperatures of 1000°C and 1200°C with atmospheric pressure. The major gas constituents of the syngas were measured using online micro-GC with a model number Varian 490, whereas the minor pollutant gases were analysed using Kitagawa gas detection tubes. A maximum carbon conversion of 86% was achieved under steam gasification at a temperature of 1200°C compared to 74% from CO2 gasification. The higher carbon conversion from steam gasification is due to the higher gasification reactivity than CO2 gasification. At 1000°C, the lower heating value (LHV) from steam gasification was determined to be 60%, 70% and 80% higher than that of CO2 gasification using the reactant concentrations of 10, 20 and 40 vol.%, respectively. Using a stoichiometric 50/50 ratio of CO2 and steam, the yield of H2, CO and CH4 were increased by 56%, 106% and 35% compared to that of pure CO2 gasification. At 1000°C, the LHV under mixed reactant condition is close to the LHV from the pure steam gasification at 1200°C. In steam gasification, increasing the temperature by 200°C from 1000°C decreases the LHV by 17 and 10% using 10 and 20 vol.% steam. The higher heating value from steam gasification is due to the H2 and CH4-rich syngas compared to CO-rich syngas in CO2 gasification. The BET surface area of the solid char from steam gasification is about 17 and two times higher than that of CO2 gasification at 1000°C and 1200°C, respectively. © 2021 John Wiley & Sons Ltd
Energy poverty, children's wellbeing and the mediating role of academic performance : evidence from China
- Authors: Zhang, Quanda , Appau, Samuelson , Kodom, Peter
- Date: 2021
- Type: Text , Journal article
- Relation: Energy Economics Vol. 97, no. (2021), p.
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- Description: Using data from the China Family Panel Studies, we examine the effects of energy poverty on children's subjective wellbeing. We find that energy poverty reduces children's subjective wellbeing: a standard deviation increase in energy poverty is associated with 0.353 standard deviation decrease in subjective wellbeing. This general conclusion is robust to alternative ways of measuring subjective wellbeing and energy poverty, a suite of estimation techniques, and other sensitivity checks. Additionally, we find that academic performance is an important channel through which energy poverty lowers children's subjective wellbeing. Our findings point out the need to involve children both in household practices and policy decisions that seek to address energy poverty, especially when it pertains to the children's wellbeing. © 2021 Elsevier B.V.
Enhanced power extraction from thermoelectric generators considering non-uniform heat distribution
- Authors: Fauzan, Miftah , Muyeen, S. , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Energy Conversion and Management Vol. 246, no. (2021), p.
- Full Text: false
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- Description: In this paper, a technique to enhance the performances of the thermoelectric generator under non-uniform heat distribution is developed. A large area of heat source is needed when the thermoelectric generator is used for high power applications such as powering air conditioners, household appliances, and distributed generation systems. Non-uniform heat distribution is a natural phenomenon in large surface of heat source. A model was developed and was validated with a prototype of thermoelectric panel 80 V, 2 A. Results show very good similarities between the model and the prototype outputs under various operating conditions. The error during the tests for the voltage performances was 6.5%, while the current was 1.1%. A method of maximizing power, i.e., developing a specialized maximum power point tracker (MPPT) along with blocking diodes, is proposed to overcome the effects of non-uniform heat distribution. In a typical condition, the output power dropped by 30% when a non-uniform thermal distribution is imposed to the array. The blocking diode can save power by 15%, and the MPPT expands up to 20% power when adopting this method. © 2021
Evolution of twinning during cyclic loading of magnesium alloy examined by quasi-in-situ EBSD
- Authors: Fallahi, Hossein , Davies, Chris
- Date: 2021
- Type: Text , Journal article
- Relation: Materials Science and Engineering A Vol. 820, no. (2021), p.
- Full Text: false
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- Description: Most complex engineering components experience varied loading in use. We conducted successive experiments of cyclic tensile deformation followed by electron-backscattered diffraction imaging of the same area on each of several magnesium alloy (ZM) sample to investigate the microstructure and texture evolution during cyclic loading. In this way we correlated the evolving deformed microstructure of cyclically loaded magnesium to the initial grain orientations. To investigate the effects of the strain path, the behaviour of samples with and without pre-compression was compared. Twins can propagate from grain to grain and twin chains will form in the material without any pre-deformation. Twin chains are a result of twin transmission at grain boundaries and twin transmission frequency decreases with increasing grain boundary angles. In the absence of pre-compression, the extension twin fraction rises from 0.003 to 0.019 after two cycles of tensile loading to a strain of 0.03, after which it changes only slightly as strain is increased. Twin chains in the pre-compressed specimen are activated without any obvious dependence on the matrix orientation. The fraction of extension twinning is 0.2 for the pre-compressed specimen. After a cycle of tensile loading to a total plastic strain of 0.015, 90% of the extension twins undergo detwinning. The detwinning starts just after reverse loading. Secondary twins forming within primary twin interfaces start to nucleate in the microstructure of the pre-compressed material at an early stage (at plastic strain values of 0.056). This is different from the nucleation of secondary twins in the material without pre-compression that occurs at a strain of 0.104. The early formation of secondary twinning is due to the presence of residual primary twins in the microstructure of the pre-compressed material as a result of detwinning of the initial twins. © 2021
Geometric design of the limaçon-to-circular fluid processing machine
- Authors: Phung, Truong , Sultan, Ibrahim
- Date: 2021
- Type: Text , Journal article
- Relation: Journal of Mechanical Design, Transactions of the ASME Vol. 143, no. 10 (2021), p.
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- Description: A limaçon machine is a rotary positive displacement device, in which the housing and rotor are constructed of limaçon of Pascal curves. Previous works have been published to investigate the working of these machines in two applications: gas expanders and compressors. This article presents a theoretical investigation into the potential of modifying the rotor profile of the limaçon machines to simplify the machine's manufacturing process and to reduce production cost. The proposed modification will produce new characteristics for the housing-rotor interaction. An outcome that motivates the need to obtain new mathematical models to investigate the housing-rotor interference and describe the volumetric relationship of the new machine. This article also employs an optimization approach to design the best machine for a given set of operating conditions, i.e., expander, compressor, and pump. The outcome of this study confirms the validity of the proposed modification and its potential to produce a limaçon machine with favorable characteristics. Copyright © 2021 by ASME
Mobile robotic sensors for environmental monitoring using gaussian markov random field
- Authors: Nguyen, Linh , Kodagoda, Sarath , Ranasinghe, Ravindra , Dissanayake, Gamini
- Date: 2021
- Type: Text , Journal article
- Relation: Robotica Vol. 39, no. 5 (2021), p. 862-884
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- Description: This paper addresses the issue of monitoring spatial environmental phenomena of interest utilizing information collected by a network of mobile, wireless, and noisy sensors that can take discrete measurements as they navigate through the environment. It is proposed to employ Gaussian Markov random field (GMRF) represented on an irregular discrete lattice by using the stochastic partial differential equations method to model the physical spatial field. It then derives a GMRF-based approach to effectively predict the field at unmeasured locations, given available observations, in both centralized and distributed manners. Furthermore, a novel but efficient optimality criterion is then proposed to design centralized and distributed adaptive sampling strategies for the mobile robotic sensors to find the most informative sampling paths in taking future measurements. By taking advantage of conditional independence property in the GMRF, the adaptive sampling optimization problem is proven to be resolved in a deterministic time. The effectiveness of the proposed approach is compared and demonstrated using pre-published data sets with appealing results. Copyright © The Author(s), 2020. Published by Cambridge University Press.
Multi-variate data fusion technique for reducing sensor errors in intelligent transportation systems
- Authors: Manogaran, Gunasekaran , Balasubramanian, Venki , Rawal, Bharat , Saravanan, Vijayalakshmi , Montenegro-Marin, Carlos
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 21, no. 14 (2021), p. 15564-15573
- Full Text: false
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- Description: Connected vehicles in intelligent transportation system (ITS) scenario rely on environmental data for supporting user-centric applications along the driving time. Sensors equipped in the vehicles are responsible for accumulating data from the environment, followed by the fusion process. Such fusion process provides accurate and stable data required for the applications in a recurrent manner. In order to enhance the data fusion of connected vehicles, this article introduces multi-variate data fusion (MVDF) technique. This technique is competent in handling asynchronous and discrete data from the environment and streamlining them into continuous and delay-less inputs for the applications. The process of data fusion is aided through least square regression learning to determine the errors in different time instances. The indefinite and definite data fusion instances are differentiated using this regression model to identify the errors in fore-hand. Besides, the differentiation relies on the application run-time interval to progress data fusion within the same or extended time instance and data slots. In this manner the differentiation along with the error identification is regular until the application required data is met. The performance of this technique is verified using network simulator experiments for the metrics error, data utilization ratio, and computation time. The results show that this technique improves data utilization under controlled time and fewer errors. © 2001-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Venki Balasubramanian” is provided in this record**.
Real-time localisation system for GPS-denied open areas using smart street furniture
- Authors: Nassar, Mohamed , Luxford, Len , Cole, Peter , Oatley, Giles , Koutsakis, Polychronis
- Date: 2021
- Type: Text , Journal article
- Relation: Simulation Modelling Practice and Theory Vol. 112, no. (2021), p.
- Full Text: false
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- Description: Wifi-based localisation systems have gained significant interest with many researchers proposing different localisation techniques using publicly available datasets. However, these datasets are limited because they only contain Wifi fingerprints collected and labelled by users, and they are restricted to indoor locations. We have generated the first Wifi-based localisation datasets for a GPS-denied open area. We selected a busy open area at Murdoch University to generate the datasets using so-called “smart bins”, which are rubbish bins that we enabled to work as access points. The data gathered consists of two different datasets. In the first, four users generated labelled WiFi fingerprints for all available Reference Points using four different smartphones. The second dataset includes 2450865 auto-generated rows received from more than 1000 devices. We have developed a light-weight algorithm to label the second dataset from the first and we proposed a localisation approach that converts the second dataset from asynchronous format to synchronous, applies feature engineering and a deep learning classifier. Finally, we have demonstrated via simulations that by using this approach we achieve higher prediction accuracy, with up to 19% average improvement, compared with using only the fingerprint dataset. © 2021 Elsevier B.V.
Robust modelling of implicit interfaces by the scaled boundary finite element method
- Authors: Dsouza, Shaima , Pramod, A. L. N. , Ooi, Ean Tat , Song, Chongming , Natarajan, Sundararajan
- Date: 2021
- Type: Text , Journal article
- Relation: Engineering Analysis with Boundary Elements Vol. 124, no. (2021), p. 266-286
- Full Text: false
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- Description: In this paper, we propose a robust framework based on the scaled boundary finite element method to model implicit interfaces in two-dimensional differential equations in nonhomegeneous media. The salient features of the proposed work are: (a) interfaces can be implicitly defined and need not conform to the background mesh; (b) Dirichlet boundary conditions can be imposed directly along the interface; (c) does not require special numerical integration technique to compute the bilinear and the linear forms and (d) can work with an efficient local mesh refinement using hierarchical background meshes. Numerical examples involving straight interface, circular interface and moving interface problems are solved to validate the proposed technique. Further, the presented technique is compared with conforming finite element method in terms of accuracy and convergence. From the numerical studies, it is seen that the proposed framework yields solutions whose error is O(h2) in L2 norm and O(h) in the H1 semi-norm. Further the condition number increases with the mesh size similar to the FEM. © 2021 Elsevier Ltd
Smart sensing-enabled decision support system for water scheduling in orange orchard
- Authors: Khan, Rahim , Zakarya, Muhammad , Balasubramanian, Venki , Jan, Mian , Menon, Varun
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Sensors Journal Vol. 21, no. 16 (2021), p. 17492-17499
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- Description: The scarcity of water resources throughout the world demands its optimum utilization in various sectors. Smart Sensing-enabled irrigation management systems are the ideal solutions to ensure the optimum utilization of water resources in the agriculture sector. This paper presents a wireless sensor network-enabled Decision Support System (DSS) for developing a need-based irrigation schedule for the orange orchard. For efficient monitoring of various in-field parameters, our proposed approach uses the latest smart sensing technology such as soil moisture, leaf-wetness, temperature and humidity. The proposed smart sensing-enabled test-bed was deployed in the orange orchard of our institute for approximately one year and successfully adjusted its irrigation schedule according to the needs and demands of the plants. Moreover, a modified Longest Common SubSequence (LCSS) mechanism is integrated with the proposed DSS for distinguishing multi-valued noise from the abrupt changing scenarios. To resolve the concurrent communication problem of two or more wasp-mote sensor boards with a common receiver, an enhanced RTS/CTS handshake mechanism is presented. Our proposed DSS compares the most recently refined data with pre-defined threshold values for efficient water management in the orchard. Irrigation activity is scheduled if water deficit criterion is met and the farmer is informed accordingly. Both the experimental and simulation results show that the proposed scheme performs better in comparison to the existing schemes. © 2001-2012 IEEE.
When does daylight saving time save electricity? Weather and air-conditioning
- Authors: Guven, Cahit , Yuan, Haishan , Zhang, Quanda , Aksakalli, Vural
- Date: 2021
- Type: Text , Journal article
- Relation: Energy Economics Vol. 98, no. (2021), p.
- Full Text: false
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- Description: Previous research on the effects of daylight saving time (DST) on electricity consumption has provided mixed results. We use daily state-level panel data on electricity consumption in Australia between 1998 and 2015, during which period there was considerable variation in the presence and timing of DST implementation, as well as in weather conditions and cooling usage within and between states. This provides us with a unique opportunity to study the interaction effects of DST with exogenous variation in daily weather conditions and cooling usage over two decades. Our results show that the effect of DST on electricity consumption depends strongly on weather conditions and cooling usage. Forward DST increases the electricity consumption when temperatures and air conditioner ownership are higher. We provide simulations for countries in the European Union that need to decide on DST adoption in the coming year. Our findings are policy-relevant given rising temperatures and worldwide increases in cooling usage during summer. © 2021 Elsevier B.V.
A combined virtual element method and the scaled boundary finite element method for linear elastic fracture mechanics
- Authors: Adak, Dibyendu , Pramod, ALN , Ooi, Ean Tat , Natarajan, Sundararajan
- Date: 2020
- Type: Text , Journal article
- Relation: Engineering Analysis with Boundary Elements Vol. 113, no. (2020), p. 9-16
- Full Text: false
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- Description: In this paper, we propose a framework that combines the recently introduced virtual element method (VEM) and the scaled boundary finite element method (SBFEM) to evaluate the fracture parameters. The domain is discretized with arbitrary polygons and the element that contains the crack tip is treated within the framework of the SBFEM. This facilitates a semi-analytical treatment of the crack tip singularity allowing the fracture parameters are estimated directly from the definition. The VEM is employed for the rest of the domain. The salient feature of the VEM is that the terms in the stiffness matrix are computed without requiring higher order quadrature schemes. As both the methods satisfy partition of unity and the compatibility condition, the matrices are assembled as in the conventional FEM. The accuracy of the proposed formulation is demonstrated with two standard benchmark examples. The proposed VEM-SBFEM framework yields accurate results. © 2019 Elsevier Ltd
A dual scaled boundary finite element formulation over arbitrary faceted star convex polyhedra
- Authors: Ooi, Ean Tat , Saputra, Albert , Natarajan, Sundararajan , Ooi, Ean Hin , Song, Chongmin
- Date: 2020
- Type: Text , Journal article
- Relation: Computational Mechanics Vol. 66, no. 1 (2020), p. 27-47
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- Description: A novel technique to formulate arbritrary faceted polyhedral elements in three-dimensions is presented. The formulation is applicable for arbitrary faceted polyhedra, provided that a scaling requirement is satisfied and the polyhedron facets are planar. A triangulation process can be applied to non-planar facets to generate an admissible geometry. The formulation adopts two separate scaled boundary coordinate systems with respect to: (i) a scaling centre located within a polyhedron and; (ii) a scaling centre on a polyhedron’s facets. The polyhedron geometry is scaled with respect to both the scaling centres. Polygonal shape functions are derived using the scaled boundary finite element method on the polyhedron facets. The stiffness matrix of a polyhedron is obtained semi-analytically. Numerical integration is required only for the line elements that discretise the polyhedron boundaries. The new formulation passes the patch test. Application of the new formulation in computational solid mechanics is demonstrated using a few numerical benchmarks. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
An efficient 3-D model for remaining wall thicknesses of cast iron pipes in nondestructive testing
- Authors: Nguyen, Linh , Miro, Jaime
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Sensors Letters Vol. 4, no. 7 (2020), p.
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- Description: Over 50% of global pipes have been made of cast iron, and most of them are aging. In order to effectively estimate possibilities of their failures, which is paramount for efficiently managing asset infrastructures, it requires the remaining wall thickness (RWT) of a pipe to be known. In fact, RWT of the cast iron pipes can be primarily measured by the magnetism based nondestructive testing technologies though they are quite slow. To speed up the inspection process, it is proposed to sense RWT of a part of a pipe and then employ a model to predict RWT in the rest. Thus, this letter introduces a 3-D model to efficiently represent RWT of a pipe given measurements collected intermittently on the pipe's surface. The proposed model first transforms 3-D cylindrical coordinates to 3-D Cartesian coordinates before modeling RWT by Gaussian processes (GP). The transformation allows GP to work properly on RWT data gathered on a cylindrical pipe and effectively predict RWT at unmeasured locations. Moreover, periodicity of RWT along circumference of the pipe is naturally integrated. The effectiveness of the proposed approach is demonstrated by implementation in two real life inservice aging cast iron pipes, where the obtained results are highly promising. © 2017 IEEE.
Automated health condition diagnosis of in situ wood utility poles using an intelligent non-destructive evaluation (NDE) framework
- Authors: Yu, Yang , Subhani, Mahbube , Hoshyar, Azadeh , Li, Jianchun , Li, Huan
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Structural Stability and Dynamics Vol. 20, no. 10 (2020), p.
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- Description: Wood utility poles are widely applied in power transmission and telecommunication systems in Australia. Because of a variety of external influence factors, such as fungi, termite and environmental conditions, failure of poles due to the wood degradation with time is of common occurrence with high degree uncertainty. The pole failure may result in serious consequences including both economic and public safety. Therefore, accurately and timely identifying the health condition of the utility poles is of great significance for economic and safe operation of electricity and communication networks. In this paper, a novel non-destructive evaluation (NDE) framework with advanced signal processing and artificial intelligence (AI) techniques is developed to diagnose the condition of utility pole in field. To begin with, the guided waves (GWs) generated within the pole is measured using multi-sensing technique, avoiding difficult interpretation of various wave modes which cannot be detected by only one sensor. Then, empirical mode decomposition (EMD) and principal component analysis (PCA) are employed to extract and select damage-sensitive features from the captured GW signals. Additionally, the up-to-date machine learning (ML) techniques are adopted to diagnose the health condition of the pole based on selected signal patterns. Eventually, the performance of the developed NDE framework is evaluated using the field testing data from 15 new and 24 decommissioned utility poles at the pole yard in Sydney. © 2020 World Scientific Publishing Company.
- Description: This research is supported by Australian Research Council via Linkage Project (LP110200162) and Industrial Transforming Research Hub for Nanoscience Based Construction Materials Manufacturing (IH150100006) as well as Ausgrid. The authors greatly appreciate the ¯nancial and technical supports from the funding bodies.
Comparative approaches to probabilistic finite element methods for slope stability analysis
- Authors: Dyson, Ashley , Tolooiyan, Ali
- Date: 2020
- Type: Text , Journal article
- Relation: Simulation Modelling Practice and Theory Vol. 100, no. (2020), p.
- Full Text: false
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- Description: Probabilistic slope stability analyses are often preferable to deterministic methods when soils are inherently heterogeneous, or the reliability of geotechnical parameters is largely unknown. These methods are suitable for evaluating the risk of slope failure by producing a range of potential scenarios for the slope stability factor of safety. Several probabilistic methods including the Point Estimate Method, Monte Carlo Method and Random Finite Element Method, can be combined with the Finite Element technique. In this study, various shear strength distributions are considered for three different probabilistic Finite Element Methods to determine Factor of Safety and Probability of Failure distributions, based on the associated method of slope stability analysis. Results are presented for a case study of an Australian open-cut coal mine, with a range of shear strength parameter distributions for coal and interseam cohesive materials considered. Coal and interseam shear strength parameters are varied independently, to determine the effects of each material on the slope Factor of Safety. © 2019 Elsevier B.V.
Design and optimisation of drainage systems for fractured slopes using the XFEM and FEM
- Authors: Shaghaghi, Tahereh , Ghadrdan, Mohsen , Tolooiyan, Ali
- Date: 2020
- Type: Text , Journal article
- Relation: Simulation Modelling Practice and Theory Vol. 103, no. (2020), p.
- Full Text: false
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- Description: The reliable and optimised design of a drainage system for saturated slopes is often a challenging geotechnical task. Such a task becomes even more challenging when a slope contains pre-existing joints and discontinuities. In saturated and semi-saturated conditions, the existence of joints may lead to a complex distribution of pore water pressure within the slope, affecting the effective stress distribution and the stability of the slope. This paper aims to study the effect of horizontal borehole drainage systems with different arrangements on pore water pressure distributions within a saturated fractured slope. In this study, several coupled pore fluid diffusion and stress-strain analyses were conducted using the e-Xtended Finite Element Method (XFEM) in conjunction with the Finite Element Method (FEM) to simulate the efficiency of a drainage system of a deep slope at the second largest open-cut mine in Australia. As one of the objectives of this study, the effect of water flow inside a joint and normal to the joint surface (normal flow) is considered as an essential simulation component. The results show that the pore water pressure distribution at the vicinity of the joint is considerably influenced by the magnitude of normal flow. Such influence should be taken into account when designing a drainage system, as the magnitude of normal flow and the performance of the drainage system may affect each other directly. © 2020 Elsevier B.V.
Effect of rock mass permeability and rock fracture leak-off coefficient on the pore water pressure distribution in a fractured slope
- Authors: Shaghaghi, Tahereh , Ghadrdan, Mohsen , Tolooiyan, Ali
- Date: 2020
- Type: Text , Journal article
- Relation: Simulation Modelling Practice and Theory Vol. 105, no. (2020), p. 1-13
- Full Text: false
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- Description: The reliable assessment of the stability of saturated slopes becomes a challenging task when slopes are consisting of discontinuous materials and containing pre-existing joints. The discontinuous nature of the slopes' material could increase the overall permeability of the slope, while existing joints facilitate groundwater leakage through the joint surfaces into the slope which subsequently exerts a major impact on deformation and the effective stress distribution. This paper aims to study the Pore Water Pressure (PWP) distribution changes in a saturated fractured slope by conducting advanced coupled pore fluid diffusion and stress-strain analyses, while investigating the sensitivity of results to the variation of permeability and leakage properties of fracture surfaces. Modelling of jointed slopes is carried out using the e-Xtended Finite Element Method (XFEM) in conjunction with the Finite Element Method (FEM). In this study, the fluid flow inside the joint is the major focus at which the constitutive response of the fluid inside the joint considers both tangential and normal flows. To demonstrate the state-of-the-art simulation technique presented in this paper, simulation of a fractured slope at the second largest open-pit mine in Australia is performed as a case study. This study shows the effect of a variable leak-off coefficient of the joint surfaces and the permeability magnitude on the pore water pressure distribution.
- Description: This research has been supported financially by the Earth Resources Regulation of the Victorian State Government Department of Economic Development, Jobs, Transport and Resources. The first and second authors are funded by the GHERG LV Batter Stability Project Scholarship and Faculty Tuition Scholarship of Federation University Australia.