Search results for: discrete wavelet transforms

Authors: Lei Bi, Yunpeng Jiao, Chunjiang Liu, Jianhua Chen, Wei Ge

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Two energy paths are proposed from thermodynamic viewpoints. Energy consumption means total power input to the specific system, and it can be decomposed into energy retention and energy dissipation. Energy retention is the variation of accumulated mechanical energy in the system, and energy dissipation is the energy converted to heat by irreversible processes. Based on the Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) framework, different energy terms are quantified from the specific flow elements of fluid cells and particles as well as their interactions with the wall. Direct energy consumption statistics are carried out for both cold and hot flow in gas-solid fluidization systems. To clarify the statistic method, it is necessary to identify which system is studied: the particle-fluid system or the particle sub-system. For the cold flow, the total energy consumption of the particle sub-system can predict the onset of bubbling and turbulent fluidization, while the trends of local energy consumption can reflect the dynamic evolution of mesoscale structures. For the hot flow, different heat transfer mechanisms are analyzed, and the original solver is modified to reproduce the experimental results. The influence of the heat transfer mechanisms and heat source on energy consumption is also investigated. The proposed statistic method has proven to be energy-conservative and easy to conduct, and it is hopeful to be applied to other multiphase flow systems.

Keywords: energy consumption statistic, gas-solid fluidization, CFD-DEM, regime transition, heat transfer mechanism

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Authors: Nuo Duan, Yi Pik Cheng

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This paper presents the data of a series of two-dimensional Discrete Element Method (DEM) simulations of a large-diameter rigid monopile subjected to cyclic loading under a high gravitational force. At present, monopile foundations are widely used to support the tall and heavy wind turbines, which are also subjected to significant from wind and wave actions. A safe design must address issues such as rotations and changes in soil stiffness subject to these loadings conditions. Design guidance on the issue is limited, so are the availability of laboratory and field test data. The interpretation of these results in sand, such as the relation between loading and displacement, relies mainly on empirical correlations to pile properties. Regarding numerical models, most data from Finite Element Method (FEM) can be found. They are not comprehensive, and most of the FEM results are sensitive to input parameters. The micro scale behaviour could change the mechanism of the soil-structure interaction. A DEM model was used in this paper to study the cyclic lateral loads behaviour. A non-dimensional framework is presented and applied to interpret the simulation results. The DEM data compares well with various set of published experimental centrifuge model test data in terms of lateral deflection. The accumulated permanent pile lateral displacements induced by the cyclic lateral loads were found to be dependent on the characteristics of the applied cyclic load, such as the extent of the loading magnitudes and directions.

Keywords: cyclic loading, DEM, numerical modelling, sands

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Authors: Yasir Naseem

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In this fast-growing and evolving world, usage and adoption of technology have displayed an essential component of the learning process, both in and out of the class, which converges and incorporates every domain of the learning aspects. It aids in learning distinct entities irrespective of their levels of challenge. It also incorporates both viewpoints of learning, i.e., competence as well as the performances of the learner. In today's learning scenario, nearly every language class ordinarily uses some form of technology. It integrates with various teaching methodologies and transforms in a way that now it grew as an integral part of the language learning courses. It has been employed to facilitate, promote, and enhances language learning. It facilitates educators in numerous ways and enhances their methodologies by equipping them to modify classroom activities, which covers every aspect of language learning.

Keywords: communication, methodology, technology, skills

Procedia PDF Downloads 153

Authors: H. N. Agiza, M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous disorder with common age of onset, symptoms, and progression levels. In this paper we will solve analytically the PD model as a non-linear delay differential equation using the steps method. The step method transforms a system of delay differential equations (DDEs) into systems of ordinary differential equations (ODEs). On some numerical examples, the analytical solution will be difficult. So we will approximate the analytical solution using Picard method and Taylor method to ODEs.

Keywords: Parkinson's disease, step method, delay differential equation, two delays

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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Authors: Parul Khanna, Pavol Zavarsky, Dale Lindskog

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Doxing is a term derived from documents, and hence consists of collecting information on an organization or individual through social media websites, search engines, password cracking methods, social engineering tools and other sources of publicly displayed information. The main purpose of doxing attacks is to threaten, embarrass, harass and humiliate the organization or individual. Various tools are used to perform doxing. Tools such as Maltego visualize organization’s architecture which helps in determining weak links within the organization. This paper discusses limitations of Maltego Chlorine CE 3.6.0 and suggests measures as to how organizations can use these tools to protect themselves from doxing attacks.

Keywords: advanced persistent threat, FOCA, OSINT, PII

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Authors: Mojtaba Zabihi, Stephen Munro, Jonathan Little, Ri Li, Joshua Brinkerhoff, Sina Kheirkhah

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Occupational Safety and Health Administration (OSHA) identified dental workers at the highest risk of contracting COVID-19. This is because aerosol-generating procedures (AGP) during dental practices generate aerosols ( < 5µm) and droplets. These particles travel at varying speeds, in varying directions, and for varying durations. If these particles bear infectious viruses, their spreading causes airborne transmission of the virus in the dental room, exposing dentists, hygienists, dental assistants, and even other dental clinic clients to the infection risk. Computational fluid dynamics (CFD) simulation of two-phase flows based on a discrete phase model (DPM) is carried out to study the spreading of aerosol and droplets in a dental room. The simulation includes momentum, heat, and mass transfers between the particles and the airflow. Two simulations are conducted and compared. One simulation focuses on the effects of room ventilation in winter and summer on the particles' travel. The other simulation focuses on the control of aerosol and droplets' spreading. A suction collector is added near the source of aerosol and droplets, creating a flow sink in order to remove the particles. The effects of the suction flow on the aerosol and droplet travel are studied. The suction flow can remove aerosols and also reduce the spreading of droplets.

Keywords: aerosols, computational fluid dynamics, COVID-19, dental, discrete phase model, droplets, two-phase flow

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Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

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Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

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Authors: J. Sagouis, A. Chamel, E. Carre, C. Casasreales, G. Rudnik, M. Cerdan

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Robotics provides answers to amputees. The most expensive solutions surgically connect the prosthesis to nerve endings. There are also several types of non-invasive technologies that recover nerve messages passing through the muscles. After analyzing these messages, myoelectric prostheses perform the desired movement. The main goal is to avoid all surgeries, which can be heavy and offer cheaper alternatives. For an amputee, we use valid muscles to recover the electrical signal involved in a muscle movement. EMG sensors placed on the muscle allows us to measure a potential difference, which our program transforms into control for a robotic arm with two degrees of freedom. We have shown the feasibility of non-invasive prostheses with two degrees of freedom. Signal analysis and an increase in degrees of freedom is still being improved.

Keywords: prosthesis, electromyography (EMG), robotic arm, nerve message

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

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This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: real-time system (RTS), time utility function/ utility accrual (TUF/UA) scheduling, backward recovery mechanism, multiprocessor, discrete event simulation (DES)

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Authors: Kamand Bagherian, Nariman Niknejad

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A vibration isolation technology for precise position control of a rotary system powered by two permanent magnet DC (PMDC) motors is proposed, where this system is mounted on an oscillatory frame. To achieve vibration isolation for this system, active damping and disturbance rejection (ADDR) technology is presented which introduces a cooperation of a main and an auxiliary PMDC, controlled by discrete-time sliding mode control (DTSMC) based schemes. The controller of the main actuator tracks a desired position and the auxiliary actuator simultaneously isolates the induced vibration, as its controller follows a torque trend. To determine this torque trend, a combination of two algorithms is introduced by the ADDR technology. The first torque-trend producing algorithm rejects the disturbance by counteracting the perturbation, estimated using a model-based observer. The second torque trend applies active variable damping to minimize the oscillation of the output shaft. In this practice, the presented technology is implemented on a rotary system with a pendulum attached, mounted on a linear actuator simulating an oscillation-transmitting structure. In addition, the obtained results illustrate the functionality of the proposed technology.

Keywords: active damping, discrete-time nonlinear controller, disturbance tracking algorithm, oscillation transmitting support, position control, stability robustness, vibration isolation

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: Julia Cristina Bonaldo, Christophe L. Martin, Severine Romero Baivier, Stephane Mazerat

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Alumina refractories are commonly used in steel and foundry industries. These refractories are prepared through a powder metallurgy route. They are a mixture of hard alumina particles and graphite platelets embedded into a soft carbonic matrix (binder). The powder can be cold pressed isostatically or uniaxially, depending on the application. The compact is then fired to obtain the final product. The quality of the product is governed by the microstructure of the composite and by the process parameters. The compaction behavior and the mechanical properties of the fired product depend greatly on the amount of each phase, on their morphology and on the initial microstructure. In order to better understand the link between these parameters and the macroscopic behavior, we use the Discrete Element Method (DEM) to simulate the compaction process and the fracture behavior of the fired composite. These simulations are coupled with well-designed experiments. Four mixes with various amounts of Al₂O₃ and binder were tested both experimentally and numerically. In DEM, each particle is modelled and the interactions between particles are taken into account through appropriate contact or bonding laws. Here, we model a bimodal mixture of large Al₂O₃ and small Al₂O₃ covered with a soft binder. This composite is itself mixed with graphite platelets. X-ray tomography images are used to analyze the morphologies of the different components. Large Al₂O₃ particles and graphite platelets are modelled in DEM as sets of particles bonded together. The binder is modelled as a soft shell that covers both large and small Al₂O₃ particles. When two particles with binder indent each other, they first interact through this soft shell. Once a critical indentation is reached (towards the end of compaction), hard Al₂O₃ - Al₂O₃ contacts appear. In accordance with experimental data, DEM simulations show that the amount of Al₂O₃ and the amount of binder play a major role for the compaction behavior. The graphite platelets bend and break during the compaction, also contributing to the macroscopic stress. Firing step is modeled in DEM by ascribing bonds to particles which contact each other after compaction. The fracture behavior of the compacted mixture is also simulated and compared with experimental data. Both diametrical tests (Brazilian tests) and triaxial tests are carried out. Again, the link between the amount of Al₂O₃ particles and the fracture behavior is investigated. The methodology described here can be generalized to other particulate materials that are used in the ceramic industry.

Keywords: cold compaction, composites, discrete element method, refractory materials, x-ray tomography

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Authors: Danilo Habermann, Aleksander Medella, Carla Cremon, Yusef Caceres

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This paper aims to analyze the ability of 2d point clouds features to classify different models of helicopters using radars. This method does not need to estimate the blade length, the number of blades of helicopters, and the period of their micro-Doppler signatures. It is also not necessary to generate spectrograms (or any other image based on time and frequency domain). This work transforms a radar return signal into a 2D point cloud and extracts features of it. Three classifiers are used to distinguish 9 different helicopter models in order to analyze the performance of the features used in this work. The high accuracy obtained with each of the classifiers demonstrates that the 2D point clouds features are very useful for classifying helicopters from radar signal.

Keywords: helicopter classification, point clouds features, radar, supervised classifiers

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Authors: Ruiyang Bi

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Natural rock masses are cut into rock blocks of different shapes and sizes by intersecting joints. These rock blocks often determine the mechanical properties of the rock mass. In this study, fine sandstone cube specimens were produced, and three intersecting joint cracks were cut inside the specimen. Uniaxial compression tests were conducted using mechanical tests and numerical simulation methods to study the mechanical properties and crack propagation mechanism of triangular blocks within the rock. During the test, the mechanical strength, acoustic emission characteristics and strain field evolution of the specimen were analyzed. Discrete element software was used to study the expansion of microcracks during the specimen failure process, and the crack types were divided. The simulation results show that as the inclination angles of the three joints increase simultaneously, the mechanical strength of the specimen first decreases and then increases, and the crack type is mainly shear. As the inclination angle of a single joint increases, the strength of the specimen gradually decreases. When the inclination angles of the two joints increase at the same time, the strength of the specimen gradually decreases. The research results show that the stability of the rock mass is affected by the joint inclination angle and the size of the cut blocks. The greater the joint dip and block size, the more significant the development of micro-cracks in the rock mass, and the worse the stability.

Keywords: rock joints, uniaxial compression, crack extension, discrete element simulation

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Authors: Júlia Cristina Bonaldo, Christophe L. Martin, Martiniano Piccico, Keith Beale, Roop Kishore, Severine Romero-Baivier

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Refractory composite materials employed in steel casting applications are prone to cracking and material damage because of the very high operating temperature (thermal shock) and mismatched properties of the constituent phases. The fracture behavior of a model MgO-C composite refractory is investigated to quantify and characterize its thermal shock resistance, employing a cold crushing test and Brazilian test with fractographic analysis. The discrete element method (DEM) is used to generate numerical refractory composites. The composite in DEM is represented by an assembly of bonded particle clusters forming perfectly spherical aggregates and single spherical particles. For the stresses to converge with a low standard deviation and a minimum number of particles to allow reasonable CPU calculation time, representative volume element (RVE) numerical packings are created with various numbers of particles. Key microscopic properties are calibrated sequentially by comparing stress-strain curves from crushing experimental data. Comparing simulations with experiments also allows for the evaluation of crack propagation, fracture energy, and strength. The crack propagation during Brazilian experimental tests is monitored with digital image correlation (DIC). Simulations and experiments reveal three distinct types of fracture. The crack may spread throughout the aggregate, at the aggregate-matrix interface, or throughout the matrix.

Keywords: refractory composite, fracture mechanics, crack propagation, DEM

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Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

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Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

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Authors: A. Kyprianou, A. Tjirkallis

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Condition monitoring of structures in service is very important as it provides information about the risk of damage development. One of the essential constituents of structural condition monitoring is the damage detection methodology. In the context of condition monitoring of in service structures a damage detection methodology analyses data obtained from the structure while it is in operation. Usually, this means that the data could be affected by operational and environmental conditions in a way that could mask the effects of a possible damage on the data. This, depending on the damage detection methodology, could lead to either false alarms or miss existing damages. In this article a damage detection methodology that is based on the Spatio-temporal continuous wavelet transform (SPT-CWT) analysis of a sequence of experimental time responses of a cantilever beam is proposed. The cantilever is subjected to white and pink noise excitation to simulate different operating conditions. In addition, in order to simulate changing environmental conditions, the cantilever is subjected to heating by a heat gun. The response of the cantilever beam is measured by a high-speed camera. Edges are extracted from the series of images of the beam response captured by the camera. Subsequent processing of the edges gives a series of time responses on 439 points on the beam. This sequence is then analyzed using the SPT-CWT to identify damage. The algorithm proposed was able to clearly identify damage under any condition when the structure was excited by white noise force. In addition, in the case of white noise excitation, the analysis could also reveal the position of the heat gun when it was used to heat the structure. The analysis could identify the different operating conditions i.e. between responses due to white noise excitation and responses due to pink noise excitation. During the pink noise excitation whereas damage and changing temperature were identified it was not possible to clearly identify the effect of damage from that of temperature. The methodology proposed in this article for damage detection enables the separation the damage effect from that due to temperature and excitation on data obtained from measurements of a cantilever beam. This methodology does not require information about the apriori state of the structure.

Keywords: spatiotemporal continuous wavelet transform, damage detection, data normalization, varying temperature

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Authors: Revanth Rallapalli

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Manually dispensing powders can be difficult as it requires gradually pouring and checking the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and are user-dependent and difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various new powder dispensing mechanisms are being designed to overcome these challenges. A battery-operated screw conveyor mechanism is being innovated to overcome the above problems faced. These inventions are numerically evaluated at the concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices saving time and money by reducing the number of prototypes and testing. This paper describes a simulation of powder dispensation from the trocar’s end by considering the powder as secondary flow in the air, is simulated by using the technique called Dense Discrete Phase Model incorporated with Kinetic Theory of Granular Flow (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation of powder from the inlet side to the trocar’s end side is done by rotation of the screw conveyor. The performance is calculated for a 1-sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: multiphase flow, screw conveyor, transient, dense discrete phase model (DDPM), kinetic theory of granular flow (KTGF)

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Authors: Cheng Sheng, Yuemin Zhao, Chenlong Duan

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Air dense medium fluidized bed is a typical application of fluidization techniques for coal particle separation in arid areas, where it is costly to implement wet coal preparation technologies. In the last three decades, air dense medium fluidized bed, as an efficient dry coal separation technique, has been studied in many aspects, including energy and mass transfer, hydrodynamics, bubbling behaviors, etc. Despite numerous researches have been published, the fluidization features, especially dual dense medium fluidization features have been rarely reported. In dual dense medium fluidized beds, different combinations of different dense mediums play a significant role in fluidization quality variation, thus influencing coal separation efficiency. Moreover, to what extent different dense mediums mix and to what extent the two-component particulate mixture affects the fluidization performance and quality have been in suspense. The proposed work attempts to reveal underlying mechanisms of generation and evolution of two-component particulate mixture in the fluidization process. Based on computational fluid dynamics methods and discrete particle modelling, movement and evolution of dual dense mediums in air dense medium fluidized bed have been simulated. Dual dense medium fluidization experiments have been conducted. Electrical capacitance tomography was employed to investigate the distribution of two-component mixture in experiments. Underlying mechanisms involving two-component particulate fluidization are projected to be demonstrated with the analysis and comparison of simulation and experimental results.

Keywords: air dense medium fluidized bed, particle separation, computational fluid dynamics, discrete particle modelling

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Khachen Kongpakwattana, Nathorn Chaiyakunapruk

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Background: Decision-analytic models for Alzheimer’s disease (AD) have been advanced to discrete-event simulation (DES), in which individual-level modelling of disease progression across continuous severity spectra and incorporation of key parameters such as treatment persistence into the model become feasible. This study aimed to apply the DES to perform a cost-effectiveness analysis of treatment for AD in Thailand. Methods: A dataset of Thai patients with AD, representing unique demographic and clinical characteristics, was bootstrapped to generate a baseline cohort of patients. Each patient was cloned and assigned to donepezil, galantamine, rivastigmine, memantine or no treatment. Throughout the simulation period, the model randomly assigned each patient to discrete events including hospital visits, treatment discontinuation and death. Correlated changes in cognitive and behavioral status over time were developed using patient-level data. Treatment effects were obtained from the most recent network meta-analysis. Treatment persistence, mortality and predictive equations for functional status, costs (Thai baht (THB) in 2017) and quality-adjusted life year (QALY) were derived from country-specific real-world data. The time horizon was 10 years, with a discount rate of 3% per annum. Cost-effectiveness was evaluated based on the willingness-to-pay (WTP) threshold of 160,000 THB/QALY gained (4,994 US$/QALY gained) in Thailand. Results: Under a societal perspective, only was the prescription of donepezil to AD patients with all disease-severity levels found to be cost-effective. Compared to untreated patients, although the patients receiving donepezil incurred a discounted additional costs of 2,161 THB, they experienced a discounted gain in QALY of 0.021, resulting in an incremental cost-effectiveness ratio (ICER) of 138,524 THB/QALY (4,062 US$/QALY). Besides, providing early treatment with donepezil to mild AD patients further reduced the ICER to 61,652 THB/QALY (1,808 US$/QALY). However, the dominance of donepezil appeared to wane when delayed treatment was given to a subgroup of moderate and severe AD patients [ICER: 284,388 THB/QALY (8,340 US$/QALY)]. Introduction of a treatment stopping rule when the Mini-Mental State Exam (MMSE) score goes below 10 to a mild AD cohort did not deteriorate the cost-effectiveness of donepezil at the current treatment persistence level. On the other hand, none of the AD medications was cost-effective when being considered under a healthcare perspective. Conclusions: The DES greatly enhances real-world representativeness of decision-analytic models for AD. Under a societal perspective, treatment with donepezil improves patient’s quality of life and is considered cost-effective when used to treat AD patients with all disease-severity levels in Thailand. The optimal treatment benefits are observed when donepezil is prescribed since the early course of AD. With healthcare budget constraints in Thailand, the implementation of donepezil coverage may be most likely possible when being considered starting with mild AD patients, along with the stopping rule introduced.

Keywords: Alzheimer's disease, cost-effectiveness analysis, discrete event simulation, health technology assessment

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Authors: Shadan Dwairi

Abstract:

Defining proper requirements is one of the key factors for a successful construction projects. Although there have been many attempts put forward in assist in identifying requirements, but still this area is under developed. In Buildings Information Modelling (BIM) projects. The Employer Information Requirements (EIR) is the fundamental requirements document and a necessary ingredient in achieving a successful BIM project. The provision on full and clear EIR is essential to achieving BIM Level-2. As Defined by PAS 1192-2, EIR is a “pre-tender document that sets out the information to be delivered and the standards and processes to be adopted by the supplier as part of the project delivery process”. It also notes that “EIR should be incorporated into tender documentation to enable suppliers to produce an initial BIM Execution Plan (BEP)”. The importance of effective definition of EIR lies in its contribution to a better productivity during the construction process in terms of cost and time, in addition to improving the quality of the built asset. Proper and clear information is a key aspect of the EIR, in terms of the information it contains and more importantly the information the client receives at the end of the project that will enable the effective management and operation of the asset, where typically about 60%-80% of the cost is spent. This paper reports on the research done in developing the Ontology-based tool for Employer Information Requirements (OntEIR). OntEIR has proven the ability to produce a full and complete set of EIRs, which ensures that the clients’ information needs for the final model delivered by BIM is clearly defined from the beginning of the process. It also reports on the work being done into transforming OntEIR into a smart tool for Defining Employer Information Requirements (smartEIR). smartEIR transforms the OntEIR tool into enabling it to develop custom EIR- tailored for the: Project Type, Project Requirements, and the Client Capabilities. The initial idea behind smartEIR is moving away from the notion “One EIR fits All”. smartEIR utilizes the links made in OntEIR and creating a 3D matrix that transforms it into a smart tool. The OntEIR tool is based on the OntEIR framework that utilizes both Ontology and the Decomposition of Goals to elicit and extract the complete set of requirements needed for a full and comprehensive EIR. A new ctaegorisation system for requirements is also introduced in the framework and tool, which facilitates the understanding and enhances the clarification of the requirements especially for novice clients. Findings of the evaluation of the tool that was done with experts in the industry, showed that the OntEIR tool contributes towards effective and efficient development of EIRs that provide a better understanding of the information requirements as requested by BIM, and support the production of a complete BIM Execution Plan (BEP) and a Master Information Delivery Plan (MIDP).

Keywords: building information modelling, employer information requirements, ontology, web-based, tool

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Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

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Authors: Felix Platzer, Eric Fimbinger

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In Discrete Element Method (DEM) simulations, the breakage behavior of particles can be simulated based on different principles. In the case of large, complex-shaped particles that show various breakage patterns depending on the scenario leading to the failure and often only break locally instead of fracturing completely, some of these principles do not lead to realistic results. The reason for this is that in said cases, the methods in question, such as the Particle Replacement Method (PRM) or Voronoi Fracture, replace the initial particle (that is intended to break) into several sub-particles when certain breakage criteria are reached, such as exceeding the fracture energy. That is why those methods are commonly used for the simulation of materials that fracture completely instead of breaking locally. That being the case, when simulating local failure, it is advisable to pre-build the initial particle from sub-particles that are bonded together. The dimensions of these sub-particles consequently define the minimum size of the fracture results. This structure of bonded sub-particles enables the initial particle to break at the location of the highest local loads – due to the failure of the bonds in those areas – with several sub-particle clusters being the result of the fracture, which can again also break locally. In this project, different methods for the generation and calibration of complex-shaped particle conglomerates using bonded particle modeling (BPM) to enable the ability to depict more realistic fracture behavior were evaluated based on the example of filter cake. The method that proved suitable for this purpose and which furthermore allows efficient and realistic simulation of breakage behavior of complex-shaped particles applicable to industrial-sized simulations is presented in this paper.

Keywords: bonded particle model, DEM, filter cake, particle breakage

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Authors: Levent Dumenci, Laura A. Siminoff

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Health literacy has been shown to predict a variety of health outcomes. Reliable identification of persons with limited cancer health literacy (LCHL) has been proved questionable with existing instruments using an arbitrary cut point along a continuum. The CHLT-6, however, uses a latent mixture modeling approach to identify persons with LCHL. The purpose of this study was to estimate two-week and six-month stability of identifying persons with LCHL using the CHLT-6 with a discrete latent variable approach as the underlying measurement structure. Using a test-retest design, the CHLT-6 was administered to cancer patients with two-week (N=98) and six-month (N=51) intervals. The two-week and six-month latent test-retest agreements were 89% and 88%, respectively. The chance-corrected latent agreements estimated from Dumenci’s latent kappa were 0.62 (95% CI: 0.41 – 0.82) and .47 (95% CI: 0.14 – 0.80) for the two-week and six-month intervals, respectively. High levels of latent test-retest agreement between limited and adequate categories of cancer health literacy construct, coupled with moderate to good levels of change-corrected latent agreements indicated that the CHLT-6 classification of limited versus adequate cancer health literacy is relatively stable over time. In conclusion, the measurement structure underlying the instrument allows for estimating classification errors circumventing limitations due to arbitrary approaches adopted by all other instruments. The CHLT-6 can be used to identify persons with LCHL in oncology clinics and intervention studies to accurately estimate treatment effectiveness.

Keywords: limited cancer health literacy, the CHLT-6, discrete latent variable modeling, latent agreement

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Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

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Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

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The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

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Authors: William Albeiro Alvarez, Gloria Patricia Jaramillo, Ivan Reinaldo Sarmiento

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Understanding the behavior of individuals and the different human factors that influence the choice when faced with a complex system such as transportation is one of the most complicated aspects of measuring in the components that constitute the modeling of route choice due to that various behaviors and driving mode directly or indirectly affect the choice. During the last two decades, with the development of information and communications technologies, new data collection techniques have emerged such as GPS, geolocation with mobile phones, apps for choosing the route between origin and destination, individual service transport applications among others, where an interest has been generated to improve discrete choice models when considering the incorporation of these developments as well as psychological factors that affect decision making. This paper implements a discrete choice model that proposes and estimates a hybrid model that integrates route choice models and latent variables based on the observation on the route of a sample of public taxi drivers from the city of Medellín, Colombia in relation to its behavior, personality, socioeconomic characteristics, and driving mode. The set of choice options includes the routes generated by the individual service transport applications versus the driver's choice. The hybrid model consists of measurement equations that relate latent variables with measurement indicators and utilities with choice indicators along with structural equations that link the observable characteristics of drivers with latent variables and explanatory variables with utilities.

Keywords: behavior choice model, human factors, hybrid model, real time data

Procedia PDF Downloads 119