Search results for: prediction modelling

Authors: Tae Gwan Kim, Hyun Kyu Cho, Young Hoon Lee, Young Chul Park

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Foam monitors are devices that are installed on cargo tank decks to suppress cargo area fires in oil tankers or hazardous chemical ship cargo ships. In general, the main design parameter of the foam monitor is the distance of the projection through the foam monitor. In this study, the relationship between flow characteristics and projection distance, depending on the shape was examined. Numerical techniques for fluid analysis of foam monitors have been developed for prediction. The flow pattern of the fluid varies depending on the shape of the flow path of the foam monitor, as the flow losses affecting projection distance were calculated through numerical analysis. The basic shape of the foam monitor was an L shape designed by N Company. The modified model increased the length of the flow path and used the S shape model. The calculation result shows that the L shape, which is the basic shape, has a problem that the force is directed to one side and the vibration and noise are generated there. In order to solve the problem, S-shaped model, which is a change model, was used. As a result, the problem is solved, and the projection distance from the nozzle is improved.

Keywords: CFD, foam monitor, projection distance, moment

Procedia PDF Downloads 344

Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

Procedia PDF Downloads 390

Authors: Ashwini Shripatwar, Mayur Biyani, Nikhil Rao, Rajendra Bodake, Sachin Sane

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This paper documents the correlation of valve cover sealing, cracking, and warpage Finite Element Modelling with observations on engine test development. The valve cover is a component mounted on engine head with a gasket which provides sealing against oil which flows around camshaft, valves, rockers, and other overhead components. Material nonlinearity and contact nonlinearity characteristics are taken into consideration because the valve cover is made of a composite material having temperature dependent elastic-plastic properties and because the gasket load-deformation curve is also nonlinear. The leakage is observed between the valve cover and the engine head due to the insufficient contact pressure. The crack is observed on the valve cover due to force application at a region with insufficient stiffness and with elevated temperature. The valve cover shrinkage is observed during the disassembly process on hot exhaust side bolt holes after the engine has been running. In this paper, an analytical approach is developed to correlate a Finite Element Model with the observed failures and to address the design issues associated with the failure modes in question by making design changes in the model.

Keywords: cracking issue, gasket sealing analysis, nonlinearity of contact and material, valve cover

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Authors: Md. Moinul Islam, N. M. Golam Zakaria

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Seakeeping analysis of catamaran vessels in the earlier stages of design has become an important issue as it dictates the seakeeping characteristics, and it ensures safe navigation during the voyage. In the present paper, a 3D numerical method for the seakeeping prediction of catamaran vessel is presented using the 3D Green Function method. Both steady and unsteady potential flow problem is dealt with here. Using 3D linearized potential theory, the dynamic wave loads and the subsequent response of the vessel is computed. For validation of the numerical procedure catamaran vessel composed of twin, Wigley form demi-hull is used. The results of the present calculation are compared with the available experimental data and also with other calculations. The numerical procedure is also carried out for NPL-based round bilge catamaran, and hydrodynamic coefficients along with heave and pitch motion responses are presented for various Froude number. The results obtained by the present numerical method are found to be in fairly good agreement with the available data. This can be used as a design tool for predicting the seakeeping behavior of catamaran ships in waves.

Keywords: catamaran, hydrodynamic coefficients , motion response, 3D green function

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

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This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: N. V. Nikhil, S. R. Lee, Do Won Park

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Korean peninsula receives about two third of the annual rainfall during summer season. The extreme rainfall pattern due to typhoon and heavy rainfall results in severe mountain disasters among which 55% of them are debris flows, a major natural hazard especially when occurring around major settlement areas. The basic mechanism underlined for this kind of failure is the unsaturated shallow slope failure by reduction of matric suction due to infiltration of water and liquefaction of the failed mass due to generation of positive pore water pressure leading to abrupt loss of strength and commencement of flow. However only an empirical model cannot simulate this complex mechanism. Hence, we have employed an empirical-physical based approach for hazard analysis of debris flow using TRIGRS, a debris flow initiation criteria and DAN3D in mountain Woonmyun, South Korea. Debris flow initiation criteria is required to discern the potential landslides which can transform into debris flow. DAN-3D, being a new model, does not have the calibrated values of rheology parameters for Korean conditions. Thus, in our analysis we have used the recent 2011 debris flow event in mountain Woonmyun san for calibration of both TRIGRS model and DAN-3D, thereafter identifying and predicting the debris flow initiation points, path, run out velocity, and area of spreading for future extreme rainfall based scenarios.

Keywords: debris flow, DAN-3D, extreme rainfall, hazard analysis

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Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

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Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: Surendra Kumar Chourasiya, Sandeep Kumar, Devendra Singh

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In the present investigation tribological behavior of Al-6Si-1Mg-1Graphite composite has been explained. The composite was developed through the unique spray forming route in the spray forming chamber by using N₂ gas at 7kg/cm² and the flight distance was 400 mm. Spray formed composite having a certain amount of porosity which was reduced by the deformations. The composite was subjected to the warm rolling (WR) at 250ºC up to 40% reduction. Spray forming composite shows the considerable microstructure refinement, equiaxed grains, distribution of silicon and graphite particles in the primary matrix of the composite. Graphite (Gr) was incorporated externally during the process that works as a solid lubricant. Porosity decreased after reduction and hardness increases. Pin on disc test has been performed to analyze the wear behavior which is the function of sliding distance for all percent reduction of the composite. 30% WR composite shows the better result of wear rate and coefficient of friction. The improved wear properties of the composite containing Gr are discussed in light of the microstructural features of spray formed the composite and the nature of the debris particles. Scanning electron microscope and optical microscope analysis of the present material supported the prediction of aforementioned changes.

Keywords: Al-6Si-1Mg-1Graphite, spray forming, warm rolling, wear

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Suby Khanam, Faisal Talib, Jamshed Siddiqui

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Total Quality Management (TQM) is a managerial approach that improves the competitiveness of the industry, meanwhile Information technology (IT) was introduced with TQM for handling the technical issues which is supported by quality experts for fulfilling the customers’ requirement. Present paper aims to utilise AHP (Analytic Hierarchy Process) methodology to priorities and rank the hierarchy levels of TQM enablers and IT resource together for its successful implementation in the Information and Communication Technology (ICT) industry. A total of 17 TQM enablers (nine) and IT resources (eight) were identified and partitioned into 3 categories and were prioritised by AHP approach. The finding indicates that the 17 sub-criteria can be grouped into three main categories namely organizing, tools and techniques, and culture and people. Further, out of 17 sub-criteria, three sub-criteria: Top management commitment and support, total employee involvement, and continuous improvement got highest priority whereas three sub-criteria such as structural equation modelling, culture change, and customer satisfaction got lowest priority. The result suggests a hierarchy model for ICT industry to prioritise the enablers and resources as well as to improve the TQM and IT performance in the ICT industry. This paper has some managerial implication which suggests the managers of ICT industry to implement TQM and IT together in their organizations to get maximum benefits and how to utilize available resources. At the end, conclusions, limitation, future scope of the study are presented.

Keywords: analytic hierarchy process, information technology, information and communication technology, prioritization, total quality management

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Authors: Michal Stelmach

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The aim of this paper is a critical analysis of the security policy in the field of the fight against transnational criminal groups in Central America in XXI century. We are analyzing all taken issues from several perspectives: political, anthropological, sociological and legal which allows me to confront behavior and the attitudes of the political elites against official legislative changes and declared actions, strategies and policies against practice. In the first part of paper we would like to present the genesis and characteristic of transnational gangs, called maras and next we would like to present their activities and roles within chosen sectors of organized crimes. In the second part we will analyze the government’s policy towards transnational criminal groups. The analysis will be concentrated on public safety policy implemented in specific Central American countries as well as regional international cooperation. The main intention of the author is to present the state of the security in Central America in XXI century by emphasizing failures and successes in the fight against transnational criminal organizations. Additionally we want to present and define the challenges currently facing the region now and to show the prediction of the situation’s development within next future and to define the recommendations on the design of public security policies in Central American countries.

Keywords: maras, public security, human rights, Central America

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Authors: Tonga Agadi Danladi, Ajao Wasiu Bamidele, Terdue Dyeko

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Recent advancement in microwave communications technologies especially in telecommunications and broadcasting have resulted in congestion on the frequencies below 10GHz. This has forced microwave designers to look for high frequencies. Unfortunately for frequencies greater than 10GHz rain becomes one of the main factors of attenuation in signal strength. At frequencies from 10GHz upwards, rain drop sizes leads to outages that compromises the availability and quality of service this making it a critical factor in satellite link budget design. Rain rate and rain attenuation predictions are vital steps to be considered when designing microwave satellite communication link operating at Ku-band frequencies (112-18GHz). Unreliable rain rates data in the tropical regions of the world like Nigeria from radio communication group of the international Telecommunication Union (ITU-R) makes it difficult for microwave engineers to determine a realistic rain margin that needs to be accommodated in satellite link budget design in such region. This work presents an empirical tool for predicting the amount of signal due to rain on DBS signal operating at the Ku-band.

Keywords: attenuation, Ku-Band, microwave communication, rain rates

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Authors: Natasha Mandal, Rakesh Singh Moirangthem

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The present work reports a theoretical model to develop a plasmonic biosensor for the detection of glucose concentrations in human blood and urine as the abnormality of glucose label is the major cause of diabetes which becomes a life-threatening disease worldwide. This study is based on the surface plasmon resonance (SPR) sensor applications which is a well-established, highly sensitive, label-free, rapid optical sensing tool. Here we have introduced a sandwich assay of two dielectric spacer layers of MgF2 and BaTiO3which gives better performance compared to commonly used SiO2 and TiO2 dielectric spacers due to their low dielectric loss and higher refractive index. The sensitivity of our proposed sensor was found as 3242 nm/RIU approximately, with an excellent linear response of 0.958, which is higher than the conventional single-layer Au SPR sensor. Further, the sensitivity enhancement is also optimized by coating a few layers of two-dimensional (2D) nanomaterials (e.g., Graphene, h-BN, MXene, MoS2, WS2, etc.) on the sensor chip. Hence, our proposed SPR sensor has the potential for the detection of glucose concentration in blood and urine with enhanced sensitivity and high affinity and could be utilized as a reliable platform for the optical biosensing application in the field of medical diagnosis.

Keywords: biosensor, surface plasmon resonance, dielectric spacer, 2D nanomaterials

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Authors: Innocent C. Ezenwa, Takashi Yoshino

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Knowledge of the transport properties of Fe and its alloys at extreme high pressure (P), temperature (T) conditions are essential for understanding the generation and sustainability of the magnetic field of the rocky planets with a metallic core. Since Pt, an unfilled d-band late transition metal with an electronic structure of Xe4f¹⁴5d⁹6s¹, is paramagnetic and remains close-packed structure at ambient conditions and high P-T, it is expected that its transport properties at these conditions would be similar to those of ε-Fe. We investigated the T-dependent electrical resistivity of solid and liquid Pt up to 8 GPa and found it constant along its melting curve both on the liquid and solid sides in agreement with theoretical prediction and experimental results estimated from thermal conductivity measurements. Our results suggest that the T-dependent resistivity of ε-Fe is linear and would not saturate at high P, T conditions. This, in turn, suggests that the thermal conductivity of liquid Fe at Earth’s core conditions may not be as high as previously suggested by models employing saturation resistivity. Hence, thermal convection could have powered the geodynamo before the birth of the inner core. The electrical resistivity and thermal conductivity on the liquid and solid sides of the inner core boundary of the Earth would be significantly different in values.

Keywords: electrical resistivity, thermal conductivity, transport properties, geodynamo and geomagnetic field

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Authors: Ehsan Mehryaar, Reza Bushehri

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One of the principal parameters defining the clay soil dynamic response is the strain-shear modulus relation. Predicting the strain and, subsequently, shear modulus reduction of the soil is essential for performance analysis of structures exposed to earthquake and dynamic loadings. Many soil properties affect soil’s dynamic behavior. In order to capture those effects, in this study, a database containing 1193 data points consists of maximum shear modulus, strain, moisture content, initial void ratio, plastic limit, liquid limit, initial confining pressure resulting from dynamic laboratory testing of 21 clays is collected for predicting the shear modulus vs. strain curve of soil. A model based on an extreme gradient boosting technique is proposed. A tree-structured parzan estimator hyper-parameter tuning algorithm is utilized simultaneously to find the best hyper-parameters for the model. The performance of the model is compared to the existing empirical equations using the coefficient of correlation and root mean square error.

Keywords: XGBoost, hyper-parameter tuning, soil shear modulus, dynamic response

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Authors: Desmond Adair, Kairat Ismailov, Martin Jaeger

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Modelling of Timoshenko beams on elastic foundations has been widely used in the analysis of buildings, geotechnical problems, and, railway and aerospace structures. For the elastic foundation, the most widely used models are one-parameter mechanical models or two-parameter models to include continuity and cohesion of typical foundations, with the two-parameter usually considered the better of the two. Knowledge of free vibration characteristics of beams on an elastic foundation is considered necessary for optimal design solutions in many engineering applications, and in this work, the efficient and accurate variational iteration method is developed and used to calculate natural frequencies of a Timoshenko beam on a two-parameter foundation. The variational iteration method is a technique capable of dealing with some linear and non-linear problems in an easy and efficient way. The calculations are compared with those using a finite-element method and other analytical solutions, and it is shown that the results are accurate and are obtained efficiently. It is found that the effect of the presence of the two-parameter foundation is to increase the beam’s natural frequencies and this is thought to be because of the shear-layer stiffness, which has an effect on the elastic stiffness. By setting the two-parameter model’s stiffness parameter to zero, it is possible to obtain a one-parameter foundation model, and so, comparison between the two foundation models is also made.

Keywords: Timoshenko beam, variational iteration method, two-parameter elastic foundation model

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Authors: Yuanxiang Miao

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Couchsurfing is a free homestay and social networking service accessible via the website and mobile app. Couchsurfers can directly request free accommodations from others and receive offers from each other. However, it is typically difficult for people to make a decision that accepts or declines a request when they receive it from Couchsurfers because they do not know each other at all. People are expected to meet up with some Couchsurfers who are kind, generous, and interesting while it is unavoidable to meet up with someone unfriendly. This paper utilized classification algorithms of Machine Learning to help people to find out the Good Couchsurfers and Not Good Couchsurfers on the Couchsurfing website. By knowing the prior experience, like Couchsurfer’s profiles, the latest references, and other factors, it became possible to recognize what kind of the Couchsurfers, and furthermore, it helps people to make a decision that whether to host the Couchsurfers or not. The value of this research lies in a case study in Kyoto, Japan in where the author has hosted 54 Couchsurfers, and the author collected relevant data from the 54 Couchsurfers, finally build a model based on classification algorithms for people to predict Couchsurfers. Lastly, the author offered some feasible suggestions for future research.

Keywords: Couchsurfing, Couchsurfers prediction, classification algorithm, hospitality tourism platform, hospitality sciences, machine learning

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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The probability distributions are the best method for forecasting of extreme hydrologic phenomena such as rainfall and flood flows. In this research, in order to determine suitable probability distribution for estimating of annual extreme rainfall and flood flows (discharge) series with different return periods, precipitation with 40 and discharge with 58 years time period had been collected from Karkheh River at Iran. After homogeneity and adequacy tests, data have been analyzed by Stormwater Management and Design Aid (SMADA) software and residual sum of squares (R.S.S). The best probability distribution was Log Pearson Type III with R.S.S value (145.91) and value (13.67) for peak discharge and Log Pearson Type III with R.S.S values (141.08) and (8.95) for maximum discharge in Jelogir Majin and Pole Zal stations, respectively. The best distribution for maximum precipitation in Jelogir Majin and Pole Zal stations was Log Pearson Type III distribution with R.S.S values (1.74&1.90) and then Pearson Type III distribution with R.S.S values (1.53&1.69). Overall, the Log Pearson Type III distributions are acceptable distribution types for representing statistics of extreme hydrologic phenomena in Karkheh River at Iran with the Pearson Type III distribution as a potential alternative.

Keywords: Karkheh River, Log Pearson Type III, probability distribution, residual sum of squares

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Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in the supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: supply chain management, balanced scorecard, value, structural modeling, stakeholders

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Authors: Lei Zhang, Wen-jun Ruan, Hao Wang, Peng-Xin Wang

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The source of the jet noise is generated by rocket exhaust plume during rocket engine testing. A domain decomposition approach is applied to the jet noise prediction in this paper. The aerodynamic noise coupling is based on the splitting into acoustic sources generation and sound propagation in separate physical domains. Large Eddy Simulation (LES) is used to simulate the supersonic jet flow. Based on the simulation results of the flow-fields, the jet noise distribution of the sound pressure level is obtained by applying the Ffowcs Williams-Hawkings (FW-H) acoustics equation and Fourier transform. The calculation results show that the complex structures of expansion waves, compression waves and the turbulent boundary layer could occur due to the strong interaction between the gas jet and the ambient air. In addition, the jet core region, the shock cell and the sound pressure level of the gas jet increase with the nozzle size increasing. Importantly, the numerical simulation results of the far-field sound are in good agreement with the experimental measurements in directivity.

Keywords: supersonic gas jet, Large Eddy Simulation(LES), acoustic noise, Ffowcs Williams-Hawkings(FW-H) equations, nozzle size

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Authors: Kimuli Ismail, Michael Lubwama, John Baptist Kirabira, Adam Sebbit

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This study develops 4 energy scenarios for Greater Kampala Metropolitan Area (GKMA). GKMA is Uganda’s capital with a population of 4.1million and a GDP growth rate of 5.8 with a nonsustainable energy management system. The study uses TIMES-VEDA to examine the energy impacts of business as usual (BAU), Kabejja, Carbon-Tax, and Lutta scenarios in commercial, industrial, transportation, residential, agricultural, and electricity generation activities. BAU is the baseline scenario with limited CO2 emissions restrictions against which Kabejja with 20% CO2 emissions restriction, a carbon tax of $100/ton imposed in 2050 for Carbon-Tax scenario, and Lutta with 95% CO2 emissions restriction is made. The analysis suggests that if the current policy trends continue as BAU, consumption would increase from 139.6PJ to 497.42PJ and CO2 emissions will increase from 4.6mtns to 7mtns. However, consumption would decrease by 2.3% in Kabejja, 3.4% in Carbon-Tax, and 3.3 % in Lutta compared to BAU. The CO2 emissions would decrease by 8.57% in Kabejja, 55.14% in Carbon-Tax, and 60% in Lutta compared to BAU. Sustainability is achievable when low-carbon electricity is increased by 53.68% in the EMS, and setting up an electrified Kampala metro. The study recommends Lutta as the sustainable pathway to a lowcarbon 2050.

Keywords: Sustainability, Scenario Plannnig, Times-Veda Modelling, Energy Policy Development

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Authors: Titilola Adebowale

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Some factors are responsible for the social adjustment among the adolescents. The study investigated resiliency, peer and parental support as factors that could determine social adjustment among adolescents in Ilorin, Kwara state. The study adopted descriptive survey research design. A sample size of 300 SS1 & SS2 students from ten secondary schools, six public and four private schools were randomly selected within Ilorin Metropolis. Self-structured questionnaire that was validated and the reliability ensured was used to collect data from the respondents. Four hypotheses were postulated and tested at 0.05 level of significance. Data collected was analysed using Pearson Product Moment Correlation (PPMC) and Regression Analysis. The findings revealed that there was a positive relationship between resiliency and social adjustment: r (298) = .402, p<0.01, r2 = .162; that there was a positive relationship between peer support and social adjustment: r (298) = .570, p<0.01, r2 = .325; that there was a positive relationship between parental support and social adjustment: r (298) = .451, p<0.01, r2 = .203; also reveals significant joint contribution of the independent variables (resilience, peer support, parental support) to the prediction of social adjustment: F (3,296) = 55.587, P<0.01. Various recommendations were given which includes the roles of government, agencies, individuals, parents, teachers, religious and marriage institutions.

Keywords: resiliency, peer support, parental support, adolescents, social adjustment

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Authors: Hamid Goharnejad, Milad Sadeghpoor Moalem, Mahmood Zakeri Niri, Leili Sadeghi Khalegh Abadi

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While there are many benefits to using reservoir dams, their break leads to destructive effects. From the viewpoint of International Committee of Large Dams (ICOLD), dam break means the collapse of whole or some parts of a dam; thereby the dam will be unable to hold water. Therefore, studying dam break phenomenon and prediction of its behavior and effects reduces losses and damages of the mentioned phenomenon. One of the most common types of reservoir dams is embankment dam. Overtopping in embankment dams occurs because of flood discharge system inability in release inflows to reservoir. One of the most important issues among managers and engineers to evaluate the performance of the reservoir dam rim when sliding into the storage, creating waves is large and long. In this study, the effects of floods which caused the overtopping of the dam have been investigated. It was assumed that spillway is unable to release the inflow. To determine outflow hydrograph resulting from dam break, numerical model using Flow-3D software and empirical equations was used. Results of numerical models and their comparison with empirical equations show that numerical model and empirical equations can be used to study the flood resulting from dam break.

Keywords: embankment dam break, empirical equations, Taleghan dam, Flow-3D numerical model

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Authors: Reena Murali, David Peter S.

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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

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Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: torsional vibration, full-size model, scale model, scaling laws

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

Abstract:

The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

Procedia PDF Downloads 323

Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

Abstract:

Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

Procedia PDF Downloads 446