Search results for: EKC model

Authors: Mukesh Ranjan

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Applying probit model on the micro data of NSS 71st round on education for understanding the access to education post the passage of Right to Education act,2009 in India. The empirical analysis shows that at all India level the mean age of enrollment in school is 5.5 years and drop-out age is around 14 years (or studied up to class 7) and around 60 percent females never get enrolled in any school in their lifetime. Nearly 20 percent children in Bihar never seen school and surprisingly, the relatively developed states like Gujarat, Maharashtra, Karnataka, Kerala and Tamil Nadu have more than one-third of the children and half of the children in Andhra Pradesh, West Bengal and Orissa as educationally wasted. The relative contribution in educational wastage is maximum by Bengal (10 %) while UP contributed a maximum of 30 % in educational non-enrollment in the country. Educational wastage is more likely to increase with age. Marriage is a resistive factor in getting education. Muslims are educationally more deprived than Hindus. Larger family and rich household are less likely to be educationally deprived. Major reasons for drop-out until 9 years were lack of interest in education and financial constraint; between 10-12 years, lack of interest and unable to cope up with studies and post 12 years financial constraint, marriage and other household reasons.

Keywords: probit model, educational wastage, educational non-enrollment, educational deprivation

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Authors: Vera Karla S. Caingles, Glen A. Lorenzo

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Soil, as the main material of landslides, plays a vital role in landslide assessment. An efficient and accurate method of doing an assessment is significantly important to prevent damage of properties and loss of lives. The study has two phases: to establish an empirical correlation of the residual soil thickness with the slope angle and to investigate the geotechnical characteristics of residual soil. Digital Elevation Model (DEM) in Geographic Information System (GIS) was used to establish the slope map and to program sampling points for field investigation. Physical and index property tests were undertaken on the 20 soil samples obtained from the area with Pliocene-Pleistocene geology and different slope angle in Kibawe, Bukidnon. The regression analysis result shows that the best fitting model that can describe the soil thickness-slope angle relationship is an exponential function. The physical property results revealed that soils contain a high percentage of clay and silts ranges from 41% - 99.52%. Based on the index properties test results, the soil exhibits a high degree of plasticity and expansion but not collapsible. It is deemed that this compendium will serve as primary data for slope stability analysis and deterministic landslide assessment.

Keywords: collapsibility, correlation, expansiveness, landslide, plasticity

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Authors: Caglayan Hizal, Hasan Emre Demirci, Engin Aktas, Alper Sezer

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Offshore wind turbines consist of a long slender tower with a heavy fixed mass on the top of the tower (nacelle), together with a heavy rotating mass (blades and hub). They are always subjected to environmental loads including wind and wave loads in their service life. This study presents a three-stage methodology for reliability-based condition assessment of offshore wind-turbines against the seismic, wave and wind induced effects considering the soil-structure interaction. In this context, failure criterions are considered as serviceability limits of a monopile supporting an Offshore Wind Turbine: (a) allowable horizontal displacement at pile head should not exceed 0.2 m, (b) rotations at pile head should not exceed 0.5°. A Bayesian system identification framework is adapted to the classical reliability analysis procedure. Using this framework, a reliability assessment can be directly implemented to the updated finite element model without performing time-consuming methods. For numerical verification, simulation data of the finite model of a real offshore wind-turbine structure is investigated using the three-stage methodology.

Keywords: Offshore wind turbines, SHM, reliability assessment, soil-structure interaction

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Authors: Morgane Chatard, Clémentine Puech, Nathalie Perek, Frédéric Roche

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Several neurological disorders are linked to repeated hypoxia. The impact of such repeated hypoxic stress, on endothelial cells function of the blood-brain barrier (BBB) is little studied in the literature. Indeed, the study of hypoxic stress in cellular pathways is complex using hypoxia exposure because HIF 1α (factor induced by hypoxia) has a short half life. Our study presents an innovative induction method of repeated hypoxic stress, more reproducible, which allows us to study its impacts on an in vitro contact co-culture BBB model. Repeated hypoxic stress was induced by hydralazine (a mimetic agent of hypoxia pathway) during two hours and repeated during 24 hours. Then, BBB integrity was assessed by permeability measurements (transendothelial electrical resistance and membrane permeability), tight junction protein expressions (cell-ELISA and confocal microscopy) and by studying expression and activity of efflux transporters. First, this study showed that repeated hypoxic stress leads to a BBB’s dysfunction illustrated by a significant increase in permeability. This loss of membrane integrity was linked to a significant decrease of tight junctions’ protein expressions, facilitating a possible transfer of potential cytotoxic compounds in the brain. Secondly, we demonstrated that brain microvascular endothelial cells had set-up defence mechanism. These endothelial cells significantly increased the activity of their efflux transporters which was associated with a significant increase in their expression. In conclusion, repeated hypoxic stress lead to a loss of BBB integrity with a decrease of tight junction proteins. In contrast, endothelial cells increased the expression of their efflux transporters to fight against cytotoxic compounds brain crossing. Unfortunately, enhanced efflux activity could also lead to reducing pharmacological drugs delivering to the brain in such hypoxic conditions.

Keywords: BBB model, efflux transporters, repeated hypoxic stress, tigh junction proteins

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Authors: Mohd Raish Ansari, Tauheed Alam Khan

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This research paper is a comparative study of the belt truss in the Regular RC frame structure at the different positions of the floor. The method used in this research is the response spectrum method with the help of the ETABS Software, there are six models in this paper with belt truss. The Indian standard code used in this work are IS 456:2000, IS 800:2007, IS 875 part-1, IS 875 part-1, and IS 1893 Part-1:2016. The cross-section of the belt truss is the I-section, a grade of steel that is made up of Mild Steel. The basic model in this research paper is the same, only position of the belt truss is going to change, and the dimension of the belt truss is remain constant for all models. The plan area of all models is 24.5 meters x 28 meters, and the model has G+20, where the height of the ground floor is 3.5 meters, and all floor height is 3.0 meters remains constant. This comparative research work selected some important seismic parameters to check the stability of all models, the parameters are base shear, fundamental period, storey overturning moment, and maximum storey displacement.

Keywords: belt truss, RC frames structure, ETABS, response spectrum analysis, special moment resisting frame

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Authors: Imam Muthohar, Budi Hartono, Sigit Priyanto, Hardiansyah Hardiansyah

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The eruption of Merapi Volcano in Yogyakarta, Indonesia in 2010 caused many casualties due to minimum preparedness in facing disaster. Increasing population capacity and evacuating to safe places become very important to minimize casualties. Regional government through the Regional Disaster Management Agency has divided disaster-prone areas into three parts, namely ring 1 at a distance of 10 km, ring 2 at a distance of 15 km and ring 3 at a distance of 20 km from the center of Mount Merapi. The success of the evacuation is fully supported by road network infrastructure as a way to rescue in an emergency. This research attempts to model evacuation process based on the rise of refugees in ring 1, expanded to ring 2 and finally expanded to ring 3. The model was developed using SATURN (Simulation and Assignment of Traffic to Urban Road Networks) program version 11.3. 12W, involving 140 centroid, 449 buffer nodes, and 851 links across Yogyakarta Special Region, which was aimed at making a preliminary identification of road networks considered vulnerable to disaster. An assumption made to identify vulnerability was the improvement of road network performance in the form of flow and travel times on the coverage of ring 1, ring 2, ring 3, Sleman outside the ring, Yogyakarta City, Bantul, Kulon Progo, and Gunung Kidul. The research results indicated that the performance increase in the road networks existing in the area of ring 2, ring 3, and Sleman outside the ring. The road network in ring 1 started to increase when the evacuation was expanded to ring 2 and ring 3. Meanwhile, the performance of road networks in Yogyakarta City, Bantul, Kulon Progo, and Gunung Kidul during the evacuation period simultaneously decreased in when the evacuation areas were expanded. The results of preliminary identification of the vulnerability have determined that the road networks existing in ring 1, ring 2, ring 3 and Sleman outside the ring were considered vulnerable to the evacuation of Mount Merapi eruption. Therefore, it is necessary to pay a great deal of attention in order to face the disasters that potentially occur at anytime.

Keywords: model, evacuation, SATURN, vulnerability

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Authors: Mlondi Ndovela

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Globally, the manufacturing employment has been declining and the South African manufacturing sector experiences the very same trend. Despite the commonality between the global and South African manufacturing trend, there is an understanding that local areas provide distinct contributions to the provincial/national economy. Therefore, the growth/decline of a particular manufacturing division in one local area may not be evident in another area since economic performances vary from region to region. In view of the above, the study employed the Esteban-Marquillas model of shift-share analysis (SSA) to conduct an empirical analysis of manufacturing employment performance at uMhlathuze Local Municipality in the KwaZulu-Natal province. The study set out two objectives; those are, to quantify uMhlathuze manufacturing jobs that are attributed to the provincial manufacturing employment trends and identify manufacturing divisions are growing/declining in terms of employment. To achieve these objectives, the study sampled manufacturing employment data from 2010 to 2017 and this data was categorised into ten manufacturing divisions. Furthermore, the Esteban-Marquillas model calculated manufacturing employment in terms of two effects, namely; provincial growth effect (PGE) and industrial mix effect (IME). The results show that even though uMhlathuze manufacturing sector has a positive PGE (+230), the municipality performed poorly in terms of IME (-291). A further analysis included other economic sectors of the municipality to draw employment performance comparison and the study found that agriculture; construction; trade, catering and accommodation; and transport, storage and communication, performed well above manufacturing sector in terms of PGE (+826) and IME (+532). This suggests that uMhlathuze manufacturing sector is not necessarily declining; however, other economic sectors are growing faster and bigger than it is, therefore, reducing the employment share of the manufacturing sector. To promote manufacturing growth from a policy standpoint, the government could create favourable macroeconomic policies such as import substitution policies and support labour-intensive manufacturing divisions. As a result, these macroeconomic policies can help to protect local manufacturing firms and stimulate the growth of manufacturing employment.

Keywords: allocation effect, Esteban-Marquillas model, manufacturing employment, regional competitive effect, shift-share analysis

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Zeinu Ahmed Rabba, Derek D Stretch

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Remote sensing contributes valuable information to streamflow estimates. Usually, stream flow is directly measured through ground-based hydrological monitoring station. However, in many developing countries like Ethiopia, ground-based hydrological monitoring networks are either sparse or nonexistent, which limits the manage water resources and hampers early flood-warning systems. In such cases, satellite remote sensing is an alternative means to acquire such information. This paper discusses the application of remotely sensed rainfall data for streamflow modeling in Gilgel Ghibe basin in Ethiopia. Ten years (2001-2010) of two satellite-based precipitation products (SBPP), TRMM and WaterBase, were used. These products were combined with the PyTOPKAPI hydrological model to generate daily stream flows. The results were compared with streamflow observations at Gilgel Ghibe Nr, Assendabo gauging station using four statistical tools (Bias, R², NS and RMSE). The statistical analysis indicates that the bias-adjusted SBPPs agree well with gauged rainfall compared to bias-unadjusted ones. The SBPPs with no bias-adjustment tend to overestimate (high Bias and high RMSE) the extreme precipitation events and the corresponding simulated streamflow outputs, particularly during wet months (June-September) and underestimate the streamflow prediction over few dry months (January and February). This shows that bias-adjustment can be important for improving the performance of the SBPPs in streamflow forecasting. We further conclude that the general streamflow patterns were well captured at daily time scales when using SBPPs after bias adjustment. However, the overall results demonstrate that the simulated streamflow using the gauged rainfall is superior to those obtained from remotely sensed rainfall products including bias-adjusted ones.

Keywords: Ethiopia, PyTOPKAPI model, remote sensing, streamflow, Tropical Rainfall Measuring Mission (TRMM), waterBase

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The accelerating requirement to reach 0% sulfur content in liquid fuels demands researchers to seek efficient alternative technologies to challenge the predicament. In this current study, the adsorption capabilities of modified Cu(I)-Y zeolite were tested for removal of organosulfur compounds (OSC) present in TPO. The π-complexation-based adsorbent was obtained by ion exchanging Y-zeolite with Cu+ cation using liquid phase ion exchange (LPIE). Preparation of the adsorbent involved firstly ion-exchange between Na-Y zeolite with a Cu(NO3)2 aqueous solution of 0.5M for 48 hours followed by reduction of Cu2+ to Cu+. Batch studies for TPO in comparison with model diesel comprising of sulfur compounds such as thiophene (TH), benzothiophene (BTH), dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophe (4,6-DMDBT) showed that modified Cu(I)-Y zeolite is an effective adsorbent for removal of OSC in liquid fuels. The effect of multiple operating conditions such as adsorbent dosage, reaction time and temperature were studied to optimize the process. For model diesel fuel, the selectivity for adsorption of sulfur compounds followed the order 4,6-DMDBT> DBT> BTH> TH. Interpretation of the results was justified using the molecular orbital theory and calculations. Langmuir and Freundlich isotherms were used to predict adsorption of the reaction mixture. The Cu(I)-Y zeolite is fully regeneratable and this is achieved by a simple procedure of blowing the adsorbent with air at 350 °C, followed by reactivation at 450 °C in a rich helium surrounding.

Keywords: adsorption, desulfurization, TPO, zeolite

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Authors: Zohreh Soltani, Seyedmohammadhossein Hosseinian

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Reduction of energy consumption in built infrastructure, through the installation of energy-efficient technologies, is a major approach to achieving sustainability. In practice, the viability of energy efficiency projects strongly depends on the cost reimbursement and profitability. These projects are subject to failure if the actual cost savings do not reimburse the project cost in a timely manner. In such cases, refinancing could be a solution to benefit from the long-term returns of the project if implemented wisely. However, very little is still known about the effect of refinancing options on financial performance of energy efficiency projects. To fill this gap, the present study investigates the financial behavior of energy efficiency projects with focus on refinancing options, such as Leveraged Loans. A System Dynamics (SD) model is introduced, and the model application is presented using an actual case-study data. The case study results indicate that while high-interest start-ups make using Leveraged Loan inevitable, refinancing can rescue the project and bring about profitability. This paper also presents some managerial implications of refinancing energy efficiency projects based on the case-study analysis. Results of this study help implementing financially viable energy efficiency projects, so the community could benefit from their environmental advantages widely.

Keywords: energy efficiency projects, leveraged loan, refinancing, sustainability

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Zakheleni P. Dube, Phatu W. Mashela

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The Curve-fitting Allelochemical Response Data (CARD) model had been adopted as a valuable tool in enhancing the understanding of the efficacy of cucurbitacin-containing phytonematicides on the suppression of nematodes. In most cases, for registration purposes, the active ingredients should be in purified form. Evidence in other phytonematicides suggested that purified active ingredients were less effective in suppression of nematodes. The objective of this study was to use CARD model to compare the overall sensitivities of Meloidogyne incognita J2 hatch, mobility and mortality to Nemarioc-AL phytonematicides, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B. Meloidogyne incognita eggs and J2 were exposed to 0.00, 0.50, 1.00, 1.50, 2.00, 2.50, 3.00, 3.50, 4.00, 4.50 and 5.00% of each phytonematicide, whereas in purified form the concentrations were 0.00, 0.25, 0.50, 0.75, 1.00, 1.25, 1.50, 1.75, 2.00, 2.25 and 2.50 μg.mL⁻¹. The exposure period to each concentration was 24-, 48- and 72-h. The overall sensitivities of J2 hatch to Nemarioc-AL phytonematicide, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B were 1, 30, 5 and 2 units, respectively, whereas J2 mobiltity were 3, 17, 3 and 6 units, respectively. For J2 mortality overall sensitivities to Nemarioc-AL phytonematicide, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B were 2, 4, 1 and 4 units, respectively. In conclusion, the two crude extracts, Nemarioc-AL and Nemafric-BL phytonematicides were generally more potent to M. incognita compared to their pure active ingredients. The crude plant extract preparation is easy, and they could be an ideal tactic for the management of nematodes in resource poor farming communities.

Keywords: Botanicals, cucumin, leptodermin, plant extracts, triterpenoids

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Ali Raza, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

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Diesel engines are most efficient and reliable in terms of efficiency, reliability, and adaptability. Most of the research and development up till now have been directed towards High Speed Diesel Engine, for Commercial use. In these engines, objective is to optimize maximum acceleration by reducing exhaust emission to meet international standards. In high torque low speed engines, the requirement is altogether different. These types of engines are mostly used in Maritime Industry, Agriculture Industry, Static Engines Compressors Engines, etc. On the contrary, high torque low speed engines are neglected quite often and are eminent for low efficiency and high soot emissions. One of the most effective ways to overcome these issues is by efficient combustion in an engine cylinder. Fuel spray dynamics play a vital role in defining mixture formation, fuel consumption, combustion efficiency and soot emissions. Therefore, a comprehensive understanding of the fuel spray characteristics and atomization process in high torque low speed diesel engine is of great importance. Evaporation in the combustion chamber has a rigorous effect on the efficiency of the engine. In this paper, multiphase evaporation of fuel is modeled for high torque low speed engine using the CFD (computational fluid dynamics) codes. Two distinct phases of evaporation are modeled using modeling soft wares. The basic model equations are derived from the energy conservation equation and Naiver-Stokes equation. O’Rourke model is used to model the evaporation phases. The results obtained showed a generous effect on the efficiency of the engine. Evaporation rate of fuel droplet is increased with the increase in vapor pressure. An appreciable reduction in size of droplet is achieved by adding the convective heat effects in the combustion chamber. By and large, an overall increase in efficiency is observed by modeling distinct evaporation phases. This increase in efficiency is due to the fact that droplet size is reduced and vapor pressure is increased in the engine cylinder.

Keywords: diesel fuel, CFD, evaporation, multiphase

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Authors: Hossam Shalabi, George Hadjisophocleous

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The Canadian Nuclear Power Plants (NPPs) use some portions of NUREG/CR-6850 in carrying out Fire Probabilistic Risk Assessment (PRA). An assessment for the applicability of NUREG/CR-6850 to CANDU reactors was performed and a CANDU Fire PRA was introduced. There are 19 operating CANDU reactors in Canada at five sites (Bruce A, Bruce B, Darlington, Pickering and Point Lepreau). A fire load density survey was done for all Fire Safe Shutdown Analysis (FSSA) fire zones in all CANDU sites in Canada. National Fire Protection Association (NFPA) Standard 557 proposes that a fire load survey must be conducted by either the weighing method or the inventory method or a combination of both. The combination method results in the most accurate values for fire loads. An updated CANDU Fire PRA model is demonstrated in this paper that includes the fuel survey in all Canadian CANDU stations. A qualitative screening step for the CANDU fire PRA is illustrated in this paper to include any fire events that can damage any part of the emergency power supply in addition to FSSA cables.

Keywords: fire safety, CANDU, nuclear, fuel densities, FDS, qualitative analysis, fire probabilistic risk assessment

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Chengfeng Fang, Mohamed Ali Sadakkathulla, Abdul Sheikh

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Ultra-high-performance fiber reinforced concrete (UHPFRC) is a specially formulated cement-based composite characterized with an ultra-high compressive strength (f_c^’ = 240 MPa) and a low water-cement ratio (W/B= 0.2). With such material characteristics, UHPFRC is favored for the design and constructions of structures required high structural performance and slender geometries. Unlike conventional concrete, the structural performance of members manufactured with UHPFRC has not yet been fully studied, particularly, for UHPFRC columns with high slenderness. In this study, the behaviors of slender UHPFRC columns under concentric or eccentric load will be investigated both experimentally and numerically. Four slender UHPFRC columns were tested under eccentric loads with eccentricities, of 0 mm, 35 mm, 50 mm, and 85 mm, respectively, and one UHPFRC beam was tested under four-point bending. Finite element (FE) analysis was conducted with concrete damage plasticity (CDP) modulus to simulating the load-middle height or middle span deflection relationships and damage patterns of all UHPFRC members. Simulated results were compared against the experimental results and observation to gain the confidence of FE model, and this model was further extended to conduct parametric studies, which aim to investigate the effects of slenderness regarding failure modes and load-moment interaction relationships. Experimental results showed that the load bearing capacities of the slender columns reduced with an increase in eccentricity. Comparisons between load-middle height and middle span deflection relationships as well as damage patterns of all UHPFRC members obtained both experimentally and numerically demonstrated high accuracy of the FE simulations. Based on the available FE model, the following parametric study indicated that a further increase in the slenderness of column resulted in significant decreases in the load-bearing capacities, ductility index, and flexural bending capacities.

Keywords: eccentric loads, ductility index, RC column, slenderness, UHPFRC

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Authors: Wenting Zhang, Shishi Liu, Peihong Fu

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As an indicator of air quality and directly related to concentration of ground PM2.5, the spatial-temporal variation and impact factor analysis of Aerosol Optical Depth (AOD) have been a hot spot in air pollution. This paper concerns the non-stationarity and the autocorrelation (with Moran’s I index of 0.75) of the AOD in Wuhan agglomeration (WHA), in central China, uses the geographically weighted regression (GRW) to identify the spatial relationship of AOD and its impact factors. The 3 km AOD product of Moderate Resolution Imaging Spectrometer (MODIS) is used in this study. Beyond the economic-social factor, land use density factors, vegetable cover, and elevation, the landscape metric is also considered as one factor. The results suggest that the GWR model is capable of dealing with spatial varying relationship, with R square, corrected Akaike Information Criterion (AICc) and standard residual better than that of ordinary least square (OLS) model. The results of GWR suggest that the urban developing, forest, landscape metric, and elevation are the major driving factors of AOD. Generally, the higher AOD trends to located in the place with higher urban developing, less forest, and flat area.

Keywords: aerosol optical depth, geographically weighted regression, land use change, Wuhan agglomeration

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Authors: Teresita Lopez Joy, Jose A. Acevedo Suarez, Martha I. Gomez Acosta, Ana Julia Acevedo Urquiaga

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Current trends in business competitiveness indicate the need to manage businesses as supply chains and not in isolation. The use of strategies aimed at maximum satisfaction of customers in a network and based on inter-company cooperation; contribute to obtaining successful joint results. In the Cuban economic context, the development of productive linkages to achieve integrated management of supply chains is considering a key aspect. In order to achieve this jump, it is necessary to develop acting capabilities in the entities that make up the chains through a systematic procedure that allows arriving at a management model in consonance with the environment. The objective of the research focuses on: designing a model and procedure for the development of integrated management of supply chains in economic entities. The results obtained are: the Model and the Procedure for the Development of the Supply Chains Integrated Management (MP-SCIM). The Model is based on the development of logistics in the network actors, the joint work between companies, collaborative planning and the monitoring of a main indicator according to the end customers. The application Procedure starts from the well-founded need for development in a supply chain and focuses on training entrepreneurs as doers. The characterization and diagnosis is done to later define the design of the network and the relationships between the companies. It takes into account the feedback as a method of updating the conditions and way to focus the objectives according to the final customers. The MP-SCIM is the result of systematic work with a supply chain approach in companies that have consolidated as coordinators of their network. The cases of the edible oil chain and explosives for construction sector reflect results of more remarkable advances since they have applied this approach for more than 5 years and maintain it as a general strategy of successful development. The edible oil trading company experienced a jump in sales. In 2006, the company started the analysis in order to define the supply chain, apply diagnosis techniques, define problems and implement solutions. The involvement of the management and the progressive formation of performance capacities in the personnel allowed the application of tools according to the context. The company that coordinates the explosives chain for construction sector shows adequate training with independence and opportunity in the face of different situations and variations of their business environment. The appropriation of tools and techniques for the analysis and implementation of proposals is a characteristic feature of this case. The coordinating entity applies integrated supply chain management to its decisions based on the timely training of the necessary action capabilities for each situation. Other cases of study and application that validate these tools are also detailed in this paper, and they highlight the results of generalization in the quantitative and qualitative improvement according to the final clients. These cases are: teaching literature in universities, agricultural products of local scope and medicine supply chains.

Keywords: integrated management, logistic system, supply chain management, tactical-operative planning

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Authors: Nadeem Bashir, Ghulam Mustafa Peerzada

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The present study pertains to the nonlinear behavior of acetaminophen based uncatalyzed Belousov-Zhabotinsky (BZ) oscillator and its dynamics in the presence of Ferroin as the catalyst. The role of free metal ions as catalysts was examined and the results compared with corresponding complexed catalysts. Free metal ions were found to be sluggish with respect to the evolution of the oscillatory regime as compared to complexed ones. Effect of change of the ligand moiety of the catalyst complex on the oscillatory parameters was monitored. Since ethanol potentiates the hepatotoxicity caused by acetaminophen in-vivo, it is thought to understand this interaction by virtue of causing perturbation of the acetaminophen based oscillator with different concentrations of the ethanol with and without ferroin as the catalyst. Another dimension to the ethanol effect was added by perturbation of the system with ethanol at different stages of the reaction so as to get an idea whether it is acetaminophen or some reactive intermediate generated in the reaction system which reacts with ethanol. Further, the ferroin-catalyzed oscillator is taken as a prototype inorganic model of the acetaminophen-ethanol syndrome, as ferroin and HOBr were inorganic replacements to Cyt P450 and NADPH in the alcohol metabolism.

Keywords: Belousov-Zhabotinsky reaction, ferroin, Paracetamol-Ethanol syndrome, kinetics

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Authors: Meng Koon Lee, Mohammad Hosseini Fouladi, Satesh Narayana Namasivayam

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Research is focused on the response of soundboards of Classical guitars at frequencies up to 5 kHz as the soundboard is a major contributor to acoustic radiation at high frequencies when compared to the bridge and sound hole. A thin rectangular plate of variable thickness that is simply-supported on all sides is used as an analytical model of the research. This model is used to study the response of the guitar soundboard as the latter can be considered as a modified form of a rectangular plate. Homotopy Perturbation Method (HPM) is selected as a mathematical method to obtain an analytical solution of the 4th-order parabolic partial differential equation of motion of the rectangular plate of constant thickness viewed as a linear problem. This procedure is generalized to the nonlinear problem of the rectangular plate with variable thickness and an analytical solution can also be obtained. Sound power is used as a parameter to investigate the acoustic radiation of soundboards made from spruce using various bracing patterns. The sound power of soundboards made from Malaysian softwood such as damar minyak, sempilor or podo are investigated to determine the viability of replacing spruce as future materials for soundboards of Classical guitars.

Keywords: rectangular plates, analytical solution, homotopy perturbation, natural frequencies

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Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

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Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

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Authors: Sabrina Neururer, Marco Schweitzer, Werner Hackl, Bernhard Tilg, Patrick Raudaschl, Andreas Huber, Bernhard Pfeifer

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History and the current outbreak of Covid-19 have shown the deadly potential of infectious diseases. However, infectious diseases also have a serious impact on areas other than health and healthcare, such as the economy or social life. These areas are strongly codependent. Therefore, disease control measures, such as social distancing, quarantines, curfews, or lockdowns, have to be adopted in a very considerate manner. Infectious disease modeling can support policy and decision-makers with adequate information regarding the dynamics of the pandemic and therefore assist in planning and enforcing appropriate measures that will prevent the healthcare system from collapsing. In this work, an agent-based simulation package named “survival” for simulating infectious diseases is presented. A special focus is put on SARS-Cov-2. The presented simulation package was used in Austria to model the SARS-Cov-2 outbreak from the beginning of 2020. Agent-based modeling is a relatively recent modeling approach. Since our world is getting more and more complex, the complexity of the underlying systems is also increasing. The development of tools and frameworks and increasing computational power advance the application of agent-based models. For parametrizing the presented model, different data sources, such as known infections, wastewater virus load, blood donor antibodies, circulating virus variants and the used capacity for hospitalization, as well as the availability of medical materials like ventilators, were integrated with a database system and used. The simulation result of the model was used for predicting the dynamics and the possible outcomes and was used by the health authorities to decide on the measures to be taken in order to control the pandemic situation. The survival package was implemented in the programming language Java and the analytics were performed with R Studio. During the first run in March 2020, the simulation showed that without measures other than individual personal behavior and appropriate medication, the death toll would have been about 27 million people worldwide within the first year. The model predicted the hospitalization rates (standard and intensive care) for Tyrol and South Tyrol with an accuracy of about 1.5% average error. They were calculated to provide 10-days forecasts. The state government and the hospitals were provided with the 10-days models to support their decision-making. This ensured that standard care was maintained for as long as possible without restrictions. Furthermore, various measures were estimated and thereafter enforced. Among other things, communities were quarantined based on the calculations while, in accordance with the calculations, the curfews for the entire population were reduced. With this framework, which is used in the national crisis team of the Austrian province of Tyrol, a very accurate model could be created on the federal state level as well as on the district and municipal level, which was able to provide decision-makers with a solid information basis. This framework can be transferred to various infectious diseases and thus can be used as a basis for future monitoring.

Keywords: modelling, simulation, agent-based, SARS-Cov-2, COVID-19

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Authors: Hugo F. Lobaton

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The cyanobacterium Spirulina platensis is a prokaryotic photoautotrophic microorganism that is successfully cultivated for the commercialization as whole biomass due to its high protein content and promising valuable substance. For instance, phycocyanin has recently drawn the interest of the food and cosmetic industries due to its bright blue colour and its strong antioxidant capacities. The phycocyanin (PC) is the main protein-pigment in S. platensis (4% to 20%). In batches, the rate of overproduction of metabolites by cyanobacteria is limited or activated by the depletion of required substrates. The aim of this study was to develop a kinetic law that describes phycocyanin formation during batch cultivation. S. platensis was cultivated in 1 L bubble column photobioreactor with 30°C and 700 µmol m⁻² s⁻¹. Culture samples were daily collected from the bubble columns in sterile conditions. The biomass (g l⁻¹) was measured directly after a biomass lyophilisation process, and phycocyanin extractions and measurements were done according to a well-established protocol. A kinetic law for phycocyanin formation that includes nitrate and bicarbonate limitations was proposed and linked to the biomass core model. The set of differential equations were solved in MATLAB. Concerning to product formation, the experimental results show that phycocyanin mass fraction is degraded as results of the complete nitrate depletion and nitrate additions during the cultivation help to keep constant this molecule until new macro-element limitation appear. According to the model, bicarbonate is this limitation.

Keywords: phycocyanin, nitrate, bicarbonate, spirulina

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Authors: Abdulrahman Aljabri, Essam R. I. Mahmoud, Hamad Almohamedi, Zhengyi Jiang

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Cold rolled thin strip has received intensive attention through technological and theoretical progress in the rolling process, as well as researchers have focused on its control during rolling as an essential parameter for producing thinner strip with good shape and profile. An advanced approach has been proposed to analysis the thin strip profile in cold rolling of pair roll crossing and shifting mill using Finite Element Analysis (FEA) with an ALE technique. The ALE (Arbitrary Lagrangian-Eulerian) techniques to enable more flexibility of the ALE technique in the adjustment of the finite element mesh, which provides a significant tool for simulating the thin strip under realistic rolling process constraint and provide accurate model results. The FEA can provide theoretical basis for the 3D model of controlling the strip shape and profile in thin strip rolling, and deliver an optimal rolling process parameter, and suggest corrective changes during cold rolling of thin strip.

Keywords: pair roll crossing, work roll shifting, strip shape and profile, finite element modeling

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Maryam Khazaee-Pool, Tahereh Pashaei, Koen Ponnet

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Background: The global prevalence and morbidity of Coronavirus disease 2019 (COVID-19) are high. Preventive behaviors are proven to reduce the damage caused by the disease. There is a paucity of information on determinants of preventive behaviors in response to COVID-19 in Mazandaran province, north of Iran. So, we aimed to evaluate the protection motivation theory (PMT) in promoting preventive behaviors of COVID-19 in Mazandaran province. Materials and Methods: In this descriptive cross-sectional study, 1220 individuals participated. They were selected via social networks using convenience sampling in 2020. Data were collected online using a demographic questionnaire and a valid and reliable scale based on PMT. Data analysis was done using the Pearson correlation coefficient and linear regression in SPSS V24. Result: The mean age of the participants was 39.34±8.74 years. The regression model showed perceived threat (ß =0.033, P =0.007), perceived costs (ß=0.039, P=0.045), perceived self-efficacy (ß =0.116, P>0.001), and perceived fear (ß=0.131, P>0.001) as the significant predictors of COVID-19 preventive behaviors. This model accounted for 78% of the variance in these behaviors. Conclusion: According to constructs of the PMT associated with protection against COVID-19, educational programs and health promotion based on the theory and benefiting from social networks could be helpful in increasing the motivation of people towards protective behaviors against COVID-19.

Keywords: questionnaire development, validation, intention, prevention, covid-19

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Authors: Iris W. A. Boot, Anke Wesselius, Maurice P. Zeegers

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Diet may play an essential role in the aetiology of bladder cancer (BC). Vitamin D is involved in various biological functions which have the potential to prevent BC development. Besides, vitamin D also influences the uptake of calcium and phosphorus , thereby possibly indirectly influencing the risk of BC. The aim of the present study was to investigate the relation between vitamin D intake and BC risk. Individual dietary data were pooled from three cohort studies. Food item intake was converted to daily intakes of vitamin D, calcium and phosphorus. Pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs) were obtained using Cox-regression models. Analyses were adjusted for gender, age and smoking status (Model 1), and additionally for the food groups fruit, vegetables and meat (Model 2). Dose–response relationships (Model 1) were examined using a nonparametric test for trend. In total, 2,871 cases and 522,364 non-cases were included in the analyses. The present study showed an overall increased BC risk for high dietary vitamin D intake (HR: 1.14, 95% CI: 1.03-1.26). A similar increase BC risk with high vitamin D intake was observed among women and for the non-muscle invasive BC subtype, (HR: 1.41, 95% CI: 1.15-1.72, HR: 1.13, 95% CI: 1.01-1.27, respectively). High calcium intake decreased the BC risk among women (HR: 0.81, 95% CI: 0.67-0.97). A combined inverse effect on BC risk was observed for low vitamin D intake and high calcium intake (HR: 0.67, 95% CI: 0.48-0.93), while a positive effect was observed for high vitamin D intake in combination with low, moderate and high phosphorus (HR: 1.31, 95% CI: 1.09-1.59, HR: 1.17, 95% CI: 1.01-1.36, HR: 1.16, 95% CI: 1.03-1.31, respectively). Combining all nutrients showed a decreased BC risk for low vitamin D intake, high calcium and moderate phosphor intake (HR: 0.37, 95% CI: 0.18-0.75), and an increased BC risk for moderate intake of all the nutrients (HR: 1.18, 95% CI: 1.02-1.38), for high vitamin D and low calcium and phosphor intake (HR: 1.28, 95% CI: 1.01-1.62), and for moderate vitamin D and calcium and high phosphorus intake (HR: 1.27, 95% CI: 1.01-1.59). No significant dose-response analyses were observed. The findings of this study show an increased BC risk for high dietary vitamin D intake and a decreased risk for high calcium intake. Besides, the study highlights the importance of examining the effect of a nutrient in combination with complementary nutrients for risk assessment. Future research should focus on nutrients in a wider context and in nutritional patterns.

Keywords: bladder cancer, nutritional oncology, pooled cohort analysis, vitamin D

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Authors: Srikanth Pandurangi, Basheer Mohammed, Nezar Al Sayegh

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In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.

Keywords: innovative methods in transportation data collection, integrated public transportation system, traffic forecasts, transportation modeling, travel behavior

Procedia PDF Downloads 204