The Experts below are selected from a list of 1093125 Experts worldwide ranked by ideXlab platform
Junjun Yin - One of the best experts on this subject based on the ideXlab platform.
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self organized natural roads for predicting traffic flow a Sensitivity Study
Journal of Statistical Mechanics: Theory and Experiment, 2008Co-Authors: Bin Jiang, Sijian Zhao, Junjun YinAbstract:In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a Sensitivity Study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both annual average daily traffic (AADT) and global positioning system (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our great surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial light on the understanding of road networks and their traffic from the perspective of complex networks.
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self organized natural roads for predicting traffic flow a Sensitivity Study
arXiv: Data Analysis Statistics and Probability, 2008Co-Authors: Bin Jiang, Sijian Zhao, Junjun YinAbstract:In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a Sensitivity Study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both Annual Average Daily Traffic (AADT) and Global Positioning System (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our big surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial insights into the understanding of road networks and their traffic from the perspective of complex networks. Keywords: topological analysis, traffic flow, phase transition, small world, scale free, tipping point
Bin Jiang - One of the best experts on this subject based on the ideXlab platform.
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self organized natural roads for predicting traffic flow a Sensitivity Study
Journal of Statistical Mechanics: Theory and Experiment, 2008Co-Authors: Bin Jiang, Sijian Zhao, Junjun YinAbstract:In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a Sensitivity Study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both annual average daily traffic (AADT) and global positioning system (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our great surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial light on the understanding of road networks and their traffic from the perspective of complex networks.
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self organized natural roads for predicting traffic flow a Sensitivity Study
arXiv: Data Analysis Statistics and Probability, 2008Co-Authors: Bin Jiang, Sijian Zhao, Junjun YinAbstract:In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a Sensitivity Study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both Annual Average Daily Traffic (AADT) and Global Positioning System (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our big surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial insights into the understanding of road networks and their traffic from the perspective of complex networks. Keywords: topological analysis, traffic flow, phase transition, small world, scale free, tipping point
Sijian Zhao - One of the best experts on this subject based on the ideXlab platform.
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self organized natural roads for predicting traffic flow a Sensitivity Study
Journal of Statistical Mechanics: Theory and Experiment, 2008Co-Authors: Bin Jiang, Sijian Zhao, Junjun YinAbstract:In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a Sensitivity Study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both annual average daily traffic (AADT) and global positioning system (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our great surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial light on the understanding of road networks and their traffic from the perspective of complex networks.
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self organized natural roads for predicting traffic flow a Sensitivity Study
arXiv: Data Analysis Statistics and Probability, 2008Co-Authors: Bin Jiang, Sijian Zhao, Junjun YinAbstract:In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a Sensitivity Study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both Annual Average Daily Traffic (AADT) and Global Positioning System (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our big surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial insights into the understanding of road networks and their traffic from the perspective of complex networks. Keywords: topological analysis, traffic flow, phase transition, small world, scale free, tipping point
Sulaiman Alobaidani - One of the best experts on this subject based on the ideXlab platform.
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potential of membrane distillation in seawater desalination thermal efficiency Sensitivity Study and cost estimation
Journal of Membrane Science, 2008Co-Authors: Sulaiman Alobaidani, Efrem Curcio, Francesca Macedonio, Gianluca Di Profio, Hilal Alhinai, Enrico DrioliAbstract:Abstract In this work, an extensive analysis on direct contact membrane distillation (DCMD) performance was developed to estimate the mass flux and the heat efficiency, considering transport phenomena, membrane structural properties and most sensitive process parameters, with the aim to provide optimization guidelines for materials and methods. The results showed that an increase of the temperature gradient resulted in the enhancement of both transmembrane flux and thermal efficiency. The investigation of the effects of membrane properties confirmed that better DCMD performance was achieved when using polymeric membranes characterized by low thermal conductivity (flux and thermal efficiency declined by 26% and 50%, respectively, when increasing thermal conductivity from 0.1 to 0.5 W/m K), and high porosity. An optimal thickness value (around 0.7 mm) was identified when operating at low temperature gradient ( 10 °C), increasing the membrane thickness from 0.25 to 1.55 mm resulted in a flux decay of about 70% without a significant improvement in thermal efficiency. Exergy analysis, Sensitivity Study and economical evaluation were carried out to assess the feasibility of DCMD process. For DCMD with heat recovery, the estimated water cost was $1.17 m −3 , which was comparable to the cost of water produced by conventional thermal processes: i.e. around $1.00 m −3 for multiple effect distillation (MED) and $1.40 m −3 for multi-stage flash (MSF). However, significant savings are expected when using a low-grade thermal energy source, decreasing the cost of DCMD to values approaching the cost of water produced by reverse osmosis (RO), which is about $0.50 m −3 .
Soren Ehlers - One of the best experts on this subject based on the ideXlab platform.
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parametric structural analysis for a platform supply vessel at conceptual design phase a Sensitivity Study via design of experiments
Ships and Offshore Structures, 2017Co-Authors: Sthefano L Andrade, Henrique M Gaspar, Soren EhlersAbstract:ABSTRACTParametric structural design is a promising alternative for hull design, capable of combining weight reduction, material efficiency and safety. The challenge of investigating a large space of alternatives created by the parametric model is caused by the high amount of engineering time required to model, analyse and evaluate each of the possible configurations. The objective of this paper is thus to demonstrate the application of a design of experiments Sensitivity Study for a parametrically modelled global structure of a platform supply vessel with a focus on mass reduction during the conceptual design phase (CDP). The focus on CDP allows for simplifications in the model, thus gaining computational time by reducing discretisation. As a result, knowledge on the impact of design variables on various combined responses is obtained and used to determine a viable alternative within the solution space that has better material usage in comparison to a base case design.
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Parametric Structural Analysis for a Platform Supply Vessel at Conceptual Design Phase – a Sensitivity Study via Design of Experiments
Ships and Offshore Structures, 2017Co-Authors: Sthefano L Andrade, Henrique M Gaspar, Soren EhlersAbstract:ABSTRACTParametric structural design is a promising alternative for hull design, capable of combining weight reduction, material efficiency and safety. The challenge of investigating a large space of alternatives created by the parametric model is caused by the high amount of engineering time required to model, analyse and evaluate each of the possible configurations. The objective of this paper is thus to demonstrate the application of a design of experiments Sensitivity Study for a parametrically modelled global structure of a platform supply vessel with a focus on mass reduction during the conceptual design phase (CDP). The focus on CDP allows for simplifications in the model, thus gaining computational time by reducing discretisation. As a result, knowledge on the impact of design variables on various combined responses is obtained and used to determine a viable alternative within the solution space that has better material usage in comparison to a base case design.
