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REVIEW ARTICLE
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3122 Views, 416 PDF Downloads
Xin Wang, Zhen Li, Bing Han, Baoguo Han, Xun Yu, Shuzhu Zeng, Jinping Ou DOI:10.26789/JSC.2016.02.005 AbstractIntelligent concrete refers to the structural materials which can sense the changes of environment and make suitable responses by altering one or more working parameters in real time. The ‘intelligent’ properties of concrete are achieved mainly by improving the composition of raw materials or combining some functional materials with concrete matrix, thus leading to the concrete possessing bionic features. Compared to conventional concrete, the reliability and sustainability of structures can be optimized by applying properly designed intelligent concrete materials. Additionally, the life-cycle costs, resource consumption and environment pollution can be reduced. In the past few decades, considerable efforts have been put towards the research of intelligent concrete and many innovative achievements have been gained in the development and application of intelligent concrete. Twelve types of intelligent concrete emphasizing on its self-x capabilities are systematically reviewed in this paper, with attentions to their principles, composition, fabrication, properties, research progress and structural applications. In addition, some comments and prospects for the development of self-x concrete are also discussed. |
1-39
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RESEARCH ARTICLE
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1061 Views, 382 PDF Downloads
Fabio Casciati, Sara Casciati, Clemente Fuggini, Lucia Faravelli, Ivan Tesfai, Michele Vece DOI:10.26789/JSC.2016.02.003 Abstract“Smart city” is a term currently used to denote cities moved by the opportunity to enhance the quality of life and the security of their citizens. Attention is here focused on the concept that the development of smart cities can also be achieved by improving the efficiency of civil infrastructures through a real-time monitoring. This is the specific target of the European Union FP7 project (SPARTACUS), moved from the parallel chance to develop industry pull applications for the European EGNOS and GALILEO satellite systems. In this paper, laboratory tests are carried out to provide specific devices the ability to run while satisfying the requirements of the incoming GALILEO system. Moreover, some of the targets are achieved within the current GPS system. An extensive experimental campaign is offered to validate the units in such a scenario. |
40-48
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3746 Views, 1234 PDF Downloads
Ankit Kumar Singh, Dwipen Boruah, Lakshey Sehgal, Arun Prasath Ramaswamy DOI:10.26789/JSC.2016.02.004 AbstractThe race of smart cities in India places Pondicherry at 75th position. To improve its ranking position for smart city race, we propose the implementation of 2MW Floating Solar Photovoltaic (FSPV) system -where a large water body could be used for generation of solar power. The floating PV system can be used to attain much higher efficiency compared to its counterpart on land based PV system. The proposed FSPV system could cover solar panel of 1/3rd area of the proposed lake to generates 2685 MWh annually. A geo-synchronized layout has been prepared using 3D SketchUp Pro with Google maps. The FSPV system could cost USD 1.6 million with a payback period of 6 years. In addition, the implementation of e-transport facility by utilizing e-rickshaws with a battery capacity of 90Ah with 15 Amps DC charging facility has been proposed with an investment of USD 30k, with payback period of just 5 month. The bright side being improved overall payback due to money inflow with the implementation of e-rickshaws; greater job opportunities with benefits to physically challenged persons to improve their overall socio economic status. It is viewed that the proposed FSPV and e-transport could increase the chance to secure smart city plan for Pondicherry.
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49-59
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830 Views, 224 PDF Downloads
Ioannis Kaparias, Edouard Manassa, Niv Eden, Antonios Tsakarestos, Pierre Schmitz, Suzanne Hoadley, Susanna Hauptmann DOI:10.26789/JSC.2016.02.002 AbstractIn recent research a performance evaluation framework for traffic management and Intelligent Transport Systems was developed, consisting of a set of Key Performance Indicators (KPIs) for the themes of traffic efficiency, safety, pollution reduction and social inclusion, all of which are key components of a smart city. One of the innovative elements of these KPIs is their ability to consider the transport policy layer, in the sense that the evaluation of the suitability and effectiveness of different strategies and ITS options is calculated in relation to the decision-maker’s high-level transport policy rather than objectively. This is achieved through weighting factors, whereby more important policy objectives are weighted more heavily in the calculation. But while the theoretical framework is ready to accommodate the policy layer, no methodology to determine the values of the weighting factors has been developed so far. The present study, therefore, concentrates on the development and testing of such a methodology, focusing on the environmental impact aspect of urban mobility management and ITS in the context of smart cities. The development is based on existing policy objectives and legislation in different cities and countries, while testing is carried out using the purpose-developed CONDUITS_DST software with data from microsimulation models before and after the implementation of a bus priority signalling system in Brussels, Belgium. The results show that the method captures the expected effects, but also that it is able to reflect policy objectives and deliver evaluation results in relation to their alignment with those
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60-68
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1480 Views, 362 PDF Downloads
Costas Argyris, Costas Papadimitriou, Panagiotis Panetsos DOI:10.26789/JSC.2016.02.001 AbstractA Bayesian optimal experimental design (OED) method is proposed in this work for estimating the best locations of sensors in structures so that the measured data are most informative for estimating reliably the structural modes. The information contained in the data is measured by the Kullback-Leibler (K-L) divergence between the prior and posterior distribution of the model parameters taken in modal identification to be the modal coordinates. The optimal sensor placement that maximizes the expected K-L divergence is shown also to minimize the information entropy of the posterior distribution. Unidentifiability issues observed in existing formulations when the number of sensors is less than the number of identified modes, are resolved using a non-uniform prior in the Bayesian OED. An insightful analysis is presented that demonstrates the effect of the variances of Bayesian priors on the optimal design. For dense mesh finite element models, sensor clustering phenomena are avoided by integrating in the methodology spatially correlated prediction error models. A heuristic forward sequential sensor placement algorithm and a stochastic optimization algorithm are used to solve the optimization problem in the continuous physical domain of variation of the sensor locations. The theoretical developments and algorithms are applied for the optimal sensor placement design along the deck of a 537 m concrete bridge.
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69-86
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