<abstract xmlns="http://www.w3.org/1999/xhtml"><p>We have seen in the previous paper that in the case of resistance elements made of steel, at least in this case study, the structure’s response to strains, in this case sunshine, is uncertain, may or may not be linear. The analysis continues for the four characteristic months of 2013, respectively the second month (February), the fifth (May), the eighth (August) and the event (November), covering the four seasons and approximately the entire range of temperatures to which the resistance elements of the bridge are subject to along a calendar year - case study Incheon Grand Bridge, Seoul, South Korea. The number of data pairs recorded, as we have noted, every 15 minutes, is initially 11,616, being difficult to process. Some software (e.g. Table Curve 2D) can work with a maximum of 3000 data pairs. In what follows we will examine the behaviour of a reinforced concrete element of the North Bridge Gap front line and we will build a mathematical model of its behaviour to sunshine, from the input data, one recording every hours, thus reducing the number of measurements to 2904. The aim is to obtain a mathematical model with a correlation coefficient above 0.9, which is also verified and validated. This model will allow us to calculate the expected position of the sensor mounted on the resistance element for a certain temperature, the degree of confidence of the result, the interval of residual values. Because the history of the evolution of temperatures for each moment analyzed is different it produces different results, but ones that fit the specified regressive mathematical model.</p></abstract>

We have seen in the previous paper that in the case of resistance elements made of steel, at least in this case study, the structure’s response to strains, in this case sunshine, is uncertain, may or may not be linear. The analysis continues for the four characteristic months of 2013, respectively the second month (February), the fifth (May), the eighth (August) and the event (November), covering the four seasons and approximately the entire range of temperatures to which the resistance elements of the bridge are subject to along a calendar year - case study Incheon Grand Bridge, Seoul, South Korea. The number of data pairs recorded, as we have noted, every 15 minutes, is initially 11,616, being difficult to process. Some software (e.g. Table Curve 2D) can work with a maximum of 3000 data pairs. In what follows we will examine the behaviour of a reinforced concrete element of the North Bridge Gap front line and we will build a mathematical model of its behaviour to sunshine, from the input data, one recording every hours, thus reducing the number of measurements to 2904. The aim is to obtain a mathematical model with a correlation coefficient above 0.9, which is also verified and validated. This model will allow us to calculate the expected position of the sensor mounted on the resistance element for a certain temperature, the degree of confidence of the result, the interval of residual values. Because the history of the evolution of temperatures for each moment analyzed is different it produces different results, but ones that fit the specified regressive mathematical model.

Mathematical Modelling Of The Bridges Structural Monitoring II

Technical University of Cluj Napoca, Faculty of Civil Engineering, Department of Terrestrial Measurement and Cadastre, 25 G. Baritiu St., 400027 Cluj-Napoca, Romania

Journal of Applied Engineering Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Mathematical Modelling Of The Bridges Structural Monitoring II"}

We have seen in the previous paper that in the case of resistance elements made of steel, at least in this case study, the structure’s response to strains, in...

Mathematical Modelling Of The Bridges Structural Monitoring II

Publié en ligne: 08 juin 2015

Pages: 91 - 100

Reçu: 11 mars 2015

Accepté: 19 mars 2015

DOI: https://doi.org/10.1515/jaes-2015-0012

Mots clés
Incheon Grand Bridge, Structural Health Monitoring, Mathematical Model, Sensors, Steel Structural Element

© G.M.T. Rădulescu et al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mathematical Modelling Of The Bridges Structural Monitoring II

Publié en ligne: 08 juin 2015

Pages: 91 - 100

Reçu: 11 mars 2015

Accepté: 19 mars 2015

DOI: https://doi.org/10.1515/jaes-2015-0012

Mots clésIncheon Grand Bridge, Structural Health Monitoring, Mathematical Model, Sensors, Steel Structural Element

© G.M.T. Rădulescu et al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Incheon Grand Bridge, Structural Health Monitoring, Mathematical Model, Sensors, Steel Structural Element