Uncertainty and Fuzzy Decisions in Earthquake Risk Evaluation of Buildings

The Northern region of Thailand has been considered as one of the seismic risk zones. However, most existing buildings in the area had been designed and constructed based on old building design codes without seismic consideration. Therefore, those buildings are required to upgrade based on earthquake building damage risk evaluation. With resource limitations, it is not feasible to retrofit all buildings in a short period. In addition, the results of the risk evaluation contain uncertain inputs and outputs. The objective of this study is to prioritize building retrofit based on fuzzy earthquake risk assessment. The risk assessment of a building was made considering the risk factors including (1) building vulnerability, (2) seismic intensity and (3) building values. Then, the total risk was calculated by integrating all the risk factors with their uncertainties using a fuzzy rule based model. An example of the retrofit prioritization is shown here considering the three fuzzy factors. The ranking is hospital, temple, school, government building, factory and house, respectively. The result helps decision makers to screen and prioritize the building retrofitting in the seismically prone area

Pre-earthquake fuzzy logic-based rapid hazard assessment of reinforced concrete buildings

The main purpose of this paper is to present a rapid building assessment fuzzy logic (FL) modelling for risk assessment based on expert construction engineering verbal informatics. Before an earthquake, a set of input expert assessment variables are transformed into five types of hazard categorization as "no damage", "slight damage", "moderate damage", "severe damage", and "collapse". Main variables are reported by expert engineers based on visual inspection of structural components in addition to the building location's peak ground velocity (PGV) micro zonation numerical value, soil type and building's material information. Each input variable and output hazard class is fuzzified. A valid set of fuzzy rule base components is written based on input variables, each of which has an appropriate output hazard class. The fuzzy hazard assessment model has input and output variables in terms of fuzzy sets. Thus, the overall model output is in the form of a fuzzy set and then defuzzified to find the percentage of each hazard class for a single building. The application of this fuzzy logic model is presented for twenty existing reinforced concrete buildings, and the final hazard categories of these buildings are presented with interpretations and recommendations.Istanbul Medipol Universit

Fuzzy Inference System (FIS) model for the seismic parameters of code-based earthquake response spectra

The response spectra defined in seismic design codes include crisp classifications of seismic parameters, which directly affect the spectra’s shape and greatly alter seismic design loads. The optimum design phase seismic forces have an important role in the efficiency of the construction costs and structural safety. Various parameters are used to calculate the seismic design forces, especially presented in the codes with earthquake design spectra. This study presents a rule-based fuzzy inference model with fuzzy sets to determine these parameters using fuzzy inference system (FIS) modelling, which is the most appropriate approach among the different alternatives because both the input and output variables have numerical and linguistic uncertainties in the earthquake problem. Using the seismic zone factor of the region and shear wave velocity of the soil profile as inputs, the model generates the seismic coefficients and peak ground acceleration values of the response spectra specified in the Uniform Building Code (UBC, 1997). The response spectra in this code can be easily generated with these seismic coefficients after their fuzzification. Response spectra of twenty-five different sample cases with and without the FIS model are generated, which provide comparisons for the model superiority assessment. Significant differences are observed between the crisp logic and the FIS model-generated spectra. It is suggested that the FIS model can be modified and applied to various parameters to generate response spectra in different seismic design codes.Istanbul Medipol Universit

Fuzzy Sets Applications in Civil Engineering Basic Areas

Civil engineering is a professional engineering discipline that deals with the design, construction, and maintenance of the physical and naturally built environment, including works like roads, bridges, canals, dams, and buildings. This paper presents some Fuzzy Logic (FL) applications in civil engeering discipline and shows the potential of facilities of FL in this area. The potential role of fuzzy sets in analysing system and human uncertainty is investigated in the paper. The main finding of this inquiry is FL applications used in different areas of civil engeering discipline with success. Once developed, the fuzzy logic models can be used for further monitoring activities, as a management tool