Ricardo M. S. F. Almeida

Pushover analysis of asymmetric three‐dimensional building frames

Abstract The effect of higher modes of vibration on the total non‐linear dynamic response of a structure is a very important and unsolved problem. To simplify the process the static non‐linear pushover analysis was proposed associated with the capacity spectrum method, utilising a load pattern proportional to the shape of the fundamental mode of vibration of the structure. The results of the pushover analysis, with this load pattern, are very accurate for structures that respond primarily in the fundamental mode. But when the higher modes of vibration become important for the total response of the structure, this load pattern loses its accuracy. To minimise this problem a new multimode load pattern is proposed based on the relative participation of each mode of vibration in the elastic response of a structure subjected to an earthquake ground motion. This load pattern is applied to the analyses of symmetric frames as well as to stiffness asymmetric and mass asymmetric irregular building frames, under seis...

Application of Data Mining Techniques

In this chapter, the data mining techniques described in chapter 3 are applied to the case study described in chapter 4. The overcome of the difficulties associated with the analysis process of the data using appropriate techniques is demonstrated.

An insulation thickness optimization methodology for school buildings rehabilitation combining artificial neural networks and life cycle cost

AbstractThe energy efficiency of buildings, including public buildings, is a major concern for all European governments, since they are responsible for a large share of the total energy bill of the states. School buildings play an important role in these costs. The best strategy for reversing this scenario includes efforts on buildings retrofit, seeking to optimize their energy efficiency and indoor environmental quality. However, in the unfavourable economic climate we are experiencing, which requires great prudence when it comes to public investment, special attention should be given to this multi-objective optimization process. In this research, a methodology to optimize the insulation thickness of the external walls and roof on school buildings retrofit is proposed. The procedure includes the optimization of the building performance considering the following objectives: the minimization of the annual heating load; the minimization of the discomfort in the classrooms due to overheating; and the minimiz...

Indoor Environmental Quality

This chapter starts by explaining the notion of indoor environmental quality. Afterwards a complete description of thermal comfort and indoor air quality is provided. The thermal comfort concept, the factors that most influence it and the criteria for thermal comfort assessment, including the adaptive models, are described in detail. Regarding the indoor air quality, the most important pollutants are presented, including their concentration limits currently in force in Portugal.

Data Mining Techniques

This chapter presents available data mining techniques that can be of interest for application in indoor environment analysis. Descriptive statistics tools are presented with the focus on probability distribution and correlation analysis. Multivariate data techniques are also addressed, with a special focus on principal components determination and cluster analysis.

Indoor Hygrothermal Conditions

The evaluation of indoor hygrothermal conditions is described, supported by a literature review. Involved parameters and standardized methodologies are summarized. The procedures for evaluation of human comfort are also briefly described.

Indoor Environmental Quality in Classrooms: Case Studies

This chapter presents the results of the in-situ evaluation of the hygrothermal performance of classrooms of 9 Portuguese school buildings (2 non-retrofitted and 7 recently retrofitted). Temperature, relative humidity and carbon dioxide concentration were monitored in continuum for at least 1 week in each classroom. Results are analysed and discussed.

Optimization and Approximation Methods

This chapter describes the basic mathematical formulation of the Artificial Neural Networks and the multi-objective optimization methods. The concept of Artificial Neural Network is presented and its potential for engineering applications is highlighted. The multi-objective optimization problem is described and formulated and the evolutionary algorithms are described as very promising tools for solving this kind of problems.