Artigos de Revista

The purpose of this paper is to present a simple yet highly effective method to reconstruct missing data in flow time series. The presence of missing values in network flow data severely restricts their use for an adequate management of billing systems and for network operation. Despite significant technology improvements, missing values are frequent due to metering, data acquisition and storage issues. The proposed method is based on a weighted function for forecast and backcast obtained from existing time series models that accommodate multiple seasonality. A comprehensive set of tests were run to demonstrate the effectiveness of this new method and results indicated that a model for flow data reconstruction should incorporate daily and seasonal components for more accurate predictions, the window size used for forecast and backcast should range between 1 and 4 weeks, and the use of two disjoint training sets to generate flow predictions is more robust to detect anomalous events than other existing methods. Results obtained for flow data reconstruction provide evidence of the effectiveness of the proposed approach.

The purpose of this paper is to present a simple yet highly effective method to reconstruct missing data in flow time series. The presence of missing values in network flow data severely restricts their use for an adequate management of billing systems and for network operation. Despite significant technology improvements, missing values are frequent due to metering, data acquisition and storage issues. The proposed method is based on a weighted function for forecast and backcast obtained from existing time series models that accommodate multiple seasonality. A comprehensive set of tests were run to demonstrate the effectiveness of this new method and results indicated that a model for flow data reconstruction should incorporate daily and seasonal components for more accurate predictions, the window size used for forecast and backcast should range between 1 and 4 weeks, and the use of two disjoint training sets to generate flow predictions is more robust to detect anomalous events than other existing methods. Results obtained for flow data reconstruction provide evidence of the effectiveness of the proposed approach.

A decision support system (DSS) tool for the assessment of intervention strategies (Alternatives) in an urban water system (UWS) with an integral simulation model called

The construction and maintenance of a road network involve the expenditure of large budgets. In order to optimize the investments in road infrastructures, designers and decision makers should have the instruments to make the most suitable decision of paving solutions for each particular situation. The life-cycle assessment is an important tool of different road pavement solutions with this purpose. This paper presents a study concerning the life-cycle cost analysis of different flexible and semi-rigid paving alternatives, with the objective to contribute for a better support in the decision process when designing new pavement structures. The analysis was carried out using data on construction costs of certain typical pavement structures and taking into consideration appropriate performance models for each type of structure being selected. The models were calibrated using results from long term performance studies across Europe and the maintenance strategies considered have taken into account the current practice also found in the European context. Besides the life-cycle administration costs, the proposed methodology also deals with user and environmental costs through its inclusion in the decision process using multi-criteria analysis. It was demonstrated that this methodology could be a simple and useful tool in order to achieve the most adequate paving solutions of a road network, in terms of construction and maintenance activities, based simultaneously on technical, economic and environmental criteria.

Resumo:Extreme sea levels along the Atlantic Iberian coast are determined through the development and application of a numerical model for tides and surges, followed by a statistical analysis of the model results. A recent statistical method is assessed using 131 years of data from the Brest tide gauge, and the number of years of data required for an accurate statistical analysis is estimated. The statistical method is extended to consider tide

Abstract A buried plastic pipe undergoes deformation, but it stabilizes at the end of a certain time not exceeding two years. Thus, there is an interest in determining the extrapolated creep of structured wall plastic pipes at 2 years. The main goal of this work is to present information regarding the assessment of results and their accuracy, based both on the requirements of the product standard [3] and on the uncertainty of the tests.

Advances in measurement and automation technologies enabled the deployment of monitoring systems with data acquisition at high frequency in Wastewater Treatment Plants (WWTP). The aim of this work is the design of soft sensors to predict hard-to-measure quality variables of wastewater required for mechanistic modeling of the biological treatment system in a real municipal WWTP. The input data collected in the WWTP using a flowmeter and spectro-photometric and electrochemical online probes, sampling campaigns and on-line analysis, was used for the development of soft sensors by multivariate analysis, like Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression. Exploratory data analysis was performed in order to detect outliers, patterns and correlations. PLS models for soft sensors were developed using leave-one-out cross validation and the predictive capacity of independent data was evaluated by root mean square error (RMSE). The normalized RMSE obtained for organic nitrogen prediction were 19.5% and 18.1%, using sensors with analytical and spectral data, respectively. The possibility of using spectro-photometric probes providing measurements of a single wavelength was evalu-ated in order to reduce the online monitoring investment costs.

Salt decay is one of the harshest, most frequent and more complex types of decay of porous materials in built heritage, including natural stones, ceramics and mortars. In this article, we address the mechanism of thermal expansion which is one of the least studied, yet most controversial, of those proposed over time to explain salt decay. We present a review of scientific literature on the topic, followed by a study of the effects of thermal expansion on a specific material, the well-known Ançã limestone. The study included experimental measurement of the linear thermal expansion coefficient of the Ançã, both in its natural state and with varying contents of sodium chloride, sodium sulphate or sodium nitrate. The results show that this coefficient: (i) is significantly higher when the stone is contaminated with salt; (ii) scales approximately with the amount of salt contained in the stone pores, regardless of the type of salt. Based on these results and on modelling of damage modes at the microscopic and macroscopic levels respectively, we conclude that thermal expansion can cause powdering, disaggregation or other types of decay consisting in internal loss of cohesion. However, it is not likely to cause exfoliation of salt loaded layers.

The 1:10 scale model of the 15th century Mustafa Pasha Mosque in Skopje, that underwent a comprehensiveshake table program, is modeled by the discrete elements approach. A rigid block model withnonlinear behavior concentrated at the joints was developed and calibrated by comparison with theobserved response. Time domain analyses of the discrete model were performed under the various levelsof dynamic excitation used in the shake table test. Under the lower levels of input, the time and frequencydomain characteristics of the shake table experimental response were fairly well simulated by thenumerical model. This model also predicted well the zones and the level of damages. For the higher inputlevels, the comparison was less satisfactory. Overall, the discrete element approach showed the capabilityto handle the dynamic nonlinear modeling of relatively complex masonry structures.