The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

Using glass-fibre reinforced polymer composites in the production of sustainable water storage vessels

The present work focuses on the use of the life cycle assessment (LCA) and life cycle costing (LCC)methodologies to evaluate environmental and economic impacts of polymers and polymer composites materials and products. Initially a literature review is performed in order to assess the scope and limitations of existing LCA and LCC studies on these topics. Then, a case study, based on the production of a water storage glass-fibre reinforced polymer (GFRP) composite storage tank, is presented. The storage tank was evaluated via a LCA/LCC integrated model, a novel way of analysing the life cycle (LC) environmental and economic performances of structural products. The overarching conclusion of the review is that the environmental and economic performances of polymers composites in non-mobile applications are seldom assessed and never in a combined integrated way.

Potential implications of ketamine anesthesia on zebrafish behavior

Dissertação de mestrado integrado em Psicologia

Development of a thermoelectric generator for the exhaust of a vehicle

Dissertação de mestrado integrado em Engenharia Mecânica

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Oxygen mass transfer impact on citric acid production by Yarrowia lipolytica from crude glycerol

Production of citric acid from crude glycerol from biodiesel industry, in batch cultures of Yarrowia lipolytica W29 was performed in a lab-scale stirred tank bioreactor in order to assess the effect of oxygen mass transfer rate in this bioprocess. An empirical correlation was proposed to describe oxygen volumetric mass transfer coefficient (kLa) as a function of operating conditions (stirring speed and specific air flow rate) and cellular density. kLa increased according with a power function with specific power input and superficial gas velocity, and slightly decreased with cellular density. The increase of initial kLa from 7 h-1 to 55 h-1 led to 7.8-fold increase of citric acid final concentration. Experiments were also performed at controlled dissolved oxygen (DO) and citric acid concentration increased with DO up to 60% of saturation. Thus, due to the simpler operation setting an optimal kLa than at controlled DO, it can be concluded that kLa is an adequate parameter for the optimization of citric acid production from crude glycerol by Y. lipolytica and to be considered in bioprocess scale-up. Our empirical correlation, considering the operating conditions and cellular density, will be a valid tool for this purpose.

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.

Influência do fator visão do céu na propagação do ruído em zonas urbanas

Dissertação de mestrado integrado em Engenharia Civil

Continuous-flow precipitation as a route to prepare highly controlled nanohydroxyapatite

[Excerpt] Hydroxyapatite Ca10(PO4)6(OH)2 (HAp) has been widely used for biomedical purposes because of its exceptional biocompatibility, bioactivity and osteoconductivity [1]. As these properties are directly related to HAp particles characteristics (size, morphology and purity), a very good control of the reaction conditions is required to obtain particles with the desired properties. Usually, HAp is synthesized by wet chemical precipitation in stirred tank batch reactors that often lead to inconsistencies in product specifications due to their low mixing efficiency [2]. (...)

Comunicar a Direito

Relatório de estágio de mestrado em Ciências da Comunicação (área de especialização em Informação e Jornalismo)

FluidUM: análise de fluidos de um automóvel

Dissertação de mestrado integrado em Engenharia Mecânica