3 resultados para method for accident investigation

em Universidad de Alicante


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This paper shows the results of an experimental analysis on the bell tower of “Chiesa della Maddalena” (Mola di Bari, Italy), to better understand the structural behavior of slender masonry structures. The research aims to calibrate a numerical model by means of the Operational Modal Analysis (OMA) method. In this way realistic conclusions about the dynamic behavior of the structure are obtained. The choice of using an OMA derives from the necessity to know the modal parameters of a structure with a non-destructive testing, especially in case of cultural-historical value structures. Therefore by means of an easy and accurate process, it is possible to acquire in-situ environmental vibrations. The data collected are very important to estimate the mode shapes, the natural frequencies and the damping ratios of the structure. To analyze the data obtained from the monitoring, the Peak Picking method has been applied to the Fast Fourier Transforms (FFT) of the signals in order to identify the values of the effective natural frequencies and damping factors of the structure. The main frequencies and the damping ratios have been determined from measurements at some relevant locations. The responses have been then extrapolated and extended to the entire tower through a 3-D Finite Element Model. In this way, knowing the modes of vibration, it has been possible to understand the overall dynamic behavior of the structure.

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Objective: To analyse the time evolution of the rates of mortality due to motor vehicle traffic accidents (MVTA) injuries that occurred among the general population of Comunitat Valenciana between 1987 and 2011, as well as to identify trend changes by sex and age group. Methods: An observational study of annual mortality trends between 1987 and 2011. We studied all deaths due to MVTA injuries that occurred during this period of time among the non-institutionalised population residing in Comunitat Valenciana (a Spanish Mediterranean region that had a population of 5,117,190 inhabitants in 2011). The rates of mortality due to MVTA injuries were calculated for each sex and year studied. These rates were standardised by age for the total population and for specific age groups using the direct method (age-standardised rate – ASR). Joinpoint regression models were used in order to detect significant trend changes. Additionally, the annual percentage change (APC) of the ASRs was calculated for each trend segment, which is reflected in statistically significant joinpoints. Results: For all ages, ASRs decrease greatly in both men and women (70% decrease between 1990 and 2011). In 1990 and 2011, men have rates of 36.5 and 5.2 per 100,000 men/year, respectively. In the same years, women have rates of 8.0 and 0.9 per 100,000 women/year, respectively. This decrease reaches up to 90% in the age group 15–34 years in both men and women. ASR ratios for men and women increased over time for all ages: this ratio was 3.9 in 1987; 4.6 in 1990; and 5.8 in 2011. For both men and women, there is a first significant segment (p < 0.05) with an increasing trend between 1987 and 1989–1990. After 1990, there are 3 segments with a significant decreasing APC (1990–1993, 1993–2005 and 2005–2011, in the case of men; and 1989–1996, 1999–2007 and 2007–2011, in the case of women). Conclusion: The risk of death due to motor vehicle traffic accidents injuries has decreased significantly, especially in the case of women, for the last 25 years in Comunitat Valenciana, mainly as of 2006. This may be a consequence of the road-safety measures that have been implemented in Spain and in Comunitat Valenciana since 2004. The economic crisis that this country has undergone since 2008 may have also been a contributing factor to this decrease. Despite the decrease, ASR ratios for men and women increased over time and it is still a high-risk cause of death among young men. It is thus important that the measures that helped decrease the risk of death are maintained and improved over time.

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The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.