The effect of linseed oil on the properties of lime-based restoration mortars

The traditional lime mortar is composed of hydrated lime, sand and water. Besides these constituents it may also contain additives aiming to modify fresh mortar´s properties and/or to improve hardened mortar´s strength and durability. Already in the first civilizations various additives were used to enhance mortar´s quality, among the organic additives, linseed oil was one of the most common. From literature we know that it was used already in Roman period to reduce water permeability of a mortar, but the mechanism and the technology, e.g. effects of different dosages, are not clearly explained. There are only few works studying the effect of oil experimentally. Knowing the function of oil in historical mortars is important for designing a new compatible repair mortar. Moreover, linseed oil addition could increase the sometimes insufficient durability of lime-based mortars used for reparation and it could be a natural alternative to synthetic additives. In the present study, the effect of linseed oil on the properties of six various lime-based mortars has been studied. Mortars´ compositions have been selected with respect to composition of historical mortars, but also mortars used in a modern restoration practise have been tested. Oil was added in two different concentrations – 1% and 3% by the weight of binder. The addition of 1% of linseed oil has proved to have positive effect on mortars´ properties. It improves mechanical characteristics and limits water absorption into mortar without affecting significantly the total open porosity or decreasing the degree of carbonation. On the other hand, the 3% addition of linseed oil is making mortar to be almost hydrophobic, but it markedly decreases mortars´ strength. However, all types of tested lime-based mortars with the oil addition showed significantly decreased water and salt solution absorption by capillary rise. Addition of oil into mortars is also decreasing the proportion of pores which are easily accessible to water. Furthermore, mortars with linseed oil showed significantly improved resistance to salt crystallization and freeze-thaw cycles. On the base of the obtained results, the addition of 1% of linseed oil can be taken into consideration in the design of mortars meant to repair or replace historic mortars.

Assessment of Daily Life Mobility Levels using Wearable Inertial Sensors and Minimun Measured Input Models

Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.

Statistical Physics and Modeling of Human Mobility

In this thesis, we extend some ideas of statistical physics to describe the properties of human mobility. By using a database containing GPS measures of individual paths (position, velocity and covered space at a spatial scale of 2 Km or a time scale of 30 sec), which includes the 2% of the private vehicles in Italy, we succeed in determining some statistical empirical laws pointing out "universal" characteristics of human mobility. Developing simple stochastic models suggesting possible explanations of the empirical observations, we are able to indicate what are the key quantities and cognitive features that are ruling individuals' mobility. To understand the features of individual dynamics, we have studied different aspects of urban mobility from a physical point of view. We discuss the implications of the Benford's law emerging from the distribution of times elapsed between successive trips. We observe how the daily travel-time budget is related with many aspects of the urban environment, and describe how the daily mobility budget is then spent. We link the scaling properties of individual mobility networks to the inhomogeneous average durations of the activities that are performed, and those of the networks describing people's common use of space with the fractional dimension of the urban territory. We study entropy measures of individual mobility patterns, showing that they carry almost the same information of the related mobility networks, but are also influenced by a hierarchy among the activities performed. We discover that Wardrop's principles are violated as drivers have only incomplete information on traffic state and therefore rely on knowledge on the average travel-times. We propose an assimilation model to solve the intrinsic scattering of GPS data on the street network, permitting the real-time reconstruction of traffic state at a urban scale.