Characterization of earth-based mortars for rammed earth repair

All over the world, many earth buildings are deteriorating due to lack of maintenance and repair. Repairs on rammed earth walls are mainly done with mortars, by rendering application; however, often the repair is inadequate, resorting to the use of incompatible materials, including cement-based mortars. It has been observed that such interventions, in walls that until that day only had presented natural ageing issues, created new problems, much more dangerous for the building than the previous ones, causing serious deficiencies in this type of construction. One of the problems is that the detachment of the new cement-based mortar rendering only occurs after some time but, until that occurrence, degradations develop in the wall itself. When the render detaches, instead of needing only a new render, the surface has to be repaired in depth, with a repair mortar. Consequently, it has been stablished that the renders, and particularly repair mortars, should have physical, mechanical and chemical properties similar to those of the rammed earth walls. This article intends to contribute to a better knowledge of earth-based mortars used to repair the surface of rammed earth walls. The studied mortars are based on four types of earth: three of them were collected from non-deteriorated parts of walls of unstabilized rammed earth buildings located in Alentejo region, south of Portugal; the fourth is a commercial earth, consisting mainly of clay. Other components were also used, particularly: sand to control shrinkage; binders stabilizers such as dry hydrated air-lime, natural hydraulic lime, Portland cement and natural cement; as well as natural vegetal fibers (hemp fibers). The experimental analysis of the mortars in the fresh state consisted in determining the consistency by flow table and the bulk density. In the hardened state, the tests made it possible to evaluate the following properties: linear and volumetric shrinkage; capillary water absorption; drying capacity; dynamic modulus of elasticity; flexural and compressive strength.

Study of AC losses in medium-sized high temperature superconducting coils

The study of AC losses in superconducting pancake coils is of utmost importance for the development of superconducting devices. Due to different technical difficulties this study is usually performed considering one of two approaches: considering superconducting coils of few turns and studying AC losses in a large frequency range vs. superconducting coils with a large number of turns but measuring AC losses only in low frequencies. In this work, a study of AC losses in 128 turn superconducting coils is performed, considering frequencies ranging from 50 Hz till 1152 Hz and currents ranging from zero till the critical current of the coils. Moreover, the study of AC losses considering two different simultaneous harmonic components is also performed and results are compared to the behaviour presented by the coils when operating in a single frequency regime. Different electrical methods are used to verify the total amount of AC losses in the coil and a simple calorimetric method is presented, in order to measure AC losses in a multi-harmonic context. Different analytical and numerical methods are implemented and/or used, to design the superconducting coils and to compute the total amount of AC losses in the superconducting system and a comparison is performed to verify the advantages and drawbacks of each method.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.