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Various factors influence wildfire probability, including land use/land cover (LULC), fuel types, and their moisture content, meteorological conditions, and terrain characteristics. The Adriatic Sea coastal area in Croatia has a long record of devastating wildfires that have caused severe ecological and economic damages as well as the loss of human lives. Assessing the conditions favorable for wildfires and the possible damages are crucial in fire risk management. Adriatic settlements and ecosystems are highly vulnerable, especially during summer, when the pressure from tourist migration is the highest. However, available fire risk models designed to fit the macro-scale level of assessment cannot provide information detailed enough to meet the decision-making conditions at the local level. This paper describes a model designed to assess wildfire risks at the meso-scale, focusing on environmental and anthropogenic descriptors derived from moderate- to high-resolution remote sensing data (Sentinel-2), Copernicus Land Monitoring Service datasets, and other open sources. Risk indices were integrated using the multi-criteria decision analysis method, the analytic hierarchy process (AHP), in a GIS environment. The model was tested in three coastal catchments, each having recently experienced severe fire events. The approach successfully identified zones at risk and the level of risk, depending on the various environmental and anthropogenic conditions.

Considering that the machining of composites particularly fiber-reinforced polymer composites (FRPCs) has remained a challenge associated with their heterogeneity and anisotropic nature, damage caused by drilling operations can be considerably mitigated by following optimum cutting parameters. In this work, we numerically evaluated the effects of cutting parameters, such as feed rate and spindle speed, on the thrust force and torque during the drilling of glass-fiber-reinforced polymers (GFRPs). A meso-scale, also known as unidirectional ply-level-based finite element modeling, was employed assuming an individual homogenized lamina with transversely isotropic material principal directions. To initiate the meso-scale damage in each lamina, 3D formulations of Hashin’s failure theory were used for fiber damage and Puck’s failure theory was implemented for matrix damage onset via user subroutine VUMAT in ABAQUS. The developed model accounted for the complex kinematics taking place at the drill–workpiece interface and accurately predicted the thrust force and torque profiles as compared with the experimental results. The thrust forces for various drilling parameters were predicted with a maximum of 10% error as compared with the experimental results. It was found that a combination of lower feed rates and higher spindle speeds reduced the thrust force, which in turn minimized the drilling-induced damage, thus providing useful guidelines for drilling operations with higher-quality products. Finally, the effect of coefficient of friction was also investigated. Accordingly, a higher coefficient of friction between the workpiece and drill-bit reduced the thrust force.

Damage initiation and crack propagation in concrete are associated with localisation of energy dissipation by the concrete meso-structure. Meso-scale models are, therefore, required for realistic analysis of concrete non-linear behaviour. Such models are constructed either from X-ray Computed Tomography images (image-based modelling) or by in silico meso-structure generation (parametric modelling), while both approaches are widely used and their advantages and disadvantages are recognised, little work is done on comparing their performance in predicting measured macroscopic behaviour with equivalent constitutive relations for meso-structural features. This work uses microstructure characterisation and mechanical behaviour data to construct, validate and compare the two modelling approaches. The macroscopic behaviour obtained with both meso-structural models is found to be in good agreement with experimental data. Differences are observed only between the predicted distributions of damage within specimens. These outcomes suggest that the computationally simpler parametric meso-structures are sufficient to derive stress–strain behaviour for engineering-scale models in the absence of other environmental factors. The observed differences in damage distribution could be important for analysis of coupled behaviour, e.g., mass transport and chemical reactions affecting local mechanical properties and being affected by local damage. Establishing the importance of damage distribution is such cases requires further research.

Two-dimensional meso-scale finite element models with real aggregates are developed using images obtained by digital image processing to simulate crack propagation processes in concrete under uniaxial compression loading. The finite element model is regarded as a three-phase composite material composed of aggregate, mortar matrix and interface transition zone (ITZ). Cohesive elements with traction–separation laws are used to simulate complex nonlinear fracture. During the experiment, digital image correlation (DIC) was used to obtain the deformation and cracks of the specimens at different loading stages. The concept of strain ratio is proposed to describe the effectiveness of simulation. Results show that the numerical strain ratio curve and stress–strain curves are both in good agreement with experimental data. The consistency between the cracks obtained by simulation and those obtained by DIC shows the good performance of cohesive elements as well as the effectiveness of simulation. In summary, the model is able to provide accurate predictions of the whole fracture process in concrete under uniaxial compression loading.

Over the years, floods have caused economic damage that has impacted development in many regions. As a result, a comprehensive overview of flood-prone areas at the provincial scale is important in order to identify zones that require detailed assessment with hydrodynamic models. This study presents two approaches that were used to prioritize flood-prone areas at the provincial scale in New Brunswick, Canada. The first approach is based on a spatial multi-criteria evaluation (SMCE) technique, while the second approach pertains to flood exposure analysis. The results show the variation in the identified flood-prone areas and, depending on the methodology and scenario used, prioritization changes. Therefore, a standard methodology might not be feasible and should be developed based on the objective of the study. The results obtained can be useful for flood risk practitioners when making decisions about where to commence detailed flood hazard and risk assessment.

This paper reports a numerical approach for modelling the thermal behavior and heat accumulation/liberation of sustainable cementitious composites made with Recycled Brick Aggregates (RBAs) employed as carriers for Phase-Change Materials (PCMs). In the framework of the further development of the fixed grid modelling method, classically employed for solving the well-known Stefan problem, an enthalpy-based approach and an apparent calorific capacity method have been proposed and validated. More specifically, the results of an experimental program, following an advanced incorporation and immobilization technique, developed at the Institut für Werkstoffe im Bauwesen for investigating the thermal responses of various combinations of PCM-RBAs, have been considered as the benchmark to calibrate/validate the numerical results. Promising numerical results have been obtained, and temperature simulations showed good agreement with the experimental data of the analyzed mixtures.

Floods, at present, may constitute the natural phenomenon with the greatest impact on the deterioration of cultural heritage, which is the reason why the study of flood risk becomes essential in any attempt to manage cultural heritage (archaeological sites, historic buildings, artworks, etc.) This management of cultural heritage is complicated when it is distributed over a wide territory. This is precisely the situation in the region of Castile and León (Spain), in which 2155 cultural heritage elements are registered in the Catalog of Cultural Heritage Sites of Castile and León, and these are distributed along the 94,226 km2 of this region. Given this scenario, the present study proposes a methodological framework of flood risk analysis for these cultural heritage sites and elements. This assessment is based on two main processing tools to be developed in addition: on the one hand, the creation of a GIS database in which to establish the spatial relationship between the cultural heritage elements and the flow-prone areas for different flood return periods and, on the other hand, the creation of a risk matrix in which different variables are regarded as associated both to flood hazard (return period, flow depth, and river flooding typology) and to flood vulnerability (construction typology, and construction structural relationship with the hydraulic environment). The combination of both tools has allowed us to establish each cultural heritage flood risk level, making its categorization of risk possible. Of all the cultural heritage sites considered, 18 of them are categorized under an Extreme flood risk level; and another 24 show a High potential flood risk level. Therefore, these are about 25% to 30% of all cultural heritage sites in Castile and León. This flood risk categorization, with a scientific basis of the cultural heritage sites at risk, makes it possible to define territories of high flood risk clustering; where local scale analyses for mitigation measures against flood risk are necessary.

The north-eastern escarpment of Madagascar harbours the island’s last remaining large-scale humid forest massifs surrounded by a small-scale agricultural mosaic. There is high deforestation, commonly thought to be caused by shifting cultivation practiced by local land users to produce upland rice. However, little is known about the dynamics between forest and shifting cultivation systems at a regional level. Our study presents a first attempt to quantify changes in the extent of forest and different agricultural land cover classes, and to identify the main dynamics of land cover change for two intervals, 1995–2005 and 2005–2011. Over the 16-year study period, the speed of forest loss increased, the total area of upland rice production remained almost stable, and the area of irrigated rice fields slightly increased. While our findings seem to confirm a general trend of land use intensification, deforestation through shifting cultivation is still on the rise. Deforestation mostly affects the small forest fragments interspersed in the agricultural mosaic and is slowly leading to a homogenization of the landscape. These findings have important implications for future interventions to slow forest loss in the region, as the processes of agricultural expansion through shifting cultivation versus intensified land use cannot per se be considered mutually exclusive.

The aim of this paper is to explore possible links between forest cover change and characteristics of social-ecological systems at sub-national scale based mainly on census data. We assessed relationships between population density, poverty, ethnicity, accessibility and forest cover change during the last decade for four regions of Bolivia and the Lao PDR, combining a parcel-based with a cell-based approach. We found that accessibility is a key driver of forest cover change, yet it has the effect of intensifying other economic and policy-related underlying drivers, like colonization policies, cash crop demand, but also policies that lead to forest gain in one case. Poverty does not appear as a driver of deforestation, but the co-occurrence of poverty and forest loss driven by external investments appears critical in terms of social-ecological development. Ethnicity was found to be a moderate explanatory of forest cover change, but appears as a cluster of converging socio-economic characteristics related with settlement history and land resource access. The identification of such clusters can help ordering communities into a typology of social-ecological systems, and discussing their possible outcomes in light of a critical view on forest transition theory, as well as the relevance and predictive power of the variables assessed. Résumé: L’objectif de cet article est d’explorer les liens entre le changement de la couverture forestière et les caractéristiques des systèmes socio-écologiques à l’échelle nationale, principalement à l’aide de données de recensement. Nous avons évalué les relations entre la densité de population, la pauvreté, l’ethnicité, l’accessibilité et le changement de la couverture forestière pendant la dernière décennie pour quatre régions de Bolivie et du Laos, en combinant des approches par parcelles et par cellules. Nous avons constaté que l’accessibilité est un facteur clé du changement de la couverture forestière, tandis qu’elle a pour effet d'intensifier d'autres facteurs économiques et politiques sous-jacents, comme les politiques de colonisation, la demande de cultures de rente, mais aussi, dans un cas, des politiques conduisant à un accroissement de la forêt. La pauvreté n’apparait pas comme un facteur de déforestation, mais la co-occurrence de la pauvreté et de la perte de forêt entrainée par les investissements extérieurs semble critique en termes de développement socio-écologique. L'ethnicité se révèle être modérément explicative du changement de la couverture forestière, mais elle apparait comme un ensemble de caractéristiques socio-économiques convergentes liées à l'histoire de l’implantation humaine et à l'accès aux ressources foncières. L'identification de tels ensembles peut aider à classer les communautés selon une typologie des systèmes socio-écologiques, et à discuter leurs possibles impacts sur la forêt avec un point de vue critique sur la théorie de la transition forestière, ainsi que la pertinence et la puissance prédictive des variables évaluées.

IN-depth SYnthetic Model for Flood Damage Estimation (INSYDE) is a model for the estimation of flood damage to residential buildings at the micro-scale. This study investigates the sensitivity of INSYDE to the accuracy of input data. Starting from the knowledge of input parameters at the scale of individual buildings for a case study, the level of detail of input data is progressively downgraded until the condition in which a representative value is defined for all inputs at the census block scale. The analysis reveals that two conditions are required to limit the errors in damage estimation: the representativeness of representatives values with respect to micro-scale values and the local knowledge of the footprint area of the buildings, being the latter the main extensive variable adopted by INSYDE. Such a result allows for extending the usability of the model at the meso-scale, also in different countries, depending on the availability of aggregated building data.