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Prioritization of Preventive Measures: A Multi-Criteria Approach to Risk Mitigation in Road Infrastructure Projects
No full textRisk management in construction projects is a critical process aimed at identifying,
evaluating, and mitigating potential risks that could impact project performance.
Preventive measures play a central role in this process, serving as proactive strategies to
minimize the likelihood and impact of risks on project outcomes. This study involved
37 experts from multidisciplinary fields related to road infrastructure, ensuring a diverse
and comprehensive perspective on risk evaluation and prevention. The DELPHI method
was employed to systematically define key risks and their corresponding preventive measures,
providing a structured foundation for further analysis. The experts evaluated
302 preventive measures across 56 risks using 4 predefined criteria: implementation costs,
time required for implementation, implementation complexity, and probability of success.
A multi-criteria decision making (MCDM) approach was then applied to analyze these evaluations,
enabling the prioritization of preventive measures and the allocation of resources
toward the most effective strategies. Additionally, fuzzy logic was employed to analyze
and validate the results, providing a complementary approach to the MCDM methodology.
The results of this research provide a robust framework for risk management, offering
practical guidance for decision makers in the construction industry. By integrating expert
judgment, systematic evaluation, and advanced analytical methods, this study delivers
actionable insights and establishes a reliable methodology for enhancing the effectiveness
of risk mitigation in road infrastructure projects
Vascular plant nano-hotspots in the central Balkan Peninsula – A novel GIS-based approach for identifying centres of species richness
No full textAlthough the Balkan Peninsula is one of the most biodiverse regions in Europe, there is still a lack of knowledge about its plant diversity. This study aimed to fill this knowledge gap by studying the spatial patterns of plant diversity on three massifs that had previously been identified as hotspots for endemics, Arctic-alpine and Boreal relics. To achieve this objective, we employed data gap and GIS analysis techniques to identify species-rich areas and to assess the relationship between taxa richness and the components of environmental heterogeneity. Targeted field surveys were carried out over two seasons, and a total of 97 environmental factors were selected as elements of environmental heterogeneity. A considerable number of hotspots of plant richness were identified, comprising 18 actual and 57 potential nano-hotspots. Most of the identified potential nano-hotspots are situated in areas characterized by a pronounced canyon or ravine formation, while the lowest number was observed at the highest elevations of the mountains, especially in regions where silicate substrates predominate. Our findings confirm the importance of factors previously identified as pivotal, including terrain ruggedness, topoclimate, elevation, geological substrate, and vegetation types, and for the first time suggest that hydrographic factors exert a strong influence on patterns of species richness. Given the considerable taxa richness observed in the ravine habitats of the study area, which makes them of high conservation value, it is essential to implement robust protective mechanisms to mitigate the impending effects of global warming and carefully plan the construction of hydropower plants
In-plane behaviour of RC frames with traditional and decoupled infills: parametric study
No full textMasonry infills are used as outer and inner partitions in reinforced concrete (RC) frame buildings. Although regarded as non-structural elements, masonry infills are activated under seismic actions. Because of this activation, masonry infills experience life-threatening damage. Moreover, they affect the seismic response of the whole RC frame structure, as they modify the dynamic characteristics of the structure. An innovative decoupling solution is developed to improve the seismic response of the infilled RC frames. In this paper, the in-plane behaviour of the RC frames with traditional and innovative decoupled infills is investigated by means of the simplified micro-model developed in Abaqus. Firstly, the numerical model is validated against the in-plane experimental tests on the RC frames, fully infilled with traditional and decoupled infill. Afterwards, a parametric study is carried out, focusing on the effect of the brick thickness and infill height-to-length ratio on the in-plane behaviour of the infilled RC frames. The level of the frame-infill interaction is evaluated through a comparison of the numerical results on the referent bare RC frame and RC frames with traditional and decoupled infills. The damage on masonry infills and surrounding RC frames, infill contribution forces and initial in-plane stiffness of the RC frames are observed. Additionally, a distribution of internal forces on the RC frames is evaluated in the post-processing of the results, which represents an important novelty of the study. Numerical results show that the decoupling system significantly reduces the activation of the decoupled infills, for all investigated infill geometries. Furthermore, the overall in-plane response of the RC frames with decoupled infills is very similar to the in-plane response of the bare RC frame up to 2.0 % of in-plane drift, which is certainly not the case for the traditionally infilled RC frames
A Geospatial Assessment Toolbox for Spatial Allocation of Large-Scale Nature-Based Solutions for Hydrometeorological Risk Reduction
No full textThe compounding effects of hydrometeorological hazards are being driven by climate change. As urban areas expand, this leads to degradation of the surrounding environment and exposes more people to hazards. Growing losses show that conventional approaches to addressing these issues can compound these problems. Over the last few decades, nature-based solutions (NBSs) have become an increasingly popular alternative. These measures, inspired by natural processes, have shown potential for reducing hazards by complementing traditional approaches and providing co-benefits in the form of eco-system services. With the adoption of NBSs becoming a more mainstream approach, there is a need for tools that support the planning and implementation of interventions. Geospatial suitability assessment is a part of this planning process. Existing tools are limited in their
application for large-scale measures. This paper intends to improve this by building upon a multi-criteria analysis (MCA)-based approach that incorporates biophysical and land use criteria and conditions for mapping the suitability of large-scale NBSs. The methodology was developed and tested on six sites to assess the suitability of floodplain restoration, retention or detention, afforestation, and forest buffer strips. The resulting suitability maps also show potential for combining two or more measures for greater risk reduction
Machine learning model for predicting hourly energy consumption in non-residential buildings based on meteorological data
No full textAccurate forecasting of hourly energy consumption in non-residential buildings is
essential for optimizing operations and supporting demand-side management and may offer
insights into inefficiencies that prompt further analysis relevant to renovation planning. This
study develops a machine learning model based on the K-Nearest Neighbors algorithm, trained
on the Building Data Genome Project (BDGP) dataset using only meteorological and temporal
inputs. The model was evaluated on a subset of 52 buildings across four seasonal periods and
various energy intensity categories. The model performed best during autumn and summer, with
an average RMSE as low as 14.9 kWh and 15.8 kWh, and an average MAPE of 0.216 in autumn.
The lowest individual MAPE of 0.026 was recorded in high-consumption buildings at the start
of the year, indicating strong predictive accuracy under stable conditions. Statistical testing
confirmed that the energy consumption category significantly affects model accuracy (Kruskal
Wallis p = 0.0004), while seasonal variation did not show a statistically significant effect,
suggesting the model’s robustness over time. The novelty of this work lies in the integration of
time-series clustering with KMeans, applied to stratified samples from a large open dataset,
enabling generalizable and seasonally consistent predictions
Synchronous Measurement of Optical Transmission and Viscoelastic Properties of Polymer Optical Fibers
No full textIn this paper, synchronous mechanical and optical measurements are proposed using
the dual cantilever mode of dynamic mechanical analysis (DMA). It was demonstrated
that this mode enables the detection of phase transitions in both the core and cladding
materials of polymer optical fibers (POFs), with corresponding changes in optical signal
intensity observed across different light wavelengths. In dual cantilever mode DMA, an
increase in optical transmission was recorded between the two detected glass transition
temperatures. The initial increase in transmission is attributed to cladding softening and
the consequent reduction in internal stresses in the POF, while the maximum in optical
transmission coincides with the beginning of the phase transition in the core material. To
compare and interpret the optical and thermo-mechanical results, Differential scanning
calorimetry (DSC) and Fourier transform infrared (FTIR) measurements were carried out
on POF pieces, as well as separately on the core and cladding materials. This integrated
technique yields quantitative data on a material’s viscoelasticity and light-transmission
changes, making it valuable for quality control and for predicting the long-term behavior
of advanced POFs in various applications
Publicly available landslide inventories in Serbia – status, challenges and perspectives
No full textКлизишта представљају један од најзначајнијих геохазарда у Србији, с великим утицајем на инфраструктуру и просторно планирање и урбанизацију. Рад даје преглед јавно доступних катастара клизишта у Србији, уз анализу њихове структуре, доступности и нивоа детаљности података. Посебна пажња усмерена је на институционални и законски оквир, улогу Геолошког завода Србије и значај јавне доступности просторних података у управљању ризиком од геолошких хазарда. Истиче се потреба за стандардизацијом, бољом интеграцијом и успостављањем јединствене националне инфраструктуре катастара клизишта као предуслова за ефикасније планирање, превенцију и заштиту простора.Landslides are among the most significant geohazards in Serbia, with substantial impacts on infrastructure, spatial planning, and urbanization. This paper provides an overview of publicly available landslide cadasters in Serbia, analyzing their structure, accessibility, and level of data detail. Special attention is given to the institutional and legal framework, the role of the Geological Survey of Serbia, and the importance of public accessibility of spatial data in managing geological hazard risks. The paper highlights the need for standardization, better integration, and the establishment of a unified national infrastructure for landslide inventories as a prerequisite for more efficient spatial planning, prevention, and protection
Assimilation method for hydrology models: FEWS Kolubara case study
No full textThe role of the flood early warning system is to provide information on forecasted water levels along river reaches obtained using mathematical models. Accordingly, it is necessary to ensure adequate initial conditions of mathematical models for the forecast period. Initial conditions are provided through the assimilation process, where corrections to input data, states, or model parameters are made based on the difference between observed and modeled values in the pre-forecast period. This paper presents the initial testing results of the proposed assimilation method for a hydrological-hydraulic model within the Kolubara Flood Early Warning System, based on solving an optimization problem using a genetic algorithm
Effect of boundary conditions on residual stress in cold metal transfer-based wire arc additively manufactured steel components
No full textThis research focusses on wire arc additive manufacturing (WAAM) of carbon steel components made of 3Dprint AM35 (grade S355) by cold metal transfer-based welding process. A finite element (FE) model is developed to simulate the deposition process, and the numerical results are rigorously validated against experimental measurements, demonstrating that the temperature, deformation, and stress fields developing during the additive process can be reproduced accurately. The sensitivity of the FE model to ambient temperature, element activation strategies, alignment errors of thermocouples and strain gauges, and the use of a sequentially coupled approach is analysed. The effect of boundary conditions on the longitudinal and transverse residual stress patterns is studied, revealing that they are highly sensitive to the bolt pretension forces and substrate joining methods. However, they redistribute in a similar manner after the removal of the substrate. Guidance is provided to monitor the residual stress distribution in the fabricated component
A novel semi-numerical infiltration model combining conceptual and physically based approaches
No full textHydrological models use methods of varying complexity to compute vertical infiltration described by Richards equation, which lacks an analytical solution, and is often solved using time-consuming, iterative numerical models. For continuous hydrological simulations these models are often replaced by simpler, yet less accurate models for greater computational efficiency. Seeking a compromise between accuracy and efficiency, a new semi-numerical infiltration model, combining conceptual and physically based approaches is developed and presented in this paper. The model assumes dividing the computational domain into computational cells that retain a differential form of the mass balance equation. After linearizing the input and output flux in each cell, an analytical solution of the mass balance equation is obtained. The solution is similar to a “linear reservoir” function, and it is valid only for a discrete time interval. By combining such solutions for each computational cell, a tridiagonal system of linear equations is obtained and solved directly without iterations. This non-iterative approach to solving Richards equation is reminiscent of the Ross model, with a key difference in the “linear reservoir” exponential term, contributing to the accuracy and stability of the presented semi-numerical model. Comparison between this model and the Ross model on four numerical examples shows that, except in strictly unsaturated conditions when the soil is exposed to low-intensity precipitation, the semi-numerical model achieves more stable results with considerably smaller number of computational steps and reduced mass balance errors. This indicates a clear potential for effective application of the proposed approach in distributed hydrological models