41. Experimental carbonation study for a durability assessment of novel cementitious materialsLucija Hanžič, Sebastijan Robič, Alisa Machner, Marie Helene Bjørndal, Klaartje De Weerdt, Yushan Gu, Benoit Bary, Rosa Maria Lample Carreras, Aljoša Šajna, 2021, original scientific article Abstract: Durability predictions of concrete structures are derived from experience-based require- ments and descriptive exposure classes. To support durability predictions, a numerical model related to the carbonation resistance of concrete was developed. The model couples the rate of carbonation with the drying rate. This paper presents the accelerated carbonation and moisture transport exper- iments performed to calibrate and verify the numerical model. They were conducted on mortars with a water-cement ratio of either 0.6 or 0.5, incorporating either a novel cement CEM II/C (S-LL) (EnM group) or commercially available CEM II/A-S cement (RefM group). The carbonation rate was determined by visual assessment and thermogravimetric analysis (TGA). Moisture transport experi- ments, consisting of drying and resaturation, utilized the gravimetric method. Higher carbonation rates expressed in mm/day−0.5 were found in the EnM group than in the RefM group. However, the TGA showed that the initial portlandite (CH) content was lower in the EnM than in the RefM, which could explain the difference in carbonation rates. The resaturation experiments indicate an increase in the suction porosity in the carbonated specimens compared to the non-carbonated specimens. The study concludes that low clinker content causes lower resistance to carbonation, since less CH is available in the surface layers; thus, the carbonation front progresses more rapidly towards the core.
Keywords: mortar, absorption of water, carbonation, durability assessment, model verification
Published in DiRROS: 05.07.2023; Views: 483; Downloads: 276
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42. Causes and consequences of large-scale windthrow on the development of fir-beech forests in the Dinaric mountainsMatjaž Čater, Ajša Alagić, Mitja Ferlan, Jernej Jevšenak, Aleksander Marinšek, 2023, original scientific article Abstract: We investigated several aspects of windthrow that are relevant to our understanding and management of forest ecosystems. As an example, we used an extreme event in December 2017, when the strongest storm in recent history occurred in the Slovenian Dinaric High Karst. We examined influential factors such as soil properties, wind speed, precipitation and ecological consequences for the affected forests. Soil properties were measured around standing and fallen silver fir trees at all three research sites. Tree species composition in the regeneration was observed on plots with chemical and acoustic ungulate deterrents and on control plots without deterrents. Economic estimates of yield loss due to damage were calculated at the national level. A model of the potential threat from windthrow was also developed based on data collected from windthrow events and meteorological data over the past 20 years. Our results indicate that soil depth and mineral fraction depth were similar at sites with and without damaged trees and were not the determining factors for tree toppling. Plots with acoustic deterrents showed the most effective regeneration development, the least decline in silver fir and the greatest increase in noble hardwood seedlings, while plots with chemical deterrents showed the least browsing damage. The estimated economic loss of €16.1 million is 6.6% less than the harvest under normal conditions. The economic loss was relatively low due to the nature of the storm, with the predominant type of damage being uprooted trees with no damaged trunks. The windthrow hazard model revealed that a large number of consecutive events with strong winds in each section weakened the stand, which was subsequently knocked down during the next extreme wind and rainfall event.
Keywords: natural forest regeneration, windthrow, economic loss, browsing, ungulate deterrents, forest soil properties, potential threat model
Published in DiRROS: 27.06.2023; Views: 1494; Downloads: 719
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43. Organoidi glioblastoma razkrivajo odpornost na standardno terapijoBernarda Majc, Anamarija Habič, Marta Malavolta, Aleksander Sadikov, Andrej Porčnik, Jernej Mlakar, Tamara Lah Turnšek, Barbara Breznik, Metka Novak, 2023, published scientific conference contribution abstract Keywords: glioblastom, organoidi, standardna terapija, model ex vivo, biologija raka
Published in DiRROS: 16.06.2023; Views: 559; Downloads: 218
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44. Model updating concept using bridge Weigh-in-Motion dataDoron Hekič, Andrej Anžlin, Maja Kreslin, Aleš Žnidarič, Peter Češarek, 2023, original scientific article Abstract: Finite element (FE) model updating of bridges is based on the measured modal parameters and less frequently on the measured structural response under a known load. Until recently, the FE model updating did not consider strain measurements from sensors installed for weighing vehicles with bridge weigh-in-motion (B-WIM) systems. A 50-year-old multi-span concrete highway viaduct, renovated between 2017 and 2019, was equipped with continuous monitoring system with over 200 sensors, and a B-WIM system. In the most heavily instrumented span, the maximum measured longitudinal strains induced by the full-speed calibration vehicle passages were compared with the modelled strains. Based on the sensitivity study results, three variables that affected its overall stiffness were updated: Young’s modulus adjustment factor of all structural elements, and two anchorage reduction factors that considered the interaction between the superstructure and non-structural elements. The analysis confirmed the importance of the initial manual FE model updating to correctly reflect the non-structural elements during the automatic nonlinear optimisation. It also demonstrated a successful use of pseudo-static B-WIM loading data during the model updating process and the potential to extend the proposed approach to using random B-WIM-weighed vehicles for FE model updating and long-term monitoring of structural parameters and load-dependent phenomena.
Keywords: monitoring, bridge, viaduct, bridge weigh-in-motion (B-WIM), structural health monitoring (SHM), finite element (FE), calibration, model updating
Published in DiRROS: 29.05.2023; Views: 610; Downloads: 301
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45. Development of groundwater flow models for the integrated management of the alluvial aquifer systems of Dravsko polje and Ptujsko polje, SloveniaAda Vengust, Anja Koroša, Janko Urbanc, Nina Mali, 2023, original scientific article Abstract: With increasing exploitation of groundwater resources and implementation of various activities in their recharge areas, it is vital to conduct a comprehensive assessment of aquifers to ensure their conservation and sustainable management. In the present study, we used a comprehensive approach to conceptualise and identify the functioning of two connected aquifer systems in north-eastern Slovenia: the Quaternary porous aquifers Dravsko polje and Ptujsko polje. The study presents the conceptual models of both aquifers and their interconnectedness using separate mathematical-numerical models with the aim of ensuring an integrated management of these alluvial aquifer systems. It also highlights the importance of understanding connections between such systems for simulating groundwater flow and transport of different contaminants.
Keywords: hydrogeological model, Modflow model, aquifer geometry, aquifer recharge, modelling
Published in DiRROS: 27.03.2023; Views: 647; Downloads: 220
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46. Verjetnostna napoved sanitarnega poseka smreke zaradi podlubnikov v Sloveniji v 2023Nikica Ogris, Maarten De Groot, 2023, other scientific articles Keywords: gozdovi, varstvo gozdov, navadna smreka, Picea abies, sanitarni posek, napoved, prognoza, ogroženost, model, smrekovi podlubniki, Ips typographus, Pityogenes chalcographus
Published in DiRROS: 24.03.2023; Views: 638; Downloads: 287
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48. Preverjanje verjetnostne in količinske napovedi sanitarnega poseka smreke zaradi podlubnikov v Sloveniji v 2022Nikica Ogris, Maarten De Groot, 2022, other scientific articles Keywords: gozdovi, zdravje gozdov, sanitarni posek, napovedi, podlubniki, Slovenija, navadna smreka, Picea abies, ogroženost, model, validacija, zmogljivost, zanesljivost, točnost, natančnost, AUC, občutljivost, specifičnost
Published in DiRROS: 14.12.2022; Views: 639; Downloads: 364
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49. Evaluation of thermal conductivity estimation models with laboratory-measured thermal conductivities of sedimentsSimona Adrinek, Rao Martand Singh, Mitja Janža, Mateusz Żeruń, Grzegorz Ryżyński, 2022, original scientific article Abstract: Thermal conductivity is one of the key parameters for estimating low-temperature geothermal potential. In addition to field techniques, it can be determined based on physical parameters of the sediment measured in the laboratory. Following the methodology for cohesive and non-cohesive sample preparation, laboratory measurements were carried out on 30 samples of sediments. Density, porosity and water content of samples were measured and used in thermal conductivity estimation models (TCEM). The bulk thermal conductivity (λb) calculated with six TCEMs was compared with the measured λb to evaluate the predictive capacity of the analytical methods used. The results show that the empirical TCEMs are suitable to predict the λb of the analysed sediment types, with the standard deviation of the residuals (RMSE) ranging from 0.11 to 0.35 Wm−1 K−1. To improve the fit, this study provides a new modified parameterisation of two empirical TCEMs (Kersten and Côté&Konrad model) and, therefore, suggests the most suitable TCEMs for specific sample conditions. The RMSE ranges from 0.11 to 0.29 Wm−1 K−1. Mixing TCEM showed an RMSE of up to 2.00 Wm−1 K−1, meaning they are not suitable for predicting sediment λb. The study provides an insight into the analytical determination of thermal conductivity based on the physical properties of sediments. The results can help to estimate the low-temperature geothermal potential more quickly and easily and promote the sustainable use of this renewable energy source, which has applications in environmental and engineering science.
Keywords: thermal conductivity, non-cohesive sediment, cohesive sediment, estimation model
Published in DiRROS: 25.08.2022; Views: 771; Downloads: 350
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50. Modelling seasonal dynamics of secondary growth in RJernej Jevšenak, Jožica Gričar, Sergio Rossi, Peter Prislan, 2022, original scientific article Abstract: The monitoring of seasonal radial growth of woody plants addresses the ultimate question of when, how and why trees grow. Assessing the growth dynamics is important to quantify the effect of environmental drivers and understand how woody species will deal with the ongoing climatic changes. One of the crucial steps in the analyses of seasonal radial growth is to model the dynamics of xylem and phloem formation based on increment measurements on samples taken at relatively short intervals during the growing season. The most common approach is the use of the Gompertz equation, while other approaches, such as general additive models (GAMs) and generalised linear models (GLMs), have also been tested in recent years. For the first time, we explored artificial neural networks with Bayesian regularisation algorithm (BRNNs) and show that this method is easy to use, resistant to overfitting, tends to yield s-shaped curves and is therefore suitable for deriving temporal dynamics of secondary tree growth. We propose two data processing algorithms that allow more flexible fits. The main result of our work is the XPSgrowth() function implemented in the radial Tree Growth (rTG) R package, that can be used to evaluate and compare three modelling approaches: BRNN, GAM and the Gompertz function. The newly developed function, tested on intra-seasonal xylem and phloem formation data, has potential applications in many ecological and environmental disciplines where growth is expressed as a function of time. Different approaches were evaluated in terms of prediction error, while fitted curves were visually compared to derive their main characteristics. Our results suggest that there is no single best fitting method, therefore we recommend testing different fitting methods and selection of the optimal one.
Keywords: artificial neural networks, cambium, generalized additive model, Gompertz function, growing season, intra-annual time series
Published in DiRROS: 21.07.2022; Views: 668; Downloads: 426
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