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Povzetek: 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.
Ključne besede: thermal conductivity, non-cohesive sediment, cohesive sediment, estimation model
Objavljeno v DiRROS: 25.08.2022; Ogledov: 550; Prenosov: 245
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Povzetek: Waste management in Europe has improved in recent years, reducing the amount of waste disposed at landfills. However, there are still many landfills in the countries. It is well known that landfills that do not have measures in place to control leachate entering groundwater can contaminate groundwater long after the landfill is closed. Collecting monitoring results from all landfills allows permitting and management agencies to improve action plans. This relies on a synoptic risk assessment that allows prioritization and milestones to be set for required actions. The developed method of synoptic risk assessment is based on a conceptual model of the landfill and the results of chemical groundwater monitoring tested at 69 landfills in Slovenia. The study confirms that most landfills have a direct or indirect impact on groundwater quality. All landfills were classified into three priority classes on the basis of the synoptic risk assessment. The results show that a total of 24 landfills have a clearly pronounced impact on groundwater. A total of 31 landfills have a less pronounced impact due to the favorable natural attenuation capacity of the soil or the technically appropriate design of the landfill itself. A total of 14 landfills have a less pronounced or negligible impact on groundwater.
Ključne besede: conceptual model, synoptic risk assessment, landfill, groundwater, chemical analysis
Objavljeno v DiRROS: 19.07.2022; Ogledov: 552; Prenosov: 291
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Ključne besede: electrical discharge machining, mathematical model, numerical simulation, response-surface methodology, white layer
Objavljeno v DiRROS: 22.06.2022; Ogledov: 619; Prenosov: 138
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Povzetek: Tree heights are one of the most important aspects of forest mensuration, but data are often unavailable due to costly and time-consuming field measurements. Therefore, various types of models have been developed for the imputation of tree heights for unmeasured trees, with mixed-effects models being one of the most commonly applied approaches. The disadvantage here is the need of sufficient sample size per tree species for each plot, which is often not met, especially in mixed forests. To avoid this limitation, we used principal component analysis (PCA) for the grouping of similar plots based on the most relevant site descriptors. Next, we compared mixed-effects models with height-diameter models based on artificial neural networks (ANN). In terms of root mean square error (RMSE), mixed-effects models provided the most accurate tree height predictions at the plot level, especially for tree species with a smaller number of tree height measurements. When plots were grouped using the PCA and the number of observations per category increased, ANN predictions improved and became more accurate than those provided by mixed-effects models. The performance of ANN also increased when the competition index was included as an additional explanatory variable. Our results show that in the pursuit of the most accurate modelling approach for tree height predictions, ANN should be seriously considered, especially when the number of tree measurements and their distribution is sufficient.
Ključne besede: height-diameter models, national forest inventory, permanent sample plot, mixed forests, model comparison, principal component analysis
Objavljeno v DiRROS: 08.06.2022; Ogledov: 510; Prenosov: 217
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Ključne besede: gozdovi, varstvo gozdov, navadna smreka, Picea abies, sanitarni posek, napoved, prognoza, ogroženost, model, smrekovi podlubniki, Ips typographus, Pityogenes chalcographus
Objavljeno v DiRROS: 13.04.2022; Ogledov: 543; Prenosov: 356
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