The objective of this paper is to represent an alternative approach to conventional numerical methods for solving heat transfer and charring behavior of timber when exposed to fire. The model consists of differential equations for heat transfer with the corresponding boundary conditions. The char formation in the wood beam as a function of its temperature is also taken into account by the model. Picard’s or Newton’s methods are used for solving the second order non-linear partial differential equations. In recent years, the RBF methods have emerged as novel computing method in scientific computing community. Traditionally, the most popular methods have been the finite element methods (FEM), the finite difference methods (FDM), and boundary element method (BEM). The results are tested on the one dimensional case in standard fire conditions, for which the comparison is made with the results of one-dimensional charring rate models for wood. The same model is used to analyze a two-dimensional behavior of timber beam exposed to fire from three sides.
COBISS.SI-ID: 5477217
A new method is presented for the self-noise estimation of a seismometer using a single, side-by-side, reference instrument and taking into consideration the misalignment in the orientation of both seismometers. The self-noise of seismometers is extracted directly from the measurements without using any information relating to the transfer functions. This procedure can be applied if the self-noise of the reference seismometer is well known and defined, or if the self-noise of the reference seismometer is sufficiently below the self-noise of the tested instrument and can be neglected. The latter case applies to this study. An algorithm is also developed where we apply self-noise data in order to determine the orientation misalignment between two seismometers, which is then resolved in three-dimensional space. This new method provides an estimate of the self-noise and can also be used to extract some parameters of the installed seismic system in comparison with the reference seismic system, such as generator constants and seismometer orientation or to eliminate unwanted noise sources, which have their origin in the seismic station’s design. The new technique was applied to the CMG-3ESPC and CMG-40T seismometers, where an STS-2 instrument served as the reference seismometer.
COBISS.SI-ID: 1165663
This paper describes the implementation of process-based models reflecting relative groundwater nitrate vulnerability of the shallow alluvial Lower Savinja Valley (LSV) aquifer in Slovenia. A spatially explicit identification of the potentially vulnerable priority areas within groundwater bodies at risk from a chemical point of view is being required for cost-effective measures and monitoring planning. The shallow LSV unconfined aquifer system consists of high-permeable Holocene and middle- to low-permeable Pleistocene gravel and sand, with a maximum thickness of about 30 m, mainly covered by shallow eutric fluvisoils or variously deep eutric cambisoil. The hydrogeological parameters, e.g. the depth to the groundwater, hydrological role of the topographic slope, etc. usually used in different point count schemes are, in the case of the lowland aquifer and shallow groundwater, spatially very uniform with low variability. Furthermore, the parametric point count methods are generally not able to illustrate and analyze important physical processes, and validation of the results is difficult and expensive. Instead of a parametric point count scheme, we experimentally used the Arc-WofE extension for weights-of-evidence (WofE) modelling. All measurement locations with a concentration higher than the value of 20 mg NO3 − per litre of groundwater have been considered as training points (173), and the three process-based models generalized output layers of groundwater recharge (GROWA), nitrate leached from the soil profile (SWAT) and groundwater flow velocity (FEFLOW), served as evidential themes. The technique is based on the Bayesian idea of phenomena occurrences probability before (prior probability) and after consideration of any evidential themes (posterior probability), which were measured by positive and negative weights as an indication of the association between a phenomena and a prediction pattern. The response theme values describe the relative probability that a 100 × 100 m spatial unit will have a groundwater nitrate concentration higher than the training points’ limit values with regard to prior probability value. The lowest probability of groundwater nitrate occurrence is in the parts of the LSV aquifer, which are known as anoxic condition areas with very likely denitrification processes. The cross-validation of the dissolved oxygen and dissolved nitrate response theme confirmed the accuracy of the groundwater nitrate prediction. The WofE model results very clearly indicate regional groundwater nitrate distribution and enable spatial prediction of the probability for increased groundwater nitrate concentration in order to plan the groundwater nitrate reduction measures and optimize the programme for monitoring the effects of these measures.
COBISS.SI-ID: 1091679