Uradne nepremičninske evidence pa žal pogosto ne zagotavljajo celovitih informacij o stanju nepremičnin, ki so potrebne za sprejemanje odločitev pri njihovem upravljanju in rabi. Take organizacije ...pogosto nimajo dobrega pregleda nad celotnim fondom nepremičnin, s katerimi razpolagajo, predvsem pa manjkajo pomembni podatki o nepremičninah, ki so ključni za upravljanje z njimi. V Sloveniji se lastniki, ki imajo v lasti in/ali upravljanju več nepremičnin, spopadajo z velikimi izzivi že pri sami vzpostavitvi podatkovne zbirke in vzdrževanju temeljnih podatkov o pravnih in fizičnih lastnostih nepremičnin, saj ni mogoče enostavno prevzemati podatkov za množico nepremičnin iz uradnih nepremičninskih evidenc. Med večje lastnike oziroma upravljavce nepremičnin v Republiki Sloveniji štejemo tudi številne javne institucije, kot so ministrstva, ki se zaradi omejenega dostopa do informacij, ključnih za sprejemanje odločitev, prav tako spopadajo z velikimi izzivi pri upravljanju nepremičnin ter načrtovanju dejavnosti in investicij. Unified Modelling Language), ki med drugim določa standardne diagrame za predstavitev različnih vidikov informacijskega sistema. 2.3 Izzivi procesnega modeliranja Modeliranje postopkov, ki jih mora podpirati sodoben nepremičninski informacijski sistem in na temelju katerih se bo tak sistem posodabljal in uporabljal, mora temeljiti na protokolu za učinkovit popis uporabniške izkušnje in prednosti, ki jih takšen pristop prinaša. Dodaten razmislek zahteva podatkovna podlaga, vezana na različne podatkovne vire. 3 ZASNOVA NEPREMIČNINSKEGA INFORMACIJSKEGA SISTEMA IN PILOTNI PRIMER Pri zasnovi večnamenskega nepremičninskega informacijskega sistema s prostorsko podatkovno zbirko o nepremičninah v lasti Republike Slovenije in v upravljanju MP RS (NEPIS-MP) smo posebno pozornost namenili: (i) ustvarjanju podatkovne zbirke in opredelitvi njene strukture, (ii) vzdrževanju podatkovne zbirke, (iii) zagotavljanju integritete podatkov, (iv) izvajanju transakcij ter (v) zagotavljanju
In order to predict a product’s durability in the early phases of development it is necessary to know the stress–strain behaviour of the material, its resistance to fatigue and the loading states in ...the material. These parameters, however, tend to exhibit a considerable degree of uncertainty. Due to a lack of knowledge of the actual circumstances in which the product is used, during the early development phase, simulations based on statistical methods are used. The results of the experiments show that the cyclic stress–strain curves demonstrate not only a large amount of scatter, but also a dependence on the temperature, the size of the cross-section, the content of alloying elements, the loading rate, etc.
This article presents a method for modelling cyclic stress–strain curve scatter using a hybrid neural network for an arbitrary selection of the influencing factors. In an example of the measured data for a high pressure die-cast aluminium alloy it is clear that the suggested method is suitable for describing cyclic stress–strain curves. The main advantage of a hybrid neural network in comparison with a conventional method is the neural network’s ability to precisely describe the influence of various factors, and their combinations, based on the form and scatter of the cyclic stress–strain curve families. Defining the model parameters, i.e., training the neural network, is a procedure that does not require any additional user interventions; however, it enables us to gather knowledge that would otherwise require a lot of research. Thus, the trained neural network is a robust tool that can be used to predict cyclic stress–strain curves for random values of influencing factors. The capabilities of the presented method are only limited by the quantity of the measured data used for the neural-network training.
If structural reliability is estimated by following a strain-based approach, a material’s strength should be represented by the scatter of the ε–
N
(
E
–
N
) curves that link the strain amplitude ...with the corresponding statistical distribution of the number of cycles-to-failure. The basic shape of the ε–
N
curve is usually modelled by the Coffin–Manson relationship. If a loading mean level also needs to be considered, the original Coffin–Manson relationship is modified to account for the non-zero mean level of the loading, which can be achieved by using a Smith–Watson–Topper modification of the original Coffin–Manson relationship. In this paper, a methodology for estimating the dependence of the statistical distribution of the number of cycles-to-failure on the Smith–Watson–Topper modification is presented. The statistical distribution of the number of cycles-to-failure was modelled with a two-parametric Weibull probability density function. The core of the presented methodology is represented by a multilayer perceptron neural network combined with the Weibull probability density function using a size parameter that follows the Smith–Watson–Topper analytical model. The article presents the theoretical background of the methodology and its application in the case of experimental fatigue data. The results show that it is possible to model ε–
N
curves and their scatter for different influential parameters, such as the specimen’s diameter and the testing temperature.
ABSTRACT
Calculating the fatigue damage with a strain‐based approach requires an ɛ–N durability curve that links the strain amplitude to the corresponding number of cycles‐to‐failure. This ɛ–N curve ...is usually modelled by the Coffin–Manson relationship. If a loading mean‐level also needs to be considered, the original Coffin–Manson relationship is modified using a Smith–Watson–Topper parameter. In this article a methodology for modelling the dependence of the Smith–Watson–Topper parameter on the number of cycles‐to‐failure is presented. The core of the presented methodology represents a multilayer perceptron neural network combined with the Smith–Watson–Topper analytical model. The article presents the theoretical background of the methodology, which is applied for the case of the experimental fatigue data. The results show that it is possible to model ɛ–N curves for different influential parameters, such as the specimen's diameter and the testing temperature. The results further show that it is possible to predict ɛ–N curves even for those combinations of the influential parameters for which no experimental data about the material endurance is available. This fact makes the presented model very suitable for the application in an R&D process when a durability of a product should be estimated on the basis of a very limited set of experimental data about the material endurance characteristics.
Urban planning and real estate GIS applications include visualization and analysis of objects, especially buildings, geocoded in three dimensions. Data must be free of topologic errors. Municipal ...community of Ljubljana is building 3D city model for which topologic and geometric rules for data acquisition and logical consistency assurance were formed. Computer software for automatic topology and geometry checking in 3D was elaborated and tested. Visualization of 3D city model is presented in MS Internet Explorer.
All-atom classical force-field based molecular dynamics simulations have been employed to investigate the structure and dynamics of interfacial water in systems of pure water, 1 M LiOH and 1 M KOH ...aqueous solutions at an uncharged Pt(111) surface. Results indicate that the ordering of water molecules is affected as far as 9 from the Pt surface, corresponding to three layers of water molecules. Specific packing geometries of water in electrolyte solutions depend on the ionic radius, and both Li
+
and K
+
ions are found to adsorb directly onto the Pt surface. Significantly higher values of the water-dipole autocorrelation function in the adlayer are found for the system with Li
+
ions compared to the systems with K
+
ions or pure water. Also strongly reduced translational motion is observed in the case of Li
+
, both in-plane and perpendicular to the surface. This result suggests a strong stabilizing role of Li
+
ions on water molecules. Decreased mobility of the water adlayer makes it difficult for other compounds in the aqueous solution to access the Pt surface. This implies that the reason for the reduced catalytic activity of Pt(111) surface in the presence of LiOH is due to the freezing effect Li
+
ions have on water.
The effect of cations on the catalytic activity of Pt(111) might be established from their influence on adlayer water dynamics.
