Tikimybinis ekstremalių temperatūrų dinamikos vertinimas

In order to estimate likelihood of the annual minimum and maximum Lithuanian air temperatures (based on 1961–2014 data) the probabilistic assessment using the extreme value distributions was performed, in particular, for each sample the best extreme value distribution was identified. In addition, to the previously mentioned study of dry bulb temperature extremes, wet bulb temperature extremes study, which enables to determine the relative humidity, was also carried out. Usingthe selected Gumbel distribution, the local temperature data analysis in eastern Lithuania, i.e. in Dūkštas, region was conducted. Then temperature variation analysis using the moving average method was carried out and the extremes changes in view of the uncertain data were investigated.Siekiant atlikti Lietuvos oro metinių minimalių ir maksimalių temperatūrų (1961–2014 m.) tikimybinį vertinimą, taikant ekstremalių reikšmių skirstinius, visų pirma, kiekvienai ekstremumų imčiai buvo išrinktas jai tinkamiausias ekstremalių reikšmių skirstinys. Be minėto vertinimo ir sausojo termometro temperatūrų ekstremumų tyrimo, buvo atliktas ir drėgnojo termometro temperatūrų įvertinimas, įgalinantis nustatyti santykinį oro drėgnumą. Be to, taikant atrinktą Gumbelio skirstinį, buvo atlikta lokalių temperatūrų tikimybinė analizė duomenims rytinėje Lietuvos dalyje, tai yra Dūkšto regione. Pabaigoje buvo atlikta temperatūrų kitimo analizė naudojant slenkančių vidurkio metodą bei tyrinėta ekstremumų vertinimo kaita atsižvelgiant į duomenų neapibrėžtumą

Stimuliuojama dinamika ir jos modeliavimas

There is not abstract.Darbe nagrinėjami tikimybinės dinamikos bei dinaminio patikimumo veiksniai susieti su stimuliuojamos dinamikos apibrėžimu ir agregatinio modeliavimo metodo taikymu, analitinis ir imitacinis hibridinių sistemų formalizavimo ir modeliavimo būdai bei dinaminių sistemų modeliavimas atsižvelgiant į atsitiktines laiko trukmes tarp stimulų atsiradimo ir dinamikos kitimo.  Pateikta nauja metodika, skirta tolydžių procesų ir nuo jų priklausančių  įvykių sąveikos modeliavimui

Probabilistic Dynamics for Integrated Analysis of Accident Sequences considering Uncertain Events

The analytical/deterministic modelling and simulation/probabilistic methods are used separately as a rule in order to analyse the physical processes and random or uncertain events. However, in the currently used probabilistic safety assessment this is an issue. The lack of treatment of dynamic interactions between the physical processes on one hand and random events on the other hand causes the limited assessment. In general, there are a lot of mathematical modelling theories, which can be used separately or integrated in order to extend possibilities of modelling and analysis. The Theory of Probabilistic Dynamics (TPD) and its augmented version based on the concept of stimulus and delay are introduced for the dynamic reliability modelling and the simulation of accidents in hybrid (continuous-discrete) systems considering uncertain events. An approach of non-Markovian simulation and uncertainty analysis is discussed in order to adapt the Stimulus-Driven TPD for practical applications. The developed approach and related methods are used as a basis for a test case simulation in view of various methods applications for severe accident scenario simulation and uncertainty analysis. For this and for wider analysis of accident sequences the initial test case specification is then extended and discussed. Finally, it is concluded that enhancing the modelling of stimulated dynamics with uncertainty and sensitivity analysis allows the detailed simulation of complex system characteristics and representation of their uncertainty. The developed approach of accident modelling and analysis can be efficiently used to estimate the reliability of hybrid systems and at the same time to analyze and possibly decrease the uncertainty of this estimate

Stochastic Simulation of Flow Rate and Power Consumption Considering the Uncertainty of Pipeline Cracking Rate and Time-Dependent Topology of a Natural Gas Transmission Network

Various gas pipeline networks used for the transit of energy sources are some of the most important infrastructures. However, carrying gas from one point to another is not the only concern when planning the construction of a new network or expanding an already existing one. The reliability and environmental impact of the system are crucial when evaluating the network and risks posed by potential gas leaks, fires, explosions, etc. Even though everyone admits that reliability is a key aspect of any system, its constraints will still be most likely neglected in the assessment of the pipeline project. How much energy is wasted by pushing an additional amount of gas through the pipeline network, which will eventually gush out of the pipeline because of one crack or another? Moreover, if this additional power or fuel consumption and related environmental impact are significant, how could it be reduced? In this paper, an approach is introduced for the simulation and quantification of how much more power would be required if the pipelines are regarded as unreliable (i.e., by leaking, rupturing, or even exploding). By employing stochastic simulations and time-dependent topology (topology determined by the value of a variable representing time) of the pipeline network as a case study for the selected representative gas transmission network, the amount of additional power consumption in gas compressor stations due to uncertain cracking and the leaking rate was evaluated. Although the analysis of power consumption was performed for a hypothetical network, the estimates of the cracking rates, detection effectiveness, and leaking rates used were as close to the real cases as possible