Wyniki wyszukiwania - BazTech

1

Reliability analysis of multi-site damage with failure dependency of the turbine based on flow-thermal-solid coupling analysis and the Monte Carlo validated simulations

Qian Wenxue, Zeng Xianhai, Huang Shuanghui, Yin Xiaowei

Eksploatacja i Niezawodność

|

2023

|

Vol. 25, no. 3

art. no. 168771

EN

The harsh environmental loads may lead to strength failure in the turbine in an aero-engine. To accurately assess the strength reliability of the turbine under multiple loads, the stress distributions of 41 danger sites of a turbine under thermal, centrifugal, and pneumatic loads were determined by the flow-thermal-solid coupling analysis using ANSYS. Second, based on the flow-thermal-solid coupling analysis and response surface method, the probabilistic analysis model of stress at the danger site was established. And the probabilistic distribution of stress was determined by sampling and hypothesis testing. Finally, the reliability model of the turbine with multi-site damage and failure dependency was established, by which a reliability of 0.99802 was calculated. And the actual reliability of the turbine was 0.99626 determined by the Monte Carlo simulations, which verified the model in precision. The results indicated that the reliability model has a high efficiency and higher precision than the traditional reliability model with failure independence.

2

Modeling vessel passage speed by using passage-time in restricted areas

Kasyk L., Kijewska M.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

|

2018

|

nr 54 (126)

63--69

EN

Vessel passage speed is one of the parameters describing the vessel traffic stream on a selected waterway. Knowing the probability distribution of vessel passage speeds is essential for modeling vessel traffic streams on a waterway. This article undertakes probabilistic modeling for vessel speeds in restricted areas, where the distribution of the vessel passage time of the waterway section is known. The probabilistic procedure of the inverse random variable is used. Four different cases are considered. First, the probabilistic distribution of the vessel passage speed is given, where the vessel passage time is described by the normal distribution in certain restricted areas. The next three cases present the probabilistic distribution of vessel passage speeds on the Szczecin–Świnoujście fairway, where the vessel passage time is described by the extreme value distribution, the Frèchet distribution and the Weibull distribution.

3

A simple tool for evaluating the risks related to hazardous interactions between the processes realized in the Baltic Sea Region port areas

Malinowski J.

Journal of Polish Safety and Reliability Association

|

2018

|

Vol. 9, No. 3

39--46

EN

This paper is a continuation of [1] which presents a probabilistic model of hazard-related interactions between different operations carried out in a (generic) Baltic Sea Region port area. Each such operation, considering its hazardous aspect, is defined as a series of undesired events (emergencies and/or accidents) occurring at random instants, i.e. as a random process. An event can be primary (occurring by itself) or secondary (caused by another event in the same or another process). The processes interact in the sense that a primary event in one process can cause a cascade of events spanning multiple processes. In [1] the formulas were derived for the cause-effect probabilities expressing the impact of a single event on the occurrence of the ensuing events in the triggered cascade. Also, the formulas for risks of undesired events, using these probabilities, were obtained. As these formulas are complicated and difficult to implement numerically, the need arose to develop a simple tool for computing the considered risks. Such a tool, in the form of an easy-toimplement algorithm, along with an illustrative example is presented in the current work.

4

Modeling hazard-related interactions between the processes realized in and around the Baltic Sea Region ports

Malinowski J.

Journal of Polish Safety and Reliability Association

|

2017

|

Vol. 8, No. 1

87--96

EN

This paper presents a probabilistic model of hazard-related interdependence between the operations carried out in the ports of the Baltic Sea region and in their neighborhoods. Each single operation, considered w.r.t. its hazardous aspect, will be defined as a point process consisting of undesired events (emergencies and/or accidents). Thus, the interdependence between these processes can be regarded as interaction between such events. The developed model will specify the impact of hazard related events occurring within one process on the risk of occurrence of such events in the other processes. This model will be a basis for the analysis of inter-process dependencies, including the feedback and cascading effects, as implied by the cause-effect relationships between the events occurring in different processes. Furthermore, it is envisaged to be used for assessing the potential effects of accidents or catastrophic events, and for developing the appropriate prevention measures. The procedures derived from the model will be applied to analyzing the mutual impacts between the processes realized in the oil and container terminals, forecasting negative effects of these impacts along with assessing their costs, and planning preventive actions aimed at avoiding such effects.

5

Reconstruction of high-dimensional data using the method of probabilistic features combination

Jakóbczak D. J.

Zeszyty Naukowe Wydziału Elektroniki i Informatyki Politechniki Koszalińskiej

|

2016

|

Nr 9

37--50

EN

Proposed method, called Probabilistic Features Combination (PFC), is the method of multi-dimensional data modeling, extrapolation and interpolation using the set of high-dimensional feature vectors. This method is a hybridization of numerical methods and probabilistic methods. Identification of faces or fingerprints need modeling and each model of the pattern is built by a choice of multi-dimensional probability distribution function and feature combination. PFC modeling via nodes combination and parameter γ as N-dimensional probability distribution function enables data parameterization and interpolation for feature vectors. Multidimensional data is modeled and interpolated via nodes combination and different functions as probability distribution functions for each feature treated as random variable: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function.

PL

Autorska metoda Probabilistycznej Kombinacji Cech - Probabilistic Features Combination (PFC) jest wykorzystywana do interpolacji i modelowania wielowymiarowych danych. Węzły traktowane są jako punkty charakterystyczne N-wymiarowej informacji, która ma być odtwarzana (np. obraz). Wielowymiarowe dane są interpolowane lub rekonstruowane z wykorzystaniem funkcji rozkładu prawdopodobieństwa: potęgowych, wielomianowych, wykładniczych, logarytmicznych, trygonometrycznych, cyklometrycznych.

6

Probabilistic model for flexural strength of dental composites used in modeling reliability of the “tooth-dental composite” system

Bartnik G., Pieniak D., Niewczas A. M., Marciniak A.

Eksploatacja i Niezawodność

|

2016

|

Vol. 18, no. 1

136--141

EN

In the article the application of Bayesian probabilistic modeling was presented as a way to standardize analytics of measurement results, which completes the operational and procedural standardization of determining the strength of dental composites. The traditional way of conducting studies of strength performed as services and calculations, and which do not refer to previous studies, was changed into an adaptation process of knowledge accumulation in a form of an increasing precise models. Probabilistic flexural strength models were used to create a reliability ranking of studied dental composites. Conceptualization of reliability of a biotechnological system, such as a “tooth-dental composite” required the expansion of the notion of“failure” with random events involving the occurrence of compatibility failure.

PL

W pracy przedstawiono zastosowanie bayesowskiego modelowania probabilistycznego jako sposobu standaryzacji opracowania wyników pomiarów, uzupełniającego standaryzację operatorowo – proceduralną wyznaczania wytrzymałości kompozytów stomatologicznych. Tradycyjny sposób prowadzenia badań wytrzymałościowych, wykonywanych usługowo i obliczeniowo nienawiązujących do badań poprzednich, zmieniono w adaptacyjny proces kumulacji wiedzy w postaci coraz dokładniejszych modeli. Probabilistyczne modele wytrzymałości na zginanie wykorzystano do utworzenia rankingu niezawodnościowego badanych kompozytów stomatologicznych. Konceptualizacja niezawodności układów biotechnologicznych takich jak „ząb – wypełnienie stomatologiczne” wymagała rozszerzenia zakresu pojęcia uszkodzenie o losowe zdarzenia polegające na zaistnieniu niezgodności pomiędzy komponentami układu biotechnologicznego (compability failure).

7

Data Forecasting and Extrapolation via Probability Distribution and Nodes Combination

Jakóbczak D. J.

Zeszyty Naukowe Wydziału Elektroniki i Informatyki Politechniki Koszalińskiej

|

2015

|

Nr 8

25--37

EN

Proposed method, called Probabilistic Nodes Combination (PNC), is the method of 2D data interpolation and extrapolation. Nodes are treated as characteristic points of information retrieval and data forecasting. PNC modeling via nodes combination and parameter γ as probability distribution function enables 2D point extrapolation and interpolation. Two-dimensional information is modeled via nodes combination and some functions as continuous probability distribution functions: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot or power function. Extrapolated values are used as the support in data forecasting.

PL

Autorska metoda Probabilistycznej Kombinacji Węzłów- Probabilistic Nodes Combination (PNC) jest wykorzystywana do interpolacji i ekstrapolacji dwuwymiarowych danych. Węzły traktowane są jako punkty charakterystyczne informacji, która ma być odtwarzana lub przewidywana. Dwuwymiarowe dane są interpolowane lub ekstrapolowane z wykorzystaniem różnych funkcji rozkładu prawdopodobieństwa: potęgowych, wielomianowych, wykładniczych, logarytmicznych, trygonometrycznych, cyklometrycznych. W pracy pokazano propozycję metody ekstrapolowania danych jako pomoc w przewidywaniu trendu dla nieznanych wartości.

8

On a risk perspective for maritime domain

Montewka J., Goerlandt F., Kujala P.

Journal of Polish Safety and Reliability Association

|

2013

|

Vol. 4, No. 1

101--108

EN

In the maritime domain, the risk is evaluated within the framework of Formal Safety Assessment (FSA), introduced by International Maritime Organization in 2002. Although the FSA has become internationally recognized and recommended method, the definition, which is adopted there, to describe the risk, seems to be too narrow to reflect properly the actual content of the FSA. Therefore this article discusses methodological requirements for the risk perspective, which is appropriate for risk management in the maritime domain with the special attention to maritime transportation systems (MTS). This perspective considers risk as a set encompassing the following: the set of plausible scenarios leading to an accident, the likelihoods of the unwanted events within the scenarios and the consequences of the events. These elements are conditional upon the available knowledge about the analyzed system, and understanding of the system behaviour, therefore these two are inherent parts of risk analysis, and need to be included in the risk description.