Stochastic Time-Dependent Deterioration Models for Estimating Residual Service Life of Offshore Jacket-Type Platforms

2021 ◽  
Author(s):  
Ishwarya Srikanth ◽  
M. Arockiasamy
Keyword(s):  
Markov Chain ◽  
Service Life ◽  
Transition Probability ◽  
Steel Corrosion ◽  
Transition Probability Matrix ◽  
Time Dependent ◽  
Residual Service Life ◽  
Jacket Platform ◽  
Offshore Jacket Platform ◽  
Residual Service

Abstract This paper presents deterioration models for maintenance planning of offshore jacket platform based on two methods: i) stochastic Markov-chain based model and ii) stochastic-mechanistic deterioration models based on steel corrosion rates. Markov-chain models require the estimation of transition probability matrix (TPM), which is typically derived from the inspection data. The global structural health condition of the jacket is computed based on the condition of individual elements and their criticality in terms of failure consequence. The criticality factors are established based on nonlinear static redundancy analyses. This method can model deterioration when routine inspection records of jacket members are available. When there is scarcity of inspection records, stochastic-mechanistic deterioration modeling approach can be used. Monte-Carlo simulations with established corrosion wastage models are utilized to estimate the time-dependent deterioration of jacket legs, horizontal and diagonal bracings in splash and immersion zones. This method is proposed when there is scarcity of inspection records. The deterioration models are further utilized to predict the timing for Maintenance, Repair and Rehabilitation (MRR) actions, and estimate the residual service life of the jacket platform. This study demonstrates the application of the proposed deterioration modeling approaches with a case study of a typical 4-legged offshore jacket platform.

Finite dams with inputs forming a Markov chain

1970 ◽  
Vol 7 (02) ◽  
pp. 291-303 ◽  
Author(s):  
M.S. Ali Khan
Keyword(s):  
Markov Chain ◽  
Probability Distribution ◽  
Generating Functions ◽  
State Transition ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Time Dependent ◽  
Probability Generating Functions ◽  
State Transition Probability ◽  
Finite Dam

This paper considers a finite dam fed by inputs forming a Markov chain. Relations for the probability of first emptiness before overflow and with overflow are obtained and their probability generating functions are derived; expressions are obtained in the case of a three state transition probability matrix. An equation for the probability that the dam ever dries up before overflow is derived and it is shown that the ratio of these probabilities is independent of the size of the dam. A time dependent formula for the probability distribution of the dam content is also obtained.

Finite dams with inputs forming a Markov chain

1970 ◽  
Vol 7 (2) ◽  
pp. 291-303 ◽  
Author(s):  
M.S. Ali Khan
Keyword(s):  
Markov Chain ◽  
Probability Distribution ◽  
Generating Functions ◽  
State Transition ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Time Dependent ◽  
Probability Generating Functions ◽  
State Transition Probability ◽  
Finite Dam

This paper considers a finite dam fed by inputs forming a Markov chain. Relations for the probability of first emptiness before overflow and with overflow are obtained and their probability generating functions are derived; expressions are obtained in the case of a three state transition probability matrix. An equation for the probability that the dam ever dries up before overflow is derived and it is shown that the ratio of these probabilities is independent of the size of the dam. A time dependent formula for the probability distribution of the dam content is also obtained.

Time-dependent seismic demand and fragility of deteriorating bridges for their residual service life

2015 ◽  
Vol 13 (8) ◽  
pp. 2389-2409 ◽  
Author(s):  
Anxin Guo ◽  
Wei Yuan ◽  
Chengming Lan ◽  
Xinchun Guan ◽  
Hui Li
Keyword(s):  
Service Life ◽  
Time Dependent ◽  
Seismic Demand ◽  
Residual Service Life ◽  
Residual Service

Functional and operational risk as a criterion for assessing the durability of an autonomous energy system

2019 ◽  
Vol 12 (1) ◽  
pp. 56-62 ◽  
Author(s):  
A. O. Nedosekin ◽  
A. V. Smirnov ◽  
D. P. Makarenko ◽  
Z. I. Abdoulaeva
Keyword(s):  
Service Life ◽  
Structural Reliability ◽  
Residual Life ◽  
Fuzzy Random Variable ◽  
Operational Risk ◽  
Energy System ◽  
Technical System ◽  
Residual Service Life ◽  
Technological Parameters ◽  
Residual Service

The article presents new models and methods for estimating the residual service life of an autonomous energy system, using the functional operational risk criterion (FOR). The purpose of the article is to demonstrate a new method of durability evaluation using the fuzzy logic and soft computing framework. Durability in the article is understood as a complex property directly adjacent to the complex property of system resilience, as understood in the Western practice of assessing and ensuring the reliability of technical systems. Due to the lack of reliable homogeneous statistics on system equipment failures and recoveries, triangular fuzzy estimates of failure and recovery intensities are used as fuzzy functions of time based on incomplete data and expert estimates. The FOR in the model is the possibility for the system availability ratio to be below the standard level. An example of the evaluation of the FOR and the residual service life of a redundant cold supply system of a special facility is considered. The transition from the paradigm of structural reliability to the paradigm of functional reliability based on the continuous degradation of the technological parameters of an autonomous energy system is considered. In this case, the FOR can no longer be evaluated by the criterion of a sudden failure, nor is it possible to build a Markov’s chain on discrete states of the technical system. Assuming this, it is appropriate to predict the defi ning functional parameters of a technical system as fuzzy functions of a general form and to estimate the residual service life of the technical system as a fuzzy random variable. Then the FOR is estimated as the possibility for the residual life of the technical system to be below its warranty period, as determined by the supplier of the equipment.

Expected residual service life of reinforced concrete structures from current strength considerations

2019 ◽  
Vol 22 (7) ◽  
pp. 1631-1643
Author(s):  
Sushil Kumar Dhawan ◽  
Abhinav Bindal ◽  
Suresh Bhalla ◽  
Bishwajit Bhattacharjee
Keyword(s):  
Reinforced Concrete ◽  
Service Life ◽  
Residual Life ◽  
Concrete Structures ◽  
Present Condition ◽  
Material Strength ◽  
Reinforced Concrete Structures ◽  
Residual Service Life ◽  
Remaining Service Life ◽  
Residual Service

Concrete is primarily used in the form of reinforced concrete for construction of buildings, bridges and other important structures. Due to normal usage and environmental effects, the structure would gradually deteriorate. The actual residual life needs to be worked at a given time vis-à-vis the design life of the structure, commensurate with the fulfilment of essential requirements of structural integrity and safety and from strength as well as serviceability considerations. Requirements for residual life assessment would depend upon the current parameters, such as the residual cross-sectional area of concrete as well as steel, Young’s modulus of elasticity and the in situ material strength of the constituent materials, namely, concrete and steel. This article aims to develop a rigorous methodology for expected remaining service life of a reinforced concrete structure from wind/seismic considerations, based on the present condition of the structure encompassing the residual material strength and the residual reinforcement/sectional areas. The methodology development section is followed by an illustrative example and a parametric study involving a 10-storeyed reinforced concrete building frame under wind and earthquake loads. Influences of various parameters such as concrete strength and residual rebar area on the expected remaining service life are studied in detail. The proposed methodology provides a simple but rational estimation of the residual service life for reinforced concrete structures.

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