The paper describes a Markov model of corrosion growth of pipe wall defects and its implementation for assessing the conditional probability of pipeline failure and optimizing pipeline repair and maintenance. This pure growth Markov model is of the continuous time, discrete states type. This model is used in conjunction with the geometrical limit state function (LSF) to assess the conditional probability of failure of pressurized pipelines when the main concern is loss of containment. It is shown how to build an empirical Markov model for the length, depth and width of defects, using field data gathered by In-line inspection (ILI) or direct assessment (DA) or by using a combination of a differential equation (DE) that describes defect parameter growth with the Monte Carlo simulation method. As a result of implementation of this approach the probability for the defect parameters being in a given state (analog of a histogram) and the transition intensities (from state to state) are easily derived for any given moment of time. This approach automatically gives an assessment of the probability of failure of a pipeline segment, as it is derived using the data from a specific pipeline length. This model also allows accounting for the pipeline failure pressure LSF. On the basis of this model an algorithm is constructed for optimizing the time of the next inspection/repair. This methodology is implemented to a specific operating pipeline which was several times inspected by a MFL inspection tool. The expected number and volume of repairs depend on the value of the ultimate permissible pipeline failure probability. Sensitivity of pipeline conditional failure rate and optimal repair time to actual growth rate is investigated. A brief description of the software that implements the described above technology is given.
Mulchers are very useful in creating and caring for the forest. A wide range of different types of mulchers can disorient potential buyers. This article was aimed at creating a classification of mulchers based on an assessment of the most important parameters: weight, required engine power and diameter of the cut wood. Six classes of machines were created, their boundaries were defined and mulchers were assigned to these classes. Class K1 (weight up to 1300 kg; capacity up to 75 kilowatts; diameter of the working body up to 22 centimeters) the most common – 88 units of mulchers. It is followed by class K2 (1800 kilograms; 100 kilowatts; 27 centimeters) – 61 pieces, class K4 (3200 kg; 175 kW; 41 centimeters) – 44 pieces, class K3 (2300 kg; 125 kilowatts; 31 centimeters) – 34 pcs., class K5 (4100 kg; 225 kW; 51 centimeters) – 18 pcs. and class K6 (without upper limit) – 9 pcs.
In the article the method of volumetric hydrophobization by insertion of modifying agents with hydrophobization effect directly in concrete mixture on the stage of mixing is considered and the degree of their influence on physics-mathematics properties of vibropressed products which made on technological line with optimal granulometry, water to cement proportion and parameters of forming is estimated, so that the geometrical dimensions of moulded products satisfy required sizes and limits, and appearance of front-face area satisfied A3 category. There was established the increase of operational characteristics of concrete walkway vibropressed slabs when in use of polyfunctional modifying agents with hydrophobization effect – Murasan BWA 17 and SikaPaver AE-2 in 0.5 % cement weight quantity, wherein there was found the increase of compressive strength of slabs on 23 %, frost resistance on 50 cycles and decrease of water absorption up to 45 % which allows increasing the longevity of small-pieces products. Insertion of volumetric modifier-hydrophobisator Akvasil, only with a mono-characteristic to decrease of water absorption, has negative role on strength characteristics of vibropressed products with decrease of concrete compressive strength by 12 %.
The paper describes a new practical method of updating the stochastic remnant life of pipelines with defects using ILI data. The paper describes a comprehensive algorithm for assessing pipeline remnant life taking into account the stochastic results of in-line inspection (ILI). It is assumed that the pipeline segment wall has a longitudinal external crack of semi-elliptical form and is described by the J-integral. The limit state function (LSF) is described as the difference of the critical and current value of the J-integral. The latter is calculated for the current time of pipe performance and is assumed known due to monitoring of the pumping equipment. The critical crack depth is defined using the notion of fracture toughness and the J-integral approach. The algorithm contains solutions of three sequentially interconnected problems. First, the deterministic problem of fatigue crack growth (FCG) is analyzed. Then the stochastic FCG is analyzed. The probability of failure assessment algorithm is designed on the basis of the authors’ version of the adaptive important sampling (AIS) procedure. The main steps of the AIS algorithm are described in detail. The samples are generated in such a way, that at all times a majority of samples belong to the fracture region. Finally, the results of the latest ILI are fused into the algorithm, providing best possible assessment of pipeline remnant life as a random variable. The remnant life update for pipeline segment with crack-like defects using ILI data takes into account three possible outcomes: defect not discovered: defect is discovered but not measured; defect is discovered and measured. This result permits solving most important problems of pipeline maintenance: prioritization of pipeline segments for repair/rehabilitation; optimization of the time between ILI; minimization of pipe operational risk. Two real cases are described of assessing the probability of fracture/leak of a pipeline section with an external crack at different periods of its performance. The described approach currently is being generalized for the case of multiple stress corrosion SC cracks.
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