Inverse Transient Analysis Research Articles

Transient Test-Based Techniques for Checking the Sealing of In-Line Shut-Off Valves and Capturing the Effect of Series Junctions—Field Tests in a Real Pipe System

In-line valves are devices typically used for isolation or flow regulation in pipe systems, playing a key role in the operational management of transmission mains (TM). However, there is no fast and expeditious procedure available for checking the efficacy of the sealing mechanism, and its ability to prevent leakage, unwanted flow or partial blockages, which is a crucial action for any maintenance operation. Due to the different values of the conveyed discharge, the diameter changes along the TM at a series junctions which therefore makes diameter changes a very common singularity. This paper has two aims. The first one is to evaluate the feasibility of Inverse Transient Analysis (ITA) for checking the sealing of in-line valves. In particular, the primary objective of the numerical model is to identify the distinctive features of the measured pressure signals that correspond to the status of an in-line valve, discerning whether it is fully sealed or partially closed. The second objective is to use Direct Analysis (DA) of the pressure signals to appropriately capture the transient response of the series junctions. To address these issues, safe transients have been generated in a real TM by means of a Portable Pressure Wave Maker (PPWM) device, refined at the Water Engineering Laboratory (WEL) of the University of Perugia, Italy. The results of the field tests and numerical model point out that the positive pressure wave reflected by the in-line valve is smaller than the one expected if it were perfectly sealed. Moreover, the transient response of the series junction has been properly captured by the DA of the pressure signal. Accordingly, the proposed procedures have been demonstrated to be suitable tools for the management of long transmission pipelines.

Inverse transient analysis based calibration of surrogate pipeline model for fault simulation of axial piston pumps

Axial piston pumps are the key component in power hydraulic systems. Flow and pressure ripple signals, which can reflect the flow dynamics of the axial piston pump, are important information sources for condition monitoring. Therefore, the characteristics of flow and pressure ripple signals should be investigated for further condition monitoring and fault analysis. However, measuring high-frequency flow ripple directly can be difficult, and the pressure ripple is not only affected by pump dynamics but also affected by the transient pressure wave propagation. However, in practical applications, the hydraulic pipeline system is complex due to the space constraint of the equipment, and the influence of the pipeline system cannot be ignored when modeling pressure ripple. This paper proposes a novel two-stage method for fault simulation of the pumps that considers the influence of the pipeline system on the pressure ripple. Firstly, the surrogate pipeline model with free parameters is calibrated using ITA to capture the characteristics of the complex practical pipeline system. Secondly, the calibrated model is applied to the fault simulation of axial piston pumps. A detailed 3D CFD model of the pump is built up, and the flow ripple at the pump outlet from the numerical model is used as an approximation of the real flow ripple of the pump, which serves as one of the boundary conditions of the surrogate pipeline model. After calibrating the model, the CFD model of the pump is used to simulate internal failures in the pump. Two failure cases are studied: a faulty slipper and a faulty cylinder. The simulated signal of the proposed model matches the experimental signal well under the healthy and faulty conditions, which confirms the effectiveness of the proposed method.

Optimization of a Pipelines Leak Detection Method Based on Inverse Transient Analysis Using a Genetic Algorithm

Optimization of a Pipelines Leak Detection Method Based on Inverse Transient Analysis Using a Genetic Algorithm

Illegal connection detection in a viscoelastic pipeline using inverse transient analysis in the time domain

Abstract Illegal connection (IC) in water supply systems and water network wastes water as well as energy and reduces water quality, which has negative technical and economic effects on water management. Transient-based defect detection is a powerful method applied in water pipelines. This paper investigates the efficiency of the transient-based inverse transient analysis (ITA) method in estimating the characteristics of ICs in the viscoelastic water supply system in the time domain. To better evaluate this method, an experimental transient model was developed using polyethylene pipelines (with a length of 158 meters and a nominal diameter of 2 inches). In the first step, the hydraulic transient solver was calibrated in the calibration approach of dynamic parameters of pressure wave speed and pipe wall viscoelasticity. Then, the sensitivity of the ITA method to the spatial step of the method of characteristics and signal sample size was assessed. Finally, the efficiency of the ITA method was evaluated for several experiments with different transient intensities and a noisy signal. The results indicated that the accuracy for locating the IC was higher than the accuracy for the IC's length.

Development of backward transient analysis in visco-elastic pressurized pipes

This paper aims to develop a backward analysis version of the inverse transient leak detection method for plastic pipes. To carry out the analysis, the structure of the Kelvin–Voigt model is modified to match the numerical structure of the backward model. Brunone unsteady friction is also discretized to make it correspond to the numerical structure. In order to investigate the performance of the improved backward transient model for pipes with visco-elastic properties, the results of this model are compared to the results of the inverse transient model applied to two cases of considering and neglecting the unsteady friction effects. The results show that in the case with a larger leak size, both models performed well. In the case with a smaller leak size, the advantage of eliminating uncertainties in the backward transient analysis (BTA) model led to the success of the model in two of three runs of leak detection; while the inverse transient analysis (ITA) in this case encountered a significant error. The unsteady friction has a negligible effect on the quality of the leak detection process in both cases. Due to the effects that the use of laboratory data with known and simple structure can have on the quality of the results, more real-life data are required to better evaluate the BTA's performance against the ITA.

Modeling of transient flows in viscoelastic pipe network with partial blockage

Abstract In this study, transient flow and partial blockage in polyethylene (PE) pipe network are investigated experimentally and numerically using the method of characteristics in the time domain considering pipe-wall viscoelasticity. The experiments were conducted on a PE pipe network with and without partial blockage. The experimental pressure signals were damped during a short period of time in the blockage-free case. The numerical model was calibrated by the inverse transient analysis (ITA). The hydraulic transient solver calibrated with one Kelvin–Voigt element showed good consistency with the experimental results. Partial blockages with different lengths and sizes were examined at different locations of the pipe network. Results reveal an increase in head loss, pressure signal damping, and phase shift with increase in blockage. In addition, the location and characteristics of blockages with different sizes were determined using the ITA in the pipe network.

Algorithm for Detecting Multiple Partial Blockages in Liquid Pipelines by Using Inverse Transient Analysis

SummaryPartial blockages form on the inner wall of the crude-oil pipelines as a result of asphaltene precipitation, scale deposition, and so forth. If not controlled and rehabilitated periodically, these partial blockages can have a serious adverse effect on the efficiency, economy, and safety of the operation of the pipeline. Before each rehabilitation operation, the detection of the local flow-condition deterioration (change in diameter) is necessary for efficiency and economy considerations, especially for long-distance subsea crude-oil pipelines. Most conventional detection techniques require the installment of detecting devices along the pipeline. However, they are economically expensive and even technically impossible for pipelines in operation. The present work focuses on an economically efficient technique that can realize remote nonintrusive measurement (i.e., the pressure-wave technique). The purpose of our research is to develop a method for calibrating multiple irregular partial blockages inside the liquid pipe by using the pressure response in the time domain at certain measuring points along the pipe under the transient state. The method involves the direct problem and the inverse problem. The direct problem is the simulation of the transient flow in the liquid pipe with single or multiple partial blockages. A second-order direct problem solver is developed in the framework of the Godunov-type finite-volume method (FVM). The inverse problem is to determine the partial-blockage distribution by using the pressure response at the measuring point under transient conditions. Our algorithm to solve the inverse problem comprises analytical evaluation and optimization. The analytical evaluation provides a reliable search space for the following optimization procedure, and thus effectively alleviates the local optimum problem. Numerical results demonstrate the efficiency and accuracy of proposed methods for solving the direct and inverse problems.

Efficient leak detection in single and branched polymeric pipeline systems by transient wave analysis

The widespread use of plastic pipes in different fluid conveyance systems has greatly driven the recent development and application of transient-based methods (TBMs) for leak detection in viscoelastic/polymeric pipelines. Current TBMs for viscoelastic pipe leak detection are usually achieved by a two-step procedure, namely viscoelastic parameters identification and leak detection, which requires the pre-knowledge of intact system states (i.e., non-leak) for comparative analysis. This paper presents an efficient single-step frequency domain inverse transient analysis (FDITA) method for simultaneous identifications of viscoelastic parameters and leaks in plastic pipes, so as to enhance the applicability and accuracy of TBMs. Both the single and branched polymeric pipe systems are applied for the method development and application. To this end, analytical solutions of single and branched systems from the transfer matrix method are firstly derived to represent the transient frequency responses of viscoelastic pipelines with leaks. A global optimized nonlinear curve fitting method is then employed to identify both viscoelastic parameters and potential leaks by knowing/measuring other system and flow conditions. Extensive experimental validations and numerical applications of both single and branched pipe systems demonstrate the very good efficiency and accuracy of the developed method for leak detection in different viscoelastic pipe systems. Furthermore, the mechanism of transient wave-leak-viscoelasticity is analysed based on these application results and theoretical evidence. Finally, a sensitivity analysis is performed to quantify and discuss the advantages and potential limitations of the developed method in the paper.

Fast computation of inverse transient analysis for pipeline condition assessment via surrogate modeling with sparse sampling strategy

Inverse transient analysis (ITA) is a powerful tool for pipeline condition assessment, where the concerned parameters are decided by matching the measured transient signal with its physical model. This scheme is computationally expensive because, in the optimization procedure, the model has to be evaluated many times via time-domain full-wave numerical simulations. To address this problem, a fast algorithm of ITA is proposed, where the role of the numerical model is replaced by an easy-to-evaluate surrogate model. The Kriging method is employed to build the surrogate model of transient wave, given a series of samples of concerned parameters and the associated numerical model outputs. Considering the sparse nature of the high-dimensional pipe condition parameters, a sparse sampling strategy is proposed to optimize the samples of parameters. Two application examples, i.e., pipe viscoelastic parameter estimation and leakage identification, are introduced to demonstrate that the proposed method is as accurate as the traditional ITA but has a much lower computational cost.

The method for leakage detection of urban natural gas pipeline based on the improved ITA and ALO

To solve the problems of the difficulty in early leakage monitoring and larger positioning error for urban hazardous chemicals pipelines, the optimized method based on the improved Inverse Transient Analysis (ITA) and Ant Lion Optimizer (ALO) was proposed. Firstly, based on the obtained experiment's results of leakage of natural gas in the non-metallic pipeline, the segment classification method was incorporated into the pressure gradient calculation. The modified method can adapt to the multi-node characteristics of urban pipe networks and help to obtain the preliminary positioning calculation results after optimization. Then the calculation results were embedded in the ITA calculation model. The input parameters of the gas pipeline such as boundary conditions, leakage rate and friction coefficient were used to establish the characteristic linear equations. Then the objective function of the least-squares criterion was defined, and the improved ITA model suitable for leakage detection of urban natural gas pipeline networks was constructed. Finally, the ALO was used to optimize the calculation process of the improved ITA model, and iteratively optimize the optimal friction coefficient and its corresponding minimum objective function (OF) value. As a result, a more precise location of the leakage source was calculated. The validation of the modified method is conducted by comparing the calculated values with the experiment's results. The results show that the method can accurately predict the location where the pipeline leakage occurs. The minimum error is 3.17%. Compared with the traditional ITA, this method not only accelerates the convergence speed of the objective function, but also improves the accuracy of location calculation.

Real-time leak detection in oil pipelines using an Inverse Transient Analysis model

Based on Inverse Transient Analysis (ITA) method, a real-time leak detection method is proposed to capture leak location and the associated leak rate in oil pipe conveyance systems. In the proposed approach, location and flow rate of leak (if any), the fluid properties, as well as physical parameters of the system, are calculated in consecutive periods through minimizing the discrepancy between the calculated and measured flow parameters of the system. The method of characteristics is employed to numerically calculate the transient responses of the system and the genetic algorithm is utilized as the optimization engine. The proposed approach was applied to several real pipeline systems in which the required transient flow data are either directly collected from the field or fabricated with a third-party numerical software. Extensive numerical explorations were conducted to investigate the performance of the proposed method in real-time leak detection and to determine the extent to which field data errors, stemming from Supervisory Control and Data Acquisition (SCADA) systems and measurement equipment, affect the leak flow rate and location detectability of the proposed approach. The results show that the proposed approach provides promising results under a variety of transient and steady-state flow conditions even in the case with small leak flow rate of around 2% of the line rate. The results also reveal that the noises in the measurement data and the errors originated from SCADA systems do not significantly compromise the leak detectability of the proposed approach, confirming that the proposed approach can be utilized in practice.

A Nelder–Mead algorithm-based inverse transient analysis for leak detection and sizing in a single pipe

Abstract In this paper the results of an experimental validation of a technique for leak detection in polymeric pipes based on the inverse transient analysis (ITA) are presented. In the proposed ITA the Nelder–Mead algorithm is used as a calibration tool. Experimental tests have been carried out in an intact and leaky high-density polyethylene (HDPE) single pipe installed at the Water Engineering Laboratory (WEL) of the University of Perugia, Italy. Transients have been generated by the fast and complete closure of a valve placed at the downstream end section of the pipe. In the first phase of the calibration procedure, the proposed algorithm has been used to estimate both the viscoelastic parameters of a generalized Kelvin–Voigt model and the unsteady-state friction coefficient, by minimizing the difference between the numerical and experimental results. In the second phase of the procedure, the calibrated model allowed the evaluation of leak size and location with an acceptable accuracy. Precisely, in terms of leak location the relative error was smaller than 5%.

Surrogate-Assisted Inverse Transient Analysis (SAITA) for Leakage Detection in Pressurized Piping Systems

The inverse transient analysis (ITA) is a well-known leak detection method for pressurized piping systems. In this method, unknown parameters of the number, location, and size of leakages are obtained through solving a nonlinear programming problem using an optimization technique. Both transient analysis and optimization are time consuming and make the whole process of ITA computationally inefficient. In this study to increase the efficiency of the ITA, the methods of Surrogate Assisted Genetic Algorithm-Local Search (SAGA-LS), SAGA-Pre Selection, and SAGA-Clustering Technique are investigated. The methods are applied to a benchmark example and the results are compared to the standard ITA. The results indicate that the ITA-SAGA-LS has the best performance with 92% increase in the accuracy of the calculated leakage area as compared to the standard ITA.

Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification

Strategic pipeline asset management requires accurate and up-to-date information on pipeline condition. As a tool for pipeline condition assessment, inverse transient analysis (ITA - a pipeline model calibration approach) is typically formulated as a deterministic problem, and optimization methods are used for searching a single best solution. The uncertainty associated with the single best solution is rarely assessed. In this paper, the pipeline model calibration problem is formulated as a Bayesian inverse problem, and a Markov Chain Monte Carlo (MCMC) based method is used to construct the estimated posterior probability density function (PDF) of the calibration parameters. The MCMC based method is able to achieve parameter estimation and uncertainty assessment in a single run, which is confirmed by numerical experiments. The proposed technique is also validated using measured hydraulic transient response data from an experimental laboratory pipeline system. Two thinner-walled pipe sections (simulating extended deterioration) are successfully identified with an assessment of the parameter uncertainty. The results also suggest that proper sensor placement can reduce parameter uncertainty and significantly enhance system identifiability.

Sensor Placement Strategy for Pipeline Condition Assessment Using Inverse Transient Analysis

Inverse transient analysis (ITA) has been recognized as a useful technique for pipeline condition assessment, such as leak detection and pipe wall thickness estimation. The effectiveness and accuracy of the inverse analysis are dependent on the sensor placement design; however, previous research on this topic is limited. This paper investigates how the number and location of pressure sensors affects the identifiability of pipeline parameters in the ITA approach. An analytical analysis demonstrates that infinite pipe parameter combinations can produce almost the same pressure responses at specific observation locations, which means that the identifiability of the pipe parameters will be poor if sensors are installed at these locations. Numerical sensitivity studies and multiple ITA case studies are conducted to investigate the relationship between the sensor locations and the parameter identifiability. It is found that at least three sensors are needed, and given the first two sensors are N reaches apart (i.e. N pipe segments in the inverse model), the third sensor should not be placed at nodes that are separated from any of the first two sensors by an integer multiple of N reaches.

Simulation of transient flow in viscoelastic pipe networks

The use of polymeric pipes such as polyethylene (PE) and polyvinyl chloride (PVC) has recently increased in water distribution networks. This necessitates the understanding of the viscoelastic behaviour of these pipes in practice and in particular for transient flow analysis. The purpose of this study is to calibrate a developed numerical model based on the experimental results of transient flow in PE pipe networks. The linear viscoelastic model parameters were calibrated using the inverse transient analysis. Comparison of numerical results with experimental data indicated that the developed viscoelastic model was able to predict both pressure wave damping and dispersion in these pipe systems. Results confirmed a negligible viscoelastic effect of single pipe and pipe network on the linear viscoelastic model. Hence, the calibrated results of a single PE pipe were used to simulate the transient flow in the pipe network. The experimental and simulation results of pipe network transient flow in this study are new and advance previous studies.

Reduced-order model with radial basis function network for leak detection

ABSTRACTAn inverse transient analysis technique for detecting leaks in water pipe systems through proper orthogonal decomposition (POD) with a radial basis function network (RBFN) is proposed. To verify its novelty and credibility, the performance of this technique was compared with a conventional technique which uses a metaheuristic algorithm in artificial cases with various leak conditions. The inherent shortcomings of heuristic techniques requiring a substantial computational cost were shown to have been resolved. This is because POD acquires a basis by using singular value decomposition and handles data in a reduced-order space which is composed of that basis. Several conclusions were derived. First, the reliability to detect leaks was confirmed. Next, the RBFN learned the relationship between the POD coefficients and leak coefficients through map learning supervised by snapshots with a reliable resolution. Finally, even if another leak occurred, it could be assessed using the presented technique without any data updates.

Leakage detection and calibration of pipe networks by the inverse transient analysis modified by Gaussian functions for leakage simulation

The Inverse Transient Analysis (ITA) is a well known method for leakage detection and calibration of pipe networks. To reduce the problem of dimensionality as well as to allocate candidate leakages everywhere in the network and to handle the simulation and measurement uncertainties, it is assumed that a leakage has a quasi-normal distribution around its true location. Accordingly, a Gaussian function is introduced to simulate each candidate leakage so that the Gaussian function parameters are the ITA decision variables. To manage the ITA process and decrease unnecessary computations, a conceptual step-by-step algorithm is introduced through which the number of candidate leakages is gradually increased until the convergence criteria are met. Solving a benchmark example reveals that the modifications play a significant role in increasing both accuracy and efficiency of the ITA. As compared to the traditional ITA, the new version was successful in solving the example with about 30 times less computation.

Development of Multiple Leakage Detection Method for a Reservoir Pipeline Valve System

The detection of multiple leakages in pipeline systems has been one of the challenging issues for the control of water loss in water distribution systems. Inverse transient analysis can be a useful principle for predicting leakage through the calibration of location and leakage quantity, based on the pressure reflection that originates from an abnormal boundary condition. In this study, an innovative leakage detection method is proposed to address unknown conditions on multiple leakage dimensions through introduction of revised leakage expressions based on a frequency domain approximation. A multiple leakage function was modified for an efficient representation of multiple abnormalities at a reservoir pipeline valve system. An iterative metaheuristic scheme (IMS) was designed to handle an optimization scheme for multiple leakages using a pressure response for a discharge impulse introduced through value manipulation. In order to address unsteady friction in hydraulic transients combined with multiple leakages, both one-dimensional and two-dimensional models were used to derive leakage expressions for turbulent and laminar flow conditions. An isolated multiple leakage function (IMLF) was proposed to exclusively encapsulate the impact of leakages and unsteady fiction. Considering uncertainties in the hydraulic transient propagation, data noise, and multiple local optima issues in large parameter calibrations, three advanced schemes were modularized to improve detectability of IMS. Several hypothetical examples were presented to show the potential of IMS, validity of three advanced schemes, and robustness in multiple leakage prediction compared to existing approaches.

Multi-stage parameter-constraining inverse transient analysis for pipeline condition assessment

Abstract Fault detection in water distribution systems is of critical importance for water authorities to maintain pipeline assets effectively. This paper develops an improved inverse transient analysis (ITA) method for the condition assessment of water transmission pipelines. For long transmission pipelines ITA approaches involve models using hundreds of discretized pipe reaches (therefore hundreds of model parameters). As such, these methods struggle to accurately and uniquely determine the many parameter values, despite achieving a very good fit between the model predictions and measured pressure responses. In order to improve the parameter estimation accuracy of ITA applied to these high dimensional problems, a multi-stage parameter-constraining ITA approach for pipeline condition assessment is proposed. The proposed algorithm involves the staged constraining of the parameter search-space to focus the inverse analysis on pipeline sections that have a higher likelihood of being in an anomalous state. The proposed method is verified by numerical simulations, where the results confirm that the parameters estimated by the proposed method are more accurate than the conventional ITA. The proposed method is also verified by a field case study. Results show that anomalies detected by the proposed methods are generally consistent with anomalies detected by ultrasonic measurement of pipe wall thickness.