Power Plant Piping Research Articles

Creep fatigue life prediction of pipe joints under complex bending-torsional loading using large-scale nonlinear structural analysis

With the expansion of clean energy, thermal power plants will be used as a load-following power plant. Thus, temperature and strain variations will occur during load fluctuations including start and stop of operation, and large-diameter pipes will be damaged by fatigue in addition to creep due to internal pressure. Especially, in a bent pipe such as an elbow pipe, bending and torsion are simultaneously applied. Therefore, it is important to predict the creep fatigue life in a bending and torsional stress environment. In this study, analysis method for creep fatigue life using Norton’s law, ductile exhaustion law, and Manson-Coffin’s law is proposed. Next, the proposed method was applied to the prediction of creep fatigue life of the test samples for thermal power plant piping, and the validity of the proposed method was verified by comparing creep fatigue life obtained by proposed method and that obtained by an experiment. In addition, the proposed method is applied to the prediction of creep fatigue life with load fluctuations and investigation of the effects of load fluctuation interval on creep fatigue life.

Hydrogen Measurement & Extraction at Nevada Solar One

Hydrogen was measured and extracted from the headspace gas of four expansion vessels that are components of the heat transfer fluid (HTF) subsystem in the Nevada Solar One (NSO) power plant, Boulder City, Nevada. Direct, real-time measurements of hydrogen partial pressures in the headspace gas were accomplished using the recently installed hydrogen mitigation process that was developed jointly by the National Renewable Energy Laboratory (NREL) and Acciona Energy, the owner/operator of NSO. This method combines the two functions of extracting hydrogen from the headspace gas and measuring hydrogen partial pressure in the headspace gas. During 2022 and 2023, we operated the process regularly and made real-time measurements of hydrogen partial pressures. In addition, DLR in Germany measured dissolved hydrogen concentration in the circulating HTF. These two measurements were compared via Henry’s Law and found to be consistent. Measured values also were compared to model results that were generated by the NSO plant model that was written to predict hydrogen levels in the power plant piping and components. The model predicted hourly hydrogen partial pressures in the expansion tanks for two cases - hydrogen extraction off, and hydrogen extraction on. Real-time hydrogen measurements and sampled HTF measurements were compared to hydrogen levels that were predicted for these two cases. We found good agreement between the hydrogen measurements and the modeled hydrogen for the extraction on case. These results indicate that the extraction process is working properly with its expected performance.

Failure criterion and seismic fragility evaluation of isolated nuclear power plant piping system using BP neural network

The pipeline connecting the isolated nuclear island and the non-isolated turbine building is prone to significant relative displacements during intensive earthquakes. Generally, elbows closest to the isolation layer are considered to be at particularly high risk of seismic damage. The failure criterion is the critical part in determining the damage state of elbows throughout the loading cycle. Therefore, in this study, a three-tier, four-category failure criterion was firstly proposed in response to the damage patterns of elbows. A BP neural network model was subsequently developed using extensive simulation data derived from a verified numerical model, accompanied by influence analysis of the three failure indices. Finally, a fragility evaluation was conducted based on the seismic response of the piping system, and a comparison is made between the new criterion and the existing ones. The results indicate that the new failure criterion demonstrates comprehensiveness and safety, enabling a more detailed division of damage before elbow failure and providing more conservative estimates upon failure occurrence. Additionally, the study finds that under the current design of nuclear power plants, elbows across isolation layers fail to meet the requirements for safe shutdown earthquakes in certain directions. By adjusting the elbow parameters, the resistance of the elbows to damage under seismic conditions can be improved to some extent.

Engineering estimate of plastic collapse loads for cracked pipe bends under in-plane and out-of-plane bending

Nuclear power plant piping systems frequently encounter complex loads due to factors like internal pressure, self-weight, structural supports, and operational conditions. Within these systems, pipe bends play a crucial role in releasing energy through deformation. Cracks pose a risk to the integrity of the system, necessitating the calculation of the plastic collapse load for cracked pipe bends. This study presents estimations for the plastic collapse load of cracked pipe bends under pure out-of-plane bending moments and simultaneous in-plane and out-of-plane bending moments. Cracks located in the intrados, extrados, and crown of pipe bends were considered. The estimations for plastic collapse load are proposed based on the observed similarity between plastic collapse load and plastic deformation under both in-plane and out-of-plane bending conditions. For combined in-plane and out-of-plane bending moment conditions, circular and parabolic relationships have been proposed for a straightforward plastic collapse load prediction. Additionally, the estimations for plastic collapse loads were derived from the results of finite element analysis conducted on crack-free pipe bends, demonstrating its applicability to cracked pipe bends as well.

Identification of acid phosphate corrosion in heat recovery piping of combined cycle power plants

Failure of heat recovery units in power plants is a serious problem that causes large economic losses. Accurate determination of the failure mechanism is critical to identify problems at an early stage and make recommendations to power plant operators to prevent equipment failures. These failures are due to tube breakage caused by various mechanisms such as acid corrosion (hydrogen attack), temperature damage, caustic corrosion, and acid phosphate corrosion. The present work aims to report a case study of four damaged tubes from a heat recovery steam generator from a unit of combined cycle power plants (HRSG). The techniques of simple and high-resolution transmission electron microscopy (TEM-HRTEM), scanning electron microscopy with elemental analysis (SEM-EDS) and X-ray diffraction (XRD) allowed to provide evidence of the presence of the acid phosphate corrosion mechanism in three of the four pipes analyzed.

Effects of microalloying element addition on mechanical properties of SA508 Gr.1A low-alloy steels

SA508 Gr.1A low-alloy steel is being considered as a candidate material for main steam line piping in nuclear power plants. Therefore, improving its strength and toughness is essential for enhancing the leak-before-break (LBB) margin. In this study, six types of model alloys were fabricated by varying the contents of microalloying elements (C, Cu, B, Ti, and Nb) to enhance the mechanical properties of the specimens. The addition of a few ppm of B led to the formation of a fine-grained low-temperature transformation microstructure, resulting in the highest strength among the model alloys. However, the addition of Nb and Ti increased the formation of coarse ferrite, significantly decreasing the strength of the alloys. Reducing the C content while adding a small amount of B simultaneously maintained strength and enhanced toughness. Furthermore, the LBB margins of model alloys and commercial steel were evaluated to validate the influence of varying microalloying content. The model alloys exhibited a substantial increase in yield strength and fracture resistance, resulting in a more than 10% increase in the LBB margin. Notably, the LBB margin of the alloy with 15 ppm B was 1.39, approximately 25% higher than that of commercial steels.

Noise-robust pipe wall-thinning discrimination system using convolution recurrent neural network model

Pipe wall-thinning is a phenomenon whereby the thickness of pipes in a nuclear power plant decreases over time owing to extended operational years. This thickness reduction is caused by various long-term thermal aging mechanisms such as Flow-Accelerated Corrosion, Liquid Droplet Impingement Erosion, cavitation, and flashing. Reducing the thickness of the secondary system pipes to the point of rupture can lead to severe human casualties and significant economic losses. Consequently, domestic power plant operators regularly manage the power plant pipes. Ongoing research focuses on the identification and management of pipe wall-thinning. However, previous studies have encountered problems in accurately judging the decrease in pipe wall-thinning in the presence of noise. To overcome this, Convolutional Neural Network (CNN) models based on image feature analysis have been used. This approach allows for the differentiation of pipe wall-thinning feature from small-sized noise in a single image. However, there were difficulties in making accurate judgments for large-sized noise that resembled the feature of pipe wall-thinning. This paper aims to analyze the limitations of the current pipe wall-thinning evaluation methods and to achieve accurate pipe wall-thinning discrimination through time-series analysis of continuous pipe wall-thinning data. The proposed method employs a Convolutional Recurrent Neural Network (CRNN) model, integrating the Recurrent Neural Network(RNN) model with the CNN model. The image feature of the pipes, extracted using CNN, are utilized as inputs for the RNN. This enables the observation of how the image features of the pipes change over time. This feature differentiates from the time-series feature of noise that occurs suddenly. Through this method, the paper proposes a new approach for effectively identifying the gradual decrease in pipe wall-thinning, enabling precise assessment of pipe wall-thinning progression.

Dynamics optimization of small branch pipes in nuclear power plants based on machine learning algorithms

Vibration fatigue failure of small branch pipes poses a great threat to the safe operation of nuclear power plants. However, the transient and wide-band vibration problems are not adequately considered in ASME and RCC-M code, resulting in repeated fatigue failures. In addition, the current research mainly focuses on vibration test methods and fatigue analysis methods, neglecting the study of pipeline vibration characteristics. Therefore, innovative approaches were essential for effectively managing complex dynamic loads. In this study, an innovative approach combining backpropagation artificial neural networks (BP-ANN) and non-dominated sorting Genetic Algorithm II (NSGA-II) was proposed to optimize the vibration of these pipes. The goal was mitigating vibration-induced failures by enhancing operational stability. The methodology progressed through several key stages. Firstly, BP-ANN was utilized for regression analysis, correlating pipe characteristics to vibration effects. Through regression analysis, the complex interrelationships governing the pipes' dynamic behavior was revealed. Subsequently, based on the regression model, NSGA-II was used to derive an optimal combination of design parameters to minimize the vibration response. The proposed technique was validated on an L-shaped cantilevered pipe via finite element simulations and physical experiments. The analysis case shows that the BP-ANN model demonstrated excellent accuracy in predicting vibration responses. Meanwhile, NSGA-II successfully revealed the trade-offs between conflicting objectives, generating a Pareto-optimal set balancing stability under different excitation directions. This study highlights the potential of machine learning methods for dynamic optimization of small branch pipes in nuclear power plants, and verifies the accuracy and effectiveness of the method through experiments. The research results provide a new idea for small branch pipe design and vibration control of nuclear power plant, which contributes to enhancing the safety and reliability of small branch pipes.

Creep-Fatigue Life Evaluation for Grade 91 Steels with Various Origins and Service Histories

Grade 91 steel is widely used in the boilers and piping of thermal power plants. There has been significant research interest in understanding the variations in creep characteristics among different heats of this steel for effective plant management. In recent years, thermal power plants have been subjected to frequent load changes and startup/shutdown to adjust power supply and demand and stabilize frequencies. These operational shifts have raised concerns regarding the potential for creep-fatigue damage in high-temperature components. Therefore, this research focuses on creep-fatigue properties of Grade 91 steel and their predictability. Tensile, creep, strain-controlled fatigue, and strain-controlled creep-fatigue tests were performed on six Grade 91 steels with different heats and/or histories, and the characteristics in each test were compared. As a result, the variations in creep-fatigue life among the materials were found to be correlated with the difference in creep characteristics and stress level during stress relaxation. Furthermore, the study involved a comparative assessment of the predictive performance of creep-fatigue life using five different approaches: time fraction, classical ductility exhaustion, modified ductility exhaustion, energy-based, and hybrid approaches. Among these approaches, the hybrid approach, based on inelastic strain energy density at fracture formulated as a function of inelastic strain rate, exhibited the most accurate predictive performance.

Reliability Analysis of PAUT Based on the Round-Robin Test for Pipe Welds with Thermal Fatigue Cracks.

Thermal fatigue cracks occurring in pipes in nuclear power plants pose a high degree of risk. Thermal fatigue cracks are generated when the thermal fatigue load caused by local temperature gradients is repeatedly applied. The flaws are mainly found in welds, owing to the effects of stress concentration caused by the material properties and geometric shapes of welds. Thermal fatigue pipes are classified as targets of risk-informed in-service inspection, for which ultrasonic testing, a volumetric non-destructive testing method, is applied. With the advancement of ultrasonic testing techniques, various studies have been conducted recently to apply the phased array ultrasonic testing (PAUT) method to the inspection of thermal fatigue cracks occurring on pipes. A quantitative reliability analysis of the PAUT method must be performed to apply the PAUT method to on-site thermal fatigue crack inspection. In this study, to evaluate the quantitative reliability of the PAUT method for thermal fatigue cracks, we fabricated crack specimens with the thermal fatigue mechanism applied to the pipe welds. We performed a round-robin test to collect PAUT data and determine the validity of the detection performance (probability of detection; POD) and the error in the sizing accuracy (root-mean-square error; RMSE) evaluation. The analysis results of the POD and sizing performance of the length and depth of thermal fatigue cracks were comparatively evaluated with the acceptance criteria of the American Society of Mechanical Engineers Code to confirm the effectiveness of applying the PAUT method.

Numerical investigation of dusty tri-hybrid Ellis rotating nanofluid flow and thermal transportation over a stretchable Riga plate

Due to high-ultra thermic significances, the nanosize materials are used in various chemical and mechanical engineering, modern technology and thermic engineering eras. For industrial growth of a country, one of the biggest challenges for engineers and scientists is improvement in thermal production and resources. In this study we analyzed the momentum and thermic aspects of MHD Ellis ternary nano material embedded with dust particles via stretchable Riga plate including volume concentration of dust material. The flow generating PDE’s for two phase models are minimized into dimensionless nonlinear ODE’s by using the right modification. To acquire the graphical results the BVP4c method was adopted in MATLAB software. Fundamental aspects affecting velocity and temperature have investigated through graphs. Additionally Nusselt number and skin friction have also been evaluated. Compared it with previous literature to check the validity of results. Finding reveals that as compared to dusty phase the performance of trihybrid nano phase thermal transport is improved. Moreover, the temperature profile increases for rotational and volume fraction dust particles parameter. Dusty fluids are used in numerous manufacturing and engineering sectors, like petroleum transport, car smoke emissions, caustic granules in mining and power plant pipes.

Detection of defects initiation in weld joints

Welded joints on various pipelines, especially steam pipelines of fossil power plants, are exposed to high pressure and temperature of steam during operation. The applied stress and temperature together with the chemical composition and microstructure of the material have a major influence on the damage growth in these joints. Growth of defects as a time-dependent event, the sensitivity of the material to damage due to stress temperature and others plays a major role. In the case of steam pipes of fossil power plants, this is mainly creep damage. Early detection of these defects, especially at their initial stage, can help in managing the service life and thereby reducing the costs for operation, both by minimizing unplanned shutdowns as well as by planning any repairs in time. The work is focused on the detection of defect indications, especially creep damage occurring in weld joints and heat-affected areas. The aim is to distinguish manufacturing defects of welded joints from indications of early crack growth by ultrasonic testing. Indications from manufacturing defects may also be detected during testing and, if detected, will be evaluated in the same way as defects that are primarily targeted by the testing techniques. Several different techniques were tested on samples cut from the operated steam pipeline systems and compared with the results of metallographic analyses on selected parts.

Reliability Analysis of Pipe Wall Thinning based on Quantification of Ultrasonic Testing

Piping in nuclear power plants is subject to corrosion and erosion caused by the interaction with fluids it carries. In order to prevent accidents such as pipe rupture, it is necessary to non-destructively inspect the thickness of the pipe wall and predict the remaining pipe life. In contrast, signals obtained by non-destructive inspection are affected by various uncontrollable and unknown factors, which will result in uncertainty in evaluating pipe wall thickness. Ignoring the uncertainty would lead to a large error in the pipe reliability assessment. Therefore, it is important to develop a reasonable pipe wall thinning management that can takes the uncertainty of non-destructive testing into consideration. Based on this background, this study aimed to develop a piping wall thinning prediction model that accounts for the uncertainty in evaluating pipe wall thickness and to evaluate its applicability to ultrasonic testing. At first, ultrasonic tests were performed to measure the thickness of specimens simulating flow accelerated corrosion. The results of the measurements were statistically analysed to obtain a mathematical model correlating the evaluated and true thickness. A numerical model to predict the reduction of wall thinning with its uncertainty is developed. Compared to the conventional method, the proposed method is able to predict wall thickness with high accuracy.

Ultimate Strength of a Thin Wall Tee for Sodium Cooled Fast Reactors Under Seismic Loads

Abstract It is a key issue to clarify failure mode of piping in nuclear power plants and its safety margin included in the design practice. In this study, a series of dynamic failure tests of a thin wall tee for sodium-cooled fast reactors was conducted. Some discussions related to the thin wall tee are provided on the failure mode under seismic load, dynamic response behavior, accuracy of fatigue prediction by dynamic elastic-plastic analysis, and a safety margin of fatigue evaluation which is included in conventional design rule.

Numerical study of thermal mixing phenomenon using partially averaged Navier-Stokes

Thermal mixing between cold and hot streams of fluids in a T-junction may lead to high-cycle thermal fatigue in nuclear power plant piping material. Temperature fluctuations near the wall surface are the main reason for this degradation. Computational Fluid Dynamics (CFD) using space and energy-resolving turbulence modeling paradigms can predict this transient behavior. In this study Partially averaged Navier-Stokes (PANS) turbulence method is used to simulate the Vattenfall T-junction test case. Two different values for the filter control parameter fk = 0.5 and fk = 0.25 are used. Calculations results for velocity and temperature fields are compared with Large Eddy Simulations (LES) and available experimental data. For fk = 0.5, time-averaged and root mean square (RMS) temperatures show lower values than the LES and experimental data. For fk = 0.25 both time-averaged and RMS temperature results are close to the LES and experimental values. The Power Spectral Density (PSD) of the temperature signal shows peaks in the case of both PANS-0.25 and LES in the range of 3 to 4 Hz, which is in line with the experimental results. It can be concluded that the PANS method has the capability to resolve temperature and velocity fields for thermal mixing phenomenon in T-junction pipes and can be used for the assessment of high-cycle thermal fatigue.

Fatigue damage development in 10CrMo9-10 steel for power plant pipes in as-received state and after 280,000 h of exploitation

This paper discusses an effect of 280,000 h of exploitation under internal pressure of 2.9 MPa and high temperature of 540 °C on the mechanical properties of 10CrMo9-10 (10H2M) power engineering steel. The mechanical response of the specimens obtained from two pipes: a new in the as-received state and exploited for a long period was assessed through the uniaxial tensile tests and subsequent fatigue tests. The long-term, high-temperature exposure of 10H2M steel resulted in the deterioration of its mechanical properties and was quantitatively described as a function of the fatigue damage measure, φ, and the fatigue damage parameter D. Finally, the proposed methodology of power exponent approximation with both damage sensitive parameters (φ, D) enabled for successful determination of the 10H2M steel fatigue life.

New estimation method of limit pressures for thick curved pipes under internal pressure applicable to various bend angles

In this study, a new estimation method of limit pressures (loads) is suggested for reliability design of curved pipes under high internal pressure and temperature. The curved pipes are used in boiler pipes in a supercritical thermal power plants. To find any design parameters and their dimensions in reliability design of curved pipes, various boilers in supercritical thermal power plants in operation were investigated. In order to analyse the effect of the design parameters on the limit pressure, the design of experiment (DOE) was applied to design a curved pipes with various combinations of design parameters, and then the FE limit load analyses were performed to obtain limit pressures. The thickness of the curved pipe has the greatest effect on the limit pressure among the design parameters. Although the bend angle is design parameter, the proposed estimation methods for easily calculating the limit load do not include the bend angle and then there have been difficulties in reliability design of curved pipes with any band angle. Therefore, to solve such difficulties, two estimation methods of limit pressure (load) including bend angle were suggested and the validity of the proposed estimation methods of limit load (plastic pressure) under internal pressure was objectively verified through statistical error analysis with the 60 FE analysis results which are different from the data used when the method was derived. The proposed estimation method applicable to various bend angles shows the best results in the evaluation of mean error, maximum error, and standard deviation of error, which are evaluation criteria. The proposed estimation method shows a very good result compared to existing methods, having the mean error of 0.89%, a maximum error of 2.50%, and a standard deviation of 0.70% for all data regardless of the bend angle.

A review on crack growth simulation for estimating failure probability of pipes in nuclear power plants

A review on crack growth simulation for estimating failure probability of pipes in nuclear power plants

Evaluation of seismic margins for nuclear power plant piping systems using ratcheting criterion

In the wake of recent beyond design basis earthquakes, it is very essential to evaluate seismic margins of nuclear power plant piping systems. Better seismic margins will ensure the safety in the event of less probable bigger seismic event beyond consideration of design level. At present, permissible codal stress limits are used to evaluate these margins and it has been experimentally demonstrated that ratcheting is the significant failure mode for piping systems subjected to reversing dynamic load. Hence, it is more prudent to use actual failure criterion for evaluation of seismic margins. In this paper, a detailed framework is provided for evaluation of seismic margins of piping systems using ratcheting criterion. As ratcheting is the potential mode of failure for piping systems under earthquake load, two strain-based performance levels based on code practice and experience gained with experiments carried out by Bhabha Atomic Research Centre, are used for margin assessment. It is usual practice to carry out stress-based response spectrum analysis for design and qualification of piping systems under earthquake load. In order to offer a practical, simpler and feasible solution for ratcheting evaluation, the same response spectrum analysis in iterative way, can be used to evaluate ratcheting in the piping systems. Experimentally validated numerical procedure is used for ratcheting evaluation. This procedure is demonstrated for a piping system of a typical nuclear power plant. Seismic margins for the piping system are evaluated using codal provision and two ratcheting based performance levels for deterministic and probabilistic methods.

Review of Creep-Thermomechanical Fatigue Behavior of Austenitic Stainless Steel

Research on the creep-thermomechanical fatigue (CTMF) behaviors of austenitic stainless steel for nuclear power plant pipelines is reviewed in the present paper. The stress response behavior, the main damage mechanisms, including thermomechanical fatigue, creep, oxidation, and dynamic strain aging (DSA), as well as the effects of strain dwell type, dwell time, and temperature-strain phase angle on fatigue life behavior of austenitic stainless steel under CTMF loading conditions are systematically discussed, and the coupled effects of various damage mechanisms are revealed. It is emphasized that CTMF is closer to the actual service condition of nuclear power plant pipes. It is pointed out that the traditional method of life design based on the isothermal fatigue test data is not conservative. Finally, the research on CTMF behaviors of austenitic stainless steel for nuclear power plant is summarized and prospected.