High Cycle Thermal Fatigue Research Articles

Development of a real-time ultrasonic monitoring tool for high-cycle thermal fatigue

Pipe networks within nuclear power plants (NPPs) are susceptible to high-cycle thermal fatigue (HCTF) failures especially in so-called mixing zones where fluids with different thermal and hydraulic properties interact. The 1998 incident at Civaux 1 NPP is a good example of such a failure and its potential consequences. Given the critical impact on safety of these NPP components, a non-invasive method for HCTF progression monitoring in real time is expected to be of great use. Previous ultrasonic monitoring work showed that it is possible to predict the through-thickness temperature distribution and its temporal evolution of a mild steel block to within ±2 °C, relative to a resistance temperature device. These predictions were achieved using time of flight measurements from an ultrasonic transducer placed on the accessible surface with the so-called inverse thermal model (ITM) to invert the data. However, experiments to date have been limited to slow (10 minute) thermal transients at low temperatures (T < 100 °C). Given that HCTF is driven by thermal gradients, the ITM method seems promising to monitor its progression. In this work the performance of the ITM method was investigated under more realistic conditions: faster (1 minute) thermal transients at higher temperatures (≈ 250-300 °C). A special high temperature electromagnetic acoustic transducer (EMAT) and a fast acquisition and inversion methodology were created to collect the data. The measurement setup and the collected data will be presented in this paper.

High cycle thermal fatigue of two austenitic stainless steels

Thermal fatigue is one of the main damage mechanisms that engineers must take into account in the periodic assessment of current nuclear power plants or the design of future ones. Fluctuations of temperature in the fluid is indeed inevitable, as is a partial transfer of these fluctuations to the solid walls, and the resulting oscillations of thermal gradients must stay low enough to prevent the formation of typical crack networks. In this study, high cycle thermal fatigue tests are performed under helium environment on two types of austenitic stainless steels, with an original apparatus called FLASH for thermal Fatigue by pulsed LASer beam and Helium jets. Crack initiation and crack network developments are detected by an InfraRed (IR) camera that is also used with IR pyrometers to accurately measure the cyclic thermal loading. The influence of temperature variation, pulse duration and an additional constant mechanical stress on crack initiation, crack propagation rate and crack network morphology is evaluated. Eventually, a numerical analysis of thermal fatigue tests, fed by proper experimental measurements on the crack initiation surface, allows deducing that the number of cycles to crack initiation is similar to the one obtained in more classical uniaxial isothermal fatigue results.

A two-level machine learning approach for predicting thermal striping in T-junctions with upstream elbow

Thermal striping is a phenomenon characterized by oscillatory mixing of non-isothermal streams, which is commonly seen in industrial processes such as nuclear coolant piping, petrochemical plants and liquefied natural gas transportation. The oscillatory mixing of hot and cold fluid can produce thermal field fluctuations and pose a potential risk of high-cycle thermal fatigue failures. Predicting and evaluating spatiotemporal fluctuations in thermal striping often requires high resolution and massive computational power. Although there have been extensive studies using machine learning algorithms on surrogate modeling, research focused on spatiotemporal fluctuation predictions is very limited. Due to the high dimensionality, it often requires complex algorithms with a large amount of high-fidelity training data, which limits the adoption of such methods for industrial applications. In this research, a two-level machine learning framework based on turbulence coherent structures is proposed and its application to a practical problem is demonstrated. The two-level design leverages vortex identification and local bias correction techniques, efficiently reducing the number of full-order simulations required for training. In the first level, well-organized coherent structures are extracted by performing Proper Orthogonal Decomposition on local parameters and then a tree-based machine-learning model is used to down-select the reference structures for the field reconstruction. In the second level, a parameterized convolution neural network is trained to predict the bias introduced by reference structures approximation. The demonstration of the methodology shows that the method can accurately capture the fluctuation frequencies and amplitudes of the spatiotemporal fields in a highly variational setting. Based on the vortex identification method, the methodology is expected to be applicable to general phenomenon driven by large coherent structures.

A comparison of ultrasonic temperature monitoring using machine learning and physics-based methods for high-cycle thermal fatigue monitoring

Failure of pipe network components in so-called mixing zones due to high-cycle thermal fatigue (HCTF) can occur within nuclear power plants where fluids of different thermal and hydraulic properties interact. Given that the consequences of such failures are potentially deadly, a method to monitor HCTF non-invasively in real-time is expected to be of great use. This method may be realised by a technique to determine the inaccessible temperature distribution of a component since thermal gradients drive HCTF. Previous work showed that a physics-based method called the inverse thermal modelling (ITM) method can obtain the temperature distribution from external temperature and ultrasonic time of flight (TOF) measurements. This study investigated whether the long-short-term memory (LSTM) machine learning architecture could be a faster alternative to the ITM method for data inversion. On experimental data, a 25-member ensemble of LSTM networks achieved an ensemble median root mean square error (RMSE) of 1.04°C and an ensemble median mean error of 0.194°C (both relative to a resistance temperature device measurement). These values are similar to the ITM method which achieved a RMSE of 1.04°C and a mean error of 0.196°C. The single LSTM network and the ITM method achieved a computation-to-real-world time ratio of 0.008% and 14%, respectively demonstrating that both methods can invert data in real-time. Simulation studies revealed that LSTM performance is sensitive to small differences between the training and real-world parameters leading to unacceptable errors. However, these errors can be detected via an ensemble of independent networks and, corrected by simply adding a correction factor to the TOF prior to being input into the networks. The results show that LSTM has the potential to be an alternative to the ITM method; however, the authors favour ITM for temperature distribution monitoring given its interpretability.

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.

Numerical analysis of temperature fluctuation characteristics associated with thermal striping phenomena in the PGSFR

Thermal striping is a complex thermal–hydraulic phenomenon caused by fluid temperature fluctuations that can also cause high-cycle thermal fatigue to the structural wall of sodium-cooled fast reactors (SFRs). Numerical simulations using large-eddy simulation (LES) were performed to predict and evaluate the characteristics of the temperature fluctuations related to thermal striping in the upper internal structure (UIS) of the prototype generation-IV sodium-cooled fast reactor (PGSFR). Specific monitoring points were established for the fluid region near the control rod driving mechanism (CRDM) guide tubes, CRDM guide tube walls, and UIS support plates, and the normalized mean and fluctuating temperatures were investigated at these points. It was found that the location of the maximum amplitude of the temperature fluctuations in the UIS was the lowest end of the inner wall of the CRDM guide tube, and the maximum value of the normalized fluctuating temperatures was 17.2%. The frequency of the maximum temperature fluctuation on the CRDM guide tube walls, which is an important factor in thermal striping, was also analyzed using the fast Fourier transform analysis. These results can be used for the structural integrity evaluation of the UIS in SFR.

Simulation of mixing flows with different temperatures in a T-junction using OpenFOAM code

This paper aims to evaluate the frequency of velocity and temperature fluctuations in the mixing region using OpenFOAM code. Turbulent mixing of fluids at different temperatures can lead to temperature fluctuations at the pipe material. These fluctuations, or thermal striping, inducing cyclical thermal stresses and resulting thermal fatigue, may cause unexpected failure of pipe material. Therefore, an accurate characterization of temperature fluctuations is important in order to estimate the lifetime of pipe material. Thermal fatigue of the coolant circuits of nuclear power plants is one of the major issues in nuclear safety. To investigate thermal fatigue damage, the OECD/NEA-Vattenfall T-Junction Benchmark was initiated to test the ability of state-of-the-art Computational Fluid Dynamics (CFD) codes to predict the important parameters affecting high-cycle thermal fatigue in mixing tees. In this study, to simulate the standard problem described above, the OpenFOAM code is used, which is an open integrated platform for numerical simulation of problems in continuum mechanics. At the first with Salome-meca code, a computational grid was created, consisting of about 450,000 nodes, and k-eps model and RANS models were used to simulate turbulence. OpenFOAM code results were compared with the available experimental results. The results were found to be in well-agreement with the experimental results in terms of amplitude and frequency of temperature and velocity fluctuations.

Numerical investigation on similarity of isothermal and thermal flow mixing in a horizontal T-junction configuration

Turbulent and stratified mixing flows can cause thermal fatigue in nuclear power plant piping systems. An isothermal Mixed-Fluid-Interaction (MFI) test rig is used to investigate mixing phenomena related to High Cycle Thermal Fatigue in nuclear power plant piping systems. Here, the cold heavy branch pipe fluid of the thermal mixing Fluid Structure-Interaction (FSI) facility is modeled by a sugar or salt solution. Due to limited optical accessibility of the FSI facility a numerical similarity comparison of the flow phenomena occurring in both experimental setups (MFI/FSI) is essential. Thus, Large-Eddy Simulations are carried out which are experimentally validated by applying the Wire-Mesh-Sensor measurement technique (MFI) and temperature measurements (FSI). Numerical LES investigation on similarity between two isothermal cases, three thermal mixing cases, and one geometrically similar scaled-up thermal mixing case is performed when the momentum ratio MR and the Richardson number Ri is kept constant. A very good agreement in the spatial distribution of the time averaged mean and rms values as well as statistical fluctuations is observed between the isothermal and thermal cases. Non-dimensional power spectrum density (PSD) of the mixing scalar fluctuation showed an almost unique profile, indicating the same origin for the occurring periodical fluctuation in all cases. The non-dimensional magnitude of the dominant frequency of the mixing scalar fluctuations in terms of the Strouhal number is in the range of 0.38<Sr<0.40. In the context of similarity, it is shown that the momentum ratio and the Richardson number are mainly responsible for the jet-formation and thus for the down- and upstream flow behaviour. The influence of the inlet Reynolds numbers Rem and Reb as well as the density ratio ΓR on the normalized flow characteristics seem to be negligible in comparison.

Effect of the Reynolds and Richardson numbers on thermal mixing characteristics

This paper presents a detailed numerical study regarding the influence of Reynolds and Richardson numbers in T-junctions with circular cross-section. The numerical investigation is based on the wall-resolved Large-Eddy Simulation (LES), which has been experimentally validated. The Reynolds number in the main pipe covers a range from Re=78400 to Re=235200, which is high enough to approach the engineering applications. This also belongs to the primary contribution of the current study. Furthermore, the temperature difference between the main pipe and branch pipe (Tm−Tb) is 180 K and the mass flow rate ratio (m˙m/m˙b) is 3. The primary focus is on thermal mixing characteristics in the downstream as well as on the evolution of the flow by consideration of gravity and buoyancy effects. Additionally, our study considers the thermal field and its corresponding fluctuations in the near-wall region. In addition, this paper also includes simulations with different T-junction configurations therefore we can examine the influence of the entrance orientation of the heavier cold branch pipe fluid on the mixing process and heat transfer. The analysis of our results indicates that gravity effects can be neglected in cases with increased Reynolds number and simultaneously decreased Richardson number. The area with high fluctuation intensities becomes larger by the higher Reynolds number and lower Richardson number of the mixing flow therefore they shows a higher potential for High Cycle Thermal Fatigue (HCTF). Furthermore, the highest near-wall thermal fluctuations are 40% of the temperature difference between the mixing flows.

Demonstration of the STRUCT turbulence model for mesh consistent resolution of unsteady thermal mixing in a T-junction

A STRUCTure-based (STRUCT) second generation (2G) URANS turbulence model is presented in this paper and assessed on the simulation of unsteady turbulent flow, with application to thermal striping evaluation in T-junctions. The closure methodology leverages the robustness of the Unsteady Reynolds-Averaged Navier-Stokes (URANS) formulation and enhances it with the addition of physics-based local resolution of flow structures. Numerical predictions of the velocity and temperature fields for the STRUCT model compare favorably with experimental data, where the main inlet Reynolds number ranges from 8790 to 16,300. Spectral analyses of the temperature signals are also performed in order to investigate the mechanism of high-cycle thermal fatigue in the flow mixing region. The computed spectra from the STRUCT solution agree with the reference LES calculations and experimental data, accurately reproducing both shape and magnitude of the power spectra density. Overall, the STRUCT model demonstrates significant potential to accurately and efficiently model the thermal striping phenomenon. Its application produces LES quality results, while the computational cost is comparable to the URANS solution.

Large-Eddy Simulation of turbulent thermal flow mixing in a vertical T-Junction configuration

Turbulent mixing of warm and cold water streams within a vertical T-junction configuration of a nuclear power plant piping system causes near-wall temperature fluctuations which may lead to High-Cycle Thermal Fatigue (HCTF) failure of the wall material. To predict frequency and amplitude of such temperature fluctuations accurately the method of Large-Eddy Simulation (LES) in the numerical simulation code OpenFOAM is used. As an experimental test case, the turbulent mixing experiment of Kamide et al. [1], where a vertical branch pipe with a cold water stream is connected from below to a horizontal main pipe with a warm water stream to form a vertical T-junction configuration. From the various observed flow patterns, the temperature and velocity data of the ‘wall jet’ are chosen as a reference because it is known to have the highest potential for thermal fatigue. Incomplete mixing and an instability associated with large turbulent structures near the junction region lead to significant temperature fluctuations close to the wall before a vertical thermal stratification further downstream stabilizes the flow. The highest near-wall fluctuation amplitudes are 26% of the temperature difference between the streams. A spectral peak occurs at a Strouhal number of 0.2. The results of the simulations demonstrate, that the mean velocity and temperature profiles of the experiments are well captured, whereas the root-mean-square (RMS) temperature fluctuations deviate from the measurements in some cases, in particular when coarse grids are used. In order to find a lower limit for the required spatial resolution three different numerical meshes with a variable number of cells up to 28 × 106 are investigated. The results demonstrate that with a sufficient mesh resolution the velocity and temperature distributions as well as the spectral peak can be simulated with good agreement to the experimental data.

Design of A Chemical Heat Pump System to Utilize Wasted Thermal Energy，Applying Porous Structures

Towards the “Sustainable low CO2 emission world”, the research findings have been applied to extend to explore a new type of thermal energy storage system, employing a concept of chemical heat pumps. For this purpose a new original facilities have been designed and fabricated. Whereas many advantages were found in the new systems; e.g., high speed thermal energy absorption and generation, high cycle thermal fatigue failures must be always a critical problem for structural reliability in future.

Investigation on mixing behavior and heat transfer in a horizontally arranged tee pipe under turbulent mixing of hot and cold fluid

Tee pipes are commonly used in piping systems and multichannel networks in various industries. When two fluids at different temperatures mixing turbulently in a tee pipe, and the mass flow rate ratio Qm,m/Qm,b is large, both the turbulent penetration and the thermal stratification may appear simultaneously in the branch pipe. The temperature fluctuation induced by the turbulent penetration may lead to high-cycle thermal fatigue of the pipe structure, and the thermal stratification may lead to the pipeline distortion and pipeline support damage. This test section has reference meaning in some typical pipelines in nuclear power plant. In this study, the mixing behavior and heat transfer phenomena in a horizontally arranged tee pipe under turbulent mixing of hot and cold fluids are studied by us with the experiment and the numerical simulation based on the CFD software package FLUENT 16.0. Results show that both the length of the turbulent penetration zone “Ltp” and the length of the thermal stratification zone “Lts” tend to increase with the increase of the mass flow rate ratio Qm,m/Qm,b. As the root cause of different mixing behaviors and heat transfer phenomena in the branch pipe is the combined effect of the buoyancy lift and the inertia force. To obtain a complete description of the mixing behavior, numerical simulations are still essential.

Detached eddy simulation of turbulent and thermal mixing in a T-junction

Turbulent thermal mixing is one of the major degradation mechanisms of thermal fatigue, called high cycle thermal fatigue, and a mixing tee has been known as typical component susceptible to high cycle thermal fatigue. From a numerical analysis point of view, accurate prediction of turbulent flow and associated thermal fields in a T-junction is an essential task; that requires computational fluid dynamics (CFD) with advanced turbulence modeling. The detached eddy simulation (DES) model is hybrid turbulence model which combines classical Reynolds Averaged Navier-Stokes (RANS) formulations with elements of large eddy simulation (LES) method. The DES model has a benefit from computational cost point of view, but the studies of its applicability to industrial problems seem to have been conducted relatively insufficiently. Therefore, in this study, transient CFD analysis using the DES model was performed against Vattenfall T-junction test, and the applicability of DES model to turbulent thermal mixing was evaluated by comparing with its experimental data. For the comparison of velocities, the DES results were in good agreement with the experimental data. For the comparison of temperature, the calculated results were generally in good agreement, but at separation region, a large difference of mean temperature was observed. For the locations where the wall temperature variation is large in which the risk of thermal fatigue is expected to be higher, it was seen that the low frequency oscillations are dominant and the energy begins to decrease from ∼4 Hz. In conclusions, it was confirmed that the DES turbulence model has a capability to simulate turbulent thermal mixing phenomenon in a mixing tee and the CFD analysis using that model can provide reliable results for the assessment of the structural integrity of such a piping system.

STRUCTure-based URANS simulations of thermal mixing in T-junctions

Abstract Turbulent mixing of hot and cold streams in T-junction geometries is a critical safety issue for power plants, as temperature fluctuations have the potential to lead to high cycle thermal fatigue failures. Due to strong flow deformation in the mixing region, the time-scale separation assumption is not locally respected, and unsteady Reynolds-averaged Navier-Stokes (URANS) models fail to provide sufficient accuracy in predicting the temperature variations. Turbulence resolving methods such as large eddy simulation (LES) can in contrast provide reliable results, while being computationally overly expensive for industrial application. A STRUCTure-based second-generation URANS (2G-URANS) model was recently proposed at MIT, which aims at locally resolving unsteady flow structures; its applicability was demonstrated on a collection of classic flow tests. In the present work, the performance of the STRUCT model is assessed against low Reynolds number DNS data for a squared section T-junction, produced at the THTLAB (Fukushima et al., 2003). The mean and root mean square of the temperature and velocity predictions from the STRUCT solution are evaluated, confirming consistent predictions to the reference DNS results as well as the high-resolution LES simulations. The STRUCT turbulence model demonstrates LES-like accuracy on a URANS-like computational mesh. Spectral analysis of the velocity and temperature variation is also presented and provides consistent prediction of the frequencies of the large turbulent eddies.

Study on the coolant mixing phenomenon in a 45° T junction based on the thermal-mechanical coupling method

The Emergency Core Cooling System (ECCS) is actuated following Loss of Coolant Accidents (LOCA) to inject coolant into the primary loop through a 45° T junction configuration in advanced nuclear power plants. The T junction would suffer high cycle thermal fatigue due to possible temperature fluctuations in a non-isothermal mixing cross section. In this paper, the feasibility of Computational Fluid Dynamics (CFD) method on the complex mixing phenomenon simulation in a 45° T junction during the injecting process was verified against experimental data. The thermal mixing mechanism of different injection patterns, which was characterized by the MR number, was unveiled. Moreover, the structure stress analysis was performed to investigate the stress distribution features utilizing thermal-mechanical coupling method. The flow patterns of impact jet flow, deflection flow and upper wall jet flow were defined. The structure stresses were concentrated at the junction joint zone under all the three flow patterns. The variations of maximum stress with MR number were achieved. This work provides a guideline of CFD method for the mixing process simulation in a 45° T junction of ECCS and an important basis for the fatigue assessment and safety management in nuclear power plants.

Experimental and numerical study of crack damage under variable amplitude thermal fatigue for compacted graphite iron EN-GJV-450

Fatigue crack under variable amplitude thermal cycles is a common failure in combustion chamber components, proposing great challenges during the temperature reproduction of actual working condition. In this paper, this complicated thermal cycle was realized with pulsed laser experimentally, causing two kinds of damage such as the low cycle thermal fatigue (LCF) and high cycle thermal fatigue (HCF). A numerical model was developed to simulate the temperature, stress and strain under variable amplitude thermal cycles. The results showed that, there was good agreement between the measured temperature curve and the simulated results with different crack parameters. The observed crack depth at different cycles was consistent with the predicted ones. Furthermore, the mechanism of crack evolution under variable amplitude thermal fatigue was discussed. The calculated thermal-structural interaction depth of LCF thermal cycle was found to be larger than the HCF thermal cycle. The effect of LCF thermal loadings was associated with the initiation of major cracks, while the failure related to the superimposed HCF action was the acceleration of crack growth with a surface wedging process. This paper provides comprehensive experimental and numerical insights into the thermal damage process under variable amplitude thermal loading, showing a significant engineering value for failure analysis and design optimization of combustion chamber components.

Development of a spectrum method for modelling fatigue due to thermal mixing

Turbulent mixing of cold and hot fluids can lead to high-cycle thermal fatigue in T-junctions. In this work, a spectrum method for the thermal fatigue modelling was further developed. Estimation of the reference frequency, which determines the frequency range of the temperature spectrum, was considered in particular by utilizing flow mixing data from two T-junctions. Fatigue and crack growth obtained with the method were compared with the sinusoidal (SIN) method and with a computational fluid dynamics (CFD) load. The reference frequency was determined by fitting the model spectrum with temperature spectra obtained from measurements and CFD simulations. A formula for the reference frequency was proposed, which can be used in approximating the frequency also for other flow conditions. The SIN method resulted in over-conservatism in the fatigue and crack growth assessment. Results from the spectrum method agreed quite well with those obtained with the CFD load, showing that the method could result in significant improvement over the SIN method.

Synthesis of a CFD benchmarking exercise for a T-junction with wall

This article reports the CFD benchmark to validate different turbulent modelling approaches for transient heat transfer in the context of high-cycle thermal fatigue due to mixing of hot and cold flow in a T-junction including the wall. This validation exercise has been carried out within the MOTHER project. In the framework of the project, new experiments were performed with a novel measurement sensor allowing the measurements of the fluctuating wall temperature inside the solid in the mixing region between hot and cold water after a T-junction. The tests were performed for two different Reynolds numbers 40,000 and 60,000 and for two different T-junction geometries; a sharp corner and a round corner. The CFD validation study has been performed using five different CFD softwares, namely STAR-CCM+, Code_Saturne, LESOCC2, Fluent and OpenFOAM. In addition, seven different turbulence models i.e. wall resolved LES, wall function LES, VLES, DES, PRNS, URANS, RANS and AHFM (RANS), were used to perform the CFD computations.The validation exercise has shown that LES shows the best agreement with the experimental data followed by hybrid (LES/RANS), URANS and RANS models, respectively. The velocity and the thermal fields in the fluid region are correctly predicted by the proper use of the LES modelling. Whereas, the accurate prediction of the thermal field in the solid requires very long sampling time to achieve statistically converged solution, which of course requires an enormous computational power. Therefore, the statistical convergence of the thermal field in the solid has been found to be one bottleneck in order to accurately predict the temperature fluctuations in the wall and the transient heat transfer. However, measuring the small amplitude temperature fluctuations is also associated with an uncertainty so the disagreement between CFD and measurements (of the order of 10%) can also be attributed, in part, to uncertainties in the measurements.

Thermal mixing of flows in horizontal T-junctions with low branch velocities

High cycle thermal fatigue (HCTF) damage in the vicinity of T-junction piping, where mixing of coolant streams at significant temperature differences occur, is considered to be an important problem in the context of operational safety in nuclear power plants (NPPs). The present study deals with the experimental and numerical investigations of T-junction flow mixing at realistic temperature differences encountered in NPPs. Experiments were carried out at the fluid-structure interaction (FSI) T-junction test facility at the University of Stuttgart. Near-wall thermocouples were used in the mixing zone to record temperature information inside the flow and the structure. A conductivity based wire mesh sensor (WMS) instrumentation designed at the Laboratory of Nuclear Energy Systems at the ETH Zurich for high-pressure high-temperature applications was also used during the measurements to characterize the cross-sectional thermal field in the mixing zone. Aside from experiments, numerical studies were carried out using the large-eddy simulation (LES) turbulence model to gain further insights into the flow mixing behavior and its predictions were validated with measurement data.With a constant mass flow rate ratio (main/branch) of 4:1, thermal mixing tests were carried out at temperature differences (ΔT) between the mixing fluids of 65°C (Case 1) and 143°C (Case 2), respectively. Two distinct flow trends were identified in the mixing region: (i) an unstable stratified flow being subjected to extreme oscillations in case 1 and (ii) a stable stratified flow being subjected to significant buoyancy effects in case 2. Near-wall thermal fluctuations (a factor in thermal fatigue analysis) with highest amplitudes were recorded by the thermocouples located in the vicinity of the stratification layer in both the cases. Frequency analyses of thermal fluctuations using the power spectral density (PSD) method indicates no dominant frequency (spectral peak) in the frequency range identified to be of relevance for HCTF (0.1–10Hz). Instead, the energy of thermal fluctuations were mainly contained in the frequency range of 0.1–2Hz. LES predictions of parameters, viz., mean temperature, thermal fluctuations and its frequency distribution showed good agreement with measurement data.