Channel Temperature Research Articles

Optimizing neural network models for predicting nuclear reactor channel temperature: A study on hyperparameter tuning and performance analysis

This study emphasizes how important accurate prediction of channel temperatures in nuclear reactors is for safety and operational efficiency. While traditional methods require long and complex processes such as kernel modeling and mathematical simulations, artificial neural networks (ANN) provide more efficient predictions by accelerating this process. The superior ability of ANNs to process large data sets is intended to demonstrate that this study will provide a valuable alternative compared to conventional methods and increase the accuracy of reactor temperature predictions. In this study, the training performances of Artificial Neural Network (ANN) developed to determine the nuclear reactor channel temperature with different hyperparameter combinations were analysed. It was conducted several experimental studies to assess the influence of hyperparameters on our model for nuclear reactor parameter data prediction. The training and validation results indicates that learning rate, hidden layer sizes and number have critical effects for the more precisive prediction. It was observed that models with a learning rate of 0.05 and 0.5 achieved successful learning with less fluctuation in training and validation errors. When looking at hidden layer sizes, networks with 32 and 64 neurons performed better than networks with 16 neurons. For the test phase our model can successfully predict data with slight error margin. As a result, we demonstrated that neural networks are a powerful tool in nuclear reactor channel temperature prediction through our proposed model.

First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method

We present a one-dimensional first-principle model for parallel-flow regenerative kilns that accounts for the most important effects. These include the kinetics and thermal effects of the limestone decomposition as well as the heat transfer between the gaseous and solid phases. The model consists of two coupled equation systems for the upper and lower part of the kiln. The results of the model are validated qualitatively and are used to train an artificial neural network that predicts the conversion and the temperature in the crossover channel. The artificial neural network performs very well with values of the root mean squared error that are two to three orders of magnitudes lower than the range covered within the data. Finally, we use a genetic algorithm to optimize the feed mass flows such that the conversion and the fuel efficiency are improved in a Pareto-optimal manner. The results are compared to those of a gradient-based optimization method, which shows the usefulness and validity of the approach with the genetic algorithm.

A parallel and multi-scale probabilistic temporal convolutional neural networks for forecasting the key monitoring parameters of gas turbine

As a crucial equipment in the power industry, gas turbines need effective condition monitoring techniques to maintain safe and reliable operations. Fast yet accurate long-term forecasting of the key monitoring parameters of gas turbine is vital for achieving the overall effective condition monitoring. This however poses challenges in terms of both efficacy and efficiency for conventional time series models like recurrent neural networks (RNN), since they run in a sequential manner. To this end, this paper introduces a novel parallel probabilistic time series prediction model. Particularly, the proposed model leverages the parallelism of temporal convolutional neural network (TCN) and exploits the power of latent space in the Bayesian framework. Besides, a multi-scale feature extraction strategy based on dense connections and a lagged observation strategy are presented to improve the model performance. In the comparative study against state-of-the art competitors on four classical system identification benchmarks, the proposed model significantly reduces the training time, while consistently achieving highly accurate predictions and providing appropriate uncertainty quantification. Thereafter, the proposed model is adopted to build a systematic workflow for the fast yet accurate long-term forecasting of the temperature of blade channel of gas turbine. The comprehensive results again highlight the superiority of the proposed model in terms of both the prediction quality and the training efficiency.

Thermo-neutronic integrated coupling effects on nuclear reactor core calculations

Small Modular Reactors (SMRs) have gained significant attention as the next generation of nuclear reactors due to their unique features, such as improved economic viability and safety. This study focuses on the SMART reactor, the first certified design of an SMR, and investigates various Thermo-Neutronics aspects using an integrated coupling scheme of nuclear codes. The Neutronics cell and core calculations are performed using the DRAGON/DONJON codes, while the COBRA code is employed for thermal-hydraulic calculations. The analysis considers parameters including axial and radial power peaking factors (PPFs), critical heat flux (CHF), minimum departure from nucleate boiling ratio (MDNBR), axial average coolant temperature in hot channel and core, and maximum fuel temperature. These parameters are evaluated using the developed coupling system. Code-to-code verification is conducted to ensure the accuracy of the results, demonstrating good agreement. The coupling approach reveals significant effects compared to stand-alone code modeling, emphasizing the importance of considering the coupling between Neutronics and thermal-hydraulics, especially during the cycle length. This study contributes to the understanding of SMRs, particularly the SMART reactor, by providing insights into key parameters and their interdependencies. The integrated coupling scheme enhances the accuracy of the analysis and highlights the significance of considering coupling effects in the modeling process during the steady state and the cycle length.

Retrieval of total precipitable water from INSAT-3D Imager observations using deep neural network

Total precipitable water (TPW) is a key parameter for monitoring the development of the various weather phenomenon, viz., deep convective systems, thunderstorms, etc. Moreover, various nowcasting applications such as heavy rainfall alerts, cloudbursts, thunderstorms, etc. require high spatio-temporal TPW information, which can be achieved with the satellite-based observations from geostationary platform. Therefore, the present study deals with the estimation of TPW from observations in the water vapour (WV) absorption (6.5–7.0 μm) and thermal infrared (TIR) channels (TIR1 (10.3–11.2 μm); TIR2 (11.5–12.5 μm)) of Imager onboard the third generation Indian National Satellite (INSAT-3D) deployed in a geostationary orbit, using the machine-learning technique. The deep neural network (DNN) technique is utilized here to estimate TPW from INSAT-3D Imager observations over the Indian subcontinent region. Herein, the observations from three channels (WV, TIR1 & TIR2) of INSAT-3D Imager for three years from 2018 to 2020 are collocated with TPW from European Center for Medium range Weather Forecast (ECMWF) reanalysis (ERA5) available at 0.25° uniform spatial resolution to prepare a matchup dataset. The input vector consists of Julian day, geolocation (latitude/longitude), brightness temperatures of WV, TIR1 and TIR2 channels of INSAT-3D Imager, surface emissivity of all three channels and the satellite zenith angles. The ERA5 TPW is the output (predictand) of the DNN. For the training of the DNN, 70 % of the total collocated matchups are selected randomly, and the rest 30 % are used for the testing. The DNN is developed for land and ocean surfaces separately, due to a larger variation in the emissivity over land. The assessment of the developed DNN over both surfaces show the similar statistics. The quality evaluation of the training and testing dataset shows the negligible biases and root-mean-squared error (RMSE) of ∼3.5 mm over the land and ∼4.5 mm over the ocean, respectively, in the predicted TPW when compared with ERA5 TPW. However, the bias (RMSE) in the predicted TPW is observed -0.3 (4.4) mm and 0.4 (4.8) mm, respectively over the land and ocean surfaces with reference to the ERA5 TPW for the independent testing of the developed DNN, which was performed on the observations of INSAT-3D for 2021. Additionally, the comparison with radiosondes’ TPW demonstrates the 6.7 mm RMSE with bias of -0.7 mm for 2021.

Thermal analysis of GaN HEMTs using nongray multi-speed phonon lattice Boltzmann method under Joule heating effect

Gallium Nitride (GaN) high electron mobility transistors (HEMTs) exhibit superior electrical properties for power and radio frequency applications, but performance is compromised by localized Joule heating, increasing channel temperatures. Precise thermal analysis during design is essential for optimizing device architecture and management strategies. Traditional methods like the Fourier heat diffusion equation (HDE) and the phonon lattice Boltzmann method (PLBM) with the D2Q8 scheme inadequately model phonon ballistic transport at high Knudsen numbers. This study introduces a nongray multi-speed PLBM integrated with the drift-diffusion model to analyze electro-thermal processes in GaN HEMTs. Validated through simulations of thermal conductivities in two-dimensional GaN thin films, the approach examines internal temperature rise in GaN HEMTs under different gate voltages, comparing results with HDE and gray BTE models, and emphasizing the need for non-Fourier effects in thermal analysis. It also evaluates the impact of GaN layer thickness on temperature distribution, providing a robust solution for thermal analysis in GaN HEMTs and other field-effect transistors.

Enhancing Sustainable Development: Assessing a Solar Air Heater (SAH) Test Bench through Computational and Experimental Methods

A solar air heater is a device that gathers solar radiation and converts it into heat. The core principle involves air moving through a solar collector, where sunlight naturally increases the air temperature within the collector. The benefit of this technology lies in its affordability and simplicity. The implementation of a solar air heater (SAH) test bench holds significant promise in addressing both global change and sustainable development objectives. The primary goal of this study is to examine the aerodynamic configuration of a novel solar air heater test bench accessible at the Laboratory of Electro-Mechanic Systems (LASEM). This study was carried out using the standard k-ω turbulence model with the use of the ANSYS Fluent 17.0 software. The results indicate that the velocity at the inlet directly influences the velocity fields, temperature, static pressure, and characteristics of turbulence. Furthermore, the numerical findings confirmed that the temperature and velocity profiles in the second channel are in good concordance with the experimental findings in the case of a fan, placed alongside the insulation, operating in a delivery mode. Based on these results, the computational approach is validated. When comparingforced convection to natural convection under identical conditions, there was a notable increase in the energy efficiency, with forced convection showing a significant improvement of approximately 31.8%. Indeed, the range of temperatures reached with the proposed design, is highly beneficial for both industrial and household applications.

LIF Thermometry With A sCMOS Color Camera And Multiple Dyes

We propose a method to perform accurate temperature measurements by means of Laser Induced Fluorescence (LIF). We use a sCMOS color camera and a 2-dye solution based on RuPhen, excited in the blue part of the visible spectrum. By changing the relative concentration of the dyes we can manipulate the color channels temperature sensitivity, which allows us to apply a laser power correction which is robust and less affected by image noise compared to convectional ratiometric approaches. Another advantage is that the overall temperature sensitivity is only partially reduces compared to the one of RuPhen, which is not the case if a ratiometric approach is chosen. The method is demonstrated on a bench-top setup, where temperatures can be precisely controlled. An error analysis shows that an accuracy better than 0.5 ◦ C is possible. The correction method can be applied to other measurement techniques, such as Pressure Sensitive Paints (PSPs).

Ozone production by an He+O2 radio-frequency atmospheric pressure plasma jet driven by tailored voltage waveforms

Atmospheric pressure plasma jets are efficient sources of reactive oxygen and nitrogen species with potential applications in medicine, materials processing, green industry and agriculture. However, selective control over the production of reactive species presents an ongoing challenge and a barrier to the widespread uptake of these devices in applications. This study therefore investigates the production of ozone by a radio-frequency plasma jet driven with tailored voltage waveforms composed of up to five consecutive harmonics, with a fundamental frequency of 13.56 MHz. The plasma is supplied with helium with small admixtures (0.1%–1.0%) of oxygen gas. The ozone density in the far effluent is measured with Fourier transform infrared spectroscopy and the gas temperature in the plasma channel is determined with optical emission spectroscopy. Voltage waveform tailoring is found to enhance the ozone density in the far effluent of the plasma jet in comparison to operation with single-frequency voltage waveforms. Increasing the number of applied harmonics in the driving voltage waveform for a fixed peak-to-peak voltage enhances the ozone density but significantly increases the gas temperature within the plasma channel. Meanwhile, increasing the number of applied harmonics while maintaining a constant RF power deposition allows the density of ozone in the effluent to be increased by up to a factor of 4 relative to single-frequency operation, up to a maximum density of 5.7 ×1014 cm−3, without any significant change to the gas temperature. This work highlights that tailored voltage waveforms can be used to control the density of ozone delivered through the plasma effluent, marking an important step towards realising the potential of these plasmas for applications.

A hybrid solar-driven membrane distillation-assisted liquid desiccant air conditioning system: Mathematical modeling and feasibility analysis

Membrane distillation (MD) is a promising method for liquid desiccant (LD) regeneration as it can mitigate LD carryover and produce freshwater as a by-product. Previous research on MD regeneration was mainly focused on performance evaluation and optimization of the regenerator itself. This paper proposed a hybrid solar-driven direct contact MD (DCMD) regeneration-assisted liquid desiccant air conditioning (LDAC) system for air dehumidification, cooling, and freshwater production. A mathematical model for the DCMD regenerator was first developed by considering both temperature and concentration polarizations. This model was validated against the experimental data in terms of the outlet channel temperature and LD solution concentration in the feed tank with relative deviations of ± 9.8 % and ± 0.5 %, respectively. The DCMD model was further integrated into an LDAC system with a batch-wise operation. To investigate the technical feasibility of the proposed system, a one-week simulation was conducted in a residential house during summer in a tropical climate area of Australia. The results showed that the latent heat load was effectively removed from the process air and the regenerated liquid desiccant solution can meet the dehumidification requirement with a concentration over 30.0 wt%. The dehumidification rate and regeneration rate were at 0.49–1.25 kg/h and 0.95–4.25 kg/h, respectively. Solar energy contributed to 52 %-78 % of the total system thermal energy consumption. Furthermore, this system can produce 11.0–12.8 kg of water daily.

Comparison of Lightning Channel Luminosity Versus Time Profiles in the Infrared and Visible Ranges

AbstractInfrared (IR) luminosity of lightning channel in the 3–5 μm range usually persisted throughout the entire interstroke interval, which is in contrast to the simultaneously recorded visible (0.4–0.8 μm) luminosity that always decayed to an undetectable level prior to a subsequent return stroke pulse. A longer visible luminosity period at the end of flash tended to be associated with a longer IR afterglow period following the decay of visible luminosity (and by inference current) to an undetectable level. At the end of flash, the IR luminosity persisted up to about 1 s, and the median IR afterglow duration was a factor of 10 longer than the median visible luminosity duration. The IR luminosity often exhibited a hump when the visible luminosity was monotonically decaying or undetectable, with the corresponding channel temperature being likely around 3400 K.

Application of BPNN algorithm in thermal-hydraulic analysis of unwrapped LFR core

Due to the complex structure of the LFR fuel rod bundle, refined CFD simulation consumes significant computing resources and time, making it difficult to meet the immediate needs of engineering design and research. This paper introduces a method that integrates the sub-channel level thermal-hydraulic analysis code CorTAF-LBE with the BPNN algorithm to analyze the thermal-hydraulic phenomena within the LFR core. The method has been validated by refined simulation results of the THEADES test section, which indicate that the error is within an acceptable range. The feasibility of its application in LFR fuel assemblies was also evaluated. The flow characteristics and temperature distribution in unwrapped LFR rod bundles are investigated. Due to differences in fuel distribution and flow area, the temperature in the central channel is much higher than that in the side and trapezoidal channels. Three accident conditions, including inlet blockage, center blockage, and outlet blockage, were simulated. The corresponding peak temperatures of the fuel cladding were 670 K, 767 K, and 860 K, respectively, representing an increase of approximately 170 K compared to the nominal conditions. The analysis results effectively demonstrate the 3D temperature distribution of the fluid in the rod bundles, which is significant for reactor design and safety analysis of LFRs.

A novel dielectric barrier discharge ozone generator with excellent microdischarge temperature behavior

In this paper, the electrical characteristics and optical emission spectroscopy of a dielectric barrier discharge ozone generator with water as the grounding electrode are investigated. The gas temperature of the microdischarge channel and at the reactor outlet have also been studied. Results show that the working plasma has a very small effect on the increase in gas temperature at the reactor outlet. At applied power frequency of 5 kHz and applied peak voltage of 7 kV, the microdischarge temperature is obtained as 310 K from N2(C3Πu → B3Πg) spectra ranging from 370-381 nm. In addition, the plasma emission spectra of gas mixtures (95 % O2 + 5 % N2) are investigated and the microdischarge temperature is determined as 309 K with applied power frequency of 5 kHz and applied peak voltage of 8 kV. It is concluded that observed microdischarge temperatures reaches the lowest values reported for filamentary air discharges, capable of promoting ozone production.

Simulation investigation of effects of substrate and thermal boundary resistance on performances of AlGaN/GaN HEMTs

The temperature distributions and thermal resistances of the GaN HEMTs fabricated on different substrates (sapphire, Si, SiC and diamond) with Mo/Au interlayers were calculated and analyzed by numerical simulation. The results show that the GaN HEMT on the diamond substrate exhibits the lowest channel temperature and thermal resistance, and the thermal resistance rises with the increase of the thermal boundary resistance (TBR) for all the GaN HEMTs with the different substrate materials. Meanwhile, the high TBR (2 × 10−7 m2·K/W) severely hinders the heat exchange between the GaN layer and the substrate, which makes it difficult for the heat flux to pass through the barrier. Even diamond with high thermal conductivity can hardly reduce the channel temperature of the device. Therefore, TBR must be reduced so that the heat flux can be dissipated through a high thermal conductivity substrate. In addition, the Mo/Au interlayer generates a lower thermal boundary resistance, which has little effect on the channel temperature, thermal resistance and interfacial temperature discontinuity of GaN HEMTs.

Numerical study on heat transfer deterioration of supercritical CO2 in lattice structure array channel

This study numerically explores the fluid flow and heat transfer features of supercritical carbon dioxide (CO2) in lattice structure array channel. The mitigation mechanism of the miniature cylindrical lattice structure array on heat transfer deterioration (HTD) of supercritical CO2 in vertically upward heated channel is studied. This paper evaluates the effect of several key influential parameters (length, diameter, pitch and number) of cylindrical lattice structure array on fluid flow field involving vortex structures, heat transfer coefficient, buoyancy effect and accelerated effect. The results indicate that the lattice structure can effectively suppress the HTD by generating the vortex structure which promoting the turbulent mixing effect and enhancing the turbulent kinetic energy (TKE) of the fluid. Compared with the smooth channel, the peak wall temperature of the lattice structure channel is reduced by about 50 °C, with a corresponding increase in the heat transfer coefficient of about 140 %. The average heat transfer coefficient of the channel is increased by more than 1/3. Furthermore, by increasing lattice length can reduce flow layer stratification and by increasing lattice diameter can creating a composite vortex, which enhance flow mixing strength. The larger the lattice pitch, the worse the overall suppression effect. A denser lattice arrangement produces more temperature valleys, thereby increasing the heat transfer coefficient. The conclusions in this study could provide the main theory support for security and stability of supercritical CO2 heat exchangers in power system.

Thermal and hydraulic characteristics analysis of horizontal lead-bismuth reactor assembly based on sub-channel analysis code

In this paper, the self-developed subchannel analysis program SACOS-PB was used to analyze the thermal hydraulic characteristics of 127 rods in horizontal lead-bismuth reactor under steady state and typical ocean transient conditions. The results of the steady-state analysis showed that the coolant flow and temperature of the vertical assembly were symmetrically distributed, the coolant flow of the horizontal assembly gradually increased along the gravity direction, the temperature rose first and then fell, and the peak coolant temperature of the cross-sectional channel was about 365 °C. Three typical ocean transient operating conditions, inclined, undulating and swing, were also carried out. The results showed that the maximum temperature of the coolant at the exit of the assembly increased with the increase of the transverse heeling angle and the decrease of the trim angle after the incline motion changes the gravity component. Under the undulating and swing conditions, the coolant hydrothermal parameters fluctuated periodically, and the parameter fluctuation period is 10s in line with the oceanic conditions. In the above transient conditions, the peak coolant temperature at the assembly outlet increases and exceeds 365 °C. Compared with the pitching motion on the Y-axis, the rolling and tumbling motion on the X-axis had a significant effect on the coolant flow rate and temperature distribution. The calculation results can provide support for the analysis study of the safety characteristics of lead-bismuth power units under marine conditions.

Raman Spectroscopy Analysis for Precise Channel Temperature Estimation in AlGaN/GaN HEMT Devices

In recent years, high-electron-mobility GaN HEMTs have demonstrated significant advancements in applications such as power converters and RF amplifiers. Nevertheless, their thermal reliability poses a notable challenge, placing constraints on their power-handling capacities. This study employs micro-Raman spectroscopy to evaluate the localized self-heating-induced channel temperature. The channel temperature, determined using the single phonon modes of GaN HEMT (E2(H) & A1(LO)), exhibits discrepancies and does not align with device temperature values calculated using the SiC phonon peak near the GaN channel. However, by employing both phonon modes of GaN to decouple the combined effects of joule heating and the thermoelastic effect, accurate channel temperature values are obtained, matching well with those obtained from the SiC phonon peak. The agreement between calculated temperatures from phonon modes and those obtained by heating the device from the back side enhances the credibility of the proposed method.

Numerical study on spark characteristics and evolution of plasma jet igniter

In this paper, a compressible spark plasma simulation model with fully coupled electromagnetic, flow, and thermal multi-physics process is developed based on COMSOL, and the evolution of spark properties during the spark plasma development of embedded plasma jet igniter is investigated by combining high-speed ICCD experimental data. The results show that in the early stage of spark plasma discharge, strong electric field distortion occurs in the near cathode electrode area, current density and temperature rise sharply, which develop close to each other and subsequently form spark plasma discharge channels; during the discharge development period, under the continuous Joule heat deposition, the plasma channel temperature rises and volume expands, and the plasma high pressure channel formed has obvious ‘shockwave-like’ pressure interrupted surface with the surrounding environment, and the ‘shockwave-like’ pressure interrupted surface propagates and reflects in the igniter cavity, driving the plasma cluster to move outward. The energy is gradually dissipated as the spark cluster rolls outside the igniter cavity sucking in the surrounding cold air. The energy loss of the spark plasma comes mainly from the heat exchange with the surrounding environment and the partial stay in the igniter cavity of the ignition plasma cluster that fails to participate in the ignition.

Contrastive Analysis of Interferometric Techniques for Small Channel Temperature Measurements

This research employs a state-of-the-art digital interferometric technique to investigate the temperature distribution within a confined rectangular channel, with a hydraulic diameter of 3 mm. The experimental setup incorporates an optical glass channel, with nanofluids (Aluminium oxide) as the test fluid at 0.001% volume concentration. To induce controlled heating, a heater filament is strategically placed along the bottom wall of the channel. Simultaneously, a T-type thermocouple is carefully placed to measure the temperature along the upper wall. Two distinct interferometric methods, namely the Michelson interferometer and the Mach-Zehnder interferometer, are employed to capture the complex details of fringes resulting from the evolving temperature field within the test section. A high-resolution CCD camera is employed to capture these fringes, and sophisticated digital image processing techniques are subsequently applied for in-depth fringe analysis. The culmination of these efforts results in the origin of a comprehensive localized temperature distribution map within the small-sized channel. The obtained temperature profiles are meticulously compared, providing valuable insights into the effectiveness and reliability of the Michelson and Mach-Zehnder interferometric techniques in this specific experimental context. This detailed comparative analysis contributes to the broader understanding of interferometric methods for temperature measurements in confined fluidic systems.

Characteristics of planar buoyant jets and plumes in a turbulent channel crossflow from direct numerical simulations

AbstractThis paper is motivated by an interest in understanding the characteristics of buoyant fluids discharged from the bottom wall of channels, such as encountered during tunnel fires or in river effluent discharge. Direct numerical simulation is used to model the upward release of a planar buoyant jet or plume from the bottom wall of a channel into an incoming turbulent crossflow. The well-studied jet-in-crossflow with only a momentum source is simulated first, and subsequently, fixing the incoming Reynolds number, buoyancy source as heat flux is added alongside varying momentum source, with two cases where only a buoyancy source is present. Appropriate five non-dimensional parameters relevant for this flow are defined, of which three are fixed and two—source to channel momentum ratio and Richardson number—are varied. The changes in turbulence characteristics as the buoyant jet or plume evolves downstream are presented. In all cases with buoyancy, except for the pure jet case, the plume is initially confined to the lower half of the channel before it suddenly lifts to the top half, an effect that occurs at an increasingly smaller downstream distance with increasing buoyancy, and dividing the flow into a near and far field. The distributions of mean and Reynolds stresses in the near and far field of the source are reported, and it is found that the channel flow becomes more turbulent downstream of the source, and further, the turbulent vertical temperature flux switches sign from near to far field owing the a change in the mean temperature gradient sign. From the input parameters and using the integrated temperature equation a reasonable estimate of the far field mean channel temperature can be obtained by a reference temperature based on the heat conservation that includes the convective and diffusive source heat flux. A monotonic behaviour of the back-layering distance is also observed a function of this reference temperature, which was difficult to obtain with the two specified non-dimensional parameters.