Layer Temperature Research Articles

THE DEVELOPMENT OF THE RESEARCH OF THERMAL PROCESSES IN MECHANICAL ENGINEERING TECHNOLOGY

A method for calculating the temperature in the surface layer of the work-piece with a blade tool is described, taking into account the volumetric heat source in the cutting zone, on the basis of which it is proposed to calculate the processing errors caused by thermal effects on the cutting tool and the workpiece. The results of calculations of the temperature in the surface layer of the part material are compared when calculating taking into account flat and volumetric heat sources. The peculiarity of the proposed method for determining the temperature in the surface layer of the workpiece is that the physical and mechanical properties of the processed and tool materials, processing modes, dimensions of the workpiece and cutting tool, geometry of the cutting part of the tool are taken into account. The calculations take into account the change in the intensity of volumetric heat flows in the cutting zone according to their height.

Quantifying the Role of Ocean Dynamics in SST Variability across GCMs and Observations

Abstract Midlatitude SSTs forced by mesoscale oceanic processes can affect the large-scale atmosphere, pointing to the ocean's crucial role outside the tropics. Previous studies have shown oceanic mesoscale processes' effect on global and regional climate variability. This study quantifies the local contribution of ocean dynamics to mixed-layer temperature across the globe by directly estimating the ocean heat flux divergence resolved by state-of-the-art ocean reanalysis, eddy-resolving, and eddy-parameterized versions of two US national climate models and indirectly from air-sea flux satellite-based estimates. Our results show that the eddy-resolving climate simulations resolve mixed-layer temperature variances that are larger and closer to those inferred from observations than both their eddy-parameterized counterparts and ECCO over much of the extratropics. The observations and the eddy-resolving models indicate a more significant role of ocean dynamics in the mixed layer temperature variability than the surface fluxes over most extratropics compared to their eddy-parameterized versions. A frequency domain analysis shows that the better-resolved ocean mesoscale and thermal gradients enhance the variance over timescale from two months to thirty years. Results show agreement in the ocean's contribution among satellite-based estimates, ocean reanalysis products, and ocean eddy-resolving simulations. At the same time, differences emerge for ECCO and the eddy-parameterized models, suggesting that surface fluxes account for a larger fraction of the mixed layer temperature variability in most of the extratropics.

Ocean component of the first operational version of Hurricane Analysis and Forecast System: Evaluation of HYbrid Coordinate Ocean Model and hurricane feedback forecasts

The first operational version of the coupled Hurricane Analysis and Forecast System (HAFSv1) launched in 2023 consists of the HYbrid Coordinate Ocean Model (HYCOM) and finite-volume cubed-sphere (FV3) dynamic atmosphere model. This system is a product of efforts involving improvements and updates over a 4-year period (2019–2022) through extensive collaborations between the Environmental Modeling Center at the US National Centers for Environmental Prediction (NCEP) and NOAA Atlantic Oceanography and Meteorology Laboratory. To provide two sets of numerical guidance, the initial operational capability of HAFSv1 was configured to two systems—HFSA and HFSB. In this study, we present in-depth analysis of the forecast skills of the upper ocean that was co-evolved by the HFSA and HFSB. We chose hurricane Laura (2020) as an example to demonstrate the interactions between the storm and oceanic mesoscale features. Comparisons performed with the available in situ observations from gliders as well as Argos and National Data Buoy Center moorings show that the HYCOM simulations have better agreement for weak winds than high winds (greater than Category 2). The skill metrics indicate that the model sea-surface temperature (SST) and mixed layer depth (MLD) have a relatively low correlation. The SST, MLD, mixed layer temperature (MLT), and ocean heat content (OHC) are negatively biased. For high winds, SST and MLT are more negative, while MLD is closer to the observations with improvements of about 8%–19%. The OHC discrepancy is proportional to predicted wind intensity. Contrarily, the mixed layer salinity (MLS) uncertainties are smaller and positive for higher winds, probably owing to the higher MLD. The less-negative bias of MLD for high winds implies that the wind-force mixing is less effective owing to the higher MLD and high buoyancy stability (approx. 1.5–1.7 times) than the observations. The heat budget analysis suggests that the maximum heat loss by hurricane Laura was O(< 3°C per day). The main contributor here is advection, followed by entrainment, which act against or with each other depending on the storm quadrant. We also found relatively large unaccountable heat residuals for the in-storm period, and the residuals notably led the heat tendency, meaning that further improvements of the subscale simulations are warranted. In summary, HYCOM simulations showed no systematic differences forced by either HFSA or HFSB.

The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation

Abstract. Although the quality of weather forecasts in the polar regions is improving, forecast skill there still lags behind lower latitudes. So far there have been relatively few efforts to evaluate processes in numerical weather prediction systems using in situ and remote sensing datasets from meteorological observatories in the terrestrial Arctic and Antarctic compared to the mid-latitudes. Progress has been limited both by the heterogeneous nature of observatory and forecast data and by limited availability of the parameters needed to perform process-oriented evaluation in multi-model forecast archives. The Year of Polar Prediction (YOPP) site Model Inter-comparison Project (YOPPsiteMIP) is addressing this gap by producing merged observatory data files (MODFs) and merged model data files (MMDFs), bringing together observations and forecast data at polar meteorological observatories in a format designed to facilitate process-oriented evaluation. An evaluation of forecast performance was performed at seven Arctic sites, focussing on the first YOPP Special Observing Period in the Northern Hemisphere (NH-SOP1) in February and March 2018. It demonstrated that although the characteristics of forecast skill vary between the different sites and systems, an underestimation in boundary layer temperature variability across models, which goes hand in hand with an inability to capture cold extremes, is a common issue at several sites. It is found that many models tend to underestimate the sensitivity of the 2 m air temperature (T2m) and the surface skin temperature to variations in radiative forcing, and the reasons for this are discussed.

Enhancing PEMEC Efficiency: A synergistic approach using CFD analysis and Machine learning for performance optimization

The proton exchange membrane electrolytic cell (PEMEC) is a clean, pollution-free, and promising device for producing hydrogen from water electrolysis. This paper enhances the electrochemical performance of the PEMEC by developing a comprehensive three-dimensional two-phase non-isothermal heat and mass transfer cell model. An analysis was conducted to study the influence of various operating parameters on the temperature safety and efficiency of the cell. The performance of the latter was optimized by adopting the machine learning technology, which aimed at identifying optimal conditions for improved performance. The obtained results showed that, when the inlet water flow rate and membrane thickness were increased, the average temperature of the anode catalyst layer (A-CL) was decreased by 1.4 K and 2.31 K, respectively. This allowed to improve the safety of the electrolytic cell. However, it would reduce the hydrogen and oxygen mole fraction in the electrolyzer. On the contrary, enhancing the porosity or thickness of the anode gas diffusion layer can increase the average A-CL temperature and decrease the oxygen and hydrogen mole fraction. Therefore, the backpropagation neural network and non-dominated sorting genetic algorithm were used to predict and optimize the performance of the electrolyzer, in order to maximize its temperature safety, electrochemical reaction rate, and hydrogen evolution efficiency as much as possible. The results of this study provide a theoretical foundation for the selection of suitable cell models according to different conditions in engineering applications. It also has an application value in energy saving and sustainable development.

Mean Summer Land Temperatures in the Southern California Coastal Zone: Connections With Ocean Processes

AbstractThe cooling effect of the ocean on the Southern California coastal zone is investigated using a high‐resolution (4‐km) gridded surface meteorological data set (gridMET) of daily maximum temperature (Tmax), with focus on summer mean conditions, taken as the July–August–September (JAS) average. An empirical orthogonal function analysis reveals a coastal mode of JAS temperature covariability, distinct from a more energetic inland mode, that captures Tmax averaged across the Southern California coastal plain. The coastal mode temperature correlates significantly with, and has similar amplitude to, regional sea surface temperature (SST). High (low) summer land and sea surface temperatures, as well as inversion layer temperature differences, are associated with decreases (increases) of northerly coastal wind speeds and coastal cloudiness. The number of extreme heat days on land increases as regional SST increases (4.3 days °C−1), with heat wave days 10 times more likely during peak warm versus cool coastal mode years. The coastal zone was notably warmer and heat wave days peaked during the well documented marine heat wave events of 2014/15 and 2018 off Southern California. The marine variability associated with the coastal mode also has strong expression off the Baja California peninsula, presumably due to strong covarying winds in that area. As in previous studies, higher ocean temperatures are attributed to weaker summer winds, with associated reductions in ocean surface heat loss, coastal upwelling, and cloudiness.

Dislocation half-loop control for optimal V-defect density in GaN-based light emitting diodes

V-defects are morphological defects that typically form on threading dislocations during epitaxial growth of (0001)-oriented GaN layers. A V-defect is a hexagonal pyramid-shaped depression with six {101¯1}-oriented sidewalls. These semipolar sidewalls have a lower polarization barrier than the polarization barriers present between the polar c-plane quantum wells and quantum barriers and can laterally inject carriers directly into quantum wells in GaN-based light emitting diodes (LEDs). This is especially important, as the high polarization field in c-plane GaN is a significant factor in the high forward voltage of GaN LEDs. The optimal V-defect density for efficient lateral carrier injection in a GaN LED (∼109 cm−2) is typically an order of magnitude higher than the threading dislocation density of GaN grown on patterned sapphire substrates (∼108 cm−2). Pure-edge dislocation loops have been known to exist in GaN, and their formation into large V-defects via low-temperature growth with high Si-doping has recently been studied. Here, we develop a method for pure-edge threading dislocation half-loop formation and density control via disilane flow, growth temperature, and thickness of the half-loop generation layer. We also develop a method of forming the threading dislocation half-loops into V-defects of comparable size to those originating from substrate threading dislocations.

Empirical study on the influence of initial relative humidity on wood crib fire behavior in compartment under varied natural ventilation conditions

This empirical study investigates the influence of initial relative humidity (RH) variations (35 % and 95 %) on key fire behavior parameters, specifically focusing on the fully developed stage, occurrences of flashover, and the temperature of the upper gas layer. Wooden cribs weighing 10 kg–40 kg are used as fuel in a compartment with three openings to establish different natural ventilation conditions. The experimental findings reveal that increasing the initial RH within the chamber leads to a delay in the onset of the fire growth phase. Furthermore, it induces two noticeable effects on the fully developed fire stage: a reduction in its duration by up to 50 % and a delay in its initiation by at least 30 s. While heightened initial RH does not prevent flashover, it effectively postpones its occurrence by a minimum of 40 s. Experiments with maximum fuel loads demonstrate negligible effects of increased RH on the maximum temperature, even under varying ventilation conditions. Conversely, lower fuel loads exhibit a significant decline in temperature with rising humidity, notably from 626 °C to 474 °C. The quantitative and qualitative insights derived from this study have considerable potential to inform the development of more effective fire suppression strategies in enclosed compartments.

Fatigue Damage in Asphalt Pavement Based on Axle Load Spectrum and Seasonal Temperature

In asphalt pavement structure design, traffic axle loads and pavement layer temperatures are crucial factors affecting fatigue damage calculations. To investigate the differences in fatigue damage calculations caused by different characterizations of traffic axle loads and temperature, fatigue damage calculations were conducted under equivalent standard axle loads (ESALs), axle load spectra (ALS), constant temperatures, and seasonal temperature variations using the field data from an expressway in Shandong Province, China under seven calculation plans. The results indicated: (1) the annual traffic composition is dominated by vehicle Type 9, with a proportion of about 43% in all the vehicle types, and its load level is also high, with a proportion about of 80% in the heavy load interval at all axle types; (2) The ESALs method underestimates the actual fatigue damage incurred in asphalt pavement by 6.04 times, with an accumulated damage of 2.34 × 10−9 (ESALs), 1.69 × 10−8 (ALS), respectively; (3) The fatigue damage results from a single month with consistent temperature showed similar trends, with an accumulated damage of 1.50 × 10−5, 9.07 × 10−5, respectively; (4) The cumulative fatigue damage calculated using the ALS method across the four seasons, respectively, is 6.51, 5.88, 6.42, and 4.60 times that of the fatigue damage calculated using the ESALs method. Although the ratio of fatigue damage between the two characterizations of traffic axle loads remains consistent, which is 6.04, the fatigue damage calculation that accounts for temperature variations can reveal seasonal trends in fatigue damage development. Based on the axle load spectra and considering temperature variations, fatigue damage calculation will be more closely related to the actual service state of asphalt pavement. These research findings provide insights for estimating asphalt pavement fatigue damage to some extent.

Upper Ocean Responses to Tropical Cyclone Mekunu (2018) in the Arabian Sea

Based on Argo observations and a coupled atmosphere–ocean–wave model, the upper ocean responses to the tropical cyclone (TC) Mekunu (2018) were investigated, and the role of a pre-existing cold eddy in modulating the temperature response to TC Mekunu was quantified by employing numerical experiments. With TC Mekunu’s passage, the mixed layer depth (MLD) on both sides of its track significantly deepened. Moreover, two cold patches (<26 °C) occurred, where the maximum cooling of the mixed layer temperature (MLT) reached 6.62 °C and 6.44 °C. Both the MLD and MLT changes exhibited a notable rightward bias. However, the changes in the mixed layer salinity (MLS) were more complex. At the early stage, the MLS on both sides of the track increased by approximately 0.5 psu. When TC Mekunu made landfall, the MLS change around the track was asymmetric. Significantly, a cold eddy pre-existed where the second cold patch emerged, and this eddy was intensified after TC Mekunu’s passage, with an average sea surface height reduction of approximately 2.7 cm. By employing the stand-alone ocean model, the numerical experimental results demonstrated that the pre-existing cold eddy enhanced TC-induced MLT cooling by an average of approximately 0.41 °C due to steeper temperature stratification at the base of mixed layer. Moreover, heat budget analysis indicated that the pre-existing cold eddy also enhanced subsurface temperature cooling mainly through zonal advection.

Droplet temperature measurement using a fiber Bragg grating

The need to measure droplets temperature with high precision in moderate or extreme environments has driven the development of advanced methods. Here, we report, for the first time, the measurement of droplet temperature using optical fiber-based temperature sensors. Specifically, a fiber Bragg grating sensor was used as a non-invasive technique to determine the temperature behavior of single micro-volumetric pendant droplets. The fiber sensor method, which provides indirect measurements, was validated by experimental and simulation data from the literature, showing good agreement. The temperature measurements rely on monitoring the vapor layer temperature near the droplet at sub-millimeter fiber-to-droplet distances and on determining a coefficient that characterizes the temperature difference between the droplet and the surrounding vapor layer at the liquid–gas interface. We calibrated the method by conducting measurements under various relative humidities and fiber-droplet contact conditions. We found that the coefficient remains constant for a specific distance regardless of the relative humidity or the droplet volume. Furthermore, we observed the minor influences that the environmental relative humidity and droplet content has on the behavior of the recorded temperatures during the short period after droplet generation.

Study of the thermal state of the transformer depending on the operating mode

Accurate analysis and prediction of the transformer's thermal condition depending on the operating mode, for example, in cold winters with a shortage of electricity, allows for effective planning of regular maintenance. In the course of the work, mathematical models were created to analyze the thermal state of the transformer, in particular, models for finding the temperature of the upper layers of oil and the highest temperature on the transformer winding. The data from these mathematical models were verified by comparing them with an already identified analog model. It was determined that the difference between the results is no more than 7 %. It has been established that the thermal state of the transformer is influenced by the ambient temperature much more than by the load. This is due to the fact that without cases of overload and emergencies, the load on the transformer, depending on the season, does not change significantly. It has been determined that the highest time utilization and the highest temperature on the high and low voltage windings are observed in August, which coincides with the peak ambient temperature. The lowest temperature on the windings and the lowest life utilization of the transformer are observed in January, which also correlates with the lowest ambient temperature. It is determined that under such operating conditions, given that the nominal service life of the transformer is 20 years, the actual service life will be approximately 90 years. It was also found that the reduction in service life in winter is 5 times less than in summer. This allows us to predict a reduction in maintenance needs during the cold months and more intensive maintenance in the summer. In addition, such models can predict potential problems and emergencies, which can significantly reduce the risk of unforeseen outages and increase the reliability of power supply. Regular monitoring and analysis of the thermal condition of the transformer makes it possible to respond quickly to changes in operating conditions and make timely maintenance decisions, which helps to optimize costs and increase the efficiency of power grids.

The Effect of Interlayer Delay on the Heat Accumulation, Microstructures, and Properties in Laser Hot Wire Directed Energy Deposition of Ti-6Al-4V Single-Wall.

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process-structure-property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 °C to 263 °C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 °C using a one-dimensional thermal model based on a numerical method allowed us to establish the process-structure-property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

The X-ray rise and fall of the symbiotic recurrent nova system T CrB

ABSTRACT We present the analysis of publicly available NuSTAR, Suzaku, and XMM–Newton observations of the symbiotic recurrent nova T CrB covering the 2006.77–2022.66 yr period. The X-ray spectra are analysed by adopting a model that includes a reflection component produced by the presence of a disc that mimics the accretion disc and the immediate surrounding medium. Our best-fitting model requires this disc to have a radius of 1 au, effective thickness of 0.1 au, averaged column density 10$^{25}$ cm$^{-2}$ and orientation of 50$^{\circ }$ with respect to the line of sight. This disc is about a factor of two larger than recent estimations for the accretion disc and its presence contributes significantly via reflection to the total X-ray flux detected from T CrB, which naturally produces the emission of the 6.4 keV Fe line. Our analysis suggests that the temperature of the boundary layer evolved from 14.8 keV in the steady-state phase (before 2016), to 2.8 keV in the 2017.24 epoch, to finally stabilize to about $\sim$8 keV in the subsequent epochs. These variations in the plasma temperature of the boundary layer are attributed to the evolution of the mass accretion rate ($\dot{M}_\mathrm{acc}$), which is estimated to have an averaged value of $\dot{M}_\mathrm{acc}$ = 2.6$\times \,10^{-8}$ M$_\odot$ yr$^{-1}$ for the current active phase. The presence of emission lines in the XMM–Newton Reflection Grating Spectrometer spectrum of 2017.24 prevents from adopting a blackbody emission model to fit the soft X-ray range. Instead, we use plasma emission models that suggest the presence of adiabatically shocked gas produced by gas velocities of 110–200 km s$^{-1}$, very likely tracing jet-like ejections similar to what is found in other symbiotic systems. The analysis of X-ray and optical data together show that T CrB has a similar evolution as black hole binaries, accreting neutron stars and active galactic nuclei in the hardness–intensity diagram.

Study of the Safety Characteristics of Different Types of Pepper Powder (Capsicum L.)

This research was aimed at comparing the fire characteristics of different types of pepper in the context of explosion prevention. The following characteristics were studied: explosion pressure Pmax and Kst at selected concentrations, ignition temperature of the deposited dust layer from the hot surface, and minimum ignition energy. The comparison of the chemical properties of the used types of pepper was performed using TG/DSC. The results of the measurements suggest that different types of peppers exhibit different explosion characteristics. Each sample reached the maximum value of the explosion pressure and rate of pressure rise at different concentrations. The volume of the explosion chamber used also influenced the explosion characteristics. It is a consequence of the fact that the explosion characteristics strongly depend on the mechanism of action of a particular igniter. The minimum effect on the safety characteristics was observed when measuring the minimum ignition energy and the minimum ignition temperature of the dust layer from the hot surface. The results of the measurements suggest that different types of peppers exhibit different explosion characteristics. This information should then be considered in explosion prevention.

Responses of cold eddies to Typhoon Soulik (2013) off northeastern Taiwan Island

By using multisource reanalysis datasets, satellite data, etc., the influences of Typhoon Soulik on the upper ocean of two cold eddies off northeastern Taiwan Island (hereafter referred to as the P-Cold Eddy and D-Cold Eddy), which are distributed around Pengjia Islet and northeastern Diaoyu Island, respectively, were investigated. The results showed that the P-Cold Eddy was strengthened, and the D-Cold Eddy, which was previously invisible in the surface layer, began to appear. The seawater temperatures in the upper mixed layer of the two cold eddies decreased the most on 13 July, with the sea surface temperatures (SSTs) decreasing by 1.16 °C and 0.97 °C and the mixed layer temperatures decreasing by 1.23 °C and 1.06 °C, respectively. The upper ocean cooling of the P-Cold Eddy was mainly caused by upwelling, whose formation was related to the climb of more Kuroshio subsurface cold water northward forced by the typhoon. The upwelling of the D-Cold Eddy was weak, and the warming effect of the heat pump could be observed at the bottom of its mixed layer. The process of cooling and increasing salinity in the mixed layer of the D-Cold Eddy was mainly associated with the inflow of the upper cooler and saltier seawater from the P-Cold Eddy. The air–sea exchange term was not the main factor in the cooling of the seawater in the mixed layer during the forced stage, but it became dominant during the relaxation stage, and the latent heat flux (QLH) contributed significantly to its change.

Integrating Machine Learning for Improved Prediction of Temperature and Moisture in Pavement Granular Layers

Abstract Pavement temperature and moisture content within the base and subgrade layers affect the load-bearing capacity of the pavement and dominate the pavement performance in cold regions. Accurately predicting pavement temperature and moisture content can improve pavement design and management. Conventional approaches, including numerical and statistical models, have been implemented to predict pavement temperature and soil moisture content. However, they have weaknesses, such as being only suitable for warm regions or only for predicting pavement temperature within the asphalt layer. Furthermore, none of them can simultaneously predict the pavement temperature and moisture content. To address this issue, data collected from an instrumented test road in Alberta, Canada, were used to train a model to predict the daily average pavement temperature and moisture content at various depths through three parameters, namely depth, day of the year, and air temperature. The MATLAB toolbox, Neural Net Fitting, was used, and the performance of three built-in algorithms, Levenberg–Marquardt, Bayesian regularization, and Scaled conjugate gradient backpropagation, was compared. The model with Bayesian regularization showed the highest accuracy, with an R2 value of 0.99 and a root mean square error (RMSE) of 1.49°C for pavement temperature prediction, and an R2 value of 0.95 and an RMSE of 0.025 m3/m3 for moisture content prediction. The model developed in this research is the first to simultaneously estimate pavement temperature and moisture content, so its performance was separately compared with two existing models in the literature. The artificial neural network (ANN) model shows higher accuracy than the two existing models, so it was found that the ANN could be a robust method for pavement temperature and moisture content prediction at various depths.

Local augmentation of phonon transport at GaInN/GaN heterointerface by introducing a graded variation of InN mole fraction

The pump and probe technique in Raman spectroscopy of the E2 (high) mode is exploited to uncover the enhancing factor of the phonon transport across Ga1−xInxN/GaN interfaces. Two samples are investigated: one with a uniform x of 0.09 and another one with a graded variation in x from 0.17 to 0 along the depth direction. Lateral phonon transport is obtained by scanning the 532-nm probing laser from the irradiation position of the 325-nm heating laser. No difference in the lateral diffusion length is observed between the two samples, while the transport probability across the interface is higher for the sample with the graded variation in x than the sample with the uniform x of 0.09. The microscopic images of the decrease in the mode energy or the increase in temperature of the GaN layer reveal that the local phonon transport across the heterointerface is enhanced in regions with low differences in the phonon mode energy between the GaN and GaInN rather than the difference in crystal quality.

CFD simulation of thermal stratification and mixing in a Nordic BWR pressure suppression pool

Boiling Water Reactor (BWR) employs the Pressure Suppression Pool (PSP) as a heat sink to prevent overpressure of the reactor vessel and containment. Steam can be injected into the PSP through spargers in normal and accident conditions and through blowdown pipes in case of a loss of coolant accident (LOCA). There is a safety limit on the maximum PSP temperature at which such steam injection might cause dynamic loads on the containment structures. The performance of the pool can be affected if thermal stratification is developed when temperature of the hot layer grows rapidly while cold layer remains inactive. Simulation of pool behavior during realistic accident scenarios requires validated models that can sufficiently address the interaction between phenomena, safety systems and operational procedures. Direct modeling of steam injection into a water pool in long-term transients is computationally expensive due to the need to resolve simultaneously the smallest space and time scales of individual steam bubbles and the scales of the whole PSP. To enable PSP analysis for practical purposes, Effective Heat source and Effective Momentum source (EHS/EMS) models have been proposed that avoid the need to resolve steam-water interface. This paper aims to implement mechanistic approaches previously developed by authors for the simulation of transient thermal stratification and mixing phenomena induced by steam injection through spargers in a Nordic BWR PSP. The latest version of the EHS/EMS models using the ‘Unit cell’ approach has been validated against integral effect pool tests and applied to plant simulations. Several scenarios with boundary conditions corresponding to postulated accident sequences were simulated to investigate the possibility of stratification development and the effects of activation of different systems (e.g., blowdown pipes, high momentum nozzle) on the pool behavior.

Impacts of synoptic weather patterns on Hefei's ozone in warm season and analysis of transport pathways during extreme pollution events

Extreme ozone pollution events (EOPEs) are associated with synoptic weather patterns (SWPs) and pose severe health and ecological risks. However, a systematic investigation of the meteorological causes, transport pathways, and source contributions to historical EOPEs is still lacking. In this paper, the K-means clustering method is applied to identify six dominant SWPs during the warm season in the Yangtze River Delta (YRD) region from 2016 to 2022. It provides an integrated analysis of the meteorological factors affecting ozone pollution in Hefei under different SWPs. Using the WRF-FLEXPART model, the transport pathways (TPPs) and geographical sources of the near-surface air masses in Hefei during EOPEs are investigated. The results reveal that Hefei experienced the highest ozone concentration (134.77 ± 42.82 µg/m³), exceedance frequency (46 days (23.23 %)), and proportion of EOPEs (21 instances, 47.7 %) under the control of peripheral subsidence of typhoon (Type 5). Regional southeast winds correlated with the ozone pollution in Hefei. During EOPEs, a high boundary layer height, solar radiation, and temperature; low humidity and cloud cover; and pronounced subsidence airflow occurred over Hefei and the broader YRD region. The East-South (E_S) patterns exhibited the highest frequency (28 instances, 65.11 %). Regarding the TPPs and geographical sources of the near-surface air masses during historical EOPEs. The YRD was the main source for land-originating air masses under E_S patterns (50.28 %), with Hefei, southern Anhui, southern Jiangsu, and northern Zhejiang being key contributors. These findings can help improve ozone pollution early warning and control mechanisms at urban and regional scales.