Decrease In Maximum Temperature Research Articles

Impact of introducing electric vehicles on ground-level O3 and PM2.5 in the Greater Tokyo Area: yearly trends and the importance of changes in the urban heat island effect

Abstract. Battery electric vehicles (BEVs) are considered a solution for global warming and air pollution, and several countries have announced they will shift to BEVs in the 2030s. Even though previous studies have shown the effects of reducing vehicular emissions on the formation of tropospheric ozone (O3), no studies have evaluated the effect of decreasing anthropogenic heat, which is expected to mitigate urban heat island (UHI) effect, on air quality issues. We used a numerical weather prediction to estimate changes in the UHI effect in the Greater Tokyo Area (GTA) of Japan by introducing BEVs. The results indicated that the introduction of BEVs would lead to a maximum local temperature decrease of 0.25 °C in the GTA. The effects of introducing BEVs on O3 and fine particulate matter (PM2.5) were estimated using a regional chemical transport model. The results indicated that mitigating the UHI effect would lead to a reduction in ground-level O3 formation. This is due to the increased NO titration effect caused by the lowered planetary boundary layer height and due to the degradation of photochemistry related to O3 formation caused by a decrease in temperature and biogenic volatile organic compounds (BVOCs). The mitigation of UHI would result in enhanced particle coagulation, with an increase in ground-level PM2.5. Furthermore, a decrease in BVOC emissions would result in increased PM2.5 owing to enhancement of the OH + SO2 reaction. A total of 175 and 77 annual premature deaths would be prevented from changes in O3 and PM2.5, respectively.

Numerical Study on the Effect of Tunnel Slope on Smoke Exhaust Performance in Metro Tunnels

Utilizing the intermediate air shaft for smoke exhaust is one of the crucial emergency ventilation methods in metro tunnel fires. To study the impact of metro tunnel slope on smoke exhaust performance of intermediate air shaft, this paper employs numerical simulation to conduct research from the following aspects: the longitudinal distribution of ceiling smoke temperature, visibility distribution, smoke layer height, and the smoke exhaust efficiency of intermediate air shaft. The results demonstrate that as the tunnel slope increases, the maximum ceiling temperature decreases, and the visibility at dangerous height increases. The smoke layer height on the downhill side of a sloped tunnel is higher than that of a horizontal tunnel, while the smoke layer height on the uphill side is lower. Under single-side smoke exhaust mode, the smoke exhaust efficiency of the 2# intermediate air shaft rises as the tunnel slope increases. However, under air supply plus smoke exhaust mode, the smoke exhaust efficiency of the 2# intermediate air shaft decreases with the growing tunnel slope.

INVESTIGATION OF PHASE CHANGE MATERIAL WITH/WITHOUT ALUMINIUM PLATE FOR BATTERY THERMAL MANAGEMENT

Concerns about global warming related to carbon emissions increased interest in electric vehicles (EVs). The current EV technology requires development on fast charging and battery lifetime increment, which require strict temperature control. This study investigated the effectiveness of implementing phase change material (PCM) for battery thermal management with/without an aluminum plate. Initially, a 73 Ah NMC pouch cell was discharged in an insulated environment at a 1°C rate to record the behavior of the battery. Then, a PCM pack is inserted into the cell during discharge. Finally, an aluminum plate with 0.5 mm thickness is inserted between the battery and the PCM pack to uncover the effect on the thermal behavior. To reveal the impact of the experiments, temperature measurements are taken from the upper surface (near positive and negative tabs) and bottom surface of the battery. Results show that the maximum temperature decreases, and temperature uniformity increases with PCM (with/without an aluminum plate) relative to the base case. The temperature difference between the two sides of the battery was measured as 4.3°C, 1.1°C, and 1.2°C for the base case, with the PCM pack and the PCM pack and aluminum plate, respectively. Even though the net temperature differences do not reflect the increased temperature homogeneity achieved with the added aluminum plate, the data set is helpful. In the end, the results of these experiments successfully demonstrated that using PCM is helpful in the thermal management of batteries and that using conductive layers can improve the battery’s thermal uniformity.

Three-Dimensional Structural Analysis of Sea Temperature During Typhoon Transit

This study uses the Finite-Volume Community Ocean Model (FVCOM) to simulate the hydrodynamic processes during typhoon “Saola”. The simulation results closely match observed data. Typhoon “Saola” was a major system in the Pacific typhoon season, highlighting the complexity and uncertainty of tropical cyclone dynamics. By analyzing historical sea surface temperature data and the typhoon’s trajectory, the three-dimensional response of sea temperature during typhoon “Saola” was explored. The key findings are as follows: 1. Typhoon passage affects both coastal and deep-sea warming and cooling. Temperature changes are more pronounced near the coast, with the highest warming and cooling occurring within five days after the typhoon. In deep-sea areas, the highest warming occurs within five days, while the lowest cooling occurs within two days. 2. The nearshore water layers respond quickly to the typhoon, while the deep-sea water layers primarily respond in the middle depths, with a delayed effect. 3. In coastal shallow waters, the response is intense, with the maximum temperature increase and decrease occurring near the bottom, reaching 5.26 °C and −5.17 °C, respectively. In deep-sea areas, the response is weaker, with the maximum temperature change occurring near the surface: an increase of 0.49 °C and a decrease of −0.98 °C. The deepest response in coastal waters reaches about 80 m, while in the deep-sea area, it only reaches 50 m due to the thicker mixed layer.

In vivo pharmacokinetic, pharmacodynamic and brain concentration comparison of fentanyl and para-fluorofentanyl in rats

In 2022, para-fluorofentanyl (pFF) rose to the 6th most reported drug and the most reported fentanyl analog in the United States according to the Drug Enforcement Administration (DEA). pFF differs from fentanyl by the addition of a single fluorine group. To date, pFF has not been extensively evaluated in vivo and is frequently seen in combination with fentanyl. In the present study, the pharmacodynamic (PD) and pharmacokinetic (PK) properties and brain region-specific concentrations of pFF were evaluated in male Sprague–Dawley rats and compared to fentanyl. A 300 μg/kg subcutaneous dose of fentanyl or pFF was administered to assess PD and PK parameters as well as brain region concentrations. PD parameters were evaluated via a tail flick test to evaluate analgesia and core body temperature to measure hypothermia, a surrogate marker of overall opioid toxicity. Fentanyl and pFF were found to be equally active at the tested dose in terms of tail flick response with both compounds producing an analgesic response that lasted up to 240 min post-drug treatment. pFF induced a significantly greater hypothermic effect compared to fentanyl with a maximum temperature decrease of −5.6 ℃. Plasma PK parameters (T1/2, AUC, etc.) did not differ between fentanyl and pFF. However, pFF concentrations in the medulla, hippocampus, frontal cortex and striatum were more than two times the fentanyl concentrations. The increase in brain concentrations and greater hypothermic effect suggests that pFF is potentially more dangerous than fentanyl.

Epidemiological Study of Downy Mildew Disease of Opium Poppy

The downy mildew caused by Peronosporaspp is a major disastrous disease of many plant species. The symptoms of downy mildew disease incidence on opium poppy (Papaver somniferum L.) were collected in three years from 2019-20 to 2021-22 for prediction of weather parameters on the progression of downy mildew disease. The downy mildew disease initiation was recorded in the 52nd SMW (10.0%DMI) when the maximum temperature was 19.430C. At 3rd SMW, the maximum temperature dropped 17.330C and DMI reached up to 20.00 percent depicting the progression and spread of downy mildew disease in opium poppy with the decrease of maximum temperature. The maximum disease incidence was recorded 92.53 percent in 10th SMW when maximum and minimum temperature were 29.030C and 13.530C. Regression analysis between dependent variable downy mildew disease incidence Vs. independent variables (viz., rainfall, maximum and minimum temperature and relative humidity) showed that all the weather parameters contributed more than 85 percent variation (R2 = 0.869, 0.957, 0.859) in the downy mildew incidence of opium poppy. One unit change of maximum temperature, minimum temperature (1.00c), maximum and minimum relative humidity (1.0%) might cause to change 0.128, 0.70, 0.117 0.130 units in downy mildew incidence, respectively.

Monthly, Annual and Seasonal Changes in Temperature by Using Mann Kendall and Sen’s Slope Estimator in Karnataka, India

The mean annual minimum temperature during the period 1979-2019 has increased significantly in Eastern dry zone, Southern dry zone and Southern transition zone to a cumulative of total of 0.010°C, 0.013°C and 0.08 °C respectively while it has decreased significantly in Hilly zone with a magnitude of -0.032°C. The annual maximum temperature significantly increased in North eastern transition zone (0.018°C), North eastern dry zone (0.017°C), Northern dry zone (0.014°C), Central dry zone (0.010°C), Eastern dry zone (0.011°C), Southern dry zone (0.013°C), Southern transition zone (0.016°), Northern transition zone (0.016°C) and Coastal zone (0.018°C). The hilly zone experienced a decrease in annual maximum temperature by-0.055°C. Therefore, it is evidential that, Karnataka is getting raised over the years. Researchers should develop crop varieties that are insensitive to temperature changes and scientist should develop packages of practices which will reduce adverse effect of fluctuations in climate parameters on crop productivity.

Optimal design and control strategy for enhanced battery thermal management

The Battery Thermal Management System (BTMS) plays a crucial role in the safety and performance of new energy vehicles. This study proposes an innovative cooling structure design that ingeniously combines the advantages of air cooling, water cooling, and Phase Change Materials (PCMs) to enhance the cooling efficiency of the battery system. Through numerical simulations, the effectiveness of this cooling system was validated and further supported by experimental evidence confirming the accuracy of the simulation results. Subsequently, this research utilized the Response Surface Methodology (RSM) to optimize key parameters of the cooling structure, including the fin height, gap length, and PCM thickness, with their optimal values determined to be 5.20 mm, 17.69 mm, and 3.38 mm, respectively. This parameter optimization work provides precise guidance for the design of battery thermal management systems, contributing to enhanced heat dissipation performance. To further enhance the intelligence of battery thermal management, this study introduced a novel neural network model based on Temporal Convolutional Networks (TCN) and Bidirectional Long Short-Term Memory (BiLSTM) with Multi-Head Attention (MHA). This model is capable of predicting temperature changes during the battery discharge process in real-time with high accuracy. Based on the prediction results, this research designed an efficient control strategy that, compared to a scenario without a control strategy, demonstrated a reduction in energy consumption by 20.87 %, a decrease in maximum temperature by 2.52 K, and a reduction in the maximum temperature difference by 0.05 K. These results not only prove the effectiveness of the control strategy but also provide a new direction for the optimization of battery thermal management systems.

A novel cooling structure of narrow copper plate for small chamfered mold

A three-dimensional mathematical model of a narrow copper plate coupled with the cooling water is established to elucidate the heat transfer and cooling intensity in a small chamfered slab mold with original and redesigned schemes. Then, the precision of the models is validated by measured temperatures of the copper plate in actual production. The water boxes, bolts and thermocouple holes are considered, and the temperature distribution on different longitudinal and transverse planes is discussed. A novel one-hole and one-slot cooling structure is proposed for a small chamfered narrow copper plate. The results show that the Redesign1 scheme with an 8 mm diameter round hole makes the maximum temperature decrease from 673.5 to 644.0 K, reduced by 29.5 K. By analysing temperature uniformity on the hot face at maximum temperature transverse plane and second-row bolts transverse plane, it is found that the standard deviation value in Redesign1 decreases 8 to 10 K, compared with the Original scheme. Besides, it is seen from the Redesign1# scheme that while the water velocity of the round hole water slot can be controlled to be 9.24, 11.24 and 13.24 m s−1, the maximum values of copper plate temperature are reduced to 616.4, 606.9 and 599.3 K, respectively. Compared with the Original scheme values, the maximum temperature difference is 74.2 K. Hence, the cooling uniformity of the chamfered copper plate should be improved by increasing the water velocity of the round hole water slot.

Synergistic performance enhancement of lead-acid battery packs at low- and high-temperature conditions using flexible phase change material sheets

Thermal management of lead-acid batteries includes heat dissipation at high-temperature conditions (similar to other batteries) and thermal insulation at low-temperature conditions due to significant performance deterioration. To address this trader-off, this work proposes a thermal management solution based on flexible phase change materials (PCMs) with moderate thermal conductivity and other favourable properties including high specific heat capacity and high latent heat. A novel type of flexible PCM sheets is prepared with paraffin, olefin block copolymers (OBC) and expanded graphite using the co-melting method. The flexible PCM sheets are attached to a common type of lead-acid battery packs (12 Ah, dimensions of 151 × 98 × 97 mm) and thermal management performance is experimentally investigated at –10 °C and 40 °C as low- and high-temperature conditions, respectively, along with 25 °C as a baseline case for comparison purposes. Thermal properties of the battery packs such as temperature regulation and electric properties including charge/discharge capacities and rates are studied synchronously based on a standard high-performance battery detection facility. The results indicate that at –10 °C condition, the PCM sheet enhances thermal insulation of the battery pack and significantly promotes the service temperature during the charging processes. Compared with a benchmark pack attached with an encapsulated sheet, the charge and discharge capacities of the PCM-attached pack are improved by 3.7% and 5.9%, respectively. At 40 °C condition, phase transition of the PCM sheet restrains the temperature rise of the battery pack, with a maximum temperature decrease of 4.2 °C during the charging processes relative to the benchmark pack, and the temperature of the PCM-attached pack is maintained below 45 °C across 60% of the overall charge period. The overcharge and overdischarge have also been alleviated by 3.2% and 2.8%, respectively, and thus the running stability and service lifespan can be improved. The proposed PCM sheets with preferable thermal properties demonstrate potential to promote performance of lead-acid battery packs and such components are also expected to improve heat dissipation and thermal insulation in similar applications including building energy saving, thermal management of electronic chips and thermal regulation of electronic devices.

Experimental Study on Thermal Runaway Characteristics of High-Nickel Ternary Lithium-Ion Batteries under Normal and Low Pressures

High-nickel (Ni) ternary lithium-ion batteries (LIBs) are widely used in low-pressure environments such as in the aviation industry, but their attribute of high energy density poses significant fire hazards, especially under low pressure where thermal runaway behavior is complex, thus requiring relevant experiments. This study investigates the thermal runaway characteristics of LiNi0.8Mn0.1Co0.1O2 (NCM811) 18650 LIBs at different states of charge (SOCs) (75%, 100%) under various ambient pressures (101 kPa, 80 kPa, 60 kPa, 40 kPa). The results show that, as the pressure is decreased from 101 kPa to 40 kPa, the onset time of thermal runaway is extended by 28.2 s for 75% SOC and by 40.8 s for 100% SOC; accordingly, the onset temperature of thermal runaway increases by 19.3 °C for 75% SOC and by 33.5 °C for 100% SOC; the maximum surface temperature decreases by 70.8 °C for 75% SOC and by 68.2 °C for 100% SOC. The cell mass loss and loss rate slightly decrease with reduced pressure. However, ambient pressure has little impact on the time and temperature of venting as well as the voltage drop time. SEM/EDS analysis verifies that electrolyte evaporates faster under low pressure. Furthermore, the oxygen concentration is lower under low pressure, which consequently leads to a delay in thermal runaway. This study contributes to understanding thermal runaway characteristics of high-Ni ternary LIBs and provides guidance for their safe application in low-pressure aviation environments.

Thermal Runaway Characteristics of Ni-Rich Lithium-Ion Batteries Employing Triphenyl Phosphate-Based Electrolytes

Abstract Enhancing the safety performance of high-energy-density lithium-ion batteries is crucial for their widespread adoption. Herein, a cost-effective and highly efficient electrolyte additive, triphenyl phosphate (TPP), demonstrates flame-retardant properties by scavenging hydrogen radicals in the flame, thereby inhibiting chain reactions and flame propagation to enhance the safety performance of graphite/LiNi0.8Co0.1Mn0.1O2 (Gr/NCM811) pouch cells. The results reveal that the capacity retention of cells without flame retardants, and those with the addition of 1 wt%, 3 wt%, 5 wt%, and 10 wt% TPP is 96.4%, 92.1%, 84.15%, 40.8%, and 12.4% (at 1/2C 300 cycles), respectively. Furthermore, compared to cells without flame retardants, the highest temperature during thermal runaway (TR) decreases by 8.3%, 26.9%, 35.1%, and 38.8% with the addition of 1 wt%, 3 wt%, 5 wt%, and 10 wt% TPP, respectively. Through comprehensive analysis of the impact of flame-retardant additives on battery electrochemical performance and safety, it is determined that the optimal addition amount is 3 wt%. At this level, there are no significant flames during battery abuse, the triggering temperature for TR increases by 26.6 ℃, and the maximum temperature decreases by 157 ℃. Moreover, even after 300 cycles at 1/2C, a capacity of 814.5 mAh is retained, with a capacity retention rate of 84.1%. This study provides valuable insights into mitigating TR in high-energy-density power batteries.

Numerical assessment of hydrothermal and entropy generation characteristics of graphene quantum dots nanofluid in a microchannel heat sink incorporating secondary channels and ribs

Efficient heat dissipation from electronic chips is essential for enhancing their performance and longevity. Significant progress has been achieved through the introduction of nanofluids and microchannel heat sinks. However, there is still a need for nanofluids that demonstrate exceptional thermal properties and stability. Graphene quantum dots nanofluid, an innovative carbon-based coolant with zero-dimensional nanostructures, presents promising features such as excellent chemical stability, surfactant-free preparation, superior thermal properties, and minimal impact on rheological characteristics. This study explores, for the first time, the hydrothermal behavior and entropy generation of graphene quantum dots nanofluid in a microchannel heat sink comprising secondary flow channels and ribs. To this end, a three-dimensional conjugate heat transfer model is built using ANSYS Fluent software, and the governing equations are solved using the finite volume method. The simulations are carried out considering temperature-dependent thermophysical properties under different concentrations ranging from 0 to 0.5 % and Reynolds numbers ranging from 100 to 500. The results reveal that the maximum bottom wall surface temperature decreases by 5.88 K, while the heat transfer coefficient improves by 24.9 % compared to the base fluid. Moreover, the total entropy generation reduces by 14.7 %. On the other hand, the pressure drop increases by 43 %. Overall, the highest increment in Performance Evaluation Criteria is 10.8 % at a Reynolds number of 100 and a concentration of 0.5 %, making this particular condition suitable for practical applications.

Experimental study on a dual synthetic jets liquid cooling device

To address the growing heat dissipation requirements of high heat flux electronic devices, this work presents experimental research on a dual synthetic jets (DSJ) liquid cooling device. The effects of different heat flux, channel inlet flow rates, driving frequencies, and other parameters on the device ability have been explored. The experimental results indicate that the wall temperature increases by increasing the heat flux. Raising the channel inlet flow rate will reduce wall temperature. When DSJ is off, increasing the inlet flow rate from 0.16 L/min to 0.40 L/min results in a maximum temperature decrease of 6.30 °C and a pressure drop increase of 2.20 kPa. There is essentially no change in the pressure drop when DSJ is operating. When the inlet flow rate is 0.16 L/min, the maximum wall temperature at DSJ on is reduced by 6.83 °C compared with DSJ off. The convective heat transfer coefficient was raised by 40.55%. The vibrating diaphragm exhibits better low-frequency characteristics when working underwater. The convective heat transfer coefficient increases by 36.46% when the driving frequency is 20 Hz. Increasing the driving voltage, the device cooling performance increased. By increasing the driving voltage to 240 V, the wall temperature decreased by 6.30 °C, a decrease of 13.82%, and the convective heat transfer coefficient raised by 28.51%. The device overall performance increased by a maximum of 39.55% after DSJ on compared with DSJ off.

Optimization of the PVT performance with various orientations of jets and MFFNN-RSA prediction model for smart buildings

The combined thermal and photovoltaic technology in PV/T systems is considered as a greatly promising technology for smart buildings. Thus, investigations for enhancing the PV/T performance are still proceeding. This research presents an investigation for novel configurations of cooling jets for the PVT system. The linear and circular distribution for the inlet jets considering regular and irregular positioning for all the jets as new cooling configurations are implemented. Moreover, the proposed geometrical configurations are optemized regarding the performance to identify the most suitable configuration that achieves the optimum efficiency and temperature. Furthermore, a novel hybrid ANN model is presented for predicting the performance of the PVT systems. This model combines the multi-feedforward neural network (MFFNN) with an optimization technique called reptile search algorithm (RSA). The proposed model can process the studied parameters to predict the PVT performance parameters (top surface temperature, temperature un-uniformity, outlet temperature, and efficiencies). The proposed MFFNN-RSA model minimized the mean square error to less than 0.4857×10-3. The maximum temperature decrease achieved by the presented configuration reached 60.62K compared to the uncooled case, while the minimum temperature un-uniformity reached 1K and 6K for 400 and 1000 W/m2, respectively. The increase of the ambient temperature found to decrease the temperature un-uniformity in all the cases. The irregular jet with the linear distribution was found to achieve the optimum performance of the overall, thermal, and electrical efficiencies of 63.5%, 49.6%, and 14.25%, respectively. Furthermore, the electricity production cost was reduced by 11.6%, and the yearly CO2 emissions were reduced by 215.3 kg/m2 compared to the normal PV system. The proposed irregular-line distribution of the jets is found to be the best configuration regarding the temperature of the PV model and the overall efficiency considering the pumping losses.

Time Series Analysis: Associations Between Temperature and Primary Care Utilization in Philadelphia, Pennsylvania

IntroductionEarth's temperature has risen by an average of 0.11°Fahrenheit per decade since 1850 and experts predict continued global warming. Studies have shown that exposure to extreme temperatures is associated with adverse health outcomes. Missed primary care visits can lead to incomplete preventive health screenings and unmanaged chronic diseases. This study examines the associations between extreme temperature conditions and primary care utilization among adult Philadelphians. Methods1,048,575 appointments from 91,580 patients age ≥ 18 years enrolled in the study at thirteen university-based outpatient clinics in Philadelphia from January 1, 2009, to December 31, 2019. Statistical analysis was performed from June to December 2023. Data on attended and missed appointments was linked with measures of daily maximum temperature and precipitation, stratified by warm and cold seasons. Sociodemographic variables and associations with chronic disease status were explored. ResultsRates of missed appointments increased by 0.72% for every 1°F decrease in daily maximum temperatures below 39°F and increased by 0.64% for every 1°F increase above 89°F. Individuals≥65 years and those with chronic conditions had stronger associations with an increased rate of missed appointments. ConclusionsTemperature extremes were associated with higher rates of missed primary care appointments. Individuals with chronic diseases were more likely to have missed appointments associated with extreme temperatures. The findings suggest the need for primary care physicians to explore different modes of care delivery to support vulnerable populations, such as making telemedicine during extreme weather events a viable and affordable option.

Effect of oxy-fuel combustion with different O2/CO2 fractions on the pulverized coal combustion mechanism and heat transfer characteristics in rotary kilns: A numerical simulation study

Oxy-fuel combustion combined with carbon capture and storage is the most effective and direct technology to achieve carbon neutrality in cement industry. In this work, numerical simulation was employed to investigate the effects of air combustion and oxy-fuel combustion with different O2/CO2 fractions on the airflow field, temperature field, pulverized coal combustion mechanism, heat transfer characteristics and NOx distribution in rotary kiln. The results show that the airflow field under different conditions has no significant change. When transitioning from the air condition to the oxy-fuel condition, the ignition point of pulverized coal extends backward by approximately 0.2 m. The maximum temperature decreases from 2306 K to 2052 K, and the temperature becomes more uniform. As the oxygen concentration in the primary air increases, both the maximum and average temperatures gradually rise, and the flame length shortens from 25.4 m to 24.16 m. In the rotary kiln, the locations of char oxidation and gasification reactions differ, but these reaction locations remain consistent under different conditions. Under oxy-fuel conditions, the oxidation rate and oxidation proportion of char decrease, while the gasification rate and gasification proportion of char increase, resulting in a shortening of the burnout distance of coal from 34.5 m to 31.3 m. With increasing oxygen concentration in the primary air, the rates of char oxidation and gasification gradually rise, further shortening the burnout distance. The decrease in temperature at the front end of the rotary kiln under oxy-fuel conditions reduces the total heat transfer in the burning zone by 15 %. When the oxygen content of the primary air is 70 %, it ensures stable calcination of clinker. Additionally, under oxy-fuel conditions, the NOx generation is significantly reduced. With the increase of oxygen concentration in the primary air, the NOx concentration at the outlet decreases slightly from 451 ppm to 406 ppm, due to the increase in kiln temperature that favors the reduction of fuel NOx.

Thermodynamic performance and flow structures analysis of supercritical CO2 applied in a regenerative cooling channel mounted with mini-ribs

Supercritical CO2 (SCO2) is regarded as a promising supplementary coolant for traditional regenerative cooling at extremely high flight speed (Ma ≥8) due to its superior heat and mass transfer capability. Using sCO2 as the coolant, mini-ribs is introduced to the rectangular regenerative cooling channel to solve the difficulties in transferring enough heat from near walls to core mainstream at a heat flux of 5 MW/m2 in this paper. With the thermophysical properties near the supercritical point interpolated in the solver, flow structures and heat transfer performance in the cooling channels are obtained using a validated k-ω SST turbulence model. Effects of pitch ratios, channel materials and acceleration and buoyancy effects are also investigated in terms of the local bulk heat transfer coefficients, Fanning friction factors and entropy generation numbers by heat transfer and fluid flow. Overall, the existing of mini-ribs improves the heat transfer coefficient and reduces the entropy number by heat transfer at the cost of the increased fluid friction and the corresponding entropy number. Compared with the smooth channel, the overall enhanced factor can reach 1.73 with an overall thermal performance factor of 1.43 and the maximum wall temperature decreases by 27.57 % in the case of P/e = 10. When the solid channel material has higher thermal conductivity, it leads to a more uniform temperature distribution and lower entropy generation number by heat transfer with the enhanced transverse heat conduction within solid walls which also leads large heat transfer coefficients. Larger accelerations result in stronger heat transfer and larger fluid friction by strengthening the buoyancy effect which is more obvious when the state approach the critical point. This work provides a good reference for the application of supercritical CO2 in a regenerative cooling channel of scramjet engine at extremely high heat flux.

Examining the role of biophysical feedbacks on simulated temperature extremes during the Tinderbox Drought and Black Summer bushfires in southeast Australia

The Tinderbox Drought (2017–2019) was one of the most severe droughts recorded in Australia. The extreme summer air temperatures (>40 °C) combined with drought, contributed to the unprecedented Black Summer bushfires in 2019–20 over southeast Australia. Whilst the temperature extremes were largely driven by synoptic processes, it is important to understand to what extent interactions between land and atmosphere played a role. In this study, we use the WRF-LIS-CABLE land-atmosphere coupled model to examine the impacts of changes in leaf area index (LAI) and albedo by contrasting simulations with climatological and time-varying LAI and albedo. We analyse the impact of these biophysical feedbacks on temperature extremes and fire risk during the Tinderbox Drought and the Black Summer bushfires. Remote-sensing data showed a decrease in LAI (0.1–4.0 m2 m−2) over the three years of the drought along the southeast coast of Australia relative to the long-term climatology, while albedo increased inland (0.02–0.14). These changes in LAI and albedo were accompanied by an overall decrease in daily maximum temperature (Tmax) in the vast majority of interior regions (by ∼0.5 °C) and, in the 2019–20 summer, by a clear increase in Tmax in the coastal regions of up to ∼1 °C. Increased albedo explained most of the decreases in Tmax inland, whereas increases in Tmax along the coasts were mostly associated with LAI declines. The magnitude of the impact of biophysical changes on temperature demonstrates the potential impact that would be missed in simulations that assumed fixed vegetation properties. Finally, we only found a small impact from LAI and albedo changes on the fire risk (as measured by the fuel moisture index) preceding the Black Summer bushfires, suggesting these biophysical feedbacks did not significantly modulate fire risk. Our results have implications for coupled simulations relying on climatological LAI and albedo, including operation weather and seasonal climate predictions.

Numerical simulation, ANN training and predictive analysis of phase change material with 3D printing lattice structures

This study simulated and analysed the performance of phase change material with three lattice structures, i.e., simple cubic, body-centered cubic, and face-centered cubic, at various porosities and heat fluxes. Three parameters are analysed, including the maximum temperature of the heated wall, melting and solidifying times of PCM. The findings suggest that as the porosity rises, the maximum temperature decreases, while the increase in heat flux leads to a higher maximum temperature. Both the melting and solidifying times extend as porosity increases. An artificial neural network trained by the Levenberg-Marquardt algorithm is used to predict these three parameters. The lattice structure type, porosity, and heat flux are established as the input parameters for the network. The ANN predictions demonstrated outstanding performance in estimating these parameters with a minimum MSE of 0.00015 and a maximum R of 0.99899. The trained ANN is used to predict the crucial parameters of PCM with 82% SC, BCC, and FCC lattice structures. An excellent agreement is observed between the ANN predicted results and the simulation outcomes with a maximum relative error of 9.43%.