Temperature Curves Research Articles

Project Report: Thermal Performance of FIRSTLIFE House

The paper deals with selected thermal properties of a small building that was built during the international student competition Solar Decathlon 2021/2022 and is now part of the Living Lab in Wuppertal. It summarizes the essential information about the overall design of this wooden building with construction and technologies corresponding to the passive building standard. Built-in sensors and other equipment enable long-term monitoring of thermal parameters. Part of the information comes from the building operation control system. The thermal transmittance value for the perimeter wall matches calculated expectation well, even from a short period of time and not at an achievable perfectly steady state boundary condition. The (positive) difference between the calculated values and the measured ones did not exceed 0.015 W/(m2K). It was proven that even for such a small building with a very small heat demand, the heat transfer coefficient can be estimated alternatively from a co-heating test (measured electricity power for a fan heater) and from energy delivered to underfloor heating (calorimeter in heating system). Differences among both measurement types and calculation matched in the range ± 10%. In the last section, the dynamic response test is briefly described. The measured indoor air temperature curves under periodic dynamic loads (use of fan heater) are compared with the simulation results. The simulation model working with lumped parameters for each element of the building envelope was able to replicate the measured situation well, while its use does not require special knowledge of the user. In the studied case, the differences between measured and simulated air temperatures were less than 1 Kelvin if the first two to three days of the test period are ignored due to large thermal inertia. Finally, the measurement campaign program for the next period is outlined.

Simulations of Cryogenic Line Chilldown with Advanced Subgrid Wall Boiling Models

A mesoscale model for boiling processes in water was adapted for cryogens and demonstrated for chilldown of propellant transfer lines in both liquid nitrogen and hydrogen. The subgrid boiling model accurately captures the contributions to heat transfer from the generation of bubble nuclei, growth, and interaction of the bubbles in the microlayer as well as quenching of the boiling surface following bubble departure. It was adapted for cryogenic fluids using thermodynamic scaling concepts, considering nondimensional pressures and temperatures that are scaled by the corresponding critical values for the fluid. The boiling model was demonstrated for line chilldown in liquid nitrogen. The predicted wall temperature at which quenching occurs was close to the test data for liquid nitrogen, while the slope of the temperature curve after quenching is initiated shows a steeper variation than the test data. Simulations were also performed for liquid hydrogen. Chilldown times in liquid hydrogen are much more rapid due to higher heat transfer in the film boiling regime, and accurately modeling the impact of turbulent heat transfer was found to be important. Furthermore, due to the much colder fluid temperatures in liquid hydrogen, it is critical to model the variable thermal properties of the solid material.

A Physics Informed Neural Network for Solving the Inverse Heat Transfer Problem in Gas Turbine Rotating Cavities

Abstract Recently, Physics-Informed Neural Networks have displayed great potential in delivering swift and accurate solutions for inverse problems. Here, a Physics-Informed Neural Network (PINN) was used to solve the inverse heat conduction problem in the rotating cavities of a aeroengine high-pressure compressor internal air system. The neural network was designed to receive experimentally captured radially distributed temperature profiles as inputs and predict the associated surface heat fluxes. The correctness of these predicted heat fluxes are assessed by numerically solving the direct heat conduction equation using a 2D Finite-Element model, thereby recovering the original temperature profiles. A comparative analysis is conducted between the predicted temperature profiles and the initial inputs. The physics informed neural network is trained using noise free synthetic data, created from a range of radial temperature curve fit coefficients, and subsequently tested on noisy experimental data at engine representative conditions. The predicted temperature values exhibit some good agreement with their respective actual counterparts. Furthermore, the sensitivity of model hyperparameters are explored to showcase the capability of the proposed approach. The results show that Physics- Informed Neural Networks exhibit reduced susceptibility to experimental uncertainties when addressing inverse problems, in contrast to inverse solution methods, and offer a possible new approach for analysis of experimental data if trained on a sufficiently large dataset.

Optimization of chemical engineering control for large-scale alkaline electrolysis systems based on renewable energy sources

In the context of renewable energy, dynamic control is crucial for large-scale alkaline water electrolysis systems. Under traditional Proportional-Integral-Derivative (PID) control, the system's temperature and impurity levels may exceed safe limits during sudden load changes, compromising system safety. Therefore, this study proposes a control strategy based on mathematical models of system temperature and impurities, including Model Predictive Control (MPC) for temperature and Optimal Curve Tracking (OCT) for impurities. The MPC controller offsets the disturbances in temperature caused by current fluctuations through state prediction, while the OCT controller ensures that impurity levels remain within safe limits. Real-time application of these control strategies is achieved through MATLAB-PLC communication, validating controller performance. Experimental results show that the MPC controller exhibits excellent dynamic response and stability in controlling the stack temperature, with a maximum temperature peak deviation of only 2.9 K and a temperature fluctuation range of 5.9 K. This represents a reduction of 1.6 K in peak deviation compared to traditional PID controllers and significantly decreases the temperature fluctuation range. The OCT controller also demonstrates good safety and stability in controlling hydrogen to oxygen (HTO) impurity levels, consistently maintaining the HTO content at the set upper limit of 1.5%, thereby expanding the safe operational range of the system and reducing the need for frequent adjustments to the system setpoints.

Optimization of batch cooling crystallization systems considering crystal growth, nucleation and dissolution. Part I: Simulation

Optimal control of batch crystallization systems is still a focus and hot topic in the field of industrial crystallization, which seriously affects the consistency of batch product quality. In this paper, a new method with a new objective function and improved optimization algorithm was proposed for optimization of crystal size distribution (CSD) in case of fine crystals occurrence. The new objective function was developed with better margin metric and weighting technique to minimize fine crystal mass, meanwhile, a newly constructed sinusoidal weight function was introduced to improve the particle swarm optimization (PSO) algorithm. A precise control of CSD with suppressed numerical discrepancy caused by fine crystals removal was developed by combining seed recipe and temperature-swing. In addition, the effects of temperature curve segments on CSD during process optimization were systematically investigated to achieve optimal results. Two typical batch cooling crystallization systems were used to verify the effectiveness of the proposed method in controlling product CSD while minimizing fine crystal mass. Results demonstrated that the desired product CSD can be achieved with minor errors while the fine crystals could be shrunk to be negligible, i.e., the fine crystal mass and number can be reduced by over 90%. This work has an important guiding significance for the removal of fine crystals in industrial crystallization processes, especially when only operational optimization rather than equipment updating is considered.

Thermal Cycling Behavior of Aged FeNiCoAlTiNb Cold-Rolled Shape Memory Alloys

Fe–Ni–Co–Al-based systems have attracted a lot of interest due to their large recoverable strain. In this study, the microstructure and thermal cycling behaviors of Fe41Ni28Co17Al11.5Ti1.25Nb1.25 (at.%) 98.5% cold-rolled alloys after annealing treatment at 1277 °C for 1 h, followed by aging for 48 h at 600 °C, were investigated. From the electron backscatter diffraction results, we see that the texture intensity increased from 9.4 to 16.5 mud and the average grain size increased from 300 to 400 μm as the annealing time increased from 0.5 h to 1 h. The hardness results for different aging heat treatment conditions show the maximum value was reached for samples aged at 600 °C for 48 h (peak aging condition). The orientation distribution functions (ODFs) displayed by Goss, brass, and copper were the main textural features in the FeNiCoAlTiNb cold-rolled alloy. After annealing, strong Goss and brass textures were formed. The transmission electron microscopy (TEM) results show that the precipitate size was ~10 nm. The X-ray diffraction (XRD) results show a strong peak in the (111) and (200) planes of the austenite (⁠⁠γ, FCC) structure for the annealed sample. After aging, a new peak in the (111) plane of the precipitate (⁠⁠γ′, L12) structure emerged, and the peak intensity of austenite (⁠⁠γ, FCC) decreased. The magnetization–temperature curves of the aged sample show that both the magnetization and transformation temperature increased with the increasing magnetic fields. The shape memory properties show a fully recoverable strain of up to 2% at 400 MPa stress produced in the three-point bending test. However, the experimental recoverable strain values were lower than the theoretical values, possibly due to the fact that the volume fraction of the low-angle grain boundary (LABs) was small compared to the reported values (60%), and it was insufficient to suppress the beta phases. The beta phases made the grain boundaries brittle and deteriorated the ductility. On the fracture surface of samples after the three-point bending test, the fracture spread along the grain boundary, and the cross-section microstructural results show that the faces of the grain boundary were smooth, indicating that the grain boundary was brittle with an intergranular fracture.

A simplified methodology to determine the latent heat of macroencapsulated phase change materials for building envelope applications

Incorporating macroencapsulated phase change materials (PCMs) in building envelopes is a strategy to reduce energy consumption. Current characterization methods focus on small quantities of PCM alone, even if it was demonstrated that they are not representative of the thermal behavior of macroencapsulated PCMs, and rely on highly specific equipment. This work proposes a novel methodology to determine the latent heat of whole macroencapsulated PCMs for building envelope applications using only temperature measurements. This method takes into account the greater quantity of PCM and the capsule material, unlike previous works, while it simplifies the necessary equipment. To develop the predictive model, a wide set of PCM panels was subjected to controlled temperature variations of 0.5 °C/h and 1 °C/h employing an insulated hotbox connected to a climatic module. Transient surface temperature and heat flux were measured. Experimental results demonstrated that not only heat flux measurements, but also temperature can be used to identify the beginning and end of the phase change process. The experimental results were then divided into a training and validation dataset. The training dataset was used to build the predictive model that correlates the area under the heat flux curve to that enclosed by the temperature curve during phase transitions. The model was validated with the remaining experimental data and optimized to assess the influence of temperature variation rate and phase change processes (melting and solidification). We found that the quotient of the heat flux area over the temperature area is 20.5 W/m2·K. Based on this, we identified that the latent heat can be accurately estimated using only temperature data, with an average error of less than 6 %. This methodology is simple but efficient requiring only thermocouples, and no other sophisticated instrumentation. The proposed model predicts the thermal response of macroencapsulated PCM with robustness, versatility, and accuracy (R2 value above 0.95). The trained empirical model applies to other macroencapsulated PCMs, contributing to the effective deployment of PCM-based thermal storage in buildings. Numerical models of envelopes with macroencapsulated PCMs will benefit from the results presented in this work, since the presented model determines the latent heat of whole PCM macrocapsules, unlike previous studies where only small quantities of PCM alone were analyzed.

Study of Li2O reduction in mould slag for continuous casting of low-carbon steel slab

The addition of Li2O increases production costs for continuous casting, despite its enhancement of the melting and flow properties of mould slag. Initially, laboratory research focused on assessing the individual impacts of Li2O, F, Na2O and Al2O3 on the viscosity and melting temperature of the slag, using a basicity of 0.95. Subsequently, four stages of industrial testing were conducted to optimise the slag, evaluating parameters such as temperature and friction force curves of the mould copper plate thermocouple, steel slag consumption per ton and strand surface quality. The optimised slag achieved a basicity of 0.98, a viscosity of 0.29 Pa·s and a melting temperature of 1115 °C, meeting all performance requirements for low-carbon steel mould slag. Compared to the original flux, the mass percentage of Li2O decreased significantly from 1.54 to 0 wt-%, while Na2O increased from 2.36 to 7.35 wt-%, and Al2O3 decreased from 7.28 to 3.49 wt-%. The operation of the optimised flux remained stable, with smooth fluctuations observed in the mould copper plate thermocouple temperature and friction force curves. These research findings hold significant reference and practical value for further development and application.

Study on the characteristics of acoustic-thermal precursors of destabilization damage in coal-rock combination bodies with different proportions

The instability and failure processes of coal-rock combinations are accompanied by the release of acoustic emission (AE) and infrared radiation (IR) signals. To investigate the characteristics of AE and IR signals during the failure process in coal-rock combinations with different ratios, and to analyze the effectiveness and applicability of the monitoring methods for these two signals in various specimen ratios. In this paper, the uniaxial compression tests were conducted on seven coal-rock combinations with different ratios by using the rock mechanics loading system and the cooperative monitoring platform of infrared and acoustic emission. The results show that (1) the AE counts for failure precursors in coal-rock combinations are positively correlated with the coal-rock ratio, whereas the AE peak counts are negatively correlated. Moreover, as the coal-rock ratio decreases, the slope of the cumulative AE count curve during the peak failure stage approaches 1. (2) During the elastic and yield stages, the maximum infrared radiation temperature (MIRT) curve fluctuates, and just before peak failure, the curve displays a distinctive “V” shape. This “V” shape becomes more pronounced as the coal-rock ratio decreases. (3) In the monitoring of damage precursors of coal-rock combinations, when the ratio of coal to rock is 1:3 or less, IR monitoring is better than AE monitoring. Conversely, when the ratio of coal to rock is greater than 1:3, AE monitoring is more suitable. Consequently, the combined monitoring of AE and IR signals can increase the reliability and precision of early warning signals for coal-rock assemblage damage precursors.

An efficient state-of-health estimation method for lithium-ion batteries based on feature-importance ranking strategy and hybrid kernel extreme learning machine algorithm

The safe and reliable operation of battery systems depends critically on accurately and dependably estimating the state of health (SOH) of lithium-ion batteries (LIBs). However, accurate prediction of SOH still needs improvement due to the complex battery aging mechanism. This paper introduces a hybrid kernel extremum learning machine (HKELM) for estimating battery SOH. To improve estimation accuracy, we enhance the standard dung beetle optimization algorithm (DBO) with a new initialized population, adaptive weights method, and improved population diversification. We then use the enhanced IDBO algorithm to optimize the parameters of HKELM. This study examines two distinct anode types of LIBs from NASA and Oxford datasets. Fifty significant features are extracted from charging voltage, current, temperature, and incremental capacity (IC) curves. The importance indices of these features are then computed using statistical analyses, including Pearson's correlation coefficient and Spearman's rank correlation coefficient, followed by optimal ranking. The optimal number of final features is determined by comparing various combinations of high-level features, thus reducing model complexity and improving estimation accuracy. This paper proposes the IDBO-HKELM algorithm for SOH estimation. Compared to other methods, the algorithm shows superior estimation performance and anti-interference capability. Both B0007 and Cell8 estimate SOH with MAE < 0.15, RMSE <0.2, and R2 > 99.9 %. Experimental results demonstrate the robustness of the proposed method, achieving accurate and noise-immune SOH estimation.

Performance of RC beams strengthened using NSM FRP and cement based adhesives after exposure to elevated temperatures

A popular method for strengthening of reinforced concrete (RC) structures is the use of carbon fiber reinforced polymers (CFRP) bonded to the structural elements using the near surface mounted (NSM) techniques. While this method possesses many advantages, poor fire resistance as a result of the low glass transition temperatures (TG) of organic resins remains a significant drawback. Replacement of organic resins with cement based adhesives (CBA) could potentially improve the fire performance of NSM FRP systems and reduce the amount of insulation required to achieve the required fire endurance period. This paper presents an experimental program consisting of fifteen RC beams strengthened in flexure using NSM FRP bonded using CBA and subjected to the standard fire time temperature curve up to a target temperature of 600 °C. Twelve of the beams were strengthened using NSM-FRP laminates and bars including both smooth and rough FRP laminates and the remaining three specimens acted as control beams. Further, the use of plasterboard was explored as fire protection to further increase the residual strength of the specimens after heating. Results showed that the reinforced concrete beams strengthened with NSM CFRP retained 82 % to 61 % of their unheated strengthened ultimate load after heat exposure. This was a result of the superior performance of the cement-based adhesive at high temperature and the fire protection provided to the CFRP through embedment in the grooves. Moreover, the use of plasterboard as fire protection decreased the CFRP temperature by 42–24 %. The insulated beams behaved similarly to strengthened beams prior to fire exposure.

Design and verification of high-precision dynamic temperature control system

In view of the fact that the current temperature environment simulation equipment is difficult to realize the temperature offset test of temperature-sensitive scientific payloads in deep space exploration, a high-precision dynamic temperature control system was designed and built, and then tested and verified. The system uses liquid nitrogen cold plate as the cold source, and realizes high-precision static 300 mm × 300 mm and dynamic temperature control on the contact surface of the payload through electric heating temperature control, heat pipe heat transfer and firmware heat conduction. The test results show that in the case of scientific payload-10 ∘C ∼ 45 ∘CWithin the working temperature range, the contact surface between the temperature control system and the scientificpayload can achieve high-precision temperature stability control, and the temperature fluctuation is better than ± 0.001 ∘C; at the same time, it can also realize ± 0.05 ∘C/1000 s ∼ 1 ∘C/1000 slinear control of the heating and cooling rate of the scientific payload contact surface. Compared with the temperature curve set by the temperature offset test, the maximum errors of the whole temperaturetracking are 0.003 ∘C and respectively 0.04 ∘C . The established temperature control system has the ability of high-precision temperature dynamic offset test, and has considerable application prospects in tasks such as deep space exploration payload development test.

Estimation and research of the temperature field models of large space spherical mesh shell structures under localized fire

This paper firstly investigated fire dynamics characteristics and the temperature field distributions of large space spherical mesh shell (SMS) structures under localized fire in FDS, and divided the temperature fields into plume region, smoke accumulation region and ceiling jet region. Based on the classical axisymmetric plume model, the predictive models for the steady-state and transient temperature fields in different fire regions for large space SMS structures were proposed in this paper. Thereafter, the proposed temperature models were compared with the simulated results and experimental test results by other scholars, and they were in good agreement. In order to further discover the realistic fire development progress and temperature distribution of large space fire, and validate the proposed temperature field models, this paper designed and conducted three full-scale large space fire tests (Test-1 ∼ Test-3) with different fire source powers in a large space building. Results showed that temperature fields of large space fires could be consisted of near-fire region (Flame region) and far-fire region (Plume region and Ceiling jet region). The steady-state fire source powers were tested for 443 kW, 886 kW, 1090 kW for Test-1, Test-2 and Test-3, respectively, while their maximum temperatures of the roof reached 75 °C, 105 °C and 120 °C. Based on McCaffrey plume model, we further proposed the transient temperature model in flame region for large space structures, and its accuracy was verified by the test results. Moreover, the proposed steady-state and transient temperature fields for large space SMS structures were compared with the tested temperature field data, and the tested and predicted temperature curves were generally in good agreement in plume and ceiling jet regions. Finally, the test results aimed to provide a scientific basis and reference for the fire safety and structural fire-resistant design of large space buildings.

Effect of discharge thermal action in ECDM on electrochemical behaviours of matrix material and its recast layer in glycol-based solution

The interaction between thermal and electrochemical corrosion in the ECDM process remains unclear. This study clarifies the effect of discharge thermal action on electrochemical corrosion. Real-time temperature curves indicate that the solution temperature in the electrochemical corrosion zone increased significantly due to discharge thermal action. The corrosion resistance of the recast layer’s passive film is superior to that of the matrix due to the enrichment of Cr2O3. As the electrolyte temperature rises, the passive film thickens but shows lower polarization resistances and poorer corrosion resistance due to a loose and weak structure. The matrix material and its recast layer dissolved uniformly, resulting in a considerably flat surface in a glycol-based solution, with enhanced levelling efficiency due to discharge thermal action.

Versatile binder system as enabler for multi-material additive manufacturing of ceramics by vat photopolymerization

Vat photopolymerization is an additive manufacturing process for producing ceramics with high printing resolution. Extending this approach to multi-material additive manufacturing, the aim is to combine two or more different ceramics in a single component to aggregate their advantages. For this, binders for different ceramic materials are required. To enhance the debinding step, this work aimed to develop a versatile binder system suitable for different ceramic materials. Finally, a binder system was developed and qualified for several different ceramic materials. By thermogravimetrical analyses, a suitable temperature curve for debinding was derived. In a final sintering step, the components were densified almost defect-free. Therefore, this work serves as an enabler for multi-material vat photopolymerization.

КОМПЬЮТЕРНОЕ МОДЕЛИРОВАНИЕ ТЕМПЕРАТУРНЫХ ПОЛЕЙ В СВАРНОМ ШВЕ ПРИ ИЗМЕНЕНИИ ТЕХНОЛОГИЧЕСКИХ ПАРАМЕТРОВ СВАРКИ ТРЕНИЕМ С ПЕРЕМЕШИВАНИЕМ АЛЮМИНИЯ И МЕДИ

This paper discusses numerical modeling of temperature fields in friction stir welding (FSW) of aluminum (AD1) and copper (M1). A three-dimensional thermomechanical finite element model based on the coupled Euler-Lagrange (CEL) approach is used. The paper models and experimentally confirms the influence of FSW parameters on the distribution and peak temperature values in weld zones. The maximum temperature values are observed on the copper side. This is due to the high thermophysical properties of copper compared to aluminum. Changing the rotation speed of the welding tool from 800 rpm to 1000 rpm leads to an increase in the peak temperature from 492 °C (800 rpm) to 692 °C on the side of the copper plate (1000 rpm). The maximum discrepancy between the calculated and experimental temperature curves does not exceed 9%, which is quite acceptable for assessing the temperature field.

Fever Prevention in Patients With Acute Vascular Brain Injury: The INTREPID Randomized Clinical Trial.

Fever is associated with worse outcomes in patients with stroke, but whether preventing fever improves outcomes is unclear. To determine whether fever prevention after acute vascular brain injury is achievable and impacts functional outcome. Open-label randomized clinical trial with blinded outcome assessment that enrolled 686 of 1176 planned critically ill patients with stroke at 43 intensive care units in 7 countries from March 2017 to April 2021 (last date of follow-up was May 12, 2022). Patients randomized to fever prevention (n = 339) were targeted to 37.0 °C for 14 days or intensive care unit discharge using an automated surface temperature management device. Standard care patients (n = 338) received standardized tiered fever treatment on occurrence of temperature of 38 °C or greater. Primary outcome was daily mean fever burden: the area under the temperature curve above 37.9 °C (total fever burden) divided by the total number of hours in the acute phase, multiplied by 24 hours (°C-hour). The principal secondary outcome was 3-month functional recovery by shift analysis of the 6-category modified Rankin Scale, which is scored from 0 (no symptoms) to 6 (death). Major adverse events included death, pneumonia, sepsis, and malignant cerebral edema. Enrollment was stopped after a planned interim analysis demonstrated futility of the principal secondary end point. In total, 686 patients were enrolled, and 9 were consented but not randomized, leaving a primary analysis population of 677 patients (254 ischemic stroke, 223 intracerebral hemorrhage, 200 subarachnoid hemorrhage; 345 were female [51%]; median age, 62 years) with 433 (64%) completing the study through 12 months. Daily mean (SD) fever burden was significantly lower in the fever prevention group (0.37 [1.0] °C-hour; range, 0.0-8.0 °C-hour) compared with the standard care group (0.73 [1.1] °C-hour; range, 0.0-10.3 °C-hour) (difference, -0.35 [95% CI, -0.51 to -0.20]; P < .001). Between-group differences for the primary outcome by stroke subtype were -0.10 (95% CI, -0.35 to 0.15) for ischemic stroke, -0.50 (95% CI, -0.78 to -0.22) for intracerebral hemorrhage, and -0.52 (95% CI, -0.81 to -0.23) for subarachnoid hemorrhage (all P < .001 by Wilcoxon rank-sum test). There was no significant difference in functional recovery at 3 months (median modified Rankin Scale score, 4.0 vs 4.0, respectively; odds ratio for a favorable shift in functional outcome, 1.09 [95% CI, 0.81 to 1.46]; P = .54). Major adverse events occurred in 82.2% of participants in the fever prevention group vs 75.9% in the standard care group, including 33.8% vs 34.5% for infections, 14.5% vs 14.0% for cardiac disorders, and 24.5% vs 20.5% for respiratory disorders. In patients with acute vascular brain injury, preventive normothermia using an automated surface temperature management device effectively reduced fever burden but did not improve functional outcomes. ClinicalTrials.gov Identifier: NCT02996266.

Correcting the effect of temperature changes in the measurement results of dielectric response in power transformers as an arrhenius type dielectric with the help of artificial neural network

Polarization and Depolarization Current (PDC) and Frequency Domain Spectroscopy (FDS) measurements are common dielectric response tests in time and frequency domain that are widely used to diagnosis insulation status in power transformer companies. Numerous factors affect the PDC and FDS test results, which the most important of them is temperature variation. To accurately interpret the results of the dielectric response, the effect of temperature on the results in time and frequency domains, must be corrected. In this paper, firstly a 200 MVA transformer is selected as a test object and FDS and PDC tests are performed on it at different temperatures. Then, based on the FDS results performed on a transformer at different temperatures, the parameters of the insulation model have been estimated by using genetic algorithm (GA). Next, with the help of artificial neural network (ANN), the parameters of the insulation model, related to the different temperatures are transferred into the reference parameters. After that, the parameters of the transferred insulation model, the FDS curves are plotted and transferred to the reference temperature curve and the effect of temperature on them is compensated. By using the correlation of the time and frequency domain results, with the help of transferred insulation model parameters, the PDC results are also plotted and transmitted on the reference PDC curve. Finally, with such a method, the effect of temperature on the PDC results is compensated.

Impact of chaplygin-like equation of state on Joule–Thomson expansion and tidal forces of AdS black holes

This study examines a recently hypothesized black hole. We study the Joule–Thomson coefficient, the inversion temperature and also the isenthalpic curves in the Ti−Pi plane. The Joule–Thomson coefficient, the inversion curves and the isenthalpic curves are discussed in AdS black holes surrounded by Chaplygin dark fluid. In T−P plane, the inversion temperature curves and isenthalpic curves are obtained with different parameters. Next, we explore the radial time-like geodesics that leads us to explore the tidal force effects for a radially in-falling particle in such black hole spacetime. We also numerically solve the geodesic deviation equation for two nearby radial geodesics for a freely falling particle. Our analysis shows that contrary to the Schwarzschild spacetime, the tidal forces do not become zero at spatial infinity due to the lack of asymptotic flatness because of the presence of a non-zero cosmological constant. The geodesic separation profile shows an oscillating trend and depends on the dynamic spacetime parameters q,B and Λ.

Effect of heat production on MHD natural convection transport of nanofluid flow via a vertical uniform perforated plate: An unsteady analysis

This article statistically investigates the impact of heat production on the unstable MHD natural convection transport of nanofluid flow via a perforated sheet. The ordinary differential equations (ODEs) are derived from the partial differential equations (PDEs) by using of the similarity transformation. The dimensionless ordinary differential equations (ODEs) may be numerically resolved with the help of the MATLAB ODE45 tool and the finite difference method (FDM) along with the shooting strategy. Four innovative water-based nanofluids such as TiO2, Cu, Al2O3, and Ag are considered nanoparticles. The numerical results have been explained for the role of numerous non-dimensional numbers or parameters such as heat generation or absorption (Q), nanoparticle volume fraction (φ), Dufour number (Df), Prandtl number (Pr), magnetic force parameter (M), Soret number (Sr), and Schmidt number (Sc) on the fluid flow, and heat and mass transfer rates. The fluid temperature drops but velocity is enhanced for higher amounts of Q. Copper nanoparticle volume fraction up to 4 % shows a rise in temperature, concentration, and velocity curves. Heat transfer rate ( − θ′(0)) diminishes by about 124 %, while the values of f′(0) promote by approximately 26 % owing to an increase in the values of Q (heat generation) from 1.0 to 2.0. The value of ( − θ′(0)) increases by 49 %, but f′0 decreases by 15 % due to a rise in Q (heat absorption) from -3.0 to -10.0. The local skin friction coefficient (f′(0)) diminishes by about 65.21 % due to an increase in the values of the magnetic force parameter (M) from 0.5 to 3.5 whereas the rate of heat and mass transfer remain unchanged. As φ increased from 0.01 to 0.04, the local skin friction coefficient (f′(0)) exhibited a 36 % increase, while the heat transport rate (θ′(0)) decreased around by 10 %. In conclusion, a comparison was made between our findings and those of the published research. The comparison indicates a high degree of consistency.