Journal of Thermal Analysis and Calorimetry最新文献

The smoke mass flow rate (MFR) is a fundamental parameter for determining the design exhaust smoke volume in fires. In this study, the influence of the sidewall restriction on smoke MFR of double-fire scenarios in long-narrow spaces was systematically studied. Two typical fire scenarios, namely the center fire and the wall fire, were studied with particular emphasis. Additionally, three heat release rates (HRRs) and six dimensionless separation distances (S/D) were also considered. The results show that for a given S/D, smoke MFR increases with HRR due to enhanced plume entrainment, while the wall fire configurations consistently produce lower smoke MFR values compared to the center fire under equivalent cases. By analyzing smoke MFR evolution characteristics, a novel stepwise coupling model was developed to establish the functional relationship between dimensionless MFR, fire separation distance, and HRR for both fire scenarios. A prediction model of smoke MFR during the one-dimensional spread stage was also proposed. The results could provide valuable engineering insights for optimizing smoke management systems and enhancing emergency preparedness in long-narrow spaces.

Accurate prediction of heat transfer coefficients (HTCs) is essential for optimizing the performance of helical plate heat exchangers (HPHEs), especially given their complex flow structures. This study develops a machine-learning-based framework to predict HTCs and improve HPHE thermal performance without relying on computationally expensive turbulence modelling. Using experimental data, geometric factors (pitch ratio, helix diameter, and plate spacing), and thermal parameters, the proposed models effectively capture the nonlinear behaviour of heat transfer. The results demonstrate that increasing flow rates enhances HTC from 450 to 680 W m⁻² K⁻¹, while surface modifications such as graphene oxide and nanofluid coatings improve the thermal enhancement factor (TEF) to 1.52 and 1.58, respectively. A CNN-based Bayesian optimization algorithm (BOA) further identified optimal operating conditions, including a pitch ratio of 0.67 and fluid velocities of 0.93 m s⁻¹ (hot) and 0.19 m s⁻¹ (cold), achieving an optimized HTC of 580 W m⁻² K⁻¹. The machine-learning framework produced accurate HTC predictions within 2.03 s, compared to 45 min required for high-fidelity simulations, demonstrating a substantial reduction in computational cost. This confirms the potential of ML models as efficient surrogates for complex numerical simulations. The study provides a practical pathway for designing next-generation heat exchangers with enhanced thermal performance. Future scope includes integrating advanced nanomaterials, expanding the ML framework to multi-objective optimization, incorporating real-time adaptive learning for dynamic systems, and validating the approach at industrial scale to further strengthen the deployment of ML-driven thermal system design.

The energy efficiency of heat exchangers can be enhanced by integrating passive methods, such as tubular fin turbulators, nanofluids, and helical coil tubes. This study experimentally investigates the synergistic effects of tubular fin turbulators in conjunction with two types of nanofluids: graphene oxide (GO) and alumina (Al₂O₃) focusing on the heat transfer characteristics of a helically wrapped coil-in-shell heat exchanger (CSHE). The experiment uses three distinct helically wound coils and is conducted at a constant heat flux of 4 kW m⁻². Two of the coils are equipped with tubular fins brazed to their outermost annular surfaces at orientations of α = 45° and 90°, while the third coil is a plain design without fins. The GO and Al₂O₃ nanofluids are used at volume concentrations of 0.05, 0.10, and 0.15%, flowing through the coil side under laminar to turbulent flow conditions (500 ≤ Re ≤ 5500). The shell-side fluid is hot air, with velocities ranging from 1 to 5 m s⁻¹. Empirical data indicate that both nanofluids significantly enhance heat transfer in a finned coil-in-shell heat exchanger (FCSHE). The FCSHE exhibited a considerable increase in heat transfer compared to the unfinned CSHE using water at a moderate shell-side velocity of HAV = 3 m s⁻¹. At a volume concentration of 0.15%, the Nusselt number increased by 60.33% with GO and by 69.62% with the Al₂O₃ nanofluid. Furthermore, under identical operating conditions, the combination of the 45°-oriented tubular fin and the 0.15% Al₂O₃ nanofluid demonstrated an 8.90% greater enhancement in the Nusselt number indicating superior thermal performance compared to the finned CSHE–GO nanofluid combination with nominal pumping power loss. Additionally, the thermo-hydraulic performance (THP) factor nearly doubled when combining the Al₂O₃ nanofluid with the 45° tubular fin orientation. In the end, the Nusselt number, friction factor, and THP values in both laminar and turbulent regimes showed reasonable agreement with permissible limits of ± 10– ± 14% between empirical and predicted outcomes.

Graphical Abstract

Material modeling involving chemical reactions demands substantial energy input, particularly in processes such as chemical vapor deposition and chemical liquid deposition, which are widely utilized in the fabrication of diodes, transistors, metallic-glass coatings, and gas-barrier layers. Owing to their industrial importance, understanding the complex fluid behavior associated with these thermochemical processes is essential. Motivated by these considerations, the present study aims to investigate the influence of slip effects, activation energy, Ohmic dissipation, and Darcy–Forchheimer resistance on the spinning flow of shear-thinning materials over a magnetized rotating disk. The governing physical phenomena are formulated through a system of nonlinear partial differential equations that describe the momentum, thermal, concentration, and pressure fields. These equations are numerically solved using the modified three-stage Lobatto method to ensure high accuracy in capturing the underlying flow characteristics. The numerical findings show that increasing the magnetic parameter significantly suppresses both radial and tangential velocity components, while the Forchheimer factor leads to a further reduction in radial flow due to enhanced porous medium drag. Moreover, elevated values of the magnetic parameter and Forchheimer number diminish the primary velocity gradient yet amplify the secondary velocity gradient, indicating a dynamic trade-off in velocity responses. Higher material parameters and Eckert number are associated with increased temperature and pressure levels, whereas enhanced reaction rates result in reduced concentration profiles. The numerical approach is validated through a close agreement with benchmark data. The study provides valuable insights into the interplay between magnetic field, porous media, and thermochemical effects in shear-thinning fluid systems, and offers relevant implications for optimizing industrial material-processing operations.

The current investigational research is to enhance the operational features of Calophyllum inophyllum biodiesel (CIBD) fuelled diesel engine through DiEthyl Ether (DEE) and Iso-Butanol (IB) as secondary fuel along with PCCI strategy. Premixing of DEE and IB was carried out at two different conditions, in terms of 10% and 20% energy share of primary injected fuel B20 (20% CIBD + 80% diesel). The Response Surface Methodology Design of Experiments (DoE) was employed to enhance engine performance, emissions, and combustion characteristics. At all loaded conditions, the premixing of DEE and IB increased Brake Thermal Efficiency (BTE) and decreased Brake-Specific Fuel Consumption (BSFC) in comparison with B20. IB premixing showed higher BTE and lower BSFC than DEE at peak load. Additionally, the combustion characteristics were enhanced by IB premixing. Under all conditions, IB demonstrated reduced emissions of CO, NO_x, and CO₂ in comparison with DEE premixing. However, HC emissions got elevated. The optimal parameters of 60% load and B20 + 10IB yielded better engine working characteristics. The adaptation of the Premixed Charge Compression Ignition (PCCI) strategy in conventional CI engines is considered a sustainable technology to reduce emissions without sacrificing engine performance, especially when compared to conventional combustion.

Graphical abstract

Due to technological advancements, the energy demand on electronic devices has been reduced from milliwatts (mW) to microwatts (µW), and this microwatt power will be manageable with the usage of thermoelectric generators (TEGs). The TEGs work on the Seebeck effect and generate electricity due to temperature differences. To ascertain the temperature difference required for the power generation, phase change materials (PCMs) are widely recommended to integrate with TEGs. It is desired to prefer the PCMs of low temperature and high temperature types for cold and hot sides of TEGs, and as a result, it could be indeed beneficial to achieve a larger temperature difference for the power generation. The power output from TEGs could be sufficient to feed low power devices such as sensors, IoTs, ships, locomotive industries, wearable devices and signal indicators. The latest research progresses on the materials used for fabricating TEGs, placement of TEGs in the waste heat areas so as to achieve a maximum conversion efficiency, and heat transfer enhancement of PCMs used in TEGs. Due to their environmental sustainability, reliability, minimal maintenance costs, and direct power generation, TEGs are widely employed in various industries. The Internet of Things periphery devices are classified into three categories: Smart Home, Smart Factory, and Energy Efficiency. The high thermal capacity of PCM protects TEG and prevents device failure. The expansion of PCM-TEG's cooling capacity enhances its efficacy. The results indicate that the operating duration is extended by higher thermal power levels and that PCM reduces output voltage fluctuations. Inadequate heat source power may lead to partial PCM melting, which could result in a reduction in electricity output during non-heating periods. This study illustrates the great potential of thermoelectric power generators to herald in a new era of Internet of Things sensing devices by extracting energy from the ambient temperatures. This work could portray the wide area from the development of the novel generators and materials for better performance (Figure of merit), less space, and economically feasible, and the mechanism of heat transfer, critical analysis, importance of IoT, applications, advantages to drawbacks of TEG-PCM module.

Graphical abstract

Ambient ionisation mass spectrometry methods have been routinely applied to organic materials; however, the literature covering the analysis of inorganic materials, particularly with plasma-based methods such as DART-MS, appears scarce. Here we report the use of the combined DART-MS and hot-stage microscopy technique termed HDM to the analysis of inorganic compounds, including salts, metal complexes and the in situ study of solvent-free metal–ligand complexing. The higher temperature capabilities of HDM allow for the analysis of these thermally stable compounds, observing temperature transitions higher than with conventional DART-MS analysis alone. Optical data collected using the integrated microscope are processed, and events such as melting, dehydration, degradation and thermochromism can be linked directly to the DART mass spectra.

In order to maintain system longevity and performance, creative cooling solutions are required due to the growing thermal challenges in electronic systems. In this work, a novel microchannel heat sink (MCHS) design that combines triangular cavities and wavy walls (WMCHS-WTC) is presented. In this work, a novel microchannel heat sink design with triangular cavities and wavy walls (WMCHS-WTC) is evaluated using AlO₃/H₂O nanofluids. To compare the thermal and hydraulic performance of WMCHS-WTC with that of a traditional rectangular microchannel heat sink (RMCHS) under the same conditions, a dual-model experimental setup was created. Experiments and numerical simulations were conducted across Reynolds numbers (Re) ranging from 200 to 1000, heat fluxes between 50 and 200 W, and nanofluid volume concentrations from 0% to 0.05%. Results show that WMCHS-WTC significantly enhances heat transfer, achieving a 20% reduction in average wall temperature and a 66% increase in the Nusselt number at Re = 1000 and 0.05 vol% nanofluid concentration. Friction factor analysis showed a 26% increase for WMCHS-WTC at 0.04 vol% concentration compared to 15% for RMCHS. Thermal resistance typically decreases with increasing Re number and volume concentration for both types of MCHS, but it also depends on the design of the MCHS, where the findings show that the thermal resistance in WMCHS-WTC is lower than in RMCHS. The lowest thermal resistance value is 0.075 °C/W (at Re = 1000, P = 200 W, 0.04% volume concentration) in WMCHS-WTC, and the weakest in RMCHS is 0.115 at the same conditions. This is the first experimental and numerical study to integrate dual geometries in a single test section, offering a scalable and efficient solution for next-generation electronics cooling.

This study investigates waste heat recovery in an industrial setting using the ORC to generate electricity. The ORC system, using different organic fluids (R1234yf, R423A, R450A, R515A, and R161), converts low-temperature waste heat (averaging 120 °C) into electrical energy. Analysis shows that increasing both temperature and pressure ratio enhances power output and exergy efficiency across all fluids, with R1234yf, R423A, and R515A yielding higher efficiencies. However, R161 demonstrates lower efficiency and higher exergy destruction, making it less suitable for effective energy recovery. The study also evaluates economic and sustainability aspects, revealing that higher waste heat temperatures and pressure ratios reduce electricity generation costs, with R1234yf and R515A emerging as cost-effective choices. R515A achieves the highest exergy sustainability index (ESI), whereas R161 scores lower, indicating reduced sustainability. A Taguchi analysis highlights waste heat temperature and pressure ratio as primary factors affecting system performance, with fluid type and turbine efficiency showing limited impact. The findings support ORC as a valuable solution for sustainable energy recovery from low-grade industrial waste heat, emphasizing the importance of optimal temperature and pressure management for enhanced efficiency.

This study explores the flow behavior of a magnetized three-dimensional rotating penta-hybrid nanofluid (PHNF) over a stretched sheet, focusing on its potential applications in polymer processing and industrial cooling. The aim of the study is to investigate how various factors, such as nonlinear thermal radiation, heat source/sink, magnetic impact, porosity effects, and temperature ratio, influence the flow and heat transfer characteristics of PHNF. The modeling assumptions include the consideration of a porous medium, the influence of rotational effects, and the impact of magnetic fields on the fluid. The research methodology involves transforming the governing partial differential equations into ordinary differential equations using similarity transformations, followed by numerical solutions in MATLAB. The results show that higher radiation parameters and temperature ratios enhance fluid temperature, while magnetic fields and porosity reduce fluid velocity and boundary layer thickness. Additionally, the study finds that using PHNF instead of ternary hybrid nanofluid (THNF) leads to a reduction in the skin friction coefficient and an increase in the Nusselt number, making PHNF a superior candidate for heat and mass transfer applications in industrial systems. The findings highlight the practical value of PHNF in improving cooling efficiency and product quality, particularly in polymer processing applications such as blown film extrusion.