Search Results (2,494)

The convective drying of agricultural materials is an energy-intensive process, and optimizing dryer design is critical for improving efficiency and product quality. This study presents a comprehensive heat and mass transfer model for the convective drying of alfalfa leaves in a rotary drum dryer. Freshly harvested leaves with an initial moisture content of approximately 70% (w.b.) were used as the test material. The proposed system features a simplified drum design aimed at enhancing process efficiency while reducing equipment complexity. The primary objective was to reduce the moisture content of alfalfa leaves to below 50% to ensure their quality during subsequent storage and transportation. To determine the optimal operating conditions, the kinematics of leaf motion inside the rotating drum and the associated heat and mass transfer phenomena were investigated through analytical modeling, numerical simulation, and experimental studies on a laboratory-scale physical model. An analytical model was developed to establish relationships between transverse kinematic characteristics (detachment condition, Froude number, drum inclination angle), average longitudinal velocity, and residence time. Numerical simulations based on the Navier–Stokes equations (continuity, momentum, and energy) provided detailed moisture content distributions within individual leaves under varying airflow orientations and drying durations. The novelty of this work lies in the integrated determination of optimized operating parameters through combined analytical, numerical, and experimental approaches. A regression model relating final moisture content to key process variables (air velocity, temperature of 60 °C, drum rotation frequency and mass of loaded material) was developed from experimental data, yielding practical recommendations for the design and operation of rotary drum dryers for alfalfa and similar agricultural materials. Full article

Starch-based bioplastics are renewable and biodegradable, but their wider use is constrained by moisture sorption, humidity-dependent aging, insufficient tensile performance, and weak water- and oxygen barrier stability. This review critically synthesizes the peer-reviewed literature from 2020 to 2026 on enzymatically engineered starch for film, packaging, and thermoplastic applications using an architecture–property framework that links enzyme specificity, chain-length distribution, crystallinity, processing route, and material response. Controlled α-1,4 hydrolysis mainly improves processability by lowering molecular weight, viscosity, and gelatinization resistance. However, excessive hydrolysis can increase water uptake, solubility, and loss of cohesive strength. Debranching by pullulanase or isoamylase increases amylose-like linear chains and can promote B-type crystallinity or V-type starch–lipid complexes, with reported gains in tensile strength, contact angle, and water vapor barrier when the chain lengths and recrystallization conditions are controlled. Branching enzymes and transglycosylases increase branch density or redistribute glucan chains, suppressing retrogradation and improving flexibility, water retention, and aging resistance, but often with trade-offs in strength, crystallinity, and barrier performance. Lipase- and laccase-catalyzed functionalization expands starch functionality by increasing hydrophobicity, compatibility with hydrophobic phases, antioxidant activity, and active-packaging potential. The evidence indicates that enzymatic modification should not be generalized as uniformly improving starch bioplastics; performance gains are conditional on the starch source, amylose content, enzyme dosage, reaction severity, plasticizer composition, processing method, film conditioning, and storage humidity. Industrial implementation remains limited by enzyme cost and reuse, high-solids mass transfer, reaction time, enzyme stability under heat and shear, and reproducibility across botanical sources. Overall, enzymatic molecular editing is most promising when mechanistic architecture control is coupled with standardized structure–property reporting and scalable processing, such as immobilized-enzyme reactors, high-solids systems, and reactive extrusion. Full article

Solar-Driven Photothermal Membrane Distillation (SPMD) integrates solar energy using photothermal coatings on the hydrophobic membranes, such as carbon black nanoparticles coated on PVDF membranes, to achieve localized heating at the liquid–vapor interface. This approach enhances energy efficiency by mitigating temperature polarization and reducing thermal energy demands compared to conventional membrane distillation (MD). However, the challenges of fouling and scaling, which can significantly impair membrane performance, continue to be a serious concern, similar to other MD configurations. This comprehensive review establishes a unified framework connecting core transmembrane mass and heat transfer mechanisms with the thermodynamic pathways of surface fouling and scaling. We critically evaluate various strategies for mitigating scaling and fouling, including the development of omniphobic membranes, the introduction of nano/micro bubbles, the addition of anti-scalants and surfactants, and the implementation of chemical and mechanical pretreatments. Subsequently, the impact of photothermal coatings, applied to the feed–membrane interface in SPMD to absorb solar radiation, on scaling and fouling resistance is also discussed. Finally, we provide a comprehensive review of advanced computational paradigms, for both coupled radiative-thermal and dynamic fouling models—contrasting deterministic, physics-based multi-phase Computational Fluid Dynamics (CFD) with empirical Response Surface Methodology (RSM) and predictive Artificial Intelligence (AI) data-driven models. Beyond this survey, we identify and directly address a critical, previously unquantified gap in the field of SPMD: the absence of an explicit thermodynamic link between transmembrane heat/mass transfer and the nucleation and adhesion processes that govern scaling and fouling, and we further highlight the practical barriers—photothermal coating durability, economic feasibility, and technology readiness—that currently separate laboratory-scale SPMD from field deployment. This holistic synthesis charts future engineering strategies for scalable, fouling-resistant, and optimized solar-driven desalination infrastructure. Full article

Fluidic oscillators (FOs) are self-excited jet-generating devices without moving parts that convert steady fluid supply into oscillatory jets through inherent flow instabilities. Among various FO configurations, dual-feedback fluidic oscillators (DFFOs) have attracted extensive attention due to their simple structure, high reliability, stable oscillation characteristics, and broad applications in active flow control, heat transfer enhancement, and fluid mixing. However, conventional trial-and-error-based optimization methods are limited by strong parameter coupling and trade-offs among multiple performance objectives, such as oscillation frequency, jet deflection angle, and energy efficiency. This review systematically summarizes recent advances in performance enhancement strategies for DFFOs from the perspective of “from geometric control to intelligent design”. The effects of multi-scale geometric regulation, including macroscopic structures, internal microstructures, and manufacturing-related factors, are discussed. Advanced optimization approaches, including active control, novel configurations, inverse design, and data-driven methods, are further reviewed. Particular attention is given to additive manufacturing challenges and DFFO performance under multiphase flow conditions, including erosion, particle deposition, atomization, and mass transfer. Finally, future perspectives are proposed regarding multi-physical coupling, intelligent optimization, and engineering applications. This review provides a comprehensive reference for the cross-scale performance enhancement and intelligent design of DFFOs. Full article

Boil-off from cryogenic liquids is a significant economic, operational, and safety challenge across the global energy industry, yet existing models lack the scope and predictive capability needed to simulate boil-off across a range of fluids and storage conditions. This work introduces a new, one-dimensional lumped parameter model for predicting boil-off from a variety of fluids under a range of storage conditions. The new model divides the liquid into discrete, homogeneous layers coupled by a set of heat and mass transfer equations and can capture liquid-phase thermal stratification effects and compositional changes as the tank both self-pressurises and operates isobarically. During pressurisation, the model simulates convection within the liquid by dividing it into conduction and convection domains and calculating boundary layer and recirculation flowrates within the latter. During isobaric operation, the model applies a shortcut convection term that allows ambient heat ingress into a layer to be transferred to the liquid surface where it generates boil-off instead of heating the liquid. Unlike previously published works, this model does not require manipulation of adjustable parameters to describe pressurisation and boil-off rates relative to experimental data. It thus offers improved predictive capability compared to existing homogeneous-phase models, with applications to the design of boil-off handling systems, maritime shipping, and long-term storage of cryogenic liquids. Full article

Current thermal validation in food engineering commonly depends on rigid, temperature-only endpoints that generate thermal stress and the associated energy cost in the case of high-caliber matrices. To overcome this, this study provides a proof of concept for post-heating cooling inertia as the main kinetic driver of cumulative integrated lethality in mass-transfer-limited geometries (p value framework), followed by separate enzymatic and not microbial (or, e.g., oxidative) degradation following product heat transfer. Time-series and multi-spatial thermodynamic profiling was performed for the commercial validation runs of three pasteurization processes of large-diameter (90 mm) finely minced cooked chicken emulsions packed in polyamide casing. When active heating was stopped at a lower core limit of 71 °C, the thermal cooling inertia led total integrated lethality to increase by more than 216%, leading to an ultimate core p value of 76.87–89.56 min. It systematically exceeded the mandatory food safety limit (p ≥ 40 min) in all spatial coordinates in the forced convection chamber, confirming absolute thermal homogeneity. In a subsequent cold-chain stability challenge at around 70 days (0–4 °C), foodborne pathogens were not detected in the product, and saprophytic microflora was limited below critical spoilage bounds (total viable counts (TVC) and dominant lactic acid bacteria (LAB) progressively increased to 3.7 and 3.5 log10 CFU/g on day 70). The autoxidation pathways for primary and secondary lipids remained low (peroxide at 0.00 mmol/kg and malondialdehyde at less than 0.15 mg MDA/kg). On the other hand, a linear progression of free fatty acids (R² = 0.9673) determined that the single enzymatic lipid hydrolysis is responsible for the final biochemical limiting effect of the sensory lifespan. Shelf life evaluation via rigorous quantitative descriptive analysis showed that all organoleptic attributes remained well above market acceptance criteria until day 70. At the same time, this study supports a scalable, prediction-based thermodynamic paradigm that ensures biological safety and fundamentally optimizes industrial energy use. Full article

Molten salts have attracted considerable attention as heat transfer and thermal storage media in high-temperature energy systems, including concentrating solar power systems, advanced heat exchangers, and nuclear-related thermal systems. However, their relatively low thermal conductivity, high Prandtl number, and strong temperature-dependent viscosity may limit convective heat transfer performance and increase the difficulty of thermal-hydraulic design. Internally helically finned tubes have been widely used as passive heat transfer enhancement structures in conventional thermal systems, but their applicability to high-temperature molten-salt flows remains insufficiently understood. In this study, a three-dimensional numerical model was developed to investigate the thermal-hydraulic performance of a low-melting-point quaternary nitrate salt flowing through internally helically finned tubes. The effects of fin pitch, fin height, and helix angle were systematically examined over a Reynolds number range of 14,000–26,000. The results show that decreasing the fin pitch and increasing the helix angle enhance near-wall flow disturbance and improve convective heat transfer, while also increasing the pressure drop. The fin height exhibits a more pronounced trade-off effect: although larger fins increase the heat transfer coefficient, excessive fin height causes a substantial hydraulic penalty and weakens the overall performance. Based on the Performance Evaluation Criterion, the configuration with a fin pitch of 1.4 mm, fin height of 0.4 mm, and helix angle of 30° achieves the best overall thermal-hydraulic performance within the investigated parameter range, with a maximum PEC of 2.14. Compared with representative enhanced-tube configurations reported for molten-salt heat transfer, the internally helically finned tube shows competitive comprehensive performance. This work provides a numerical assessment of the feasibility and design sensitivity of internally helically finned tubes for molten-salt heat exchangers and offers useful guidance for the optimization of high-temperature thermal energy systems. Full article

Liquid hydrogen (LH2) is a promising energy carrier for maritime transportation owing to its high storage density and carbon-free utilization. However, its cryogenic storage temperature inevitably causes boil-off gas (BOG) generation, even with advanced insulation, and ship-induced sloshing can further disturb interfacial heat and mass transfer. This study numerically investigates BOG generation in a Type-C LH2 tank under sloshing conditions. A transient two-phase CFD model was developed using the volume of fluid method to track the liquid–vapor interface and the Lee phase-change model to calculate evaporation and condensation. Sloshing excitation was imposed through mesh motion, and parametric simulations were performed for different filling ratios, frequencies, amplitudes, and baffle configurations. The results show that the 50% filling condition produced the lowest boil-off rate, while amplitude had a stronger influence than frequency by increasing free-surface deformation, internal velocity, and convective heat transfer. Baffles reduced liquid motion but could increase BOG through additional conductive heat-transfer paths. These findings support BOG prediction and baffle design for Type-C LH2 tanks. Full article

Geothermal energy extraction using existing wellbore systems provides a promising approach for sustainable heat utilization; however, the long-term thermo-hydro-mechanical (THM) responses associated with different working fluids remain insufficiently understood. In this study, a three-dimensional coupled THM model was developed to compare geothermal heat extraction using water and pressurized CO₂ under identical geological and operational conditions. The model integrates Darcy flow, heat transfer, and linear elastic deformation to investigate the evolution of hydraulic, thermal, and mechanical fields over a 100-year operation period. The results show that the hydraulic fields rapidly reach quasi-steady states, whereas thermal responses continuously evolve due to cold-front propagation from the injection well. Compared with water, pressurized CO₂ exhibits stronger fluid mobility and produces a larger thermal influence region, resulting in different heat extraction characteristics under the same mass-flow-rate condition. Thermal cooling induces reservoir contraction and stress redistribution; however, the calculated stress and displacement variations remain within a stable range throughout the simulation period. The comparison demonstrates that pressurized CO₂ can enhance long-term thermal utilization while maintaining acceptable geomechanical stability under the investigated conditions. These findings provide insights into the selection of working fluids for wellbore-based geothermal systems and highlight the importance of coupled THM evaluation for long-term reservoir performance assessment. Full article

Pulverized coal explosions pose significant hazards during pneumatic conveying and handling in coal preparation and mining. To investigate flame propagation and pressure evolution under conditions representative of vertical conveying pipelines, explosion experiments were conducted using pulverized coal with defined particle sizes and dust concentrations. Flame propagation and pressure dynamics were synchronously captured via high-speed imaging and dynamic pressure measurements. Results showed that flame height exhibited a Logistic growth pattern, whereas flame propagation velocity followed an inverted parabolic trend, reaching a maximum value of 14.5 m s⁻¹ at approximately 20 ms after ignition. Significant flame-front wrinkling, distortion, and oscillatory propagation were observed during explosion development, reflecting increasingly complex flame evolution within the confined vertical pipeline. Increasing dust concentration from 0.3 to 0.5 kg m⁻³ promoted flame acceleration and pressure development. For 45 μm particles, the maximum explosion pressure increased from 0.710 to 0.948 MPa. At a constant concentration, decreasing particle size enhanced both flame propagation and explosion severity. Under 0.5 kg m⁻³, the maximum pressure increased from 0.788 MPa for 200 μm particles to 0.948 MPa for 45 μm particles. The enhanced explosion intensity at higher concentrations and smaller particle sizes is attributed to accelerated heat and mass transfer together with more efficient combustion under confined conditions. These findings provide new insight into the coupled evolution of flame propagation and pressure development and contribute to explosion risk assessment in pulverized coal conveying systems. Full article

This investigation meticulously examines the influence of activation energy, thermophoresis, Brownian motion, and magnetic fields on the flow dynamics and heat transfer characteristics of a non-Newtonian hybrid nanofluid comprising aluminum oxide (Al₂O₃), copper (II) oxide (CuO), and ethylene glycol over a horizontally stretching porous wedge. This research addresses the imperative need for enhancing energy transfer and thermal management systems, which possess considerable technical significance and industrial relevance. The flow equations were formulated into ordinary differential equations through the use of similarity transformations, which in turn were solved numerically by employing the spectral relaxation (SR) scheme. The findings indicate that the Brownian motion, activation energy, wedge angle, and magnetic field intensity are pivotal determinants of the system’s flow and thermal behavior. In particular, an increase in the wedge angle correlates with an augmentation of the Nusselt number while concurrently diminishing the thermal and diffusion profiles. A comparative analysis of the current investigation and earlier scrutiny revealed that hybrid nanofluids enhance mass and energy transfer rates in both studies. The novelty of this investigation is anchored in its comprehensive exploration of magneto-flow dynamics and the characteristics of hybrid nanofluids within the context of porous wedge-shaped geometries and external magnetic influences. The findings of this study extend previous research by offering quantitative elucidation regarding how pivotal parameters, such as wedge angles, activation energy, thermophoresis, and Brownian motion, affect heat and mass transfer phenomena, thus laying a robust groundwork for the optimization of hybrid nanofluid applications in engineering and industrial environments. The results are in robust agreement with the existing body of literature, thereby affirming the contributions of this study to the academic discourse in the field. Full article

An adaptive immersed boundary method (IBM) for simulating non-isothermal incompressible flows with convective heat transfer involving a rotating circular cylinder is developed. Both Dirichlet- (isothermal) and Neumann (zero heat flux)-type temperature boundary conditions are implemented. In addition to the discrete momentum forcing and energy forcing adopted to effectively satisfy the prescribed velocity and temperature boundary conditions, a mass source/sink term is introduced into the continuity equation to meet the mass conservation at the immersed boundary. The Navier–Stokes equations are solved using the fractional step method implemented on a staggered Cartesian grid system. Time stepping is performed using a second-order Adams–Bashforth/backward-differentiation method, while spatial derivatives are approximated with a second-order centered scheme. Testing of the flow induced by a rotating disk demonstrates that the spatial accuracy of the presented algorithm is second-order. Furthermore, the proposed method is validated by forced convective flow past a rotating isothermal circular cylinder. Finally, mixed Rayleigh–Bénard convection in a square cavity with an embedded adiabatic rotating circular cylinder is simulated, showing that heat transport can be greatly enhanced by increasing the rotating rate and radius of the cylinder at larger Prandtl numbers in the laminar regime. Full article

Efficient heat transfer is essential for the in-situ conversion of steeply dipping oil shale reservoirs. In this study, a superheated steam-driven integrated multi-branch well system was proposed, and a coupled thermo-hydro-chemical-mass transport model considering reservoir anisotropy was established in COMSOL Multiphysics-5.6 to investigate heat transfer characteristics and evaluate the effects of key engineering parameters. The numerical model was validated through comparison with an analytical solution and previously published numerical results. The results show that superheated steam preferentially migrates through hydraulic fractures and bedding-parallel high-permeability pathways, resulting in anisotropic heat transfer. Continuous steam injection gradually forms a connected high-temperature region, and most of the reservoir exceeds 500 °C after approximately 600 days. Compared with the conventional well arrangement, the proposed well system achieves more uniform reservoir heating and enlarges the effective pyrolysis region. Parametric analysis indicates that the highest thermal performance among the investigated cases is obtained with a heating well length of 22.5 m, while increasing the inter-well angle, fracture number, and fracture width enhances heat transfer and kerogen conversion. Among the investigated cases, the configuration with three hydraulic fractures achieves the best performance, with the high-temperature region (>500 °C) exceeding 80% of the reservoir after 400 days and a cumulative hydrocarbon production of approximately 4.7 × 10⁷ mol. Sensitivity analysis further demonstrates that fracture-related parameters exert a greater influence on reservoir thermal performance than heating well length and inter-well angle. These findings provide theoretical guidance for the design and performance evaluation of integrated multi-branch well systems for the efficient in-situ conversion of steeply dipping oil shale reservoirs. Full article

This research presents a physics-informed deep learning framework for investigating the magnetohydrodynamic flow of a dissipative non-Newtonian micropolar nanofluid induced by a stretching sheet, incorporating Stefan blowing, internal heat generation, and the zero nanoparticle mass flux condition. The physical model consists of the interplay between the microrotation dynamics, resistance of porosity on the microrotation, Brownian diffusion, and thermophoretic transport phenomenon. The numerical solutions for the nonlinear yielded equations that result from the above interaction are obtained by employing a PINN that considers the laws of physics and boundary conditions. With this technique, the flow behavior, temperature, concentration, and microrotation fields can be predicted accurately without requiring huge datasets. This shows the ability of PINNs to numerically treat highly-coupled nonlinear transport equations in a very efficient manner compared to other traditional methods. The important discoveries from this study include that the porous and magnetic factors increased the skin friction coefficient, but the magnetic effect and viscous dissipation decreased the rate of heat transfer, and the thermophoresis effect decreased the rate of mass transfer while the Brownian effect increased it. The precision of the PINN algorithm is confirmed by comparison of the results with the earlier findings, which proves very high accuracy and hence the robustness of the current computing framework. Results of this research are useful for the development of some thermal management systems, energy converters, cooling methods, chemical reaction processes, fuel cell technology, porous media reactors, and ocean engineering involving the transport of complicated non-Newtonian nanofluids. Full article

Wet cooling towers are widely used for low-energy thermal management and ventilation support; however, high-fidelity simulations are computationally expensive for large design studies. This work develops a physics-based static reduced-order model for a two-dimensional axisymmetric counterflow wet cooling tower derived from computational fluid dynamics (CFD) simulations coupled with a user-defined source-term formulation for heat and mass transfer in the fill region. A design of experiments based on advanced Latin hypercube sampling generated 210 configurations, of which 168 valid simulations were retained. The active inputs included tower diameter, fill height, inlet air mass flow rate, inlet air temperature, inlet humidity ratio, inlet water mass flow rate, and inlet water temperature, while the cooling range and evaporation rate were selected as target outputs. Five surrogate families were compared by cross-validation. Kriging was statistically most accurate, with $R_{CV}^2$ values of 0.9999 and 0.9998 for the cooling range and evaporation rate, respectively. Second-order quadratic polynomial models were selected as the engineering reduced order model (ROM) because they capture non-linear boundary curvatures with accuracy, achieving $R_{CV}^2\ge 0.9989$ and root mean square errors of 0.0426 K and 0.00042 kg/s while preserving an explicit, directly implementable algebraic form. Sensitivity analysis indicated that the inlet water temperature and air mass flow rate are dominant factors within the sampled domain. Full article