Search Results (233)

This study investigates the thermal dynamics and material behavior involved in the baking process for Lebanese flatbread, focusing on the heat transfer mechanisms, water loss, and dough expansion under high-temperature conditions. Despite previous studies on flatbread baking using impingement or conventional ovens, this work presents the first experimental investigation of the traditional Lebanese flatbread baking process under realistic industrial conditions, specifically using a high-temperature tunnel oven with direct flame heating, extremely short baking times (~10–12 s), and peak temperatures reaching ~650 °C, which are essential to achieving the characteristic pocket formation and texture of Lebanese bread. This experimental study characterizes the baking kinetics of traditional Lebanese flatbread, recording mass loss pre- and post-baking, thermal profiles, and dough expansion through real-time temperature measurements and video recordings, providing insights into the dough’s thermal response and expansion behavior under high-temperature conditions. A custom-designed instrumented oven with a steel conveyor and a direct flame burner was employed. The dough, prepared following a traditional recipe, was analyzed during the baking process using K-type thermocouples and visual monitoring. Results revealed that Lebanese bread undergoes significant water loss due to high baking temperatures (~650 °C), leading to rapid crust formation and pocket development. Empirical equations modeling the relationship between baking time, temperature, and expansion were developed with high predictive accuracy. Additionally, an energy analysis revealed that the total energy required to bake Lebanese bread is approximately 667 kJ/kg, with an overall thermal efficiency of only 21%, dropping to 16% when preheating is included. According to previous CFD (Computational Fluid Dynamics) simulations, most heat loss in similar tunnel ovens occurs via the chimney (50%) and oven walls (29%). These findings contribute to understanding the broader thermophysical principles that can be applied to the development of more efficient baking processes for various types of bread. The empirical models developed in this study can be applied to automating and refining the industrial production of Lebanese flatbread, ensuring consistent product quality across different baking environments. Future studies will extend this work to alternative oven designs and dough formulations. Full article

The synthesis of “green ammonia” from “green hydrogen” represents a critical pathway for renewable energy integration and industrial decarbonization. This study investigates the green ammonia synthesis process using an axial–radial fixed-bed reactor equipped with three catalyst layers. A simplified two-dimensional physical model was developed, and a multiscale simulation approach combining computational fluid dynamics (CFD) with physics-informed neural networks (PINNs) employed. The simulation results demonstrate that the majority of fluid flows axially through the catalyst beds, leading to significantly higher temperatures in the upper bed regions. The reactor exhibits excellent heat exchange performance, ensuring effective preheating of the feed gas. High-pressure zones are concentrated near the top and bottom gas outlets, while the ammonia mole fraction approaches 100% near the bottom outlet, confirming superior conversion efficiency. By integrating PINNs, the prediction accuracy was substantially improved, with flow field errors in the catalyst beds below 4.5% and ammonia concentration prediction accuracy above 97.2%. Key reaction kinetic parameters (pre-exponential factor k₀ and activation energy Ea) were successfully inverted with errors within 7%, while computational efficiency increased by 200 times compared to traditional CFD. The proposed CFD–PINN integrated framework provides a high-fidelity and computationally efficient simulation tool for green ammonia reactor design, particularly suitable for scenarios with fluctuating hydrogen supply. The reactor design reduces energy per unit ammonia and improves conversion efficiency. Its radial flow configuration enhances operational stability by damping feed fluctuations, thereby accelerating green hydrogen adoption. By reducing fossil fuel dependence, it promotes industrial decarbonization. Full article

Transcranial direct current stimulation (tDCS) can modulate cortical excitability in a polarity-specific manner, yet identical protocols often produce inconsistent outcomes across sessions or individuals. This narrative review proposes that much of this variability arises from the brain’s intrinsic temporal landscape. Integrating evidence from chronobiology, sleep research, and non-invasive brain stimulation, we argue that tDCS produces reliable, polarity-specific after-effects only within a circadian–homeostatic “window of efficacy”. On the circadian (Process C) axis, intrinsic alertness, membrane depolarisation, and glutamatergic gain rise in the late biological morning and early evening, whereas pre-dawn phases are marked by reduced excitability and heightened inhibition. On the homeostatic (Process S) axis, consolidated sleep renormalises synaptic weights, widening the capacity for further potentiation, whereas prolonged wakefulness saturates plasticity and can even reverse the usual anodal/cathodal polarity rules. Human stimulation studies mirror this two-process fingerprint: sleep deprivation abolishes anodal long-term-potentiation-like effects and converts cathodal inhibition into facilitation, while stimulating at each participant’s chronotype-aligned (phase-aligned) peak time amplifies and prolongs after-effects even under equal sleep pressure. From these observations we derive practical recommendations: (i) schedule excitatory tDCS after restorative sleep and near the individual wake-maintenance zone; (ii) avoid sessions at high sleep pressure or circadian troughs; (iii) log melatonin phase, chronotype, recent sleep and, where feasible, core temperature; and (iv) consider mild pre-heating or time-restricted feeding as physiological primers. By viewing Borbély’s two-process model and allied metabolic clocks as adjustable knobs for plasticity engineering, this review provides a conceptual scaffold for personalised, time-sensitive tDCS protocols that could improve reproducibility in research and therapeutic gain in the clinic. Full article

The application of hot in-place recycling asphalt mixtures (HIRAMs) is gaining increasing attention in highway maintenance due to its environmental and economic benefits. This paper comprehensively reviews and discusses the state-of-the-art studies in the field of hot in-place recycling (HIR). Firstly, different HIR technologies are introduced, including surface recycling, remixing, and repaving. Then, this paper provides a detailed description of the key factors influencing the road performance of HIRAMs in terms of both materials and production, such as reclaimed asphalt pavement (RAP), rejuvenators, virgin asphalt, virgin asphalt mixtures, preheating temperature, and mixing time. Furthermore, the environmental and economic benefits of HIR are compared with other preventative maintenance and recycling technologies. Finally, some challenges for the investigation of HIR are further discussed, and the corresponding suggestions are recommended for future investigation. Full article

The significant contribution of buildings to the global primary energy consumption necessitates the application of energy management methodologies at a building scale. Although dynamic simulation tools and decision-making algorithms are core components of energy management methodologies, they are often accompanied by excessive computational cost. As future controlling structures tend to become autonomized in building heating layouts, encouraging distributed heating services, the research scope calls for creating lightweight building energy system modeling as well monitoring and controlling methods. Following this notion, the proposed methodology turns a programmable controller into a smart thermostat that utilizes surrogate modeling formed by the ALAMO approach and is applied in a 4-m-by-4-m-by-2.85-m environmental chamber setup heated by a heat pump. The results indicate that the smart thermostat trained on the indoor environmental conditions of the chamber for a one-week period attained a predictive RMSE of 0.082–0.116 °C. Consequently, it preplans the heating hours and applies preheating controlling strategies in real time effectively, using only the computational power of a conventional controller, essentially managing to attain at least 97% thermal comfort on the test days. Finally, the methodology has the potential to meet the requirements of future building energy systems featured in urban-scale RES-based district heating networks. Full article

This study evaluates the feasibility of integrating pulsed electric field (PEF) technology with heat recovery for fruit juice pasteurization, comparing it to conventional high-temperature short-time (HTST) pasteurization. Three preheating temperature conditions (35 °C, 45 °C, and 55 °C) and varying heat recovery efficiencies have been assessed to analyze energy consumption, economic feasibility, and environmental impact. The results indicate that, while PEF pasteurization requires a higher initial investment, it improves energy efficiency, leading to significant reductions in utility costs. Across the tested configurations, PEF technology achieved reductions in electricity consumption by up to 20%, fuel gas usage by over 60%, greenhouse gas emissions by approximately 30%, and water consumption by 25%, compared to HTST. The optimal configuration of the PEF process, featuring a 35% waste heat recovery efficiency and a pre-heating temperature of 55 °C, has been identified as the most energy-efficient and sustainable solution, effectively reducing both water consumption and CO₂ emissions. A life cycle assessment has confirmed these environmental benefits, demonstrating reductions in global warming potential, fossil fuel consumption, and other impact categories. This study suggests that PEF technology can significantly contribute to more sustainable food processing by reducing environmental impacts, optimizing resource usage, and enhancing energy efficiency. Full article

The rapid progress in additive manufacturing (AM) has unlocked significant possibilities for producing 316/316L stainless steel components, particularly in industries requiring high precision, enhanced mechanical properties, and intricate geometries. However, the widespread adoption of AM—specifically Directed energy deposition (DED), selective laser melting (SLM), and electron beam melting (EBM) remains challenged by inherent process-related defects such as residual stresses, porosity, anisotropy, and surface roughness. This review critically examines these AM techniques, focusing on optimizing key manufacturing parameters, mitigating defects, and implementing effective post-processing treatments. This review highlights how process parameters including laser power, energy density, scanning strategy, layer thickness, build orientation, and preheating conditions directly affect microstructural evolution, mechanical properties, and defect formation in AM-fabricated 316/316L stainless steel. Comparative analysis reveals that SLM excels in achieving refined microstructures and high precision, although it is prone to residual stress accumulation and porosity. DED, on the other hand, offers flexibility for large-scale manufacturing but struggles with surface finish and mechanical property consistency. EBM effectively reduces thermal-induced residual stresses due to its sustained high preheating temperatures (typically maintained between 700 °C and 850 °C throughout the build process) and vacuum environment, but it faces limitations related to resolution, cost-effectiveness, and material applicability. Additionally, this review aligns AM techniques with specific defect reduction strategies, emphasizing the importance of post-processing methods such as heat treatment and hot isostatic pressing (HIP). These approaches enhance structural integrity by refining microstructure, reducing residual stresses, and minimizing porosity. By providing a comprehensive framework that connects AM techniques optimization strategies, this review serves as a valuable resource for academic and industry professionals. It underscores the necessity of process standardization and real-time monitoring to improve the reliability and consistency of AM-produced 316/316L stainless steel components. A targeted approach to these challenges will be crucial in advancing AM technologies to meet the stringent performance requirements of various high-value industrial applications. Full article

Solid oxide fuel cell (SOFC) systems often employ metallic cathode air pre-heaters (CAPHs), frequently made from alloys with high chromium (Cr) content, to recover thermal energy from exhaust gases and pre-heat incoming air and fuel. Cr evaporation from metallic CAPHs can poison SOFC cathodes, reducing their durability. To mitigate this, we investigated controlled pre-oxidation of a FeCrAl alloy (alloy 318) to form a protective alumina scale by self-growing, assessing its impact on and oxidation resistance and Cr retention capability for CAPH applications. The effects of pre-oxidation were investigated across a temperature range of 800 to 1100 °C and dwelling times of 0.5 to 4 h. The formed oxide scales were characterised using gravimetry in combination with advanced analytic techniques, such as SEM/EDX, STEM/EDX, TEM, and XRD. Subsequently, the pre-oxidised FeCrAl alloys were characterised with respect to the oxidation rate and Cr₂O₃ evaporation in a tubular furnace at 850 °C, with 6.0 L/min air flow and 3 vol% H₂O to simulate the SOFC cathode environment. TEM analysis confirmed that the FeCrAl alloys formed alumina scales with 10 nm and 34 nm thickness after 1 h of pre-oxidation at 900 and 1100 °C, respectively. The corrosion and Cr₂O₃ evaporation rates of the FeCrAl alloy at 850 °C in humidified air were shown to be dramatically decreased by pre-oxidation. It was found that the mechanisms of oxidation and Cr₂O₃ evaporation were found to be controlled by the formation of different alumina phases during the pre-oxidation. Measurements of Cr₂O₃ evaporation and weight gain revealed that the alloy 318 pre-treated at 1100 °C for 1 h will form an α-Al₂O₃ scale, leading to a 98% reduction of the oxidation rate and 90% reduction of Cr₂O₃ evaporation compared to the non-oxidised alloy 318 under simulated SOFC cathode conditions. Full article

In low-temperature environments, both the electrochemical and thermodynamic performances of lithium-ion batteries are significantly affected, leading to a substantial decline in overall performance. This deterioration is primarily manifested in the inability of the battery to release its actual capacity effectively, a marked reduction in charge–discharge efficiency, and accelerated capacity degradation, directly undermining its power output capability under low-temperature conditions. This performance degradation severely restricts the application of lithium-ion batteries in scenarios requiring high power and extended range, such as EVs. This paper proposes an intelligent low-temperature DC discharge heating optimization strategy based on the PSO algorithm. The strategy aims to simultaneously optimize heating time and minimize capacity loss by employing the PSO algorithm to dynamically optimize discharge currents under varying ambient temperatures. This approach achieves the simultaneous optimization of battery heating efficiency and capacity loss. It effectively overcomes the limitation of traditional constant-current discharge methods, which struggle to dynamically adjust current intensity based on real operating conditions. By balancing heating efficiency and capacity degradation, the model significantly enhances energy utilization. Taking the weighting factor λ = 0.5 as an example, the battery is heated from −30 °C to 0 °C at a 90% initial SOC. Compared to preheating methods that directly use the minimum optimized dynamic current threshold, it reduces heating time by 48.71 s and increases the heating rate by more than twofold. In contrast to preheating methods using the maximum optimized dynamic current threshold, it decreases capacity degradation by 0.10 Ah after 1000 heating cycles. This strategy addresses the limitations of traditional heating methods, providing a novel solution for the efficient application of lithium-ion batteries in low-temperature environments. Full article

Some studies have reported the microstructure evolution of nickel-based superalloys during isothermal forging (IF). However, most of them have not taken into account the microstructure evolution during the preheating stage in manufacturing processes. Investigating the microstructure evolution mechanisms during preheating of nickel-based superalloy can provide a more accurate characterization of the initial microstructures prior to IF. In this study, the evolution of grain structure, participation phase, and twins in a hot extruded nickel-based superalloy are examined during heat treatment at the temperature range of 1050~1140 °C and 5~180 min. Also, the interaction mechanisms among the above microstructures are analyzed. Experimental results demonstrate that higher temperature significantly accelerates the dissolution of the primary γ′ (γ′_p) phase and grain growth. At 180 min, the average grain size rapidly grows from 4.59 μm at 1080 °C to 14.09 μm at 1110 °C. In contrast, the impact of holding time on the microstructure diminishes after 30 min. At 1080 °C, the average grain size grows from 2.52 μm at 5 min to 4.95 μm at 30 min, after which it remains relatively stable. Initially, the γ′_p phase hinders grain boundary migration and inhibits grain growth. However, its complete dissolution at high temperatures significantly promotes grain growth. Careful selection of preheating temperature can mitigate rapid grain growth before forging. Additionally, twins not only refine grains through nucleation and segmentation, but also hinder grain boundary migration in regions with high dislocation density, thereby alleviating grain growth. A model detailing the dissolution of the γ′_p phase during preheating is developed, with a correlation coefficient and average absolute relative error of 0.9947 and 9.15%, respectively. This model provides theoretical support for optimizing preheating temperatures and estimating initial microstructures prior to IF. Full article

Surface laser processing of metallic materials is known to be effective in improving wear resistance due to microstructure refinement and the associated hardening effect. However, the formation of cracks, which frequently accompanies such processing, remains a challenge. This work focusses on partial laser processing of Ni-based protective coatings as a method that could potentially reduce the risk of crack formation due to lower overall heat input and retaining softer material portions that facilitate stress redistribution. A fibre-optic laser with a wavelength of λ = 976 nm and beam oscillation capability was used. After laser processing at 175 W power, a 250 mm/min processing rate, and a 2 mm oscillation amplitude, coating hardness increased by ~1.49 times reaching 713 ± 19 HV0.2 value. Preheating the samples to 400 °C inhibited crack formation but partially reduced the quenching effect, providing a ~30% increase in coating hardness (631 ± 16NV0.2). The resistance to dry sliding wear was increased by ~2 times and to abrasive wear—by ~2.9 times. Partial laser treatment of 25%, 50%, and 75% of the surface area enhanced the coating’s wear resistance by 1.29, 2.13, and 2.81 time, respectively, indicating that when the processed surface area reaches 50% or more, wear resistance is primarily determined by the hardened regions and to a greater extent than what is expected based on the proportion of the treated area. Full article

The rehydroxylation (RHX) dating technique offers a promising method for determining the ages of ceramic materials, leveraging the time-dependent mass gain from water reabsorption after high-temperature firing. However, the reliability of RHX dating is under discussion in many cases, with its accuracy depending on the various component materials in ceramics. In the present study, we considered the incomplete removal of weakly bonded water molecules during the conventional preheating step at 105 °C, a phenomenon that may lead to inaccurate mass measurements and overestimates of age. In this study, we propose an enhanced experimental protocol incorporating thermogravimetric analysis (TGA) to identify and quantify interstitial water fractions within ceramics. For samples exhibiting significant water retention (>1%), we recommend preheating at relatively higher temperatures (up to 300 °C) to ensure complete water removal and a more accurate mass determination. This approach was tested on five archaeological samples, yielding improved consistency and agreement with independently known dates. The method highlights the importance of tailored preheating protocols in RHX dating of ancient ceramics. Full article

Although various studies on nitrous oxide as a prospective green propellant have been recently explored, a polyethylene nitrous oxide catalytic decomposition hybrid thruster was barely demonstrated due to an inordinately high catalyst preheating time of a heater, which led to the destruction of components. Therefore, hydrogen peroxide was used as a preheatant, a substance to preheat, with a dual-catalyst bed. The thruster with polyethylene (PE) as a fuel, N₂O as an oxidizer, H₂O₂ as the preheatant, Ru/Al₂O₃ as a catalyst for the oxidizer, and Pt/Al₂O₃ as a catalyst for the preheatant was arranged. A preheatant supply time of 10 s with a maximum catalyst bed temperature of more than 500 °C and without combustion and an oxidizer supply time of 20 s with a burning time of approximately 15 s were decided. Because the catalyst bed upstream part for decomposing the preheatant was far from the post-combustion chamber, the post-combustion chamber pressure increased and the preheatant mass flow rate decreased after a hard start during the preheatant supply time. Moreover, because the catalyst bed upstream part primarily contributed to preheating, the maximum catalyst bed temperature was less than the decomposition temperature of the preheatant during the preheatant supply time. Additionally, because the catalyst bed downstream part for decomposing the oxidizer was far from the post-combustion chamber, the post-combustion chamber pressure decreased and then increased during a transient state in the oxidizer supply time. Full article

Hydrogen peroxide (High Test Peroxide, HTP) emerges as a promising candidate for green space propulsion applications due to its lower toxicity compared to liquid conventional propellants such as hydrazine and nitrogen tetroxide. This study aims to optimize the performance and reliability of HTP monopropellant thrusters, focusing on catalyst bed stability, efficiency, and durability during extended steady-state operations. Key parameters, including catalyst bed packing, pellet size, bed load, and HTP concentration, were investigated in this study for their impact on the steady-state performance, using the pressure loss across the catalyst bed as an indicator of catalyst deterioration. Results indicate that an optimal pressure drop of 1–1.5 bar across the catalyst bed provides optimal stability and durability. To evaluate transient characteristics, effects of bed load, HTP concentration, and pre-heating temperature on thruster response times were investigated. Following the optimization process, a lifetime test with an HTP throughput of 6 kg was conducted to monitor performance variations over time. Additionally, the blowdown characteristics of the thruster were analyzed to assess performance under end-of-life conditions. The experiments in this study demonstrate that HTP monopropellant thrusters are viable candidates for reliable space missions, particularly for long-duration operations such as station-keeping maneuvers. Full article

This paper reports studies on the thermal chemistry of the flash pyrolysis (heating rate of 20,000 °C/s up to 800 °C) of non-fossil fuel carbon (NFF-C) waste (or refuse-derived fuel, RDF) in the context of using this as an alternative reductant for blast furnace ironmaking. Gas chromatography–mass spectrometry (GCMS) analysis linked to the pyrolyser was used to simulate the thermal processes that take place during injection in the blast furnace raceway, where material experiences extreme temperature (ca. 1000 °C) over very short residence times (<300 ms). Species identification and qualitative analysis of evolved species generated are reported. Whilst the pyrolyser uses flash heating of a static sample, a drop tube furnace was also employed to study a sample moving rapidly through a pre-heated furnace held at 1000 °C to enable reductant burnout rates to be measured. The overarching aim of this piece of work is to study the suitability of replacing fossil fuel with non-recyclable plastic and paper as blast furnace reductants. Full article