This research analyzes the co-pyrolysis of an under-utilized wetland plant Stenochlaena palustris residue and a low-rank coal (lignite). The objectives are to investigate the thermal behavior, synergistic interactions and their kinetic parameters. Three different mass ratios of Stenochlaena palustris (S) to lignite (L) were examined, namely 3:1 (SL31), 1:1 (SL11), and 1:3 (SL13). The thermogravimetry and derivative thermogravimetry (TG/DTG) analysis revealed the non-additive behavior, indicating an interactive process between biomass and lignite. The SL11 exhibited best synergy, two distinct DTG peaks, a steep decline in pre-exponential factor, and a low mass loss, which shows the inhibition of secondary reactions. These findings were further confirmed by fixed-bed pyrolysis experiment at 550 °C. The SL11 mixture produced a significantly higher yield of bio-oil and a lower char fraction. Apparent activation energy was found to decrease gradually as lignite composition increased. Order of reaction 0.5 fit the best in all the samples (R2 > 0.98). These results dispute the belief that the higher the volatile release, the larger the liquid yield and show that a moderate reactivity range, between moderate pre-exponential factor and controlled mass loss rate, gives the maximum liquid production for SL11. These results validate the fact that the co-pyrolysis of Stenochlaena palustris residue and lignite, especially in an equimolar ratio, represents an effective approach of upgrading both feedstocks. The process improves production of bio-oil. This integrated co-processing provides a long-term solution of valorization of biomass residues and low-rank coal, thus contributing the development of more resource efficient and circular energy economy.
This article presents a high-fidelity numerical investigation of magnetohydrodynamic (MHD) buoyancy-driven transport of an Al_2O_3 –water nanofluid inside a wavy closed isosceles triangular cavity. We employ a customized, non-orthogonal algebraic coordinate transformation mapped onto a custom discrete finite element method (DFEM) solver to eliminate boundary staircase errors and capture steep localized gradients near the corrugated bottom wall. To address the predictive limits of legacy constant-property models, we implement and contrast two mathematical frameworks: the classical Maxwell–Brinkman formulations and the highly non-linear, temperature-dependent empirical Khanafer–Vafai experimental framework. The parametric space is systematically analyzed across Rayleigh numbers ( 10^3≤Ra≤ 10^6 ), Hartmann numbers ( 0 ≤Ha≤ 100 ), and nanoparticle volume fractions ( 0 ≤ϕ≤ 0.06 ). Our computational results quantitatively reveal that classical homogeneous models consistently underpredict the convective heat transfer enhancement by up to 7.2% under high-buoyancy states, failing to resolve localized micro-convective thermal paths. We also characterize the coupled interactions of Lorentz damping and geometric modifications, identifying a critical Hartmann threshold ( Ha≈ 50 ) where electromagnetic forces completely suppress boundary layer geometric perturbations. These findings establish a mathematically rigorous baseline for active-passive thermal control optimizations in highly restricted physical domains, directly applicable to the thermal management of attic-shaped roofs, wedge-shaped electronic heat sinks, and triangular solar cavity receivers.
Rapid advances in AI and electronics have dramatically increased device integration and computing power, causing surging heat flux densities and making thermal management a critical bottleneck for performance and reliability. Conventional microchannel heat sinks (MCHS) under laminar flow suffer from excessive thermal boundary layer growth, limited convective heat transfer, and flow maldistribution. To address these issues, passive-enhanced heat transfer techniques have gained prominence in MCHS research, due to their zero extra energy consumption, structural simplicity, and ease of integration. Single-phase microchannel flow is more mature and offers superior stability. This paper establishes a systematic framework for a comprehensive review and critical analysis of recent advances in passive enhancement techniques for single-phase MCHS. Diverging from existing reviews, it classifies enhancement strategies into three major approaches: channel configuration optimization, internal enhancement structures, and heat transfer fluid optimization. Within this framework, the physical mechanisms, performance characteristics, and practical trade-offs of each method are detailed. The review summarizes the strengths and limitations of current technologies, highlights multi-mechanism synergy as a crucial future direction, and analyzes critical challenges including the trade-off between heat transfer enhancement and flow resistance and the lack of experimental validation. A forward-looking outlook is also provided, emphasizing the adoption of advanced manufacturing technologies, a robust evaluation system, and the translation of basic research into engineering applications, offering theoretical guidance and engineering references for developing next-generation high-performance, low-power MCHS.
Water scarcity and the intermittency of solar energy motivate hybrid solar stills that recover both heat and electricity. However, published gains are difficult to compare because studies use different climates, basin depths, reference areas, operating periods, and efficiency definitions. This critical structured review evaluates photovoltaic/thermal (PV/T) integration, phase change materials (PCMs), sensible and porous storage media, heat exchangers, nanofluids and selective coatings, cover cooling, Internet of Things (IoT) monitoring, artificial intelligence (AI), and multi-technology water-power systems. The evidence was organized by physical enhancement mechanism and assessed using normalized daily productivity, thermal and electrical performance, system complexity, durability, and economic reporting. Across the reviewed literature, conventional still productivity of approximately 2–5 L m−2 day−1 is frequently increased to reported ranges of 3.5–7.5 L m−2 day−1. Multi-technology hybrids and PV/T systems provide the broadest functionality, whereas PCMs extend operation after sunset and passive porous media offer lower-cost improvements. These ranges are descriptive rather than pooled effect estimates because uncertainty and test conditions are reported inconsistently. The review contributes a physics-based interpretation, a transparent cross-study comparison framework, a proposed unified water-energy-quality score, and deployment guidance. The analysis shows that net auxiliary energy, water quality, scaling, corrosion, sensor reliability, cybersecurity, life-cycle impacts, and long-term field validation must be reported before laboratory improvements can support commercial selection in arid and remote regions.
As people pay more and more attention to sports health and energy consumption, the research of motion posture monitoring and heat consumption simulation based on target recognition and infrared thermal imaging technology becomes particularly important. The aim of this study is to develop a real-time monitoring system, which combines infrared thermal imaging and target recognition technology to realize the monitoring of human motion posture and the simulation analysis of thermal energy consumption. The study reveals the limitations of the existing technology and focuses on the design of a real-time monitoring system. The hardware and software design of the system fully consider the convenience of human–computer interaction and high efficiency of data processing. The precise monitoring and analysis of human motion state is realized by establishing the model of tracking and recognition of moving target. System test results show that the developed model has high accuracy and real-time performance in moving target recognition. In terms of infrared thermal imaging analysis technology, this study deeply discusses the extraction method of infrared thermal imaging features, and optimizes the recognition algorithm to improve the accuracy of target analysis. Recognition and comparison tests further validate the effectiveness of the improved algorithm and provide theoretical support for the application of thermal imaging technology in motion monitoring. Aiming at the simulation research of energy consumption, we built the heat energy consumption model, analyzed the energy metabolism in the process of human movement, and designed the corresponding energy consumption simulation training plan. The simulation results show that the use of infrared thermal imaging technology can effectively evaluate the heat energy consumption during exercise and provide scientific basis for daily exercise guidance.
