A swirling burner with a variable inner secondary air (ISA) flaring angle β is proposed and a laboratory scale opposed-firing furnace is built. Temperature distribution and NO_x emission are designedly measured. The combustion characteristics affected by variable β are experimentally evaluated from ignition and burnout data. Meanwhile, NO_x reduction by the variable β is analyzed through emissions measurements. Different inner/outer primary coal-air concentration ratios γ, thermal loads and coal types are considered in this study. Results indicate that β variation provides a new approach to promote ignition and burnout, as well as NO_x emission reduction under conditions of fuel rich/lean combustion and load variation. The recommended β of a swirling burner under different conditions is not always constant. The optimal β_opt of the swirling burner under all conditions for different burning performance are summarized in the form of curves, which could provide reference for exquisite combustion adjustment.

Aiming at obtaining the application characteristics of more nanofluidic stuffing to enrich the database of nanofluidic packer rubber, three zeolite-based nanofluidic types of stuffing with water, glycerin, and a saturated aqueous solution of KCl (hereinafter referred to as saturated KCl solution) as the functional liquids were studied using experiments. The results showed that all the three zeolite-based nanofluidic stuffing types could be applied as stuffing for nanofluidic packer rubber. The setting pressure ranges for zeolite/water, zeolite/glycerin, and zeolite/saturated KCl solution stuffing were 21.71 to 30.62 MPa, 15.31 to 23.57 MPa, and 27.50 to 38.83 MPa, and the specific deformation quantities of the three stuffing types were 72.76, 102.07, and 77.54 mm³∙g⁻¹, respectively. In zeolite/saturated KCl solution stuffing, the number of liquid molecules retained in the nanochannels was the minimum; thus, this stuffing type was the most stable during application. The order of the equivalent surface tensions of the three zeolite-based stuffing types in the confined nanochannels was consistent with the order of the gas–liquid surface tensions in the bulk phase. The equivalent surface tension, which reflected the interaction between liquid–solid phases, dominated the pressure threshold, the deformation capacity, and the stability of nanofluidic stuffing. This research study provided data support for the application of nanofluidic packer rubber.

Gaseous phase plays roles in a liquid/nanoporous system during application that adequate attention should be paid to the gaseous effects and the nanoscale gas-liquid interaction. In the present study, two glycerol/ZSM-5 zeolite systems with different amount of residual gas are compared by performing a series of experiments. Influences of loading rate, as well as system temperature on the gas-liquid interactions, are studied. Results show that vacuum degassing pretreatment is required to obtain a reversible and stable energy absorption system. Moreover, the influence of gas on a liquid/nanoporous system is found to mainly act on the liquid outflow. After the routine vacuum degassing pretreatment, the residual air that is left in the nanopores is around 0.9014 nm^–3 per unit specific pore volume, as presented in the current study. During compression, the existing gas left in the nanochannel tends to gather into the gas cluster, which further promotes the liquid outflow during unloading. However, excessively dissolved gas may reduce the driving force for liquid outflow by breaking the continuity of the liquid molecular chain in nanochannel. Consequently, small bubbles as a labile factor in the system must be excluded for the steady use of the system. This work sheds some light on the effect of the amount of residual gas on the liquid/nanoporous system and gives guidance on the pretreatment of the liquid/nanoporous material mixture before encapsulating.

A nanofluidic energy absorption system (NEAS) is composed of nanoporous material and functional liquid with high energy absorption density. Applying an electric field to adjust the energy absorption characteristics of a nanofluidic system will open broader prospects for its application. In the current work, ZSM-5 zeolite was adopted as the nanoporous material and water, a 25% KCl solution, and a saturated KCl solution were adopted as functional liquids to configure NEASs. Pressure-induced infiltration experiments were carried out to study the infiltration and defiltration characteristics of the NEASs under the action of an applied electric field. The results show that the introduction of an applied electric field can weaken the hydrogen bonds between molecules, thus reducing the equivalent surface tension and contact angle, changing the infiltrability of liquid molecules into the nanopores, and reducing the infiltration pressure of the system. In an electrolyte solution/zeolite system, the anions and cations move close to the two plate electrodes under the action of an external electric field, and the fluid properties in the central zone of the pressure chamber are close to the water/zeolite system. For both an ultra-low conductivity liquid and an electrolyte solution/zeolite system, applying an electric field can effectively improve the relative outflow rate of liquid, thus improving the reusability of the system.

A nanofluidic system consists of a nano-porous medium and functional liquid, which demonstrates a higher energy absorption density compared to conventional systems for energy absorption. Alterations in the composition of the functional liquid can significantly impact the properties of a nanofluidic system. In this paper, the widely used zeolite ZSM-5 was chosen as the porous medium to establish a nanofluidic system. Three distinct electrolyte solutions, namely KCl aqueous solutions, NaCl aqueous solutions and MgCl₂ aqueous solutions were employed as functional liquids while pure water served as the reference condition for configuring four kinds of nanofluidic systems. Pressure-induced percolation experiments were performed on the four zeolite-based systems. The difference in the infiltration process between the electrolyte solution systems and the deionized water system has been ascertained. The effect of the ion size on the infiltration and defiltration process has been determined. The results show that the introduction of ions induces a hydration effect, resulting in a higher critical infiltration pressure of the electrolyte solution system compared to an aqueous solution system. The magnitude of cation charge directly correlates with the strength of the hydration effect and the corresponding increase in critical infiltration pressure. Upon entering the nanochannel, the liquid infiltrates primarily in the form of ions rather than a cation hydration form. The larger the ion size, the shallower the penetration depth after entering the nanopore channel and the larger the corresponding relative outflow rate. The present work will provide valuable theoretical complementary and experimental data support for nanofluidic system applications.

Driven by global carbon neutrality targets, coal-fired power generation is undergoing substantial operational changes. Modern boilers must operate more flexibly while maintaining low emissions and reliable performance. This transition has increased the need for intelligent monitoring, operator-supervised optimization, and safety-constrained decision support. Using a reproducible search and screening procedure, this review examines the development of boiler intelligence across four interconnected technological stages. At the sensing layer, data-driven soft sensors support rapid prediction of flue gas emissions, while graph-structured spatiotemporal models are used to characterize flame and combustion states. At the modeling layer, physics-informed neural networks (PINNs) and proper orthogonal decomposition reduced-order models (POD-ROMs) are reviewed as routes for accelerating physical-field reconstruction. Surrogate models coupling computational fluid dynamics (CFD) with artificial intelligence (AI) provide another route to rapid prediction and can incorporate physical constraints. These fast field models can also serve as components of boiler digital twins for online assessment and operational guidance. They may also support early warning when abnormal conditions emerge. At the decision layer, reinforcement learning, model predictive control, and multi-objective optimization are reviewed for combustion and selective catalytic reduction (SCR) control. Because these applications are safety-critical, autonomous control must remain within actuator limits and established operating margins. Emission requirements and ammonia-slip constraints must also be satisfied. Safe deployment further requires fallback mechanisms, cybersecurity protection, and human supervision. Industrial application is still limited by data scarcity and lifecycle concept drift, while limited interpretability and simulator-to-real transfer create additional challenges. Edge latency and insufficient validation under abnormal conditions remain important barriers. Finally, industrial foundation models and large language models are discussed mainly as knowledge interfaces and operator-assistance tools rather than direct safety-critical controllers.