Yun Ji

Composting is a primary method for organic waste treatment, and ventilation is crucial for composting performance. The pipe design parameters influence ventilation efficiency, while the interactions between these parameters remain unclear. Conventional response surface methodology (RSM) is limited by discrete experimental points, potentially affecting optimization accuracy, whereas computational fluid dynamics (CFD) provides a spatially resolved analysis of airflow fields within the entire compost pile. Herein, this study combines RSM and CFD to exploit their complementary strengths for more reliable optimization. A 17-run Box–Behnken design (BBD) was conducted to evaluate compost maturity under different pipe design parameters, including pipe diameter (11, 12, 13 mm), adjacent orifice spacing increment (0.5, 0.75 and 1 cm) and orifice diameter (2, 2.5 and 3 mm). Meanwhile, CFD simulations were performed to quantitatively evaluate the effects of different design parameters on airflow distribution characteristics. An experimental validation was additionally conducted under the optimal configuration. Results indicated that the optimized design parameters reduced the coefficient of air speed variation (CASV) by 55.37%. Pipe diameter, adjacent orifice spacing and orifice diameter had significant effects on germination index and humus (p < 0.01), whereas the significance of the interaction terms differed among response variables. The influence ranking on germination index and humus was as follows: pipe diameter > adjacent orifice spacing > orifice diameter. To achieve maximum composting effectiveness, the optimal pipe design parameters were determined as an adjacent orifice spacing increment of 0.78 cm, an orifice diameter of 2.83 mm, and a pipe diameter of 12.71 mm. Relative to the 17 BBD experimental runs, these optimal parameters resulted in maximum observed improvements of 18.66 percentage points in final GI and 63.36 g/kg in final HS, while the humic acid-to-fulvic acid ratio increased by 1.27. This study provides a theoretical basis for optimizing compost ventilation pipe design and improving composting performance in aerobic composting systems.

Electro-hydrostatic actuators (EHAs) are increasingly deployed in modern aircraft due to their compact size, fast response, and high power-to-weight ratio. However, existing airborne QAR and EICAS data are typically recorded as independent parameters without explicit correspondence to system health states, making degradation assessment and remaining useful life (RUL) prediction challenging. To address this issue, this paper proposes a spatiotemporal degradation modeling framework, termed PreDyn-ST, based on multivariate time series (MTS) data. The method integrates SimCLR-based contrastive pretraining and a dynamic feature fusion mechanism to capture evolving temporal dependencies and spatial sensor correlations. Specifically, graph convolutional networks (GCNs) incorporating physical connectivity priors are employed for spatial modeling, while a Transformer extracts long-range temporal patterns. A learnable dynamic weighting mechanism adaptively balances spatial and temporal features during training. The adaptive behavior is further analyzed using correlation statistical index (CSI) curves for interpretability. Experimental validation on a self-developed EHA degradation test bench and the C-MAPSS benchmark dataset demonstrates that PreDyn-ST achieves competitive and stable prediction performance. In particular, the method shows robust performance under complex operating conditions such as FD004. These results indicate the effectiveness of the proposed framework for accurate and interpretable degradation modeling in aerospace applications.

This study investigates the motion and fragmentation of non-spherical particles in pipeline pneumatic conveying, using gangue particles as the research object. The effects of airflow velocity and particle shape on the picking characteristics, as well as the influence of elbow angle, airflow velocity, particle size, and air pressure on particle crushing, were analyzed through a combination of Computational Fluid Dynamics and Discrete Element Method (CFD-DEM) coupled simulations and experiments. Orthogonal experiments were conducted to determine the optimal combination of parameters for minimizing particle breakage rates and pipeline pressure drops. The results show that the airflow velocity significantly affects the pick-up rate of particles, while particle shape also plays a key role, with higher sphericity resulting in lower pick-up rates. Among the factors influencing particle breakage, airflow velocity has the most pronounced effect, followed by elbow angle and particle size, whereas air pressure has a relatively minor impact. In terms of the pressure drop inside the pipeline, all factors—airflow velocity, elbow angle, particle size, and air pressure—exert considerable influence, with air pressure being the most critical factor. The optimal configuration for minimizing both particle breakage and pressure drop was determined to be an elbow angle of 150°, particle size ranging from 7 to 11 mm, airflow velocity of 20 m/s, and air pressure of 0.4 MPa.

This article studies the influence of structural parameters of the optimization model for the gas–liquid mixing device of a fire truck (compressed air foam lift fire truck, model JP21/G2, made in China) on the liquid phase volume fraction, static pressure, velocity streamline, and the influence of smaller flow rates on the mixing effect. By using the computational fluid dynamics (CFD) software FLUENT 2021 R2, numerical simulations were conducted on the fluid domain model of the gas–liquid mixing device of the JP21/G2 fire truck. The changes in the mixing effect time dimension, liquid phase volume fraction, static pressure, and velocity streamline inside the gas–liquid mixing device were obtained. The optimal mixer structure combination in practical applications was inferred through orthogonal experiments, and the influence of flow rate on the optimal pipe diameter and shortest mixing distance was obtained through variable flow rate simulation experiments. The numerical simulation results show that the presence of bent pipes in the JP21/G2 real vehicle model hinders the gas–liquid mixing process. A straight pipe section of at least 8 m was added after the bent pipe to ensure the mixing effect. The optimal parameter combination for orthogonal experiments had an accurate value of 50°-50°-220 mm. Under the same pipe diameter, using a larger flow rate can achieve better mixing effects.

In this paper, the Computational Fluid Dynamics–Discrete Element Method (CFD-DEM) coupling method was used to simulate the pneumatic transport of pebble particles in a three-blade spiral tube. The results showed that the flow field distribution rotated along the circumference after loading. The maximum velocity of the flow field after loading was manifested as rotation along the circumference. In addition, the swirl intensity decreased exponentially with the increase in conveying distance, and the maximum swirl intensity had a saturation value. After reaching the saturation value, it is not evident that increasing the initial air velocity significantly affected swirl variation. The smaller the pitch, the greater the initial swirl intensity. The swirling flow was conducive to the fluidization of particles, but it would bring a significant energy loss. Increasing the swirl can increase the degree of particle dispersion. There is an optimal tangential airflow velocity, which allows the particles to fully spin and stay in the suspension zone without being thrown onto the pipe wall by excessive centrifugal force. At this time, the energy efficiency reaches the highest level. A 5.87 m/s velocity was deemed the optimal tangential airflow velocity for conveying 3 mm particles.

Pneumatic conveying is widely used in coal mining. As the lowest conveying velocity of materials, the pickup velocity is the key to the study of gas–solid two-phase flow. In this study, the pickup velocity of pebble particles was experimentally investigated. When the particle size is 3–9 mm, the airflow velocity was found to suitably describe the results as a function of the pickup velocity and have a high correlation. When the swirl number is 0.2, the optimal swirl number was found for which the highest particle pickup ratio was observed. Based on four different methods, namely, visual observation, mass weighing, coefficient of difference analysis, and determination of the peak-average ratio of the pressure drop in the flow field to measure the pickup velocity of the spraying material, the results showed that the accuracy of the particle pickup velocity obtained through visual observation was the lowest, and when the mass–loss rate of the particle was selected as the measurement index of the pickup velocity, the accuracy was the highest. The results will help to realize the long-distance transportation of spraying materials in inclined roadway under the shaft.

In order to solve the problem of uneven air inlet flow in the guide channel of autoclave, three optimization schemes for the guide plate were proposed. The flow field in the guide channels of autoclave was simulated and analyzed by the realizable k-epsilon turbulence model and dynamic boundary method. The results show that the three optimization schemes have a certain effect on solving the problem of uneven air inlet flow in each guide channel, but some of them also have some negative effects. The integration of the three optimization schemes effectively increases the total air inlet flow of the guide channels; the increase ratio reaches 4.15%, improves the flow-field characteristics at the outlet of the guide channels and greatly reduces the difference in the air inlet flow in the left and right guide channels; the difference ratio drops from 62.61% to 5.37%.

Elbows are widely used in various industrial fields and are important for industrial applications. In this study, Eulerian coupling method was used to address the fluid-particle, and particle-particle interactions in a gas-solid two-phase flow while considering the effects of lifting angle, airflow velocity, and solid mass flow rate. The Hertz-Mindlin contact model and empirical Erosion/Corrosion Research Center erosion model were used to predict erosion in a lifting elbow, and the erosion ratio was used for validation with the experimental results. Experimental results indicated that the established model herein is accurate with different airflow velocities and lifting angles. The orthogonal design method was applied to the simulation scheme design, and range and variance analyses were used for the analysis of the results. Results indicated that the solid mass flow rate most affected elbow erosion comparing with lifting angles and airflow velocities. Additionally, the effect of the elbow lifting angle on the erosion mechanism was considered, and results indicated that the maximum erosion region is independent of the airflow velocity, lifting angle, and solid mass flow rate.