High-performance aeroengine design is an important component of modern industry, and advanced sealing technology is a key technology to meet the engine fuel consumption rate, thrust-to-weight ratio, pollutant emission, durability, and lifetime. Reducing the internal airflow leakage of the engine through a sealing technology can improve the performance and efficiency of the engine. In this paper, the typical sealing technology for an aeroengine is introduced in more detail, including the structural characteristics and use limitations of the labyrinth seal, brush seal, honeycomb seal, gas film face seal, and cylindrical gas film seal. It focuses on the development history, typical structure type, working principle, basic technology research method, steady-state performance, dynamic characteristics, multi-physical field coupling, structural deformation, experimental testing, processing technology. Finally, it summarizes the problems and future development trends of the current application... [more]

Nanofluid Minimum Quantity Lubrication (NMQL) is a resource-saving, environmentally friendly, and efficient green processing technology. Therefore, this study employs Minimum Quantity Lubrication (MQL) technology to conduct milling operations on aerospace 7050 aluminum alloy using soybean oil infused with varying concentrations of MoS2 and MWCNTs nanoparticles. By measuring cutting forces, cutting temperatures, and surface roughness under three different lubrication conditions (dry machining, Minimum Quantity Lubrication, and nanofluid minimum quantity lubrication), the optimal lubricating oil with the best lubrication performance is selected. Under the conditions of hybrid nanofluid minimum quantity lubrication (NMQL), as compared to dry machining and Minimum Quantity Lubrication (MQL) processing, surface roughness was reduced by 48% and 36% respectively, cutting forces were decreased by 35% and 29% respectively, and cutting temperatures were lowered by 44% and 40%, respectively. Unde... [more]

Gas leaks can cause disasters at process sites, including fires and explosions, and thus, effective gas-leak detection systems are required. This study investigated the limitations of conventional detectors and introduced an innovative ultrasonic sensor-based approach for continuous monitoring. A new configuration for a stationary remote ultrasonic gas-leak monitoring system is proposed. The selected material was 1-Butene. The detection probability was assessed through a simulation based on a gas-leak scenario, detailing the selection criteria for leak sites and simulation conditions. Computational fluid-dynamics (CFD) simulations were used to evaluate the detection capability of the existing system, whereas Monte Carlo simulations were used to compare it with the proposed ultrasonic system. The CFD simulation was performed by setting the lower detection limit of the concentration-measurement-type gas detector to 600 ppm, and the leak-detection time was approximately 8.895 s. A Monte C... [more]

The rational structural design of polycrystalline diamond compact (PDC) cutters effectively enhances the performance of drill bits in rock fragmentation and extends their service life. Inspired by bionics, a bionic PDC cutter was designed, taking the mole claw toe, shark tooth, and microscopic biomaterial structures as the bionic prototypes. To verify its rock-breaking effectiveness, the finite element method was employed to compare the rock-breaking processes of the bionic cutter, triangular prism cutter, and axe cutter. The study also investigated the influence of different back rake angles, cutting depths, arc radii, and hydrostatic pressures on rock breaking using the bionic cutter. Prior to this, the accuracy of the finite element model was validated through laboratory tests. Subsequently, a drill bit incorporating all three types of cutters was constructed, and simulations of rock breaking were conducted on a full-sized drill bit. The results demonstrate that the bionic cutter ex... [more]

Model uncertainty creates a largely open challenge for industrial process control, which causes a trade-off between robustness and performance optimality. In such a case, we propose a generalized conditional feedback (GCF) system to largely eliminate conflicts between robustness and performance optimality. This approach leverages a nominal model to design an optimal control in the virtual domain and defines an ancillary feedback controller to drive the physical process to track the trajectory of the virtual domain. The effectiveness of the proposed GCF scheme is demonstrated in a simulation for six typical industrial processes and three model-based control methods, and in a half-quadrotor system control test. Furthermore, the GCF scheme is open to existing optimal control and robust control theories.

A waste material cannot truly be called waste when the procedures and technologies have been invented and developed to exploit and utilize it [...]

In order to achieve efficient photocatalytic N2 reduction activity for ammonia synthesis, a photochemical strategy was used in this work. UiO-66 was prepared through the solvothermal method and further loaded with Au nanoparticles (Au NPs) onto the UiO-66 (Zr) framework. The experimental results verified that there were metal−support interactions between Au NPs and UiO-66; this could facilitate charge transfer among Au NPs and UiO-66, which was beneficial to enhance the photocatalytic activity. The best N2 fixation effect of Au/UiO-66 with a loading of 1.5 wt% was tested, with a photocatalytic yield of ammonia of 66.28 μmol g−1 h−1 while maintaining good stability. The present work provides a novel approach to enhancing photocatalytic N2 fixation activity by loading NPs onto UiO-66.

It is important for data modeling to comply with a data observation window of physical variables behind the data. In this paper, a multivariate data alignment method is proposed to follow different time scales and different role effects. First, the length of the sliding windows is determined by the frequency characteristics of the time-series reconstruction. Then, the time series is aligned to the length of the window by a sequence-to-sequence neural network. This neural network is trained by replacing the loss function with dynamic time warping (DTW) in order to prevent the losses of the time series. Finally, the attention mechanism is introduced to adjust the effect of different variables, which ensures that the data model of the matrix is in accord with the intrinsic relation of the actual system. The effectiveness of the approach is demonstrated and validated by the Tennessee Eastman (TE) model.

This study reports a novel hybrid model for the prediction of six critical process variables of importance in an industrial-scale FCC (fluid catalytic cracking) riser reactor: vacuum gas oil (VGO) conversion, outlet riser temperature, light cycle oil (LCO), gasoline, light gases, and coke yields. The proposed model is developed via the integration of a computational particle-fluid dynamics (CPFD) methodology with artificial intelligence (AI). The adopted methodology solves the first principle model (FPM) equations numerically using the CPFD Barracuda Virtual Reactor 22.0® software. Based on 216 of these CPFD simulations, the performance of an industrial-scale FCC riser reactor unit was assessed using VGO catalytic cracking kinetics developed at CREC-UWO. The dataset obtained with CPFD is employed for the training and testing of a machine learning (ML) algorithm. This algorithm is based on a multiple output feedforward neural network (FNN) selected to allow one to establish correlations... [more]

Corrosion fatigue test is the most direct and effective method to study the corrosion fatigue characteristics of sucker rod. At present, the commonly used test method is the high frequency fatigue test, but the working state of sucker rod is typical low-frequency and high-cycle corrosion fatigue, and the test with high frequency will reduce the impact of corrosion. Alloy steel 4330 is widely used in coalbed gas well high strength sucker rod, but the research on its low frequency corrosion fatigue life is relatively few. Therefore, in this paper, the corrosion fatigue test method of axial low-frequency and high-cycle was adopted to study the corrosion fatigue characteristics of 4330 steel sucker rod through the corrosion fatigue test under different typical corrosion media, temperature, and stress levels. The results show that the fatigue life of 4330 sucker rod drops sharply when the Cl− concentration in high salinity well fluid exceeds the threshold value of 155 mg/L. When this thresh... [more]

This paper has proposed a comprehensive indicator based on principal component analysis (PCA) for diagnosing the state of anaerobic digestion. Various state and performance variables were monitored under different operational modes, including start-up, interruption and resumption of substrate supply, and impulse organic loading rates. While these individual variables are useful for estimating the state of anaerobic digestion, they must be interpreted by experts. Coupled indicators combine these variables with the effect of offering more detailed insights, but they are limited in their universal applicability. Time-series eigenvalues reflected the anaerobic digestion process occurring in response to operational changes: Stable states were identified by eigenvalue peaks below 1.0, and they had an average below 0.2. Slightly perturbed states were identified by a consistent decrease in eigenvalue peaks from a value of below 4.0 or by observing isolated peaks below 3.0. Disturbed states wer... [more]

With the continuous breakthrough of natural language processing, the application of intelligent question-answering technology in electric power systems has attracted wide attention. However, at present, the traditional question-answering system has poor performance and is difficult to apply in engineering practice. This paper proposes an improved BERTserini algorithm for the intelligent answering of electric power regulations based on a BERT model. The proposed algorithm is implemented in two stages. The first stage is the text-segmentation stage, where a multi-document long text preprocessing technique is utilized that accommodates the rules and regulations text, and then Anserini is used to extract paragraphs with high relevance to the given question. The second stage is the answer-generation and source-retrieval stage, where a two-step fine-tuning based on the Chinese BERT model is applied to generate precise answers based on given questions, while the information regarding document... [more]

In order to solve the problem of frequent pressure fluctuations caused by fluid quantity variation in hydraulic support liquid supply systems and the pressure response lag caused by long-distance pipelines, an online updated radial basis function neural network (RBF neural network) control method was proposed for the long-distance liquid supply system. Based on the analysis of the measured pressure fluctuations of the mining face and the process of the stable pressure liquid supply system, the influencing factors of the stable pressure liquid supply flow demand were obtained. The flow set of the stable pressure liquid supply system was established and fitted in the SimulationX−Simulink co-simulation model and the online correction was carried out by using the characteristics of the repeated action of the hydraulic support. Finally, the online updating RBF neural network regulator was established to realize the pressure regulator control of the pumping station, and the experimental plat... [more]

This study endeavors to enhance the operational efficiency of extant coal-fired power plants to mitigate the adverse environmental impact intrinsic to the prevalent utilization of coal-fired power generation, which is particularly dominant in China. It focuses on the assessment and optimization of continuous denitrification systems tailored for a 1000 MW ultra-supercritical pulverized coal boiler. The extant denitrification framework encounters challenges during startup phases owing to diminished selective catalytic reduction (SCR) inlet flue gas temperatures. To ameliorate this, three retrofit schemes were scrutinized: direct mixing of high-temperature flue gas, bypass flue gas mixing, and high-temperature flue gas mixing with cold air. Each option underwent meticulous thermodynamic computations and comprehensive cost analyses. The findings elucidated that bypass flue gas mixing, involving the extraction and blending of high-temperature flue gas, emerged as the most financially pruden... [more]

A time−frequency residual convolution neural network (TFRCNN) was proposed to identify various rolling bearing fault types more efficiently. Three novel points about TFRCNN are presented as follows: First, by constructing a double-branch convolution network in the time domain and the frequency domain, the respective features in the time domain and the frequency domain were extracted to ensure the rich and complete feature representation of raw data sources. Second, specific residual structures were designed to prevent learning degradation of the deep network, and global average pooling was adopted to improve the network’s sparsity. Third, TFRCNN was better than the other models in terms of prediction accuracy, robustness, generalization ability, and convergence. The experimental results demonstrate that the prediction accuracy rate of TFRCNN, trained using mixing load data, reached 98.88 to 99.92% after optimizing the initial learning rate and choosing the optimizer and loss function.... [more]

Effectively managing the quality of iron ore is critical to iron and steel metallurgy. Although quality inspection is crucial, the perspective of sintered surface identification remains largely unexplored. To bridge this gap, we propose a deep learning scheme for mining the necessary information in sintered images processing to replace manual labor and realize intelligent inspection, consisting of segmentation and classification. Specifically, we first employ a DeepLabv3+ semantic segmentation algorithm to extract the effective material surface features. Unlike the original model, which includes a high number of computational parameters, we use SqueezeNet as the backbone to improve model efficiency. Based on the initial annotation of the processed images, the sintered surface dataset is constructed. Then, considering the scarcity of labeled data, a semi-supervised deep learning scheme for sintered surface classification is developed, which is based on pseudo-labels. Experiments show th... [more]

The study of crude oil oxidation characteristics is fundamental to the design of ignition in situ combustion. Experimentation is the most crucial method for studying the oxidation characteristics of crude oil. Aiming to address the challenges posed by high temperature, high pressure, and rapid temperature changes during the combustion of crude oil, a dynamic simulation system for high-temperature and high-pressure ignition is designed. In order to study the oxidation characteristics of the crude oil ignition process, we conducted experiments using a high-temperature and high-pressure dynamic ignition simulation device. The experiments focused on determining the ignition point of crude oil under different pressure conditions, oil−water ratios, heating rates, gas injection rates, and other relevant characteristics. The kinetic model for the oxidation process of crude oil ignition was established. The kinetic parameters were calculated for different ignition conditions and the apparent ac... [more]

Consideration of upstream congestion caused by busy downstream machinery, as well as transportation time between different production stages, is critical for improving production efficiency and reducing energy consumption in process industries. A two-stage hybrid flow shop scheduling problem is studied with the objective of the makespan and the total energy consumption while taking into consideration blocking and transportation restrictions. An adaptive objective selection-based Q-learning algorithm is designed to solve the problem. Nine state characteristics are extracted from real-time information about jobs, machines, and waiting processing queues. As scheduling actions, eight heuristic rules are used, including SPT, FCFS, Johnson, and others. To address the multi-objective optimization problem, an adaptive objective selection strategy based on t-tests is designed for making action decisions. This strategy can determine the optimization objective based on the confidence of the objec... [more]

The soil-water retention curve (SWRC) is fundamental in presenting the hydromechanical characteristics of soils, which are closely connected with soil deformation, permeability, and shear strength. The Fredlund and Xing (FX) model accurately fits the SWRCs of different types of soils over a wide suction range. However, experimental comparisons of the fitting showed that the obtained parameters differ from the physical meanings assigned by Fredlund and Xing. To address this issue, the traditional FX model has been improved, resulting in the proposal of a two-step FX model. Firstly, the FX model is applied without taking the correction coefficient c(ψ) into account to fit the measured SWRC. The values for α, n, and m are then determined and substituted into the FX model to refit the experimental data. Finally, the last parameter Cr can be obtained. The curves resulting from these two steps have a good agreement with the experimental results, and the obtained parameters align better with... [more]

Aiming at addressing the problem of dust generated when grab is unloaded, the flow field characteristics of fugitive dust in an open space were studied and reflected its unstable and complex nonlinear dynamic process. Using coal, sand, and flour as research objects, an experimental model and measurement system for grab unloading were built, and the dust diffusion range, diffusion speed and direction, settling time, dust concentration, and induced wind velocity at different measurement points were compared. The computational fluid dynamics−discrete element method (CFD-DEM) coupling method was adopted, the discrete phase model (DPM) of dust was established, the interaction of the particle, dust, and airflow fields during the unloading process of the grab was further studied, and the distribution and diffusion laws of the induced airflow and dust were obtained. The acquisition of flow field characteristics is of great significance for controlling and guiding the orderly deposition of dust... [more]

As one of the most ideal alternative fuels for internal combustion engines, methanol can achieve near-zero carbon emissions. The main problem of methanol application in compression combustion engines is the phase lag caused by its poor combustion characteristics, but under low load conditions, the fuel activity can be improved by adding the cetane number improver EHN (Isooctyl nitrate), and the dependence on intake heating can be reduced to a certain extent. Based on a three-dimensional CFD simulation, the effects of methanol injection parameters and the addition of EHN on the combustion characteristics of a four-stroke exhaust turbocharged diesel engine were studied in this paper. With or without EHN, the increase in injection pressure and the advance in injection timing lead to an increase in the peak temperature, pressure, and heat release rate, as well as a shortening of the combustion duration. Adding EHN witnesses reduced requirements for methanol ignition, including a decreased... [more]

Rare-earth elements (REEs) are crucial metals with limited global availability due to their indispensable role in various high-tech industries. As the demand for rare-earth elements continues to rise, there is a pressing need to develop sustainable methods for their recovery from secondary sources. Focusing on Exiguobacterium sp. SH31, this research investigates the impact of La, Eu, Gd, and Sm on its physiological performance and biosorption capacity. Tolerance was assessed at pHpzc from 7 to 8 with up to 1 mM rare-earth element concentrations. This study visualized the production of extracellular polymeric substances using Congo red assays and quantified them with ultraviolet−visible spectroscopy. Attenuated total reflectance Fourier transform infrared spectroscopy characterized the functional groups involved in metal interactions. The SH31 strain displayed significant rare-earth element tolerance, confirmed extracellular polymeric substance (EPS) production under all conditions, and... [more]

Understanding the influence of environmental boundary parameters on the through-flow characteristics of two-stage supercharged centrifugal compressors is the key to maximizing the power recovery potential of diesel engines at high altitudes. In this paper, the influence of the compressor through-flow characteristics on the full-load thermal cycle performance of a diesel engine under variable altitude is studied by means of tests and simulation. The results show that with the increase in altitude, the range of stable work flow decreases, and the pressure ratio of the plugging point changes greatly with altitude. The efficiency of the compressor with the same mass flow point decreases, and the highest efficiency point moves in the direction of the small flow range. With the goal of maximizing the torque of the diesel engine under full load and low speed, the key geometric parameters of the variable-altitude through-flow characteristics of the two-stage supercharged compressor were optimi... [more]

Detailed knowledge of the flow characteristics, bubble movement, and mass transfer is a prerequisite for the proper design of multiphase bioreactors. Often, mechanistic spatiotemporal models and computational fluid dynamics, which intrinsically require computationally demanding analysis of local interfacial forces, are applied. Typically, such approaches use volumetric mass-transfer coefficient (kLa) models, which have demonstrated their predictive power in water systems. However, are the related results transferrable to multiphase fermentations with different physicochemical properties? This is crucial for the proper design of biotechnological processes. Accordingly, this study investigated a given set of mass transfer data to characterize the fermentation conditions. To prevent time-consuming simulations, computational efforts were reduced using a force balance stationary 0-dimension model. Therefore, a competing set of drag models covering different mechanistic assumptions could be... [more]

One of the most widespread and risky pollutants in the environment is phenol. It is a by-product of many industrial, agricultural, and other anthropogenic activities. Microbial-assisted transformation, known as bioremediation, is an effective and cheap method for treating groundwater, soil, and sediments contaminated with phenol and its derivates. This study aims to assess the effect of the addition of a selected, pre-adapted bacterial strain Pseudomonas aureofaciens AP-9 on key kinetic, microbiological, and enzymological parameters of simulated bioremediation processes for the removal of phenol (250 mg/kg). The early effect of adding this microbial biodegradant in contaminated sediments is insignificant. The effect of added bacteria is manifested at the 48th hour by a restructuring of the microbial sediment communities and an increase in the number of cultivated microorganisms. This preparation of the sediment communities for a prolonged detoxification process is also confirmed by the... [more]