With the pervasive integration of artificial intelligence into all aspects of human life, talent emerges as a primary resource. Upon analysing the current state of talent training in higher education institutions, iss...
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Combining pulverized coal gasifiers with cement kiln production is promising for application in low-cost and efficient NO *** paper presents a pulverized coal gasifier catalytic denitration technique and investigates ...
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Combining pulverized coal gasifiers with cement kiln production is promising for application in low-cost and efficient NO *** paper presents a pulverized coal gasifier catalytic denitration technique and investigates the homogeneous reduction(by CO and CH_(4))and heterogeneous catalytic reduction(by coke,CaO,MgO,and Fe_(2)O_(3))of NO.A combination of Chemkin simulations and fixed-bed experiments is used to elucidate the reaction pathways and key intermediates of NO reduction by carbon-based *** addition,the activation energies for different catalyst combinations were analyzed via reaction *** results demonstrate that the presence of small amounts of O_(2) inhibits NO reduction by CO but promotes NO reduction by CH_(4).The NCO·radical is essential for the NO reduction process,and the generation of this radical depends on the CH_(4) cleavage intermediate and O·*** and Fe_(2)O_(3) exhibit more significant catalytic effects on NO reduction by carbon-based gases than the other catalysts *** presence of a small amount of O_(2) in the reacting gas mixtures facilitates the NO reduction *** activation energy is reduced to 1.02 kJ/mol,and the NO conversion reaches 99.80%when the catalyst is C+CaO+MgO+Fe_(2)O_(3) and the gas composition is CO+CH_(4)+O_(2).This work provides theoretical support and data recommendations for the use of pulverized coal gasifiers for the denitrification of cement kilns.
The transient electromagnetic method (TEM) is widely used in geophysical exploration. In TEM data interpretation, nonlinear inversion plays an important role. However, traditional TEM nonlinear inversion adopts the OC...
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In order to improve the efficiency of indoor mobile robots in locating and segmenting environmental instances, an instance segmentation method based on RTMDet is proposed. Firstly, the more powerful ConvNeXt V2 is use...
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Deep Learning has been widely used to model soft sensors in modern industrialprocesses with nonlinear variables and uncertainty. Due to the outstanding ability for high-level feature extraction, stacked autoencoder (...
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Microstrip antenna as a kind of receiver front-end equipment of microwave energy transmission system, which plays an important role on the overall transmission efficiency of the system. Conventional solid metal antenn...
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sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for th...
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Due to noise disturbance, sensor drift, and some circumstance factors, process data are unavoidably contaminated with uncertainty, which may destroy the correlation structure of original data and make traditional proc...
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This study proposes a low-carbon operational optimization framework for fluid catalytic cracking (FCC) units and conducts a comprehensive evaluation of their economic performance, energy utilization, and environmental...
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ISBN:
(数字)9798350389807
ISBN:
(纸本)9798350389814
This study proposes a low-carbon operational optimization framework for fluid catalytic cracking (FCC) units and conducts a comprehensive evaluation of their economic performance, energy utilization, and environmental impacts. First, a low-carbon energy-saving operational optimization framework was developed to enhance the economic benefits of FCC units while exploring their carbon reduction potential. Subsequently, a surrogate-assisted model based on an automated machine learning (AutoML) framework was constructed to reduce computational costs. A carbon tax scenario was then introduced, converting CO 2 emissions into carbon tax values. This approach can improve the computational efficiency of the multi-objective optimization problem. The experimental results demonstrate that optimizing operational conditions increased unit-time profits by 0.5%, reduced CO 2 emissions by 1088.92 kgCO 2 eq/h, and decreased wind energy and steam energy consumption by 627.67 m 3 /h and 324.28 m 3 /h, respectively. The scientific optimization of operational parameters enhances production efficiency while mitigating environmental impacts, providing valuable guidance for energy conservation and emissions reduction in industrialprocesses and supporting sustainable development.
With the rapid development of space technology, the demand for satellite reliability is getting higher and higher. Momentum wheel is a key component of satellite attitude controlsystem, and its reliability is an impo...
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With the rapid development of space technology, the demand for satellite reliability is getting higher and higher. Momentum wheel is a key component of satellite attitude controlsystem, and its reliability is an important factor affecting the life of satellite. The condition monitoring of momentum wheel bearing (MWB) is of great significance to ensure the long life and high reliable operation of the satellite. In this paper, a new monitoring method based on multivariate statistics and canonical variable analysis (CVA) is proposed, and a new health degree function is defined from both dynamic and static aspects. First, the time-frequency domain analysis technique is used to extract the features of MWB in time domain, frequency domain and time-frequency domain, and the multi-domain high-dimensional health condition feature set is constructed. Then, in order to reduce the complexity of the problem, feature reduction is realized based on CVA. On the basis of considering steady-state error and sliding interval variance (SIV), the health degree (HD) characterizing the performance condition of MWB is defined. Finally, the experimental results based on the bearing test-bed show that the proposed method is feasible and effective, and the data-driven health condition monitoring of satellite momentum wheel bearing is realized.
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