The hydrogen produced ( ) in the Catalytic Naphtha Reforming (CNR) is important in quantity and quality, for the feedback of the process and for supplying the hydrotreatment processes in current refineries. In this work it is presented a study by process simulation using ® for finding operative transitional modes that simultaneously improve quality of the reformate and hydrogen production of the CNR. The operative conditions that were studied correspond to the recirculation ratio of hydrogen/hydrocarbon ( ), with values between 2 and 6, and the temperature (), between 450 and 525 °C, in order to determining the best operative transitional route from the initial operative state to a local improved state, applying the method of superposition of response surfaces and criteria assessment of improvement in quality and quantity of hydrogen produced. A numerical multi-objective operative improvement analysis was performed resulting the objective variables as: Research Octane Number (RON) = 90.72, mass fraction of produced ( ) = 2.9, quality of recycled ( ) = 0.87, and quality of produced hydrogen ( ) = 0.9653. Experimental pilot plant data and full-scale industrial data were compared with simulations observing significant similitudes.
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http://dx.doi.org/10.1016/j.heliyon.2024.e41428 | DOI Listing |
Heliyon
January 2025
Instituto Mexicano del Petróleo, Eje Central Lázaro Cárdenas Norte 152, Col. San Bartolo Atepehuacán, C.P. 07730, Ciudad de México, Mexico.
The hydrogen produced ( ) in the Catalytic Naphtha Reforming (CNR) is important in quantity and quality, for the feedback of the process and for supplying the hydrotreatment processes in current refineries. In this work it is presented a study by process simulation using ® for finding operative transitional modes that simultaneously improve quality of the reformate and hydrogen production of the CNR. The operative conditions that were studied correspond to the recirculation ratio of hydrogen/hydrocarbon ( ), with values between 2 and 6, and the temperature (), between 450 and 525 °C, in order to determining the best operative transitional route from the initial operative state to a local improved state, applying the method of superposition of response surfaces and criteria assessment of improvement in quality and quantity of hydrogen produced.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Free-Space Optical Communication Technology Research Center, Harbin Institute of Technology, Harbin 150001, China.
To achieve real-time deep learning wavefront sensing (DLWFS) of dynamic random wavefront distortions induced by atmospheric turbulence, this study proposes an enhanced wavefront sensing neural network (WFSNet) based on convolutional neural networks (CNN). We introduce a novel multi-objective neural architecture search (MNAS) method designed to attain Pareto optimality in terms of error and floating-point operations (FLOPs) for the WFSNet. Utilizing EfficientNet-B0 prototypes, we propose a WFSNet with enhanced neural architecture which significantly reduces computational costs by 80% while improving wavefront sensing accuracy by 22%.
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January 2025
School of Biomedical Engineering, Tsinghua University, Shuang Qing Road, Beijing 100084, China.
Mastoidectomy is critical in acoustic neuroma surgery, where precise planning of the bone milling area is essential for surgical navigation. The complexity of representing the irregular volumetric area and the presence of high-risk structures (e.g.
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January 2025
Xi'an Power Supply Company, State Grid Shaanxi Electric Power Co., Ltd., Xi'an 710032, China.
Under the carbon peaking and carbon neutrality target background, efficient collaborative scheduling between distribution networks and multi-microgrids is of great significance for enhancing renewable energy accommodation and ensuring stable system operation. Therefore, this paper proposes a collaborative optimization method for the operation of distribution networks and multi-microgrids with shared energy storage based on a multi-body game. The method is modeled and solved in two stages.
View Article and Find Full Text PDFEntropy (Basel)
January 2025
Shandong Rongxin Group Co., Ltd., Zoucheng 273517, China.
In gas-to-methanol processes, optimizing multi-energy systems is a critical challenge toward efficient energy allocation. This paper proposes an entropy-based stochastic optimization method for a multi-energy system in a gas-to-methanol process, aiming to achieve optimal allocation of gas, steam, and electricity to ensure executability under modeling uncertainties. First, mechanistic models are developed for major chemical equipments, including the desulfurization, steam boilers, air separation, and syngas compressors.
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