Gongcheng Kexue Yu Jishu/Advanced Engineering Science (ISSN: 2096-3246) is a bi-monthly peer-reviewed international Journal. Gongcheng Kexue Yu Jishu/Advanced Engineering Science was originally formed in 1969 and the journal came under scopus by 2017 to now. The journal is published by editorial department of Journal of Sichuan University. We publish every scope of engineering, Mathematics, physics.

( Vol 54 , Issue 10 )

12 Dec 2022

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( Vol 54 , Issue 10 )

31 Dec 2022

Gongcheng Kexue Yu Jishu/Advanced Engineering Science (ISSN: 20963246) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are in the following fields but not limited to:

Horticulture,
Agriculture,
Soil Science,
Agronomy,
Biology,
Economics,
Biotechnology,
Agricultural chemistry,
Soil,
development in plants,
aromatic plants,
subtropical fruits,
Green house construction,
Growth,
Horticultural therapy,
Entomology,
Medicinal,
Weed management in horticultural crops,
plant Analysis,
Tropical,
Food Engineering,
Venereal diseases,
nutrient management,
vegetables,
Ophthalmology,
Otorhinolaryngology,
Internal Medicine,
General Surgery,
Soil fertility,
Plant pathology,
Temperate vegetables,
Psychiatry,
Radiology,
Pulmonary Medicine,
Dermatology,
Organic farming,
Production technology of fruits,
Apiculture,
Plant breeding,
Molecular breeding,
Recombinant technology,
Plant tissue culture,
Ornamental horticulture,
Nursery techniques,
Seed Technology,
plantation crops,
Food science and processing,
cropping system,
Agricultural Microbiology,
environmental technology,
Microbial,
Soil and climatic factors,
Crop physiology,
Plant breeding,

Electrical Engineering,
Telecommunication Engineering,
Electro-mechanical System Engineering,
Biological Biosystem Engineering,
Integrated Engineering,
Electronic Engineering,
Hardware-software co-design and interfacing,
Semiconductor chip,
Peripheral equipments,
Nanotechnology,
Advanced control theories and applications,
Machine design and optimization ,
Turbines micro-turbines,
FACTS devices ,
Insulation systems ,
Power quality ,
High voltage engineering,
Electrical actuators ,
Energy optimization ,
Electric drives ,
Electrical machines,
HVDC transmission,
Power electronics.

Software Engineering,
Data Security ,
Computer Vision ,
Image Processing,
Cryptography,
Computer Networking,
Database system and Management,
Data mining, Big Data, Robotics ,
Parallel and distributed processing ,
Artificial Intelligence ,
Natural language processing ,
Neural Networking, Distributed Systems ,
Fuzzy logic, Advance programming,
Machine learning,
Internet & the Web,
Information Technology ,
Computer architecture,
Virtual vision and virtual simulations,
Operating systems,
Cryptosystems and data compression,
Security and privacy,
Algorithms,
Sensors and ad-hoc networks,
Graph theory,
Pattern/image recognition,
Neural networks.

Architectural Drawing,
Architectural Style,
Architectural Theory,
Biomechanics,
Building Materials,
Coastal Engineering,
Construction Engineering,
Control Engineering,
Earthquake Engineering,
Environmental Engineering,
Geotechnical Engineering,
Materials Engineering,
Municipal Or Urban Engineering,
Organic Architecture,
Sociology of Architecture,
Structural Engineering,
Surveying,
Transportation Engineering.

Chemical engineering fundamentals,
Physical, Theoretical and Computational Chemistry,
Chemical engineering educational challenges and development,
Chemical reaction engineering,
Chemical engineering equipment design and process design,
Thermodynamics,
Catalysis & reaction engineering,
Particulate systems,
Rheology,
Multifase flows,
Interfacial & colloidal phenomena,
Transport phenomena in porous/granular media,
Membranes and membrane science,
Crystallization, distillation, absorption and extraction,
Ionic liquids/electrolyte solutions.

Food science,
Food engineering,
Food microbiology,
Food packaging,
Food preservation,
Food technology,
Aseptic processing,
Food fortification,
Food rheology,
Dietary supplement,
Food safety,
Food chemistry.
AMA, Agricultural Mechanization in Asia, Africa and Latin America
Teikyo Medical Journal
Journal of the Mine Ventilation Society of South Africa
Dokkyo Journal of Medical Sciences
Interventional Pulmonology

Astrophysics,
Atomic and molecular physics,
Biophysics,
Chemical physics,
Civil engineering,
Cluster physics,
Computational physics,
Condensed matter,
Cosmology,
Device physics,
Fluid dynamics,
Geophysics,
High energy particle physics,
Laser,
Mechanical engineering,
Medical physics,
Nanotechnology,
Nonlinear science,
Nuclear physics,
Optics,
Photonics,
Plasma and fluid physics,
Quantum physics,
Robotics,
Soft matter and polymers.

Actuarial science,
Algebra,
Algebraic geometry,
Analysis and advanced calculus,
Approximation theory,
Boundry layer theory,
Calculus of variations,
Combinatorics,
Complex analysis,
Continuum mechanics,
Cryptography,
Demography,
Differential equations,
Differential geometry,
Dynamical systems,
Econometrics,
Fluid mechanics,
Functional analysis,
Game theory,
General topology,
Geometry,
Graph theory,
Group theory,
Industrial mathematics,
Information theory,
Integral transforms and integral equations,
Lie algebras,
Logic,
Magnetohydrodynamics,
Mathematical analysis.

Journal ID : AES-12-01-2022-102

Three kinds of magnesium-based foamed concrete with dry density grade A05 were prepared by chemical foaming with magnesium oxychloride cement, magnesium oxysulfide cement and magnesium phosphate cement as cementing materials respectively. By designing orthogonal tests, the influences of water/cement ratio, magnesium cement component ratio, retarder content, fly ash content and polypropylene fiber content on the compressive strength of three kinds of magnesia-based foamed concrete were determined, the action mechanisms of the important influencing factors were compared and analyzed, and the functional relationships between the specific strength of magnesium-based foamed concrete and the component ratio parameters of magnesium-based foamed concrete were established. The results showed that the primary and secondary factors affecting the compressive strength of magnesium oxychloride foamed concrete were the ratio of magnesium cement components>water/cement ratio>fly ash content>polypropylene fiber content>retarder content. The influence of various factors on compressive strength of magnesium oxysulfide foam concrete was the same as that of magnesium oxychloride foam concrete.The relationship between the factors influencing the compressive strength of magnesium phosphate foamed concrete was as follows: the ratio of magnesium cement components>retarder content>water/cement ratio>fly ash content>polypropylene fiber content. Different from magnesium oxychloride foam concrete and magnesium oxysulfide foam concrete, the content of retarder had a higher degree of influence. The component ratio of magnesium cement was an important index affecting the strength of magnesia-based foamed concrete. The compressive strength of magnesium oxychloride foamed concrete and magnesium sulfide foamed concrete had the same change trend with the increase of the component ratio of magnesium cement, both of which first decreased and then increased, while magnesium phosphate foamed concrete showed the trend of first increased and then decreased with the increase of the component ratio of magnesium cement. There was a power function relationship between the specific strength of three kinds of magnesium-based foamed concrete and the component ratio of magnesium-based foamed concrete.

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Journal ID : AES-12-01-2022-101

Frequency diverse array (FDA) radar applies a small frequency offset between the adjacent elements to synthesize a range-angle-dependent beampattern. It is difficult to control the beam steering for the coupled time-variant beampattern. For this problem, the time-variant characteristic and point beam forming of FDA radar were mainly studied in the paper. Firstly, the characteristic of transmit beampattern of FDA using linearly increasing frequency increment was analyzed. Secondly, two signal models of FDA using logarithmically frequency increments (log–FDA) and multicarrier frequency increments (multi-FDA) were constructed, where the multi-FDA transmit beampattern has lower sidelobes. Then, the relationship between the time variable of the frequency increase term and the time variable of the propagation term in the two time modulated signal models was studied in detail. If both of them are the same, the time-varying characteristics of the transmit beampattern can be eliminated by the two time variables offset. However, they have different physical meanings. When the electromagnetic signal is generated and propagated in space, the time variable in the frequency increase term will not change, whereas the time variable of the propagation term in the propagation process is related to the propagation characteristics of the electromagnetic wave, which is a variable quantity, so the two time variables cannot offset each other. Finally, the simulation results verify the correctness of the transmit beampattern analysis of time modulated FDA radar, and demonstrate that the spot transmit beampattern with dynamic forward propagation can be synthesized using log–FDA and multi-FDA, where the beampattern of the multi-FDA has lower sidelobes.

.Full article

Journal ID : AES-12-01-2022-100

In order to alleviate the burden of continuous increasing energy consumption falling on the power system and solve the complex calculation problem in the joint dispatching of large-scale electrical equipment, a hybrid decentralized optimization of dispatching the large-scale controllable appliances and energy storage equipment considering demand side response was proposed in this paper. Firstly, two mathematical models of controllable electrical equipment load and energy storage equipment were established. On this basis, a mixed integer non-linear centralized optimization model was mathematically formulated under the constraints of the operation characteristics of the system and equipment, with the objective of minimizing the sum of electricity purchase cost, users’ dissatisfaction cost and energy storage equipment loss cost. Secondly, for tackling the difficult nonlinear centralized optimization problems of high dimensionality, multi objectives and multiple constraints, the Lagrange relaxation method was used to decompose the problem into two sub-problems, namely, optimally scheduling the controllable electrical equipment load and optimizing the dispatch of the energy storage equipment. Then, the former was further decomposed into optimizing dispatch of each controllable electrical equipment and solved by the interior point method, while the latter was decomposed into a set of mixed integer linear optimization sub-problems of scheduling each energy storage equipment and solved in parallel by the Benders decomposition method. Thirdly, a series of numerical simulations together with comparison analysis were performed to verify the effectiveness and superiority of the proposed dispatch optimization method. For example, the optimization objective value and the optimal dispatch solution corresponding to the proposed method were illustrated and compared with those of the centralized method to demonstrate the effectiveness of the hybrid decentralized optimization method. And the influence of different numbers of dispatching equipment on the computation efficiency was investigated on the centralized and decentralized optimization method to show the superiority of the proposed hybrid decentralized optimization method. According to the numerical simulation results, the optimization objective value of the proposed method is basically consistent with that of the centralized. Moreover, the identified dispatch solution enables to efficiently respond to the time-of-use and results in good effect of peak-shaving and valley-filly. Besides, the calculation efficiency of the proposed hybrid decentralized optimization method is of high computation efficiency and not affected by the increasing number of the schedulable electrical equipments.

.Full article

Journal ID : AES-12-01-2022-99

Exploring the fluid flow mechanism in rock masses is of great significance for preventing water inrush during excavation of underground constructions such as tunnels. Quantitative descriptions of the hydraulic properties of single rock fracture subject to normal stresses and shear displacement are the basis for understanding the coupled hydro-mechanical processes in fractured rock masses; however, the quantitative relationships among stress, deformation, aperture, inertial coefficients have not been developed in previous works. Granite specimens with single fracture were prepared and flow tests with variable water heads were carried out, in which incremental normal stresses were applied at each fixed shear displacement to characterize the evolution of permeability. The surface morphology of fractures was digitalized using a three-dimensional high-resolution scanning system. A self-designed numerical code was employed to calculate the deformation of fractures under normal stresses based on the framework of variational principles in contact mechanics. The fracture deformation and void space variation under different shear displacements and normal stresses were investigated. By extracting the aperture data and solving Navier–Stokes equations using COMSOL software, a series of numerical simulations were performed to investigate the nonlinear flow behavior of fluids within fractures under different shear displacements and normal stresses. The relationships among shear displacement, normal stress, void space distributions and parameters describing the nonlinear flow were quantitatively analyzed. The results showed that the fracture surface damage areas obtained from the experiment agreed well with the numerical simulation results, which verified the reliability of the deformation calculation code. The normal stress and the shear displacement exhibited a decreasing power function and an increasing exponential function with the fracture aperture, respectively. The increase in the shear displacement resulted in the concentration of contact areas. The inertia coefficient *B* in the Forchheimer equation and the critical hydraulic gradient *J*c could quantitatively characterize the nonlinear flow behavior. *B* and *J*c exhibited decreasing power functions with the shear displacement. The increasing rates and ranges of *J*c and *B* decreased gradually as shear advances. When the shear displacement increased from 2 to 8 mm, the range of *J*c decreased from 6.10×10–3 to 1.20×10–3 by a rate of 80.32%. The range of *B* decreased sharply from 2.97×1014 Pa·s2·m–7 to 2.43×1013 Pa·s2·m–7 by a rate of 91.28%. A similar power function relationship existed between RSD～*B* and between RSD～*J*c. Finally, a predictive function was proposed to quantify the onset of nonlinear fluid flow through fractures.

Full article

Journal ID : AES-12-01-2022-98

Thermal error prediction and compensation of CNC machine tools is an important technology to improve the machining accuracy and reliability of CNC machine tools. The thermal error of machine tool is time-varying and nonlinear. To improve the accuracy and robustness of thermal error prediction, a numerical control machine tool thermal error prediction model based on attention mechanism and deep learning network was proposed. Using the data conversion strategy, the original temperature data of CNC machine tool was transformed into temperature image, which could be directly used as the input of deep learning network. The complete information of the temperature field of the machine tool was retained by converting the temperature field data into the temperature image points. At the same time, the nonlinear and coupling problems between the temperature measuring points were avoided by using the deep learning modeling method. A recognition network of temperature sensitive points based on attention mechanism was proposed. According to the correlation degree between temperature measuring points and thermal error, different weights were given to each temperature measuring point to avoid the disadvantages of artificial selection of temperature measuring points. A 12–layer deep CNN learning prediction network was established to mine the nonlinear mapping relationship between temperature image and thermal error by using its powerful image feature learning ability. This method does not need to preselect the key temperature points, retained more relationship between thermal error and machine temperature characteristics, and can significantly improve the prediction accuracy of the model. In order to improve the accuracy and generalization ability of thermal error model, dropout regularization method and Adam optimization algorithm were introduced to optimize the structure and parameters of deep convolution neural network. The method shows high prediction accuracy in the thermal error verification of G460L CNC lathe. Compared with the thermal error models based on BP neural network, multiple regression and CNN network, the proposed method performs better in generalization performance.

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