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Initiation and propagation laws of the glass cracks in specimens subjected to normal loading under the action of symmetric wedges

WAN Zhen-ping, LIU Ya-jun, TANG Yong, YE Bang-yan

《机械工程前沿（英文）》 2006年第1卷第2期页码 194-198 doi: 10.1007/s11465-005-0011-x

摘要： With more and more applications of glass in advanced fields of science, the demand for glass machining precision has increased greatly. More and more attention is being paid to glass cutting because precise glass parts with various shapes can be obtained at high efficiency and low cost. To improve the machining precision of part surfaces and to facilitate tool design and cutting parameter selection, the initiation and propagation laws of glass cracks in specimens subjected to normal loading by symmetric wedges were investigated. Research results show that initiation and propagation laws are the same with interior symmetric wedge angles of 30o-120o, while the laws are different with interior symmetric wedge angles equal to or more than "e150o. The relationship between medial crack length and normal loading was also investigated when specimens were indented by symmetrical wedges with interior angles of 30o-120o.

关键词： different 30o-120o relationship initiation cutting parameter

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Is atmospheric oxidation capacity better in indicating tropospheric O formation?

《环境科学与工程前沿（英文）》 2022年第16卷第5期 doi: 10.1007/s11783-022-1544-5

摘要：

● This study summarizes and evaluates different approaches that indicate O₃ formation.

关键词： O₃ AOC O₃ formation regime

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Prediction of selected biodiesel fuel properties using artificial neural network

Solomon O. GIWA,Sunday O. ADEKOMAYA,Kayode O. ADAMA,Moruf O. MUKAILA

《能源前沿（英文）》 2015年第9卷第4期页码 433-445 doi: 10.1007/s11708-015-0383-5

摘要： Biodiesel is an alternative fuel to replace fossil-based diesel fuel. It has fuel properties similar to diesel which are generally determined experimentally. The experimental determination of various properties of biodiesel is costly, time consuming and a tedious process. To solve these problems, artificial neural network (ANN) has been considered as a vital tool for estimating the fuel properties of biodiesel, especially from its fatty acid (FA) composition. In this study, four ANNs have been designed and trained to predict the cetane number (CN), flash point (FP), kinematic viscosity (KV) and density of biodiesel using ANN with logsig and purelin transfer functions in the hidden layer of all the networks. The five most prevalent FAs from 55 feedstocks found in the literature utilized as the input parameters for the model are palmitic, stearic, oleic, linoleic and linolenic acids except for density network with a sixth parameter (temperature). Other FAs that are present in the biodiesels have been considered based on the number of carbon atom chains and the level of saturation. From this study, the prediction accuracy and the average absolute deviation of the networks are CN (96.69%; 1.637%), KV (95.80%; 1.638%), FP (99.07%; 0.997%) and density (99.40%; 0.101%). These values are reasonably better compared to previous studies on empirical correlations and ANN predictions of these fuel properties found in literature. Hence, the present study demonstrates the ability of ANN model to predict fuel properties of biodiesel with high accuracy.

关键词： biodiesel fuel properties artificial neural network fatty acid prediction

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Availability of wind energy resource potential for power generation at Jos, Nigeria

O. O. Ajayi, R. O. Fagbenle, J. Katende, J. O. Okeniyi

《能源前沿（英文）》 2011年第5卷第4期页码 376-385 doi: 10.1007/s11708-011-0167-5

摘要： The objective of this study was to assess the potential viability of the wind resource potential in Jos, Plateau state, Nigeria for power generation. The monthly mean wind speeds that span from 1987 to 2007 were employed to statistically analyze the monthly, annual and seasonal potentials of the wind energy resources at the site. Besides, the results were employed together with two models of wind energy conversion system to simulate the likely average output power. The outcome showed that Jos was suitable as a site for wind farm projects of varying sizes and that MW·h to GW·h of electricity is likely to be produced per period of months, seasons and years. The average wind speed range at the site was also estimated to be between 6.7 and 11.8 m/s across the months, years and seasons.

关键词： green electricity renewable resources Weibull statistics Jos Nigeria

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Selective oxidation of o -nitrotoluene to o -nitrobenzaldehyde with metalloporphyrins as biomimetic catalysts

Xinling WANG, Yuanbin SHE,

《化学科学与工程前沿（英文）》 2009年第3卷第4期页码 453-456 doi: 10.1007/s11705-009-0167-8

摘要： Selective oxidation of -nitrotoluene to -nitrobenzaldehyde with metalloporphyrins as biomimetic catalysts was studied. The peripheral substituent around porphyrin rings and various process parameters of NaOH concentration, reaction temperature, reaction time and oxygen pressure all affect the selectivity of -nitrobenzaldehyde. Further, 82.0% selectivity of -nitrobenzaldehyde was achieved under the optimum conditions: 1.0×10mol•L of T(-NO)PPFeCl catalyst, 2.5mol•L of NaOH, 0.2mol•L of -nitrotoluene, 45°C and 2.0MPa for 6h.

关键词： -nitrobenzaldehyde temperature biomimetic selectivity pressure

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Rh₂O₃/hexagonal CePO₄ nanocatalysts for N₂O decomposition

Huan Liu, Zhen Ma

《化学科学与工程前沿（英文）》 2017年第11卷第4期页码 586-593 doi: 10.1007/s11705-017-1659-6

摘要： Hexagonal CePO nanorods were prepared by a precipitation method and hexagonal CePO nanowires were prepared by hydrothermal synthesis at 150 °C. Rh(NO ) was then used as a precursor for the impregnation of Rh O onto these CePO materials. The Rh O supported on the CePO nanowires was much more active for the catalytic decomposition of N O than the Rh O supported on CePO nanorods. The stability of both catalysts as a function of time on stream was studied and the influence of the co-feed (CO , O , H O or O /H O) on the N O decomposition was also investigated. The samples were characterized by N adsorption-desorption, inductively coupled plasma optical emission spectroscopy, X-ray diffraction, transmission electron microscopy, X-ray photoelectron microscopy, hydrogen temperature-programmed reduction, oxygen temperature-programmed desorption, and CO temperature-programmed desorption in order to correlate the physicochemical and catalytic properties.

关键词： Rh₂O₃ CePO₄ N₂O decomposition

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Al₂O₃-M_xO_y硬面陶瓷涂层的喷焊制备及性能研究

王飚,王宇栋,李慧玲,张自华

《中国工程科学》 2002年第4卷第9期页码 75-80

摘要：

在碳钢母材上，用氧乙炔焰喷焊镍包铝合金粉末制取预涂层，喷焊50% Al₂O₃+50% Ni的复合粉末制取过渡层，用等离子喷焊Al₂O₃ - M_xO_y复合粉末制取最终涂层。

关键词： Al₂O₃-M_xO_y 涂层等离子抗腐蚀抗磨损

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数学推理挑战人工智能

Sean O’Neill

《工程（英文）》 2019年第5卷第5期页码 817-818 doi: 10.1016/j.eng.2019.08.009

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Optimization of the O/HO process with response surface methodology for pretreatment of mother liquor

《环境科学与工程前沿（英文）》 2021年第15卷第4期 doi: 10.1007/s11783-020-1371-5

摘要：

• Real ML-GFW with high salinity and high organics was degraded by O₃/H₂O₂ process.

关键词： High salinity High organic matters Gas field wastewater O₃/H₂O₂ Response surface methodology

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The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for traditional masonry

Tiago Miguel FERREIRA, João ESTÊVÃO, Rui MAIO, Romeu VICENTE

《结构与土木工程前沿（英文）》 2020年第14卷第3期页码 609-622 doi: 10.1007/s11709-020-0623-6

摘要： This paper discusses the adoption of Artificial Intelligence-based techniques to estimate seismic damage, not with the goal of replacing existing approaches, but as a mean to improve the precision of empirical methods. For such, damage data collected in the aftermath of the 1998 Azores earthquake (Portugal) is used to develop a comparative analysis between damage grades obtained resorting to a classic damage formulation and an innovative approach based on Artificial Neural Networks (ANNs). The analysis is carried out on the basis of a vulnerability index computed with a hybrid seismic vulnerability assessment methodology, which is subsequently used as input to both approaches. The results obtained are then compared with real post-earthquake damage observation and critically discussed taking into account the level of adjustment achieved by each approach. Finally, a computer routine that uses the ANN as an approximation function is developed and applied to derive a new vulnerability curve expression. In general terms, the ANN developed in this study allowed to obtain much better approximations than those achieved with the original vulnerability approach, which has revealed to be quite non-conservative. Similarly, the proposed vulnerability curve expression was found to provide a more accurate damage prediction than the traditional analytical expressions.

关键词： Artificial Neural Networks seismic vulnerability masonry buildings damage estimation vulnerability curves