Thermal decomposition characteristics of foundry sand for cast iron in nitrogen atmosphere

Xu, Qingwei; Xu, Kaili; Yao, Xiwen; Li, Ji-Shuo; Li, Li

doi:10.1098/rsos.181091

Cited by 8 publications

(11 citation statements)

References 28 publications

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“…The casting process is used to obtain a part or workblank by pouring liquid metal into a cavity corresponding to the shape of the part, and then gradually cooling and solidifying it [5,6]. However, there are negative effects of the growing foundry industry, such as environment pollution [7][8][9] and casualties [10][11][12]. A severe explosion accident occurred in the Anshan Irion and Steel Group in China, killing 13 workers and injuring another 17 [10,12].…”

Section: Introductionmentioning

confidence: 99%

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Fang

2020

IJERPH

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Safety assessment of a casting workshop will provide a clearer understanding of the important safety level required for a foundry. The main purpose of this study was to construct a composite safety assessment method to protect employee health using the cloud model and cause and effect–Layer of Protection Analysis (LOPA). In this study, the weights of evaluation indicators were determined using the subjective analytic hierarchy process and objective entropy weight method respectively. Then, to obtain the preference coefficient of the integrated weight more precisely, a new algorithm was proposed based on the least square method. Next, the safety level of the casting workshop was presented based on the qualitative and quantitative analysis of the cloud model, which realized the uncertainty conversion between qualitative concepts and their corresponding quantitative values, as well as taking the fuzziness and randomness into account; the validity of cloud model evaluation was validated by grey relational analysis. In addition, cause and effect was used to proactively identify factors that may lead to accidents. LOPA was used to correlate corresponding safety measures to the identified risk factors. 6 causes and 19 sub-causes that may contribute to accidents were identified, and 18 potential remedies, or independent protection layers (IPLs), were described as ways to protect employee health in foundry operations. A mechanical manufacturing business in Hunan, China was considered as a case study to demonstrate the applicability and benefits of the proposed safety assessment approach.

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Section: Introductionmentioning

confidence: 99%

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Fang

2020

IJERPH

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“…e preexponential factor is determined by the thermal decomposition experiment, regardless of the reaction temperature and the concentration of the substance. e activation energy under kinetics theory can be calculated according to thermal decomposition data [27]. In the present study, the thermal decomposition kinetic parameters of foundry sand were calculated according to kinetics theory.…”

Section: Introductionmentioning

confidence: 99%

“…After determining the thermal decomposition kinetics parameters of foundry sand, we roughly determined the fitting effect according to Pearson's R [19,21]. Xu et al calculated the thermal decomposition kinetic parameters of foundry sand for cast iron under kinetics theory [27], but they did not test the validity of the calculation results. To rigorously test the fitting effect, we conducted single-factor analysis of variance on the source of error [28].…”

Section: Introductionmentioning

confidence: 99%

Thermal Decomposition Behaviour of Foundry Sand for Cast Steel in Nitrogen and Air Atmospheres

Chen

Zhang

et al. 2020

Mathematical Problems in Engineering

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Sand casting is the most widely used casting technique, known for ages, even since ancient times. The main goal of this study was to determine the thermal decomposition behaviour of foundry sand for cast steel. We first tested the basic properties of foundry sand, including its proximate analysis, chemical composition, and particle size characteristics; we next monitored the thermal decomposition behaviour of foundry sand for cast steel via simultaneous thermal analysis. We focused on the mass loss of foundry sand for cast steel at different heating rates in nitrogen and air atmospheres. We adopted a novel method to calculate the volatile release characteristic index of foundry sand. The volatile content of foundry sand for cast steel was very low, so the volatile release characteristic index of the sand could not be strictly calculated according to this concept. We calculated the thermal decomposition kinetics parameters of foundry sand, namely, the activation energy and preexponential factor, under kinetics theory. To thoroughly test the fitting effect, we conducted a single-factor analysis of variance on the source of error. The results showed that the independent variable has a significant influence on the dependent variable and that the fitting equation we selected is feasible and effective.

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“…With rapid economic growth comes an increase in the quality of the standard of living (Xu & Xu, ; Xu, Xu, Yao, Zhang, & Wang, ; Xu, Xu, Yao, Li, & Li, ; Yan & Xu, ; Zhang, Cliff, Xu, & You, ). Since wine has been integrated into society, more attention is being paid to wine quality.…”

Section: Introductionmentioning

confidence: 99%

Quality evaluation of Chinese red wine based on cloud model

2019

J Food Biochem

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Determining the quality of red wine is based on many qualitative and quantitative factors. Compared with other evaluation methods, the cloud model has an uncertainty transformation between a qualitative concept and its corresponding quantitative value, and the uncertainty transformation included fuzziness and randomness, which is suitable for solving the complexity of red wine evaluation. This study introduced the cloud model into quality evaluation of red wine for the first time, and a novel algorithm of comprehensive cloud model was proposed based on an addition algorithm of two cloud models. Furthermore, to validate the cloud model adopted in our red wine evaluation system, we used the gray relational analysis and fuzzy evaluation method. The evaluation result for the red wine sample was Good, and the result confirmed that our cloud model can be used to evaluate the quality of red wine. Practical applications In 2013, China surpassed France to become the largest country of red wine consumption in the world. Red wine is made by a natural fermentation process. There are several components that make up red wine, but the most abundant is grape juice. Ethyl alcohol is the second most abundant element and it is made naturally by the fermentation of the sugar in grape. There are more than 1,000 remaining components in the recipe for red wine, where 300 are comparatively important. Although the proportion of these components is not high, they are important factors in determining the quality of red wine. Sensory evaluation is the most common method used to determine the quality of red wine. This work has identified a cloud model that can be used, based on sensory evaluation, to determine the quality of red wine.

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Thermal decomposition characteristics of foundry sand for cast iron in nitrogen atmosphere

Cited by 8 publications

References 28 publications

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

Thermal Decomposition Behaviour of Foundry Sand for Cast Steel in Nitrogen and Air Atmospheres

Quality evaluation of Chinese red wine based on cloud model

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