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基于NSGM(1,4)模型的球磨改性磷建筑石膏强度预测

Strength Prediction of Ball-Milling-Modified Phosphorus Building Gypsum Based on NSGM (1,4) Model.

作者信息

Zhang Yi, Tao Zhong, Wu Lei, Zhang Zhiqi, Zhao Zhiman

机构信息

Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.

Yunnan Earthquake Engineering Research Institute, Kunming 650500, China.

出版信息

Materials (Basel). 2022 Nov 11;15(22):7988. doi: 10.3390/ma15227988.

Abstract

Phosphogypsum is an industrial byproduct from the wet preparation of phosphoric acid. Phosphorus building gypsum can be obtained from phosphogypsum after high-thermal dehydration. This study aimed to analyze the influence of ball milling with different parameters on the strength of phosphorus building gypsum. In this paper, the absolute dry flexural strength and the absolute dry compressive strength of phosphorus building gypsum were compared under different mass ratios of material to ball, ball-milling speed, and ball-milling time, and the NSGM (1,4) model was applied to model and predict the strength of phosphorus building gypsum modified by ball milling. According to the research results, under the same mass ratio of material to ball and ball-milling speed, the absolute dry flexural strength and absolute dry compressive strength of phosphorus building gypsum firstly increased and then decreased with the increase in milling time. The NSGM (1,4) model established in this paper could effectively simulate and predict the absolute dry flexural strength and the absolute dry compressive strength of the ball-milling-modified phosphorus building gypsum; the average relative simulation errors were 12.38% and 13.77%, and the average relative prediction errors were 6.30% and 12.47%.

摘要

磷石膏是湿法制备磷酸过程中的一种工业副产品。磷建筑石膏可通过磷石膏高温脱水后获得。本研究旨在分析不同参数的球磨对磷建筑石膏强度的影响。本文比较了在不同的料球质量比、球磨速度和球磨时间下磷建筑石膏的绝干抗折强度和绝干抗压强度,并应用NSGM(1,4)模型对球磨改性磷建筑石膏的强度进行建模和预测。研究结果表明,在相同的料球质量比和球磨速度下,磷建筑石膏的绝干抗折强度和绝干抗压强度随球磨时间的增加先增大后减小。本文建立的NSGM(1,4)模型能够有效地模拟和预测球磨改性磷建筑石膏的绝干抗折强度和绝干抗压强度;平均相对模拟误差分别为12.38%和13.77%,平均相对预测误差分别为6.30%和12.47%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a265/9696628/aa19a1228149/materials-15-07988-g001.jpg

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