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基于响应面分析法的氯氧镁水泥强度预测模型

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本研究旨在通过响应面分析法(RSM)建立一个预测氯氧镁水泥(MOC)强度的模型,优化其原料配比以提升其抗压强度。研究发现,MgO/MgCl2和H2O/MgCl2摩尔比显著影响MOC的抗压强度,基于RSM优化,开发了一个易于操作的Matlab图形用户界面(GUI),实现了在已知轻烧氧化镁活性条件下,快速预测MOC的最优配比及其抗压强度。本研究为MOC的配比优化提供了科学依据,并通过建立预测模型,为MOC及其他胶凝材料的应用开发提供了新的研究工具和方法,有助于推动MOC在建筑等领域的广泛应用。
The purpose of this study was to establish a model for predicting the strength of magnesium oxychloride cement(MOC)by response surface analysis(RSM),and optimize its raw material ratio to improve its compressive strength.It was found that the molar ratio of MgO/MgCl2 and H2O/MgCl2 significantly affected the compressive strength of MOC.This study provides a scientific basis for the optimization of MOC ratio,and provides a new research tool and method for the application and development of MOC and other cementitious materials by establishing a prediction model,which is helpful to promote the wide application of MOC in construction and other fields.

magnesium oxychloride cementresponse surface analysiscompressive strengthmatlab model

周爱萍、陈瑞杰

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南京交通职业技术学院,江苏 南京 211188

河海大学材料科学与工程学院,江苏 常州 526000

氯氧镁水泥 响应面分析法 抗压强度 Matlab模型

2024

江苏建材
江苏省建材工业协会

江苏建材

影响因子:0.257
ISSN:1004-5538
年,卷(期):2024.(6)