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Fly Ash and Slag as Partial Replacement of Cement for the Synthesis of Low Carbon Cementitious Materials

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Journal of Renewable Materials 2023年第5期11卷 2491-2511页

作者： Yafei Hu keqing li Lujing Zheng Bin Han School of Civil and Resource Engineering University of Science and Technology BeijingBeijing100083China Key Laboratory of Ministry of Education of China for Efficient Mining and Safety of Metal Mines University of Science and Technology BeijingBeijing100083China Mining College Guizhou UniversityGuiyang550025China

Tailings known as solid waste are generated by the mining industry.The development of tailings as wet shotcrete aggregates has significant economic and environmental benefits.The fine particle size of the tailings results in a large consumption of traditional cement as a cementitious material and insignificant improvement in strength.Therefore,a composite cementitious system of cement and solid waste resources(fly ash and slag powder)is explored for this study.In this paper,the response surface methodology(RSM)is used to optimize the experimental design and a multivariate nonlinear response model with cement,fly ash and slag powder contents as variables are constructed,which can investigate the effect of the composite cementitious system on the strength of tailing wet shotcrete(TWSC).In addition,the information entropy(IE)is introduced and combined with the RSM to evaluate the composite cementitious system.Finally,the desirability function(DF)combined with RSM is used to optimize the composite cementitious system.The results show that the response model constructed in this paper has R^(2)=0.96 and P-valueliability.The higher the content of slag powder and cement in the composite cementitious system,the higher the strength and comprehensive score of the TWSC.There is a critical value of fly ash content,which makes the maximum cementation of the composite cementing system.The optimal mix proportion of the composite cementitious system is obtained based on RSM-DF,which leads to the strength of TWSC at different curing time to achieve the expected index.

关键词： Tailings wet shotcrete composite cementitious system desirability function mix proportion optimization

Development of Wet Shotcrete with Solid Waste as Aggregate:Strength Optimization and Mix Proportion Design

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Journal of Renewable Materials 2023年第9期11卷 3463-3484页

作者： Yafei Hu keqing li Bo Zhang Bin Han School of Civil and Resource Engineering University of Science and Technology BeijingBeijing100083China Key Laboratory of Ministry of Education of China for Efficient Mining and Safety of Metal Mines University of Science and Technology BeijingBeijing100083China

The super-fine particle size of tailings is its drawback as a recycled resource,which is reflected in the low strength of the new construction and industrial materials formed when it is mixed with cement and other cementitious materials.Therefore,it is crucial to study the effect of tailings particle size and cementitious material on the strength of tailings wet shotcrete(TWSC)and to investigate the optimal mix proportion.In this paper,a multivariate nonlinear response model was constructed by conducting central composite experiments to investigate the effect of different factors on the strength of TWSC.The strength prediction and mix proportion optimization of TWSC are carried out by machine learning techniques.The results show that the response model has R^(2)>0.94 and Pliability.Moreover,the strength of TWSC increases with the increase of tailings fineness modulus and decrease of water-binder ratio,while it also increases and then decreases with the increase of replacement rate of slag powder to cement(SRC rate).The extreme learning machine(ELM)constructed in this paper predicts the strength of TWSC with an accuracy of more than 98%and achieves rapid prediction under multi-factor conditions.It is worth mentioning that the ELM combined with the genetic algorithm(ELM-GA)collaboratively solved to obtain the mix proportion for C15 and C20 strength grades of TWSC and the maximum error is verified by experiments to be less than 2%.

关键词： Tailings wet shotcrete solid waste recycling prediction model

A Modeling Method for Predicting the Strength of Cemented Paste Backfill Based on a Combination of Aggregate Gradation Optimization and LSTM

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Journal of Renewable Materials 2022年第12期10卷 3539-3558页

作者： Bo Zhang keqing li Siqi Zhang Yafei Hu Bin Han School of Civil and Re source Engineering University of Science and Technology Beijing Beijing100083China Key Laboratory of Ministry of Educ ation of China for Eficient Mining and Safety of Metal Mines University of Science and Technology BeijingBeijing 100083China

Cemented paste backill(CPB)is a susta inable mining technology that is widely used in mines and helps to improve the mine environment.To investigate the relationship between aggregate grading and different affecting factors and the uniaxial compressive strength(UCS)of the cemented paste backill(CPB),Talbol gradation theory and neural networks is used to evaluate aggregate gradation to determine the optimum aggregate ratio.The mixed aggregate ratio with the least amount of cement(waste stone content river sand content=7:3)is obtained by using Talbol grading theory and pile compactness function and combined with experiments.In addition,the response surface method is used to design strength speaific ratio experiments.The UCS prediction model which ues the ISTM and considers the aggregates gradation have high accuracy.The root mean square error(RMSE)of the prediction results is 0.0914,the coefficient of determination(R^(2))is 0.9973 and the variance account for(VAF)is 99.73.Compared with back propagation neural network(BP-ANN),extreme lea ming machine(ELM)and madal basis function neural network(RBF ANN),LSTM can efectively characterize the nonlinear relationship between UCS and individual affecting factors and predict UCS with high accuracy.The sensitivity analysis of different affecting factors on UCS shows that all 4 factors have significant effect on UCS and sensitivity is in the following ranking:cement content(0.9264)>slurry concentration(0.9179)>aggregate gradation(waste rodk content)(0.9031)>curing time(09031).

关键词： Backill aggregate gradation machine learning uniaxial compressive strength cemented paste backill

An Exploration of Growth and Selenium Enrichment of Selenium-enriched Rice

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Asian Agricultural Research 2022年第11期14卷 62-64页

作者： Maohui WANG keqing li Chunyan ZHONG Jinquan NIE Zhaoqing Institute of Agricultural Sciences Zhaoqing 526070China

[Objectives]To explore the effects of selenium fertilizer on rice growth and selenium enrichment.[Methods]Using high-quality rice varieties as experimental materials,exogenous selenium fertilizer was sprayed at two critical periods of tillering stage and full heading stage to explore the effects of different selenium treatments on rice agronomic traits,leaf SPAD value and yield.[Results]Spraying selenium fertilizer could promote the growth of rice,and the selenium enrichment effect in the aboveground parts of the plant was obvious.The selenium content of rice(milled rice)was 0.04-0.07 mg/kg.[Conclusions]This study lays a foundation for the promotion of suitable leaf fertilizers in Zhaoqing City,and is expected to promote the cultivation and promotion of selenium-enriched rice.

关键词： Rice Selenium fertilizer Agronomic traits Selenium enrichment

我国矿产资源监管体系改革路径探讨——基于因子评价与国际经验分析

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矿业研究与开发 2024年第2期44卷 228-234页

作者：宋猛李文超李克庆北京科技大学土木与资源工程学院北京100083 中国自然资源经济研究院北京101149

为促进我国矿产资源监管体系的完善,分析了矿产资源监管的内涵及基本范畴,基于全国23个省级行政区、1700多个县级行政区的问卷调查结果,以综合政策、技术政策、配套政策作为组成因子,制度、手段、组织作为驱动因子,采用组成-驱动因子法... 详细信息

为促进我国矿产资源监管体系的完善,分析了矿产资源监管的内涵及基本范畴,基于全国23个省级行政区、1700多个县级行政区的问卷调查结果,以综合政策、技术政策、配套政策作为组成因子,制度、手段、组织作为驱动因子,采用组成-驱动因子法评价了我国矿产资源监管体系运行情况,并借鉴了西方发达国家的矿产资源监管经验,从不同维度提出了我国矿产资源监管体系改革的建议路径。当前我国矿产资源监管面临监管事项不清、手段分散、分工不明,以及监管任务与人员、经费难以匹配等阻滞性难题。美国、德国、芬兰等发达国家矿产资源监管制度具有责任分工细、公众参与度高和全生命周期覆盖等特征。在未来的工作中,应从清单、流程、职责、能力、配套5个维度,构建新时代生态文明情境下的矿产资源监管体系。

关键词：矿产资源监管运行体系因子评价国际经验改革路径

基于融合健康因子和集成极限学习机的锂离子电池SOH在线估计

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上海交通大学学报 2024年第3期58卷 263-272页

作者：屈克庆董浩毛玲赵晋斌杨建林李芬上海电力大学电气工程学院上海200090 国家电投风电产业创新中心上海200233

锂离子电池健康状态(SOH)的在线估计对电池管理系统的安全稳定运行至关重要.为克服传统基于数据驱动的锂离子电池SOH估计方法训练时间长、计算量大、调试过程复杂的问题,提出一种基于融合健康因子和集成极限学习机的锂离子电池SOH估计方... 详细信息

锂离子电池健康状态(SOH)的在线估计对电池管理系统的安全稳定运行至关重要.为克服传统基于数据驱动的锂离子电池SOH估计方法训练时间长、计算量大、调试过程复杂的问题,提出一种基于融合健康因子和集成极限学习机的锂离子电池SOH估计方法.该方法通过dQ/dV和dT/dV曲线分析,筛选出与电池SOH相关性较高的数据区间进行多维健康特征提取,并对其进行主成分分析降维处理得到间接健康因子;利用极限学习机的随机学习算法建立间接健康因子和SOH之间的非线性映射关系.在此基础上,针对单一模型输出不稳定的特点,提出一种集成极限学习机模型,通过对估计结果设置可信度评价规则剔除单一极限学习机不可靠的输出,从而提高锂离子电池SOH的估计精度.使用NASA和牛津大学的锂离子电池老化数据集对该方法进行验证,结果表明该方法的平均绝对百分比误差小于1%,具有较高的准确性和可靠性.

关键词：锂离子电池健康因子集成极限学习机健康状态在线估计

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机器人工程课程的项目式教学分析

集成电路应用 2024年第5期41卷 335-337页

作者：王可庆田浩李鹏无锡学院江苏214013 南京信息工程大学江苏210003

阐述机器人工程课程教学中的问题及原因,提出将项目式教学引入课程教学的改革方法。在技术整合与应用改革方面,突出虚拟仿真与模型建立、传感器技术与数据采集、编程与控制系统、人工智能与机器学习在项目中的应用。

关键词：项目式教学机器人工程技术整合虚拟仿真模型建立

Sediment subduction actuates the accelerated India-Eurasia convergence

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Sediment subduction actuates the accelerated India-Eurasia c...

青少年抑郁症患者自伤行为与甲状腺激素和脂类的关系

2022年中国地球科学联合学术年会

作者： Hao Zhou keqing li Jiashun Hu Department of Earth and Space Sciences Southern University of Science and Technology

A mysterious increase in convergence rate between India and Eurasia occurred around 65 Ma, leading to a peak of convergence near 18 cm/yr. Several hypotheses have been proposed to explain this plate motion acceleration, including the Reunion plume push, increased slab pull from double subduction, and subduction of equatorial bulge sediments.

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中国心理卫生杂志 2024年第5期38卷 433-438页

作者：温敏张云淑刘晋宁胡晋云张歆玮张丽丽李冰栗克清华北理工大学河北唐山063000 河北省精神卫生中心河北省重大精神与行为疾病重点实验室河北保定071000 河北大学公共管理学院河北保定071002 北京首佑医学科技服务有限公司北京10002

目的:探讨青少年抑郁症患者的自伤行为与正常范围内甲状腺激素与脂类的关系。方法:纳入符合精神障碍诊断与统计手册第5版(DSM-5)抑郁症诊断标准的青少年住院患者182例,其中伴自伤行为38例,不伴自伤行为144例。比较两组各指标的差别,用lo... 详细信息

目的:探讨青少年抑郁症患者的自伤行为与正常范围内甲状腺激素与脂类的关系。方法:纳入符合精神障碍诊断与统计手册第5版(DSM-5)抑郁症诊断标准的青少年住院患者182例,其中伴自伤行为38例,不伴自伤行为144例。比较两组各指标的差别,用logistic回归分析青少年抑郁症患者自伤的相关因素。结果:青少年抑郁症患者中伴自伤行为组的总胆固醇、高密度脂蛋白胆固醇水平高于不伴自伤行为组(P<0.05),游离甲状腺素水平低于不伴自伤行为组(P<0.05)。Logistic回归分析结果显示病程时间(OR=1.03)越长、高密度脂蛋白胆固醇越高(OR=12.75)的青少年抑郁症患者越容易有自伤行为。结论:病程时间长、高密度脂蛋白胆固醇水平高可能是青少年抑郁症自伤行为发生的危险因素,游离甲状腺素水平低可能是保护因素。

关键词：抑郁症青少年自伤甲状腺激素脂类