开采沉陷预计与控制仿真试验教学系统

仿真教学是计算机辅助教学的高级阶段。从传统教学的不足与仿真教学的优点入手,针对传统矿山开采沉陷课程教学,以提高教学效果为目的,开发了基于VB的开采沉陷预计与控制仿真试验教学系统,将仿真教学引入到矿山开采沉陷学教学过程中。在论述系统开发原理及功能设计的基础上,详细介绍了系统3大模块——地表移动变形分析模块、动态演示模块及开采沉陷控制技术模块的功能与特点。基于本系统,通过人机交互界面与系统进行交流,可以让学生充分理解并掌握地表及岩层破坏机理,开采沉陷预计、开采沉陷防治等重点内容,从而有效提高教学质量和效果。教学实践表明,将计算机仿真教学纳入到矿山开采沉陷学教学过程中,可以极大地提高学生理解能力,培养学生的学习兴趣。     

面向加工特征的工件制造过程能耗预测方法

在工件的制造过程中,具有多个特征的工件在加工时,其加工特征的能耗属性不同,为了研究在工件不同的加工特征对能耗的影响,创建了面向加工特征的工件制造过程能耗预测模型。首先,将工件看成单个加工特征的集合体,其次对工件特征切削功率的分析,创建有关切削功率的能耗数学模型;然后采用GM(1,1)模型完成工件加工时其切削功率的灰色建模,实现整个工件能耗的预测过程,最后通过对冲床顶支座的加工过程为例,说明了该模型的准确性。     

基于密实核理论的单滚刀多阶段受力预测模型

基于密实核理论,针对特定岩石条件,考虑滚刀在破岩过程中复杂的受力情况,将滚刀楔形刃破岩过程分为四个阶段:弹性变形阶段、挤压破碎阶段、密实核破碎阶段与卸载阶段,且认为在密实核破碎阶段,密实核处于静水压状态,静水压力增大,会使受力物体的体积缩小,但不会改变其形状。并提出了单滚刀多阶段受力预测模型。进而开展了单滚刀线性切割岩石试验研究,并与理论模型进行了对比。结果表明:预测模型与实验数据垂直力、侧向力和滚动力的误差分别在(8~18)k N,(2~5)k N和(0~3)k N;在此基础上对预测模型进行了系数修正,使其能够更加真实地模拟滚刀破岩的受力情况,为滚刀以及刀盘的设计提供技术支撑。     

夏热冬冷地区居住建筑夏季人员开窗行为实测与建模研究

开关窗是建筑使用者控制室内热环 境和改善室内空气品质最直接且简单的手 段,同时对建筑节能也有重要影响,因此对 人员开关窗行为的定量化描述是非常必要 的。本研究通过对夏热冬冷地区—?—自贡市 7户住宅夏季人员开窗行为的实际监测,得到 以下结论：发现实测样本中存在三种明显差 异的典型开窗行为,分别是习惯性开窗型、 高强度开窗型和习惯性关窗型;对非环境因 素分析得出,一天中不同时段以及家庭成员 吸烟与否对开窗概率影响显著,而是否为工 作日以及住户所在楼层对开窗概率无明显影 夏热冬冷地区居住建筑夏季人员开窗行为实测与建模研究 * 刘奕巧　王新如　崔　颖　魏　绅　潘　嵩　LIU Yiqiao, WANG Xinru, CUI Ying, WEI Shen, PAN Song Measurement and Modelling of Occupants’ Window Opening Behavior in Residential Buildings in the Hot Summer and Cold Winter Regions in Summer 中图分类号 TU228 文献标识码 B 文 章 编 号 2095-6304（2021）05-15-09 作者简介 刘奕巧： 吉林建筑大学寒地建筑综合节能教育部重点实 验室,马来亚大学机械工程学院,博士研究生 王新如（ 通讯作者）：天津商业大学机械工程学院,讲 师,xinru5263@ticu.edu.cn 崔　颖：宝武清洁能源武汉有限公司 魏　绅： 伦敦大学学院巴特莱特可持续建筑学院,副教授 潘　嵩： 吉林建筑大学寒地建筑综合节能教育部重点 实验室,北京工业大学绿色建筑环境与节能 技术重点实验室,教授 *寒地建筑综合节能教育部重点实验室开放课题项目; 河北省国际科技合作基地（20594501D）;“十三五”国 家重点研发计划(2017YFC0702200) 响;对于环境因素而言,当室外温度超过32 ℃,开窗概率开始降低,空调开启比例升高;室外温 度超过37 ℃,空调开启比例达到100%,但开窗比例仍有11.1%;建立了基于二元逻辑回归的夏季 高强度开窗行为预测模型,模型的预测准确率达到了86%,而室外温度是该模型最为重要的预 测因子。本文的研究成果可以用于细化能耗模拟软件及室内空气品质评价软件对该类型住宅建 筑开窗行为特征的描述,对住宅建筑节能设计、运行、改造以及住宅室内空气品质和热舒适研 究均有一定程度的参考意义。     

Comparison of energy intake prediction algorithms for systems powered by photovoltaic harvesters

Small size photovoltaic modules can harvest enough energy to power many personal devices and wireless sensor nodes. The prediction of solar energy intake is possible thanks to the periodical availability of the sunlight and its cyclic behavior. Thus, smart and innovative power management strategies can take advantage from intake prediction algorithms to optimize the energy usage by keeping the system in low power state as long as possible. On the other hand, very accurate predictions need time and energy because of complex calculations, thus an algorithm that can provide the optimal trade-off between computational effort and accuracy is a breakthrough for systems with tight power constraints. In this paper we introduce an innovative, efficient and reliable solar prediction algorithm, the weather conditioned moving average (WCMA). The algorithm has been further enhanced to increase performance using a phase displacement regulator (PDR) which reduces the average error to less than 9.2% at a minimum energy cost. The proposed new algorithm compares favorably with several competing approaches.     

自然崩落法放矿排产品位连续预测模型

简单介绍了自然崩落法的放矿原理,阐述了劳伯斯特品位估值法的原理,针对目前该方法不能计算任意放矿阶段出矿品位的缺点,提出了连续品位预测模型,并采用VB语言和Access数据库技术实现了排产品位预测软件。     

Kinetic model and prediction for coal hydrogasification

Coal hydrogasification is a key component of zero emission coal (ZEC) power generation system which discharges little CO₂ and other pollutants at a thermal efficiency close to 70%. In addition, coal hydrogasification itself has many advantages. A hydrogasification kinetic model including ten homogeneous reactions and four heterogeneous reactions is established in this work and is validated against experiment data available in literatures. The validated model is then used to predict the effects of different reaction conditions including the reaction temperature T, the reaction pressure p_t, the H₂/coal mass ratio U and the reaction time t on coal hydrogasification properties. The results indicate that coal hydrogasification is facilitated by the increased p_t and t. When T is not higher than 1273 K, the gasification process is promoted with T increment. Increasing U can promote the coal hydrogasification process on the whole. When U is larger than 0.5, however, the coal conversion ratio (x_coal) will slightly decrease with U increment.     

Determination of ionization conditions characterizing the breakdown threshold of a point-plane air interval using fuzzy logic

The objective of this paper is to study the discharge phenomenon for a point-plane air interval using an original fuzzy logic system. Firstly, a physical model based on streamer theory with consideration of the space charge fields due to electrons and positive ions is proposed. To test this model we have calculated the breakdown threshold voltage for a point-plane air interval. The same model is used to determine the discharge steps for different configurations as an inference data base. Secondly, using results obtained by the numerical simulation of the previous model, we have introduced the fuzzy logic technique to predict the breakdown threshold voltage of the same configurations used in the numerical model and make estimation on the insulating state of the air interval. From the comparison of obtained results, we can conclude that they are in accordance with the experimental ones obtained for breakdown discharges in different point-plane air gaps collected from the literature. The proposed study using fuzzy logic technique shows a good performance in the analysis of different discharge steps of the air interval.     

Prediction model,experimental optimization,and verification for yield of high-pressure crystallization: a case study of citric acid

ABSTRACT

Yield is one of the most important quality indexes for the crystal produced by high-pressure crystallization such as supercritical antisolvent (SAS) crystallization. In this study, a prediction model of yield of the SAS crystallization was proposed in the first place. Then, an experiment that prepares the citric acid particle crystallization was conducted through SAS batch device. With the help of a uniform design method, the maximum yield (0.86) was obtained under the combination of process parameters (the initial concentration of solution 0.35 g/mL, the operating temperature of 33°C, the operating pressure of 12.5 MPa, and the holding time of 3.5 h), the regression equation between yield of crystallization and four factors was obtained, and the effects of each factor on the yield are as follows: initial solution concentration > operating pressure > operating temperature > holding time. Finally, the prediction model was verified by an experiment, and the results show that the average relative error between the values calculated by prediction model and the experimental ones is 9.77%.