Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

Machine learning reveals the influences of grain morphology on grain crushing strength

Acta Geotechnica - Grain morphology has significant impacts on the mechanical behaviors of granular materials. However, its influences on grain breakage are still poorly understood due to the...     

世界气象中心(北京)全球预报服务共享平台设计与实现

世界气象中心(北京)建设是中国气象局承担世界气象组织(WMO)的全球数据处理和预报系统(GDPFS)要求的任务,为全球实时气象预报预测业务提供高效丰富的无缝隙天气气候监测、预报、预测分析指导产品及数据产品服务共享,提高区域性国际天气业务会商交流效率,国家气象中心设计并实现了世界气象中心(北京)全球预报服务共享平台,通过分析全球监测、预报预测等业务数据海量、异构、实时性强等特征,采用浏览器/服务器(B/S结构)多层架构和分布式实时处理、任务调度等关键技术实现了全球实况监测、天气模式、气候模式、模式检验数据的高效加工预处理、产品分析制作、产品自动流转、网络服务共享和业务指导等全流程业务功能,并提供了国际天气预报会商等专业化功能。平台自2018年6月6日业务运行以来,已有13个国家和地区注册会商用户,超过15万次全球访问量,为全球专业用户高效提供了全球实时天气监测、预报服务产品业务指导,未来将成为中国气象局对外气象业务指导和气象服务的重要窗口和纽带。     

百色气候变化特征及城市适应策略建议

利用气候观测数据分析表明,近60a来,百色出现了与全球气候变化背景一致的增暖变化,主要变化特征有:气温明显升高,年降水日数减少,冬季降水量增多,年日照时数减少;高温和干旱频率高,20世纪90年代以来暴雨日数偏多。与广西平均气候变化状况相比,百色的气候变化程度风险低于广西平均水平。预估到本世纪中期,百色气温仍将缓慢升高,干旱和强降水的强度可能加剧。建议科学规划,统筹协调,科学评估城市气候承载力,开展城市适应气候变化风险管理,提升生态气候环境监测及自然灾害预警应急能力,建设生态气候宜居城市。     

数字地震台网文件自动传输系统的设计

为完善数字地震台网数据服务处理功能,使用DOS脚本及汇编语言,设计开发了网络文件自动传输系统--AFTFRSD Version 1.0,每天完成前台机地震实时数据自动传输到后台机.本系统可应用于各省数字地震台网中心.     

我国现代地震台网观测技术的开拓者

引言 张奕麟先生是我国现代地震台网观测技术的开拓者和奠基人之一.20世纪60年代至90年代,他致力于现代模拟和数字地震台网观测技术研究,为推动我国地震观测技术现代化做出了突出贡献.本文就他在北京八条线遥测地震台网、国家地震局768工程,以及中国数字地震台网(CDSN)等科技项目中,发挥的历史作用做简要回顾.     

Backward automatic calibration for three-dimensional landslide models

Back-analysis is broadly used for approaching geotechnical problems when monitoring data are available and information about the soils properties is of poor quality.For landslide stability assessment back-analysis calibration is usually carried out by time consuming trial-and-error procedure.This paper presents a new automatic Decision Support System that supports the selection of the soil parameters for three-dimensional models of landslides based on monitoring data.The method considering a pool of possible solutions,generated through permutation of soil parameters,selects the best ten configurations that are more congruent with the measured displacements.This reduces the operator biases while on the other hand allows the operator to control each step of the computation.The final selection of the preferred solution among the ten best-fitting solutions is carried out by an operator.The operator control is necessary as he may include in the final decision process all the qualitative elements that cannot be included in a qualitative analysis but nevertheless characterize a landslide dynamic as a whole epistemological subject,for example on the base of geomorphological evidence.A landslide located in Northeast Italy has been selected as example for showing the system potentiality.The proposed method is straightforward,scalable and robust and could be useful for researchers and practitioners.     

500kN 足尺磁流变液阻尼器设计的关键技术

对我们制作的、目前出力居世界前列的500kN足尺MR阻尼器设计的关键技术、阻尼器的性能试验及力学模型的参数识别进行了研究。在对磁流变液材料的最大屈服剪应力、抗沉降稳定性以及磁滞响应时间等关键性能试验分析的基础上,确认该磁流变液的抗沉降稳定性和其他两项性能指标满足MR阻尼器的设计与工程应用要求。同时,对此500kN足尺MR阻尼器设计的关键技术,包括内置式碟型弹簧蓄能器、磁场防漏设计以及引线保护等进行了介绍;并通过对此MR阻尼器性能的试验,依据阻尼最小二乘法,对MR阻尼器采用的修正的B ingham模型的参数进行了识别,得到了与试验结果吻合的MR阻尼器的力学模型。通过研究可知,高性能磁流变液材料的制备以及MR阻尼器设计的关键技术是大吨位足尺MR阻尼器成功的关键。     

核心筒部分悬挂结构抗震分析的简化力学模型

提出了核心筒部分悬挂结构体系,在已有该体系振动台试验基础上,建立了该体系的抗震分析简化力学模型及其理论公式。按小震、中震和大震3种不同的地震作用情况,分析了该结构体系力学模型和动力方程的差异。利用有限元分析程序SAP2000,对这种结构体系进行了小震和大震作用下的结构地震反应分析,计算结果与试验结果吻合较好。     

Estimation of peak relative velocity and peak absolute acceleration of linear SDOF systems

In the seismic analysis and design of structures, the true velocity and absolute acceleration are usually approximated by their corresponding pseudo-values. This approach is simple and works well for structures with small damping (say, less than 15%). When the damping of a structure is enhanced for the purpose of response reduction, it may result in large analysis and design errors. Based on theory of random vibration and the established mechanism of seismic response spectra analysis, a method is developed (1) to predict the relative velocity spectra with any damping ratio level directly from the 5% standard pseudo-acceleration spectrum; and (2) to estimate the peak absolute acceleration. The accuracy of both is validated by using two selected ensembles of ground motion records.