TopSTO: a 115-line code for topology optimization of structures under stationary stochastic dynamic loading

The use of topology optimization in structural design under dynamic excitation is becoming more prevalent in the literature. While many such applications utilize frequency or time domain formulations, relatively few consider stochastic dynamic excitations. This paper presents an efficient and compact code called Top STO for structural topology optimization considering stationary stochastic dynamic loading using a method derived from random vibration theory. The theory, described in conjunction w...     

形变单位在地震文献中的正确使用

针对地震观测技术论文中有关形变单位"毫秒",即10~(-3″)混用为时间单位ms的情况,笔者从单位符号的意义及观测技术仪器的工作原理出发,最终明确,地震观测仪器中倾斜仪观测量单位应为10~(-3″),不能以时间单位ms代替,二者不能混为一谈。     

综合地震和地质数据获得的坎特伯雷地震序列的震级—频度分布模型

我们综合地质和地震数据获得了坎特伯雷地震序列的震级—频度分布模型。在确定分布曲线时,借机用新的数据解决了文献中的一个长期争议:对于断层或断裂带的地震活动性,究竟是古登堡—里克特关系还是特征地震模型描述得更好。结果表明,对于坎特伯雷地震序列的整个复合断裂带而言,若综合考虑古登堡—里克特曲线(拟合仪器目录数据)误差和格林代尔断层上大(主)震根据古地震推断的复发周期界限,震级—频度分布可用古登堡—里克特关系很好地描述。相反,对于格林代尔断层的较小区域,震级—频度分布用特征地震模型描述得更好。不同的就是尺度,因为坎特伯雷地震序列所代表的复合断裂带表现为古登堡—里克特分布,而该断裂带内的单个断层表现为特征地震分布。因此,地震风险模拟中震级—频度分布的确定必须考虑尺度因素,而不能简单地认为一条震级—频度分布曲线适用于所有断层情形。     

中亚增生造山过程与成矿作用研究进展

中亚造山带作为全球最大的显生宙增生型造山带,是大陆动力学和成矿作用研究的天然实验室.文章简要概述中国新中国成立以来中亚造山带研究发展情况,并对未来研究提出展望. 20世纪50～70年代是中亚造山带研究的奠基时期,各地质研究学派理论相继运用于解释中亚地区的地质演化.改革开放初期,李春昱先生等开创性地运用板块构造理论解析北疆及兴蒙地区大地构造演化,提出了西伯利亚、哈萨克斯坦、中朝-塔里木三大板块俯冲-碰撞的认识,并提出了索伦山至延边缝合线的观点. 20世纪90年代,中亚造山带研究进入快速发展期,前苏联学者提出了多陆块碰撞模型;土耳其学者提出了单一岛弧增生模型,指出中亚造山带是一种特殊类型的碰撞造山带.中国学者对中国北方地区的蛇绿岩、高压变质岩等进行了大量开拓性研究,划分了主要缝合带. 1999年,"中亚成矿域"概念被提出,并与环太平洋成矿域和特提斯成矿域并称全球三大成矿域.进入21世纪,鉴于中亚在大陆增生理论和成矿机制研究领域的重要性,中亚造山带研究成为国际学术前沿.中国在中亚地区布局了一系列科研项目,催生了一大批重要科研成果,包括微陆块属性、蛇绿岩时代和构造背景、岩浆弧性质、增生楔识别和解剖、区域变质-变形作用、俯冲带(超)高压变质作用、洋中脊俯冲、地幔柱与板块相互作用、多岛海构造古地理与复式增生造山时空格架、大陆增生、增生成矿、构造叠加改造等.这些成果产生了重要的国际影响.展望未来,中亚造山带主要有以下几方面的内容需要进一步深入研究:(1)古亚洲洋早期演化历史及起始俯冲机制;(2)古亚洲洋外部造山带(Extroversion)的增生机制;(3)古亚洲洋地幔属性及其时空分布;(4)古亚洲洋与特提斯洋相互作用过程;(5)显生宙大陆增生机制及其全球对比;(6)中亚成矿域增生成矿机制;(7)大陆改造机制.     

Cross-borehole flowmeter tests for transient heads in heterogeneous aquifers

Cross-borehole flowmeter tests have been proposed as an efficient method to investigate preferential flowpaths in heterogeneous aquifers, which is a major task in the characterization of fractured aquifers. Cross-borehole flowmeter tests are based on the idea that changing the pumping conditions in a given aquifer will modify the hydraulic head distribution in large-scale flowpaths, producing measurable changes in the vertical flow profiles in observation boreholes. However, inversion of flow measurements to derive flowpath geometry and connectivity and to characterize their hydraulic properties is still a subject of research. In this study, we propose a framework for cross-borehole flowmeter test interpretation that is based on a two-scale conceptual model: discrete fractures at the borehole scale and zones of interconnected fractures at the aquifer scale. We propose that the two problems may be solved independently. The first inverse problem consists of estimating the hydraulic head variations that drive the transient borehole flow observed in the cross-borehole flowmeter experiments. The second inverse problem is related to estimating the geometry and hydraulic properties of large-scale flowpaths in the region between pumping and observation wells that are compatible with the head variations deduced from the first problem. To solve the borehole-scale problem, we treat the transient flow data as a series of quasi-steady flow conditions and solve for the hydraulic head changes in individual fractures required to produce these data. The consistency of the method is verified using field experiments performed in a fractured-rock aquifer.     

表面活性剂改善钻井液速溶的效果评价

针对钻井液材料溶解慢,达到理想性能时间长,提出使用表面活性剂降低配浆水的表面张力和接触角,同时对材料有润湿和增溶作用。通过分析表面活性剂的作用机理,测试表面活性剂对钻井液基本性能影响来优化表面活性剂;观察表面活性剂对土(上海佳友土、鄂州素土和碱土)和大分子材料的性能影响来优化表面活性剂的加量。结果表明,卵磷脂1在短时间内促进材料的水化分散效果最好,且最优加量为0.2‰,对于6%的上海佳友土、鄂州素土和碱土,表观黏度分别提高20%、20%和6%。0.2‰的卵磷脂可以促进配方(4%佳友土+1‰黄原胶+0.8%改性淀粉)表观黏度提高15%,润滑性提高37%,表面张力降低42%,大分子材料分散得更均匀,泥皮更致密。      

地震复发周期性与地震灾害风险评估:一项在意大利的对比分析研究

开展严格而客观的地震灾害风险评估与真实地震活动对比测试,是进行任何负责任的地震灾害风险评估的必要前提。针对意大利境内实际发生的地震活动,将经典概率性方法(PSHA)得到的意大利抗震标准的参考灾害图与基于新的确定性方法(NDSHA)获取的可供参考的地震动图进行了交叉对比和测试。通过对大量可能地震的真实地面运动的模拟,结果表明,NDSHA方法可以给出可靠的设计地震的合理定义。NDSHA的灵活性可用于解释地震复发周期性,并可用于产出特定复发周期的地面运动图,以便与PSHA方法所获取的地面运动图进行直接对比分析。     

亚马逊上空的烟雨云

人们观测到亚马逊森林大火的浓烟减小了云滴的大小,使降水产生延迟。因为清洁云在云底以上1．5km处就可以产生降水,而被污染的云中这个高度要抬升到5km以上．在火成云中就要到7km以上了。云中低层被抑止的降雨和气溶胶沉降使得水份和烟尘向高层输送,高层的云就像能卸下很多污染物的‘烟’。在抬高了的降雨启动高度上,由于相变触发的上升气流导致强的雷雨、大雹以及其他类似的云体突破云顶进入平流层,在平流层沉降的污染物和水汽的辐射效应对气候系统有深刻的影响。大气中激发的风暴在更高层释放出潜热,这就从本质上影响了区域和全球的环流系统。这些过程共同影响了水份循环、大气中污染物的分布以及大气环流的动力学特征。     

Improved prediction of clay soil expansion using machine learning algorithms and meta-heuristic dichotomous ensemble classifiers

Soil swelling-related disaster is considered as one of the most devastating geo-hazards in modern history.Hence,proper determination of a soil’s ability to expand is very vital for achieving a secure and safe ground for infrastructures.Accordingly,this study has provided a novel and intelligent approach that enables an improved estimation of swelling by using kernelised machines(Bayesian linear regression(BLR)&bayes point machine(BPM)support vector machine(SVM)and deep-support vector machine(D-SVM));(multiple linear regressor(REG),logistic regressor(LR)and artificial neural network(ANN)),tree-based algorithms such as decision forest(RDF)&boosted trees(BDT).Also,and for the first time,meta-heuristic classifiers incorporating the techniques of voting(VE)and stacking(SE)were utilised.Different independent scenarios of explanatory features’combination that influence soil behaviour in swelling were investigated.Preliminary results indicated BLR as possessing the highest amount of deviation from the predictor variable(the actual swell-strain).REG and BLR performed slightly better than ANN while the meta-heuristic learners(VE and SE)produced the best overall performance(greatest R2 value of 0.94 and RMSE of 0.06%exhibited by VE).CEC,plasticity index and moisture content were the features considered to have the highest level of importance.Kernelized binary classifiers(SVM,D-SVM and BPM)gave better accuracy(average accuracy and recall rate of 0.93 and 0.60)compared to ANN,LR and RDF.Sensitivity-driven diagnostic test indicated that the meta-heuristic models’best performance occurred when ML training was conducted using k-fold validation technique.Finally,it is recommended that the concepts developed herein be deployed during the preliminary phases of a geotechnical or geological site characterisation by using the best performing meta-heuristic models via their background coding resource.