简介:Anoptimizationmethodisbasedtodesignasnowfallestimatemethodbyradarforoperationalsnowwarning,anderrorestimationisanalyzedthroughacaseofheavysnowonMarch4,2007.Threemodifiedschemesaredevelopedforerrorscausedbytemperaturechanges,snowflaketerminalvelocity,thedistancefromtheradarandcalculationmethods.Duetotheimprovements,thecorrelationcoefficientbetweentheestimatedsnowfallandtheobservationis0.66(exceedingthe99%confidencelevel),theaveragerelativeerrorisreducedto48.74%,andthemethodisabletoestimateweaksnowfallof0.3mm/handheavysnowfallabove5mm/h.Thecorrelationcoefficientis0.82betweentheestimatedsnowfallfromthestations50to100kmfromtheradarandtheobservation.Theimprovedeffectisweakwhentheinfluenceofthesnowflaketerminalvelocityisconsideredinthosethreeimprovementprograms,whichmayberelatedtotheuniformecho.Theradarestimateofsnow,whichisclassifiedbythedistancebetweenthesampleandtheradar,hasthemostobviouseffect:itcannotonlyincreasethedegreeofsimilarity,butalsoreducetheoverestimateandtheundervaluationoftheerrorcausedbythedistancebetweenthesampleandtheradar.Theimprovedalgorithmfurtherimprovestheaccuracyoftheestimate.Theaveragerelativeerrorsare31%and27%fortheheavysnowfallof1.6to2.5mm/handabove2.6mm/h,respectively,buttheradaroverestimatesthesnowfallunder1.5mm/handunderestimatesthesnowfallabove2.6mm/h.Radarechomaynotbesensitivetotheintensityofsnowfall,andtheconsistencyshownbytheerrorcanbeexploitedtoreviseandimprovetheestimationaccuracyofsnowforecastintheoperationalwork.
简介:帮助的酸水解作用被建立准备-carra-oligosaccharides的微波的一个快速的方法。最佳的水解作用条件被直角的测试决定。oligosaccharides的聚合(DP)的度被高效检测薄层层析(HPTLC)和polyacrylamide胶化电气泳动(页)。就HPTLC和页的结果而言,微波的最佳条件帮助了酸水解作用被决定。-carrageenan的集中是5mgmL<啜class=“a-plus-plus”>1;反应答案被适应pH3与冲淡盐酸酸;答案为在这些indic燬?燬的15个变化是在在100点的微波照耀下面的hydrolyzed吗??
简介:Thisstudyproposesanewidentificationalgorithmabouttheadmittancefunction,whichcanestimatethefullsetofsixaerodynamicadmittancefunctionsconsideringcrosspowerspectraldensityfunctionsabouttheforcesandtheturbulencecomponents.ThemethodwasfirstnumericallyvalidatedthroughMonteCarlosimulations,andthenadoptedtoestimatetheaerodynamicadmittanceofastreamlinedbridgedeck.Theidentificationmethodwasfurthervalidatedthroughacomparisonbetweenthenumericalcalculationandwindtunneltestsonamovingbridgesection.
简介:Buildingcodeshavewidelyconsideredtheshearwavevelocitytomakeareliablesubsoilseismicclassification,basedontheknowledgeofthemechanicalpropertiesofmaterialdepositsdowntobedrock.Thisapproachhaslimitationsbecausegeophysicaldataareoftenveryexpensivetoobtain.Recently,otheralternativeshavebeenproposedbasedonmeasurementsofbackgroundnoiseandestimationoftheH/Vamplificationcurve.However,theuseofthistechniqueneedsaregulatoryframeworkbeforeitcanbecomearealisticsiteclassificationprocedure.ThispaperproposesanewformulationforcharacterizingdesignsitesinaccordancewiththeAlgerianseismicbuildingcode(RPA99/ver.2003),throughtransferfunctions,byfollowingastochasticapproachcombinedtoastatisticalstudy.Foreachsoiltype,thedeterministiccalculationoftheaveragetransferfunctionisperformedoverawidesampleof1-Dsoilprofiles,wheretheaverageshearwave(S-W)velocity,Vs,insoillayersissimulatedusingrandomfieldtheory.Averagetransferfunctionsarealsousedtocalculateaveragesitefactorsandnormalizedaccelerationresponsespectratohighlighttheamplificationpotentialofeachsitetype,sincefrequencycontentofthetransferfunctionissignificantlysimilartothatoftheH/Vamplificationcurve.ComparisonisdonewiththeRPA99/ver.2003andEurocode8(EC8)designresponsespectra,respectively.Intheabsenceofgeophysicaldata,theproposedclassificationapproachtogetherwithmicro-tremormeasurescanbeusedtowardabettersoilclassification.
简介:蜿蜒地流的河免职的水库建筑学是建筑群,当层厚度在地震垂直分辨率下面时,传统的地震外形解释方法不能描绘它。在这研究,为点酒吧描述的一个地震sedimentology解释方法和工作流被造。第一,地震频率的影响和在地震思考以后的沙岩厚度被露头察觉与渗透雷达(GPR)并且地震前面的建模的地面分析。(1)沙岩厚度能影响点工具条建筑学的地震思考,这被发现。与从1/4波长增加沙岩厚度()到/2,从模糊思考各种各样的地震思考几何学,V类型思考到X类型思考;(2)地震频率能影响水库地震思考几何学。地震事件跟随使倾向的侧面的沉积表面,它是isochronicdepositional边界,在高频率地震数据当事件延长时,lithologic出现,它是水平,在低频率数据。第二,为薄层depositional描述的阶层片解释方法与地震前面的建模被讨论。最后,一个方法和工作流基于上述学习被造它包括地震频率分析,分阶段执行的90o,stratal切和片和地震侧面的综合解释。这个方法在泰戈在真实数据学习被使用浅,墨西哥湾。蜿蜒地流的河的免职的二个事件在学习层被认出。更低的单位的沙岩,在低基础水平舞台被形成,散布有限。沙岩分发尺寸和隧道蜿蜒在上面的层变得更大,它是高基础的水平免职。
简介:利用邵武探空资料,尝试将1992~2013年的闽北81个雹日归纳为五型:显式位势不稳定型(Ⅰ型)、隐式位势不稳定型(Ⅱ型)、上干下湿型(Ⅲ型)、整层潮湿型(Ⅳ型)和上层不稳定型(V型)。分析它们的特征表明:(1)Ⅰ型和Ⅱ型为位势不稳定;其它型为对流性不稳定,无条件性不稳定。(2)Ⅰ型具有明显的位势不稳定,垂直风切变达到中等强度既能出现强冰雹;Ⅱ型的边界层逆温较突出,位势不稳定表现在925hPa以上,需要有克服逆温的动力条件才能发生冰雹;Ⅲ型的冰雹发生需要整层垂直风切变大,当低层温度较低时,要在较深厚的系统性抬升作用下才能使对流充分发展;Ⅳ型具有类似暴雨的特征,当中低层风切变很强时,有利雹暴出现;Ⅴ型的能量廓线为弱对流型或假对流型,对雹暴有利之处是有明显的超低温特征且湿球温度0℃层高度低,需要有明显的能量增长机制或中等强度的垂直风切变。
简介:从23个省的工厂级的数据和在在2012生产工业和socio经济的水泥的一些国家统计数据被用来为由扩大Exergy财务方法生产工业的瓷器水泥分析exergy使用的空间分发。这个方法拿精力和原料供应和另外的外部因素(资本,劳动和环境)的包括的完整的报道进一个全面资源费用评价。在水泥生产的省的层次的扩大exergy消费和它的紧张份量上被计算然后在地区性的水平的exergy使用的凝块水平也被评估。把分析基于这,他们在在省的水平的exergy使用的尺寸和效率的空间差别被识别。而且,他们的地区性的特征被揭示。一些重要结果能如下被拉。首先,不可见的社会费用在生产工业的水泥说明了全部的exergy使用的1/10,当精力元素关于9/10分享了时。第二,在生产工业的瓷器水泥的exergy使用的粗野分发主要在象安徽和山东省一样的东方区域,并且在象四川省一样的西方的区域被集中。以exergy使用,而资本,劳动和外部环境因素的费用在中央、西方的区域为水泥生产加亮不可见的社会费用到某程度,煤和电在东方区域的精力费用中是最高的。第三,在生产工业的瓷器水泥的exergy使用的效率分发从西方说明了一个增长特征到东方特别为精力,劳动和大写的效率。环境效率上的评估显示象西藏,Xinjiang,内部蒙古和山西一样的省或区域承担了高得多的环境费用。第四,23个省能被欧几里德几何学的距离模型分类进八个组用粗野并且exergy使用的效率结果。第五,高工业集中度是为在中国生产工业的水泥的exergy效率改进的主要开车因素。
简介:BasedonarrivaltimedataofseismicphasesofML≥2.0earthquakesmeasuredatShanxiDigitalSeismicNetworkfortheperiodfromJanuary2001toOctober2014,V_P/V_SintheShanxiregioniscalculatedusingtheWadatisinglestationandmulti-earthquakemethod,andaninvestigationisconductedintothevariationbehaviorofV_P/V_SintheShanxiregionbeforeandafterthethreeearthquakesofMS≥4.5in2010.OurstudyfindsthatabnormalV_P/V_Sappearedearlieratdistantstationsbeforeallofthethreeearthquakes,whichisatthetimerangefrom6monthsto1yearbeforetheearthquakes,andlateratnearstations,atthetimerange10daysto2monthsbeforeearthquakes.Therefore,itspossibletonarrowdownthescopeofthelocationinearthquakepredictionfromthedistantandnearstationdata.ThecalculationsofDongshanseismicstationindicatethatthesizeoftheresidualoftheorigintimehasimpactonthedetailofV_P/V_Svariation,thus,appropriatethresholdsshouldfirstlybesetfortheresidualsoforigintimeateachseismicstationinpracticalapplication,toensurescientificandsteadyV_P/V_Scalculations.