Analysis ofReservoir Performancefor Shale Gas Systems(页岩气系统储层特征分析)

Purification Of Minute Virus Of Mice Using High PerformanceTangential Flow FiltrationMiriam I. Hensgen1,2, Peter Czermak2,4,Jonathan O. Carlson3,S. Ranil Wickramasinghe11Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO,USA2Institute of Biopharmaceutical Technology, University of Applied Sciences Giessen-Friedberg,35390 Giessen, Germany3Department of Microbiology, Immunology & Pathology, Colorado State University, Fort Collins,CO, USA4Department of Chemical Engineering, Kansas State University, Manhattan, KS, USACorresponding author: ***************************.deKeywords: Virus Recovery, High Performance Tangential Flow Filtration, Ultrafiltration, Minute Virus of Mice,Downstream Purification, Filtration ProcessAbstractMembrane technology has proven to be a mainstay separation technology over the past two decades. Some major advantages of membrane technology are application without the addition of chemicals and a comparatively low energy use. With its current applications, membrane technology has been widely used in biotechnology processes. Cell harvesting and virus purification/removal are important processes in many downstream purifications of biopharmaceutical products. For this project, ultrafiltration (UF) for virus purification from cell culture broth was used. Recently, it has been demonstrated that UF is a powerful tool for purification of other viruses such as Aedes aegypti and virus-like particles. More precisely, high-performance tangential flow filtration (HPTFF) will be used, which was first introduced by Robert van Reis in 1997. To date HPTFF has been used in other projects, as for protein concentration, purification, and buffer exchange as a single unit operation. The virus used in this study was the parvovirus Minute Virus of Mice (MVM); characterized by an average diameter of 22-26 nm and icosahedral symmetry. Experiments were conducted with 300, 100 and 50 kDa Sartorius membranes. Results obtained indicate that using the 50 or 100 kDa membrane, viral particles get excluded, whereas the 300 kDa membrane allows the passage of the virus particles into the permeate. In HPTFF mode the permeate flux decline of the 300 kDa ultrafiltration membrane is much greater than for the other membranes used. One possible explanation for this decay could have to do with the virus particles’ access to the membrane pores (gradual pore narrowing). Additionally the permeate flux and level of protein rejection as well, are strongly affected by the cell culture medium.This article published as: Hensgen M I, P Czermak, J O Carlson, S R Wickramasinghe: Purification of Minute Virus of Mice using High Performance Tangential Flow Filtration, Desalination 250 (2010) p. 1121-11241. IntroductionMembrane technology has proven to be a mainstay separation technology over the past two decades. Some major advantages of membrane technology are application without the addition of chemicals and a comparatively low energy use. Cell harvesting and virus purification/removal are important processes in many downstream purifications of biopharmaceutical products [1]. In order to avoid membrane fouling ultrafiltration with tangential flow is emplyed because high density cell cultures and the corresponding increase in the level of cell debris cause fouling of membrane systems. Thus membrane fouling by cell debris and or cell-derived proteins presents a serious problem. For this project, ultrafiltration (UF) for virus purification from cell culture broth was used. Recently it has been demonstrated that UF is a powerful tool for purification of other viruses such as Aedes aegypti and virus-like particles [4, 5, 6]. More precisely, high-performance tangential flow filtration (HPTFF) will be used, which was first introduced by Robert van Reis in 1997 [2, 3]. The virus used in this study was the parvovirus Minute Virus of Mice (MVM); characterized by an average diameter of 22-26 nm and icosahedral symmetry. In general, members of parvoviridae are among the smallest known DNA viruses. They replicate in the nucleus of actively dividing cells. The genome of MVM is linear, single stranded, and approximately 5kb long [7, 9]. Environmental extremes, like pH or temperature do not critically damage the virus [8]. MVM has a broad in vitro host range such as NBK324 cells, A9 cells, and T-cell lymphomas producing cytopathic effects. As part of this project, A9 mouse cells were infected with MVM.The experiments were conducted with 50, 100 and 300 kDa Sartorius membranes. The analysis methods included flux measurement, real-time PCR and protein concentration determination (data not shown).2. Materials and MethodsCell culture and virus productionA9 mouse Fibroblast cells (ATCC® No. CCL-1.4, Manassas, VA) were grown at 37°C and 10% carbon dioxide in Dulbecco's Modified Eagle's Medium (DMEM High Glucose, with 4.5g/L Glucose, Fisher Scientific-Hyclone, Cat. No. SH3002201, Pittsburgh, PA) in plastic cell culture T-75 flasks (TPP®, Product No. 90076, Trasadingen, Switzerland). The medium was supplemented with 1% penicillin (Invitrogen, 50 units/ml, Carlsbad, CA) and streptomycin (Invitrogen, 50 µg/ml) and 10% heat inactivated fetal bovine serum (Atlas Biologicals, Catalog No. F-0500-A, Fort Collins, CO). After formation of an adherent cell monolayer, sub-cultivation was carried out by removing old medium and adding fresh Trypsin- EDTA solution (Gibco-Invitrogen, 0.25% Trypsin-EDTA, Product No. 25200). For initial infection of A9 cells with Minute Virus of Mice (MVM), approximately 200 µl MVM stock solution (ATCC® No. VR-1346) was added to a confluent monolayer of cells in a T-75 flask. The infected cells were incubated for 6-8 days under the same conditions as uninfected cells. After incubation the cells (Corning Incorporate, Corning tubes, 50ml, Corning, NY) cells were lysed using three freeze/thaw cycles with freezing at -80°C and thawing in a 37°C water bath. The cell lysate was then centrifuged using a Beckman GS-6R centrifuge (Beckman, Fullerton, CA) at 1500 rpm at 4 °C for 15 minutes to remove large cell debris. The supernatant, containing the virus, was filtered using 0.22 µm bottle top sterilization filters (Nalgene Company, Rochester NY) and stored at -80 °C. Before using the virus solution for experiments, a 1:100 dilution with pure media is carried out, meaning that the amount of FBS in samples collected is low.Membrane FiltrationFiltration experiments were conducted using flat sheet Sartocon® Slice 200 cassettes (Sartorius AG, Göttingen, Germany). Three ultrafiltration membranes, Sartorius polyethersufone 308 1465002E SG, 308 1466802E SG and 308 1467902E SG, with molecular weight cut offs (MWCO) of 50, 100 and 300 kD were tested in this study. All experiments were run at a feed flow rate of 150 mL/min controlled by a peristaltic pump. Figure 1 shows the experimental set up for high performance tangential flow filtration (HPTFF) whereas the experimental set up for tangential flow filtration (TFF) is not shown. Then 500 mL of clarified medium containing virus was added to a feed reservoir. Additionlly, throughout the entire experiment 1ml samples of the feed, retentate and permeate were collected at fixed mass points of intervals of 25g of the permeate, for analysis of virus titer and protein concentration. All samples were analyzed in triplicate and average results reported.Figure 1: High performance tangential flow filtration system 50kDa, 100kDa and 300kDa PES membranes were used. Experiments were run at a flow rate of 150 ml/minProtein assayProtein concentration was measured using a bicinchoninic acid assay (BCA, Protein Assay Kit, Pierce, Rockford, IL) following the manufacturer’s instructions. As described by the manufacturer, the protein concentration is determined and reported with reference to a standard albumin solution provided by the manufacturer. All samples were analyzed in triplicate and average values reported.Quantitative Polymerase Chain Reaction (QPCR, rt-PCR)The quantitative QPCR assay is a rapid, sensitive and efficient way to compare samples. The QPCR assay will detect both viral genomic and naked DNA. In order to prevent detection of naked DNA, samples are DNAse (RQ1 RNA- free DNAse, Category No. M6101, Promega, Madison, WI) treated for 45minutes. Reverse and forward primers were designed for quantification of Minute Virus of Mice (MVM). Primers for MVM DNA amplification were as follows:forward,5’-GAC GCA CAG AAA GAG AGT AAC CAA-3’ and reverse, 5’-CCA ACC ATC TGC TCC AGT AAA CAT-3’. Further melting curve analysis was conducted in order to receive information about the length of the fragment and of the specificity of the primers. Amplification and real-time detection of PCR products were performed on the DNA samples using the iCycler system (Bio-Rad Laboratories, iQTM 5 iCycler, Multicolor Real time PCR Detection System) withSYBR Green Mastermix (Bio-Rad Laboratories iQ™ SYBR® Green Supermix). At the end of the extension step of every cycle, the fluorescence was measured. Cycling conditions consisted of an initial step at 95 °C for 10 minutes, which is vital for breaking up viral capsids and it also activates the polymerase enzyme. This step was followed by 40 cycles with the following thermal profile: 95°C and 15s, 57°C and 10s, and 72°C and 45s, and 72°C and 10s for real time detection.3. ResultsVirus titer analysisThe variation of virus titer in retentate and permeate over permeate volume collected for HPTFF and TFF mode is displayed in figures 2 and 3. Permeate virus titers in HPTFF and TFF are only shown when they were detectable.Figure 2: Variation of the virus titer in the retentate and permeate with cumulative permeate volume during HPTFF. Samples were diluted 1000 fold for rt - PCRFor the 50 and 100 kDa membranes, no virus particles were detected in permeate samples, whether for TFF nor for HPTFF mode; whereas the 300 kDa membrane showed no retention of virus particles. To be precise, it was possible to detect virus particles in retentate and permeate samples of the 300 kDa membrane in both modes. Further, complete passage is shown by the fact, that the same viral titers were measured, using rt-PCR, in both retentate and permeate samples. Consequently, exclusion of virus particles is only feasible with 50 kDa and 100 kDa membrane cassettes. Pore size of 300 kDa is nominal, which means that the greatest percentages of pores are around 300 kDa. Potentially, virus particles “squeeze” through membrane pores, meaning the virus takes advantage of the pore size distribution. The determined detection limit, using Sybr Green I dye for the detection of M inute Virus of Mice, was determined to be 14 viral copies/μl. Due to an extra 10 fold dilution, which has to be added because of DNase treatment of samples, the final detection limit was set to 1.4*105 viral copies/ml. We showed that with a 95% confidence less than 1.4*105 viral copies/ml are present in permeate samples (data not shown). Furthermore, the retention percentage is less than 0.01%, as determined by dividing the limit of detection by the starting viral titer (approximately 109).Figure 3: Variation of the virus titer in the retentate and permeate with cumulative permeate volume during TFF. Samples were diluted 1000 fold for rt - PCRTangential FiltrationThe variation of permeate flux with permeate volume in HPTFF mode for 50, 100, 300 kDa membranes is presented in figure 4. The graph demonstrates, that all flux regimes are relatively constant during the experiments, except for drop in 300 kDa curve. In addition, the 300 kDa curve shows a decline in flux throughout the entire experiment. One possible explanation for the decay could have to do with the virus particles’ access to the membrane pores. In the case of the 50 and 100 kDa membranes, the virus particles have little to no access to the pores (particles are too large) and therefore could not non-specifically bind to the internal pore structure of the membrane. Gradual increases in virus particle binding to the inside of the pores (and therefore gradual pore narrowing) could account for the observed flux decrease. The regular interval drops observed in all flux curves correspond to points where samples were taken from the permeate outlet.Figure 4: Variation of the permeate flux with cumulative permeate volume in HPTFF mode. Virus in DMEM medium was pumped through PES 50, 100 and 300 kDa membranes at a flow rate of 150 ml/min (1:100 dilution of initial virus solution with pure media was carried out before each experiment)Figure 5: Variation of the permeate flux with cumulative permeate volume in TFF mode. Virus in DMEM medium was pumped through PES 50, 100 and 300 kDa membranes at a flow rate of 150 ml/min (1:100 dilution of initial virus solution with pure media was carried out before each experiment)Figure 5 shows as expected, the highest permeate flux with the 300 kDa membrane cassette. Comparing the permeate flux of 50 and 100 kDa membranes, it is significant that those two fluxes differ from each other. At first, this seems to be an expected result, but the fact that the 50 kDa flux is higher than the 100 kDa flux leads to the question, why do the larger pores of the 100 kDa membrane not give a higher flux compared to the smaller pores of the 50 kDa membrane. Occurrence of higher flux using the 50 kDa membrane can be explained by an irregularity in pores sizes (larger pore-size distribution). Pores are never identical or uniform due to production steps. This hypothetical assumption was discussed and agreed upon by Sartorius (email contact with Sartorius). This high flux decay for the 50 kDa membrane can be explained by a gradual blocking of the small pores of the membrane, which then results in a flux decrease. During this type of process, tangential flow filtration, a thin cake layer of retained viral particles and other particles builds up on the membrane surface. The thickness and especially particle size distribution of this layer controls the passage of most soluble components [9].4. ConclusionsResults obtained indicate that 50, and 100 kDa membranes are able to retain the Parvovirus Minute Virus of Mice, whereas the 300 kDa membrane is not capable of excluding viral particles of MVM, due to the fact that the same amount of viral particles is found in the 300 kDa permeate and retentate for TFF and HPTFF mode (measured by rt-PCR). The decrease in permeate flux for the 300 kDa ultrafiltration membrane is much greater than for the 50, and 100 kDa membranes for HPTFF, indicating possible entrapment of virus particles in membrane pores. The permeate flux and level of protein rejection is strongly affected by the cell culture growth medium.Feed fluxes for all membranes were always lower than initial water fluxes due to the higher viscosity of DMEM media supplemented with FBS compared to water viscosity (data not shown). Real-time PCR was used for virus titer determination as well as for evaluation of the ultrafiltration membranes ability to exclude viral particles. By using the Sybr Green assay we developed, it was possible to detect the amount of viral particles in samples collected with a determined detection limit of 14 viral copies/μl.References[1] Olsen, W. P.; Separations Technology: Pharmaceutical and Biotechnology Applications; 1st edition;Informa Healthcare, 1995; 122-130V an Reis,R.; Gadam, S.; Frautschy, L.N.; Orlando, S.; Goodrich, E.M.; Saksena, S.; Kuriyel, R.;[2]Simpson, C.M.; Pearl, S.; Zydney, A.L. High Performance Tangential Flow Filtration, Biotechnology and Bioengineering, 1997, 56, 71-82[3] Van Reis,R.; Brake, J.M.; Charkoudian, J.; Burns, D.B.; Zydney, A.L. High–performance tangentialflow filtration using charged membranes, Journal of Membrane Science, 1999, 159, 133-142[4] Czermak, P.; Grzenia, D.; Wolf, A.; Carlson, J.; Specht, R.; Han, B.; Wickramasinghe, S.R.Purification of the densonucleosis virus by tangential flow ultrafiltration and by ion exchange membranes, Desalination 224, 2007, 23-27[5] Grzenia D., Specht R., B.B. Han, J.O. Carlson, P. Czermak, S. R. Wickramasinghe: Purification ofDensonucleosis Virus by Tangential Flow Filtration, Biotechnology Progress 22, 2006, 1346 -1353 [6] Czermak, P., Nehring, D., Wickramasinghe, S.R.: Membranfiltration in Animal Cell Culture, inPoertner, R. (ed.): Animal Cell Biotechnology: Methods and Protocols, 2nd Edition, Chapter 19, p.397-420, Humana Press, Totoba USA, 2007[7] Agbandje-McKenna, M.; Llamas-Saiz, A.L.; Wang, F.; Tattersall, P.; Rossmann, M.G. FunctionalImplications of the Structure of Murine Parvovirus, Minute Virus of Mice, Structure, 1998, 6, 1369-1381[8] Segovia, J.C.; Real, A.; Bueren, J.A.; Almendral, J.M. In Vitro Myelosuppressive Effects of theParvovirus Minute Virus of Mice (MVMi) on Hematopoietic Stem and committed Progenitor Cells, Blood, 1991, 77, 980-988[9] Llamas-Saiz, A.L.; Agbandje-McKenna, M.; Wikoff W.R.; Bratton, J.; Tattersall, P.; Rossmann, M.G.Structure of minute virus of mice, Acta Crystallographica, 1997, 93-102。

第 51 卷 第 4 期石 油 钻 探 技 术Vol. 51 No.4 2023 年 7 月PETROLEUM　DRILLING　TECHNIQUES Jul., 2023doi:10.11911/syztjs.2023023引用格式：蒋廷学. 非常规油气藏新一代体积压裂技术的几个关键问题探讨[J]. 石油钻探技术，2023, 51（4）：184-191.JIANG Tingxue. Discussion on several key issues of the new-generation network fracturing technologies for unconventional reservoirs [J].Petroleum Drilling Techniques，2023, 51(4)：184-191.非常规油气藏新一代体积压裂技术的几个关键问题探讨蒋廷学1,2,3（1. 页岩油气富集机理与有效开发国家重点实验室, 北京 102206；2. 中国石化页岩油气钻完井及压裂重点实验室, 北京 102206；3. 中石化石油工程技术研究院有限公司, 北京 102206）摘　要: 体积压裂技术是实现非常规油气藏高效开发的关键，围绕有效改造体积及单井控制EUR最大化的目标，密切割程度、加砂强度、暂堵级数及工艺参数不断强化，导致压裂作业综合成本越来越高。

为此，开展了新一代体积压裂技术（立体缝网压裂技术）的研究与试验，压裂工艺逐渐发展到“适度密切割、多尺度裂缝强加砂、多级双暂堵和全程穿层”模式。

为促进立体缝网压裂技术的发展与推广应用，对立体缝网的表征、压裂模式及参数界限的确定、“压裂–渗吸–增能–驱油”协同提高采收率的机制、一体化变黏度多功能压裂液的研制、石英砂替代陶粒的经济性分析及“设计–实施–后评估”循环迭代升级的闭环体系构建等关键问题进行了探讨，厘清了立体缝网压裂技术的概念、关键技术及提高采收率机理，对于非常规油气藏新一代压裂技术的快速发展、更好地满足非常规油气藏高效勘探开发需求，具有重要的借鉴和指导意义。

Identification of TranscriptomeSNPs Assessing Allele-Specific Gene Expression in a Super-Hybrid Rice Xieyou9308Rongrong Zhai1.,Yue Feng1.,Xiaodeng Zhan1,Xihong Shen1,Weiming Wu1,Ping Yu1,Yingxin Zhang1, Daibo Chen1,Huimin Wang2,Zechuan Lin1,Liyong Cao1*,Shihua Cheng1*1State Key Laboratory of Rice Biology,China National Rice Research Institute,Hangzhou,Zhejiang,China,2College of Agronomy,Shenyang Agricultural University, Shenyang,Liaoning,Chinais an important component of lead to speciation, adaptive[1,2,3,4],and can give rise to a[5].Combination of these allelic of gene action, and is thought to contribute to heterosis,a phenomenon in which hybrids show improved and superior performance compared with either inbred parental line[6,7,8].Most efforts to understand the genetic mechanisms of heterosis have been focused on total gene expression levels in hybrids and their parents,with differential regulation of parental alleles in hybrids not well characterized. Although allele-specific gene expression(ASGE)in inter-specific hybrids has been reported in insects[9],fish[10],mammals [11,12],and plants[5,13,14],illuminating the direct impact of parental alleles on gene regulation,these studies were conducted using a limited number of genes.Recently-developed next-generation high-throughput RNA sequencing technology(RNA-Seq)has enabled the analysis of genome-wide ASGE,facilitating the examination of allelic contributions to gene expression in hybrids.Allelic expression bias in hybrids has been found to be correlated with parental differences[15],with trans effects possibly mediating most hybrid transcriptional differences[16].No attempt has been made, however,to compare ASGE at different developmental stages on a global transcriptomic scale.In this study,we focused our research on the late-stage high-vigor super-hybrid rice variety,Xieyou9308,which has a grain yield as high as12.236103kg?hm22and was designated as a‘super rice’by the Chinese Ministry of Agriculture in2005[17]. Xieyou9308is derived from a cross between the restorer line R9308(with25%japonica genetic composition)and the maternal line Xieqingzao B(indica).We applied RNA-Seq technology to assess genome-wide ASGE in the hybrid genetic background at tillering and heading stages.Results from this study indicate thatin the hybrid,Materials and MethodsPlant materials andRNA isolationExperiments were conductedin2011on Xieyou9308,a super-hybrid rice commonly plantedin China,and its parents XieqingzaoB(female)and R9308(male).After approximately30d of growth inthe field at theNational Rice Research Institute,Fuyang,China,40seedlings of each genotype were transplanted into plots ofplastic foam floating in a pool filled with nutrient solution.Two rootsof each genotype were collected at tillering and heading stages andimmediately frozen in liquid nitrogen.Total RNA was extractedfrom roots with Trizol reagent(Invitrogen,Carlsbad,CA)andpurified using an Oligotex mRNA Midi kit(Qiagen,Valencia,CA).RNA quality was assessed on a Bioanalyzer2100(Aligent,SantaClara,CA);all samples were found to have RNA Integrity Number(RIN)values greater than8.5.RNA-Seq library preparation and sequencingPoly(-A)-containing mRNA was isolated from total RNA in tworounds of purification using poly-T oligo-attached magnetic beads.Purified mRNA was then fragmented using an RNA fragmenta-tion kit,converted to cDNA using reverse transcriptase andrandom primers,and PCR amplified for18cycles(Illumina).PCRproducts were loaded onto an Illumina Hiseq2000instrument andsubjected to paired-end(100bp62)sequencing for100cycles.Processing of fluorescent images into sequences,base calling,andquality value calculations were performed via the Illumina dataprocessing pipeline(version1.8).Single nucleotide polymorphism(SNP)diversity analysisAfter filtering out low-quality reads(i.e.,reads in which morethan30%bases had Q-scores below20)from the raw reads,wediscarded low-quality bases(Q,20)from the59and39ends of theremaining high-quality reads.Cleaned RNA-Seq reads weremapped to the Nipponbare reference genome(IRGSP build5.0)by determiningfrom the binomial(i.e.,thein the hybridsthis publication haveunder accessionTranscriptome profileDifferentialR software edgeR(R version:2.14;edgeR version:2.3.52)[19].We characterized gene expression levels in terms of reads perkb per million reads(RPKM)[20],caculated false(FDR)for each transcript,and estimated foldlog2values of FC.Transcripts that exhibited anan estimated absolute log2(FC)$1weresignificantly differentially expressed.Transcriptestimated as the number of mapped reads for aby100bp and then divided by the summed exonlocus.ResultsDeep sequencing and mapping of RNA-Seq readsRNA-Seq technology is a powerful approach for transcriptionalanalysis and ASGE assessment[21,22].To measure ASGEpatterns in rice,we amplified cDNA fragments from a heteroticcross involving Xieyou9308,its maternal line Xieqingzao B,andpaternal line R9308,and sequenced them on an IlluminaHiseq2000platform.In total,448million short reads wereobtained at tillering and heading stages,with391million high-quality100-bp reads selected for further analysis.With respect togene expression levels,the two biological replicates were in goodagreement(0.86,R2,0.96).We then pooled and aligned theshort reads against the Nipponbare reference genome(IRGSPbuild5.0),and found that50.32–73.09%of reads were mapped toexonic regions,2.12–2.83%to intronic regions,and4.04–5.66%root and aboveground phenotypes relative to its two(Figure2).Although this superior performance may be dueinteraction of the two genomes,the genetic mechanismsin producing such hybrid phenotypes are not well understood.investigate ASGE in the hybrid,we identified SNPs fromsequencing reads by comparing each base position in exons of38,872annotated transcripts.After applying quality controlcriteria,9325SNPs(3746transcripts)were further analyzedS1).The most frequently occurring SNPs involved C to T(corresponding to G to ACombined,these mutationisTo ensure accuracyand reliability,only SNPs exhibitinga significant allelic bias (P ,0.01)were included in our analyses.In addition,among those transcripts with more than one SNP identified,two showed a contradictory allelic expression bias for different SNPs and were excluded from further analyses.Out of 4685identified SNPs (2793transcripts)(Table S2),significant allelic biases were 336SNPs (289transcripts)from the tillering stage and (316transcripts)from the heading stage (Figure 4)effects of gene the hybrid.We designated the ratio of and Xieqingzao B as R9308s /Xieqingzao B s and the ratio of allelic expression in the hybrid Xieyou9308as R9308a /Xieqingzao B a .We found that most transcripts with higher levels of gene expression in R9308also exhibited allelic biases towards R9308in the hybrid (Figure 5).Assessment of ASGE in the F 1hybridWe examined allelic expression differences between tillering and heading stages and found that 480transcripts showed allelic expression biases during at least one stage,with 125showing allelicFigure 2.Illustration of heterosis in Figure 4.Example of a transcript showing allelic bias in Xieyou9308at heading stage.Number of reads detected for a given parental allele at each SNP position is plotted.doi:10.1371/journal.pone.0060668.g004expression biases at both tillering and heading stages and 355showing allelic expression biases at only one stage.Out of the 125transcripts exhibiting biases at both stages,92showed allelic expression biases towards the R9308allele and 26towards the Xieqingzao B allele.We further investigated the 92R9308-biased transcripts using Web Gene Ontology Annotation (WEGO)software [23]and found that these transcripts could be classifiedinto a diversity of functional subcategories,such as cell and cell part in the cellular component category,binding and catalytic processes in the molecular function category,and cellular and metabolic processes in the biological process category (Figure 6).In addition,195of 289transcripts at the tillering stage and 195of 316transcripts at the heading stage showed allelic expression biases towards the R9308allele.To further investigate transcripts showing strong allelic expres-sion biases in the F 1hybrid,we analyzed 38transcripts exhibiting expression almost exclusively from one parental allele (the fraction of reads carrying R9308allele was less than 0.3or greater than 0.7at tillering or heading stages)(Table S5).Among these 38allele-specific expressed transcripts,20predominantly expressed the R9308allele at both stages,and 14primarily expressed the Xieqingzao B allele.In addition,four transcripts showed different allelic biases between the two stages.The annotation indicated that 26transcripts could be functionally characterized.Transcripts encoding proteins involving resistance to diseases or other stresses,such as nucleotide-binding adaptor shared by APAF-1,R proteins,and CED-4(NB-ARC)protein,pathogenesis-related (PR)protein,chitin elicitor receptor kinase,plant disease resistance response protein,and nucleotide binding site-leucine rich repeat (NBS-LRR protein),were predominant in the annotated list (Table 1).We further analyzed total and allelic expression with respect to the two parents and the hybrid in the above-mentioned resistance transcripts.Two transcripts (Os02t0272900and Os11t0229300)at both tillering and heading stages and one transcript (Os07t0617100)at the heading stage showed significant total expression differences between parental strains.The other transcripts did not show significantly different total expression between parental strains.For Os11t0229300,R9308a /Xieqingzao B a ratios in the hybrid were as expected from R9308s /Xieqingzao B s ratios of the parental strains;however,R9308a /Xieqingzao B a ratios of Os02t0272900in the hybrid were lower than expected from R9308s /Xieqingzao B s ratios.DiscussionASGE in hybrids can be studied using two general approaches [24].The first approach,a polymorphism-directed method,utilizes known genome variants and can achieve highly ASGE results [9,25].A second approach employs SNP arrays to examine tens of thousands of ASGE sites simultaneously [13,26].Both approaches,however,requires prior knowledge of genomic information.Another approach,used in this study,is based on RNA-Seq,does not rely on previous knowledge of genetic variation and provides an unbiased view of gene regulation.TheFigure 5.Allelic biases in Xieyou9308according to their differences between parents.R9308s ,gene expression levels in R9308;Xieqingzao B s ,gene expression levels in Xieqingzao B;R9308a ,R9308allele;Xieqingzao B a ,Xieqingzao B allele.doi:10.1371/journal.pone.0060668.g005single-base resolution obtained using this method provides in-formation regarding both transcript abundance and allelic bias.In this study,we employed Illumina/Solexa sequencing to identify SNPs between the parental lines R9308and Xieqingzao B and quantify ASGE in the F 1hybrid Xieyou9308.Interestingly,we found that CT and GA SNPs between R9308and Xieqingzao B constituted nearly 68%of all identified SNPs,consistent with a previous study in which these SNP types accounted for 73%of SNPs between Nipponbare and 93–11[16].This phenomenon may be due to methylated cytosines that mutate more frequently than non-methylated cytosines.In addition,deamination of methylcytosine,yielding thymine,occurs at higher rates than other spontaneous mutations [16,27,28,29].DNA methylation is a heritable epigenetic mark;it can control gene expression and environmental stress responses,and may play a role in heterosis in plants [16,30,31].In a future study,we plan to determine if DNA methylation is present in the parents and their F 1hybrid,and,if so,to characterize how methylation from inbred parents interacts during generation of their hybrid progeny and contributes to heterosis.In our study,only 480(17%)of 2793identified transcripts showed significant allelic biases at tillering and heading stages.A similar result was observed in another recent study,in which 398(22.7%)out of 1754genes exhibited significant allelic expression differences in a reciprocal F 1hybrid between Nipponbare and 93–11[15].Differences in allelic expression were also observed in 73%and 57%of identified genes in maize and Populus ,respectively [5,14].In contrast,in a study of hybrid mice,allelic expression differences were found in only 10%of genes [11].The relatively high allelic expression variation observed in maize and Populus is probably a consequence of their highly polymorphic genomes.Similarly,the genetic divergence between indica and japonica subspecies may account for the higher degree of allelic expression variation observed compared with mouse hybrids [5].Of the 480transcripts that showed allelic expression biases during at least one stage,67%and 62%were biased towards the R9308allele at tillering and heading stages,respectively.In addition,transcripts with higher gene expression levels in R9308also exhibited R9308allelic biases in the hybrid.Furthermore,92(74%)of the 125transcripts exhibiting allelic expression biases atboth tillering and heading stages were biased towards the R9308allele at both stages and were associated with different functional proteins.These results indicate that R9308alleles tend to preserve their characteristic activity states in the hybrid and may play important roles in hybrid vigor at both stages.Functional diversity of the R9308alleles in the hybrid may have an impact on hybrid performance.Interestingly,about 355(74%)of the 480transcripts with allelic biases showed divergent allelic expression patterns at different developmental stages,indicating that allelic expression in hybrids can be highly stage-specific [5,32].Allelic variation in gene expression may arise from cis -and/or trans -regulatory elements [9].Alteration of cis -elements may affect aspects such as promoter strength,enhancer action,or transcript stability,whereas trans -element changes may involve structure,binding affinities,or intercellular levels of factors inuencing transcription [21].Cis -and trans -regulation can be distinguished by comparing ratios of species-specific transcripts between F 1hybrids and parental lines [5].If a mutation occurs in a cis -element,the affected gene shows the same ratio of allelic expression levels in both the hybrid and parents.On the other hand,if trans -elements are altered in the parents,no differences in allelic expression are displayed for that gene in the F 1hybrid because both alleles are exposed to the same subcellular environment.In our study,most transcripts (89.65%at the tillering stage and 88.69%at the heading stage)exhibited relatively balanced allelic expression in the hybrid genetic background,suggesting that trans effects may dominate genetically mediated allele-specific expression [18].Based on findings of a previous study,alleles derived from different parents may be differentially regulated in hybrids during plant development and in response to environmental signals [14].In our study,we analyzed 38transcripts exhibiting expression biases towards one parental allele.Four transcripts encoding UPF0307protein,ATP-binding cassette (ABC)transporter pro-tein,and Zinc finger RING-type domain containing protein displayed different allelic biases between the two stages,suggesting differential roles for the alleles during hybrid development.A majority of the 38transcripts,however,showed consistent allelic biases and were associated with different functional proteins.It should be noted that these transcripts were relatively enrichedinFigure 6.GO classification of 92R9308-biased transcripts.doi:10.1371/journal.pone.0060668.g006pathways for resistance to diseases or other stresses,implying that this category may be involved in vigorous growth in the hybrid and deserves further investigation.Furthermore,the R9308a/ Xieqingzao B a ratios of Os11t0229300(encoding the NBS-LRR protein)was as expected from R9308s/Xieqingzao B s ratios, implying the involvement of cis-regulation;in contrast,R9308a/ Xieqingzao B a ratios of Os02t0272900(encoding the NB-ARC protein)were lower than expected R9308s/Xieqingzao B s ratios, suggesting both cis-and trans-regulation.The differential regula-tion of the two parental alleles of these resistant transcripts may contribute to Xieyou9308hybrid vigor.ConclusionsIn this study,roots from tillering and heading stages of the super-hybrid rice Xieyou9308and its parents were used for global transcriptional analysis and assessment of ASGE.Our results demonstrate that Illumina paired-end sequencing is a powerful tool for exploring allelic expression patterns and gene regulatory phenomena in interspecies hybridization,and may provide valuable information to further elucidate molecular mechanisms of heterosis.Supporting InformationTable S1SNPs detected in the hybrid at tillering andTable S2SNPs showing consistent allelic expression biases in the hybrid.(XLSX)Table S3SNPs showing significant allelic biases for accumulated transcripts in the hybrid at the tillering stage.(XLSX)Table S4SNPs showing significant allelic biases for accumulated transcripts in the hybrid at the heading stage.(XLSX)Table S5Thirty-eight transcripts showing biases to-wards one parental allele in the F1hybrid.(XLSX)AcknowledgmentsWe thank Mr.Weijie Song,Dr.Gulei Jin,and Dr.Qiongyi Zhao for technical support and excellent discussions,and the associate editor and anonymous reviewers for their valuable suggestions.Author ContributionsConceived and designed the experiments:RRZ YF SHC LYC.Performed the experiments:RRZ YF HW.Analyzed the data:RRZ YF ZCL. 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SH系列表面活性剂筛选与评价-化工论文-化学论文——文章均为WORD文档，下载后可直接编辑使用亦可打印——摘要：针对江汉油区高矿化度、高地层温度地层条件研制出抗盐耐温的阴-非离子型SH系列表面活性剂。

通过溶解配伍性实验、界面张力测试, 筛选出耐温抗盐的SH01、SH03两种表面活性剂。

二者的乳化性、长期稳定性、抗盐性和耐温性能均较好, 且SH03表面活性剂性能优于SH01, 在低浓度下SH03表面活性剂可有效降低油水界面张力。

实验表明, 用浓度为0.3%的SH03表面活性剂0.3PV驱替岩芯, 采收率可提高6%。

关键词：表面活性剂; 耐温性; 耐盐性; 界面张力;Abstract：Heat-resistance and salt-tolerance surfactants, Yin-non-ionic type SH series, are developed aiming at hypersalinity and high formation temperature conditions in Jianghan Oilfield.Two surfactants (SH01 and SH03) are screened out through dissolution compatibility experiment and interfacial tension test.They are good at emulsibility, long-term stability, salt tolerance and heat resistance.SH03 is better than SH01 in performance and can reduce oil-water interface tension.the experiment shows that recovery efficiency can be increased by 6% by using 0.3 PV SH03 with 0.3% concentration to displace rock core.Keyword：Surfactant; Heat Resistance; Salt Tolerance; Interfacial Tension;江汉油区为盐湖沉积环境, 发育了下第三系沙市组上段-新沟嘴组下段及潜江组两套成盐成油岩系。

A fractal analysis of permeability for fracturedrocksTongjun Miao a ,b ,Boming Yu a ,⇑,Yonggang Duan c ,Quantang Fang caSchool of Physics,Huazhong University of Science and Technology,1037Luoyu Road,Wuhan 430074,Hubei,PR ChinabDepartment of Electrical and Mechanical Engineering,Xinxiang Vocational and Technical College,Xinxiang 453007,Henan,PR China cState Key of Oil and Gas Reservoir Geology and Exploitation,Southwest Petroleum University,8Xindu Road,Chengdu 610500,Sichuan,PR Chinaa r t i c l e i n f o Article history:Received 6September 2013Received in revised form 28March 2014Accepted 5October 2014Keywords:Permeability Rock Fractal FracturesFracture networksa b s t r a c tRocks with shear fractures or faults widely exist in nature such as oil/gas reservoirs,and hot dry rocks,etc.In this work,the fractal scaling law for length distribution of fractures and the relationship among the fractal dimension for fracture length distribution,fracture area porosity and the ratio of the maxi-mum length to the minimum length of fractures are proposed.Then,a fractal model for permeability for fractured rocks is derived based on the fractal geometry theory and the famous cubic law for laminar flow in fractures.It is found that the analytical expression for permeability of fractured rocks is a function of the fractal dimension D f for fracture area,area porosity /,fracture density D ,the maximum fracture length l max ,aperture a ,the facture azimuth a and facture dip angle h .Furthermore,a novel analytical expression for the fracture density is also proposed based on the fractal geometry theory for porous media.The validity of the fractal model is verified by comparing the model predictions with the available numerical simulations.Ó2014Elsevier Ltd.All rights reserved.1.IntroductionFractured media and rocks with shear fractures or faults widely exist in nature such as oil/gas reservoirs,and hot dry rocks,ually,the fractures are embedded in porous matrix with micro pores,which play negligible effect on the seepage characteristic,and randomly distributed fractures dominate the seepage charac-teristic in the media.The randomly distributed fractures are often connected to form irregular networks,and the seepage character-istic of the fracture networks has the significant influence on nuclear waste disposal [1],oil or gas exploitation [2],and geother-mal energy extraction [3].In this work,we focus our attention on the seepage characteristics of fracture networks in fractured rocks and ignore the seepage performance from micro pores in porous matrix.Over the past four decades,many investigators studied the seepage characteristics of fracture networks/rocks and proposed several models.Snow [4]developed an analytical method for per-meability of fracture networks according to parallel plane model.Kranzz et al.[5]studied the permeability of whole jointed granite and tested the parallel plane model by experiments.Koudina et al.[6]investigated the permeability of fracture networks with numer-ical simulation method in the three-dimensional space,they assumed that fracture network consists of polygonal shape frac-tures and fluid flow in each fracture meets the Darcy’s law.Dreuzy et al.[7]studied the permeability of randomly fractured networks by numerical and theoretical methods in two dimensions,and they verified the validity of the model by comparing to naturally frac-tured networks.Klimczak et al.[8]obtained the permeability of a single fracture by parallel plate model with the fracture length and aperture satisfying power-law and verified by the numerical simulation.However,these models did not provide a quantitative relationship among the permeability of fracture networks,poros-ity,fracture density and microstructure parameters of fractures,such as fracture length,aperture,inclination,orientation etc.Fractures in rocks are usually random and disorder and they have been shown to have the statistically self-similar and fractal characteristic [3,9–13].Chang and Yortsos [10]studied the single phase fluid flow in the fractal fracture networks.Watanabe and Takahashi [3]investigated the permeability of fracture networks and heat extraction in hot dry rock by using fractal method.But,they did not propose an expression of permeability with micro-scopic parameters included.Jafari and Babadagli [14]obtained the permeability expression with multiple regression analysis of random fractures by the fractal geometry theory according to observed data in the well logging.In addition,their expression with several empirical constants does not include the orientation factor and microstructure parameters of fracture networks.The tree-like fractal branching networks were often considered as/10.1016/j.ijheatmasstransfer.2014.10.0100017-9310/Ó2014Elsevier Ltd.All rights reserved.⇑Corresponding author.E-mail address:yubm_2012@ (B.Yu).fracture networks by many investigators.Xu et al.[15,16]studied the seepage and heat transfer characteristics of fractal-like tree networks.Recently,Wang et al.[17]studied the starting pressure gradient for Binghamfluid in a special dual porosity medium with randomly distributed fractal-like tree network embedded in matrix porous media.Most recently,Zheng and Yu[18]investigated gas flow characteristics in the dual porosity medium with randomly distributed fractal-like tree networks.However,the fractal-like tree network is a kind of ideal and symmetrical network.The purpose of the present work is to derive an analytical expression and establish a model for permeability of fracture rocks/media based on the parallel plane model(cubic law)and frac-tal geometry theory.The proposed permeability and the predicted fracture density will be compared with the numerical simulations.2.Fractal characteristics for fracture networksMany investigators[3,9–13,19–23]reported that the relation-ships between the length and the number of fractures exhibit the power-law,exponential and log-normal types.Torabi and Berg [19]made a comprehensive review on fault dimensions and their scaling laws,and they summarized several types of scaling laws such as the length distributions for faults and fractures in siliciclas-tic rocks from different scales and tectonic settings.The power-law exponents of the scaling-law between the fault length and the number of faults were found to be in the range of1.02–2.04and are probably influenced by factors such as stress regime,linkage of faults,sampling bias,and size of the dataset.Interested readers may consult Refs.[3,9–13,19–23]for detail.In addition,the self-similar fractal structures of fracture net-works were extensively studied[22,23],and the application in complex rock structures with the fractal technique was recently reviewed by Kruhl[24].Velde et al.[25]and Vignes-Adler et al.[26]studied the data at several length scales with fractal method and found that the fracture networks are fractal.Barton and Zoback [27]analyzed the2D maps of the trace length of fractures spanning ten orders,ranging from micro to large scale fractures and found that D f=1.3–1.7.The width between two plates/walls of a fracture,i.e.the paral-lel plate model is used to represent the effective aperture of a frac-ture.Generally,the relationship between the effective aperture a and the fracture length l is given by[28,29]a¼b l nð1Þwhere b and n are the proportionality coefficient and a constant according to fracture scales,respectively.The value of n=1is important,which indicates a linear scaling law,and the fracture network is self-similarity and fractal[19,29].Thus,in the current work the value of n=1is chosen for fractures with fractal characteristic.Thus,Eq.(1)can be rewritten asa¼b lð2ÞEq.(2)will be used in this work.It is well-known that the cumulative size distribution of islands on the Earth’s surface obeys the fractal scaling law[30]NðS>sÞ/sÀD=2ð3aÞwhere N is the total number of island of area S greater than s,and D is the fractal dimension for the size distribution of islands.The equality in Eq.(3a)can be invoked by using s max to represent the largest island on Earth to yield[31]NðS>sÞ¼s maxsD=2ð3bÞEq.(3b)implies that there is only one largest island on the Earth’s surface,and Majumdar and Bhushan[31]used this power-law equation to describe the contact spots on engineering surfaces,where s max¼g k2max(the maximum spot area)and s¼g k2(a spot area),with k being the diameter of a spot and g being a geometry factor.It has been shown that the length distribution of fractures sat-isfies the fractal scaling law[3,9–13,19,22,23,32],hence,Eq.(3b) for description of islands on the Earth’s surface and spots on engi-neering surfaces can be extended to describe the area distribution of fractures on a fractured surface,i.e.NðS!sÞ¼a max l maxalD f=2ð3cÞwhere a max l max represents the maximum fracture area with a max and l max respectively being the maximum aperture and maximum fracture length,and al refers to a fracture area with the aperture and length being a and l,respectively.Inserting Eq.(2)into Eq.(3c),we obtainNðS!sÞ¼b l2maxb l!D f=2ð3dÞThen,from Eq.(3d),the cumulative number of fractures whose length are greater than or equal to l can be expressed by the follow-ing scaling law:NðL!lÞ¼l maxD fð4Þwhere D f is the fractal dimension for fracture lengths,0<D f<2(or 3)in two(or three)dimensions;and Eq.(4)implies that there is only one fracture with the maximum length.Some investigators [3,9–13,19,32]reported that the length distribution of fractures in rocks has the self-similarity and the fractal scaling law can be described by N/ClÀD f,where C is afitting constant,D f is the fractal dimension for the length(l)distribution of fractures and N is the number of fractures,and this fractal scaling law is similar to Eq.(4).Eq.(4)is also the base of the box-counting method[33]for mea-suring the fractal dimension of fracture lengths in fracture net-works,and Chelidze and Guguen[9]applied the box-counting method and found that the fractal dimension of fracture network (described by Nolen-Hoeksema and Gordon[34])in a2D cross sec-tion is1.6.Since there usually are numerous fractures in fracture net-works,Eq.(4)can be considered as a continuous and differentiable function.So,differentiating Eq.(4)with respect to l,we can get the number of fractures whose lengths are in the infinitesimal rang l to l+dl:ÀdNðlÞ¼D f l D fmaxlÀðD fþ1Þdlð5ÞEq.(5)indicates that the number of fractures decreases with the increase of fracture length andÀdN(l)>0.The relationship among the fractal dimension,porosity and the ratio k max=k min for porous media was derived based on the assump-tion that pores in porous media are in the form of squares with self-similarity in sizes in the self similarity range from the mini-mum size k min to the maximum size k max,i.e.[35]D f¼d Eþln emax minð6Þwhere e is the effective porosity of a fractal porous medium,d E is the Euclid dimension,and d E=2and3respectively in two and three dimensions.It has been shown that Eq.(6)is valid not only for exactly self-similar fractals such as Sierpinski carpet and Sierpinski gasket but also for statistically self-similar fractal porous media.Fractures in rocks or in fractured media are analogous to pores in porous media.Therefore,Eq.(6)can be extended to describe the76T.Miao et al./International Journal of Heat and Mass Transfer81(2015)75–80relationship among the fractal dimension for length distribution, porosity of fractures and the ratio l max/l min of fractures in rocks,i.e.D f¼d Eþln/lnðl max=l minÞð7Þwhere l max and l min are the maximum and the minimum fracture lengths,respectively,and/is the effective porosity of fractures in a rock.The area porosity/of fractures is defined as/¼A PAð8Þwhere A is the area of a unit cell,A P is the total area of all fractures in the unite cell.Based on Eq.(5),the total area of all fractures in the unite cell can be obtained asA p¼ÀZ l maxl min aÁlÁdNðlÞ¼b D f l2max2ÀD f1Àl minl max2ÀD f"#ð9ÞInserting Eq.(7)into Eq.(9)yieldsA p¼b D f l2max2ÀD f1À/ðÞð10Þwhere porosity/is applied in Eq.(7)in two dimensions,i.e.d E=2is used.3.Relationship between fracture density and fractal dimensionThe total fracture lengths in a unit cell of area A can be obtained byl total¼ÀZ l maxl min lÁdNðlÞ¼D f l max1ÀD f1Àl minl max1ÀD f"#ð11ÞThe fracture density is defined by[36]D¼l totalð12Þwhere l total is the total length of all fractures(not a single fracture) which may be connected to form a network in the unit cell.Inserting Eqs.(7),(8)and(11)into Eq.(12)results in the fracture densityD¼ð2ÀD fÞ/1Àl minl max1ÀD fð1ÀD fÞb l max1Àl minmax2ÀD fð13aÞInserting Eq.(7)into Eq.(13a),the fracture density can also bewritten asD¼ð2ÀD fÞ1À/ðÞ1ÀD ff"#/ð1ÀD fÞb l max1À/ðÞð13bÞIt is evident that the fracture density D of fractures is a functionof the fractal dimension D f for fracture area,area porosity/,proportionality coefficient b and l max.Fig.2compares the predictions by the present fractal model(Eq.(13a))with numerical simulations of four groups of randomfracture networks by Zhang and Sanderson[36],who proposed anew numerical method for producing the self-avoiding randomgenerations,and the parameters such as the lengths of fracturescan be controlled.In their simulations,the lengths of fractures liefrom0.0005to1.5m,and the averaged fractal dimension D f is1.3.So,in this work we take the maximum length and minimumlength of fractures are1.5m and0.0005m,respectively,and theaveraged fractal dimension D f=1.3.The average porosity/is0.018calculated by Eq.(7).It can be seen from Fig.2that the pre-dictions are in good agreement with the numerical simulations.Fig.2clearly indicates that the fracture density increases withthe increase of the fractal dimension,and this is consistent withpractical situation.Fig.3presents the fracture density versus porosity of fracturenetworks as l max=1.5m,b=0.01.It can be seen from Fig.3thatthe fracture density increases with porosity.This can be explainedthat the pore area of fractures increasing with porosity means thatthe fracture density increases with porosity.This result is in agree-ment with the Monte Carlo simulations by Yazdi et al.[37].4.Fractal model for permeability of fractured rocksThe orientation of each fracture in fracture networks is definedby two angles,the fracture azimuth and fracture dip angle,whichsignificantly affect theflow and transport properties.The orienta-tions of fractures in a fracture network are non-uniform,but usu-ally with a preferred orientation[38,39].In general,the numberof fractures in fracture networks is very large.Based on generalpractice,the fracture azimuths of all fractures are taken as aver-aged/mean angle,for instance,Massart et al.[40]showed a meandip angle of70°,mean N–S(North–South)orientation from thetotal number of1878fractures.In this work,the mean dip angleof fractures between fracture orientations andfluidflow direction,and the mean azimuth of fractures perpendicular tofluidflowdirection are assumed to be h and a,respectively(see Fig.1(a)).(a)(b)T.Miao et al./International Journal of Heat and Mass Transfer81(2015)75–8077Therefore,the scalar quantity of permeability alongflow direction needs to be calculated.Iffluidflow through fractures is assumed to be laminarflow,the flow rate along theflow direction through a fracture can be described by the famous cubic law[41,42]qðlÞ¼a3l12lD PL0ð14Þwhere L0is the length of the structural unit,l is the fracture trace length,a is the fracture aperture,and D P is the pressure drop across a fracture alongflow direction.If the single fracture forms an angle with theflow direction,due to the projection on theflow direction of the fracture,theflow rate through the fracture can be written by[43,44]qðlÞ¼a3l1Àcos2a sin2h12lD PL0ð15Þwhere a and h are respectively the mean facture azimuth and facture dip angle.When a=0,Eq.(15)is reduced toqðlÞ¼a3l cos2h12lD PL0ð16ÞThis is the famous Parsons’model.See Fig.1(b)[43,44].The totalflow rate through all the fractures can be obtained by integrating Eq.(16)from the minimum length to the maximum length in a unit cross section,i.e.Q¼ÀZ l maxl minqðlÞdNðlÞ¼b3128lD f1Àcos2a sin2h4ÀD fD PL0l4max1Àl minl max4ÀD f"#ð17Þwhere D f represents the fractal dimension for the length distribu-tion of fractures.In general,l min<<l max.Since0<D f<2in two dimensions,andðl min=l maxÞ4ÀD f<<1,so that Eq.(17)can be simplified as:Q¼b3128lD f1Àcos2a sin2h4ÀD fD PL0l4maxð18ÞEq.(18)indicate that the totalflow rate through the fracture net-work is related to the fractal dimension D f of the fracture lengths, the facture azimuth a and facture dip angle h.Eq.(18)also indicates that theflow rate is very sensitive to the maximum fracture length l max.Darcy’s law for Newtonianfluidflow in porous media is given byQ¼KAlD PL0ð19ÞComparing Eq.(18)to Eq.(19),we can obtain the permeability for Newtonianfluidflow through the fracture networks asK¼b3128AD f1Àcos2a sin2h4ÀD fl4maxð20ÞInserting Eqs.(12)and(13b)into Eq.(20),the permeability for Newtonianfluidflow through fracture networks can be written asK¼b3D1281ÀD f4ÀD fl3max1Àcos2a sin2h1À/ðÞ1ÀD ff"#ð21ÞEq.(21)shows that the permeability is a function of the fractal dimension D f for the fracture length distribution,the structural parameters(maximum fracture length l max,fracture density D,fac-ture azimuth a and facture dip angle h)and fracture porosity/of fracture networks.Eq.(21)also reveals that the permeability strongly depends on the maximum fracture length l max,and the longer fracture with wider apertures conduct the higher volume offluid and higher permeability.As a result,the present fractal model can well reveal the mechanisms of seepage characteristics78T.Miao et al./International Journal of Heat and Mass Transfer81(2015)75–80in fracture networks than conventional methods.For example, many investigators proposed fracture network models by assum-ing that the media have ideal structures such as the parallel frac-ture network[4,5,8,45],the orthogonal plane network cracks [46,47],alternate level matrix layer and fractures[48]etc.The frac-ture network permeability was often expressed as K=/a2/12, where/is fracture porosity and a is fracture aperture.Recently, Jafari and Babadagli[14]obtained an expression(with several empirical constants)by fractal geometry for fracture networks according to the well logging and observation data.Therefore,it is clear that Eq.(21)has the obvious advantages over the conven-tional models/methods.5.Results and discussionIn this section,the model predictions will be compared with the simulated data and the effects of model parameters on the perme-ability will be discussed.The procedures for determination of the relevant parameters in Eq.(21)are as follows:(1)Given the fracture network parameters(such as l max,/,a,hand b)based on a real sample.(2)Find the fractal dimension D f of fracture lengths in a fracturenetwork by the box-counting method or by Eq.(7).(3)Determine the fracture density D by Eq.(13b).(4)Finally,calculate the permeability by Eq.(21).Jafari and Babadagli[49]obtained the fractal dimensions D f of2D maps from22different nature fracture networks by box-counting method,and then they calculated the equivalent fracture network permeability by a3D model with a block size of100Â100Â10m simulated/constructed.The maximum fracture length was taken to be2m and dip angle h=0.In comparison,the fracture density D and permeability are calculated by procedures3and4,respec-tively.Fig.4shows that the present model predictions are in good agreement with the simulation results[49].Fig.5depicts the permeability for Newtonianfluid through frac-ture networks against porosity of fracture networks at different dip angles at l max=10mm,b=0.01.It is seen from Fig.5that the per-meability for fracture networks increases with porosity.This is consistent with practical situation.From Fig.5,we can also see that the permeability decreases as the fracture plane dip angle increases.This can be explained that a higher fracture plane dip angle leads to an increase of theflow resistance.Fig.6plots the permeability versus the fracture density of the fracture networks at l max=10mm,a=0,h=p/4and b=0.01.It suggests that the permeability of the fracture networks increases with the increases of fracture density.The reason is that when the fracture density D increases,the area of fracture networks increases and thus results in increasing the permeability.This result agrees with the numerical simulation results in Ref.[50]. 6.ConclusionsIn this paper,the fractal geometry theory has been applied to describe the fractal fracture system,and the fractal scaling law for length distribution of fractures and the relationship among the fractal dimension for fracture length distribution,fracture area porosity and the ratio of the maximum length to the minimum length of fractures have been proposed.Then,a model for perme-ability of fractured rocks has been derived based on the famous cubic law,fractal geometry theory and technique.A novel expres-sion for the fracture density has also been proposed based on the fractal scaling law of length distribution of fractures.The present results show that the permeability of fracture networks increases with the increases of porosity and fracture density.Our results agree well the available numerical simulations.This verifies the validity of the proposed models.It should be point out that the percolation and critical behavior are not involved in this work.In this paper,we focus on the perme-ability that all fractures are assumed to be connected to form frac-ture network,which contributes the permeability of the fracture system.This means that we have ignored the interaction between fractures.The permeability after including the interaction and con-nectivity between fractures and critical behavior of fractures near the threshold undoubtedly is an interesting topic,and this may be our next workConflict of interestNone declared.AcknowledgmentThis work was supported by the National Natural Science Foundation of China through Grant Number10932010. 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10.16638/ki.1671-7988.2018.18.046商用车前下防护安全性能分析张德伟，李冰，孔雪，祝哮，孙巍，尚帅涛（辽宁忠旺集团有限公司，辽宁辽阳111003）摘要：文章对某商用车铝合金前下防护依据GB26511-2011对其进行安全性能进行分析，分析借助CAE的仿真手段，通过分析初版数据结果，探究其不满足标准的原因，并进行结构优化，结构优化后其安全性能满足标准要求。

前下防护采用铝合金材质既可以实现轻量化目标，同时也能满足其安全性能目标。

通过CAE技术可以提高试验通过率，从而降低研发成本，缩短研发周期。

关键词：前下防护；安全性能；结构优化；满足标准中图分类号：U467 文献标识码：B 文章编号：1671-7988(2018)18-135-03The Safety Performance Analysis of Front Underrun Protection for commercial vehicle Zhang Dewei, Li Bing, Kong Xue, Zhu Xiao, Sun Wei, Shang Shuaitao( Liaoning Zhongwang Group Co. Ltd., Liaoning Shenyang 111003 )Abstract: This paper analyzes the safety performance of aluminum alloy front underrun protection for commercial vehicle according to GB26511-2011. By analyzing the results of the first version of the data by CAE technology, this paper studies the reasons why it does not meet the standards. After structural optimization, its safety performance satisfy criteria The aluminum alloy material can not only achieve the lightweight target, but also meet its safety performance target. By CAE technology, the passing rate of test can be improved, so as to reduce the design cost and shorten the design time. Keywords: Front underrun protection; Safety performance; Structure optimization; Satisfy criteriaCLC NO.: U467 Document Code: B Article ID: 1671-7988(2018)18-135-03前言随着我国汽车保有量的快速增加，交通事故也不断攀升，尤其是小型车辆与商用车发生正面碰撞事故，小型车辆很多时候被卷入到商用车下部而造成车毁人亡的严重后果，为此我国国家发展与改革委员会发布了标准GB26511-2011，强制规定了商用车前下部防护装置的安全性能要求。

人工智能技术在油藏工程领域评价方法Artificial intelligence (AI) technology has been increasingly used inthe field of reservoir engineering for the evaluation of oil and gas reservoirs. It has provided great potential in improving the efficiency and accuracy of reservoir evaluation, leading to significant advancements in the industry.人工智能（AI）技术在油藏工程领域的应用日益增多，用于油气储层的评价。

它在提高储层评价的效率和准确性方面具有巨大潜力，促进了该行业的显著进步。

One major aspect of AI in reservoir engineering is its capability to analyze vast amounts of data. AI algorithms can process and interpret geological, geophysical, and engineering data, allowing for a more comprehensive understanding of reservoir characteristics and behavior.人工智能在油藏工程中的一个主要方面是其分析海量数据的能力。

AI算法可以处理和解释地质、地球物理和工程数据，使人们更全面地了解储层的特征和行为。

Additionally, AI can be utilized for predictive modeling of reservoir performance. By using machine learning and data-driven techniques, AI can forecast production rates, reservoir pressure, and other key parameters with improved accuracy, aiding in the optimization of production strategies and reservoir management.此外，人工智能还可以用于油藏性能的预测建模。

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