纳米流体燃料性能调控研究进展

高毅, 徐星星, 赵子龙, 周帅, 刘佩进, 敖文

高毅, 徐星星, 赵子龙, 等. 纳米流体燃料性能调控研究进展[J]. 实验流体力学, 2024, 38(5): 1-16. DOI: 10.11729/syltlx20220119
引用本文: 高毅, 徐星星, 赵子龙, 等. 纳米流体燃料性能调控研究进展[J]. 实验流体力学, 2024, 38(5): 1-16. DOI: 10.11729/syltlx20220119
GAO Y, XU X X, ZHAO Z L, et al. Research progress of improving nanofluid fuel performance[J]. Journal of Experiments in Fluid Mechanics, 2024, 38(5): 1-16. DOI: 10.11729/syltlx20220119
Citation: GAO Y, XU X X, ZHAO Z L, et al. Research progress of improving nanofluid fuel performance[J]. Journal of Experiments in Fluid Mechanics, 2024, 38(5): 1-16. DOI: 10.11729/syltlx20220119

纳米流体燃料性能调控研究进展

基金项目: 国防科技重点实验室稳定支持课题(××××1002)
详细信息
    作者简介:

    高毅: (1998—),男,安徽阜阳人,硕士研究生,研究方向:纳米流体燃料改性。E-mail:gy0704@mail.nwpu.edu.cn

    通讯作者:

    敖文: E-mail:aw@nwpu.edu.cn

  • 中图分类号: V231.1;V231.2

Research progress of improving nanofluid fuel performance

  • 摘要:

    纳米流体燃料是将纳米颗粒添加至液体燃料中形成的一种悬浮液,具有能量密度高、点火延迟时间短等优点,具有改善燃料燃烧特性的潜力。为探寻更为有效的纳米流体燃料性能调控方法,本文回顾了近年来国内外纳米流体燃料性能调控的研究进展,主要介绍了纳米流体的稳定性能、流变性能、蒸发性能、点火性能和燃烧性能调控的研究成果,分析了各种物理和化学调节方法及其基本原理。添加表面活性剂和金属包覆改性是改善纳米流体燃料稳定性能和流变性能的主要方法;点火性能和燃烧性能的调控主要基于提高燃料液滴热传导和热辐射吸收能力、促进金属颗粒自身释热等途径,主要包括添加纳米金属颗粒、纳米金属氧化物及新型亚稳态分子间复合物等。纳米流体燃料的下一步研究应重点围绕拓宽纳米流体燃料界限、探索新型表面活性剂、建立纳米流体燃料点火燃烧理论体系等方面展开。

    Abstract:

    Nanofluid fuel is a kind of suspension liquid, which is made by adding nanoparticles into the liquid fuel. It has advantages of high energy density and shorter ignition delay, and thus shows the potential of improving the burning characteristics of the fuels. To further improve the performance of nanofluid fuels and explore more effective performance control methods, the progress of research on nanofluid fuels in recent years at home and abroad is briefly reviewed in this work. Researches on the improvement of the stability performance, rheological performance, evaporation performance, ignition performance and combustion performance of nanofluid fuels are introduced, and the corresponding tailoring methods and mechanisms are analyzed. Adding surfactant and surface coating are effective methods to improve the stability of nanoparticles in the fuel. The methods of regulating ignition and combustion performance are based on improving the heat conduction and absorption capacity of droplets and promoting the heat release of metal particles, which mainly include nano-metal particles, nano-metal oxides, and new metastable intermixed composites. The existing problems in current research are summarized. More importantly, it is pointed out that the future study of nanofluid fuels should focus on broadening the boundary of the fuel, exploring new surfactants, and establishing the theoretical framework of ignition and combustion.

  • 附着在交通工具表面的边界层流态大部分为湍流,其所产生的摩阻较层流边界层高出约一个量级。通过控制湍流边界层内多尺度流动结构可有效减小边界层的摩阻并实现总阻力的降低,对节能减排具有重要意义。

    随着雷诺数的升高,湍流边界层内小尺度流动结构对湍动能和摩阻的贡献逐渐降低,以近壁面小尺度结构为主要控制对象的传统主/被动控制技术的减阻效果随之降低。近期对湍流边界层内跨流层跨尺度湍流结构相互作用的研究表明,外区大尺度流动结构影响着湍流边界层内跨流层能量传递和近壁雷诺切应力的生成[1-2]。因此,通过控制较高流层中的大尺度流动结构,既可直接降低其在壁面留下的大尺度摩阻成分,亦可抑制其对近壁小尺度结构的调制作用,降低小尺度结构对壁面摩阻的贡献,进而有望在高雷诺数条件下降低壁面摩阻[3-5]

    目前针对湍流边界层的减阻流动控制技术包括沟槽壁面[6-9]、超疏水壁面[10]、局部吹吸气[11]、近壁面行波[12]和涡流发生器(Vortex Generator, VG)[13-15]等。其中,VG具有结构简单、附加重量低、易于维护等优点,工程应用潜力较大。VG的特征高度h与边界层厚度δ相当(h/δ~1),存在附加压差阻力大的缺点。与之相比,微型涡流发生器(Micro Vortex Generator, MVG)几何尺寸更小(h/δ < 0.5)、附加阻力更低[16-17],具有比常规VG更好的减阻控制能力[13, 17-18]。因其特征高度h的差异,MVG也被称为低形阻VG(Low-Profile VGs, LPVG)[18-20]、亚边界层VG(Sub-Boundary-Layer VGs, SBVG)[21]、浸没式VG(Submerged VGs)[16]等。MVG有叶片形、楔形、车辙形及叉骨形等多种形状。当来流绕过MVG时,在其下游会形成较为稳定的时均流向涡对,从而对近壁流动施加控制。

    目前,对MVG流动控制技术的研究主要集中于3个方向:1)分析不同形式MVG在零压梯度或逆压梯度边界层中诱导产生的流动结构及其沿程演化规律[19, 21-22];2)应用MVG进行边界层分离流动控制[18, 20-21];3)将MVG应用于二维翼型、三维机翼、机身等处进行流动减阻试验[20-21, 23-26]。为解决MVG在湍流边界层减阻控制中的工程应用问题,需明确MVG对流场产生有效控制的流向范围。文献[20]中提到,当基于边界层动量厚度θ的特征雷诺数Reθ ≈ 3.5 × 105时,MVG产生的时均流向涡对沿程抬升并在其下游约50h处耗散殆尽。Zaman等[22]的研究表明,当Reθ ≈ 1.1 × 104时,MVG所产生的流向高、低速流动区域沿主流方向逐渐融合,并在其下游约24h处形成较厚的均匀低速流层。

    本文针对上述第一个研究方向开展实验测量,旨在研究MVG对经典零压梯度湍流边界层不同下游位置流动特性和摩阻的影响,为掌握MVG控制效果的沿程演化规律提供新的认识,为MVG在中高雷诺数湍流边界层中的减阻流动控制应用提供机理支撑。为此,本文使用体视粒子图像测速(Stereo-scopic Particle Image Velocimetry, SPIV)技术和免标定双层热膜摩阻传感器,在低速风洞中测量中等雷诺数条件下平板湍流边界层内单排楔形MVG阵列下游不同流向站位的法向–展向平面内的三分量速度场和当地壁面摩阻,使用统计分析、能谱分析和本征正交分解(Proper Orthogonal Decomposition, POD)等方法研究MVG对湍流边界层内流场统计特性和流动结构的影响,并讨论MVG下游摩阻的沿程变化及MVG几何参数对减摩阻能力的影响。

    风洞实验在北京航空航天大学D6低速风洞中进行。该风洞为直流吸气式,风速可调范围为0~50 m/s。实验段总长度为5 m,收缩比约为9∶1,采用变截面设计以减小洞壁体发展边界层对主流区流场均匀性的影响,其入口、出口横截面尺寸分别为0.4 m × 0.5 m、0.48 m × 0.5 m。

    实验模型布置如图1所示。在风洞实验段内放置长4.5 m、厚0.015 m、宽0.40~0.48 m的有机玻璃平板,用于产生零压力梯度平板湍流边界层。平板距风洞底壁0.085 m,平板前缘距风洞实验段入口约0.1 m,前缘具有9.5°切角以防止流动在前缘产生局部分离。在距平板前缘0.300 m的下游位置,沿展向布置一根直径1 mm的圆柱形碳棒作为绊线,以触发边界层转捩。本文所使用的笛卡尔坐标系原点位于平板展向中心处MVG后缘与壁面的接触点,xyz分别代表流向、法向和展向,各方向的速度、时均速度和脉动速度分别记为(UVW)、($\overline{U}$、$\overline{V}$、$\overline{W}$)和(uvw)。U为自由来流速度。如无特殊说明,在下文光滑壁面湍流和MVG壁面湍流各工况结果中,具有上标“+”的速度和长度单位均已使用光滑壁面湍流边界层的内尺度(摩擦速度uτ及涡黏尺度l*)作无量纲化。

    图  1  低速风洞中实验布置示意图
    Fig.  1  Schematic diagram of the experimental setup in the test section of a low-speed wind tunnel

    在距绊线3.1 m的下游位置,沿展向布置一排3D打印加工的MVG阵列。边界层在此流向位置已经完全转捩为湍流边界层。表1为自由来流速度U = 14 m/s时该处湍流边界层的主要特征参数,其中Reτ为摩擦雷诺数(Reτ = uτδ/νν为运动黏性系数),Reθ为动量厚度雷诺数,H为形状因子,Δy+、Δz+为空间分辨率,uτT/δ为以边界层外尺度无量纲的采样总时长(T为各工况实验的拍摄时间,用于衡量计算结果是否收敛)。上述特征参数系利用Chauhan等[27]提出的复合速度型公式对SPIV所测流向时均速度型函数${\overline{U}}^{ + }$(y+)进行拟合得到,综合考虑了内区及尾迹区内的流向时均速度的分布特点。

    表  1  光滑壁面湍流边界层主要特征参数
    Table  1  Main characteristic parameters of the studied smooth-wall TBL
    U/(m·s−1)δ/cmuτ/(m·s−1)ReτReθHΔy+ Δz+ uτT/δ
    149.980.55345363531.34.5 4.511000
    下载: 导出CSV 
    | 显示表格

    MVG阵列特征尺寸如图2所示,其中l为流向长度,a为展向宽度,s为展向间距。本文以Ashill等[21]提出的前向三角楔形MVG(Forwards Wedge MVG)作为基准模型。该构型的MVG在已有研究中表现出最小的附加阻力及较优的控制性能[21, 28]。本文中,基准楔形MVG记作MVG0,其特征高度h0 = 5 mm、展向间距s0 = 0 mm(即相邻MVG无间隙)、展向宽度a0 = 10 mm、流向长度l0 = 20 mm。下文中的部分空间坐标将使用MVG0的特征高度h0进行无量纲化。此外,本文还对比研究了具有更大展向间距的MVG阵列(记作MVGs)及更高特征高度的MVG阵列(MVGh)。3种MVG阵列的主要几何参数如表2所示。

    图  2  MVG阵列特征尺寸示意图
    Fig.  2  Schematic diagram of MVG array characteristic size
    表  2  3种MVG阵列的主要几何参数
    Table  2  Main size of the three MVG array
    模型名称s/mmh/mml/mma/mm
    MVG0052010
    MVGs552010
    MVGh0102010
    下载: 导出CSV 
    | 显示表格

    U = 14 m/s时,对3种MVG阵列下游x/h0 = 10(近尾迹区)和x/h0 = 30(远尾迹区)这2个流向站位开展SPIV测量,获得该x站位yz平面内的三分量速度场,并与无MVG条件下的光滑壁面流场测量结果进行对比。SPIV实验所使用的示踪粒子为平均粒径约2 μm的癸二酸二异辛酯(DEHS)液滴,通过网格状的分布式粒子布撒装置注入直流式风洞的进气口,被吸入风洞后流经收缩段、稳定段与主流充分掺混。双曝光脉冲激光器(Beamtech Vlite–380)激发能量为380 mJ/pulse的激光束,经透镜组整形后形成片光,从风洞侧壁垂直入射照亮测量平面。片光厚度为3 mm,以降低流向速度的测量不确定度。2台超高分辨率跨帧CCD相机(Imperx CLB–B6620M,分辨率为6600像素 × 4400像素)搭配180 mm微距镜头(TAMRON SP AF 180 mm F/3.5 MACRO1∶1)记录测量平面内的示踪粒子信息,其物理分辨率是0.016 mm/像素。2台相机分别布置于测量平面的上、下游两侧,以异侧布局的形式拍摄,相机透视角约为65°。使用经GPU加速的光流法速度场求解器(Multi–iterative Lucas–Kanade, MILK)[29]分别计算2台相机像平面内的粒子图像,获得二维二分量速度场,计算时对粒子图像进行了4次降采样,最终查询窗口尺寸为16像素 × 16像素,重叠率为75%,最大跨帧位移不超过12像素。之后,将2台相机像平面上的二维二分量速度场通过空间标定映射至测量平面,获得二维三分量速度场[30-32]。SPIV测量的有效视野范围为80 mm(法向)× 60 mm(展向)。示踪粒子以14 m/s的速度在跨帧时间20 μs内沿流向最多前进2.8 mm(小于片光厚度3 mm),可保证在跨帧粒子图像对上计算出互相关峰。各工况均采样1000对瞬时速度场,相机的采样频率为0.5 Hz。经检验,SPIV测量得到的湍流二阶统计量在此样本量下达到收敛。

    应用MILK算法得到粒子位移的不确定度约为0.1像素[29],根据陈启刚和钟强[30]给出的估算方法,面内速度分量(VW)的测量精度约为0.4%,面外速度分量(U)的测量精度约为1.0%。图3为SPIV测量得到的光滑壁面湍流边界层的流向时均速度型函数$ {\overline{U}}^{ +} $(y+)、雷诺正应力曲线($ {\overline{uu}}^{ + } $(y+)、$ {\overline{vv}}^{ + } $(y+)、$ {\overline{ww}}^{ + } $(y+))和雷诺切应力曲线($ {\overline{uv}}^{ + } $(y+)),同时给出Watanabe等[33]Reτ = 3058条件下开展时间发展湍流边界层直接数值模拟(Direct Numerical Simulation, DNS)得到的结果作为对比,图中κ为卡门常数,${\overline{{{u}_{i}{u}_{j}}}}^{ + }$(i = j = 1, 2, 3)中u1u2u3分别表示脉动速度uvw。可以看到,SPIV实验测量得到的$ {\overline{U}}^{ + } $在近壁区y + = 10处仍然能够和DNS的结果相吻合;在雷诺应力方面,实验测量的$ {\overline{vv}}^{ + } $、$ {\overline{ww}}^{ + } $及$ {\overline{uv}}^{ + } $沿法向的变化趋势和DNS的结果吻合,两者的数值在y + = 30以上的流层基本一致;但$ {\overline{uu}}^{ + } $在y + = 10~20以内(内区)总体低于DNS的结果,究其原因,一方面是本文研究的体发展湍流边界层和DNS模拟的时间发展边界层[33]在流动特性上存在差异,另一方面则是本文采用的SPIV实验布置方式导致测量面外的U分量不确定度更大,且较高的片光厚度使得沿片光厚度方向的体平均效应较强,进一步降低了对U分量小尺度脉动的解析能力,从而使$ {\overline{uu}}^{ + } $内区测量结果相较于DNS结果偏低。

    图  3  光滑壁面工况下SPIV 测量结果与 DNS结果对比
    Fig.  3  The SPIV measurement results are compared with the DNS results under the smooth wall condition

    湍流边界层的壁面摩阻由高南和刘玄鹤[34]发展的一种新型免标定双层热膜摩阻传感器测量得到。该传感器装置如图4(a)所示,其工作原理为:在外接恒温开尔文电桥的控制下,双层热膜(镍箔)同温协同工作,此时下膜的存在将上膜向壁面的传热损失限制在总产热量的5%以内,使上膜热量几乎只传给流体,解决了传统单层热膜摩阻测量技术因壁面热损失而导致的测量偏差问题。Liu等在此基础上发展了根据上层热膜发热量计算壁面摩阻的免标定测量技术,其计算原理详见文献[35-37]。本文使用的矩形镍箔流向长度为1.75 mm、展向宽度为30 mm、厚度约为40 μm,可测量矩形镍箔表面的平均摩阻。传感器电桥所测得的瞬时电压数据由数据采集卡(NI USB–6259)实时采集,采样频率为1024 Hz。

    图  4  摩阻传感器及其测量结果
    Fig.  4  The friction sensor and its measurement results

    壁面时均摩阻τw理论值[38]的半经验关系式为:

    $$ {\tau _{\rm{w}}} = \frac{1}{2}\rho U_\infty ^2 \cdot 0.059\;2\;Re_x^{- 0.2} $$ (1)

    式中:Rex表示以距边界层起点长度(绊线位置)为特征尺寸的雷诺数。

    对各工况均开展7次摩阻重复测量实验,多次测量所得不确定度用误差条表示。摩阻单次测量持续时间为40 s(满足Ashill等[21]建议的收敛性准则)。如图4(b)所示,在不同自由来流速度下利用摩阻传感器测得的光滑壁面湍流边界层的时均摩阻τw(红色曲线)与式(1)估计的理论值(黑色曲线)相比较,二者最大误差约为4.7%。图4(b)中也给出了U = 14 m/s时经SPIV所测$ {\overline{U}}^{ + } $(y+)估算所得的τw(蓝色点),比摩阻传感器的测量结果高14%。此外,本文还利用摩阻传感器测量了U = 14 m/s时光滑壁面及3组MVG阵列下游x/h0 = 10~80范围内的壁面摩阻,研究发现:即便是大间距的MVGs阵列,摩阻传感器的展向测量尺寸仍然包含了2个MVG的展向周期尺寸,这意味着摩阻传感器获得的是具有展向平均意义的当地摩阻。

    图5给出了3种MVG阵列下游近、远尾迹区2个x站位(x/h0 = 10和30)的yz平面内的时均速度场。彩色云图表示垂直平面的流向速度分量$ {\overline{U}}^{ + } $,黑色箭头表示法向速度分量$ {\overline{V}}^{ + } $和展向速度分量$ {\overline{W}}^{ + } $合成的面内速度矢量。蓝色虚线为MVG阵列下游时均速度场$ {\overline{U}}^{ + } $ = 17等值线,红色点划线为光滑壁面工况下$ {\overline{U}}^{ + } $ = 17等值线。可以看到,在3种MVG阵列的下游近尾迹区,边界层近壁区均出现时均流向涡对和时均流向速度亏损区,时均流场的展向不均匀性显著,与前人研究相符[21-22];时均流向涡对结构强度及时均流向速度亏损区沿程逐渐衰减,在下游远尾迹区仅表现为近壁处的低动量层,展向不均匀性明显减弱。相较于基准MVG0工况(图5(b)),大间距MVGs工况(图5(a))在远尾迹区形成的近壁低动量层更薄、更接近光滑壁面水平;而更高的MVGh图5(c))则显著增厚了远尾迹区的近壁低动量层。

    图  5  MVG阵列下游的时均速度场
    Fig.  5  Time averaged results of three velocity component fields behind MVG arrays

    考虑到MVG引入的展向不均匀性,对流场统计量沿展向进行了平均。图6给出了3种MVG阵列的近、远尾迹区(x/h0 = 10和 30)时均流向速度型和雷诺应力型的展向平均结果。图中,“$\langle \rangle $”表示沿时间和展向的系综平均,蓝色和红色的点划线分别为MVG阵列h = 5、10 mm所对应的法向位置。从图6(a)可以看到,MVG阵列对近尾迹区(x/h0 = 10)流场统计量的影响主要体现在3个方面:1)在MVG高度的流层(y = h)附近,产生低平均动量及高湍流脉动区,主要由MVG诱导产生的时均流向涡对和时均流向速度亏损区所致;2)在MVG高度以下的近壁区(y < h),雷诺正应力(即湍流脉动强度)及雷诺切应力均有所降低,可归因于时均流向涡对近壁湍流结构的规则化作用,在一定程度上反映了MVG的减摩阻潜力;3)MVG的h越高、s越小,对边界层的扰动作用越强,诱导产生的时均流向涡对越强。从图6(b)可以看到,在远尾迹区(x/h0 = 30),MVG对平均流场的诱导作用随时均流向涡对的耗散而减弱,但仍然在湍流脉动强度场上留下峰值“印记”,且峰值出现的流层相比近尾迹区更高,反映了时均流向涡对从壁面逐渐抬升的bottom-up过程[21, 39]。值得注意的是,在x/h0 = 30处,3种MVG阵列工况下近壁区(y + < 15)的流向雷诺正应力和雷诺切应力均低于光滑壁面湍流边界层的水平,降低的幅度仍和MVG高度及间距相关,预示MVG在远尾迹区具有减摩阻潜力。

    图  6  MVG阵列下游的时均流向速度型与雷诺应力的展向平均结果
    Fig.  6  Spanwise average results of wall-normal profiles of time-averaged streamwise velocity and Reynolds stress behind MVG arrays

    为从尺度空间上厘清MVG对湍流脉动特性的影响,对SPIV测量得到的速度场进行展向能谱分析。图7给出了MVG0阵列近、远尾迹区(x/h0 = 10和30)uvw分量的展向预乘能谱及uv的互相关展向预乘能谱,即$ {k}_{z}{\widehat{\phi }}_{{u}_{i}{u}_{j}} $(i = j = 1, 2, 3或i = 1, j = 2),同时给出光滑壁面的情况作为对比。各预乘能谱均使用所对应的光滑壁面工况的能谱峰值进行无量纲化,即${k}_{z}{\widehat{\phi }}_{{u}_{i}{u}_{j}}={k}_{z}{\phi }_{{u}_{i}{u}_{j}}/ {k}_{z}{\phi }_{{u}_{i}{u}_{j},\mathrm{光}\mathrm{滑}}^{{\rm{max}}}$。其余工况(MVGh和MVGs)的能谱特性与MVG0工况类似,受限于篇幅不再给出。如图7(a)所示,SPIV测量能够解析到光滑壁面能谱${k}_{z}{\widehat{\phi }}_{uu}$的内区峰P1和外区峰P2,峰值的法向高度和峰值波长均与前人的DNS结果[40]一致。此外,${k}_{z}{\widehat{\phi }}_{vv}$、${k}_{z}{\widehat{\phi }}_{ww}$的内区峰P1和${k}_{z}{\widehat{\phi }}_{uv}$的外区峰P2也和DNS结果[40]吻合,但现有的SPIV测量难以解析到${k}_{z}{\widehat{\phi }}_{uv}$在y+ ≈ 20处的内区峰。图7(b)表明,在MVG作用下,近尾迹区$ {k}_{z}{\widehat{\phi }}_{uu} $、$ {k}_{z}{\widehat{\phi }}_{vv} $、$ {k}_{z}{\widehat{\phi }}_{ww} $和$ {k}_{z}{\widehat{\phi }}_{uv} $的能谱中均出现一个独立的能谱峰PMVG(即第二外区峰),其所诱导的流动结构展向波长$ {\lambda }_{z}^{ + } $与MVG的展向周期(相邻MVG的中心距离,${\lambda }_{{\rm{MVG}}}^{+}$ ≈ 350,如图7(b)中竖直虚线所示)基本一致,其法向高度对应于图6显示的${{\langle uu \rangle }}^{+}$、${{ \langle vv \rangle }}^{ + }$、${{ \langle ww \rangle }}^{ + }$和${{ \langle uv \rangle }}^{ + }$在对数区的峰值位置。此外,近尾迹区$ {k}_{z}{\widehat{\phi }}_{uu} $和$ {k}_{z}{\widehat{\phi }}_{uv} $分量的外区峰P2有所增强,并能够持续到远尾迹区。从图7(c)可以看到,由MVG所导致的能谱峰PMVG在远尾迹区各分量能谱中基本消失,且$ {k}_{z}{\widehat{\phi }}_{uu} $、$ {k}_{z}{\widehat{\phi }}_{vv} $和$ {k}_{z}{\widehat{\phi }}_{ww} $的内区峰相较于光滑壁面工况均有降低、$ {k}_{z}{\widehat{\phi }}_{uv} $能谱内区峰值区域有所收缩,表明MVG对近壁小尺度结构的抑制及对内外区不同尺度结构间的传能与调制作用降低,导致图6中近壁处雷诺应力低于光滑壁面水平。

    图  7  光滑壁面及MVG0下游近、远尾迹区展向预乘能谱
    Fig.  7  Spanwise pre-multiplied energy spectra of smooth-wall and MVG0 arrays

    对SPIV测得的光滑壁面及MVG阵列下游速度场用POD进行模态分解,以厘清MVG所引入的流动结构在湍动能层面的表征。使用Snapshot POD算法对各工况的1000帧三分量平面速度场进行POD分解[41-42]图8给出了光滑壁面及MVG0阵列工况下各阶模态的能量占比及能量积累曲线,其中i为模态阶数。图9给出了光滑壁面及MVG0工况下近尾迹区(x/h0 = 10)和远尾迹区(x/h0 = 30)的部分典型POD模态的空间基$ {\varPsi }_{i} $(y, z),云图为流向分量$ {\varPsi }_{i}^{u} $,黑色箭头表示法向分量$ {\varPsi }_{i}^{v} $、与展向分量$ {\varPsi }_{i}^{w} $的合成矢量。

    图  8  光滑壁面及MVG0工况近、远尾迹区POD分解所得各阶模态的能量占比及能量积累曲线
    Fig.  8  Energy ratio of each rank and the cumulative energy of the POD result of smooth-wall case and near- or far-wake regions of MVG0 case

    图9可以看到,光滑壁面工况下,第1阶POD模态${\varPsi }_{i\;=\;1}$以贯通内外区的超大尺度结构为典型特性,高阶POD模态${\varPsi }_{i\;=\;5,\;10,\;20}$则表现出内外区分离的双层结构特征。MVG0阵列工况下,近尾迹区第1阶POD模态中出现了类似图5近壁处半圆形时均流向速度亏损区的“印记”结构,从壁面延伸到对数区中部。值得注意的是,该“印记”一直持续至第20阶模态,说明MVG所诱导的流动结构(时均流向涡对)贡献了整个SPIV测量视野范围内的大部分湍动能(即该流动结构与湍流边界层内的大、超大尺度结构对湍动能的贡献相当),并由此造成图8中MVG0阵列工况下低阶POD能量贡献率明显高于光滑壁面工况。这与Bai等[43]在湍流边界层内利用斜置沟槽产生大尺度流向环流时所观察到的各阶POD模态能量分布情况类似。在MVG0阵列下游的远尾迹区,其所诱导的流动结构不再明显呈现于低阶POD模态中,结合${{\langle uu \rangle }}^{+}$、${{ \langle vv \rangle }}^{ + }$及${{ \langle ww \rangle }}^{ + }$仍然在对数区存在峰值的观察,可以推测,MVG所诱导的时均流向涡对结构在远尾迹区难以维持规则的完整外形,而是衰减为沿展向蜿蜒的涡量层并继续影响速度统计量的分布。对比图9中的第20阶模态可以发现,MVG0诱导的流动结构影响了近壁处含能结构分布,间接表征了MVG对下游结构的控制作用。MVGs和MVGh阵列工况下的低阶POD模态在近、远尾迹区的空间分布特性与MVG0阵列工况下类似,不再另行给出。

    图  9  光滑壁面及基准MVG0工况近、远尾迹区流场第1、5、10、20阶POD模态的空间基$ {\varPsi }_{i} $(y, z
    Fig.  9  Rank 1, 5, 10 and 20 mode $ {\varPsi }_{i} $(y, z) of POD decomposition results of smooth-wall case and near- or far-wake regions of MVG0 case

    本节讨论MVG阵列下游的摩阻沿程变化,主要评估各型MVG阵列的减摩阻效果,并分析间距、高度对MVG减摩阻特性的影响。减摩阻率RD(Drag Reduction)根据下式计算:

    $$ R_{\rm{D}}=\left(\frac{{\tau }_{光滑}-{\tau }_{{\rm{MVG}}}}{{\tau }_{光滑}}\right)\times 100\% $$ (2)

    式中:$ {\tau }_{\mathrm{光}\mathrm{滑}} $与$ {\tau }_{{\rm{MVG}}} $分别为免标定双层热膜摩阻传感器所测的光滑壁面和MVG工况下同一流向位置的当地时均摩阻。

    U = 14 m/s时,3种MVG阵列下游x/h0 = 10~80范围内减摩阻率RD的沿程变化如图10所示,其中误差条表示多次重复实验的不确定度。可以看到,在x/h0 = 10处,3种MVG工况下的当地时均摩阻相较于光滑壁面工况均略有增大(RD < 0),增阻量在5%以内。增阻的主要原因是MVG产生的时均流向涡对在该处距壁面较近,其诱导产生的上洗、下洗运动增强了近壁区各流层的动量掺混。当x/h0 ≥ 20后,3种MVG均呈现出明显的减摩阻效果,增大MVG阵列高度能显著提升减摩阻率。已有研究表明[21],高度越高的MVG阵列能够诱导时均流向涡对产生更大的环量,因而对近壁处湍流结构的抑制和规则化作用也更强,最终表现为减摩阻率的提升,这与Cheng等[4]以等离子体涡流发生器产生时均流向涡对减摩阻的研究结果相符(Cheng等通过增大电极电压提升时均流向涡对的强度,实现了减摩阻率的提升)。大间距MVG阵列所诱导的时均流向涡对展向排列稀疏(图5(a)),对边界层内流动结构的不规则运动影响作用有限,在摩阻测量中则体现为大间距MVGs的减摩阻率低于MVG0阵列。但更高更密的MVG具有更大的型阻,在实际应用时需考虑MVG所引起的附加阻力。高度更高、展向间距更小的MVG阵列的最优减阻位置更靠近上游,在峰值减阻率后,各型MVG阵列的减摩阻率均沿程逐渐衰减,但在x/h0 = 80处MVGh及MVG0仍然具有超过5%的减摩阻率,说明MVG阵列的减摩阻效果能够至少持续至下游80倍自身特征高度处。

    图  10  各型MVG阵列下游减摩阻率的沿程变化
    Fig.  10  Drag reduction in different streamwise stations behind each MVG arrays

    U = 14 m/s、Reτ = 3453的湍流边界层中,利用SPIV及免标定双层热膜摩阻传感器对3种MVG阵列下游速度场统计特性及减摩阻的效果开展实验测量,结论如下:

    1)MVG在近尾迹区诱导产生时均流向涡对和时均流向速度亏损区,并在MVG特征高度附近流层产生低平均动量及高湍流脉动区。随着时均流向涡对的沿程抬升,MVG对湍流统计量的峰值扰动也在下游抬升至更高的流层。此外,MVG引起近壁区雷诺切应力的降低,说明了MVG的减摩阻能力。

    2)展向预乘能谱表明,MVG导致近尾迹区出现了第二外区峰值,其所诱导流动结构的展向波长与相邻MVG的中心距离一致,并显著影响了近尾迹区湍流边界层外区峰的强度与形貌。POD模态分析表明,MVG所诱导的流动结构与湍流边界层内的大、超大尺度结构对湍动能的贡献相当,并影响了近尾迹区近壁含能结构的分布。

    3)实验证实MVG阵列具有减摩阻效果,减摩阻有效范围至少可持续至下游80倍自身特征高度处。

    后续应在MVG减摩阻机理与参数影响规律等方面开展进一步研究,并在减阻应用中综合考虑MVG的减摩阻效果及其额外型阻。

    致谢:北京航空航天大学龙彦光博士、朱熠辰博士生在2D–PIV的基础上开发并完善了本实验所用的SPIV基础程序。加拿大新不伦瑞克大学高南教授、大连航华科技有限公司刘玄鹤博士研发了本实验所用的免标定双层热膜摩阻测量设备,天津大学王昊博士生指导了热膜传感器的制备。北京航空航天大学张清福、于悦、李拓、徐颢文等多名研究生协助开展了实验测量工作。在此,对上述个人与机构提供的帮助表示感谢。

  • 图  1   纳米流体燃料的关键性能

    Fig.  1   Key properties in nanofluid fuels

    图  2   纳米流体燃料的团聚机制

    Fig.  2   Agglomeration mechanism of nanofluid fuels

    图  3   不同纳米流体燃料稳定性比较

    Fig.  3   Comparison of stability of different nanofluid fuels

    图  4   纳米流体燃料黏度影响规律

    Fig.  4   Influence of different parameters on the viscosity of nano fluid fuel

    图  5   不同温度下0.1%、0.5%和1.0%纳米铝–煤油的蒸发速率[21]

    Fig.  5   Evaporation rates of 0.1%, 0.5% and 1.0% nano-aluminum-kerosene at different temperatures[21]

    图  6   微爆示意图[29]

    Fig.  6   Schematic representation of the ejection event [29]

    图  7   不同温度下庚烷基纳米流体燃料液滴与纯庚烷、稳定庚烷液滴的蒸发率比较[34]

    Fig.  7   Comparison of the evaporation rates of heptane-based nanofluid fuel droplets with pure and stabilized heptane droplets under different temperatures[34]

    图  8   纳米流体燃料点火性能调控规律

    Fig.  8   Regulation of ignition performance of nano fluid fuel

    图  9   纳米流体燃料液滴燃烧能量传递模型

    Fig.  9   Energy transfer model of nanofluid fuel droplet combustion

    图  10   PDA包覆层在n–Al/RP–3液滴燃烧过程中的作用机理[77]

    Fig.  10   Mechanistic diagram of the effect of PDA cladding layer in the combustion process of n–Al/RP–3 nanofluid fuel droplets [77]

    图  11   n–Al@PDA@CuO对煤油液滴点火燃烧性能调控机理[77]

    Fig.  11   Mechanism of PDA coating in the combustion process of n–Al/RP–3 nanofluid fuel droplets[77]

    图  12   装有不同样品的倒置试剂瓶[82]

    Fig.  12   Inverted bottles filled with different samples[82]

    表  1   纳米流体燃料常用基液、纳米颗粒和表面活性剂

    Table  1   Base liquid, nano particle and surfactant commonly used in nano fluid fuel

    基液纳米颗粒纳米颗粒尺寸/nm表面活性剂文献来源
    煤油
    n–Al/CuO/NC等 TOPO [17]
    n–Al 80 OA [21-22]
    n–Al 70 OA [1]
    CuO/NC、KIO4/NC、MgO/NC等 TOPO [16]
    n–Al 80 OA [23]
    硝基甲烷(NM)
    n–SiO2n–Al2O3 [24]
    n–Al,SiO2,TiO2 100,200,20 [25]
    正十四烷(C14) CNTs,CeO2,Co3O4 20和50 CTAB [18]
    正癸烷(C10)
    n–Al 80 Span 80 [26]
    n–B 80 Span 80 [27]
    n–Al2O3 40 [28]
    CeO2,Ce2O3 25 Tween 85 [29]
    柴油
    n–Al,n–Al2O3 50 [30]
    n–Al2O3n–TiO2n–Fe3O4 80,50,45 [31]
    乙醇
    n–Al 80 Span 80 [26]
    n–Fe 80 Span 80 [27]
    SWCNTs 1~2 [20]
    MWCNTs 100 [20]
    CNPs 6 [20]
    n–Al,n–Al2O3 80 [32]
    n–Al 80 [15]
    TiO2 4~8 [33]
    CeO2,Ce2O3 25 Tween 85 [29]
    n–Al,n–SiO2 80 [11]
    n–Al,n–Ag,n–Al2O3n–SiO2n–Fe 80,35,25,80,25 [34]
    正庚烷
    n–Al 80 Span 85 [35]
    n–Al 80 OA [36]
    JP10
    n–B 80 OA,TOP,TOPO,TPP等 [37]
    n–Al,NC,n–Al/NC 80,100060002000 TOPO [8]
    APcoated Al Tween 85 [19]
    n–Al 80 Tween 85 [5]
    注:NC:硝酸纤维素;CNTs:碳纳米管;SWCNTs:单壁碳纳米管;MWCNTs:多壁碳纳米管;CNTs:碳纳米颗粒;AP:高氯酸铵;OA:油酸;CTAB:十六烷基三甲基溴化铵;Span 80:山梨醇酐单油酸酯;Span 85:山梨醇酐三油酸酯;Tween 85:聚甲醛山梨醇三油酸酯;TOP:三正辛基膦;TOPO:三正辛基氧化膦;TPP:有机胺酯。
    下载: 导出CSV

    表  2   改善纳米流体燃料燃烧特性的典型研究成果

    Table  2   Typical results of improving the burning characteristic of nanofluid fuels

    基液改性方法结果文献来源
    乙醇
    加入纳米铝颗粒;改变液滴粒径加入纳米铝颗粒(质量分数5%),燃烧速率提升140%[15]
    加入纳米石墨颗粒加入50 nm石墨颗粒(质量分数3%),燃烧速率提升62%[58]
    加入纳米铝和纳米SiO2颗粒纳米铝颗粒增强燃烧的效果强于纳米SiO2颗粒[9]
    加入纳米硼和纳米铁颗粒液滴燃烧结束后,纳米颗粒团聚成块[27]
    正庚烷加入纳米铝颗粒发生微爆,无纳米颗粒残余[36]
    正癸烷
    加入纳米硼和纳米铁颗粒液滴多次微爆,颗粒从液滴内飞出[27]
    加入纳米铝颗粒CO和NOx的排放减少[59]
    煤油加入纳米铝颗粒燃烧速率显著提升[23]
    JP−10
    加入AP包覆纳米铝颗粒不完全燃烧产生的碳氢化合物减少[19]
    加入纳米铝颗粒加入纳米铝颗粒,燃烧效率为95%,密度比冲提升15%[4]
    火箭煤油加入碳纳米颗粒、多壁碳纳米管、石墨烯纳米片加入碳纳米管(质量分数0.25%),燃烧速率最高[60]
    硝基甲烷
    加入纳米SiO2和Al2O3颗粒;改变环境压力纳米颗粒质量分数低于1.0%时,5.24 MPa下燃烧速率提升超过50%[24]
    加入纳米铝、纳米TiO2和纳米SiO2颗粒燃烧速率提升,压强指数增大[25]
    柴油与生物柴油混合物
    加入纳米氧化石墨烯颗粒CO排放减少,CO2和NOx排放分别增多7%和4%~9%[61]
    加入纳米Al2O3CO和NOx排放显著减少[62]
    加入纳米Al2O3CO和烟雾排放分别减少48.43%和22.84%[63]
    加入多壁碳纳米管NOx、CO、HC的排放减少[64]
    加入纳米ZnO,改变颗粒粒径加入20 nm颗粒,排放减少;加入40 nm颗粒,排放增多[65]
    下载: 导出CSV
  • [1]

    KIM D M, BAEK S W, YOON J. Ignition characteristics of kerosene droplets with the addition of aluminum nanoparticles at elevated temperature and pressure[J]. Combustion and Flame, 2016, 173: 106–113. doi: 10.1016/j.combustflame.2016.07.033

    [2]

    WANG X R, ZHANG J, MA Y, et al. A comprehensive review on the properties of nanofluid fuel and its additive effects to compression ignition engines[J]. Applied Surface Science, 2020, 504: 144581. doi: 10.1016/j.apsusc.2019.144581

    [3]

    KIM D C, KIM J H, WOO J K, et al. A new iron-nanofluid as fuel additive for particulate matter reduction in heavy fuel oil-fired boiler facility[J]. Asian Journal of Chemistry, 2008, 20(7): 5767–5775.

    [4]

    E X-T-F, PAN L, WANG F, et al. Al-nanoparticle-containing nanofluid fuel: synthesis, stability, properties, and propulsion performance[J]. Industrial & Engineering Chemistry Research, 2016, 55(10): 2738–2745. doi: 10.1021/acs.iecr.6b00043

    [5]

    LIU J Z, CHEN B H, WU T T, et al. Ignition and combustion characteristics and agglomerate evolution mechanism of aluminum in nAl/JP–10 nanofluid fuel[J]. Journal of Thermal Analysis and Calorimetry, 2019, 137(4): 1369–1379. doi: 10.1007/s10973-019-08039-5

    [6]

    CHENG Z P, CHU X Z, YIN J Z, et al. Formation of composite fuels by coating aluminum powder with a cobalt nanocatalyst: enhanced heat release and catalytic performance[J]. Chemical Engineering Journal, 2020, 385: 123859. doi: 10.1016/j.cej.2019.123859

    [7]

    EL-SEESY A I, HASSAN H, OOKAWARA S. Influence of adding multiwalled carbon nanotubes to waste cooking oil biodiesel on the performance and emission characteristics of a diesel engine: an experimental investigation[J]. International Journal of Green Energy, 2019, 16(12): 901–916. doi: 10.1080/15435075.2019.1642895

    [8]

    GUERIERI P M, DELISIO J B, ZACHARIAH M R. Nanoaluminum/Nitrocellulose microparticle additive for burn enhancement of liquid fuels[J]. Combustion and Flame, 2017, 176: 220–228. doi: 10.1016/j.combustflame.2016.10.011

    [9]

    SIM H S, PLASCENCIA M A, VARGAS A, et al. Effects of inert and energetic nanoparticles on burning liquid ethanol droplets[J]. Combustion Science and Technology, 2019, 191(7): 1079–1100. doi: 10.1080/00102202.2018.1509857

    [10]

    XU Z, LOU W J, ZHAO G Q, et al. Cu nanoparticles decorated WS2 nanosheets as a lubricant additive for enhanced tribological performance[J]. RSC Advances, 2019, 9(14): 7786–7794. doi: 10.1039/c9ra00337a

    [11]

    SOUDAGAR M E M, NIK-GHAZALI N-N, KALAM M A, et al. The effect of nano-additives in diesel-biodiesel fuel blends: a comprehensive review on stability, engine performance and emission characteristics[J]. Energy Conversion and Management, 2018, 178: 146–177. doi: 10.1016/j.enconman.2018.10.019

    [12]

    SUNDARAM D S, PURI P, YANG V. A general theory of ignition and combustion of nano- and micron-sized aluminum particles[J]. Combustion and Flame, 2016, 169: 94–109. doi: 10.1016/j.combustflame.2016.04.005

    [13] 李鑫, 赵凤起, 郝海霞, 等. 不同类型微/纳米铝粉点火燃烧特性研究[J]. 兵工学报, 2014, 35(5): 640–647. DOI: 10.3969/j.issn.1000-1093.2014.05.010

    LI X, ZHAO F Q, HAO H X, et al. Research on ignition and combustion properties of different micro/nano-aluminum powders[J]. Acta Armamentarii, 2014, 35(5): 640–647. doi: 10.3969/j.issn.1000-1093.2014.05.010

    [14]

    SHIN Y J, SHEN Y H. Preparation of coal slurry with organic solvents[J]. Chemosphere, 2007, 68(2): 389–393. doi: 10.1016/j.chemosphere.2006.12.049

    [15]

    TANVIR S, QIAO L. Effect of addition of energetic nanoparticles on droplet-burning rate of liquid fuels[J]. Journal of Propulsion and Power, 2015, 31(1): 408–415. doi: 10.2514/1.B35500

    [16]

    GUERIERI P M, JACOB R J, DeLISIO J B, et al. Stabilized microparticle aggregates of oxygen-containing nanoparticles in kerosene for enhanced droplet combustion[J]. Combustion and Flame, 2018, 187: 77–86. doi: 10.1016/j.combustflame.2017.08.026

    [17]

    GUERIERI P M, JACOB R J, WANG H Y, et al. Droplet combustion of kerosene augmented by stabilized nano-aluminum/oxidizer composite mesoparticles[J]. Combustion and Flame, 2020, 211: 1–7. doi: 10.1016/j.combustflame.2019.07.031

    [18]

    MEI D Q, SUN C, LI L C, et al. Evaporation characteristics of fuel sessile droplets with nanoparticles[J]. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2019, 41(6): 677–688. doi: 10.1080/15567036.2018.1520350

    [19]

    CHEN B H, LIU J Z, YANG W J, et al. Effect of ammonium perchlorate coating on the ignition and combustion characteristics of Al/JP–10 nanofluid fuel[J]. Combustion Science and Technology, 2020, 192(8): 1567–1581. doi: 10.1080/00102202.2019.1613385

    [20]

    GAN Y N, QIAO L. Optical properties and radiation-enhanced evaporation of nanofluid fuels containing carbon-based nanostructures[J]. Energy & Fuels, 2012, 26(7): 4224–4230. doi: 10.1021/ef300493m

    [21]

    JAVED I, BAEK S W, WAHEED K, et al. Evaporation characteristics of kerosene droplets with dilute concentra-tions of ligand-protected aluminum nanoparticles at elevated temperatures[J]. Combustion and Flame, 2013, 160(12): 2955–2963. doi: 10.1016/j.combustflame.2013.07.007

    [22]

    JAVED I, BAEK S W, WAHEED K. Effects of dense concentrations of aluminum nanoparticles on the evapora-tion behavior of kerosene droplet at elevated temperatures: the phenomenon of microexplosion[J]. Experimental Thermal and Fluid Science, 2014, 56: 33–44. doi: 10.1016/j.expthermflusci.2013.11.006

    [23]

    JAVED I, BAEK S W, WAHEED K. Autoignition and combustion characteristics of kerosene droplets with dilute concentrations of aluminum nanoparticles at elevated temperatures[J]. Combustion and Flame, 2015, 162(3): 774–787. doi: 10.1016/j.combustflame.2014.08.018

    [24]

    SABOURIN J L, YETTER R A, PARIMI V S. Exploring the effects of nanostructured particles on liquid nitro-methane combustion[J]. Journal of Propulsion and Power, 2010, 26(5): 1006–1015. doi: 10.2514/1.48579

    [25]

    McCOWN K W III, PETERSEN E L. Effects of nano-scale additives on the linear burning rate of nitromethane[J]. Combustion and Flame, 2014, 161(7): 1935–1943. doi: 10.1016/j.combustflame.2013.12.019

    [26]

    GAN Y N, QIAO L. Evaporation characteristics of fuel droplets with the addition of nanoparticles under natural and forced convections[J]. International Journal of Heat and Mass Transfer, 2011, 54(23-24): 4913–4922. doi: 10.1016/j.ijheatmasstransfer.2011.07.003

    [27]

    GAN Y N, LIM Y S, QIAO L. Combustion of nanofluid fuels with the addition of boron and iron particles at dilute and dense concentrations[J]. Combustion and Flame, 2012, 159(4): 1732–1740. doi: 10.1016/j.combustflame.2011.12.008

    [28]

    PANDEY K, CHATTOPADHYAY K, BASU S. Combus-tion dynamics of low vapour pressure nanofuel droplets[J]. Physics of Fluids, 2017, 29(7): 074102. doi: 10.1063/1.4991752

    [29]

    PANDEY K, BASU S. How boiling happens in nanofuel droplets[J]. Physics of Fluids, 2018, 30(10): 107103. doi: 10.1063/1.5048564

    [30]

    TYAGI H, PHELAN P E, PRASHER R, et al. Increased hot-plate ignition probability for nanoparticle-laden diesel fuel[J]. Nano Letters, 2008, 8(5): 1410–1416. doi: 10.1021/nl080277d

    [31]

    SHAMS Z, MOGHIMAN M. An experimental investigation of ignition probability of diesel fuel droplets with metal oxide nanoparticles[J]. Thermochimica Acta, 2017, 657: 79–85. doi: 10.1016/j.tca.2017.09.007

    [32]

    GAN Y N, QIAO L. Radiation-enhanced evaporation of ethanol fuel containing suspended metal nanoparticles[J]. International Journal of Heat and Mass Transfer, 2012, 55(21-22): 5777–5782. doi: 10.1016/j.ijheatmasstransfer.2012.05.074

    [33]

    MIGLANI A, BASU S. Effect of particle concentration on shape deformation and secondary atomization characteristics of a burning nanotitania dispersion droplet[J]. Journal of Heat Transfer, 2015, 137(10): 102001. doi: 10.1115/1.4030394

    [34]

    TANVIR S, JAIN S, QIAO L. Latent heat of vaporization of nanofluids: measurements and molecular dynamics simula-tions[J]. Journal of Applied Physics, 2015, 118(1): 014902. doi: 10.1063/1.4922967

    [35]

    JAVED I, BAEK S W, WAHEED K. Evaporation characteristics of heptane droplets with the addition of aluminum nanoparticles at elevated temperatures[J]. Combustion and Flame, 2013, 160(1): 170–183. doi: 10.1016/j.combustflame.2012.09.005

    [36]

    JAVED I, BAEK S W, WAHEED K. Autoignition and combustion characteristics of heptane droplets with the addition of aluminium nanoparticles at elevated temperatures[J]. Combustion and Flame, 2015, 162(1): 191–206. doi: 10.1016/j.combustflame.2014.07.015

    [37]

    E X-T-F, ZHI X M, ZHANG Y M, et al. Jet fuel containing ligand-protecting energetic nanoparticles: a case study of boron in JP–10[J]. Chemical Engineering Science, 2015, 129: 9–13. doi: 10.1016/j.ces.2015.02.018

    [38]

    SEKOAI P T, OUMA C N M, DU PREEZ S P, et al. Application of nanoparticles in biofuels: an overview[J]. Fuel, 2019, 237: 380–397. doi: 10.1016/j.fuel.2018.10.030

    [39]

    SAXENA V, KUMAR N, SAXENA V K. A comprehensive review on combustion and stability aspects of metal nanoparticles and its additive effect on diesel and biodiesel fuelled C. I. engine[J]. Renewable and Sustainable Energy Reviews, 2017, 70: 563–588. doi: 10.1016/j.rser.2016.11.067

    [40]

    WANG C, ZHANG X, SU M. Synthesis and thermal stability of Field’s alloy nanoparticles and nanofluid[J]. Materials Letters, 2017, 205: 6–9. doi: 10.1016/j.matlet.2017.06.051

    [41]

    LI S J, DU H Z, ZHUO Z, et al. Dispersion stability, physical properties, and electrostatic breakup of surfactant-loaded aluminum/n-decane nanofluid fuel: nanoparticle size effect[J]. Energy & Fuels, 2020, 34(1): 1082–1092. doi: 10.1021/acs.energyfuels.9b03332

    [42]

    MEHTA R N, CHAKRABORTY M, PARIKH P A. Nanofuels: Combustion, engine performance and emissions[J]. Fuel, 2014, 120: 91–97. doi: 10.1016/j.fuel.2013.12.008

    [43]

    VAN DEVENER B, ANDERSON S L. Breakdown and combustion of JP–10 fuel catalyzed by nanoparticulate CeO2 and Fe2O3[J]. Energy & Fuels, 2006, 20(5): 1886–1894. doi: 10.1021/ef060064g

    [44]

    GAN Y N, QIAO L. Combustion characteristics of fuel droplets with addition of nano and micron-sized aluminum particles[J]. Combustion and Flame, 2011, 158(2): 354–368. doi: 10.1016/j.combustflame.2010.09.005

    [45]

    SHARIATMADAR F S, PAKDEHI S G. Effect of various surfactants on the stability time of kerosene-boron nanofluids[J]. Micro & Nano Letters, 2016, 11(9): 498–502. doi: 10.1049/mnl.2016.0223

    [46]

    KANNAIYAN K, ANOOP K, SADR R. Effect of nanoparticles on the fuel properties and spray performance of aviation turbine fuel[J]. Journal of Energy Resources Technology, 2017, 139(3): 032201. doi: 10.1115/1.4034858

    [47]

    HE Y R, JIN Y, CHEN H S, et al. Heat transfer and flow behaviour of aqueous suspensions of TiO2 nanoparticles (nanofluids) flowing upward through a vertical pipe[J]. International Journal of Heat and Mass Transfer, 2007, 50(11-12): 2272–2281. doi: 10.1016/j.ijheatmasstransfer.2006.10.024

    [48]

    NGUYEN C T, DESGRANGES F, ROY G, et al. Temperature and particle-size dependent viscosity data for water-based nanofluids-Hysteresis phenomenon[J]. International Journal of Heat and Fluid Flow, 2007, 28(6): 1492–1506. doi: 10.1016/j.ijheatfluidflow.2007.02.004

    [49]

    NGUYEN C T, DESGRANGES F, GALANIS N, et al. Viscosity data for Al2O3-water nanofluid-hysteresis: is heat transfer enhancement using nanofluids reliable?[J]. International Journal of Thermal Sciences, 2008, 47(2): 103–111. doi: 10.1016/j.ijthermalsci.2007.01.033

    [50]

    ALAWI O A, SIDIK N A C. Mathematical correlations on factors affecting the thermal conductivity and dynamic viscosity of nanorefrigerants[J]. International Communica-tions in Heat and Mass Transfer, 2014, 58: 125–131. doi: 10.1016/j.icheatmasstransfer.2014.08.033

    [51]

    CHEVALIER J, TILLEMENT O, AYELA F. Rheological properties of nanofluids flowing through microchannels[J]. Applied Physics Letters, 2007, 91(23): 233103. doi: 10.1063/1.2821117

    [52]

    ESFE M H, SAEDODIN S, WONGWISES S, et al. An experimental study on the effect of diameter on thermal conductivity and dynamic viscosity of Fe/water nanofluids[J]. Journal of Thermal Analysis and Calorimetry, 2015, 119(3): 1817–1824. doi: 10.1007/s10973-014-4328-8

    [53]

    WANG J, HUANG X, QIAO X, et al. Experimental study on evaporation characteristics of single and multiple fuel droplets[J]. Journal of the Energy Institute, 2020, 93(4): 1473–1480. doi: 10.1016/j.joei.2020.01.009

    [54]

    SUH H K, LEE C S. Experimental and analytical study on the spray characteristics of dimethyl ether (DME) and diesel fuels within a common-rail injection system in a diesel engine[J]. Fuel, 2008, 87(6): 925–932. doi: 10.1016/j.fuel.2007.05.051

    [55]

    WANG J G, WANG X R, CHEN H, et al. Experimental study on puffing and evaporation characteristics of jatropha straight vegetable oil (SVO) droplets[J]. International Journal of Heat and Mass Transfer, 2018, 119: 392–399. doi: 10.1016/j.ijheatmasstransfer.2017.11.130

    [56]

    SUNDARARAJ A J, PILLAI B C, GUNA K R. Experimental investigation of effect of temperature on ignition behaviour of seeded refined kerosene[J]. Thermochimica Acta, 2020, 683: 178469. doi: 10.1016/j.tca.2019.178469

    [57]

    HAN W K, DAI B X, LIU J Z, et al. Ignition and combustion characteristics of heptane-based nanofluid fuel droplets[J]. Energy & Fuels, 2019, 33(10): 10282–10289. doi: 10.1021/acs.energyfuels.9b02347

    [58]

    TANVIR S, QIAO L. Droplet burning rate enhancement of ethanol with the addition of graphite nanoparticles: influence of radiation absorption[J]. Combustion and Flame, 2016, 166: 34–44. doi: 10.1016/j.combustflame.2015.12.021

    [59]

    MEHREGAN M, MOGHIMAN M. Effect of aluminum nanoparticles on combustion characteristics and pollutants emission of liquid fuels A numerical study[J]. Fuel, 2014, 119: 57–61. doi: 10.1016/j.fuel.2013.11.016

    [60]

    GHAMARI M, RATNER A. Combustion characteristics of colloidal droplets of jet fuel and carbon based nano-particles[J]. Fuel, 2017, 188: 182–189. doi: 10.1016/j.fuel.2016.10.040

    [61]

    HOSEINI S S, NAJAFI G, GHOBADIAN B, et al. Performance and emission characteristics of a CI engine using graphene oxide (GO) nano-particles additives in biodiesel-diesel blends[J]. Renewable Energy, 2020, 145: 458–465. doi: 10.1016/j.renene.2019.06.006

    [62]

    RAMESH D K, DHANANJAYA KUMAR J L, HEMANTH KUMAR S G, et al. Study on effects of alumina nanoparticles as additive with poultry litter biodiesel on performance, combustion and emission characteristic of diesel engine[J]. Materials Today:Proceedings, 2018, 5(1): 1114–1120. doi: 10.1016/j.matpr.2017.11.190

    [63]

    SOUDAGAR M E M, NIK-GHAZALI N N, KALAM M A, et al. An investigation on the influence of aluminium oxide nano-additive and honge oil methyl ester on engine performance, combustion and emission characteristics[J]. Renewable Energy, 2020, 146: 2291–2307. doi: 10.1016/j.renene.2019.08.025

    [64]

    EL-SEESY A I, ABDEL-RAHMAN A K, BADY M, et al. Performance, combustion, and emission characteristics of a diesel engine fueled by biodiesel-diesel mixtures with multi-walled carbon nanotubes additives[J]. Energy Conversion and Management, 2017, 135: 373–393. doi: 10.1016/j.enconman.2016.12.090

    [65]

    JAVED S, SATYANARAYANA MURTHY Y V V, SATYANARAYANA M R S, et al. Effect of a zinc oxide nanoparticle fuel additive on the emission reduction of a hydrogen dual-fuelled engine with jatropha methyl ester biodiesel blends[J]. Journal of Cleaner Production, 2016, 137: 490–506. doi: 10.1016/j.jclepro.2016.07.125

    [66]

    CHENG Y X, ZHAO Y, ZHAO F Q, et al. ReaxFF simulations on the combustion of Al and n–butanol nanofluid[J]. Fuel, 2022, 330: 125465. doi: 10.1016/j.fuel.2022.125465

    [67]

    WEI J J, HE C J, LV G, et al. The combustion, performance and emissions investigation of a dual-fuel diesel engine using silicon dioxide nanoparticle additives to methanol[J]. Energy, 2021, 230: 120734. doi: 10.1016/j.energy.2021.120734

    [68]

    YAN Q L, GOZIN M, ZHAO F Q, et al. Highly energetic compositions based on functionalized carbon nano-materials[J]. Nanoscale, 2016, 8(9): 4799–4851. doi: 10.1039/c5nr07855e

    [69]

    HE W, LIU P J, HE G Q, et al. Highly reactive metastable intermixed composites (MICs): preparation and characteri-zation[J]. Advanced Materials, 2018, 30(41): 1706293. doi: 10.1002/adma.201706293

    [70]

    SUNDARAM D, YANG V, YETTER R A. Metal-based nanoenergetic materials: synthesis, properties, and applica-tions[J]. Progress in Energy and Combustion Science, 2017, 61: 293–365. doi: 10.1016/j.pecs.2017.02.002

    [71]

    PATEL V K, SAURAV J R, GANGOPADHYAY K, et al. Combustion characterization and modeling of novel nanoenergetic composites of Co3O4/nAl[J]. RSC Advances, 2015, 5(28): 21471–21479. doi: 10.1039/C4RA14751K

    [72]

    YAN Q L, ZHAO F Q, KUO K K, et al. Catalytic effects of nano additives on decomposition and combustion of RDX-, HMX-, and AP-based energetic compositions[J]. Progress in Energy and Combustion Science, 2016, 57: 75–136. doi: 10.1016/j.pecs.2016.08.002

    [73]

    WANG L L, MUNIR Z A, MAXIMOV Y M. Thermite reactions: their utilization in the synthesis and processing of materials[J]. Journal of Materials Science, 1993, 28(14): 3693–3708. doi: 10.1007/BF00353167

    [74]

    FOLEY T, PACHECO A, MALCHI J, et al. Development of nanothermite composites with variable electrostatic discharge ignition thresholds[J]. Propellants, Explosives, Pyrotechnics, 2007, 32(6): 431–434. doi: 10.1002/prep.200700273

    [75]

    HE W, LIU P J, GONG F Y, et al. Tuning the reactivity of metastable intermixed composite n–Al/PTFE by polydopa-mine interfacial control[J]. ACS Applied Materials & Interfaces, 2018, 10(38): 32849–32858. doi: 10.1021/acsami.8b10197

    [76]

    HE W, TAO B W, YANG Z J, et al. Mussel-inspired polydopamine-directed crystal growth of core-shell n–Al@PDA@CuO metastable intermixed composites[J]. Chemical Engineering Journal, 2019, 369: 1093–1101. doi: 10.1016/j.cej.2019.03.165

    [77]

    AO W, GAO Y, ZHOU S, et al. Enhancing the stability and combustion of a nanofluid fuel with polydopamine-coated aluminum nanoparticles[J]. Chemical Engineering Journal, 2021, 418: 129527. doi: 10.1016/j.cej.2021.129527

    [78]

    GAO Y, AO W, LI L K B, et al. Catalyzed combustion of a nanofluid fuel droplet containing polydopamine-coated metastable intermixed composite n–Al/CuO[J]. Aerospace Science and Technology, 2021, 118: 107005. doi: 10.1016/j.ast.2021.107005

    [79]

    CHEN W Q, ZHU B Z, SUN Y L, et al. Nano-sized copper oxide enhancing the combustion of aluminum/kerosene-based nanofluid fuel droplets[J]. Combustion and Flame, 2022, 240: 112028. doi: 10.1016/j.combustflame.2022.112028

    [80]

    HE W, AO W, YANG G C, et al. Metastable energetic nanocomposites of MOF-activated aluminum featured with multi-level energy releases[J]. Chemical Engineering Journal, 2020, 381: 122623. doi: 10.1016/j.cej.2019.122623

    [81]

    PANDYA N S, SHAH H, MOLANA M, et al. Heat transfer enhancement with nanofluids in plate heat exchangers: a comprehensive review[J]. European Journal of Mechanics - B/Fluids, 2020, 81: 173–190. doi: 10.1016/j.euromechflu.2020.02.004

    [82]

    YANG D L, XIA Z X, HUANG L Y, et al. Synthesis of metallized kerosene gel and its characterization for propulsion applications[J]. Fuel, 2020, 262: 116684. doi: 10.1016/j.fuel.2019.116684

    [83]

    CHEN A Q, GUAN X D, LI X M, et al. Preparation and characterization of metalized JP–10 gel propellants with excellent thixotropic performance[J]. Propellants, Explosives, Pyrotechnics, 2017, 42(9): 1007–1013. doi: 10.1002/prep.201700161

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    其他类型引用(2)

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  • 被引次数: 5
出版历程
  • 收稿日期:  2022-10-31
  • 修回日期:  2023-02-05
  • 录用日期:  2023-02-26
  • 网络出版日期:  2023-04-22
  • 刊出日期:  2024-10-24

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