蘇杰,李小平,李俊鋒,周長江
煙包新材料與數(shù)字化
柔性生物質(zhì)顆粒的流體動力學行為研究綜述
蘇杰1,李小平2,李俊鋒2,周長江1
(1.湖南大學 汽車車身先進設(shè)計與制造國家重點試驗室,長沙 410082;2.中煙機械集團常德煙草機械有限責任公司,湖南 常德 415000)
目的 分析柔性生物質(zhì)顆粒的應(yīng)用背景,提出生物質(zhì)的清潔度與取向分布是影響產(chǎn)品包裝質(zhì)量的2個關(guān)鍵因素。方法 從多相流的數(shù)值模擬方法、柔性顆粒建模理論、曳力模型適用性等角度總結(jié)國內(nèi)外生物質(zhì)流化研究成果。重點闡述本課題組在生物質(zhì)表征、生物質(zhì)分離與取向調(diào)控方面提出的解決方案。結(jié)果 機器視覺適用于生物質(zhì)物理與力學性能的測量,多傾斜曲面通道可用于混合顆粒的有效分離,楔形通道的流場速度梯度能夠加速非球形顆粒的取向調(diào)整。結(jié)論 概括了柔性生物質(zhì)顆粒流化模擬中存在的主要問題,提出了未來的研究計劃。
柔性生物質(zhì);流體動力學;生物質(zhì)表征;顆粒分離;取向調(diào)控
顆粒是物質(zhì)存在的普遍形態(tài),包含氣、液、固三相。固體顆粒應(yīng)用最為廣泛,涉及材料工程、化學工程、生物工程和各種交叉學科。柔性生物質(zhì)顆粒是一類特殊的固體顆粒[1],普遍存在于能源、材料和制藥等工業(yè)應(yīng)用中。柔性生物質(zhì)材料[2]易與雜質(zhì)混合,無序排列的顆粒將增加填充床的空隙率,因此,生物質(zhì)的清潔度與取向分布成為影響產(chǎn)品包裝質(zhì)量的2個關(guān)鍵因素。
生物質(zhì)顆粒的物理性質(zhì)主要包括顆粒的大小、形態(tài)和密度[3]。力學性能包括彈性模量、泊松比和抗拉強度等[4]。Vorobiev等[5]的研究表明生物質(zhì)的流化和燃燒受顆粒形態(tài)和力學性能影響。然而,生物質(zhì)通常被描述為球形或鏈狀顆粒[6],彈性模量和泊松比[7]很少被關(guān)注。為降低數(shù)值模擬與實驗測量的誤差,有必要提出針對柔性生物質(zhì)顆粒的機器視覺測量方法,建立物理與力學性能量化模型[8-9]。
混合生物質(zhì)顆粒的分離純化技術(shù)在農(nóng)業(yè)、環(huán)境、機械、化工等領(lǐng)域中占有重要地位。由于混合物大小、密度和形狀不同,一般使用振動、離心或篩分設(shè)備[10]進行分類。Zhou等[11]總結(jié)了異形異質(zhì)混合物的分離方法,提出氣流篩分綠色加工技術(shù)。循環(huán)流化床[12-13]是稠密氣固反應(yīng)流的典型應(yīng)用,氣固輸送系統(tǒng)[14-15]控制生物質(zhì)顆粒的進料效率,旋風分離器[16]通過離心力將混合顆粒和氣體分離。考慮到多成分混合顆粒的復(fù)雜性,分離流化床的設(shè)計原理、驗證和優(yōu)化方法有待進一步完善。
柔性顆粒取向控制是包裝工程的關(guān)鍵研發(fā)技術(shù)[17]。有序顆粒填充均勻,利于顆粒儲存和運輸。顆粒隨機分布導(dǎo)致包裝不良,降低產(chǎn)品質(zhì)量和工作效率。Cui等[18]對懸浮液內(nèi)纖維的運動規(guī)律進行了數(shù)值模擬,發(fā)現(xiàn)纖維取向影響聚合物的理化性質(zhì),因此,提高顆粒的有序性可為生物質(zhì)包裝與纖維復(fù)合材料的開發(fā)提供新的見解。目前,Cai等[19-20]已開展了柱狀顆粒的角度識別實驗,但關(guān)于小麥、茶葉、煙絲和纖維等柔性顆粒的取向研究較少。
綜上所述,多組分生物質(zhì)顆粒的分離與取向調(diào)控研究尚處于起步階段,微觀與宏觀尺度下多相相互作用機理尚未闡明。為優(yōu)化生物質(zhì)包裝質(zhì)量,文中從多相流數(shù)值模擬方法、生物質(zhì)表征、分離與取向調(diào)控等方面總結(jié)國內(nèi)外的研究現(xiàn)狀和發(fā)展趨勢,重點闡述本課題組的相關(guān)工作。
由于多相流的復(fù)雜性,現(xiàn)有的試驗技術(shù)難以全面揭示顆粒流動行為,計算流體動力學成為分析氣流與顆粒分布特征的重要手段。一般采用3種數(shù)值模擬方法研究流體域中的球形與非球形顆粒。方法1為基于歐拉?歐拉法的雙流體模型,顆粒視為連續(xù)相[21-22],粒子間的碰撞采用應(yīng)力模型[23]描述,顆粒?流體耦合通過曳力模型[24]實現(xiàn);方法2中顆粒和流體視為2種不同的相[25],流體根據(jù)納維–斯托克斯方程求解,粒子根據(jù)牛頓第二定律計算,采用拉格朗日方法跟蹤。非球形粒子的形狀可以用球形度法、多球面法[26-27]或元粒子模型[28-29]表示,如計算流體動力學–離散單元法(CFD–DEM);方法3為顆粒全解析直接數(shù)值模擬方法(PR–DNS)[30-31],流固耦合力由流體的壓力和黏滯力決定,適用于微觀尺度的顆粒運動分析。
雙流體模型難以表征顆粒的幾何特性,PR–DNS一般用于1 000顆粒以下的數(shù)值模擬。相較于其他數(shù)值模擬方法,CFD–DEM能夠滿足工業(yè)級的顆粒流化分析,得到精準的顆粒尺度信息[32]。CFD–DEM模型中,流體相由CFD計算,顆粒相由DEM求解[33],相間耦合通過曳力模型實現(xiàn)。
非球形顆粒的形貌特征復(fù)雜,先前的文獻[34-35]建立了非球形顆粒的多種表征模型,如超橢球模型和多球模型等。Kravets等[36]采用PR–DNS和CFD–DEM法比較了非球形顆粒的流動行為,證明了多球模型表征顆粒形狀的可行性。Ren等[37]利用CFD–DEM法研究了噴動床中玉米顆粒的流動特性。Atxutegi等[38]研究了橢球狀顆粒在棱柱狀和錐形噴動床中的流化行為,并預(yù)測最小噴動速度和噴泉高度。
諸多CFD–DEM研究為生物質(zhì)顆粒流化系統(tǒng)的設(shè)計與優(yōu)化提供了宏觀尺度上的重要見解。圖1為CFD–DEM耦合計算流程。單個時間步長內(nèi),DEM提供顆粒位置和速度信息。耦合模塊計算每個單元的空隙率和耦合力,更新CFD模型的流場特征。
圖1 CFD–DEM耦合求解流程
CFD–DEM既能用于兩相流動的微觀機理研究,又滿足計算的經(jīng)濟性需求,在非球形顆粒的多相流動領(lǐng)域具有巨大的發(fā)展?jié)摿?。本?jié)概述了CFD–DEM模型中柔性生物質(zhì)顆粒建模方法,稠密非球形顆粒系統(tǒng)中流體相運動方程及柔性顆粒曳力模型的適用性。相關(guān)研究為未來生物質(zhì)氣固系統(tǒng)的仿真與優(yōu)化提供理論指導(dǎo)。
柔性生物質(zhì)顆粒與球體相差較大,簡化為等效球體的模擬結(jié)果與試驗存在較大偏差[39]。為分析柔性生物質(zhì)顆粒的動力學行為[40-41],Geng等[42-43]開發(fā)了鏈狀顆粒模型。圖2為單個柔性絲狀顆粒的建模方法[43],每個顆粒由3段帶鉸鏈的剛體組成。結(jié)果表明,立管內(nèi)顆粒分布不均勻,存在濃度較高的局部區(qū)域。底部和中心顆粒密集,頂部和壁面稀疏。由于鏈狀模型比球形粒子更復(fù)雜,包含了粒子間的接觸力、鉸鏈約束和摩擦作用,數(shù)值模擬與試驗結(jié)果較為吻合。
圖2 柔性粒子的表征方法
Xia等[44]全面分析了生物質(zhì)顆粒的建模方法,發(fā)現(xiàn)黏結(jié)球模型能夠有效表征顆粒的卷曲度。本課題組基于離散元法與雙鏈狀黏結(jié)球模型對柔性顆粒的流化進行大量研究[45],包括煙絲的流化與茶葉的取向控制。柔性生物質(zhì)顆粒由多個球體組成,球體與球體之間通過黏性鍵連接,見圖3。
圖3 柔性顆粒雙鏈黏結(jié)球模型
顆粒運動主要與重力、碰撞力和曳力有關(guān)。離散相密度遠大于流體相密度,附加質(zhì)量力和浮力可忽略。單個球體的運動由牛頓第二定律運動方程描述:
式中:m為質(zhì)點的質(zhì)量;I為質(zhì)點的慣性矩;v和ω為質(zhì)點的平移速度和角速度;為重力加速度;p為質(zhì)點半徑;為質(zhì)點質(zhì)心到接觸點的矢量;r為顆粒的摩擦因數(shù);d,i為阻力;c,i為接觸力,由法向接觸力n,ij和切向接觸力t,ij組成;ψ為鏈中顆粒上的總勢函數(shù)。
式中:為作用在顆粒上的勢函數(shù)。
2個球體之間的黏性力為:
式中:s為彈簧系數(shù);0為2個球體的平衡距離;r為球體中心距離。
DEM采用Hertz–Mindlin接觸模型描述顆粒–顆粒和顆粒–壁面的相互作用,見圖4。法向力和切向力具有彈性和阻尼分量。碰撞模型表達式見表1。
圖4 顆粒碰撞模型
其中,n與t分別代表法向和切向的顆粒重疊量;nrel與trel分別為相對法向和切向速度;為摩擦因數(shù);為恢復(fù)系數(shù);和分別為顆粒的彈性模量、泊松比和半徑。
流體相采用連續(xù)性方程和動量守恒方程[46-47]描述:
表1 顆粒碰撞力表達式
Tab.1 Expression of particle collision force
式中:g為流體密度;為計算單元的空隙率;g為流體速度;g為流體壓力;g為流體黏度;pf為流體中顆粒的體積力;d,i為單個球體的曳力;Δ為流體單元體積;p為流體單元中顆粒的數(shù)量;p為顆粒體積。d,i的表達式為:
式中:p為顆粒速度;D為曳力系數(shù)。
基于–模型研究流化床內(nèi)的湍流現(xiàn)象:
式中:ε1=1.44、ε2=1.92;k為平均速度梯度產(chǎn)生的湍流動能;kb為浮力產(chǎn)生的湍流動能;k和ε為和方程的普朗特數(shù);k和ε為源項;為湍流耗散率;為湍流動能。
曳力模型是研究顆粒運動特性的前提,本課題組基于機器視覺方法捕獲顆粒的沉降過程,討論了3種曳力模型對柔性生物質(zhì)流化的影響[45]。
模型1:Haider & Levenspiel曳力系數(shù)[48]:
模型2:Chien曳力系數(shù)[49]:
模型3:Morsi曳力系數(shù)[50]:
式中:D為曳力系數(shù);為球形度;e為雷諾數(shù)。
圖5a為入口氣速0.3 m/s的顆粒沉降試驗[45]。圖5b比較了不同曳力模型下柔性顆粒模擬與試驗的相對位置偏差。基于Haider & Levenspiel曳力模型的偏差較小,且分布均勻。
Jensen等[51]研究了顆粒大小和形狀對脫揮發(fā)分的影響。Li等[52]證明了鍋爐的傳熱性能與顆粒尺寸有關(guān)。Hill等[53]評價了顆??v橫比對破碎條件的影響,因此,柔性顆粒與流體的相互作用受顆粒物理性能的影響。Bullard等[54]證明了粒子形狀可以用無量綱形狀因子來描述。Gil等[55]采用圖像處理技術(shù)研究生物質(zhì)顆粒的幾何尺寸。本課題組提出柔性生物質(zhì)顆粒的計算機視覺測量方法[56],并對生物質(zhì)的物理性能進行量化,如尺寸、形貌和密度等(圖6)。
圖5 3種曳力模型下顆粒的運動特征
圖6 柔性生物質(zhì)顆粒物理性能圖像試驗平臺
圖像測量方法[57]通過計算監(jiān)測區(qū)域內(nèi)顆粒邊緣信息與填充像素,無損獲得顆粒周長、面積,包括4個步驟:圖像預(yù)處理、圖像銳化、連通域分割和后處理(圖7)。試驗結(jié)果表明,生物質(zhì)顆粒的平均圓度為0.2、矩形度為0.4、球形度為0.16,當量直徑和密度服從偏態(tài)正態(tài)分布。
金屬材料的彈性模量一般采用單軸拉伸法測量,應(yīng)變由試樣表面的電阻應(yīng)變片獲得,但該方法不適用于小型生物質(zhì)顆粒[58],因為引伸計引起的變形誤差大于拉伸力。為此,Su等[56]提出一種計算泊松比的數(shù)字圖像相關(guān)方法,顆粒的橫向與縱向位移由生物質(zhì)表面的散斑變化計算(圖8)。彈性模量和泊松比的分布區(qū)間分別為30~600 MPa和0.25~0.307。
圖7 圖像處理流程
圖8 生物質(zhì)力學性能的動態(tài)圖像測量方法
為驗證動態(tài)圖像測量方法對生物質(zhì)顆粒力學性能的適用性,圖9a給出了拉應(yīng)力和Von Mises應(yīng)力的數(shù)值模擬結(jié)果[56]。邊界和中心的Von Mises應(yīng)力最大,拉伸時斷裂概率最高。對比試驗與有限元模型的應(yīng)力–應(yīng)變曲線(見圖9)發(fā)現(xiàn),數(shù)值模擬的結(jié)果略低于試驗的。
圖9 試驗與數(shù)值模擬結(jié)果對比
由于生物質(zhì)是由不同密度、大小和形狀的混合顆粒組成,提出了多種分離純化方法。Erman等[59]設(shè)計了包含多個收集器的新型旋風分離器。Konrath等[60]研究了離心分級設(shè)備中細顆粒的分離條件,并利用光傳感器測量了固體濃度。Yang等[61-63]模擬了管徑對水力旋流器分離增強效果的影響。Lyu等[64]研究了煤在氣固分離流化床中的運動和分離行為,證明氣泡破裂和曳力導(dǎo)致顆粒簇錯位。Ma等[65]研究了離心場中粒子的分離特性。Masliyah等[66]首次發(fā)現(xiàn)流化床的傾斜結(jié)構(gòu)能夠提高雙組分懸浮液的分離效率。Z字形通道由多個傾斜截面組成,在混合生物質(zhì)顆粒的流化和分離方面具有很大的潛力。
本課題組提出了一種含多傾斜截面的新型的Z字形流化系統(tǒng)[11],采用CFD–DEM分析氣流篩分速度對生物質(zhì)顆粒分離性能的影響(圖10)。通道中心的生物質(zhì)隨氣流呈Z字形運動,具有良好的跟隨性能,但傾向于沿壁面滑動,見圖11。在最佳氣速1.5 m/s時,清潔生物質(zhì)和雜質(zhì)得到有效分離。
圖10 Z字形流化系統(tǒng)
圖11 流化床內(nèi)顆粒分布
通過建立高速流化圖像試驗平臺驗證流化床中生物質(zhì)顆粒數(shù)值模擬的可靠性[11]。顆粒運動主要包括4個階段:上升、沉降、再懸浮和分離(圖12)。在氣流和重力的影響下,細顆粒隨氣體向上運動;當上升顆粒與傾斜截面碰撞時,顆粒濃度和氣流減弱,一些粗顆粒開始沉降(沉降階段);再懸浮階段部分細顆粒繼續(xù)上升,粗顆粒和少量細顆粒留在通道底部。相關(guān)研究的突破與創(chuàng)新對冶金、能源、化工、機械、材料等領(lǐng)域的發(fā)展具有指導(dǎo)意義。
圖12 高速流化圖像試驗平臺
Wang等[67]研究了茶葉在通道中的變形和運動軌跡,結(jié)果表明重力作用下茶葉順時針旋轉(zhuǎn)并保持振蕩狀態(tài)。Guo等[68]認為纖維傾向于與流動方向一致排列。Pei等[69]發(fā)現(xiàn)纖維與壁面碰撞使平行度變差。Cui等[18]采用浸入邊界–格子玻爾茲曼法對水平通道中纖維的運動特性進行了研究,探明漸縮管有助于加速纖維方向調(diào)整。Ma等[70]通過CFD–DEM對鼓泡床內(nèi)棒狀顆粒進行數(shù)值模擬,發(fā)現(xiàn)隨著流態(tài)化速度的增加,顆粒長軸平行于重力方向。Su等[71]基于浸沒光滑有限元法研究黏性流體域中矩形顆粒的運動規(guī)律及取向控制機理,驗證了楔形通道能夠自由調(diào)控非球形顆粒的角度。
為研究柔性生物質(zhì)顆粒的取向調(diào)控機理,本課題組開展楔形通道中混合顆粒流化試驗[45],見圖13。通過圖像處理方法去除圖片背景,得到顆粒流化二值圖。結(jié)果表明,通道下方的顆粒濃度大,柔性顆粒容易纏結(jié)成絮團?;贑FD–DEM模型分析柔性顆粒的流體動力學行為,發(fā)現(xiàn)流化特征與試驗結(jié)果吻合良好,最大相對位置偏差小于5%。
圖像處理后不同截面的顆粒分布見圖14[45],結(jié)果表明,底部顆粒分布為四周密集而中間稀疏;隨著高度的增加,柔性顆粒由壁面區(qū)域向中心聚集。數(shù)值模擬獲得了與試驗一致的顆粒團聚現(xiàn)象。
采用高速相機拍攝顆粒流化過程,動態(tài)識別顆粒濃度與角度分布[45],見圖15a。通過標記顆粒的最小外接矩形,得到生物質(zhì)的坐標信息。統(tǒng)計所有顆粒的角度范圍,發(fā)現(xiàn)流化顆粒的長軸與重力方向近似一致?;贑FD–DEM研究楔形角對顆粒取向的影響,通過改變出口直徑調(diào)整楔形角度。圖15b的結(jié)果表明,小取向角顆粒的所占比例隨著出口直徑的減小而增大。出口直徑為40 mm時取向為0°~10°的顆粒比例為25%,顆粒取向為10°~20°的比例達到35%。
圖13 楔形通道內(nèi)顆粒分布
圖14 不同截面的瞬態(tài)顆粒分布
圖15 流化通道中顆粒取向?qū)嶒炁c數(shù)值模擬
隨著多相流數(shù)值模擬算法不斷完善,各種柔性顆粒的表征模型被提出,基于機器視覺的圖像試驗開始用于顆粒形貌測量與軌跡識別。文中介紹了生物質(zhì)顆粒表征、分離與取向調(diào)控的研究進展,發(fā)現(xiàn)其應(yīng)用仍然處于初步探索階段,面臨不少亟待解決的問題。
1)柔性顆粒構(gòu)建困難。通常過度簡化為球形、橢球形和細長圓柱,模擬結(jié)果準確性低;黏結(jié)球或鏈狀顆粒模型是表征柔性顆粒的有效方法之一,但柔韌性關(guān)聯(lián)參數(shù)有待研究。
2)需要發(fā)展先進的顆粒圖像測量方法,包括柔性生物質(zhì)的物理與力學屬性測量,進一步量化顆粒的尺寸分布、形貌特征、密度分布、彈性模量和泊松比。建立光纖式顆粒圖像測量系統(tǒng),快速測量生物質(zhì)的局部濃度。
3)目前國內(nèi)外對顆粒的分離與取向調(diào)控研究較少,主要集中在離心分離和懸浮纖維的取向分析,混合柔性生物質(zhì)顆粒的分離特性和取向控制沒有得到足夠的重視。后續(xù)研究應(yīng)從數(shù)值模擬與試驗角度揭示生物質(zhì)在復(fù)雜通道的多尺度運動機制,提高對非規(guī)則流化系統(tǒng)中生物質(zhì)分離與取向調(diào)控的認知水平。
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Review on Fluid Dynamics Behavior of Flexible Biomass Particles
SU Jie1, LI Xiao-ping2, LI Jun-feng2, ZHOU Chang-jiang1
(1. State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha 410082, China; 2. Changde Tobacco Machinery Co., Ltd., China Tobacco Machinery Group, Hunan Changde 415000, China)
The work aims to analyze the application background of flexible biomass particles and propose two key factors (cleanliness and orientation distribution of biomass) affecting product packaging quality. The research achievements of biomass fluidization were summarized from the perspectives of numerical simulation methods, flexible particle modeling theory, and the applicability of the drag model. The solutions proposed by the research group in biomass characterization, biomass separation and orientation control were described. Machine vision technology was suitable for the measurement of physical and mechanical properties of biomass. Multi-inclined curved channels can be used for effective separation of mixed particles. The flow velocity gradient of the wedge-shaped channel can accelerate the orientation adjustment of non-spherical particles. The main problems in numerical simulation of biomass fluidization are summarized and future research plans are proposed.
flexible biomass particles; fluid dynamics; biomass characterization; particle separation; orientation control
O359
A
1001-3563(2023)03-0200-10
10.19554/j.cnki.1001-3563.2023.03.025
2022?06?16
國家自然科學基金(52075153);湖南省重點研發(fā)基金(2020WK2032)
蘇杰(1996—),男,博士,主要研究方向為計算流體動力學,多相流,離散元模型,圖像處理。
周長江(1974—),男,博士,教授,主要研究方向為計算流體動力學,多相流。
責任編輯:曾鈺嬋