MASTS Numercal & Expermental Hydrodynamc Modellng Forum Workshop Grassmarket Centre Ednburgh 9th Aprl 208 Expermental and Numercal Studes on Flocculaton of Sand-Mud Suspensons Dr Alan Cuthbertson Senor Lecturer n Envronmental Flud Mechancs School of Scence and Engneerng Unversty of Dundee a..s.cuthbertson@dundee.ac.uk
Background and context Subtdal/ntertdal estuarne sedments often consst of sand-mud mxtures Interacton of cohesve & non-cohesve fractons crucal n key sedmentaton processes and morphologcal change Important for sedment management ssues n estuares/coastal regons: Dredgng and dredge spol dsposal; Port/harbour developments marne renewables nstallatons; navgaton Emergng rsks from contamnants (e.g. mcroplastcs nano-materals)
Key sedmentaton processes for mxed (sand-mud) sedments Mud partcles Sand partcles Flocculaton Turbulent mxng Floc break-up Varable water surface (tdal and wave) Key processes: Mxng Aggregaton Segregaton Settlng Partcle settlng Floc settlng Sedmentaton Sand Bed Eroson Entranment Deposton Horzontal gradng and segregaton Sand/Mud Mxture Fludsed sedment bed surface layer Consoldated bed layer Key processes: Deposton Bed segregaton Consoldaton Fludsaton Entranment
Ams and obectves Am of study: Investgate flocculaton and settlng behavour of purelycohesve (mud-only) and mxed (sand-mud) suspensons Obectves: Conduct parametrc experments to determne nfluence of turbulent shear and local sedment concentratons on floc development wthn mud-only & sand-mud suspensons Develop a DV model ncorporatng a populaton balance equaton (PBE) to smulate settlng and flocculaton processes wthn mud-only & sand-mud suspensons Develop and test new model representaton of sand-mud nteractons wthn PBE approach
Expermental faclty Grd strred flocculatonsettlng column: Mxng paddles Buffer mxng tank Vbraton sand feeder Motor Controlled zero-mean shear turbulence Crcular gate () (2) Kaoln clay feed Contnuous sedment (clay + sand) supply at buffer tank Mxture concentratons n settlng column Man Settlng column secton OBS_ Probe OBS_2 Probe (3) (4) (5) (6) (7) (8) Oscllatng grds Perstaltc pump Grd oscllaton OBS_ Floc characterstcs: floc szes aggregaton and settlng rates. Gate openng Rectangular vewng tank CCD Camera Clear water chamber Floc Measurement Secton Floc vewng chamber (a) OBS_2 (b)
Expermental parameters Grd-generated turbulence: Mesh sze M = 0.045 m; Stroke S = 0.053 m Oscllaton frequency f = 0.2 0.6 s - Turbulent shear rate G = 0.7 225 s - Kaoln-clay (mud) nput condtons: Input concentraton C m =.2.8 and 2.4 g l - Feed rate nto buffer tank Q m = 0.3 l mn - Feed duraton t m = 40 25 mns (Dry) sand nput condtons: Feed rate nto column I s = 2.0 4.7 g mn - Feed duraton as above Mxng paddles Crcular gate Man Settlng column secton OBS_ Probe OBS_2 Probe Gate openng Rectangular vewng tank CCD Camera () (2) (3) (4) (5) (6) (7) (8) Buffer mxng tank Oscllatng grds Floc Measurement Secton Clear water chamber Floc vewng chamber (a)
Expermental Measurements: Floc charactersaton In-stu floc measurements n laserllumnated vewng chamber (a) (b) ( Images recorded by 3.3X macro CCD camera (2MP pxel 3.78μm) ImageJ software to dentfy geometrc propertes of ndvdual flocs: Nose removal flters and ntensty thresholds appled (a) to raw floc mages (b) Equvalent floc dameter D f : (b) 500 m (c) (c) D 2 2 f A f A f = measured floc surface area (c) Mcrofloc (D f < 50 m) and macrofloc 500 m (D f 50 m) classfcatons defned 00 m 00 m
TSS (g l - ) Floc sze D f (m) TSS (g l - ) Floc Sze D f (m) Expermental Measurements: Temporal development of floc szes Maxmal (D f95 ; D f90 ) and root-mean-square (D frms ) floc szes 2.8.6.4 TSS (md) TSS (bot) Df95 Df90 DfRMS Kaoln clay runs (b) 200 80 60 40 2.8.6.4 TSS (md) TSS (bot) Df95 Df 90 DfRMS Sand-clay runs (a) 200 80 60 40.2 20.2 20 00 00 0.8 80 0.8 80 0.6 60 0.6 60 0.4 40 0.4 40 0.2 20 0.2 20 0 0 0 50 00 50 200 250 300 350 400 Tme (mn) 0 0 0 50 00 50 200 250 300 350 400 Tme (mn)
Maxmal Floc Sze D f95 (m) Floc Sze D f90 (m) Floc Sze D frms (mm) Expermental Measurements: Analyss of equlbrum floc szes 200 80 60 40 20 00 80 60 40 20 0 Lagrangan framework for mud flocculaton by Wnterwerp (2002): dd Under equlbrum condtons: dd f /dt = 0 equlbrum floc sze D fe can be obtaned: Expermental data shows mproved relatonshp wth D fe (C/G) /2 TN-9 (Clay-only) dt TNS-6 (Sand-clay) f k n D f95 = 497.29(C b /G) /2 R² = 0.9502 (a) 0 0. 0.2 0.3 0.4 0.5 (C b /G) /2 A f CGD Floc aggregaton term 200 80 60 40 20 00 80 60 40 20 0 k p 2q D D D 4n f B q f G f p f n f Floc break-up term D f90 = 458.94(C b /G) /2 R² = 0.9563 (b) 0 0. 0.2 0.3 0.4 0.5 (C b /G) /2 p =.0 q = 0.5 (emprcal) n f = 2.0 (average) k A = aggregaton coeffcent k B = floc break-up coeffcent D 200 80 60 40 20 00 80 60 40 20 0 f e k k B A C G D frms = 267.2(C b /G) /2 R² = 0.6262 0 0. 0.2 0.3 0.4 0.5 (C b /G) /2 (c)
Numercal Modellng: DV populaton balance model DV advecton-dffuson equaton for mxed (clay + sand) sedment suspensons: Settlng column dscretsed nto cells and solved by C-N mplct fnte dfference scheme Lumped populaton balance equaton (PBE) resolved at each tme step to update floc sze dstrbuton (FSD) wthn each cell: z C z z C w t C s s = sze class ndces (mud flocs or sand partcles) M M S n n S n n n n n f n n n f dt dn 2 2 2 2 2 + floc break-up terms from sand nteractons = sze class ndex (clay flocs + sand) w s = fractonal settlng veloctes s = fractonal dffuson coeffcents
DV PBE Numercal Modellng: Model parameters and assumptons All floc collsons and break-up assumed bnary Emprcal PBE model parameters: Collson effcency aggregaton probablty of two flocs and estmated by emprcal shell-core model (Kusters 99) Collson frequency perknetc (Brownan moton) + orthoknetc (turbulent shear & dfferental settlng) nteractons Allocaton factor f fracton of newly-formed flocs allocated to each sze class to mantan mass balance n PBE Floc breakage coeffcent = ½ larger aggregates break-up nto two equal-szed flocs (.e. bnary breakage model) Fragmentaton rate coeffcent S defned by establshed sememprcal expresson (Kusters 99)
DV PBE Numercal Modellng: Temporal varaton n concentraton Measured and predcted TSS concentratons at OBS (cell k = 5) and OBS 2 (cell k = 30) over run duraton: Temporal lag at OBS 2 replcated qualtatvely by DV model Equlbrum condtons (.e. OBS 2 OBS ) also replcated by model at later elapsed tmes Model dscrepances due manly to constant dffuson coeffcent specfed n DV advecton-dffuson equaton
DV PBE Numercal Modellng: Temporal varaton n floc szes Clay-only suspensons: temporal development of maxmal (D f95 ) and root-mean-square (D frms ) floc szes (cell k = 30): Floc szes and aggregaton rates under-predcted earler n runs Floc sze boundary condton (D fn = D p at cell k = ) In realty some flocculaton wll occur wthn buffer tank (D fn >> D p ) Equlbrum D f95 and D frms floc szes well-predcted later n runs
DV PBE Numercal Modellng: Temporal varaton n floc szes Sand-clay suspensons: bnary floc breakage model (.e. = ½) assumed for floc collsons wth sand partcles: Appled to macrofloc (D 50 m) sze classes only Emprcal floc fragmentaton coeffcent based on collson effcency and frequency : S Sand-clay collsons lmt equlbrum floc sze (D f95 < 50 m) n = ndex for sand partcles Clay-only run Sand-clay run
Conclusons Combned expermental and numercal study nvestgated flocculaton behavour of clay-only and sand-clay sedment suspensons Temporal varaton n measured floc szes (D f95 ; D f90 ; D frms ) ndcated ntal aggregaton rates and equlbrum floc szes controlled prmarly by grd-generated turbulent shear and suspended clay concentratons Addton of sand fracton n sand-clay runs typcally reduced both ntal aggregaton rates and equlbrum floc szes generated DV advecton-dffuson model ncorporatng populaton balance equaton (PBE) predcted successfully both concentraton tme seres n settlng column and temporal development of flocs Influence of sand fracton on flocculaton behavour ncluded n PBE as bnary floc break-up model accountng for sand partcle collsons wth clay macroflocs (D f > 50 m)
Thanks for your attenton! Reference: Cuthbertson A J S Samsam F and Dong P (208). Model studes for flocculaton of sand-clay mxtures. Coastal Engneerng 32(2) 3-32. https://do.org/0.06/.coastaleng.207..006