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On modeling boundary layer and gravity-driven fluid

mud transport

T.-J.Hsu,1P.A.Traykovski,2and G.C.Kineke3

Received19May2006;revised14November2006;accepted21November2006;published14April2007.

[1]A model for fine sediment transport processes in the fluvial and coastal environment

is proposed based on a simplified two-phase formulation.This simplified approach for

fine-sediment transport is essentially single-phased;however,it retains several critical

mechanisms originated from the complete two-phase formulation.By incorporating

closures of carrier fluid turbulence and turbulent suspension and rheology of the sediment,

the model is first tested with laboratory measurements of flow velocity and concentration

for fine-sand transport driven by steady currents.Next,particle diameter and density are

prescribed in the model according to fractal dimensions of typical flocs for fluid mud

observed on the continental shelf.The model is able to predict the dynamics of

tidal-driven lutocline behavior observed on the Amazon shelf and wave-supported

gravity-driven fluid mud transport measured at the Po prodelta.Model results also indicate

strong interplay between flow turbulence and fluid-mud concentration,suggesting that the

mechanism of sediment-induced stratification on damping the carrier fluid turbulence

is crucial in determining the fluid mud behavior.Results are encouraging for incorporation

in the future of more comprehensive descriptions on floc dynamics,mud-bed

consolidation and various mud rheology closures.

Citation:Hsu,T.-J.,P.A.Traykovski,and G.C.Kineke(2007),On modeling boundary layer and gravity-driven fluid mud transport, J.Geophys.Res.,112,C04011,doi:10.1029/2006JC003719.

1.Introduction

[2]Fine-sediment transport processes are of great impor-tance for fluvial,estuarine and coastal morphology,water quality and navigation.When fine cohesive sediments are delivered by the river and mixed with salt water in the coastal ocean,they flocculate and form aggregates.The initial deposition of terrestrial sediment from the river plume and the subsequent resuspension processes and interaction with adjacent beach sand(noncohesive)under combined tidal,wave,and current forcing are highly com-plex[e.g.,Wright and Nittrouer,1995;Bhattacharya and Giosan,2003;Geyer et al.,2004].Field observations of fluid-mud processes suggest resuspension on the continental shelf involves both boundary layer-driven and wave-supported gravity-driven sediment flows[e.g.,Wright et al.,2001;Kineke et al.,1996;Traykovski et al.,2000;Puig et al.,2004].Near the edge of the continental shelf,strong gravity-driven flow,such as turbidity currents,delivers sediment into the deep water[e.g.,Middleton,1993].For a negatively-buoyant river plume that has a high sediment-water ratio,the initial deposition may also take place through turbidity currents or the so-called hyperpyncal flow [e.g.,Mulder and Syvitski,1995].Hence,in terms of transport mechanisms,both boundary-layer shear-driven and gravity-driven sediment transport must be studied.Fluid mud is highly concentrated suspended sediment[e.g.,Ross and Mehta,1989]from concentrations of about10g/l to a few hundred g/l above a consolidated bed.On the Amazon shelf for example,fluid-mud thickness can be on the order of several meters near the salinity front and fluid-mud flow is the major mode of transport causing the growth of a sub-aqueous delta[Kineke et al.,1996]or coastal clinoform [Friedrichs and Wright,2004].

[3]Accurate prediction of fine-sediment transport requires detailed water column models that resolve time-dependent flow velocity and sediment concentration[Winterwerp and van Kesteren,2004].In general,the dynamics of sedi-ment transport is a multiphase phenomenon.A multiphase approach provides rigorously derived balance equations that incorporate fluid-sediment interactions and sediment granular rheology[e.g.,Gidaspow,1994]and hence allows modeling transport continuously from consolidating bed to dilute sus-pension.Existing water column models for mud suspension [e.g.,Li and Parchure,1998;Winterwerp,2001]incorporate the damping of flow turbulence due to sediment-induced stratification,which is a crucial mechanism for the formation of fluid mud.However,the rheology of sediment is often neglected.In order to model the concentrated region of the mud aggregate network[e.g.,Toorman,1999;Winterwerp and

JOURNAL OF GEOPHYSICAL RESEARCH,VOL.112,C04011,doi:10.1029/2006JC003719,2007 1Civil and Coastal Engineering,University of Florida,Gainesville,

Florida,USA.

2Applied Ocean Physics and Engineering,Woods Hole Oceanographic

Institution,Woods Hole,Massachusetts,USA.

3Geology and Geophysics,Boston College,Chestnut Hill,

Massachusetts,USA.

0148-0227/07/2006JC003719

van Kesteren,2004]and perhaps other important applications, such as the dissipation of wave energy on muddy coasts[e.g., Dalrymple and Liu,1978;Maa and Mehta,1987;Sheremet and Stone,2003],the rheology of sediment and the suspension must be incorporated.

[4]Recent advancements in multiphase noncohesive sed-iment transport[e.g.,Dong and Zhang,2002;Hsu et al., 2004]and physical-based description of floc dynamics [Kranenburg,1994;Winterwerp,1998]and consolidation [e.g.,Toorman,1999]provide the opportunity to develop a more complete water-column model for fine-sediment transport.The modeling framework reported herein is based on simplified two-phase equations for fluid and sediment. The two-phase approach is adopted as a starting point because boundary-layer and gravity-driven sediment trans-ports,the interaction between flow turbulence and sediment and the sediment granular rheology can be incorporated in the model.Unlike the two-phase model for noncohesive

sediment[e.g,Hsu et al.,2004],the complete two-phase formulation is simplified here in order to calculate fine-sediment processes typical of long timescales.The govern-ing equations of the proposed model are presented in section2.1.A detailed derivation of the governing equation simplified from the two-phase equations is documented in Appendix A.Closures on flow turbulence,rheology of sediment stresses and boundary conditions adopted in this paper are presented in sections2.2and2.3.The proposed model is validated with laboratory experiments[Coleman, 1986;Sumer et al.,1996]for noncohesive fine-sediment transport(section 3.1).We further demonstrate that by incorporating more complete physics on fluid-sediment interaction and sediment rheology,but without including detailed consititutive relationships for floc dynamics and consolidation,the model is already capable of capturing several essential features of fluid mud flows observed in the field,including fluid mud under tidal flows(section3.2) and wave-supported gravity-driven fluid mud transport (section3.3).Future work is summarized in section4. 2.Model Formulation

https://www.doczj.com/doc/3813901506.html,erning Equations

[5]We consider sediment of diameter,d,a density r s, transported in a bottom boundary layer that is locally uniform in the cross-shore x and alongshore y direction. According to field and laboratory observation of fluid-mud processes,the dynamics of fluid-mud transport involve a variety of physical mechanisms,including for example,the boundary-layer and gravity-driven transport[e.g.,Wright et al.,2001;Traykovski et al.,2000],the effects of sediment on carrier fluid turbulence[e.g.,Ross and Mehta,1989; Trowbridge and Kineke,1994]and the rheology due to intergranular interactions in high concentration suspension [e.g.,Maa and Mehta,1987;Winterwerp and van Kesteren, 2004].A general formulation that is capable of describing these essential mechanisms can be obtained based on two-phase theory.However,typical processes related to fluid-mud transport are of long timescales(e.g.,several tidal cycles)and the complete two-phase equations must be simplified for computational efficiency.The governing equations that we adopted here are based on a reduction procedure detailed in Appendix A.Assuming that fine sediment follows the ensemble-averaged carrier fluid velocities closely,governing equations for flow momen-tum and sediment concentration simplified from the two-phase equations are expressed in equations(A12)and (A13)(see Appendix A).Here,to study fluid-mud trans-port on the continental shelf with both cross-shore and alongshore flow,we extend(A12)and(A13)with an alongshore y component(Figure1).The flow momentum equations for cross-shelf u and alongshelf v velocities are: @u

à1

r f1àf

@t f

@t s

tg x

sà1

eTf

1àf

;

e1Tand

à1@P

1@t f yz

@t s

tg y

sà1

eTf

e2Twith r f the fluid density,s=r s/r f the sediment specific gravity and g x,g y the gravitational acceleration in the cross-shore and alongshore directions.In the momentum equations(1)and(2)the flow momentum transport is caused by both fluid and sediment stresses t xz f,t xz s.The gravitational term contains sediment concentration and allows fluid flow to be induced by sediment.The cross-shore@P/@x and alongshore@P/@y pressure gradients are given as a prescribed flow forcing of the bottom boundary layer.

[6]The sediment volume concentration f is calculated by

?à

f1àf

eTT p1àsà1

àá

g zà

n t

s c

T p

r s

@t s

:e3T

The first two terms on the right-hand-side of(3)are the settling and turbulent mixing/suspension with the particle response time T p calculated as[e.g.,Drew,1976]

T p?

r s

b D

TFigure1.Definition of coordinate system used in this paper.

with b D estimated by Stoke’s law for a sphere of diameter d settling in a fluid of viscosity v and a correction for hindered settling[Richardson and Zaki,1954]:

b D?

18r f n

d2e1àfTq

:e5T

The power q depends on the particle Reynolds number and will be given later.The turbulent mixing here is calculated using gradient transport assumption((A11)in Appendix A) with v t the eddy viscosity and s c the Schmidt number.The third term on right-hand-side of(3)is the vertical gradient of sediment intergranular normal stress,which serves as an additional suspension mechanism of sediment.Models for particle migration in fluid usually adopt phenomenological equations for concentration that are similar to(3)[e.g., Philips et al.,1992]with various constitutive relations representing shear-induced particle dispersion.According to the two-phase theory,mechanisms for shear-induced particle dispersion result from spatial gradients of sediment stresses[e.g.,Jenkins and McTigue,1990;Nott and Brady, 1994],and in highly concentrated condition,sediment stresses also represent the microscopic contact forces among particles(aggregates).Compared to the turbulent stresses, the sediment stresses are important when concentration is very large(see example,constitutive equations(15)and (16)).In this paper,we focus on mobile fluid mud transport (and dilute suspension)above the concentrated aggregate network(i.e.,f

W s?r fesà1Tg z

b D

e1àfT?

esà1Td2g z

18n

e1àfTqt1e6T

2.2.Closures

[7]Numerical solutions of(1),(2)and(3)for u,v and f are obtained by further incorporating closures on turbulent Reynolds stresses,eddy viscosity and sediment stresses. 2.2.1.Carrier Fluid Turbulent Stress and

Eddy Viscosity

[8]The carrier fluid turbulence of particle-laden flow is studied extensively through laboratory experiments[e.g., Hetsroni,1989]and direct numerical simulation[e.g., Squires and Eaton,1994].Owing to the high complexity of fluid-sediment interactions at various turbulent scales,the eddy-viscosity type approach in general does not work very well in particle-laden flow.Accurate prediction of carrier fluid turbulence,its interaction with particles and subse-quent particle dispersion rely on full3D modeling to resolve fluid-sediment interaction to sufficiently small scales.Such a3D approach at present is too time consuming for the purpose of modeling coastal fluid mud processes.Hence, the eddy viscosity approach is adopted for the preliminary development of the modeling framework.

[9]The two-phase eddy viscosity formulation based on fluid turbulence kinetic energy k and its dissipation rate has been widely used in particle-laden flow[e.g.,Elghobashi and Abou-Arab,1983].Here we adopt the kà formulation for suspended-sediment transport proposed by Hsu and Liu [2004],which has been reduced from the full two-phase kà equations consistent with the present simplified two-phase formulation.The fluid shear stress t xz f,t yz f are calculated as

t f

?r f ntn t

;t f

?r f ntn t

e7Twith the eddy viscosity v t calculated by

n t?C m

1àf

eT:e8T

The fluid turbulence kinetic energy k and its dissipation rate are solved by their balance equations reduced from the kà equations of Hsu and Liu[2004]by assuming local equilibrium

1àf

?n t

n t

@1àf

eTk

à1àf

eT àsà1

eTg z

n t

2f sk

p L

;e9Tand

1àf

?C 1

n t

@1àf

àC 2

1àf

tC 3

àsà1

eTg

n t

s c

2f sk

T ptT L

:e10T

The last two terms in(9)and(10)represent the effects of sediment(mostly damping)on carrier fluid turbulence due to sediment-density stratification[e.g.,Winterwerp,2001] and interaction between fluid and sediment velocity fluctuations through viscous drag[Gust,1976;Hsu et al., 2003].The reduction of turbulence due to density stratification is well-known in geophysical flow.On the other hand,the reduction of carrier fluid turbulence can still occur even in well-mixed fine-particulate flow without spatial concentration gradients[Drew,1976;Gust,1976]. Hence,the last term is proportional to concentration and depends on the magnitude of the particle response time T p and the turbulent eddy timescale T L,estimated by

T L?

:e11T

According to an earlier study[Hsu et al.,2003],the damping of turbulence due to viscous drag in the fluctuation field is important for relatively coarse particle(e.g.,medium to coarse sand)and the density stratification is expected to be more important for fine sediment considered here. [10]Standard values of numerical coefficients adopted from Rodi[1993]and Elghobashi and Abou-Arab[1983] are valid for dilute concentration(f<%5%):

C m?0:09;C 1?1:44;C 2?1:92;s k?1:0;

s ?1:3;C 3?1:2e12T

Squires and Eaton[1994]provided correction to the numerical coefficients under higher concentration conditions based on valuable but limited Direct Numerical Simulation (DNS)data for isotropic turbulence.These corrections become important for high sediment volume concentration. However,they are not implemented here due to limited experimental data and other uncertainties in the model and flow condition considered(e.g.,floc dynamics).

2.2.2.Sediment Stresses

[11]For fine sediment,we consider semiempirical formu-lation for sediment stress rheology based on concentrated viscous suspension.Pioneering work was first conducted by Bagnold[1954].Later,several new formulations are pro-posed based on new experimental data[e.g.,Leighton and Acrivos,1987;Philips et al.,1992;Zarraga et al.,2000] and more complete kinetic theory[e.g.,Jenkins and McTigue,1990;Nott and Brady,1994].In this paper,results are presented using sediment stress closure of Zarraga et al. [2000].Other similar closures based on concentrated vis-cous suspension[Bagnold,1954;Philips et al.,1992]have also been implemented.The predicted concentration and velocity profiles are qualitatively similar and they are not presented here.Similarly,we will study other cohesive mud rheology closures[e.g.,Toorman,1999]in the future when measured flow velocity and concentration profiles in a more well-controlled environment become available.

[12]The sediment shear stress t xz s is calculated as

t s xz ?r f n r

;t s

?r f n r

;e13T

where v r is the relative viscosity

n r?nzefT:e14TThe relative viscosity is expected to vary with concentra-tion.It is equal to the interstitial fluid viscosity v in the dilute limit(f!0)but increases rapidly with concentra-tion.Various relations for z(f)have been proposed based on laboratory experiments[e.g.,Leighton and Acrivos,1987; Philips et al.,1992;Zarraga et al.,2000].According to Zarraga et al.[2000],z(f)is calculated as

zefT?expeà2:34fT

1àf=f0

eT3

;e15T

where f0=0.62is the maximum random packing concentration for noncohesive particles.For mud flocs considered in this paper,f0is set to be the gelling concentration[e.g.,Winterwerp and van Kesteren,2004]. The shear-induced particle pressure(normal stress)is suggested to be

t s xz ?1:89r f n

1àf=f0

eT3

:e16T

2.3.Bottom Boundary Conditions

[13]In the present model,the bottom boundary is set at a fixed level close to the actual mobile bed.A thin,highly concentrated region between the present fixed bed level and the actual mobile bed is neglected.For coarse particles,a mobile bed module based on a consititutive stress relation for enduring contact and a failure criterion can be incorpo-rated to model this highly concentrated,fluid-solid like region[e.g.,Hsu et al.,2004].However,for fine sediment and especially fluid mud considered here,these consititutive relations must also describe appropriate consolidation pro-cesses.This highly concentrated region is neglected in this paper for simplicity.Consequently,the present model cal-culates the transport above the concentrated aggregate network with concentration below gelling concentration.

[14]A logarithmic velocity profile(law of the wall)is assumed close to the bed.The time-dependent bottom friction velocity u*and v*in the x and y directions are obtained from the model velocities at the first grid point D z above the bed[e.g.,Mellor,2002]:

u*?

k u D z;t

eTu t

ln30D z=K s

!1=2

;v*?

k v D z;t

eTu t

ln30D z=K s

!1=2

;e17Twith u t=

????????????????

u2*tv2*

the total bottom friction velocity.The roughness height K s parameterizes the thin region close to the bed not resolved by the model.Its value is specified as one of the model input parameters and is discussed in the following sections.The bottom stresses t bx=r f u*2and t by= r f v*2calculated by(17)serve as the bottom boundary conditions for the momentum equations(1)and(2). [15]In a turbulent boundary layer,the bottom boundary condition for turbulence kinetic energy k is often specified using bottom friction velocities obtained from(17)without explicitly considering the effect of sediment concentration. However,in the present model the sediment concentration affects the magnitude of flow turbulence(see equation(9)). Therefore,we adopt a no-flux boundary condition for k that is more consistent for sediment-laden turbulent boundary layer[e.g.,Hagatun and Eidsvik,1986]:

?0;e18TThe bottom boundary condition for turbulence dissipation rate is then calculated with a standard near-wall approximation

C3=4

k3=2

k z

;e19T

[16]A sediment flux boundary condition is adopted at the bottom boundary.The upward flux from the highly con-centrated region is approximated as a reference concentra-tion f r multiplied by the settling velocity[Harris et al., 2004].The downward flux is approximated by the conti-neous deposition concept[Sanford and Halka,1993].The reference concentration formulation of Smith and McLean [1977]is utilized here

f r?

f0g S

e20T

in which S=t b/t crà1.The total bottom stress t b=r f u t2is calculated every time step by equation(17).The critical

bottom stress t cr is site specific and resuspension coefficient g usually varies by two orders of magnitude in the literature [e.g.,Drake and Cacchione,1989].Specifically for cohesive sediment,t b and g may further depend on the depth of erosion[e.g.,Sanford and Maa,2001].Unfortu-nately,for the fluid mud problems that we shall consider next,these site specific sediment characterizations are not available.These uncertainties must be resolved for the development of a predictive model.However,in this paper we will focus on testing the new model for capturing the dynamics of lutocline and wave-supported gravity flow using field observed data.Uncertainties in t cr and g are of less concern here because the total amount of suspended mud is known from the measured data.Specifically,the critical bottom stress is set to be0.05Pa and the resuspension coefficient g is calibrated with measured concentration at the location closest to the bed.More complicated bottom boundary conditions for fine sediment that incorporate depth-of-erosion and variable critical stress [e.g.,Sanford and Maa,2001]may be utilized in the future to extend the present model toward a predictive tool.

2.4.Flow Forcing

[17]The proposed model is a time-dependent model that can be driven by arbitrary oscillatory and current forcing.The forcing implementation we adopted here is widely used for modeling wave-current boundary layer flows[e.g.,Mellor,2002]and is briefly described as follows.The flow forcing is implemented as pressure gradients in the x–and y–directions in the momentum equations(1)and(2)through lateral boundary conditions. According to the boundary layer approximation,the pressure gradients in the x–and y–directions are assumed constant across the boundary layer(i.e.,constant in the z–direction)and equal to the corresponding free-stream pressure gradients,i.e.,

@P @x ?

@P0

;

@P0

e21T

The free-stream pressure gradients are further related to free-stream velocity time series.The free-stream velocities above the boundary layer U(t)and V(t)are first separated into oscillatory(~U(t),~V(t))and mean(U c,V c)velocities, i.e.,

~U teT?U teTàU

;~V teT?V teTàV c:e22TThe oscillatory component can be used to represent a wide range of time-dependent forcing such as waves or tidal oscillations,depending on the problem of interest. [18]The free-stream pressure gradient in the x–(or y–) direction is further calculated by the acceleration of oscil-latory velocity and a constant value due to mean current:

à@P

?r f

@~U teT

tf c x;à

?r f

@~V teT

tf c ye23T

in which f x c and f y c are the forcing associated with the mean current components.

[19]Evidently,f x c and f y c are zero for pure oscillatory forcing.On the other hand,when mean current forcing is considered,the precise values of f x c and f y c that will result in the desired magnitudes of mean flow rates(or mean velocities U c,V c at free-stream)are not known a priori. The relation between the given mean current forcing f x c (or f y c)and the resulting(net)flow rate is implicitly a complex function of wave-current interaction and the effects of sediment on the carrier flow,and is part of the solution of the model results.In general,an iteration procedure is required to obtain the precise values of f x c and f y c to match the desired flow rates.

3.Results

3.1.Model Calibration With Laboratory Experiments [20]Equations(1)–(3)along with the kà turbulence closure,rheology closure and boundary conditions are solved numerically to predict fine sediment transport.The present model has several coefficients.Standard values of some of these coefficients are adopted and indicated in the previous sections.The Schmidt number for sediment turbu-lent suspension s c(see equation(3))is calibrated here with laboratory data for sediment transport in steady flow.Due to the gradient transport assumption utilized in equation(A11), the Schmidt number parameterizes small-scale advection of sediment by turbulent eddies.In the present kà equation, the Schmidt number also affects the magnitude of the damping term due to sediment density stratification. [21]Coleman[1986]conducted a series of laboratory flume experiments for sediment(sand of diameter0.105mm and specific gravity2.65)transport under unidirectional (x-direction)steady current.In each test run,an artificial smooth bed is utilized for a given flow rate and sediment is added from the upstream end of the test section until the total sediment capacity is reached.One advantage of this set of experiments is that the bed is smooth and hence the uncertainties in bed roughness K s is excluded and we utilize a logarithmic law for a smooth wall to calculate bed friction velocity u*:

u t;D z

9u t;D z

eTD z

e24T

[22]The model results are presented here for case20of Coleman[1986],the case with the highest flow rate and concentration.The numerical model is initialized with zero flow velocity and concentration.A constant pressure gradi-ent f x c is applied to drive the model and the model calculation marches in time until a steady-state solution is obtained with the calculated total flow rate matching the measured data.The power q in equation(5)due to hindered settling is taking to be3.0and is tested to be relatively insensitive to model results in the present dilute https://www.doczj.com/doc/3813901506.html,ing s c=0.5,the predicted flow velocity(solid curve in Figure 2a)and concentration(solid curve in Figure2b)agree well with the measured data.To illustrate the effect of sediment on fluid flow,the dashed curve in Figure2a represents the calculated velocity profile without sediment(but with the same flow rate).In addition,the calculated flow velocity is replotted in Figure2c according to normalized velocity defect[Winterwerp,2001]to emphasize the effect of sed-

iment on near bed flow velocity.Clearly,the present model captures the effect of sediment on carrier fluid https://www.doczj.com/doc/3813901506.html,ing s c =0.3,the calculated flow velocity agrees better with the measured data near the bed.However,the overall suspended sediment concentration is over-predicted (not shown).In the following sections,s c =0.5is used.According to numerical experiments,the modification of flow velocity by the sediment in this case is mainly due to the effect of sediment on modifying the carrier flow turbulence through the density stratification term in the k à equation,consistent with earlier findings [e.g.,Winterwerp ,2001].The effects of sediment stress in the momentum equation is of less importance here due to relatively dilute flow condition.It

is worth mentioning that the forcing f x c required to establish the desired flow rate in case 20is 6.45Pa/m (sediment-laden condition,solid curve in Figure 2a).However,to establish the same flow rate for clear fluid flow condition requires f x c =8.57Pa/m (dashed curve Figure 2a),which is about 30%more.This is the so-called ‘‘drag reduction,’’i.e.,the presence of sediment reduces the flow turbulence (mostly through density stratification in this case),enhances the mean flow field and hence less forcing is required to establish the same flow rate.

[23]Sumer et al.[1996]conducted a series of sediment transport experiments (sand of diameter d =0.13mm)in steady channel flow over a realistic sand bed with a

smooth

Figure 2.Model-data comparison with Coleman [1986](case 20).(a)Flow velocity and (b)sediment concentration with symbols represent measured data,and solid curves represent model results with s c =0.5.(c)Further plots the velocities in defect-law with additional model results using s c =0.3(dotted curve).Model results without sediment (clear fluid flow with the same flow rate)are also shown in dashed curves of both Figures 2a and 2c to emphasize the effect of sediment on fluid flow.Sand is of diameter d =0.105mm.z m is 17

cm.

Figure 3.Sediment concentration (b)calculated by the model agrees with data (symbol)measured by Sumer et al.[1996](Shields parameter 1.1).(a)Velocity profile calculated by the model.Sand is of diameter d =0.13mm.q is taken to be 3.0.

wall covering the top of the channel to avoid surface waves. In the numerical model simulation,the flow is driven by a constant pressure gradient to match the measured flow rate.

A roughness height of K s=6d,suggested by Sumer et al. [1996],is utilized in the numerical model.The model predicts the concentration profile reasonably well when compared with measured data(Figure3b).

3.2.Fluid Mud Dynamics

[24]When modeling noncohesive sediment,it is straight-forward to prescribe the(mean)diameter and density of the particle as demonstrated in section 3.1.However,one challenge in modeling cohesive sediments is that they are often transported as aggregates with their sizes and densities constantly changing.When modeling fluid mud using the present model,the primary particle is not directly calculated. Instead,we prescribe aggregate(floc)diameter d and fractal dimension n f[e.g.,Kranenburg,1994;Hill et al.,2001]. Hence,the density of the mud flocs r m is give as

r m?r ft

3àn f

r sàr f

àá

e25T

where d0and r s are the diameter and density of the primary particle taken to be d0=3m m and r s/r f=2.65in this paper. Hence,commonly used fluid-mud mass concentration is calculated as c=r m f with f solved by equation(3).In the following section for fluid mud,we will also define

mud Figure4.Model results for flow velocity(left panels)and floc concentration(middle panels with d=

60m m,s=1.13,n f=2.15)driven by a tidal forcing.The predicted concentration during the initial(t1), middle(t2)and final(t3)stages approaching flood tide are similar to those observed(right panels)on the Amazon Shelf near the river mouth(circles)and open shelf(crosses)when thick fluid mud present [Kineke et al.,1996].To qualitatively compare the shape of concentration profiles,the concentration c

and vertical coordinate z are normalized by c b and h,respectively.h is set to be6m,approximately

1.2times of the maximum lutocline thickness.c b is set to be the bed concentration at the corresponding phase.U m is1.5m/s.

floc specific gravity as s =r m /r f .According to Winterwerp and van Kesteren [2004],the gelling concentration required in (15)and (20)is then given as

f 0?

r s

d 0d

àá3àn f

r m

:e26T

More detailed dynamics of floc aggregation and breakup [e.g.,Winterwerp ,1998]process (i.e.,floc diameter changes with flow condition and sediment concentration)are neglected in this paper.

[25]In the following sections for fluid mud processes,a roughness height of K s =3mm is specified in all the cases for simplicity.Numerical experiments suggest that changing the values of roughness by a factor of five does not change the model results qualitatively.A detailed quantitative model-data comparison for fluid mud is not the aim here due to too many uncertainties.For instance,the effect of reduced roughness height can be easily compensated by an enhanced resuspension coefficient g in (20)if the goal is to match the magnitude of fluid-mud concentration.However,

the shape of the concentration profile is insensitive to these uncertainties.

3.2.1.Fluid Mud Dynamics Under Tidal Forcing

[26]The model is utilized to calculate concentrated fluid-mud dynamics observed during AMASSEDS [e.g.,Nittrouer et al.,1991]and qualitatively compared with measured data near the river mouth and open shelf anchor stations [Kineke et al.,1996].The model is driven by a prescribed sinusoidal forcing with maximum tidal velocity 1.5m/s and period of 12hr to represent the tidal forcing (upper panel in Figure 4).The floc is of diameter d =60m m ,density r m =1130kg /m 3(i.e.,n f =2.15in (25)).The model calculated shape of the sediment concentration profiles resemble that observed on the Amazon shelf at similar tidal phases (Figure 4,(t1),(t2)and (t3)).Based on numerical experiments,the existence of a lutocline and fluid mud behavior is mostly determined by the density stratification term in the k à equations,consis-tent with earlier studies [e.g.,Trowbridge and Kineke ,1994;Winterwerp ,2001].

[27]Figure 5further illustrates the strong interplay be-tween time-dependent concentration (second panel)and turbulent intensity (third panel).When the tidal forcing

first

Figure 5.Time-dependent floc concentration (second panel)and turbulent intensity (third panel)under the same tidal forcing (first panel)presented in Figure 4.The lowest panel (a)–(d)shows four snapshots (timing of each snapshot is shown in the first panel)of fluid turbulent Reynolds stress (solid-black)and sediment shear stress (dashed-red).The dashed blue curve in the first panel represents 2.5B .

starts to increase from (a)to (b)(see the 1st panel),turbulence becomes stronger and the available sediment is suspended higher and the averaged concentration below the lutocline is smaller.Further increases of forcing from (b)to (c)suspends slightly more sediment from the bed (buoyancy anomaly B defined in equation (27),which represents depth-integrated concentration increases by about 4percent)which causes a collapse of turbulence (3rd panel)and highly-concentrated sediment confined below the lutocline (c)(2nd panel).Later the tidal flow becomes even stronger (d),boundary-layer turbulence increases dramatically and sediment is suspended much higher in the water column.Sediment shear stress (or equivalently a mud viscosity)is only important (as compared to Reynolds stress)when turbulence is damped by the existence of high sediment concentration ((a)and (c)in the lowest panel).Following Trowbridge and Kineke [1994],the buoyancy anomaly is defined as

B ?s à1eTg

0f dz :e27T

The buoyancy anomaly on the one hand represents the total amount of suspended sediment in the water column.On the

other hand,the square root of B represent a velocity scale that characterizes a critical velocity for a fully turbulent suspension.In Trowbridge and Kineke [1994],the critical velocity is determined to be 2???

B p based on a simpler model than the present formulation.In Figure 5a,the blue-dashed curves represents the model results for 2.5???B p .Overall,???B p does not change much (about 10–20cm/s)as compared with tidal velocity amplitude,suggesting that the total amount of suspended sediment is more or less constant over the tidal cycle.The fluid mud is simply redistributed throughout the water column depending on the overall height of the lutocline.However,the lutocline behavior is controlled by the interplay between the flow turbulence and sediment (which damps the flow turbulence).In addition,the small settling velocity of fluid mud prevents the fluid mud to settle quickly (and consolidate)into the bed when the turbulence collapses and concentrated fluid mud remains confined near the bed.Clearly,the present model suggests that when tidal velocity increases beyond about 2.5???B p ,fully turbulent suspension occurs,which is similar to that predicted by Trowbridge and Kineke [1994].3.2.2.Wave-Supported Gravity-Driven Fluid Mud [28]Wave-supported gravity-driven fluid mud flows have been measured on several continental shelves (e.g.,see

Figure 6.Time-averaged model results (high concentration event burst #5[Traykovski et al.,2007])driven by (a)field measured flow velocities at 75cmab (thin-solid and dashed represent x-and y-directions).(b)Measured floc concentration (dashed)is predicted well by the model (solid curve,d =60m m ,s =1.2,n f =2.3).(c)Both model results (solid curve)and measured velocities (circles)suggest wave-supported gravity-driven mud flow in the cross-shelf direction,but not in the alongshore direction (dashed curve:model,crosses:measured).Dashed curves in Figures 6c and 6d represent measured profiles but are in fact interpolated from two discretely measured locations at 75cmab and 11cmab.The model predicts a larger maximum downslope velocity at 5cmab.No measured data are available at this location.Hence,(d)the model predicts a stronger downslope sediment flux than interpolated values from measured data at 11cmab.The dashed blue curve in Figure 6a represents 2.5B .

review by Wright et al.[2001]).Here,new data measured at the Po prodelta [Traykovski et al.,2007]are examined in light of the new model.The cross-shore slope at the Po prodelta is rather mild and is set to be a =0.002[Traykovski et al.,2007].The definition of cross-shore and alongshore coordinate system is depicted in Figure 1.The numerical model is driven by measured near-bed (75cm above the bed,75cmab)cross-shore (x)and alongshore (y)velocities (e.g.,Figure 6a).The measured velocity time series (2Hz,520sec in length)are first separated into oscillatory (wave)and mean components described in equation (22).The oscillatory components are directly used to drive the model while f x c and f y c associated with mean current forcing are applied concurrently to match the desired mean current ve-locities measured at 75cmab.Fine grid size D z =2.5mm near the bed is adopted.Hence,the numerical model resolves

both the wave phase and the wave boundary layer processes (about 10to 20cm in thickness)near the bed.

[29]For a high concentration event (burst #5),the mea-sured r.m.s.wave forcing velocity at 75cmab is 51cm/s (Figure 6a)with a relatively weak alongshore current (à5cm/s)and highly-concentrated fluid mud with near-bed concentration of about 150g/l (dashed in Figure 6b).In order to match the overall magnitude of the measured concentration,the resuspension coefficient in (20)is set to be g =0.045.Model results for time-averaged concentra-tion (averaged over the entire wave group of 520s)indicates that due to relatively weak currents and the damping effect of concentrated fluid mud on flow turbu-lence,sediment is mostly confined within the wave bound-ary layer (Figure 6b)and the lutocline is within $10cmab.More importantly,the calculated cross-shore flow

velocity

Figure 7.Time-averaged model results for burst #9of high concentration event [Traykovski et al.,2007].The floc properties used in the model are the same with that in #5.(a)Field measured flow velocities at 75cmab (r.m.s.wave forcing 52cm/s).(b)Time-averaged floc concentration (modeled:solid curve;measured:dashed curve).(c)Cross-shore velocity,and (d)cross-shore sediment flux profiles (modeled:solid curve;measured with interpolation:dashed curve).(e)Time-averaged alongshore velocity and (f)alongshore sediment flux profiles.

(Figure 6c,solid curve)shows gravity-flow characteris-tics that matches measured data at 11cmab (circle).Accord-ing to Figure 6c,the model predicts a larger maximum downslope velocity (solid curve)than the logarithmically interpolated data (dashed curve).Model results for time-averaged alongshore flow velocity shows a logarithmic profile (dashed curve)without a gravity-flow feature,which is also consistent with the measured data (crosses).Model results also suggest that the buoyancy anomaly B over the entire wave group event does not change much (not shown),suggesting that the commonly used assumption for a buoy-ancy anomaly that is constant over the individual wave period or wave timescale to parameterize wave-supported gravity flow is appropriate [e.g.,Wright et al.,2001].

[30]Figure 7presents another high concentration case (burst #9),where the magnitude of measured r.m.s.wave velocity (52cm/s)and alongshore current velocity (7cm/s)are both similar to those in burst #5.However,in this case the variation of the wave-velocity amplitude within the wave group is more uniform (Figure 7a).Measured fluid-mud concentration in this case is smaller than that in burst #5with a maximum near bed concentration of about 60g/l (Figure 7b),possibly limited by the total amount of available soft mud.Hence,a resuspension coefficient of g =0.007is used in the model.The model predicts a time-averaged concentration profile that is more uniformly distributed throughout the region below the lutocline as compared to the measured data (Figure 7b).The downslope

gravity flow is predicted well by the model (Figure 7c).Moreover,the predicted alongshore velocity profile close to the bed is almost zero (in fact,slightly negative,see Figure 7e).This feature is not directly measured in the field observations.Clearly,further measurements that resolve velocity structure in the concentrated region of fluid mud are highly desirable.

[31]One of the major factors controlling the dynamics of fluid mud is the wave energy.According to field observa-tion when the wave energy is low,a high-concentration fluid-mud event cannot persist and downslope gravity flow is not observed [e.g.,Traykovski et al.,2000,2007].Our numerical experiments also indicate that when artificially reducing the magnitude of wave forcing to 20%for high concentration burst #5(r.m.s.velocity reduced to 11cm/s),time-averaged sediment concentration within the wave boundary layer reduces significantly and the subsequent downslope gravity flow stops.This is consistent with analysis of field observations that the shelf slope is too mild for auto-suspension [e.g.,Middleton ,1993]typical of turbidity currents.

[32]The numerical model is further used to calculate a typical dilute suspension event (burst #16)observed at Po prodelta (Figure 8).The r.m.s.wave velocity measured at 75cmab is only 18cm/s (as compare to 50cm/s for the gravity flow cases)with a stronger along-shelf current of à23cm/s (red curve in Figure 8a).Both the observed concentration and model results (Figure 8b)suggest

that

Figure 8.Time-averaged model results (dilute event burst #16[Traykovski et al.,2007])driven by (a)field measured flow velocities at 75cmab (solid and dashed curves represent x-and y-directions).(b)Measured floc concentration (dots)is predicted well by the model (solid curve,d =60m m ,s =1.498,n f =2.4).(c)The predicted velocity profiles in both cross-shelf and along-shore directions are of logarithmic shape.Symbols are measured data at 75cmab.No gravity flow features are observed in the cross-shelf flow.(d)The model predicts a strong along-shelf sediment flux.

dilute sediment is suspended much higher above the wave boundary layer and a near-bed lutocline is not observed. Notice that due to the sharp changes of concentration near the bed,the acoustic instrument cannot accurately determine the mud bed and the mobile sediment.Hence,measured concentration at the lowest3cm near the bed is not reliable (dots with light color).In the cross-shelf direction(with Po shelf slope a=0.002),the model predicts a logarithmic shape of velocity profile due to weak cross-shelf current without gravity-flow features(Figure8c).For a relatively dilute suspension condition considered here at the Po prodelta,the major transport is in the along-shelf direction due to strong along-shelf currents(Figure8d).

[33]In summary,the proposed model captures the essen-tial features of wave-supported gravity-driven mud flow observed at the Po prodelta.Two major mechanisms are responsible for the dynamics of wave-supported gravity-driven mud flow.The downslope gravitational term in the momentum equations is certainly the driving force of the gravity flow.However,the effects of sediment on damping the flow turbulence must be considered otherwise sediment can not be confined within the thin lutocline to enhance the magnitude of the downslope gravitational force.

4.Concluding Remarks

[34]The model based on simplified two-phase formula-tion is able to capture at least qualitatively the dynamics of tidal-driven lutocline behavior on the Amazon shelf and wave-supported gravity-driven fluid mud transport at the Po prodelta.Model results suggest that the effect of sediment-induced stratification on damping the carrier fluid turbu-lence plays a major role on the fluid mud dynamics, consistent with earlier studies[e.g.,Trowbridge and Kineke, 1994;Winterwerp,2001].The existence of downslope gravity flow depends on the intensity of wave energy and the availability of soft mud[Traykovski et al.,2007].The present model can be driven by various wave and current forcing and predicts flow characteristics for both high and dilute concentration events that are consistent with observa-tions.However,the availability of mud from the bed is not explicitly modeled here and deserves future work.Further quantitative model-data comparison and model calibration also require more detailed measured data.Future work will focus on implementing detailed dynamics on mud-bed con-solidation and various mud rheology closures.The floc aggregate and breakup processes may be considered by incorporating additional constitutive relation for floc size [e.g.,Winterwerp,1998].The small-scale model proposed here eventually can be used to study improved parameter-izations of detailed near-bed sediment dynamics required by large-scale coastal models[Harris et al.,2004,2005]. Appendix A

[35]The two-phase equations for carrier fluid and dis-persed sediment particles provides a complete framework for particulate transport under various forcing conditions and transport mechanisms[e.g.,Gidaspow,1994;Nott and Brady,1994;Hsu et al.,2004;Pasini and Jenkins,2005]. However,typical fine sediment transport processes are of much longer timescale ranging from hours to several tidal cycles.Hence,the complete two-phase equations are sim-plified here for computational efficiency.The general two-phase equations for boundary layer sediment transport consist of continuity equations for fluid and sediment [e.g.,Hsu et al.,2004]

r f

@1à f

àá

@1à f

àá

w f

?0;eA1T

and

r s

@ f

@ f w s

?0eA2T

where z denotes the direction normal to the bed, f is the sediment volume concentration, w f, w s are the fluid and sediment velocities in z direction and r f,r s the fluid and sediment densities,respectively.In the dominant flow (x)direction,the momentum equations for fluid and sediment phases are written as

r f

@1à f

àá

u f

?à1à f

àá@ P f

@t f

tr f1à f

àá

g x

à f

r s

T p

u fà u s

àá

r s

T p

;eA3Tand

r s

@ f u s

?à f

@ P f

@t s

tr s f g x

t f

r s

T p

u fà u s

àá

r s

T p

f u f0:eA4T

Similarly,the momentum equations in the z-direction for fluid and sediment phases are

r f

@1à f

àá

w f

?à1à f

àá@ P f

@t f

tr f1à f

àá

g z

à f

r s

T p

w fà w s

àá

r s

T p

f w f0;eA5Tand

r s

@ f w s

?à f

@ P f

@t s

tr s f g z

t f

r s

T p

w fà w s

àá

r s

T p

f w f0:eA6T

In equations(A3)to(A6), P f is the fluid pressure,g x and g z are the gravitationaly acceleration in the x and z direction, t zx f and t zz f are the fluid shear and normal stresses,includ-ing viscous and turbulent components and t zx s and t zz s are the sediment intergranular stresses[e.g.,Bagnold,1954]. The terms in the second row of equations(A3)to(A6) account for interphase momentum exchange,modeled as drag force here appropriate for fine particles with T p the particle response time[e.g.,Drew,1976].

[36]Because these(ensemble)averaged flow equations are obtained via a separation of scales between mean flow (e.g.,u f)and fluctuation(u f’),the drag is expressed into a

contribution that is proportional to the mean velocity difference between fluid and sediment(first term in the second row of(A3)to(A6))and the other contribution due to the interaction between the fluid velocity fluctuation and sediment concentration(second term),i.e.,the turbulent suspension.By further incorporating closures on turbulent stress,turbulent suspension and sediment stress,the two-phase formulation has been adopted to model transport of medium to coarse sediment in wave boundary layer[e.g., Dong and Zhang,2002;Hsu et al.,2004]or aeolian transport[Pasini and Jenkins,2005].

[37]For typical fine sediment transport processes in the nature,the timescale involved are often tremendous to allow solving the full two-phase equations(A1)–(A6).Here,the full two-phase equations are further simplified(see Nott and Brady[1994]for a similar derivation).Because fine sedi-ment(diameter d%<100m m)has very small particle response time(%<0.001sec)compared with typical timescale of forcing(e.g.,waves,tides),in terms of the ensemble-averaged velocity,the sediment is expected to follow the fluid velocity closely and the fluid-sediment flow may be well described by a single mean flow velocity(i.e., one momentum equation represents the flow).Hence,we neglect the acceleration terms(left-hand-side)of the sedi-ment momentum equations for fine sediment of small T p. Substituting the reduced sediment x-momentum equation into fluid x-momentum equation(A3),we obtain:

@ u f @t ?

à1

r f1à f

àá@

P f

r f1à f

àá@t f xz

@t s

tg x

sà1

eT f

1à f

;

eA7T

with s=r s/r f the sediment specific gravity,g x the gravitational acceleration in the x direction and t xz f,t xz s the fluid and sediment stresses.The horizontal pressure gradient@P/@x is given as a prescribed flow forcing of the bottom boundary layer.A similar substitution of the reduced sediment z-momentum equation into the sediment con-tinuity equation(A2)gives an advection-diffusion equation for concentration f:

@ f

T p@t s

zzt f T p r s g

@ P f

?0:eA8T

Near the bed,equation(A8)can be further simplified by adopting boundary layer approximation to the first-order [e.g.,Trowbridge and Madsen,1984].The vertical(z)fluid momentum equation(A5)is thus reduced to give an explicit relation for vertical pressure gradient:

@P f @z ?r f1àf

eTg ztr s f g zeA9T

and the fluid continuity equation(A1)is readily satisfied (i.e., w f=0).Substituting(A9)into(A8),we obtain

@ f @t ?à

f1à f

àá

T p1àsà1

àá

g zt0t

T p

r s

@t s

;eA10T

[38]When the turbulent eddy viscosity v t is adopted in

this study to calculate fluid turbulent stress(section2.2.1),

the gradient transport assumption is used to calculate

turbulent suspension:

f w f0?à

n t

s c

@ f

eA11T

with s c the Schmidt number.In the following,the overbar

that represents ensemble-averaged quantity and the super-

script f for velocity and pressure are dropped for simplicity.

Substituting(A11)into(A7)and(A10),in the present1D

water column model the flow velocity u is calculated by the

momentum equation

à1@P

1@t f

xzt@t

tg x

sà1

eTf

;

eA12T

and the solution of sediment concentration f is calculated

?à

f1àf

eTT p1àsà1

àá

g zà

n t

s c

T p

r s

@t s

eA13T

[39]In summary,a simplified formulation is derived from

the two-phase flow formulation in order to provide a

middle-ground approach appropriate for fine sediment

transport.The new formulation,though looks simple,still

improves upon the conventional single-phase formulation in

several aspects that allows calculating concentrated sedi-

ment transport.Firstly,the new formulation incorporates

rheological terms in both the momentum and sediment

equations.Secondly,terms related to gravity in the original

two-phase equations are reduced to the downslope gravita-

tional term in the momentum equations allowing calculation

of gravity-driven sediment flows.Finally,the effects of

sediment on damping the flow turbulence are preserved in

the balance equations of turbulence kinetic energy and

turbulent dissipation rate(see equations(9)and(10)).

Mechanisms related to interactions between flow turbulence

and sediment are critical to the overall modeling of sedi-

ment dynamics.

[40]Acknowledgments.This research is supported by the Office of

Naval Research(N00014-05-1-0082),the National Science Foundation

(CTS-0426811)and the WHOI Penzance support for Assistant Scientist.

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àààààààààààààààààààààà

T.-J.Hsu,Civil and Coastal Engineering,University of Florida, Gainesville,FL32611,USA.(thsu@https://www.doczj.com/doc/3813901506.html,)

G.C.Kineke,Geology and Geophysics,Boston College,Chestnut Hill, MA02467,USA.

P.A.Traykovski,Applied Ocean Physics and Engineering,Woods Hole Oceanographic Institution,Woods Hole,MA02540,USA.

船舶原理

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船舶原理及结构课程教学大纲

文档来源为:从网络收集整理.word版本可编辑.欢迎下载支持. 《船舶原理与结构》课程教学大纲一、课程基本信息 1、课程代码：NA325 2、课程名称（中/英文）：船舶原理与结构/Principles of Naval Architecture and Structures 3、学时/学分：60/3.5 4、先修课程：《高等数学》《大学物理》《理论力学》 5、面向对象：轮机工程、交通运输工程 6、开课院（系）、教研室：船舶海洋与建筑工程学院船舶与海洋工程系 7、教材、教学参考书：《船舶原理》，刘红编，上海交通大学出版社，2009.11。《船舶原理》（上、下册），盛振邦、刘应中主编，上海交通大学出版社，2003、2004。《船舶原理与结构》，陈雪深、裘泳铭、张永编，上海交通大学出版社，1990.6。《船舶原理》，蒋维清等著，大连海事大学出版社，1998.8。相关法规和船级社入级规范。二、课程性质和任务《船舶原理与结构》是轮机工程和交通运输工程专业的一门必修课。它的主要任务是通过讲课、作业和实验环节，使学生掌握船舶静力学、船舶阻力、船舶推进、船舶操纵性与耐波性和船体结构的基本概念、基本原理、基本计算方法，培养学生分析、解决问题的基本能力，为今后从事工程技术和航运管理工作，打下基础。本课程各教学环节对人才培养目标的贡献见下表。

三、教学内容和基本要求课程教学内容共54学时，对不同的教学内容，其要求如下。 1、船舶类型了解民用船舶、军用舰船、高速舰船的种类、用途和特征。 2、船体几何要素了解船舶外形和船体型线力的一般特征，掌握船体主尺度、尺度比和船型系数。 3、船舶浮性掌握船舶的平衡条件、船舶浮态的概念；掌握船舶重量、重心位置、排水量和浮心位置的计算方法；掌握近似数值计算方法—梯形法和辛普森法。 2

2020年研究生入学考试考纲

武汉理工大学交通学院2020年研究生入学考试大纲 2020年研究生入学考试考纲《船舶流体力学》考试说明一、考试目的掌握船舶流体力学相关知识是研究船舶水动力学问题的基础。本门考试的目的是考察考生掌握船舶流体力学相关知识的水平，以保证被录取者掌握必要的基础知识，为从事相关领域的研究工作打下基础。考试对象：2020年报考武汉理工大学交通学院船舶与海洋工程船舶性能方向学术型和专业型研究生的考生。二、考试要点（1）流体的基本性质和研究方法连续介质概念；流体的基本属性；作用在流体上的力的特点和表述方法。（2）流体静力学作用在流体上的力；流体静压强及特性；压力体的概念，及静止流体对壁面作用力计算。（3）流体运动学研究流体运动的两种方法；流体流动的分类；流线、流管等基本概念。（4）流体动力学动量定理；伯努利方程及应用。（5）船舶静力学船型系数；浮性；稳性分类；移动物体和液舱内自由液面对船舶稳性的影响；初稳性高计算。（6）船舶快速性边界层概念；船舶阻力分类；尺度效应，及船模阻力换算为实船阻力；方尾和球鼻艏对阻力的影响；伴流和推力减额的概念；空泡现象对螺旋桨性能的影响；浅水对船舶性能的影响。三、考试形式与试卷结构 1. 答卷方式：闭卷，笔试。 2. 答题时间：180分钟。 3. 试卷分数：总分为150分。 4. 题型：填空题（20×1分=20分）；名词解释（10×3分=30分）；简述题（4×10分=40分）；计算题（4×15分=60分）。四、参考书目 1. 熊鳌魁等编著，《流体力学》，科学出版社，2016。 2. 盛振邦、刘应中，《船舶原理》（上、下册）中的船舶静力学、船舶阻力、船舶推进部分，上海交通大学出版社，2003。 1

教师基本功训练计划

小学教师基本功训练计划为了加快教育发展，全面提高教师政治业务素质，更好的实施新课程改革，全面推行素质教育，培养发展型人才，多年来我校一直注重提高教师的基本功，本学年继续有效的开展教师基本功训练工作，特制定如下训练计划：一、指导思想与目标要求教师基本功是教师从事教学工作必须具备的最根本的职业技能。为深入贯彻落实学校教育教学工作意见，以提高教师岗位实际能力为目的，牢固练就扎实的基本功。使每位教师都能练就一笔好字；说一口流利的普通话；独立设计一个完整的教学案例；制作一个合格的多媒体课件；上好一堂学生满意的课；写出一篇内容丰富的教学论文。要通过开展教师基本功训练的一系列活动，在全体教职工中，牢固树立“以质兴教”的教育质量年意识。同时，学校将加强领导，制定措施，层层落实，使人人参与，练有所得，练以致用，持之以恒，提高教师整体素质，为提高教学质量打好基础。二、基本功训练的原则： 1、在训练内容上，坚持注重实际，讲求实效，从课堂教学直观行为及“三字一话一机”同时入手，进行全面培训。 2、在训练形式上，坚持以岗位练兵为主，自学为主，业务训练为主的原则，采取集中辅导与个人自学相结合，培训学习与实践锻炼相结合，定期开展各种比赛活动，以赛促练。规划达标时限，限期进行达标。 3、在工作组织上，坚持自练、教研、比赛三位一体的原则。 4、在评价验收上，坚持评比检查和教师量化管理相结合的原则。三、教师基本功训练内容有以下三方面：根据上级要求，结合我校实际情况，我们将利用有限时间组织教师完成以下方面的训练：1、普通话方面：能熟练掌握汉语拼音，用普通话进行教学，普通话一般应达到国家语委制定的《普通话水平测试》二级水平；在公众场合即席讲话，用词准确，条理清楚，节奏适宜。我们要求每位教师都要在校内用普通话对话。 2、写字方面：能正确运用粉笔、钢笔、毛笔按照汉字的笔画，笔顺和间架结构，书写规范的正楷体字，并具有一定的速度。要求每位教师每周书写钢笔字16开纸字帖两张，毛笔字50个，在教学板书中练习粉笔字。 3、学习现代化教育技术方面：能熟练操作电脑，制作与教学内容相符的多媒体课件，能运用多媒体进行教学。 4、教学设计、教学论文、课堂教学方面：要求教师按照课程改革标准，随平时的教学活动认真改进，达到要求。四、教师基本功训练的保障措施及要求： 1、切实提高在职教师对基本功训练意义的认识。抓住教师基本功技能训练的关键是提高教师对这项工作重要意义的认识，要组织教师认真学习，研究讨论、统一思想，明确要求，形成共识，将教师基本功训练要求转化为自觉行动，要落实目标责任制，校长、主任分级管理，分工负责，层层发动，真正使教师基本功训练做到人人重视，成为每个人的实际行动。 2、坚持把师德教育放在训练工作的首位，教师基本功训练主要是针对教师业务素质的培训，但师德教育是搞好训练的重要前提和保证。学校要开展系统的，有针对性的师德培训活动和师德教育活动，通过加强师德建设为技能训练提供强大动力。保证基本功训练达到预期效果。 3、集中培训与自觉训练相结合，讲求实效。教师“三字一话一机”实施先集中培训后自学训练的方式，要取得实效，必须打破形式主义，依靠教师的自觉行为，因此，既要统一组织全体教师参加培训学习，又要以教师自学训练为主，人人建立各种笔记，保证落到实处。 4、建立激励机制，强化检查评比，要重视基本功训练的激励机制的建立，一是反复宣传“教

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第四篇船舶电气设备检修第一章船舶电气设备概述第二章船舶常用电工材料第三章船舶电工仪表及测量第四章船舶常用低压电器及其检修第五章船舶电机维护检修第六章船舶电站维护检修第七章船舶辅机电气控制装置维护检修第八章船舶内部通信及其信号装置检修第九章船舶照明系统维护检修第五篇船舶轴舵系装置检修第一章船舶轴系检修第二章船舶舵系检修第三章液压舵机检修第四章轴舵系主要设备与要求第五章轴舵系检测与试验第六篇船舶辅机检修第一章船用泵概述第二章往复泵检修第三章回转泵检修第四章离心泵和旋涡泵第五章喷射泵检修第六章船用活塞空气压缩机检修第七章通风机检修第八章船舶制冷装置检修第九章船舶空气调节装置检修第十章船用燃油辅机锅炉和废气锅炉检修第十一章船舶油分离机检修第十二章船舶防污染装置检修第十三章海水淡化装置检修第十四章操舵装置检修第十五章锚机系缆机和起货机检修第七篇船舶静电安全检修技术第一章船舶静电起电机理第二章舱内静电场计算第三章船舶静电安全技术研究第四章静电放电点燃估算第五章船舶静电综合分析防治对策

(完整版)教师基本功训练实施方案

教师基本功训练实施方案为了加快学校发展，全面提高教师业务素质，根据区教体局关于提高教师队伍素质的要求，现就开展教师教学基本功训练做如下实施方案。一、指导思想与目标要求：教师基本功是教师从事教学工作必须具备的最根本的职业技能。以提高教师岗位实际能力为目的，牢固练就扎实五项基本功：普通话、三笔字、说课评课。使每位教师都能练就一笔好字；说一口流利的普通话；独立设计一个完整的教学案例；制作一个合格的多媒体课件；上好一堂学生满意的课；写出一篇内容丰富的教学论文。要通过开展教师基本功训练的一系列活动。学校将加强领导，制定措施，层层落实，使人人参与，练有所得，练以致用，持之以恒，提高教师整体素质，为提高教学质量打好基础。二、基本功训练的原则： 1、在训练内容上，坚持注重实际，讲求实效，从课堂教学直观行为及“三字一话”入手。 2、在训练形式上，坚持以岗位练兵为主，自学为主，业务训练为主的原则，采取集中辅导与个人自学相结合，培训学习与实践锻炼相结合，定期开展各种比赛活动，以赛促练。规划达标时限，限期进行达标。 3、在工作组织上，坚持自练、教研、比赛、展示四位一体的原则。４、根据学校教师实际情况，分层培训，使培训更有实效性，针对性。 5、在评价验收上，坚持评比检查和教师量化管理相结合的原则。三、教师基本功训练内容： 1、普通话方面：能熟练掌握汉语拼音，用普通话进行教学；在公众场合即席讲话，用词准确，条理清楚，节奏适宜。 2、写字方面：能正确运用粉笔、钢笔按照汉字的笔画，笔顺和间架结构，书写规范的楷书字体，并具有一定的速度。 3、教学设计、教学论文、随笔、课堂教学方面：要求教师按照课程改革标准，随平时的教学活动认真改进，达到要求。 5、说课评课方面：能设计具有可操作性、明显特征的说课稿，并结合课件进行脱稿说课，思路清晰；能应用课改理论对一堂课进行较有针对性的评价。

船舶原理名词解释啊

1长宽比L/B 快速性、操纵性宽吃水比B/d 稳性、摇荡性、快速性、操纵性深吃水比D/d 稳性、抗沉性、船体强度宽深比B/D 船体强度、稳性长深比L/D 船体强度、稳性 2船长：船舶的垂线间长代表船长，即沿设计夏季载重水线，由首柱前缘至舵柱后缘或舵杆中心线的长度 3型宽：在船体最宽处，沿设计水线自一舷的肋骨外缘量至另一舷的肋骨外缘之间的水平距离 4型表面：不包括船壳板和甲板板厚度在内的船体表面 5型深：在船长中的处，由平板龙骨上缘量至上甲板边线下缘的垂直距离 6型吃水：在船长中点处由平板龙骨上缘量至夏季载重水线的垂直距离 7型线图是表示船体型表面形状的图谱,由纵剖线图、横剖线图、半宽水线图和型值表组成; 8浮性：船舶在给定载重条件下,能保持一定的浮态的性能； 9平衡条件：作用在浮体上的重力与浮力大小相等、方向相反并作用于同一铅垂线上； 10净载重量NDW：指船舶在具体航次中所能装载货物质量的最大值 11漂浮条件：满足平衡条件，且船体体积大于排水体积; 12浮心：浮心是船舶所受浮力的作用中心，也是排水体积的几何中心； 13漂心：船舶水线面积的几何中心； 14平行沉浮：船舶装卸货物前后水线面保持平行的现象； 15每厘米吃水吨数（TPC）：船舶吃水d每变化1cm，排水量变化的吨数，称为TPC。 16储备浮力：满载吃水以上的船体水密容积所具有的浮力 17干舷：在船长中点处由夏季载重水线量至上甲板边线上缘的垂直距离 18船舶稳性：船舶在外力（矩）作用下偏离其初始平衡位置，当外力（矩）消失后船舶能自行恢复到初始平衡状态的能力 19静稳性曲线：稳性力臂GZ或稳性力矩Ms随横倾角?变化曲线 20动稳性曲线：稳性力矩所做的功Ws或动稳性力臂I d随横倾角?变化的曲线 21吃水差比尺：是一种少量载荷变动时核算船舶纵向浮态变化的简易图表，它表示在船上任意位置加载100t后，船舶首、尾吃水该变量的图表 22最小倾覆力矩（力臂）：船舶所能承受动横倾力矩（力臂）的极限 23进水角：船舶横倾至最低非水密度开口开始进水时的横倾角 24可浸长度：船舶进水后的水线恰与限界线相切时的货仓最大许可舱长称为可浸长度 25稳性衡准数K是指船舶最小倾覆力矩(臂)与风压倾侧力矩（臂）之比 26稳性的调整方法：船内载荷的垂向移动及载荷横向对称增减 27静稳性力臂的表达式：1）基点法2）假定重心法3）初稳心点法 28船体强度：为保证船舶安全，船体结构必须具有抵抗各种内外作用力使之发生极度形变和破坏的能力 29局部强度表示方法：①均布载荷；②集中载荷；③车辆甲板载荷；④堆积载荷 30MTC为每形成1cm吃水差所需的纵倾力矩值，称为每厘米纵倾力矩 31载荷纵向移动包括配载计划编制时不同货舱货物的调整及压载水、淡水或燃油的调拨等情况 32重量增减包括中途港货物装卸、加排压载水、油水消耗和补给、破舱进水等情况 33抗沉性：是指船舶在一舱或数舱破损进水后，仍能保持一定浮性和稳性，使船舶不致沉没或延缓沉没时间，以确保人命和财产安全的性能

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船舶原理 名词解释啊

船舶原理名词解释啊