Ice accretion on aircraft wings with thermodynamic effects

This paper describes an analysis method for an inertial particle separator system modeled as a multi-element airfoil configuration. The analysis method is implemented in a numerical tool that is able to perform impingement analysis using spherical, nonspherical particles as well as water droplets for a range of Reynolds number (10 4 Re 5 10 5 ). A limitations of the analysis tool is that it lacks an appropriate particle rebound model for the treatment of particle-wall collisions. The usefulness of the analysis tool is its use in conjunction with a multipoint inverse design tool for the design of a multi-element airfoil based inertial particle separator system model in an inverse fashion as opposed to the direct design methods being employed currently for this task. With such a design and analysis tool at hand, the design space can be explored as well as tradeoff studies can be performed that can aid in the development of a more efficient design methodology for multi-element airfoil based inertial particle separator systems.= Runge-Kutta coefficients used to integrate the momentum equation l 0 ; n 0 = trajectory direction vector l 1 ; n 1 = airfoil panel plane direction vector m p = particle mass, p V p n = surface normal vector p = ambient pressure Re = Reynolds number based on particle diameter, a D eq U= a r p = particle position r p;i x p;i ; z p;i = particle current position during trajectory integration r p;i1 x p;i1 ; z p;i1 = particle new position during trajectory integration S = particle surface projection on the U * perpendicular plane S p = particle surface area s = airfoil panel surface arc length,= trajectory parametric equation parameter t 1 , t 2 = airfoil panel parametric equation parameters U = magnitude of particle relative velocity in body reference frame, jUj U = particle relative velocity in body reference frame, V a V p U 0 = initial particle relative velocity in body reference frame V a = freestream velocity in body reference frame, u a i w a k V i u i ; w i = current particle velocity during the trajectory integration V i1 u i1 ; w i1 = new particle velocity during the trajectory integration V p = particle volume V p = particle velocity in body reference frame, dr p =dt V 1 = unperturbed freestream velocity in wind reference frame, u 1 i w 1 k V 0 a = initial freestream velocity in body reference frame V 0 p = initial particle velocity in body reference frame u= axes in wind reference frame x p ; z p = axes in body reference frame x 0 ; z 0 = initial particle location in wind reference frame x 1 ; z 1 , x 2 ; z 2 = airfoil panel coordinates z = pressure head = geometric angle of attack with respect to airfoil chord line = impingement efficiency, dz 0 =ds x = step along the x axis z = step along the z axis = angle between the z p axis and z axis a = ambient air viscosity a = ambient air density p = particle mass density = time step in Runge-Kutta integration = shear stress = shape factor

Section: Particle Trajectory Analysismentioning

confidence: 84%

Section: Validation Examplementioning

confidence: 99%

Analysis Method for Inertial Particle Separator

Saeed

Al-Garni

2007

“…The icing/antiicing simulation code CANICE2D has been developed at École Polytechnique de Montréal as part of collaborative research and development activities funded by Bombardier Aerospace and the Natural Sciences and Engineering Research Council of Canada (NSERC) over 15 years [10][11][12][13][14][15][16][17]. The version of CANICE presented here is the research version, which differs from the version used at Bombardier Aerospace named CANICE-BA in the literature [18], but it contains the same four basic modules: extemal flow simulation, droplet trajectory and local catch efficiently calculation, surface ice/water interface thermodynamic balance and ice accretion, and, finally, hot air antiicing simulation (see Fig.…”

Section: Imethodologymentioning

confidence: 99%

Quasi-Steady Convergence of Multistep Navier–Stokes Icing Simulations

Hasanzadeh

Laurendeau

Paraschivoiu

2013

Self Cite

A newly developed two-dimensional ice accretion and antiicing simulation code, CANICE2D-NS, is presented. The method is used to predict iced airfoil shapes and performance degradation with a multistep approach. A multiblock Navier-Stokes code, NSMB, has been coupled with the CANICE2D icing framework, supplementing the existing panel method-based flow solver. Attention is paid to the roughness iniplementation within the turbulence model and to the convergence of the steady and quasi-steady iterative procedure. The new conpling allows fully automated multilayer icing simulation, whereas also permitting flow analysis and performance prediction of iced airfoils. Effects of uniform surface roughness in quasi-steady ice accretion simulation are analyzed through different validation test cases. The results demonstrates the benefits and robustness of the new framework in predicting ice shapes and aerodynamic performance parameters, as well as iced airfoil surface pressure coefficients. Finally, the convergence of the quasi-steady algorithm is verified and identifies the need for an order of magnitude increase in the number of multitime steps in icing simulations. Nomenclaturethe nearest wall, m í/() = offset in the wall distance to account for wall roughness, m /(,., = turbulent convective heat transfer coefficient, W/m-•K K¡ = equivalent sand grain roughness height normalized hy chord k = von Kármán constant k^ = equivalent sand grain roughness height, m LWC = liquid water content, kg/m' MED = mean droplet diameter, m Pr, = turbulent Prandtl number 5? = Stanton number Stf. = roughness Stanton number S = transformed vorticity u = longitudinal velocity component, m/s Ug = boundary-layer edge velocity, m/s «J = friction velocity, m/s 1/ = kinematic viscosity, m^/s t/, = turbulent eddy viscosity, m-/s D = transported quantity in the S-A model w = wall value y = distance along the wall normal, m y+ = normalized wall distance •p = density, kg/m-

“…The resulting momentum equation (a differential equation) is then solved with some known initial conditions until the particle impacts a surface panel or travels past the entire multi-element configuration without an impact. Similar studies related to sand and water-droplet impingement and ice accretion on aircraft and engine inlet surfaces are available in the literature [5][6][7][12][13][14][15][16][17][18][19][20][21].…”

Section: A Flow and Trajectory Analysismentioning

confidence: 95%

Design and Optimization Method for Inertial Particle Separator Systems

Al-Faris

Saeed

2009

The paper presents a method for the design and optimization of a multi-element airfoil-based inertial particle separator. To facilitate design in an interactive manner, a MATLAB graphical user interface was developed with the following capabilities: 1) design of individual airfoil elements; 2) orientation and arrangement of the airfoils to form a multi-element airfoil-based inertial particle separator system by employing translational, scaling, and rotational functions; 3) analysis of the inertial particle separator system; and 4) optimum design of the inertial particle separator system using an evolutionary algorithm-based direct-search optimization technique. The design of individual airfoils was achieved through the use of the PROFOIL code, a state-of-the-art multipoint inverse airfoil design program. Multiple airfoils were arranged to form a multi-element airfoil-based inertial particle separator system subject to geometric constraints. A two-dimensional analysis tool for the multi-element airfoil was linked to the synthesis component of the graphical user interface to carry out flow and particle trajectory analysis component of the program. For the optimization component of the program, a computational objective function was implemented and coupled with a pattern search optimizer of the Direct Search Toolbox in MATLAB. Design and optimization was achieved using multivariable optimization. The paper presents two design examples to demonstrate the design method. Nomenclature C d = particle drag coefficient c = airfoil chord length D eq = equivolumetric or mean volumetric diameter F a = aerodynamic force F g = gravitational force g = gravitational acceleration constant i, k = unit direction vectors in the wind reference frame i p , k p = unit direction vectors in the body reference frame m p = particle mass, p V p n = surface normal vector p = ambient pressure Re = Reynolds number based on particle diameter, a D eq U= a r p = particle position S = particle surface projection on the U perpendicular plane S p = particle surface area t = time U = magnitude of particle relative velocity in the body reference frame, jUj U = particle relative velocity in the body reference frame, V a V p V a = freestream velocity in the body reference frame, u a i w a k V p = particle volume V p = particle velocity in the body reference frame, dr p =dt x, z = axes in the wind reference frame x p , z p = axes in the body reference frame z = pressure head = angle between the z p axis and z axis a = ambient air viscosity a = ambient air density p = particle mass density = shear stress