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Potential flow

Potential flow is a fundamental concept in fluid dynamics that models the motion of an ideal fluid as inviscid, incompressible, and irrotational, where the velocity field can be expressed as the gradient of a scalar velocity potential function, resulting in zero vorticity throughout the flow field.^[1]^[2] This idealized framework assumes the absence of viscosity, ensuring no frictional losses or boundary layer effects dominate the flow, while incompressibility implies constant fluid density, and irrotationality means fluid elements do not rotate about their own axes.^[3] The governing equation for the velocity potential in such flows is Laplace's equation, ∇²φ = 0, which arises from the continuity equation for incompressible fluids and allows for analytical solutions through the superposition of elementary flow components, such as uniform streams, sources, sinks, vortices, and doublets.^[1]^[2] In practice, potential flow theory is widely applied in aerodynamics and hydrodynamics to approximate external flows around streamlined bodies, such as airfoils, wings, and ship hulls, providing insights into pressure distributions, lift generation, and wave patterns without the complexities of turbulence or viscosity.^[3]^[1] For instance, it forms the basis for thin airfoil theory and panel methods in aircraft design, where the Kutta-Joukowski theorem quantifies lift as proportional to circulation around the airfoil.^[1] Extensions to compressible flows, like the Prandtl-Glauert transformation, adapt the model for subsonic regimes, enhancing its utility in aerospace engineering.^[1] Despite its elegance, potential flow has notable limitations, including the prediction of zero drag on closed bodies (D'Alembert's paradox), which contradicts real-world observations due to neglected viscous effects, and its inapplicability to rotational or turbulent flows.^[3]^[1] These shortcomings are often addressed by combining potential flow solutions with boundary layer corrections in modern computational and experimental analyses.^[2]

Fundamentals

Definition and Characteristics

Potential flow is a fundamental concept in fluid dynamics that describes the motion of an ideal fluid where the velocity field \mathbf{u} can be expressed as the gradient of a scalar velocity potential \phi, such that \mathbf{u} = \nabla \phi. This representation inherently implies that the flow is irrotational, meaning the curl of the velocity field vanishes: \nabla \times \mathbf{u} = 0.^[4]^[5] The assumption of irrotationality simplifies the analysis by eliminating the need to track vorticity, allowing the flow to be fully determined by solving for the potential in a simply connected domain.^[1] Key characteristics of potential flow include its inviscid nature, where viscous shear stresses are neglected, leading to no energy dissipation due to friction.^[3] This model is often applied to both incompressible and compressible fluids, depending on the specific conditions, and enables the use of Bernoulli's equation, which relates pressure, velocity, and elevation along streamlines in steady, inviscid flow.^[1]^[3] In potential flow, the absence of viscosity and rotation results in smooth, reversible streamlines without turbulence or shock waves in the subsonic regime.^[6] The theoretical foundations of potential flow originated in the 18th century, building on earlier work by Leonhard Euler on inviscid and irrotational flows, contributions from Daniel Bernoulli on the pressure-velocity relation in ideal fluids, and Jean le Rond d'Alembert on the paradox of zero drag, with Joseph-Louis Lagrange developing variational principles for ideal fluid motion in his 1788 Mécanique Analytique.^[1]^[7]^[8] During the 19th century, advancements by figures such as George Stokes formalized concepts like streamlines and circulation, laying the groundwork for its application in early aerodynamics, including airfoil theory.^[1] This idealization proved instrumental in modeling fluid behavior before the full incorporation of viscosity in the Navier-Stokes equations.^[8] Physically, potential flow represents scenarios where viscous effects are negligible, such as in high Reynolds number regimes, where inertial forces dominate and the flow remains attached to bodies without separation or boundary layer formation.^[9]^[10] It approximates real-world flows around streamlined objects, like aircraft wings at subsonic speeds, providing insights into pressure distributions and lift generation under idealized conditions.^[1]^[6]

Mathematical Formulation

In potential flow theory, the velocity field \mathbf{u} is represented by the gradient of a scalar velocity potential \phi, such that \mathbf{u} = \nabla \phi. In Cartesian coordinates (x, y, z), this yields the components u = \partial \phi / \partial x, v = \partial \phi / \partial y, and w = \partial \phi / \partial z.^[3]^[11] The existence of such a potential \phi stems from the irrotational condition, where the vorticity \boldsymbol{\omega} = \nabla \times \mathbf{u} = 0. By the vector calculus identity, the curl of a gradient is always zero (\nabla \times (\nabla \phi) = 0), ensuring that any irrotational velocity field can be expressed as the gradient of a scalar potential in simply connected domains.^[12]^[3] For incompressible flow, the governing equation for \phi is derived from the continuity equation \nabla \cdot \mathbf{u} = 0 and the irrotationality condition. Substituting \mathbf{u} = \nabla \phi into the continuity equation gives \nabla \cdot (\nabla \phi) = \nabla^2 \phi = 0, which is Laplace's equation. This linear partial differential equation is elliptic and harmonic, allowing solutions via separation of variables or other methods.^[12]^[3]^[11] In compressible flow, the continuity equation involves density variations, leading to a nonlinear governing equation for \phi. Under small perturbation assumptions for steady flow aligned with the x-direction, the equation simplifies to

(1 - M^2) \frac{\partial^2 \phi}{\partial x^2} + \frac{\partial^2 \phi}{\partial y^2} + \frac{\partial^2 \phi}{\partial z^2} = 0,

where M is the local Mach number based on the speed of sound. The full nonlinear form arises from the isentropic relation and momentum equations, incorporating terms dependent on \nabla \phi and the local speed of sound, resulting in an equation of mixed elliptic-hyperbolic type depending on M < 1 or M > 1.^[13]^[1] The formulation of Laplace's equation or its compressible analogs is typically expressed in specific coordinate systems for practical solutions. In Cartesian coordinates, it takes the standard form \partial^2 \phi / \partial x^2 + \partial^2 \phi / \partial y^2 + \partial^2 \phi / \partial z^2 = 0. In cylindrical coordinates (r, \theta, z), the equation becomes

\frac{1}{r} \frac{\partial}{\partial r} \left( r \frac{\partial \phi}{\partial r} \right) + \frac{1}{r^2} \frac{\partial^2 \phi}{\partial \theta^2} + \frac{\partial^2 \phi}{\partial z^2} = 0,

suitable for axisymmetric flows. In spherical coordinates (r, \theta, \phi), it is

\frac{1}{r^2} \frac{\partial}{\partial r} \left( r^2 \frac{\partial \phi}{\partial r} \right) + \frac{1}{r^2 \sin \theta} \frac{\partial}{\partial \theta} \left( \sin \theta \frac{\partial \phi}{\partial \theta} \right) + \frac{1}{r^2 \sin^2 \theta} \frac{\partial^2 \phi}{\partial \phi^2} = 0,

useful for flows around spheres or point sources. These forms facilitate analytical solutions using series expansions, such as Legendre polynomials in spherical coordinates.^[12]

Incompressible Potential Flow

Governing Equations

In incompressible potential flow, the continuity equation simplifies to \nabla \cdot \mathbf{u} = 0, reflecting the constant density assumption.^[14] For irrotational flow, the velocity \mathbf{u} is expressed as the gradient of a scalar potential \phi, so \mathbf{u} = \nabla \phi.^[14] Substituting this into the continuity equation yields Laplace's equation, \nabla^2 \phi = 0.^[14]^[1] The momentum equations for inviscid flow are the Euler equations: \frac{\partial \mathbf{u}}{\partial t} + (\mathbf{u} \cdot \nabla) \mathbf{u} = -\frac{1}{\rho} \nabla p + \mathbf{g}, where \mathbf{g} is the body force per unit mass, typically gravity \mathbf{g} = -g \hat{z}.^[15] For irrotational flow, the convective term expands using vector identities as (\mathbf{u} \cdot \nabla) \mathbf{u} = \nabla \left( \frac{1}{2} |\mathbf{u}|^2 \right) - \mathbf{u} \times (\nabla \times \mathbf{u}), and the curl term vanishes, yielding \frac{\partial \mathbf{u}}{\partial t} + \nabla \left( \frac{1}{2} |\mathbf{u}|^2 \right) = -\frac{1}{\rho} \nabla p + \mathbf{g}.^[15] Substituting \mathbf{u} = \nabla \phi gives \nabla \left( \frac{\partial \phi}{\partial t} + \frac{1}{2} |\nabla \phi|^2 + \frac{p}{\rho} + gz \right) = 0, assuming conservative gravity.^[15] Integrating this gradient equation results in the unsteady Bernoulli equation:

\frac{\partial \phi}{\partial t} + \frac{1}{2} |\nabla \phi|^2 + \frac{p}{\rho} + gz = F(t),

where F(t) is an arbitrary function of time determined by boundary conditions.^[15] Laplace's equation is an elliptic partial differential equation, characterized by its lack of real characteristics, which implies that solutions are smooth and determined globally by boundary values rather than propagating disturbances locally.^[16] Due to its linearity, solutions obey the superposition principle: if \phi_1 and \phi_2 satisfy \nabla^2 \phi = 0, then so does a \phi_1 + b \phi_2 for constants a and b.^[16] For boundary value problems in a bounded domain, uniqueness holds: the Dirichlet problem (specifying \phi on the boundary) has a unique solution in C^2(\Omega) \cap C(\overline{\Omega}), and the Neumann problem (specifying the normal derivative \partial \phi / \partial n) has a unique solution up to an additive constant, provided the compatibility condition \int_{\partial \Omega} g \, dS = 0 is met for the boundary data g.^[16] The elliptic nature of Laplace's equation renders the initial value problem ill-posed for time-dependent incompressible potential flow; small perturbations in initial data can lead to exponentially growing instabilities in the solution, as there are no finite propagation speeds for disturbances—instead, information spreads instantaneously across the entire domain.^[17] This limitation underscores why incompressible potential flow is typically analyzed as a steady-state or boundary value problem rather than an evolutionary initial value one.^[17]

Boundary Conditions and Solutions

In incompressible potential flow, the primary boundary conditions arise from the physical constraints of the flow domain. On solid surfaces, the impermeability condition requires that the normal component of the velocity vanishes, ensuring no fluid penetrates the boundary; this translates to \frac{\partial \phi}{\partial n} = 0, where \phi is the velocity potential and n is the outward normal direction.^[5]^[14] At large distances from the body (far-field condition), the flow approaches a uniform stream, such that \phi \to U x as r \to \infty, where U is the uniform flow speed and x is the streamwise coordinate.^[14]^[18] Solutions to the resulting boundary value problem for Laplace's equation \nabla^2 \phi = 0 can be obtained analytically for simple geometries using separation of variables in appropriate coordinate systems, such as spherical coordinates for axisymmetric bodies.^[19] For more complex shapes, numerical methods like panel methods discretize the body surface into panels and solve for source or doublet distributions to satisfy the boundary conditions; these methods were developed in the 1970s to handle airfoil and aircraft geometries efficiently.^[1]^[20] The exterior Neumann problem posed by these conditions—specifying \frac{\partial \phi}{\partial n} on the body surface and behavior at infinity—admits a unique solution up to an additive constant, provided the total source strength is zero (consistent with incompressibility); this follows from the properties of harmonic functions in unbounded domains, though open domains introduce challenges related to decay at infinity.^[21]^[22] A classic example is the uniform flow past a sphere of radius a. Assuming axial symmetry, the solution via separation of variables yields the velocity potential \phi = -U r \cos \theta \left(1 + \frac{1}{2} \frac{a^3}{r^3}\right), which satisfies the impermeability condition at r = a and recovers the uniform flow far upstream.^[18]^[12] This dipole-like disturbance decays as $1/r^3, illustrating how the body perturbs the oncoming flow without altering its irrotational nature.^[14]

Compressible Potential Flow

Steady Compressible Flow

In steady compressible potential flow, the velocity field is derived from a scalar potential \phi such that \mathbf{v} = \nabla \phi, assuming irrotational and isentropic conditions. The governing continuity equation takes the form \nabla \cdot (\rho \nabla \phi) = 0, where the density \rho is related to the local Mach number via isentropic relations: \frac{\rho}{\rho_\infty} = \left[1 + \frac{\gamma - 1}{2} M_\infty^2 \left(1 - \frac{|\nabla \phi|^2}{U_\infty^2}\right)\right]^{\frac{1}{\gamma - 1}}, with \gamma as the specific heat ratio, \rho_\infty and U_\infty as freestream density and velocity, and M_\infty as the freestream Mach number.^[23] This nonlinear equation captures density variations essential for transonic and supersonic regimes, where compressibility effects dominate.^[24] For subsonic flows where perturbations are small (M < 1), linearization yields the Prandtl-Glauert equation: (1 - M_\infty^2) \frac{\partial^2 \phi}{\partial x^2} + \frac{\partial^2 \phi}{\partial y^2} + \frac{\partial^2 \phi}{\partial z^2} = 0. This is solved via a coordinate transformation x' = x / \sqrt{1 - M_\infty^2}, y' = y, z' = z, reducing the problem to an equivalent incompressible flow in the transformed space, with pressures scaled by \sqrt{1 - M_\infty^2}. The transformation highlights how compressibility stretches the flow field in the streamwise direction, increasing lift and drag coefficients proportionally to $1 / \sqrt{1 - M_\infty^2}.^[25] Pressure recovery in steady potential flow follows from integrating the Euler equations along streamlines, yielding the steady Bernoulli equation: \frac{1}{2} |\nabla \phi|^2 + \int \frac{dp}{\rho} = \text{const}. For isentropic conditions, this simplifies to \frac{\gamma}{\gamma - 1} \frac{p}{\rho} + \frac{1}{2} |\nabla \phi|^2 = \frac{\gamma}{\gamma - 1} \frac{p_\infty}{\rho_\infty} + \frac{1}{2} U_\infty^2.^[3] This relation links velocity perturbations to local pressure and density changes, enabling computation of aerodynamic forces.^[26] In transonic flows (M \approx 1), the full potential equation's nonlinearity is approximated by the transonic small disturbance equation, retaining key terms for mixed subsonic-supersonic regions: (1 - M_\infty^2) \frac{\partial^2 \phi}{\partial x^2} + \frac{\partial^2 \phi}{\partial y^2} + \frac{\partial^2 \phi}{\partial z^2} = (\gamma + 1) M_\infty^2 \frac{\partial \phi}{\partial x} \frac{\partial^2 \phi}{\partial x^2}. This facilitates numerical solutions for airfoils with weak shocks, though it assumes small perturbations relative to freestream. Applications include predicting transonic drag rise and shock locations on thin bodies.^[27] Despite these advances, potential flow models face limitations in capturing shocks fully, as the continuous potential cannot inherently represent discontinuities without additional shock-fitting techniques. Shock-fitting embeds the shock as an internal boundary, enforcing Rankine-Hugoniot jump conditions, but requires iterative location updates and struggles with multiple or unsteady shocks.^[28] In transonic regimes, this leads to non-physical entropy production or smeared shocks, necessitating hybrid approaches with Euler equations for accurate shock resolution.^[29]

Unsteady Compressible Flow

Unsteady compressible potential flow extends the irrotational flow assumption to time-dependent scenarios where density variations and compressibility effects are significant, such as in transonic or supersonic aerodynamics involving dynamic motions. The governing continuity equation takes the form \partial \rho / \partial t + \nabla \cdot (\rho \nabla \phi) = 0, where \phi is the velocity potential and \rho is the fluid density determined from unsteady isentropic relations.^[30] Specifically, for an ideal gas, \rho = \rho_0 (p / p_0)^{1/\gamma}, with pressure p obtained from the unsteady Bernoulli equation \partial \phi / \partial t + \frac{1}{2} |\nabla \phi|^2 + \int dp / \rho + gz = f(t), where \gamma is the specific heat ratio and f(t) is an arbitrary function of time.^[30] This nonlinear partial differential equation couples the potential \phi with density variations driven by local speed changes, making analytical solutions challenging except in simplified geometries. For small perturbations around a uniform mean flow, the equations linearize to the acoustic wave equation \nabla^2 \phi - \frac{1}{c^2} \frac{\partial^2 \phi}{\partial t^2} = 0, where c is the speed of sound in the undisturbed medium.^[31] This form arises by assuming perturbations in velocity potential \phi' such that \rho = \rho_\infty + \rho'(\phi') and linearizing the continuity and momentum equations, valid for low Mach number disturbances where nonlinear terms are negligible.^[31] The wave equation describes propagating pressure waves, essential for analyzing transient phenomena like gust responses or oscillating airfoils in subsonic regimes. Applications of unsteady compressible potential flow include computing aerodynamic derivatives, which quantify stability derivatives such as lift and moment coefficients due to angular rates or accelerations in aircraft dynamics.^[32] For instance, boundary integral methods solve the linearized equations to evaluate unsteady airloads on lifting surfaces undergoing harmonic motions.^[32] In hypersonic flows where Mach numbers greatly exceed unity (M \gg 1), piston theory provides a brief linearized approximation for surface pressures, treating the boundary as a pulsating piston and yielding p / p_\infty \approx 1 + \gamma M_\infty \frac{v_n}{a_\infty}, where v_n is the normal velocity at the surface, useful for rapid estimates of aeroelastic responses.^[33] However, these models inherently ignore vorticity generation mechanisms in unsteady flows, such as those from curved shock waves or boundary layer interactions, limiting accuracy where Kelvin's circulation theorem does not preclude vorticity amplification despite initial irrotationality.^[30]

Two-Dimensional Analysis

Complex Potential Method

In two-dimensional incompressible potential flow, the complex potential w(z) is defined as a function of the complex variable z = x + iy, where x and y are the spatial coordinates, the velocity potential \phi(x, y) is the real part, and the stream function \psi(x, y) is the imaginary part, such that w(z) = \phi + i\psi.^[34] The derivative of the complex potential yields the complex conjugate velocity, given by \frac{dw}{dz} = u - iv, where u and v are the velocity components in the x- and y-directions, respectively.^[34]^[35] The real and imaginary parts of the analytic complex potential satisfy the Cauchy-Riemann equations:

\frac{\partial \phi}{\partial x} = \frac{\partial \psi}{\partial y}, \quad \frac{\partial \phi}{\partial y} = -\frac{\partial \psi}{\partial x}.

These equations ensure that both \phi and \psi are harmonic functions, satisfying Laplace's equation \nabla^2 \phi = 0 and \nabla^2 \psi = 0 in two dimensions.^[3]^[36] If w(z) is holomorphic (analytic) in a domain, the resulting flow is irrotational because the velocity field is the gradient of \phi, implying \nabla \times \mathbf{v} = 0, and incompressible because the divergence vanishes from the continuity equation, \nabla \cdot \mathbf{v} = 0./07:_Two_Dimensional_Hydrodynamics_and_Complex_Potentials/7.04:_Complex_Potentials)^[37] Conversely, for simply connected domains, any irrotational and incompressible two-dimensional flow admits a holomorphic complex potential.^[38] Singularities in w(z), such as poles or essential singularities, correspond to physical features like sources, sinks, or vortices in the flow field.^[14] The complex potential method derives from representing the two-dimensional Laplace equation in the complex plane, where solutions to \nabla^2 \phi = 0 are the real parts of analytic functions, leveraging the identification of the plane with the complex domain.^[39]^[37] Liouville's theorem, stating that bounded entire holomorphic functions are constant, implies that non-trivial potential flows without singularities must be unbounded, such as uniform flows extending to infinity.^[40]^[41]

Stream Function and Conformal Mapping

In two-dimensional incompressible potential flow, the stream function \psi(x, y) is a scalar field that describes the flow pattern by defining streamlines as curves where \psi is constant. The velocity components are related to the stream function by the partial derivatives u = \frac{\partial \psi}{\partial y} and v = -\frac{\partial \psi}{\partial x}, which automatically satisfy the continuity equation \frac{\partial u}{\partial x} + \frac{\partial v}{\partial y} = 0 for incompressible flow.^[1] This formulation simplifies the analysis of irrotational flows, as \psi also satisfies Laplace's equation \nabla^2 \psi = 0 when the vorticity is zero.^[1] The stream function is orthogonal to the velocity potential \phi, meaning that the gradients satisfy \nabla \phi \cdot \nabla \psi = 0, so streamlines (\psi = constant) intersect equipotential lines (\phi = constant) at right angles.^[42] This orthogonality aids in visualizing the flow field, as the two families of curves form a curvilinear coordinate system aligned with the flow direction and its perpendicular. In practice, plotting these lines reveals the direction and magnitude of the velocity, with the difference in \psi values between adjacent streamlines representing the volume flow rate per unit depth.^[1] Conformal mapping techniques leverage complex analysis to solve boundary value problems in two-dimensional potential flow by transforming complicated geometries into simpler ones, such as mapping an arbitrary boundary to a unit circle. A conformal map z = f(\zeta), where f is analytic and non-constant, preserves local angles and scales lengths uniformly, ensuring that solutions to Laplace's equation in one plane transform correctly to the other.^[43] Since both \phi and \psi satisfy Laplace's equation and the Cauchy-Riemann conditions, the complex potential w = \phi + i\psi remains analytic under such mappings, preserving the irrotational and incompressible nature of the flow.^[43] A key example is the Joukowski transformation, given by z = \zeta + \frac{a^2}{\zeta}, which maps a circle in the \zeta-plane (centered at the origin with radius greater than a) to a symmetric airfoil-like shape in the z-plane.^[44] The uniform flow past this circle in the \zeta-plane, combined with a vortex for circulation to satisfy the Kutta condition, transforms to the flow around the airfoil, providing insights into lift generation without solving the full boundary problem directly.^[44] This mapping is foundational for early airfoil design, as variations in circle position and size yield families of airfoils with controllable thickness and camber.^[44] The Milne-Thomson circle theorem facilitates solutions for flows around circular boundaries by superposing the undisturbed flow with an image system. If the complex potential without the cylinder of radius a is f(z), with no singularities inside |z| > a, then the potential with the cylinder present is w(z) = f(z) + f\left(\frac{a^2}{z}\right), ensuring the boundary |z| = a becomes a streamline (\psi = 0).^[45] This theorem applies to superpositions like uniform flow plus sources or vortices outside the cylinder, yielding exact solutions for circular obstacles in otherwise simple flows.^[45] In broader applications, conformal mappings extend these ideas by transforming arbitrary airfoil or body shapes to the unit circle, where uniform oncoming flow solutions are straightforward via the Milne-Thomson theorem or basic singularities. The inverse mapping then yields the flow field for the original geometry, enabling analytical predictions of pressure distributions and forces on non-circular boundaries without numerical methods.^[43] This approach, while limited to two dimensions, underpins classical thin airfoil theory and remains influential in educational and preliminary design contexts.^[43]

Two-Dimensional Examples

Uniform Flow and Superpositions

In two-dimensional incompressible potential flow, uniform flow represents the fundamental building block, characterized by a constant velocity vector throughout the domain. The complex potential for uniform flow with speed U in the positive x-direction is w(z) = U z, where z = x + i y is the complex position variable.^[1] This expression separates into the velocity potential \phi = U x and stream function \psi = U y, yielding constant velocity components u = U and v = 0./06:_Chapter_6/6.02:_Complex_Potential-_Basic_examples) The streamlines are parallel straight lines perpendicular to the flow direction, and the flow satisfies Laplace's equation everywhere./06:_Potential_Flows) The superposition principle arises from the linearity of Laplace's equation governing potential flows, allowing the complex potentials (or equivalently, the velocity potentials and stream functions) of multiple elementary flows to be added linearly to construct more complex solutions.^[6] This method preserves irrotationality and incompressibility, enabling the modeling of flows around bodies by combining uniform flow with singularities like sources or doublets./06:_Potential_Flows) For instance, the complex potential method facilitates such combinations using analytic functions in the complex plane.^[1] A classic application is the Rankine half-body, formed by superposing a uniform flow of speed U with a two-dimensional source of strength m located at the origin, yielding the complex potential w(z) = U z + \frac{m}{2\pi} \log z.^[46] The source introduces radial outflow that divides the oncoming uniform stream, creating a stagnation streamline that originates from the stagnation point ahead of the source and extends downstream to form the closed "nose" and open-ended body boundary.^[47] Far upstream, the flow asymptotes to uniform conditions, while the half-width of the body at large distances is h = m / U, independent of the x-coordinate.^[46] Another key example is the irrotational flow past a circular cylinder of radius a, obtained by superposing uniform flow with a doublet (the limiting case of a source-sink pair) aligned opposite to the flow direction, giving the complex potential w(z) = U \left( z + \frac{a^2}{z} \right).^[48] On the cylinder surface (|z| = a), the tangential velocity is q_\theta = 2 U \sin \theta, where \theta is the polar angle from the x-axis. Applying Bernoulli's equation along a streamline, the surface pressure coefficient is C_p = 1 - 4 \sin^2 \theta, with maximum pressure at the stagnation points (\theta = 0, \pi) where C_p = 1, and minimum at the sides (\theta = \pm \pi/2) where C_p = -1.^[49] Integrating the pressure distribution yields zero net drag force on the cylinder, a result embodying d'Alembert's paradox, which highlights the idealization of inviscid flow neglecting real-fluid separation and boundary layers.^[49]

Sources, Sinks, and Vortices

In two-dimensional potential flow, a line source represents a singularity where fluid emanates radially outward from a point in the plane, modeling the flow due to a continuous injection of fluid along a line perpendicular to the plane. The complex potential for a line source of strength m (volume flow rate per unit length) located at the origin is given by

w(z) = \frac{m}{2\pi} \log z,

where z = x + iy is the complex position variable.^[50] The corresponding velocity field derives from the complex velocity \frac{dw}{dz} = \frac{m}{2\pi z}, yielding a purely radial velocity component u_r = \frac{m}{2\pi r} in polar coordinates (r, \theta), with no tangential component u_\theta = 0. A line sink is obtained by taking the negative strength m < 0, resulting in inward radial flow u_r = -\frac{|m|}{2\pi r}. These singularities are irrotational everywhere except at the origin, where the velocity becomes infinite.^[50] A line vortex models circulatory flow around a point singularity, representing irrotational rotation outside an infinitesimal core. The complex potential for a line vortex of circulation \Gamma (positive for counterclockwise) at the origin is

w(z) = -\frac{i \Gamma}{2\pi} \log z.

^[50] The complex velocity is \frac{dw}{dz} = -\frac{i \Gamma}{2\pi z}, producing a purely tangential velocity u_\theta = \frac{\Gamma}{2\pi r} and zero radial component u_r = 0. The flow is irrotational (\nabla \times \mathbf{u} = 0) away from the singularity, but the vorticity concentrates as a delta function at the origin.^[50] Combining a source and sink of equal strength m separated by a small distance $2a along the real axis yields a source-sink pair, useful for modeling localized flow disturbances. In the limit as a \to 0 while holding the product \frac{m a}{\pi} constant at doublet strength \mu, the complex potential simplifies to

w(z) = \frac{\mu}{z}.

^[50] This doublet produces a dipole-like velocity field \frac{dw}{dz} = -\frac{\mu}{z^2}, with flow directed away from the origin along the positive real axis and toward it along the negative axis. These singularities serve as fundamental building blocks in potential flow analysis. Line sources model jet-like outflows, such as in the Rankine half-body formed by superposing a source with uniform flow.^[50] Line vortices are essential for capturing circulation effects, particularly around airfoils, where the Kutta condition enforces smooth flow departure from the trailing edge by setting the circulation \Gamma such that rear stagnation occurs there. In three dimensions, analogous point sources, sinks, and vortices extend these concepts to volumetric flows.

Three-Dimensional Analysis

Basic Singularities

In three-dimensional incompressible potential flow, the velocity field is derived from a scalar potential \phi satisfying Laplace's equation \nabla^2 \phi = 0 everywhere except at singularities, where the velocity \mathbf{v} = \nabla \phi. These basic point singularities serve as fundamental building blocks for constructing more complex flows through superposition.^[14] A point source at the origin emits fluid radially outward with strength m > 0, represented by the potential \phi = -\frac{m}{4\pi r}, where r = \sqrt{x^2 + y^2 + z^2} is the radial distance. The resulting radial velocity component is v_r = \frac{m}{4\pi r^2}, which corresponds to a total flux of m through any enclosing sphere, decaying as $1/r^2 away from the singularity. A point sink is obtained by taking m < 0, reversing the flow direction to radially inward.^[14] The doublet arises as the limiting case of a source-sink pair, where a source of strength m and a sink of strength -m are separated by a small distance d along a direction, and m d \to \mu (the doublet strength) as d \to 0. The potential is \phi = \frac{\mu \cos \theta}{4\pi r^2}, with \theta the angle between the doublet axis and the position vector \mathbf{r}. This produces a dipole-like velocity field, strongest along the axis and zero in the perpendicular plane.^[14] Uniform flow in the positive x-direction, with speed U, has the simple potential \phi = U x. This linear function satisfies Laplace's equation and represents an unperturbed free stream. A classic application combines uniform flow with a doublet to model irrotational flow past a sphere of radius a: \phi = U \cos \theta \left( r + \frac{a^3}{2 r^2} \right), where the doublet strength is \mu = 2 \pi U a^3. On the sphere surface (r = a), the radial velocity vanishes, enforcing the no-penetration boundary condition, while far away the flow asymptotes to uniform.^[14] Although potential flow assumes irrotationality (\nabla \times \mathbf{v} = 0), vorticity cannot be represented using a scalar potential in three dimensions; instead, a vector potential \boldsymbol{\psi} is employed such that \mathbf{v} = \nabla \times \boldsymbol{\psi}, satisfying the solenoidal condition \nabla \cdot \mathbf{v} = 0. This limitation restricts scalar potential methods to vorticity-free regions.^[14]

Axisymmetric and General Solutions

In axisymmetric potential flows, the velocity potential \phi is independent of the azimuthal angle and depends solely on the radial coordinate r and polar angle \theta in spherical coordinates, where it satisfies Laplace's equation \nabla^2 \phi = 0.^[51] The general solution takes the form of a series expansion involving Legendre polynomials:

\phi(r, \theta) = \sum_{n=0}^{\infty} \left( A_n r^n + \frac{B_n}{r^{n+1}} \right) P_n(\cos \theta),

with coefficients A_n and B_n determined by boundary conditions, and P_n denoting the Legendre polynomials of degree n.^[51]^[52] This separation-of-variables solution applies to problems with rotational symmetry about the polar axis, such as flow past axisymmetric bodies.^[51] For instance, uniform flow of speed U past a sphere of radius a yields \phi = U r \cos \theta \left(1 + \frac{a^3}{2 r^3}\right), utilizing the n=1 term where A_1 = U and B_1 = \frac{1}{2} U a^3.^[12] For general non-axisymmetric three-dimensional incompressible potential flows, the velocity potential \phi(r, \theta, \phi) incorporates azimuthal dependence through spherical harmonics Y_l^m(\theta, \phi):

\phi(r, \theta, \phi) = \sum_{l=0}^{\infty} \sum_{m=-l}^{l} \left( A_{lm} r^l + \frac{B_{lm}}{r^{l+1}} \right) Y_l^m(\theta, \phi),

where the coefficients A_{lm} and B_{lm} are fixed by boundary conditions, and the harmonics are products of associated Legendre functions and azimuthal exponentials.^[50] In axisymmetric cases, the m=0 terms suffice, reducing to the Legendre series.^[50] Such analytical expansions prove challenging for arbitrary non-symmetric geometries, prompting numerical methods based on integral equations with Green's functions, which emerged prominently after the 1950s.^[53] These approaches express the potential as a surface integral over the body using the free-space Green's function G(\mathbf{r}, \mathbf{r}') = -\frac{1}{4\pi |\mathbf{r} - \mathbf{r}'|}, typically via source or doublet distributions to enforce the impermeability condition \frac{\partial \phi}{\partial n} = \mathbf{V} \cdot \mathbf{n}.^[54] A seminal development is the panel method of Hess and Smith (1967), which discretizes the body surface into quadrilateral panels, approximates distributions as constants per panel, and solves the resulting Fredholm integral equation of the second kind numerically for distribution strengths.^[54] This technique facilitates solutions for complex three-dimensional bodies by converting the boundary value problem into a linear algebraic system.^[54]

Applications and Limitations

Practical Uses in Aerodynamics

Potential flow theory forms the cornerstone of classical aerodynamics, particularly in the analysis of airfoils where it enables the prediction of lift generation under inviscid, irrotational conditions.^[1] In thin airfoil theory, the flow is modeled using a perturbation potential φ to approximate the velocity field around a slender airfoil at small angles of attack, allowing for the decomposition of the problem into camber, thickness, and angle-of-attack effects.^[55] The resulting circulation Γ around the airfoil is given by Γ = π c U α, where c is the chord length, U is the freestream velocity, and α is the angle of attack, which directly relates to the lift per unit span L' via the Kutta-Joukowski theorem: L' = ρ U Γ, with ρ denoting fluid density.^[56] This approach, originally developed in the early 20th century, provides accurate lift predictions for subsonic flows over symmetric and cambered airfoils, serving as a benchmark for validating more complex models.^[55] Extending two-dimensional airfoil results to finite wings, Prandtl's lifting-line theory, introduced in 1918, models the wing as a bound vortex line with trailing vortices to account for three-dimensional effects like induced drag.^[57] The theory predicts spanwise lift distribution and demonstrates that an elliptic loading achieves minimum induced drag for a given lift, optimizing wing efficiency in aircraft design.^[57] This seminal model remains influential for preliminary sizing of wings in subsonic flight, influencing designs from early monoplanes to modern transport aircraft.^[58] Advancements in computational capabilities during the 1970s led to the development of panel methods, such as the vortex-lattice method, which discretize lifting surfaces into panels with vortex distributions to solve potential flow for complex three-dimensional configurations like wings and fuselages.^[59] These methods, highlighted at the 1975 NASA conference on computational fluid dynamics, enabled rapid aerodynamic analysis and optimization for multi-element wings, interference effects, and non-planar surfaces, bridging theoretical potential flow with practical engineering applications.^[59] Beyond aviation, potential flow principles apply to hydrofoils in marine propulsion, where panel methods predict lift and cavitation risks for efficient underwater vehicles and turbines.^[60] In wind turbine design, potential flow models simulate blade aerodynamics and wake interactions, aiding in the optimization of rotor efficiency and farm layouts.^[61] In contemporary computational fluid dynamics (CFD), potential flow solutions serve as initializers for viscous simulations, providing stable starting fields that accelerate convergence for high-lift systems and full aircraft configurations.^[62]

Validity Constraints and Extensions

Potential flow theory relies on key assumptions of inviscid and irrotational flow, which impose significant constraints on its applicability. The inviscid assumption neglects viscous effects, such as shear stresses within boundary layers near solid surfaces, leading to inaccuracies in regions where viscosity generates vorticity or causes flow separation, particularly at high angles of attack (α > 15° for airfoils).^[1] Similarly, the irrotational condition (∇ × V = 0) prohibits the modeling of rotational wakes downstream of bodies, failing to capture energy dissipation or vortex shedding in real flows.^[1] These limitations become pronounced in separated flows, where potential theory predicts attached streamlines that do not align with experimental observations of stall or trailing vortices.^[63] A prominent illustration of these constraints is d'Alembert's paradox, which states that steady, inviscid, irrotational flow around a body yields zero net drag, contradicting empirical evidence of finite drag in fluids like air and water.^[64] This paradox arises because potential flow satisfies the no-penetration boundary condition but ignores the no-slip condition enforced by viscosity, resulting in symmetric fore-aft pressure distributions without form drag.^[1] The resolution lies in viscous effects confined to thin boundary layers, where shear stresses produce skin-friction drag and enable flow separation, generating pressure drag on bluff bodies.^[65] Potential flow is valid primarily in regimes where viscous and compressibility effects are negligible. For the inviscid approximation to hold, the Reynolds number must be high (Re ≫ 1), ensuring inertial forces dominate and boundary layers remain thin relative to the body scale.^[63] Compressibility effects are minimal for low Mach numbers (M < 0.3), allowing the incompressible formulation based on Laplace's equation; beyond this, density variations introduce errors in shock-free flows.^[1] In transonic regimes (M ≈ 0.8–1.2), nonlinear potential methods extend validity by incorporating density nonlinearities and weak shocks, as in the transonic small disturbance equation solved via type-dependent schemes.^[66] Extensions to potential flow address these constraints through viscous-inviscid interactions and computational hybrids. Prandtl's 1904 boundary layer theory couples inviscid outer flow with a viscous inner layer, resolving drag via transpiration velocities that account for displacement thickness, though it singularizes at separation points.^[64] Developments in the 1940s, such as Goldstein's analysis of singular behaviors near separation, led to interactive schemes like full-potential/boundary-layer coupling, where iterative transpiration enforces compatibility and handles mild separation in transonic airfoils (e.g., RAE 2822 at M = 0.73, Re = 6.5 × 10^6).^[67] Modern computational extensions integrate potential flow into hybrid CFD solvers, using it for efficient inviscid predictions while overlaying viscous corrections via Navier-Stokes modules, achieving balanced accuracy and speed in aerodynamic analyses.

References

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Potential Flow Theory – Introduction to Aerospace Flight Vehicles
A potential flow assumes the aggregate of an incompressible, irrotational, and inviscid fluid motion, i.e., which is called an “ideal” flow.
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Potential Flow - an overview | ScienceDirect Topics
Potential flow is defined as a type of fluid flow that is characterized by being incompressible, irrotational, and inviscid, where the vorticity is zero and ...
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[PDF] Potential Flow Theory - MIT
We can define a potential function, ( ) xzt. φ , , , as a continuous function that satisfies the. basic laws of fluid mechanics: conservation of mass and ...
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Irrotational Flow - Richard Fitzpatrick
This scalar function is called the velocity potential, and flow which is derived from such a potential is known as potential flow. Note that the velocity ...Missing: dynamics | Show results with:dynamics
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[PDF] Incompressible, Inviscid, Irrotational Flow
For this reason irrotational flow is often called potential flow ... These are the governing equations of planar, incompressible, inviscid, potential flow and we ...
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3. Chapter 3: Potential Flow Theory
Potential flow refers to the movement of a fluid (such as water or air) that relies on assumptions that are consistent with no viscosity or turbulence.
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[PDF] Hamiltonian Fluid Dynamics - UT Physics
Lagrange, in his famous work of 1788, Mécanique Analytique, produced in essence a variational principle for incompressible fluid flow in terms of Lagrangian ...
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[PDF] An Introduction to Theoretical Fluid Dynamics - NYU Courant
12 Feb 2008 · The Lagrangian description of a fluid emerges from this focus on the fluid properties associated with individual fluid particles. To “think ...
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Between the two extremes of sluggish creeping flow at low Reynolds number and lively ideal flow at high, there is a regime in which neither is dominant.
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Potential flows are basic ideal flows, irrotational and incompressible, described by streamfunction and velocity potential, governed by the Laplace equation. ...
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[PDF] Compressible Potential Flow
approximate U. 2. /c. 2 by M. 2 where M is the Mach number of the upstream flow. Thus the governing equation becomes. (1 − M2. ) ∂. 2 φ. ∂x. 2. 1. +. ∂. 2 φ. ∂x.Missing: nonlinear Laplace
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The flow is determined once the distribution of mass sources and vorticity sources are specified. Notice that this theory of potential flow is exactly analogous ...Missing: dynamics | Show results with:dynamics
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Dirichlet boundary conditions specify the function on the boundary, while Neumann con- ditions specify the normal derivative.
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Mathematically, we seek the potential which: [1] Obeys the 3D Laplace equation. [2] Is single-valued, non-singular, and smooth as a function of θ. [3] Is well ...
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Feb 24, 1998 · The general derivation of the integral equation for the potential solution of Laplace's equation is given in Section 4.3. Complete details ...
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So, a solution for the potential flow problem is. (2.34). Φ(ρ, φ) = U cosθ ρ + a3. 2ρ2. Uniqueness follows from the uniqueness of solution to Laplace's equation ...
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Prandtl's key equation comes in found in equation 10 in the original manuscript. (reproduced here as equation 1):. 1. 0. (1). This equation provides a ...
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[PDF] AE 6030: Advanced Potential Flow, Class Notes
Apr 6, 2003 · This is the unsteady Bernoulli equation. If we replace f by *-S#(t ... The Laplace equation describes unsteady potential flow is r is constant. In ...
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Modern Developments in Transonic Flow - jstor
A survey is given of transonic small disturbance theory. Basic equations, shock relations, similarity laws, lift and drag integrals are derived. The airfoil ...
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[PDF] Shock-Fitting for Full Potential Equation - DTIC
In the following we first discuss unsteady transonic flow equations and their weak solutions. Then, the tlme-dependent equations describing the iteratlve ...
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[PDF] AIAA 95-0741 - Virginia Tech
The nozzle problem shows that the potential flow model cannot re- spond to a change in exit, or downstream, pressure by ad- justing the shock location. This ...<|control11|><|separator|>
[30]
None
Below is a merged summary of the governing equations for unsteady compressible potential flow, consolidating all information from the provided segments into a single, comprehensive response. To maximize detail and clarity, I will use a table in CSV format to organize key components (e.g., governing equations, density relations, and sources) while retaining narrative explanations where necessary. The response avoids redundancy and ensures all unique details are included.
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[PDF] Linearized Compressible-Flow Theory for Sonic Flight Speeds - DTIC
velocity potential of the field satisfies the well—known wave equation in three space dimensions: i^t't' - <Pxx - <Pyy " ^z = °. <15). Equation (15) is ...
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[PDF] €OMPRESSIBtE AERODYNAMICS - NASA Technical Reports Server
* A general theory of potential aero- dynamic flow around a lifting body having arbitrary shape and motion is presented here. The theory is based upon the ...
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New Look at Unsteady Supersonic Potential Flow Aerodynamics ...
Piston theory, as first suggested by Lighthill [1] and developed into an effective and widely used unsteady aerodynamic tool by Ashley and Zartarian [2], ...Skip main navigation · Introduction · II. Classical Unsteady...
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[PDF] Potential Flows
Any differentiable complex function F(z) is the complex potential for a 2D incompressible potential flow. Further dF/dz = W is the complex conjugate velocity.
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Complex Velocity Potential - Richard Fitzpatrick
The complex velocity potential (6.32) corresponds to uniform flow of unperturbed speed $ V_0$ , running parallel to the $ x$ -axis, around an impenetrable ...Missing: method | Show results with:method
[36]
Cauchy-Riemann Relations - Richard Fitzpatrick
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[PDF] 6 Two dimensional hydrodynamics and complex potentials
We'll start by seeing that every complex analytic function leads to an irrotational, incompressible flow. Then we'll go backwards and see that all such flows ...
[38]
[PDF] Fluid flow We associate a complex function v(z) = v1 (z)+
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[PDF] F Laplace's equation: Complex variables
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[42]
Velocity Potentials and Stream Functions
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[PDF] Joukowski Airfoils
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[PDF] Planar Rankine Half-Bodies
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[PDF] Potential Flow around a Cylinder
the drag on the cylinder in potential flow is identically zero. This is, again, an example of D'Alembert's. Paradox which states that the drag on any finite ...
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The result of zero drag (3) is known as d'Alembert's Paradox, since it's in direct conflict with the observation that D′ > 0 for all real bodies in a uniform ...
[50]
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The complex potential for a simple source. 8.20. Combination of sources and streams. 8-21. Source in a uniform stream. 8-22. Source and sink of equal strengths.
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[PDF] Hydrodynamics
MACMILLAN AND CO. Page 7. HYDRODYNAMICS. BY. HORACE LAMB, M.A.,. F.R.S.. PBOFESSOB OF MATHEMATICS IN THE OWENS COLLEGE,. VICTORIA UNIVERSITY, MANCHESTER ...
[52]
Axisymmetric Irrotational Flow in Spherical Coordinates
$$ +1$ are known as the Legendre polynomials, and are denoted the $ P_l(\mu$ ), where $ l$ is a non-negative integer (Jackson 1962). (If $ l$ is non-integer ...Missing: potential papers
[53]
Review of integral-equation techniques for solving potential-flow ...
The numerical problems are those associated with efficient calculation of the relevant “influence” matrices and with the solution of the resulting equations, ...
[54]
[PDF] 1 CALCULATION OF POTENTIAL FLOW ABOUT ARBITRARY ...
Apr 4, 2019 · Numerically, integral equations of the second kind are considerably more tractable. For example, if the integral equation is approximated by a ...
[55]
[PDF] Potential Flow Rround Two-Dimensional Airfoils Using R Singular ...
The problem of potential flow around two-dimensional airfoils is solved by using a new singular integral method. The potential flow equations for ...<|control11|><|separator|>
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[PDF] 19830006993.pdf - NASA Technical Reports Server (NTRS)
The Kutta-Joukowski condition only pertains to the steady, incompressible potential flow around a two-dimensional airfoil having e cusped trailing edge.
[57]
[PDF] Nl\SI\ - NASA Technical Reports Server (NTRS)
UNSTEADY LIFTING-LINE THEORY AS A. SINGULAR PERTURBATION PROBLEM. Prandtl's lifting-line theory (Prandtl (1918» 'was the first successful attempt to solve the ...
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[PDF] historical evolution of vortex-lattice methods
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[60]
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[61]
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Jan 30, 2013 · Potential flow modeling of wind turbine aerodynamics has grown in popularity and offers a compromise between blade element momentum ...
[62]
[PDF] Reflections On Using Potential Flow Codes to Design High-Lift ...
This study showcases how low-order computational aerodynamic techniques can support conceptual as well as preliminary design of aircraft.
[63]
[PDF] 4 Flow at high Reynolds number
First we need to determine the Euler limit of the flow, i.e. potential flow. It makes sense to assume potential flow since the flow arrives from far upstream ...
[64]
[PDF] 1 Short History
The paradox is considered to have been resolved by Ludwig Prandtl in 1904 who, in the short report Motion of fluids with very little viscosity, introduced the ...<|control11|><|separator|>
[65]
[PDF] Chapter 9: Surface Resistance - Stern Lab
Bluff body flow: flow around bluff bodies with flow separation. ... For 3D flow, in addition it must also be explicitly ... Potential Flow Solution: θ.
[66]
[PDF] Transonic flow computations using nonlinear potential methods
Mach number contours about an airfoil showing a typi- cal two-dimensional transonic, inviscid flow field compuled us- ing a full potential algorithm. Fig. 2 ...
[67]
[PDF] Some Experiences with the Viscous-Inviscid Interaction Approach
The dual-potential equations are solved throughout, while in viscous flow regions, the boundary-layer equa- tions are also solved to resolve the vorticity, ...
[68]
Computational Fluid Dynamics and Potential Flow Modelling ... - MDPI
Findings suggest that a combined CFD-potential flow approach offers a perfect balance between accuracy and computational efficiency, offering valuable insights ...Missing: initialization | Show results with:initialization