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Dirichlet boundary condition

In the field of partial differential equations (PDEs), a Dirichlet boundary condition specifies the exact value of the solution function on the boundary of the domain, distinguishing it from other types like Neumann conditions that prescribe derivatives instead.^[1] This condition ensures the problem is well-posed by providing sufficient constraints for uniqueness and existence of solutions, particularly in elliptic PDEs.^[2] Named after the German mathematician Peter Gustav Lejeune Dirichlet (1805–1859), the concept emerged from his investigations into potential theory during the 1830s and 1840s, where he analyzed harmonic functions—solutions to Laplace's equation—with prescribed boundary values to model gravitational and electrostatic potentials.^[3] Dirichlet's foundational work, including papers on multiple integrals and the attraction of ellipsoids published around 1839, laid the groundwork for the Dirichlet problem: finding a harmonic function u in a domain \Omega such that \Delta u = 0 inside \Omega and u = f on the boundary \partial \Omega, for a given continuous function f.^[4] This formulation addressed longstanding challenges in solving boundary-value problems for Laplace's equation, building on earlier contributions from figures like Carl Friedrich Gauss and Siméon Denis Poisson.^[4] The Dirichlet boundary condition plays a central role in diverse applications across physics and engineering, often modeling scenarios where boundary values are directly controlled or measured. In heat conduction, it represents fixed temperatures on surfaces, such as the ends of a rod maintained at constant values, leading to solutions via separation of variables for the heat equation u_t = k u_{xx} with conditions like u(0, t) = a and u(L, t) = b.^[2] In electrostatics, it specifies fixed electric potentials on conductor surfaces, as in the case of a grounded cavity where \Phi = 0 on the boundary, enabling the computation of electric fields through \mathbf{E} = -\nabla \Phi.^[5] Similarly, in fluid dynamics and quantum mechanics, it models impermeable walls or infinite potential barriers, respectively, ensuring realistic simulations of confined systems.^[6] Historically, the Dirichlet problem's solution methods evolved significantly after Dirichlet's era; for instance, Bernhard Riemann's 1857 principle of minimization faced challenges from Karl Weierstrass in 1870, prompting David Hilbert's rigorous validation in 1901 using compactness arguments.^[4] Later advancements, such as Oskar Perron's 1923 method using superharmonic functions and Norbert Wiener's 1924 criterion for boundary regularity, resolved issues with irregular boundaries and discontinuous data, making the condition applicable to complex geometries.^[4] Today, numerical techniques like finite elements routinely incorporate Dirichlet conditions for engineering simulations, underscoring their enduring importance in computational mathematics.^[1]

Mathematical Formulation

For Ordinary Differential Equations

Boundary value problems (BVPs) for ordinary differential equations (ODEs) differ from initial value problems (IVPs) in that conditions are specified at multiple distinct points, typically the endpoints of an interval, rather than at a single initial point.^[7] In BVPs, Dirichlet boundary conditions prescribe the value of the solution function itself at these boundaries, as opposed to conditions involving derivatives.^[8] A canonical example is the second-order linear BVP given by the equation

-u''(x) + q(x)u(x) = f(x), \quad x \in [a, b],

subject to the Dirichlet conditions u(a) = \alpha and u(b) = \beta, where \alpha and \beta are prescribed constants, q(x) is a given function, and f(x) is the forcing term.^[9] This formulation arises frequently in Sturm-Liouville theory, where the operator is self-adjoint, and the conditions ensure the problem is well-defined on the finite interval.^[9] For higher-order ODEs, the general Dirichlet-type conditions extend to separated forms at distinct points. Consider an nth-order linear ODE

L[u](x) = f(x), \quad x \in [a, b],

where L is a linear differential operator of order n. Dirichlet conditions specify the function values at n distinct points t_1, t_2, \dots, t_n in or on the boundary of the interval, such as u(t_i) = \alpha_i for i = 1, \dots, n, ensuring the conditions are separated (each involving the solution at only one point).^[8] This separated structure facilitates analytical and numerical solutions by decoupling the constraints.^[8] Dirichlet conditions can be homogeneous or non-homogeneous. Homogeneous conditions set the boundary values to zero, e.g., u(a) = 0 and u(b) = 0, which simplify eigenvalue problems in Sturm-Liouville systems.^[9] Non-homogeneous conditions involve non-zero values, expressible via boundary operators like B_1 = u(a) - \alpha = 0 and B_2 = u(b) - \beta = 0, where the operators B_i enforce the prescribed values.^[8]

For Partial Differential Equations

In partial differential equations (PDEs), the Dirichlet boundary condition prescribes the value of the solution function directly on the boundary of the domain. For elliptic PDEs, consider the prototypical case of the Laplace equation \Delta u = 0 in a bounded domain \Omega \subset \mathbb{R}^n with smooth boundary \partial \Omega; the Dirichlet condition requires u = g on \partial \Omega, where g: \partial \Omega \to \mathbb{R} is a prescribed continuous function.^[1] This setup extends to general linear elliptic operators of the form Lu = f in \Omega, with the same boundary prescription u = g on \partial \Omega.^[10] The Dirichlet condition applies analogously to parabolic and hyperbolic PDEs, adapting to the spatio-temporal domain. For parabolic equations, such as the heat equation \frac{\partial u}{\partial t} - \Delta u = 0 in \Omega \times (0, T), the condition is u(x, t) = g(x, t) for all x \in \partial \Omega and t \in (0, T), where g is given on the lateral boundary \partial \Omega \times (0, T).^[11] For hyperbolic equations, exemplified by the wave equation \frac{\partial^2 u}{\partial t^2} - [\Delta](/page/Delta) u = 0 in \Omega \times (0, T), the Dirichlet condition similarly imposes u(x, t) = g(x, t) on \partial \Omega \times (0, T), often paired with initial conditions u(x, 0) = u_0(x) and \frac{\partial u}{\partial t}(x, 0) = u_1(x) in \Omega.^[11] For non-homogeneous Dirichlet problems, compatibility conditions ensure the existence of smooth solutions, particularly at the interface between initial and boundary data in time-dependent cases. These conditions require that the prescribed boundary data g can be extended harmoniously into the domain, such as matching initial values at the corners t=0 on \partial \Omega for parabolic or hyperbolic problems.^[10] In the framework of weak solutions, the trace operator plays a central role: for functions in the Sobolev space H^1(\Omega), the trace T: H^1(\Omega) \to H^{1/2}(\partial \Omega) provides a bounded extension of the boundary restriction, allowing the Dirichlet condition u = g to be interpreted in the sense of traces where g \in H^{1/2}(\partial \Omega).^[12] This operator satisfies \|Tu\|_{H^{1/2}(\partial \Omega)} \leq C \|u\|_{H^1(\Omega)} for a constant C depending on \Omega and the dimension.^[12] The regularity of the Dirichlet data g directly influences the smoothness of solutions. For classical solutions to elliptic or parabolic problems, g \in C(\partial \Omega) (continuous functions on the boundary) is typically required, ensuring u \in C(\bar{\Omega}) or higher classes like C^{k}(\bar{\Omega}) under compatible interior data.^[10] In Sobolev settings, weaker regularity such as g \in H^{s}(\partial \Omega) for s > 1/2 suffices for weak solutions in H^1(\Omega), with higher s yielding improved interior regularity via elliptic or parabolic estimates.^[13]

Theoretical Properties

Existence and Uniqueness

The existence and uniqueness of solutions to Dirichlet boundary value problems are fundamental theoretical properties, particularly for elliptic partial differential equations (PDEs) and ordinary differential equations (ODEs). For the homogeneous Dirichlet problem associated with the Poisson equation, -\Delta u = f in a bounded domain \Omega \subset \mathbb{R}^n with u = 0 on \partial \Omega, the weak formulation seeks u \in H_0^1(\Omega) such that \int_\Omega \nabla u \cdot \nabla v \, dx = \int_\Omega f v \, dx for all v \in H_0^1(\Omega). The Lax-Milgram theorem guarantees the existence and uniqueness of such a solution under the assumptions that f \in H^{-1}(\Omega) (the dual of H_0^1(\Omega)) and \Omega has sufficiently smooth boundary to ensure the Poincaré inequality holds, which provides coercivity of the bilinear form. This theorem applies more broadly to coercive, continuous bilinear forms on Hilbert spaces, establishing a variational framework for proving well-posedness in Sobolev spaces. For the non-homogeneous Dirichlet problem -\Delta u = f in \Omega with u = g on \partial \Omega, where g \in H^{1/2}(\partial \Omega), uniqueness follows if the corresponding homogeneous problem admits only the trivial solution u \equiv 0. This condition holds for the Laplacian on bounded domains with connected boundary, as non-trivial solutions would contradict the maximum principle or energy estimates. Existence can then be established by lifting the boundary data—finding \tilde{g} \in H^1(\Omega) with \tilde{g}|_{\partial \Omega} = g—and solving the homogeneous problem for w = u - \tilde{g}, yielding u = w + \tilde{g}. A key tool supporting uniqueness for elliptic equations is the maximum principle. For the Laplace equation \Delta u = 0 in \Omega with continuous Dirichlet data u = g on \partial \Omega, any solution u \in C^2(\Omega) \cap C(\overline{\Omega}) attains its maximum and minimum values on the boundary \partial \Omega, implying that non-constant harmonic functions cannot achieve interior extrema unless constant. This principle extends to more general uniformly elliptic operators Lu = a^{ij} \partial_i \partial_j u + b^i \partial_i u + c u = 0 with c \leq 0, where subsolutions satisfy L u \geq 0 and achieve non-positive interior maxima only if identically zero, ensuring uniqueness up to boundary data. In the context of ODEs, the Fredholm alternative provides conditions for existence and uniqueness of solutions to linear boundary value problems. Consider the second-order problem -u'' + q(x) u = f(x) on [a, b] with Dirichlet conditions u(a) = u(b) = 0, where q \geq 0. The homogeneous problem has only the trivial solution if 0 is not an eigenvalue of the associated Sturm-Liouville operator; otherwise, solutions exist if f is orthogonal to the eigenfunction corresponding to the eigenvalue 0, and the solution is unique up to multiples of that eigenfunction. This alternative generalizes to higher-order linear ODEs and separated boundary conditions, where the index of the operator determines solvability based on the kernel's dimension.

Stability and Well-Posedness

The concept of well-posedness for boundary value problems, including those with Dirichlet boundary conditions, was formalized by Jacques Hadamard, who specified that a problem is well-posed if it satisfies three criteria: existence of a solution, uniqueness of the solution, and continuous dependence of the solution on the initial or boundary data.^[14] For Dirichlet problems in ordinary differential equations (ODEs), these criteria generally hold under standard assumptions, such as smoothness of the coefficients and data, ensuring robustness to small perturbations. In partial differential equations (PDEs), the Dirichlet problem for elliptic equations like the Poisson equation is typically well-posed in appropriate Sobolev spaces, demonstrating continuous dependence through energy methods. In the context of two-point boundary value problems for linear second-order ODEs with Dirichlet conditions, stability is analyzed via the condition number, which measures sensitivity to perturbations in the boundary data. For instance, consider the problem -u''(x) = f(x) on [0,1] with u(0) = \alpha, u(1) = \beta; the condition number can become large when the homogeneous problem has nearly zero eigenvalues, leading to ill-conditioning where small changes in \alpha cause significant variations in u(1). This sensitivity arises in shooting methods or finite difference discretizations, where the eigenvalue proximity amplifies errors, though regularization techniques can mitigate it for practical computations. For PDEs, such as the Poisson equation -\Delta u = f in a bounded domain \Omega with Dirichlet boundary condition u = g on \partial \Omega, stability is established through a priori energy estimates in Sobolev spaces. Specifically, there exists a constant C > 0 depending on \Omega such that

\|u\|_{H^1(\Omega)} \leq C \left( \|f\|_{L^2(\Omega)} + \|g\|_{H^{1/2}(\partial \Omega)} \right),

which quantifies continuous dependence on the right-hand side f and boundary data g, ensuring the solution remains bounded under small data perturbations. This estimate follows from the coercivity of the bilinear form in the weak formulation and the trace theorem, providing a foundation for numerical stability in finite element methods. However, not all Dirichlet problems are well-posed; counterexamples illustrate instability in the continuous dependence criterion. A prominent ill-posed case is the backward heat equation u_t + \Delta u = 0 for t < 0 in a domain with Dirichlet boundary conditions, where solutions to final-time data at t = 0 exhibit exponential growth of high-frequency modes, rendering the problem unstable to even infinitesimal noise in the data—a phenomenon known as Hadamard instability.^[15] This contrasts with the forward heat equation, highlighting how the direction of time integration critically affects well-posedness in parabolic PDEs with Dirichlet conditions.^[15]

Examples

One-Dimensional Boundary Value Problem

A fundamental example of a one-dimensional boundary value problem with Dirichlet conditions is the homogeneous Laplace equation -u''(x) = 0 on the interval [0, 1], subject to the boundary conditions u(0) = 0 and u(1) = 1. Integrating twice yields u(x) = ax + b. Applying the boundary conditions gives b = 0 and a = 1, so the exact solution is u(x) = x. This linear profile represents the steady-state temperature distribution in a rod with fixed endpoints at 0 and 1, respectively.^[8] For numerical approximation, the shooting method converts this boundary value problem into an initial value problem by guessing the initial slope u'(0) = s and integrating forward to x = 1, then adjusting s iteratively (e.g., via secant method) until u(1) \approx 1. Starting with an initial guess s_0, the solution at the right endpoint is computed using a solver like Runge-Kutta, and the correction \Delta s is found by solving \phi(1; s_0 + \Delta s) = 1, where \phi denotes the integrated solution. This approach is particularly effective for nonlinear problems but requires careful initial guesses to ensure convergence.^[16] Another illustrative case is the eigenvalue problem u''(x) + \lambda u(x) = 0 on [0, \pi] with homogeneous Dirichlet conditions u(0) = u(\pi) = 0. The eigenvalues are \lambda_n = n^2 for n = 1, 2, \dots, with corresponding eigenfunctions u_n(x) = \sin(nx). These form an orthogonal basis for expansions in L^2[0, \pi], arising in applications like vibrating strings fixed at both ends.^[9] In non-homogeneous cases, where boundary values differ from zero (e.g., u(0) = \alpha, u(1) = \beta with \alpha \neq \beta), the solution to the homogeneous equation -u''(x) = 0 qualitatively interpolates linearly between the endpoints, forming a monotonic straight line that rises or falls smoothly without overshoot, reflecting the absence of internal sources or sinks.^[8]

Two-Dimensional Laplace Equation

A classic example of the Dirichlet boundary condition applied to the two-dimensional Laplace equation ∇²u = 0 arises in the unit disk Ω = {(r, θ) | 0 ≤ r < 1, 0 ≤ θ < 2π}, where the boundary values are prescribed as u(1, θ) = 1 for 0 ≤ θ ≤ π (upper semicircle) and u(1, θ) = -1 for π < θ < 2π (lower semicircle). This setup emphasizes the geometric role of the boundary in a rotationally symmetric domain, allowing the problem to be naturally formulated in polar coordinates (r, θ).^[17] The solution is obtained via separation of variables, yielding a Fourier series expansion tailored to the boundary data. Due to the antisymmetric nature of the boundary function across the x-axis, only odd angular harmonics contribute, resulting in the form

u(r, \theta) = \frac{4}{\pi} \sum_{k=0}^{\infty} \frac{r^{2k+1} \sin((2k+1)\theta)}{2k+1}.

The coefficients are determined by the Fourier sine series of the boundary data on the unit circle, ensuring the series matches the prescribed values at r = 1. This approach leverages the completeness of the sine basis for odd functions on [0, 2π].^[17] The Dirichlet condition requires strict conformity to the given boundary values, which the series achieves in the sense of pointwise convergence except at the discontinuities θ = 0 and θ = π. Smooth domains such as the unit disk are essential here, as they prevent singularities in the solution or its derivatives near the boundary; irregular domains could introduce logarithmic or other singularities, complicating the analysis and requiring additional regularity assumptions. Inside Ω, the solution exhibits continuous approach to the boundary values as (r, θ) → boundary point from within the domain, remaining strictly between -1 and 1 by the maximum principle for harmonic functions. Near the center, the behavior reflects the mean value property, with u(0, θ) independent of θ and equal to the spatial average of the boundary data.^[18]

Applications

In Physics

In electrostatics, the electric potential u in a charge-free region satisfies Laplace's equation \Delta u = 0, subject to Dirichlet boundary conditions where u takes a constant value on the surfaces of conductors, reflecting their equipotential nature in electrostatic equilibrium.^[5] This setup models scenarios such as the potential inside a cavity within a conductor, where the boundary potential is prescribed, ensuring the field lines are perpendicular to the conductor surface.^[5] In steady-state heat conduction, the temperature distribution u obeys the equation -\Delta u = 0 within the domain, with Dirichlet boundary conditions specifying fixed temperatures u = g on the boundary \partial \Omega, representing surfaces maintained at prescribed values by external means.^[19] This formulation captures equilibrium states in insulated regions bounded by heat reservoirs, such as a metal plate with edges held at constant temperatures, where heat flow balances to yield a harmonic temperature profile. In quantum mechanics, the infinite square well potential confines a particle to a finite interval by imposing an infinite barrier, leading to the time-independent Schrödinger equation with Dirichlet boundary conditions \psi = 0 at the well's endpoints, which enforces zero probability density outside the well and models perfect reflection.^[20] This idealization illustrates wave function quantization and energy levels discrete due to boundary-imposed confinement.^[20] Peter Gustav Lejeune Dirichlet's foundational 1839 contributions to potential theory established variational principles for solving boundary value problems, directly inspired by physical contexts like electrostatics and heat flow, where minimizing energy functionals yields solutions harmonic in the interior.^[21]

In Engineering

In engineering, Dirichlet boundary conditions are widely applied in numerical simulations to prescribe known values on domain boundaries, enabling the solution of partial differential equations (PDEs) that model physical systems. These conditions are particularly vital in computational mechanics and fluid dynamics, where they ensure accurate representation of constraints like fixed displacements or zero velocities at interfaces. Unlike natural boundary conditions, Dirichlet conditions are enforced as essential constraints in methods like the finite element method (FEM), directly influencing the system's matrix assembly to achieve precise boundary compliance.^[22] A cornerstone application is the finite element method for solving Dirichlet problems, where these conditions are imposed as essential boundary conditions on the Dirichlet part of the boundary, denoted \Gamma_D. In FEM, this enforcement involves modifying the stiffness matrix by setting the rows and columns corresponding to boundary degrees of freedom to enforce u = g on \Gamma_D, where u is the solution variable and g is the prescribed function; the right-hand side vector is then adjusted accordingly to incorporate the boundary values. This approach, standard in engineering software, ensures the numerical solution satisfies the boundary exactly, avoiding weak enforcement errors in stress or flow predictions. For instance, in structural analysis, this matrix modification prevents artificial compliance at supports, improving convergence in iterative solvers.^[23]^[24] In structural mechanics, Dirichlet boundary conditions prescribe displacements in the elasticity equations, modeling fixed supports or clamped edges where zero displacement is enforced on relevant components. This is common in finite element simulations of beams, plates, or trusses, where boundary nodes are assigned zero values for translational degrees of freedom to simulate rigid constraints, directly altering the global system to reflect immobility. Such conditions are essential for predicting deformation under loads, as seen in bridge or aircraft component design, where inaccurate enforcement could lead to overestimated flexibility.^[25]^[26] In fluid dynamics, no-slip conditions on solid walls are modeled using Dirichlet boundary conditions by setting velocity components to zero (u = 0) at the boundary, capturing the viscous adhesion that prevents fluid slippage. This enforcement is critical in computational fluid dynamics (CFD) simulations of pipe flows, aerodynamics, or heat exchangers, where it ensures realistic shear stress development near walls; for example, in Navier-Stokes solvers, boundary velocity fixation maintains mass conservation and momentum balance. Weak variants of these conditions are sometimes used for efficiency on coarse meshes, but strong Dirichlet imposition remains standard for high-fidelity engineering predictions.^[27]^[28]^[29] Modern numerical advancements address irregular boundaries in engineering geometries, such as those in additive manufacturing or biomedical devices, through adaptive meshes that refine near \Gamma_D to handle complex Dirichlet prescriptions. Techniques like octree-based refinement generate hierarchical grids that conform to irregular domains while enforcing Dirichlet conditions via localized matrix adjustments, improving accuracy for problems with curved or fragmented boundaries without excessive computational cost. These methods, integrated into tools like isogeometric analysis, enable efficient simulations of non-standard shapes, filling gaps in traditional uniform meshing for practical engineering workflows.^[30]^[31]

Neumann Boundary Conditions

Neumann boundary conditions specify the value of the normal derivative of the solution on the boundary of the domain. For partial differential equations (PDEs) defined on a domain \Omega with boundary \partial \Omega, the condition is expressed as \frac{\partial u}{\partial n} = h on \partial \Omega, where \mathbf{n} denotes the outward unit normal vector and h is a given function.^[32] In the context of ordinary differential equations (ODEs), such as a second-order boundary value problem on the interval [a, b], Neumann conditions prescribe the derivatives at the endpoints: u'(a) = \gamma and u'(b) = \delta, where \gamma and \delta are specified constants.^[33] A fundamental distinction from Dirichlet conditions, which fix the solution value itself, is that Neumann conditions control the flux across the boundary, enforcing a conservation principle. For the Poisson equation -\Delta u = f in \Omega subject to \frac{\partial u}{\partial n} = h on \partial \Omega, solvability demands the compatibility condition \int_{\Omega} f \, d\Omega = -\int_{\partial \Omega} h \, dS, ensuring the total source matches the net influx through the boundary.^[34] This condition arises from integrating the equation over \Omega and applying the divergence theorem, highlighting the physical interpretation of flux balance.^[34] In physical modeling, homogeneous Neumann conditions \frac{\partial u}{\partial n} = 0 frequently represent insulated boundaries in diffusion processes. For the heat equation u_t = k \Delta u, such conditions at the domain boundary imply no heat flow through the surface, conserving total thermal energy within \Omega.^[35] For elliptic PDEs like the Poisson equation with Neumann boundary conditions, solutions are not unique: if a solution exists under the compatibility condition, any other solution differs by an additive constant, requiring additional normalization (e.g., fixing the average value) for uniqueness.^[36] This non-uniqueness stems from the kernel of the Laplacian operator under Neumann conditions including constant functions.^[36]

Robin Boundary Conditions

Robin boundary conditions represent a hybrid form that incorporates aspects of both Dirichlet and Neumann specifications, providing a linear relation between the solution value and its normal derivative on the boundary \partial \Omega. The general form is given by

\frac{\partial u}{\partial n} + \sigma u = h \quad \text{on } \partial \Omega,

where \frac{\partial u}{\partial n} denotes the outward normal derivative, \sigma > 0 is a positive coefficient, and h is a prescribed function.^[37] This formulation allows for more realistic modeling of boundary interactions compared to pure Dirichlet or Neumann conditions.^[38] The parameter \sigma > 0 typically accounts for physical processes such as convection or linearized radiation at the boundary.^[39] In the limiting cases, the Robin condition recovers the other types: as \sigma \to \infty, it enforces u \approx h/\sigma \to 0 (assuming normalized h), approximating a homogeneous Dirichlet condition; conversely, as \sigma \to 0, it reduces to \frac{\partial u}{\partial n} = h, resembling a Neumann condition.^[40] A prominent application arises in heat transfer problems, where the Robin condition derives from Newton's law of cooling. This states that the heat flux across the boundary is proportional to the temperature difference between the domain interior u and an external environment u_{\text{ext}}, yielding

\frac{\partial u}{\partial n} + k u = k u_{\text{ext}} \quad \text{on } \partial \Omega,

with k > 0 as the convective heat transfer coefficient (assuming unit thermal conductivity).^[41] Here, the outward normal convention ensures consistency with heat loss when u > u_{\text{ext}}. From a theoretical perspective, Robin boundary conditions with \sigma > 0 guarantee uniqueness for solutions to elliptic partial differential equations, such as the Poisson equation, through the coercivity of the associated bilinear form in weak formulations. This well-posedness holds for bounded domains with sufficiently regular boundaries, ensuring stable and unique solutions under standard assumptions.^[42]

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[PDF] A New Derivation of Robin Boundary Conditions through ...
Oct 20, 2015 · While the Dirichlet boundary condition specifies the value of the solution and the Neumann boundary condition specifies the value of the ...<|control11|><|separator|>
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Physical interpretation of Robin boundary conditions - MathOverflow
Apr 27, 2012 · Neumann boundary conditions, for the heat flow, correspond to a perfectly insulated boundary. For the Laplace equation and drum modes, I ...
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The Robin boundary condition for modelling heat transfer - Journals
Mar 27, 2024 · The Robin boundary condition models heat flux as proportional to the temperature difference between a body and a fluid, where ∂U/∂n = K(T-U) on ...
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[PDF] Elliptic and Parabolic Problems with Robin Boundary Conditions on ...
Jun 22, 2010 · This thesis focuses on elliptic and parabolic problems with Robin boundary conditions, investigating existence, uniqueness, regularity, and ...