Adjoint Equation
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An adjoint equation is a
linear differential equation In mathematics, a linear differential equation is a differential equation that is defined by a linear polynomial in the unknown function and its derivatives, that is an equation of the form :a_0(x)y + a_1(x)y' + a_2(x)y'' \cdots + a_n(x)y^ = b( ...
, usually derived from its primal equation using
integration by parts In calculus, and more generally in mathematical analysis, integration by parts or partial integration is a process that finds the integral of a product of functions in terms of the integral of the product of their derivative and antiderivative. ...
. Gradient values with respect to a particular quantity of interest can be efficiently calculated by solving the adjoint equation. Methods based on solution of adjoint equations are used in
wing shape optimization Wing-shape optimization is a software implementation of shape optimization primarily used for aircraft design. This allows for engineers to produce more efficient and cheaper aircraft designs. History Shape optimization, as a software process and ...
, fluid flow control and
uncertainty quantification Uncertainty quantification (UQ) is the science of quantitative characterization and reduction of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system a ...
. For example dX_t = a(X_t)dt + b(X_t)dW this is an Itō stochastic differential equation. Now by using Euler scheme, we integrate the parts of this equation and get another equation, X_ = X_n + a \Delta t + \zeta b \sqrt, here \zeta is a random variable, later one is an adjoint equation.


Example: Advection-Diffusion PDE

Consider the following linear, scalar advection-diffusion equation for the primal solution u(\vec), in the domain \Omega with
Dirichlet boundary conditions In the mathematical study of differential equations, the Dirichlet (or first-type) boundary condition is a type of boundary condition, named after Peter Gustav Lejeune Dirichlet (1805–1859). When imposed on an ordinary or a partial differential ...
: : \begin \nabla \cdot \left(\vec u - \mu \nabla u \right) &= f, \qquad \vec \in \Omega, \\ u &= b, \qquad \vec \in \partial \Omega. \end Let the output of interest be the following linear functional: : J(u) = \int_\Omega g u \ dV. Derive the weak form by multiplying the primal equation with a weighting function w(\vec) and performing integration by parts: : \begin B(u, w) &= L(w), \end where, : \begin B(u, w) &= \int_\Omega w \nabla \cdot \left(\vec u - \mu \nabla u \right) dV \\ &= \int_ w \left(\vec u - \mu \nabla u \right) \cdot \vec dA - \int_\Omega \nabla w \cdot \left(\vec u - \mu \nabla u \right) dV, \qquad \text \\ L(w) &= \int_\Omega w f \ dV. \end Then, consider an infinitesimal perturbation to L(w) which produces an infinitesimal change in u as follows: : \begin B(u + u', w) &= L(w) + L'(w) \\ B(u', w) &= L'(w). \end Note that the solution perturbation u' must vanish at the boundary, since the Dirichlet boundary condition does not admit variations on \partial \Omega. Using the weak form above and the definition of the adjoint \psi(\vec) given below: : \begin L'(\psi) &= J(u') \\ B(u', \psi) &= J(u'), \end we obtain: : \begin \int_ \psi \left(\vec u' - \mu \nabla u' \right) \cdot \vec dA - \int_\Omega \nabla \psi \cdot \left(\vec u' - \mu \nabla u' \right) dV &= \int_\Omega g u' \ dV. \end Next, use integration by parts to transfer derivatives of u' into derivatives of \psi: : \begin \int_ \psi \left(\vec u' - \mu \nabla u' \right) \cdot \vec dA - \int_\Omega \nabla \psi \cdot \left(\vec u' - \mu \nabla u' \right) dV - \int_\Omega g u' \ dV &= 0 \\ \int_ \psi \left(\vec u' - \mu \nabla u' \right) \cdot \vec dA + \int_\Omega u' \left(-\vec \cdot \nabla \psi \right) dV + \int_\Omega \nabla u' \cdot \left( \mu \nabla \psi \right) dV - \int_\Omega g u' \ dV &= 0 \\ \int_ \psi \left(\vec u' - \mu \nabla u' \right) \cdot \vec dA + \int_\Omega u' \left( - \vec \cdot \nabla \psi \right) dV + \int_ u' \left( \mu \nabla \psi \right) \cdot \vec dA - \int_\Omega u' \nabla \cdot \left( \mu \nabla \psi \right) dV - \int_\Omega g u' \ dV &= 0 \qquad \text \\ \int_\Omega u' \left -\vec \cdot \nabla \psi - \nabla \cdot \left( \mu \nabla \psi \right) - g \rightdV + \int_ \psi \left(\vec u' - \mu \nabla u' \right) \cdot \vec dA + \int_ u' \left( \mu \nabla \psi \right) \cdot \vec dA &= 0. \end The adjoint PDE and its boundary conditions can be deduced from the last equation above. Since u' is generally non-zero within the domain \Omega, it is required that \left -\vec \cdot \nabla \psi - \nabla \cdot \left(\mu \nabla \psi \right) - g \right/math> be zero in \Omega, in order for the volume term to vanish. Similarly, since the primal flux \left(\vec u' - \mu \nabla u' \right) \cdot \vec is generally non-zero at the boundary, we require \psi to be zero there in order for the first boundary term to vanish. The second boundary term vanishes trivially since the primal boundary condition requires u' = 0 at the boundary. Therefore, the adjoint problem is given by: : \begin -\vec \cdot \nabla \psi - \nabla \cdot \left( \mu \nabla \psi \right) &= g, \qquad \vec \in \Omega, \\ \psi &= 0, \qquad \vec \in \partial \Omega. \end Note that the advection term reverses the sign of the convective velocity \vec in the adjoint equation, whereas the diffusion term remains self-adjoint.


See also

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Adjoint state method The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem. It has applications in geophysics, seismic imaging, photonics and more recently in neural net ...
*
Costate equations The costate equation is related to the state equation used in optimal control. It is also referred to as auxiliary, adjoint, influence, or multiplier equation. It is stated as a vector of first order differential equations : \dot^(t)=-\frac where ...


References

* Differential calculus {{Mech-engineering-stub