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DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-6-luna)
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Finite-dimensional backward-Euler diffusion transmission model

Definition

Let I1,I2 and the common trace space Λ be finite-dimensional real inner-product spaces, with dim⁡Λ≥1, and set Xi:=Ii⊕Λ. The trace map is γi(xi,λi)=λi. Let Mi and Ai be self-adjoint positive-definite operators on Xi, let Δt>0, and define the local backward-Euler block Bi:=Δt−1Mi+Ai. In coordinates Ii⊕Λ, write

Bi=(Bi,00Bi,0ΓBi,Γ0Bi,ΓΓ),gi=(gi,0,gi,Γ).

For a prescribed local trace λi, solve the interior equation Bi,00xi+Bi,0Γλi=gi,0 and define the outward algebraic interface flux qi:=Bi,Γ0xi+Bi,ΓΓλi−gi,Γ. Eliminating xi gives qi=Siλi−fi, where Si:=Bi,ΓΓ−Bi,Γ0Bi,00−1Bi,0Γ and fi:=gi,Γ−Bi,Γ0Bi,00−1gi,0. The sign convention is outward flux on each subdomain.

The monolithic interface equations are trace continuity λ1=λ2=λ and flux balance q1+q2=0, equivalently (S1+S2)λ=f1+f2. These finite-dimensional matrices represent a linear diffusion-transmission step; no nonlinear fluid-structure well-posedness is asserted.

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