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• A) data:image/png;base64,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
• B) data:image/png;base64,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
• C) data:image/png;base64,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
• D) data:image/png;base64,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

The boundary conditions u(0,y)=0 and u(1,y)=y for the differential equation \frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = 0 shows that the length of x is

• A) 0.5
• B) 0
• C) 2
• D) 1

The subscript $(i,j)$ of $w$ in the grid (see Fig. below) in Finite Difference Scheme for the solution of a PDE, are_________ data:image/png;base64,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

• A) $(3,3)$
• B) $(1,3)$
• C) $(1,1)$
• D) $(3,1)$

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• A) data:image/png;base64,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
• B) data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAhAAAAA7CAIAAAClliQCAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAoESURBVHhe7Zx/mdU8EIWxgIa1gIeVgAYsrAMc4AAFqwADGFgHeOB7uSfkyzZpmtsfuWk57x88TZq2M5PJnLR3Hz78NsYYYxqwYBhjjGnCgmGMMaYJC4YxxpgmLBjGGGOasGAYY4xpwoJhjDH78/r6+vT09OPHj9C+BBYMY4zZE0Ti+fkZtfjw4YMFwxhjzCwvLy9vb29IhQXDGGPMMhYMY4wxTVgwjDHGNGHBMMYY04QF41/k169fX758eX5+Dm0zGD9//nx6evr+/Xto9+X19fXTp0/8G9pmMD5//sz6fXt7C+2ObBQMbMbyjx8/chOgEIUTD2U3wVB0LlZYKQRM2NevXweZLVOEpUXiUbh7ThPPohjx0IttIa/Ht2/fWMX9txQvLy+URKpHaN8DKY3NCAbH2M+WSP0PZx/BYPHoj46vJBioBR49autq7oXV1VMzeFbPx5kt8BraUzMog5SOlHtlgztg8IDZtY9goKUsHuJyGcFgqqLCX4yNb8rDol0Lu/7QPhLWPzF8yIeOo1lR3U4B+3RcQzlCe2AwElPHLD47CAalR+qNk5cRjAtXhKsKBigJj3btwpsJIICXFAxgP3GKAqXig8KF9khsFQxt6/BNZegygkFF6LNX7c+FBYNsxLWjJ+5Ee9UV4NpVBUM/Kgw+cWxS9Xl/zBW6VTBYnBKJXDC0eiedQC1OezQGGB+6Ho1+vciXjT67QWjfIAJpD65pzLB/OXOXYJzOZRkTGsegmITGX1SMIA2spCX2aOcIDFbPgGBeo2CczmWswpKR5ZDXVoUrMimeD2fT0lJhlWJrMibuqROFCO2bfk56pCtDxUVZni4DgalYzql0k6LtQNpDQWHYOPo3QZOSe1fkdC6rijV6tw7uX0xXaVX6JUHrP+3pYN5GMK+9pJ7L5ZZSI48WOVR1uH/dyAeyXjBUSmLgVIZyP2/h/f8p2oCkPZKQoZaQkiYtiBGditYy5o8z7+2nno68i9FMtQf8XC5jBrYd9/cwil7xq5cencZBWpv2UE+HrQViYnCd07mMbeRqaAyJEmyEF7Ii6wWDNcO+MjTeCwanYjWZvL8zW0BP3I2SW5N84mw9ZRlfmXUl8SKVJOYUA0LjPZPtEotB7sSvMZya7LW5W+VZ25G/c7/Pa15aCBdknMtlnZrLn+3R0B2K99cLdzyFaClQcfFrjxUjCbI2NGZgADEPjb3h5i2kNqeczmXuvPj0Lej+RcKIJRSfuLgidMY4F9GFc3VgL1bGLm4z54gpQuGgqd268kmOaUCeTxxzNo9XCpcUt3h7IZtD4z0yXm/cejfSX+bEueTaybxydsV+gYjltypCKAhIaDSgCKcxr3Mul2Vty03WoegV769TMTNJdQUKp9TDVfFY0Ex3XTlaaOkXnkZYQRjQPsuRu6J3Ope5M4TGkBBMLJzUfcW5XhXvrQPr2C12cmmSHMBOgX7OShvwGdTDWcrKispyNHiBhaHxnrRWMgzj8Sv24Fp9MbRArsRdfPvSbUczpfi3sKPLXJJnCOzoMpcfFDeh6BXvLzWVgwxQWPhXPZzFwUkhOAIs5IkKZvssR+6KXmeX5zxqd5kBEBoluI/G1DkuwSiSHer+ag4XDCJLP2cpNDqrkewgOGCOqT4aCZqt/CYR3Q3Sq3ZHZhQzT8ZjBoWSeZUZ9CDvHNOjdykRrQ3tNhQZDriwnpcyBjAmdDWgq4reFdnRZc4WJ3dHl2UAIhfaeyMD5lJUpyiRhEUe0eRYB+muOTqiYUW4hAHteixYaBig+1duPgdX1adgAuO7uTx3bbvLDKDmhMZ44AUWxjc2oZjwb2hnxMDeVQfWcbhgkDH0s38khwgHPXrlZI5jhkUoQDoV2iWI5tFTrqJTzDwZr7e/OD0c4zjkK43Uv3fBR3jQ4tJVeBXYRjRTRe+K7Ogyg7kkNEpsd5nkucu7FXD/OS8IC8nJ2ZjDxE1O5ZfIVAnwHNxw3df8e2c5ImtDo4GeLtc9WnRZ5WVu7kYgfZuPtFTFFXVgHbsJBqUEi/NKoVmEdNOnnjwECk1dJ5lvMjI0jkG+zC2bm+3vfpTDJHqKVZLO+kxX4J6LS5cBLLDQaGNxXeX8cXgPl4tFJIV7bnSZp3OT0DiGyiNiWGJNxFp6MDhfzESpGMAUrk036e2smGXBVYtTkNLT5bpHiy7X1/UIsMRyF1qqYn1R7Mg+SwtnMBevYLI70CxOSjw9xbzRjNZ1kgFHTzkzhDtzmY0B+Ze04vLQTKdKqdVVJE90Ohc95YYQGm0srqscxq92WeWjSO5dsXNCxWU9/ej9hDwqLmAM41T+ja44mASb20qLfKZozhFG/GXFLAuuWpyClBO5jFwxIDV1NIgPFqYLDVqq4m1N9HhzOnYvdi/MaP1z02JO7IWkvj5Ji7TMdAWuXVy6LWN6UncZU+tpvdFlvZgfnR54x1PqhW+RXFlzcJMxoXEn3VZKO9tdrnu06DJbnD5VdR2KT14AF6sicOHiwtmFsQSD6axvD7csobtg8kivjXtVrOUmoXE/i0kwYFGou8zZjYJRcVlT1qciYCRmbNmrypH6HfBltTsD5sZ2l+se1V3WlHUOiPadobGENlv5RoSA1AtR3fF9GUswcBs5JaX4l2YeCAI396VodzR/9Q1RHWYaaylkK4RHT+dCLg9dWT3Vhjod8HDqLtcFY6PLXDj5bnYouClPQ/tOVL+4nAKhFzL16KxA/7QQVsCFk9A9nO0uM7hSFisuU1I4te7XoNVQOngohPYSUpdcUOnEtVgV1ZO62bMOjCUYClksGRKMNILkU67Ax0EJUwavmwxlDGUlT4IKWkUpschynCa9SmRojEHdZVwrCsZGl6k+t+r9ae5T2BGQEjJm3c6O+JBaXB53JASBHh0DA/B9xX6F0N1C+D9pcXkg213mbDHadZdVTzurBb7gqTQsdFWR78XiNqmKMHGnZx0YSzAmUK+pAqGxYQltgRrEhBXLXGdIF1ZXWhNp9pTP/rS4rJXZOSsiPJcUJVFDewMUFwiNv2WupwT2p4PLFFMSpnMYyVtlhXZCoXceBpPYaSgqPLYODC0Yqahy0FNIB4R8ojiGxt9d+eULyj/iMk6la54mqX7t3cCFXf4jg7fq3ygYd/HYRTG0YET0yolgpJH6Z1GK7LWxPQX/lMt4qj1j3C1dniu5nH4XiYIRe3bkIYviHIJhjDGnIP9BRYTTJ8eCYYwxhxDfMC6DBcMYYw5BgtHtB4YOWDCMMWZ/ftz+N+7b56jrlFkLhjHGmCYsGMYYY5qwYBhjjGnCgmGMMaYJC4YxxpgmLBjGGGOasGAYY4xpwoJhjDGmCQuGMcaYJiwYxhhjmrBgGGOMacKCYYwxpgkLhjHGmCYsGMYYY5qwYBhjjGnCgmGMMaYJC4YxxpgmLBjGGGOasGAYY4xp4Pfv/wBtgtICno1OIwAAAABJRU5ErkJggg==
• C) data:image/png;base64,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
• D) data:image/png;base64,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

The black points are known by the given boundary conditions with a PDE $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = xe^y$, and The pointsdisplayed by the red dots are to be calculated by Finite Difference Scheme. We got a ____________matrix from Finite Difference Scheme data:image/png;base64,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

• A) $3 \times 6$
• B) $3 \times 3$
• C) $9 \times 9$
• D) $6 \times 6$

The Poisson Differential Equation \frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = f(x,y) becomes Laplace Differential Equation when

• A) f(x,y)=0
• B) f(x,y)=xe^y
• C) f(x,y)=1
• D) f(x,y)=e^x

The Partial Differential Equation \frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = xe^y is

• A) Non-Linear
• B) Non-homogeneous
• C) Homogeneous
• D) Heat Equation

The number of grid points along x-axis is n=10, For the solution of a PDE through finite difference method the valu of i=_____________.

• A) 1,2,3,...,9
• B) 0,1,2,3,...,9,10
• C) 0,1,2,3,...,9
• D) 1,2,3,...,9,10

The Partial Differential Equation \frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = f(x,y) is

• A) Legendre Differential Equation
• B) Poisson Differential Equation
• C) Cauchy-Euler Differential Equation
• D) Laplace Differential Equation

The subscript (i,j) of w in the grid (see Fig. below) in Finite Difference Scheme for the solution of a PDE, are_________ data:image/png;base64,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

• A) (1,1)
• B) (3,3)
• C) (1,3)
• D) (3,1)

In the finite difference method for solving the Laplace PDE \nabla^2 u = 0, which of the following approximations is used for the Laplacian \nabla^2 u at a grid point (i,j)?

• A) \nabla^2 u \approx \frac{u_{i+1,j} - 2u_{i,j} + u_{i-1,j}}{h^2} + \frac{u_{i,j+1} - 2u_{i,j} + u_{i,j-1}}{h^2}
• B) \nabla^2 u \approx \frac{u_{i+1,j} + u_{i,j+1} - 2u_{i,j}}{h^2}
• C) \nabla^2 u \approx \frac{u_{i+1,j} - u_{i,j}}{h} - \frac{u_{i,j} - u_{i-1,j}}{h}
• D) \nabla^2 u \approx \frac{u_{i+1,j} - u_{i,j}}{h} + \frac{u_{i,j+1} - u_{i,j}}{h}