MCQ Bank
Laplace partial differential equation is a type of…………………. partial equation.
- A) None of these
- B) Elliptical
- C) Parabolic
- D) Hyperbolic
Which of the following is a key disadvantage of the Crank–Nicolson scheme compared to Forward Time Central Space (FTCS) scheme?
- A) It cannot handle boundary conditions
- B) It requires solving a system of equations at each time step
- C) It is conditionally stable
- D) It is only first-order accurate in time
Which of the following discretized factor is utilized to check the stability of finite difference scheme in Fourier transform,
- 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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.
Which of the following best describes the purpose of stability analysis in numerical solutions of PDEs?
- A) To ensure that errors do not grow uncontrollably during iterations
- B) To minimize computational time
- C) To verify boundary conditions
- D) To determine the exact solution of the PDE
The Fourier method for stability analysis of PDEs is mainly used to:
- A) Optimize the grid spacing
- B) Determine whether numerical errors grow, decay, or remain bounded over time
- C) Solve the PDE analytically
- D) Approximate boundary conditions
The Crank–Nicolson scheme is preferred over Forward Time Central Space (FTCS) scheme for time-dependent PDEs because:
- A) It is second-order accurate in both time and space and unconditionally stable
- B) It only works for nonlinear PDEs
- C) It does not require a grid
- D) It is explicit and easier to implement
In Gauss–Seidel’s method, the value of each grid point is updated using:
- A) Only boundary values
- B) A weighted average of the original matrix values
- C) Only values from the previous iteration
- D) Both newly updated values and some old values
data:image/png;base64,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
- A) equal
- B) less
- C) more
- D) none of these
data:image/png;base64,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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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
data:image/png;base64,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
- A) Central difference
- B) Crank-Nicolson scheme
- C) Backward difference
- D) Forward difference
data:image/png;base64,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
- A) Liebmann's
- B) Gauss Jordan
- C) Newton's
- D) Gauss elimination
data:image/png;base64,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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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 .
data:image/png;base64,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
- A) Reduction
- B) None of these
- C) Iteration
- D) Elimination
data:image/png;base64,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
- A) Central difference
- B) Backward difference
- C) Crank-Nicolson scheme
- D) Forward difference
data:image/png;base64,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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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 .
data:image/png;base64,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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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 .
data:image/png;base64,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
- A) Secant method
- B) Iterative method
- C) Newton's
- D) Gauss Seidel method
data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA3YAAABJCAIAAAD+CyM/AAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAACGaSURBVHhe7Z1reV05skBDYTCEgjkMhGAIhTBoBs0gCIKgCYRAGITD3JWz5LrlkvbD9rbbiWv9OJ9KKtVLj6125n73w/+apmmapmma5lL6idk0TdM0TdNcTD8xm6ZpmqZpmovpJ2bTNE3TNE1zMf3EbJqmaZqmaS6mn5hN0zRN0zTNxfQTs2mapmmaprmYfmI2TdM0TdM0F9NPzKZpmqZpmuZi+onZNE3TNE3TXEw/MZumaZqmaZqL6Sdm0zRN0zRNczFPf2L+9ddfHz58+P79+5Bfhtfx8jY5zP3nz5+fPn1CB1AevW8b0rm7uyPg//znP9++fRu9zfuAdWfHDqF5yD///EN9/v777yGf4L///S/naAgr5uNGD7Ps+fr1q2pN8964/C56/bfKE26M8xzeLSdZPzG9g7bwNWNBSdIpL0Tx4ovqNVdxH9f4hb6ahxW2Gp8/f0bzy5cvo/dtw64FooXlF+7Hjx9k9PHjR1JDkzYv6TF2w6EAHepwuA/5vo4JN5z12I30K/QrTt21nEntZNFYkaHxkKtOHKa4W4bQPMTLxNv1JF7UQ1jtT3s4a5wjj5s7YecANq+JCzSEV8Sd86JfUp4+uHihB9DzIba4i6gDIlei4tN4nRdR5gk3xnnK3fJk1ia4eohb9OQ7RiwijVcoaPHCJkB80YOxA3dBbEpxjZ+5Nbc4rDCjd3d3Q/gdsFx824Y8wfvSOxcd0vdzSI75lUkPMCpuCaBRHqMZNNFh+fIsHD1qAxvbEN4MZ1KjB1SAraIxRGeYCnYK+yg0PoQ/Aj9OlGjIz8DT8ShTFJMpQ5j253zcOF/0sOhDbv5typK9BD71ykXnzuknpu13/sRkB87Xcrlbnsyxia3CvU5BX3/ZdiCSeSVejv3c/Vq8ZjzPxz+S7RwJks2PHhq+MvOfWxBhCDcohf8auPN4tZjZtTcg9of823ImNUQYwo1l0WZT14Lx32vHHsKOvapiTzC1/xmYj9uF0Ta/Cyw3i771HXm3UJNr76LXr/NVx3lZiv275Tz9xHwEy5V4OfZzd3u9ZjzPx4z4HfIJeACVKYgwhHt4jPKfYvTzchpdD1m6dspVf6L7tziTGm2wHcxFW5q6EIz/Xjv2EI/hJRV7gqn9z8C8mhdG2/wuuA22viPvFmpy7V30+nW+6jgvS7F/t5zngicmDT9Ud3d38/8BB/8l7R9LthQyfPN4Umjt48ePKBfvivHnffQ/f/6sPr+07RemL11rhLkWMf7YQw9D/tkMPqX/QRuW7VzCLNWYMrruyX97J4tQwEvMksPcM0ae8ZVQUiDr/Pc/0OacOyJgJCIkZdQ0aFQo7P/Dispb3u0MwvU+J5+YMGtmTLyMkhGdkRTpx3YCSlGKjz6jQ7j980pe0PxPQrkO6OSH76EXOplOp7sXTddiDE+cSY022M6Uoi1NbUF4uRrgMclnnGTpwYsibXeR4S1Ty/WZFYyQnjgs+Whvway8HHkb759K4gRCCp08PWwGsQdoY4r9b5AeBH1tpcaos4Y8kcMgqijjGH64P1XbR82TBdcXKY+B3bvdXPilIFZpri2Qwlbx8YgYFc5ln1F5KxggeCygFpmiQ3hj+D5gXDBRO6ixx3IpMALoGBWm7M8FBByFZZTpYZYioIxm9NBAtA2/HDz+HsYd+o7yGyuInZuNTZwuO1kIncRAZ9QnHC2xpCdvxYyRbC29Zg9Xiln0REZluYFO1IZwE5kyhBs72xswHlcQoTJKdrSLl8wLVZgpeLdccykANXwxqgI2o/K07Q+iCBQH0RrGUNl4Z1h8dQpbhbOfiM0KbmE8+DOSwREryihYhbJUGbNS36I4JbyXYFwJvNDPL5HYD2oynQZoJw8x11FrSilna2A6eHRWGBQTpHEzPNTE+GPB2K95ur6oiaNwmHsGa7oOg8QfKZSCozmmbeQOTKGHfJ0bwaBJJ6Z0RxsvTikces9maeerZwdt5j2DCENIUCj6MT7kh+CRUX6HfIN0whSHR5GAUeNX0ceBGL9tNgYKQKboU8lwTQ9qpmkdYhHPeEHMlbQdZZxBBwV+h3xDs0M4XbSlqS0ICeW8P11xUh7y/T/Zx/LRNrCt1KwPRFVRQG0Mpw2sDiBCvnYK+EIhloOJke+ZU+m5UCcOpqNxDDUOcQXTGdlhEE2GnIuIZkSlPrgWDA35IZwvwtAgOlbAnqHxcH9mF7SlRIva+YJHBezPppjLKGIstLlEBdAx1LzP1QnXRut2isvEufzeYhy38Yxh82swaIYpwTgR0m8WBg+xXnPAZhT5QhiJrOm0gDHLUBEjU2OL6840w6+ibSguHOWXwOjEo5HTjnt4f19Fj+EFZqcOHGYBiNYHg+hErcbwhCVFU5HwYi5tAsgLlME1RCTMQox8H7VS/IYRiLIDYlQJiuiUHC1i/gwxFAousTpbSb1chbPZuRTYV8ftYaiIlgILdNJjoSByNEE0HYocHT3P4qtTwDqm58LZTxVi7f2ckImi+ecCoUmIW1GqT2JDvv0Z0vKF9xwM1012l8ERQziK2CDWUiNl1M683h7dHD9iDg+MmblDTlAZgvdOxBHtXCtwzVQ4k3thnmIKc8HpjKO1zB3cT3muE3PMjNKTj1nmvPdluZaYI0aGfIMeGEJiLkhmdu12jYCtwLwBWIUh3+vY9uguq0HA1G0IDznjBTHrRBnLkgWHqcEviyeKpilEGkEsX4HcUUZB0fPI3Jy7mzwipw07qTGdUmSP5hJTcIeYt2W5dgoGme9cJrpqNPZPJbheuZIqxLpbwChCQCcQ25Bv9Sm7BdfohPctU2LiedQeGPLD/QnzlNnFyYKzTLlK2pkPOyiqkC27z/PeMP3smllWXqfzMckeM2jm8Fz0vCXmdTTN2BhzwGZEZ/RoJO8lsHMOFVOK2KENNFBjqNSfniGs4jSGvEsZpSf20uG+spgkqChLvztZAGLWifqEo4IljWRRzqu/Qz41wDpip5w4AjtcqZ3lBkTUhvBQ1EWergtQVCFPJzxCorPUOXi5Cu+UApHRrACHpRADzkUoV99JFl+dwnKDwtxPPjlWdwb5oBOU3Z8pO0nsZKJicUrtKGgun8wnOaOR5bG8xfj/0JNPBWJZCXVmR7qIo4IvRFZLs5JvijO5F+hnNMez3I7up4hwmTu4n4Zww/Cyd7OYk5Xz3rcsFDClzVIBemAIibkgGV0zSgPMl/1jwD6P5hvQQxUB5Cp5QdAzb+ato3jSi2Zty/5O2E9N6IEhJErRNFWIbTyDl0iHQ4foJvGhAPTs32U5NQKmjUHEwC2EmvpGSL8iOKuYDeZtHBjqzqkEi2lbyilgShYDOueFLpRctkwJ1hgtm83OIUzRaj8bLC7OF7xsZlcNzTHnRo4QkXbJJUfrWdhaNTU1G9BD/9A4ohif1xHoYX/a1n4J2Nxj/2skL8HJE+2eoRN33Gl2SglsjvOx9zAYdkwpomRHL3Qv0c9oxKm1spHOUOwUUcyxrJTtgJ5YbkDM6WTxcHursDwUaA458ToVllwKH0IYcSigDvQPYeUX5hoebrwldRlmjHhOctmfYzXEJfOjENQvBouXIvpVo4e58faHrZhlK/IlO5sSMEInBod8w8dH3k96XOJWOJN7Qdc5HsR5E6vGPaW4ZdMAhnBj1tRUSTZg6KT3LQsF79ZZmU4YQkJfHNohP0TXARc9By++Fs6dj6KzYmuVKnn+gVBzodgAPo75ZX0f64V22WYqZBeZ/dTEoSEkStE0xa/iIa6RvmhjhzY95uJByAcTcSc1g1lSIiyloKeYDeaNHZS6ZXa+VQYZJSpiQOccEsXBMoViCNwkkcuWKWEIhnAPRnJnEU0wG1wGv2S/4Dpa4t2+zCWHdybZmX
- A) data:image/png;base64,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
- B) data:image/png;base64,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
- C) 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==
- D) data:image/png;base64,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
The PDE \frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = 0 is _______________
- A) Elliptic
- B) Parabolic
- C) Hyperbolic
- D) Non-linear
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