mate0 发表于 2023-9-26 11:08:09

水工设计软件下载及教程

AutoBank7.7 水工设计软件和视频教程:

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1.渗流分析
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Z8YTcEG4e1wdd2EIgAxjLIC+deZAVGXweM58TPf9dl912nIR/TGMEyx0gi7JYjhMenPyN0LPJxzivshqSR2DkQCUIAfRF2GNeJnn9dZtfl9l2fIR/PWLEyt0gKKeos4m4ZFhl5wYbdXsLOyOuq4+ONbKNvso3cmHNP9GIHsQegDfkBMzJZgdHXAeMZ+PnXZXVdXp/bWkM+FqKuOcJumUKJO8uNvFlH0eLCrkWwpbc4yhN2Pr7Y0/GdDAAokx9EDvm5hIGkmxRHyIYaalv1WU7fddDbD/U4NFJ0WURdMyFGnQptRiukwFMvMuzPldkF0qzCrlm0DT5z1jDs6vwmw1z89ptvXQ+P777rdrvTD2IV6E/+MTnk35ZjZ6KbGxPt0i/FdnVhVtutWa226SX1dtGNubiJTCS30UUnY2X8t6zel0ruL/3iKFmvi+oyxhJvUBwlG6rvtkr3rU763Nbqe3vXmJEy10AKNexUSDNaoc3euWzkzSbwJhF2J5hlG1LPsOtKg/CcAdX8/vb73zzPDaPN2O+/T7cmwiU7Qv7iVnYLJZEVaU3Jn6tI/tdGl/6pYWa/X6UhZpd1o4W1i+IIPNRa2yi9j8J9pd9b1YWgj4SdhGTfrkseQ/9AlG2ABmRDdd1W8X6W/LWTIZ6jIZZhEXXthRx1KrTYCXX2zprNLN5Jw27iwdbUCGF37qhTY9xnuPb7Xz3/DpY8/iV95MjJhnHIdkpsVxJm2yS2tlEaOflM3S5aecOnEmIads4VvaFWuK9VYYbOvf52W7llSf+wy2cIbcR2l25SHCEbqu220uv33b5D3L7vMiyNE10WUdde6GGnQpzJCnn2zpp05PUOu/3+xXnxVh6TDramzhx2YwUWYYfT2e//4fn5cM4xxbCUFXPIeqa2ElI6iyahZWfnssBT/sMxNcRWhUMvi0MP46z0WRx/SdhFpW+6M4Ar/f7BausbdqXbx8HpLm0XbxMf3+WyzmhANlTTbWX3hT6GWsZQxgwTvW99LETdvIUaOaHP3rkmF3mtws4fcZOL1aGdMeyIOuAUmoXlueNP7tQh6xAHjf61MkohF7+HTi6vzrDtzM52jjtjt5OoK/ePfP+mfD/OMr0zfFbdepaGpz/9dHnulXXdCjcm7E5BNlSTbTXE9pzKMqyxo27uUUTY5UKewWL2rmgS78c7GHbVkFt8xPkQdsDCJeE3gbCz4uhK3mumgRXJ1/reuuhGf2ncmJsbvawYNDbskuvIuInMNg3AeNRVlt6XZ7btYNhV9Jyx84WdLs8bkMX18l0uX6MB2VDHtlXfbam3n8IyLA0SXRZR1x1RVxV63Om/KQIvN+osXhZ2gc7GNXGmsBszrgg7hG1qYZec1XIlsZTMeu0iDTv73jrfoZjOCVDiP/UiJ9gkkOq7zsZfEkbuIZjZOBptJwq79Et9fMzYDU821KFt1Xc7DvE8DPlcjhkket/6WJYQRIRdFTNXBF6d883iMRvXGGEHLNy0wk7DTUIuDrQ84vIZtOZhlx2KKeFUfM+a5dxXev3KTJ27nFqE3RzJhqrbVn22od6273MwxDKssaNqSSFE1NUj7hIEnt+ws3gHZuPkH+npzoq5EGcIO6IOGNOUwi47pNIGWqw0E1cOuyy+nOu5s3Q1Yee7r1HCrhxylfUl7E5BNpRvW/XZfkNs+yGfvzFDRO9bHwtRFwbCrojAq9d+Fq/FbBxhd9yJw27ssCLsgMmEXRZjpbBz48oXWtlZM+V28Zk05U89lHNlP9NO5/JKau7rdGEn15GHWW5Sa7tyP0Ov32fZpZu0Vnq1k0jvYhZkZX3r2+Ux6G36PvYhlmHZZY0ZdUuLIMLuOOKuisCrVx94PQ6rJOyOI+yAhZvcyVMKsZVEWtZDntms4oeW6/XzgLLvofMfiqnKYZe9KM5G4bZy/+Xv149ioOmyD65HeuKXuvhrSpZxUHq1k0jvYhZkZcvr22X9h3jMQ263IZfVlsaP3j9RFybCrh6BVy8JvBfpMf0dkozOYUbYHXfCsJtCVBF2wIhhpyMWV0EmibkojrI0jvRwxfj6pdksO1uXBZd/tiv/APCycth1mbFrpu7D1YeWbNF66dUydR/AnkRueXvqzKNzWeEzBmcddm3XXa/f9/EOsQxryGW1tdSgU0RdO8TdYQRe/WycBl7vICPsjjtR2BF1wFSMPGOnf2oTLNuAgXhMslnrpVfTcou3ve+jIPIQTiLbXiN7X2I6S1qOwuQe5kFW1l3fNuve93Hq7fsuwxpyWV0sOXyIuvYIu2Zs4OlY7vY6cJKTGq3jbi/3IYtV8e0Iu+MIO2DhpnAoZsr+orNjaIVlyhenuI/JS38JJnQmtBJ2pfcMZoe/2tlN++dWwi65ipXexSw4z3+b9e7zGPW2fW5fNuSy2tLo0fsn6lBG3LWznFm8Hu+NczSOOyfqrGvC7rgThB1RB0zJhMKuTK9jx1CyZclfhlzubKS/ABO+sNOZPPey7DrFsNtGMpJrZNK7mAXn+W+63l0fn96u6219hl5eW0uPHqKuP+KuvXnN4rWfjWuj/sQqFxf/+vD24uXqUr//3nx6eTV7ue8UYdfAwGE3laAi7ABrlLCTn8Cthv2F5/te22GXNdTyZjYKvDN2JyTbfOxReP6T0UTT67naLL+JoZfXlgaP3j9RhyaIu+6mF3nDzMa1VZ69+8PFxdvXD59tzD2ZzWZn9k7Zmetr/TlP2B0wYNhNKaYIO8AaLey6sb/sut6+bOjlTV7y2y915rBLXxCcZhSfy/rhu23dKN+mGXu7IQ29vDZCCDpF1A2PuOvPjTwdp9+ep52NayuOu/3++WVzd2eiL4UZOrN7ejK7QtnFCLsDBgo7og6YqpmFncv+ohuKXd6Qy5yc5Pde6lDY6ffS7eH7mIaRzpppnx/fGJJ/mfoY6oa9je975dGcfz3OJ5TYIepOh7gb1vCzefv9a+ln1KTCKHkv3c5s7jfm+dWNuCdzfxeVLssQdzUGCLuphRRhB7hmHHaW/SU3JLvMxY2C2rArnkBFPw/QvVqPs2b2HafW9X7a3Ua3xaFh18P3PTtOS0NH7yOEWboQHufYiLvT6BZ51ZCb7HMjv2tebqPPJm63p3tzffdgPidfmPvrO/OQHZZZQdjV6Bl2RB0wdQsIO8v+gsMBye+8VF3Y6eWlM2PmJ1RZ5Fkzu+47p9jnmi1Pt+cwoxw1ocxehfI4p4K4Oy1/5FUjTsfknwd7xsunzaZ4qOVuY+6ur/SHlnn/6SUJvnrEnUePsJtiRBF2QNmCws6yv9zsgCP5faftph8Ab7eR/4PdM1m8JX9f0Fkz7TboYujH02ddupNXUPG/x8vL5P7lRVT8dbsxp0Bilm48xN2pachdXdmfJTpmt70LH2PghJx8KxlvP6SzdtbObN5dm9uHz+alGnrEXUnHsCPqgLkYMex0nEP+CwG66VuSUHMOt6yE3cDS1RyK+9z7Rhd9busz9PLa6h86Ng77j1PHFrN04yPuhtJsNs7O5M1qmxfiro4emnml/4fUW/Ph84t53rwz1+tP5qU4jUfYlbQMu28ydP+ZYkARdoDPyDN2+qcd5+DenzuCkfyua267Ks3mtQ47DUPdxs5y4hOz5LG42+o78xLpajbhPn91Y0hDL/MU69jG9GauhglE3+OZ3mMN2yxjY3T93hvnP1Rzwg7F3dP9tbm6rHyOXfXQzQRx52gRdhp1Xd+Ld2pEHVBnQodi2l86vu+dmnvfbcbiJL8HE+WTpsR8YaeXxdvDmdmLadTZoLMzf8mhmvoevFV6COd2m5djspxG41yGvr9zr3/ZsiOnHId6iOnyDy+dK2bv6pz2vXGziTxf3MVRt6rMzMmvko15t95WL08Qd6mGYUfUAXM10ffY2V86x643Nnc9FzEyEmvuxxxkZ7gsn1ilcAIW/bgDJ+4K39MvNRTzoIsDb7c1TtfFZD3G5m6TIQy9vC5CnLXSx9zt8Z5u9hBFxJ3qNxvXx6RnTythp++5k3h7rcSbPUvmSzKDp5F3fVU+wQpxJxqEHVEHzNkMTp6i17UDJ5b8/rPxZW1N5Eaee3hmKfQK3yvFYTyzt1rlYRdtC4dhWumqnNvQ+9nQy+sqxKBT3aNuKMPEoY6lP3dhxd1pZ+O6soE3ufgpxN3TvbnfvhbPhhm/1+42fp+dXhzP6N1+MJ9f9mb79GTk9sn1CLvYkbAj6oC5m0HYufR25YEBxb/+skMr81H8kHI9rDK5vMgebpl+Fd0Ub5fO4MWfdyd/H4KsQ1/2MQ7BLmuo5fURctAt63GHEYiTnjlqxR9u7pjyY3yRoc/DpCIoizt3xs6eMVPPkpmeDnO3eWfW22SWzv27I/i4OxB2RB2wBDMLOx9dVt1AS8nvvvaSj08onmilEnYnkK72Me4+UR5DGHJZfbiPK7SgU+PP0k3ZMIF46ig57ezd8egaYsw/TicWeOVZu/hsmJWPPUhiLjlT5oV5+8F+/MHO7Iq/hoKOu5qwI+qApVhA2B0S/4A/MuBIfu91VZyxSw69dA/pdMj3qt/S9+jpc+Isw9JluYd8pu/501VuME7h1MtvYyrrMZZQZyfP7xxhpJ/D9vrq/17/sYToOqfJBF4h7g5w4y4ZycchOAlI2BUjbqpRp0GnzyFRB7Sx8LBrIv3h32kEL/k96ZAAy2bpSu+/yyUBVww7Nwrl+4Xbpe/5k+Wt4mVvJeyS76SrcU5Tee7tekxhXcbELN0yhfW+u+mbROBV405PmlL8APN8ps4r6KhTpbCbctQRdEAXhF0v2S+TUEcl3kqzdJXPwRO7KJIwK83YVW7nhJ8TdHHgSdXZb8k6nIP7mMfirsOY6zEVzNIt33Led7ccowbe4Vm7JPJu3741l9XPuAs+6Cwn7KYYdczSAX2NGHY6MHNx2DlBVv3su/KJVtIzbLoze6LyfrzC99OgS//MPnpBJGtxWHpVr/QqPnYfbXQfJzKFdZgiZunCwuzd9GjgTSjuNOrW5jGOuZ3ZvFubbR52RJ1Dw05qTn+nTDHqCDqgr5Fn7OIXrZg5nW1Ln8tjJ0uJZ+v0L56wKwRhZQZvlf5tWLoT6np7xlimsA5TZGfodBB14SHupufks3dpxFWWX4m73ZN52u3NPv78utv88+yWZagQm9pMHbN0wJCmcChm8jPL0hme4uF7yWF5dtbmkOLZrwqH853J8XVMxGeRvIlMJOuomyAZnpOGeLaHavfYZNuVzlg5iuyQStFgxq544pUmD1YfZ8121OXVn3xlbHY9prAuU8Mhl7A4NHOaThZ4TsAdiTudpbs2VzfZRx/E1y9cR8+muX40L8UPwYsP31wVP8i8aPfRvLuLzBfn0M6n+zdm/fit/jan0TbGNODs75VsyIX6i28KYUfQAacwnbCTgIn0xbb8udIX4DZo9E99oW6/79DDAJMfDOmQOIhvm4g/Ly39e1saTuXT9zdRWUdHssxkxBGjoSPxUncX2yjdDoXtkX6v1WOT4PGexKSdrtvEimO28HzpSB7H8bCzbLzZYdfH7ifpdaZ/8hV3oIqgQx1m76bJBp6O3pFXmZVLZMut+b7yX8f34eZqtzEfn/Ty4v8xHH/Q+WX2eOrH+1/MtxaFp1F4fZWcqbNlGJZjzBtuzvDGmx6KKd8cM+wIOuCUJjVjF8/ibJOQ2UbpC/b0RbnYRStvVJRP0GEP67MfhH2gtbzy2TA3FpqpW0dViTF3BktUvl/YHsWTjbjXdd9z5tc/7PpsEy+NcvcBlb6uhF4mj7KCUgjm6yucoIv3JVmA/Va6C56S3oc7cBhBhyaIu2nrNYt3INpUXdxdyw+PF7nTA2H3xTzc3ZvHLw/Jh5vrOr79YD68v5KIe2vevq2cdEV+f3w095vn5EPRU0/392b7WrpeA/lM31fz8Z2sR/m+Dnjz5o39HWJHpzgbMewIOuAcpnUopr5o1xkqiRhbY1ngqTzycnr9YrTY6Mn/PP7er1wpguK4Kt92F6+nn28dE7o+q3jWyz/0cNNCtMRBkoRdVKqZZPYsvZ1+/+DD6xt23beJrF9BenH82AphJ/JAPxSP/rDzzfjlX9vnJPmz7clXGsqej9KYDHmRo68hphhMNuZ0EHRoikMzp6/LLN4fZNjn1ryvP0wyXl4ab8nffWEXv+/OfiSCzpR9Mc/bTRJrulz9fnqopZceiln6SIWLi/fml29tw+7J3L/b5Id0Smi+23wpHRr61Tw97Uzyo7pikBgbIewIOuCcJhN2OuOS/dB0RunFvz2cL7s4m42x8rDKZ7U0FBoeQlia+fEFiC6vPuw865hK1sc53MNd950Eh7tIvV93O6TDLjN/bB5127I0Kg+rTo9tIvdToJfZ7ROPQnDq86SX+54re0EadqV10mUWVqn0/Xh7yWU2nu32i1eqvXz98zG4ZM0HN6VwskFHzKEPZu/moUnk/evD29WLOxt2ZHassBxv2KXiDy6/fUjegycx54ZdMiOXXK9iqLCTkHuzfswP2/wqy70vv+dvUWFH0AFjmNzJU+KgSV7Y64vvSL7W963ZF/w3N3qZkwJuJOjtonz26mD81PFFjI0P/V52X3YU78O3jlayPjZeZMhyt+76V2JJuPfvaPfYes7Y9dgm8nVBenEPui/INtP1ie87uS/dD8ozdsXtmQZ/HHZJ4OnX6WrVSR9PZZxFuuKd6Pa4lOfoOflKHnO2bcaMKBtydhB0GMrgs3fy4tp9qU84DssbeRpi+t629WM+S9fwsMd4GfVhl5xcZf3wwdzeRubLl6hV2CXfz9cgWyeJs/L3avnCzp6URb8n8Sir7Iz/KsfjnMJOo46gA8YwtbCLQ03CaCXxo6/D9fT4Ufa+tXw2LqFf6+GN8Uv7yiGLNn4qL/oPORQxmS6HYibrl58MRS8qBpLvZnm4Jo/FPQQzG0ejTdbp6HUO6LFNZP0K0ot72ZXCXp/bynNcCTsl2z6SsEv3C/1TV+nAGFWyzkK3d7pOlccYX56HdEyuH88E232qOBt87phyY46Qw6kNFnilsCsj9IbjRl4y3n4wnyWAtnoCk9Wn0qxWrfr32Gm83d3GZ7983D7FH4twf782t5eXxZk4vV89JNOdpXv73ry/kes5J1J5/8svZnV9bS7l+r88rM3m2XNSlrJDYZdcImY/Y8csHTC2qb3HLn6/WBw+eSDls1OlaNLZl+wyDSa5XuF1742Enr4oLr3wPaRHxCRK65jxh112KKbcbzU+ne2RXrcyU+cuo5YsZ0FhV2C3m66Ts47emJfr6Fs38+CPw+jfkzWbJt2uhf8jINuX3ee09PzafSL9cyf/Tpwtceq4ckNOBzGHMfQKvOfHx9ed/8V1HUKvnz9cvH98tQFnz0hZfX9d8vEESYzp++W8M3mVsItn2B5XZm3PiimRlZ0h88iM3e7jO3MfzyDm75Hr9HEHyw47gg6YihHDLhtW8oLbeSEbK72wrUSTDany7ZRc1vS9dZbeh/si2RtcB8LOu47Cvth211OWnV3Vcz++7TFK2PXYJu7z7D7Xqvy9mpGJb3RgXY6dfMV+OLo9c6luS1nsvyVLnyZ9fP7dqRiuhTPD2n0i/lMPPc2vJ4YMrXLE6SDkMCVdAu/f3svtkniw4735JC/IG76OJ/Jaen54eNlKzGTbVyKo8plzEmB38YeP2xDamc1mWxdByaGZGnZyu81Wlr3NY263uY9n2eJb1obdznx8d21uHz6n6yFhd7+ND7v8+lUCTOLzOp3Fe/9Lg8grh5w8xgWcPIWgA6ZmSidPSV7AlgLNDRf37xmJluQHi+dEHHVRl9zG94JZuS+SCy+Ym/Cuo8jO7inrpdNG8frJY7Zn7NzpXJ6jZnucLuxOs02SZ3gY8QJLj7e4LrpNdV/wrZ/d7unf5Xq63dNFT5YGXPycyON2g7bwcQ6iGHrJvhXpbTXsZN+yoSsbsU94MRuHubKBp+NYeP37436fv9yWF/5reeHfbgKvgNA7Yr99eNnsimF3F0ls5U+C2dxdm3VhBk9CS0Lp+UuUfHTB+5pDNu3v1myWTpZ1vzHP9rq+sNOwvLqNP2vuWU+6cnXp/twzb9++zWYTNfLyEJN1enNtVjWh93T/zmy+JLdz/97QlMKOoAOmanInT9EXpVnI5C9IY96ZIgmS5JVv/sJdrud/cZ87/BEIer/JD/C60KnlXUdn3WLJ8u2y9UW53pd/feS6hbDLf7nYUbhd/Nir1/GP4jY6xTaR6w8mXWS2vXS0fn5K4gVPWBxwOrOoUadxlz5n5bCr7ndb2eeSwzC38Qxl8u9EFnksxnyzcHYQcliCo7N48kI9eZmvs0S3Eg/Oq+/d5i7/4GqJiVfnRf366sqsPr3WRSCB5xHPqsnvFw23/APBi58np9v8el0MN73sbv3e3Nw+mC8ve7PdbMzBw2ftDNlj6YPKnbBz379dlc/YHaKHad5ls3xl+vl1yeP8ryazfEVTCDuCDpi6SYZdOtuQhUf8glZ/mByKtWTGSRdXPWlG1aEPEu/Du452ti6LLv/jqLxYj5XDrsuMXTOn2CbxEzyQdJGDShc9WXHIuztFGnC+sPOdLEYPw7T7THro6bFBvCEU3lm8LOo01HRGyH31/bQ2V3pWxfSy3UZPnJHMND2t10YPJ8wCozrTR9iVJFF3jEafbFs9C2V6SRxZ13fmVj9QXC+3caazcXr2S99n38Vh92Derx/N6+M6n4V7+8F8erg1V/K1fkD5wxeJPrlPG2DxdQ6Mtx+KEff1Y3KYZ8toa2LMsCPogLmYXtidwYAxtBgn2ibpUzyYdLHDiXfGZKR3MSnZoZiW/p8cckHx0EtRmbET6dkw3bDTP+WhEm9AURZ5r+kxeTbU8tfnGhi3JrLvzdJLNnfxCTk0LO7W2yQs1hvzvH9O/8xuTdTVOBp3dts6paTvb9NZsU+RRPRzZO70vWufNNaSwyeHb6qG2nz8QXtjhd03GQQdMBdTCDt054ZJEKODdFMd5b0/z4iveqahwVY5I6l+bf9MVQJQ2LNhuieLIeyAw3TGToPttvAeL6GBUTos82l9ZdaPSdjFJ+iQP3WW7nFVDEBB2B1RH3jFQyALh2Xqc3K3Tj6OwP8eu+wMmUi0CDsNOv09NEhQAjiTuYZd+cV2qCPdHDivztvd9xweHJJm7vtM3YDLTxxTvE7CPUupfv9Sbpe96CHsAI/kMEx9r9zaPEokFDJBD8PUw/iyWTh3Bi95f93lxXvz8KD/RuWyYmMQdg3UxV0cc/bQSTfg9CQndyvz6WFlrm4fzOeXwkYn6jwahp1GHUEHzNEYYed9AdtypIsCzu2s+57s7SJ//2jxcEsNNr380HtPPS5llP49tRyEIRYpDrvS++isyiyeZwZPL0tm7NKZvPxbhF0L9bN3lkb1tbnSyNP3y+lHIzxHyayp3ebX1/KzSn5gMXzjULQRdcCcjRV26V+BuTnrvpu+RBlarzDby0+NUuidYhCPODsbdsVT7SfKYVc9XDM52crjw238vrvH9D16gqjroD7uNOruTPQlmSm1h2kWPpuO2bquiDpg7gg7oJXgw+4ciEeMIQ67OjpDF58gRdOherhmcrKVZxOlJ03ZEnaDODh797Qx8effyXPzTp4bPUTz+vpaf0Yzug2iDpg7wg5o7Oz7bfryZUjETIp4hOtg1Fl6mGb8Xi89zX4edTp7F58dc/9kNpud/LnNPirh6urKvmi2g9BrqT7u9GMPrszl2w/u++uYrQMQLsIOaIz9Fq2cIR4Jx4E1CryS/IOt9TBBCY3LC/M+/6Dycsi5n59H6LVwcPYuMVrUyb/1b55/nwzG4obs69+nuz2miLADGmGfxeScadYx2PDoEnklTbZdOfTcMdttL/vmi2df6j/q0u5ahu/65xscxoggyL/tXz37P2Nag7ADjmCfRZDkl/hr6RfGKcYsAqZD6BUeV9tteXVROYwzHq8Xshqe609snHT2zDN7xyGYAIInv2f+IT9/CTvgCPZZ4ETOFI/Dj2OZdyWjeJuhAlZn+WY7mzcUJ+6IOgAQhB1wHPsrgIM8s3mnDC/CDgBQQdgBx7G/ApgSwg4AUEHYAYexrwKYGsIOAFBB2AGHsa8CmBrCDgBQQdgB9dhPAUwRYQcAqCDsgHrspwCmiLADAFQQdkA99lMAU0TYAQAqCDvAj30UwFQRdgCACsIO8GMfBTBVhB0AoIKwA6rYPwFMGWEHAKgg7IAq9k8AU0fcAQAKCDugiH0TwBwQdgCAAsIOKGLfBDAHhB0AoICwA4rYNwHMAWEHACgg7IAc+yWAuSDsAAAFhB2QY78EMBeEHQCggLADcuyXAOaCsAMAFBB2QIJ9EsCcEHYAgALCDkiwTwKYE8IOAFBA2AEJ9kkAc0LYAQAKCDuAqAMwP4QdAKCAsAMIOwDzQ9gBAAoIO4CwAzBPxB0AIEPYIXTsiwDmirADAGQIO4SOfRHAXBF2AIAMYYeQsR8CmDPCDgCQIewQMvZDAHNG2AEAMoQdQsZ+CGDOCDsAQIawQ6jYBwHMHWEHAMgQdggV+yCAuSPsAAAZwg4hYv8DsASEHQAgQ9ghROx/AJaAsAMAZAg7hIj9D8BSEHcAgBhhh9Cw7wFYEsIOABAj7BAa9j0AS0LYAQBihB1Cw74HYEkIOwBAjLBDaNj3ACwJYQcAiBF2CAn7HYClIewAADHCDiFhvwOwNIQdACBG2CEk7HcAloawAwDECDuEgn0OXnthMjuzjSKz3aVfWrutiSoXHrMzO/9NLtO7BoZA2AEAYoQdQsE+B69y2EXryOzkkl1aZdv1pbmNHkwUHQ673ebWXK4ejV3adn1roue9cRZuEXYYEmEHAIgRdggF+xy8krCToLtdm+3+OQ27rVlfapjZryXUIvkzLbPYLjK3l5e6X8Xj5uHZ7CUG7XW2a12eJ+sIOwyLsAMAxAg7hID9DbWyGTsNNYm4aKVjlUSZXLaOdsms23Zt1tvqDFw54HSGbyXX267k8mdZ5m1knouBR9hhSIQdACBG2CEE7G+oFYedRNvlpe4nN+bmJt5fzMXNg3mwgRfTWb3k8Mrc1qzX2+zwS73OJp7h00WmwbfbmNvLlXnMr0TYYWjEHQCAsEMQ2N9QK5uxi0moxTNs+lffDJ0eonlpVo/p5VkQJmP18GBWOsMn33Rn8nabjTurR9hhaIQdAICwQxDY31DLDbtddJuE2s2DeXzeSZxdaoVl4XZx4c686YlWbs1NfMKUZKZuu91W32PnvO8uRdhhaIQdAICww+Kxr+GgPOw01NZmtYrMs743Lj3EMp95Kx12uY1MtNuaVXyZht2tWUXP2feTs2I+mtXlZXJiFXs7wg7DI+wAAIQdFo99DQfZsNtFawm1/CyYifzjD5KTq7jvp1M29vL31rnsiVSKlxJ2GBxhBwAg7LB47Gs4KA677drc6mybG3LKPSum+/dM8p47WUx8+GZ+9ksJvVvnvXhFhB2GRtgBAAg7LB77Gg6yM3YJN+zk7/Fn26XfzuLP5Zmxi0+ocmMe/B9Orgg7DI2wAwAQdlg09jMcVQk7ibkousniLD4EM56VS7/2cmbu4pOppBf7EXYYGmEHACDssGjsZziqGHZnQdhhaIQdAICww6KxnwEIAWEHACDssGjsZ6izl6H7xxiDGTsMjbADABB2WCz2MQChIOwAAIQdFot9DEBIiDsACBxhh6ViHwMQEsIOAAJH2GGp2McAhISwA4DAEXZYKvYxACEh7AAgcIQdlop9DEBICDsACBxhhyVi/wIQGsIOAAJH2GGJ2L8AhIawA4DAEXZYIvYvAKEh7AAgcIQdloj9C0BoCDsACBxhhyVi/wIQGsIOAAJH2GFp2LcAhIiwA4DAEXZYGvYtACEi7AAgcIQdloZ9C0CICDsACBxhh6Vh3wIQIsIOAAJH2GFp2LcAhIiwA4DAEXZYGvYtACEi7AAgcIQdloT9CkCoCDsACBxhhyVhvwIQKsIOAAJH2GFJ2K8AhIy4A4CAEXZYEvYrACEj7AAgYIQdloT9CkDICDsACBhhhyVhvwIQMsIOAAJG2GFJ2K8AhIywA4CAEXZYEvYrACEj7AAgYIQdloT9CkDICDsACBhhhyVhvwIQMsIOAAJG2GFJ2K8AhIywA4CAEXZYEvYrACEj7AAgYIQdloT9CkDICDsACBhhhyVhvwIQMsIOAAJG2GFJ2K8AhIywA4CAEXZYEvYrACEj7AAgYIQdloT9CkDICDsACBhhh6VgnwIQOsIOAAJG2GEp2KcAhI6wA4CAEXZYCvYpAKEj7AAgYIQdloJ9CkDoCDsACNhoYcdgMBgMBoPBYDAYjEHHecMOAAAAADC+P//5L/9I/woAAAAAmCPCDgAAAABmjrADAAAAgJkj7AAAAABg5gg7AAAAAJg5wg4AAAAAZo6wAwAAAICZI+wAAAAAYOYIOwAAAACYOcIOAAAAAGaOsAMAAACAmSPsAAAAAGDmCDsAAAAAmBCNNBmm3fiL+X/gM+HuPOb3uwAAAABJRU5ErkJggg==
用有限元方法求解二维渗流控制方程(Laplace 方程),用于分析堤防、土石坝、尾矿坝、水闸等挡水建筑物引起的稳定、非稳定饱和渗流场问题,软件应能够解决各向同性、各向异性、多层地基和复杂断面情况下的渗流场分析问题,可处理垂直铺塑、水平防渗等复杂边界条件,输出等势线和流线(流网)、渗流量,浸润线,水力坡降,渗透力和边界水压力分布,任意点的流场数据、任意断面的流场数据分布图等。


2.稳定分析
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
遵照现行《碾压式土石坝设计规范》《堤防工程设计规范》和《尾矿坝安全技术规程》有关稳定安全计算的若干规定,可用于土石坝、面板堆石坝、堤防、一般土质边坡、尾矿坝的稳定计算。提供的计算方法包括:瑞典圆弧法,简化毕肖普法,摩根斯顿-普赖斯法等。能够考虑圆弧、非圆弧、软弱夹层滑动面、上部荷载、非线性砂性土质等复杂情况。可以考虑地震加速度荷载作用。提供指定滑动面安全系数计算、指定范围安全系数计算、最危险滑动面搜索计算功能。提供基于推力传递法的出口推力计算功能,用于计算挡土墙的上部推力和抗滑桩设计。

可以直接导入固结计算结果,用于确定土体中的附加孔隙压力。


3.结构分析

4.应力应变分析,可以直接导入渗流场,计算由于水位变化引起的应力位移变化。


5.固结分析(比奥固结理论)


6.水工建筑物整体稳定分析


Rueng6009 发表于 2023-9-26 20:39:55

收藏备用,谢谢分享!

mate0 发表于 2023-9-27 17:36:11

Rueng6009 发表于 2023-9-26 20:39
收藏备用,谢谢分享!

软件很好用,多多交流

joint 发表于 2023-10-4 20:45:12

有和谐吗,现状官方都免费试用的

nop 发表于 2023-11-22 22:06:34

谢谢楼主分享

月sep 发表于 2023-11-23 09:55:30

感谢分享!

月sep 发表于 2023-11-23 10:02:24

文件过期了:dizzy:

admin 发表于 2023-11-23 16:26:40

记得上线补一下链接。

李军 发表于 2023-11-23 20:00:22

看看。。。。。。。

落叶知秋 发表于 2023-11-25 10:00:44

下载试用一下
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