<rss xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" version="2.0">
  <channel>
    <title>MaplePrimes - MapleSim Connector Posts and Questions</title>
    <link>http://www.mapleprimes.com/products/MapleSim Add-Ons/MapleSim Connector</link>
    <language>en-us</language>
    <copyright>2026 Maplesoft, A Division of Waterloo Maple Inc.</copyright>
    <generator>Maplesoft Document System</generator>
    <lastBuildDate>Mon, 06 Apr 2026 21:55:12 GMT</lastBuildDate>
    <pubDate>Mon, 06 Apr 2026 21:55:12 GMT</pubDate>
    <itunes:subtitle />
    <itunes:summary />
    <description>MapleSim Connector Questions and Posts on MaplePrimes</description>
    <image>
      <url>http://www.mapleprimes.com/images/mapleprimeswhite.jpg</url>
      <title>MaplePrimes - MapleSim Connector Posts and Questions</title>
      <link>http://www.mapleprimes.com/products/MapleSim Add-Ons/MapleSim Connector</link>
    </image>
    <item>
      <title>Convert from MapleSim to Simulink Matlab by using the S-function code Generation</title>
      <link>http://www.mapleprimes.com/questions/238014-Convert-From-MapleSim-To-Simulink-Matlab?ref=Feed:MaplePrimes:Version MapleSim Connector</link>
      <itunes:summary>&lt;p&gt;Hi,&lt;/p&gt;

&lt;p&gt;I am trying to convert from MapleSim to Simulink Matlab by using the S-function code Generation connector, but I got the above message when I uploaded the selected subsystem and I have no idea how can I fix it. Please help me&lt;/p&gt;

&lt;p&gt;&lt;img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAhAAAACKCAYAAAD7YnOFAAAgAElEQVR4Ae19e5BV1Z3u+WeKVyNR4kzNlJXykcwYdaJJSweJiIoCjYqPm0RBRw7JCCiK5v4zmcw1TtU1PVY5ZUzK8d5ER+3Wq2g3KggCKtC8m35D0w39ALrp5tlAq+P1ThJrvlu/tc9vn3V273367NPnNOf0+aha7Nd6fuvb6/et31pnd+TMmTPo7+9H21u/xlutJ3Ds2DEcPXoUfX196O3txZEjR9DT04Pu7m4TDh8+jFwI9a8+imfWha+LpJu7rBz1nnZseGYu5j6zISfaZuNb/+ozKG8Y3M6DBw9CQ1dXFyR0dHSYcODAAUhoa2szobW1FRJaWloSwp49e5B/oRovPvUiqvOy7vmIN+ucf+/IyPaZd1zR8UbHHx2PdHzS8UrHLznaYx7PB4/3mcRE8F69enVKmKvdFw0gWkB0geiD48eP4+TJk4jIf3KjqeJZVDT2mEwPHTpkjJN0dGdnpzFK7e3tkKBkONfHHb9fiqdXOYYy5brsfBlL/+cHOdOGVOq94/dP4+Wdie3UF1OO+rLqSyyDXXNzswmNjY2or683oba2FhJ2797thl27dkHDjh07kB9hDZ77+XNYkzf1zRdcWc/84H9u9JOOG3K0xxQdZ3TckTFIxyMZm3Sc0nHLHstSGQ8ZJ9EWpIOHYL5y5cpBdnD//v3QoPmq3RfxJ1pANIHoAxEW4mCIPPHEUtw3swQlJfEwL/oEzP1592HpE3IuYRHmWXFK5i2K3X8CT0TnYV408bmTh6a1jg/fh5luPvOwyM3/CSyaF69DSUnisyc86e67dybsMpbeOzPehpl2veNlL5o3E/c9HL922hVwnVCenW4p7pt3HxYlKS+wLgYnC28XQws7t+5WvBhepr0P34d5P16Kxx9/PBaiuGPKFEzRcPuDePTRR01Y9sBtuO2Bv8Pca6/FtbEwd8FSLF0aD0uWLIEJi+7BjOJiFJtQigV6f8kSLCjV+3K0ny1AaemCxOelC5z8lizBortLcc98O98ZuGdRrDyT/wKUumUWo3R+0LNYuoQ6JtZl0d0zYnWX+3Y5i3BP6T1YNL809tx+ZpfHc5cLVt/zHnmRjAP2WCLnDz/8MB555BETli1bBgk6Hj322GOQsHz5chPiY5gzliUdjy07wXgBNitFjAT3hQsXxu13iun8cI+IQeU/IkAEiAARIAJEgAikioAIioj8x39EgAgQASJABIgAEUgVAQqIVJFiPCJABIgAESACRMBFgALChYInRIAIEAEiQASIQKoIGAGxiHsgUsWL8YgAESACRIAIEAHAbMKMUECQC0SACBABIkAEiEAYBLiEEQYtxiUCRIAIEAEiQAQMAhQQJAIRIAJEgAgQASIQGgEKiNCQMQERIAJEgAgQASJAAUEOEAEiQASIABEoAAQikYj5swZBTZXPj0ucVP+FEBAfYnEkYjKXAiQs/jDVYhiPCBABIkAEiAAROJcIiED4szFjfUVEsmdBdQ4pIKbh+c6grHifCBABIkAEiAARyGUE/ISC371U2kABkQpKjEMEiAARIAJEYJQgYAsG+zxs8zIgIGRpYxoWL56GSGQxPoT3GkDn85hmLX/Elz4S44atPOMTASJABIgAESAC4RFQ4RC0pJFKjiEFhL0HQsSC/HP2Rkxz1zb8r13RYMSELoV446ZSZcYhAkSACBABIkAEhoPAORAQavjtajteBFc/xDwQ7rURDCo2nHQfLtYNmN60dr48JwJEgAgQASJABDKNgIoHOdrnYcsxHoiFCxemkC7I2Hvve64pIFLAllGIABEgAkSACGQfAT/B4HcvlZqEXMJIwwMRW+JIXMJQj4RHbKRSY8YhAkSACBABIkAEQiOQTCgkexZUUEgBYe+BiMDZ9+AVAd5r7yZKW4T4xA2qKe8TASJABIgAESACaSNwDj8klXadmZAIEAEiQASIABEYZQiE8ECMspazOUSACBABIkAEiEDaCFBApA0dExIBIkAEiAARKFwEKCAKt+/ZciJABIgAESACaSNAAZE2dExIBIgAESACRKBwEaCAKNy+Z8uJABEgAkSACKSNAAVE2tAxIREgAkSACBCBwkWAAqJw+54tJwJEgAgQASKQNgIUEGlDx4REgAgQASJABAoXAQqIwu17tpwIEAEiQASIQNoIUECkDR0TEgEiQASIABEoXARiAmIpPv30UwZiQA6QA+QAOUAOkAMpcSAmIP4upcgUGRRZ5AA5QA6QA+QAOSAccJcwSAgSghwgB8gBcoAcIAdS5QAFBF1V9D6RA+QAOUAOkAOhOUABQdKEJk2q6pTxOJMhB8gBcmD0coACggKCAoIcIAfIAXKAHAjNAQoIkiY0aTijGL0zCvYt+5YcIAdS5QAFBAUEBQQ5QA6QA+QAORCaAxQQJE1o0qSqThmPMxlygBwgB0YvByggKCAoIMgBcoAcIAfIgdAcGFEBcbCrC5s2bcLrr7+Of332WfziF7/A48uXmyDnck+eSRyJS+U6epUr+5Z9Sw6QA+RAfnNgRAREU1MT3nj9dTz1y1+ivLwc1dXV6OjowNkzZ/CnP/3JBDmXe/JM4khcSSNpSbL8Jhn7j/1HDpAD5MDo40BWBcShQ4dQWVmJXz/3nBEGp/v70d9+AH0bN6LrrRXY/28vYl/ZM2h88insffZf0V5Rjp5N1TjV3o7Tp06ZNJJW8pC8MkHAgYEGlJVEEIlWZSS/VOs00FCGkpIyNAwMZL3cgaooIpESlDVkv6xU2y/xFIP6ul+NGBZh6hcUV+s9En0XVIew9x0ORBCJRBCtyjwP8hGTsBgy/ugzeOzTzPZp1gREQ0MDXnjhBWxYvx4Dp0/j6NZt6Hl3JU78+yvofvxx9DzwAI7c80P03H0XDt95JzrvvBNtd92NprvvRs3ChWgpL0d3zS4c7+szeUhekudwCdBQVmLEQzoDoEkbcQZlGZhLygbXJyjfoPuptidsemNAsiBYwtbDbp+mzTUBofUKEghBz4Pu221O5XxgoApRl1dRVMVEpsk/Er+28zJpAvrXyS+7AjJTbbfbxPPMDu7Ek3hmmwNZERA1u3bhN88/j5aWFpxubsbht9/B6YoK9D70EI7dfTf67rwTfXfcie477sDhO+5A1x13oLP0dhyYOxdtpbOxb/Zs1JWWYtttt6H5uedwor7B5CV5St7pgjKcgdWIB2vANp6MaOoeheEOuGHTq6cl07PPsPWw+0rTjhYBYbdtOOdG7MU8YlXRuDCVc7/+c4WsxUe7fINzgPCw4w3nXPsySHQNJ2+mpeEjB/KDAxkXEOIlEEPf09ODI2vXou/Nt3D0H36OozHhcGTePCMcDt1+O7puuw2dpaXYP2cOWmfPRsutt2LPrbeiaeZM1N98M+pmzMDWmTPx4a2z0LVypclT8k7XE2HPynUAVGNWFo17FryDdjLhofk46aOotNzzzkAezzcSG/Cd++FmiFpOmAFbDI3XS6L5+LU3sb6DZ74qSsT7oh6YoDR+97VsB/MoorKUZPKKY+GbLjZD17Y4ceJpZLBx8o7nGa2KLVVZLnzX8Fpl+rYpwSMQwcLfOksuXswS21MG73O3Xq53IQLlgD1A+gkIzTuov4OeO1xVXJ3yDN5uHZx+9abX62Tvg4nj5uPfFrtdPM8PI8B+Yj+ly4GMCgjZpyBLDeJ5MOLhlVdwZPESHLtrHrpnzULH9OnouuUWRzjMmYP22XPQOmsWWmbegj0zZ6Lp5pvRMPMm1Eybhh1XfxfbpkzBtuuvx6bp07F2xo3oqqoyeUsZ6eyJsA1qwoBpGRlbZCioGtdvMNdBVUWHxq0/W2nc0t77koeTJtEAallBR83Xrw6BaWQvhGevx6D6SpySMnjra4ytJ62UY9dDjZW2UdME3o/tA3EMWrz9Jt0QdXDqLcZPhEE8rbbdee7cN30Y2wPi15+mHRY2iW1yhIe2yW2zD0fU2KqB1jRaphdTuxytt8lf9+UY4+wY+CDvg6YLysutr4rVmBjSurl95NmTo/kNty1aPx5plMiB0c+BjAoI2ewoex5k2aLz179G79KlEI9D54034ORDD+H/rV6Nvocewt4fXIf9s2Zh38yZrnCou/FG1M6Yge3FxaibNw9HXnkFTfc/gI+u+DY+KSnB+qnXYdUNM3Cyrs6UIWWFJagMngmzWDFalsdA8tOB1DbU9r2EGWuS9Knkq/U3g3psZqf102d6tOug94Y6+qXx3tNr3/r6uME1viuELDe6eRZJ9MJIHb33g8qyvTd2Ot0ToDj5YRRUr0H3fWbQg+JYbXLrYd3T+NoOPSpnvM+99/U6qP80fUOCJyTRIxSPM3iDpP3MPnfbEtRHGeJzULt4f/QbFPZxYfVxxgSE/NxSfjEhGybbXnwRvf/0T+i+7Q503nQTji1cCBw/DvPv5El0LViA2uJi43EQ4bB7+nTU3DAdW6+5BrvnzMHB6mocOnsa3c3N2PXDH+GDyy/Hmu99D6uuvRbr/tsPTRlSVtifeKYtIMxAnjjr1YE508Yj6AXU8oYyPnZ6MxP2eBG8+ei1bztyTEA4noX4HoGEtlozam2TYKXnpn3WL1P0vh3He67523Hlnl4rZnrUvnGfVy5MWLLQ+xpP87ePjkC1PCnW3gj1Ith18MvLLsc+d9NRQISefNh9xPPCMpLs7+D+zpiAkG82bN68Gcdqd6PzH3+Bw7ffbsRD9733AqdOOeJB/z9+Avvvvx87v/Md7L7hBuyYNg1bvnMVakrn4uDWrejo7cW+1la0dHSgva4WH8+ejZXf+haqrrwK736vGAfe+D/mJ55SZpjOVdeybSiCBn/vwGxmv0lmoRpfB2zHfR0XHXZ6E8cyZqm0QfPVclJJYwsmje/NR6+97nZTX4/4kDycusfW0YPc40H37SUMC0stK2jpw5Rr8pRy5RcLcVz92qVtStbPg/tD2xSwhGHVV/NX7uhR+8Z9bpax4nXV+xpP624fbdFnn3uXNJLlZT8LwtTEsQSi4pFqWzR+srbY7eJ58CBMbIhNvnIgIwJCvhopH37qP3kSHW+9hc5oFJ2zb0Xb9dfj0L33AZ9/rtLBPf7niRPYd//92Hj55dh45RXYUVqKzm3b0NHXh9bWVjQ3NuLoiRP44osv8F5pKd685BK8ecUVePvKq7D+3h+Z70RImWG+WOkMprHZXYAxswdfb6eaQdNygYsr3RvfvtYZs9lwGI263z5wBu+4YfGW43ftpLE2x1mDv2/82Lq6PWuVeHb9vNeJZSS6zO0yxJgNexOlhaO9sdCvDl4j6OCaWD+7XUHnWm9vf0jb9Jnbp1b9dBOlGkvNX42tHr3P5drmgNkwagkRG1PTF579HdpubzovD1PqY7c9cdzsfEpi/Ey1LRpf2+xtC69pFMmB0c+BjAgI+fS0fD3yVHsHmpYtw/5bbkHbzJvQIpsir70WnX//98DAgBEPX331Fb788kt88dVX+LTnCOrvugtbbrzRiIcDPT1o3bfPLE0Y8fD556i48Ub8rqgIFZMm4bVJk/Dvkybh7auvwYk9e1BRUWE+ex2GqGbQ9JlZh8kjH+Iaw5XEWOVDG0ZbHU2fFAD3Rlu/sT2j3xCyj9Pr44wICPn7FfIJ6p6PNqLpRz/Gvptuwt4ZM9A4Ywbqp0/HtiuuQsuDD+LL/n78EcBnn31mPmN98tNPcWzvXrRt3GiWK2RPQ+3u3Thy9Cj+47PP8Nq0afjfRUV4fcIEvDphAl6JhTcuuggtL7+MLVu2mL+dEabz3U2QOTqQJ8w63VmjzPgHeyyC417oGz8MToyb3gvlxU09G8aLMITXyJuW15npA+JIHMmB7HAgIwJC/giW/B2L1pdeRkNpKZqn34DG6dej9vrrzU8yd133A7NUUf/AAzhz9CjOfPEFjh09an6K2d7VhZb2dvNth5qaGvSoeJgxw3ge3hg/HuUTJuC1WBAhUTF5MqqXLTNlStkkR3bIQVyJKzlADpAD5EAQBzIiIOQvacofw6r756dQf9ONrnComTYV26dOxdaSElRfdx3WXXYJts6di0N1dejq7kZbWxta9u5FY0MDdu/ejZ4jR/D5Z5/h9ZtvdsWDCAgJ4oWQIGKi/Lzz8P7MW0yZUnZQ43ifxCcHyAFygBwgB7LDgYwICPmT3PJXNTfNn4/aH/zAeB22f//72DplCqpLSrBJvuNw2WVYNW4c3ho/HptKS7GvrQ17Wlpcz8O27dtx5swZfLBwoVm2kHhvWkFEhFwbQTFhAt782781ZUrZJEd2yEFciSs5QA6QA+RAEAcyJiD+8Ic/YMvixY7HQYTDtddi05Qp+OSaa7Bm8mSsHDcOK8aPxwff+Aaa33kHDS0tqK+vhyxbbNu2DVu2bsXm7dtRt3o11lx5pREKEl/C294gAuK738Uf//hHUECQ3EHk5n1ygxwgB8iB7HEgIwJClhH6T/Vj1/94EpunTsUmEQ8lU7D+iivw/rhxqIqJh1UXXYTm1atRv38/6urqzB/G2iYCYudObNm8GRs3bsQnO3agcf16rP32t414kLQiPt6zwvtFRXhv9mycOX0aXMLIHjn44hFbcoAcIAfIgSAOZERAyEbG/Qfased3v8PHU6eaT0+vu+oqY/jFeyDLDu9ddBGaVq1CXVsb6urrsWvXLvT09eHs6dNYV1WFT8QDsWmT+TXHzqYmtG7ZgvV/8zdGfKweNw4S1kgYOxZrzzsPm5cvR3t7O7iJkuQOIjfvkxvkADlADmSPAxkREPIzTvkWRNfHH2HdddOw/uqrXfEg+xaqLrwQTStXGvFQW1eHnTt3GvEwcPYsyqdORcWll2J9ZRWqa2qMV0L+2mZ7Tw96amvwyTe/aUTDhrFj8dHYsfh47FhUnjcJrRXlaf2Mk2TKHpmILbElB8gBcqBwOJARASHi4dXXXkXf/jZ8MG0aVl5wgVl+EM/DO5Mno6my0hEPtbVGPHT39UHEw2uxn2qKyKi8/HJsXr0ajQcO4EBbG7q7u3Hm/36JM3v2oPqib2DTmDHYPGYMqseMwTsXX4KTrS2oqCgP/SEpkrtwyM2+Zl+TA+QAOZA9DmREQOinrI/29mL1rFlY8fWvm2UL+XbD25dcgtqNG1HT3IwdO3agp7cXA2fO4JUbbjC/thDxoBsl37/ySjRUV+PIqVPo7+/Hf/7Xf5mfasrnrrePGYNd48Zi+6RJqHvmX3C6vx///NRToT5lTSJlj0jEltiSA+QAOVBYHMiIgBDSyB+2kq9Rtr70Et686CKUFxWZr0f+fsIEvDVlCjatXYvDx44Z8fDy9dfjfxUVGZEhAkL2SchGSdlwufav/xqHGhvxJ/li5dmz+GjOHHwydiwaxo9H44QJqDz/fHRXO3slwv4xLZK7sMjN/mZ/kwPkADmQPQ5kTEDYf8571a234o0//3O8NGGC+SDUi/K3LIqL0bxhA16adh3+rajIfBBKljjkew+V48cb8SAbJNeNHYutV1+NI+++i8233WaWLvZMmICWoiLUT/46Vs2Zk/af8yaRskckYktsyQFygBwoLA5kTEAIcSorK7Fh/XqcqK3F69/8Fl6dPNl4GkQwSPhN7Ch/00KWN0RAyPKFeB/kVxbrx4413gbZ5yBehx1jxhjhsH/iROy54AK8dfHF6G9owEcbNpiySNbCIiv7m/1NDpAD5EDucCCjAuLQoUN44YUX0NLSgvYVK/DGxRfjpcmT8duYcJBlC/nLmraAkOULWboQ74P8wkLEw87x41E/bpwRDwcmTkTL5MlY8Vd/hUMr38W+fftMGVIWiZQ7RGJfsC/IAXKAHCgsDmRUQAh55CeYv3n+efT09KBjxQq8dtllePnCC/HbiRONF8IWEOYnnh7vw7axY7G7qAjNRUVomzgRTZMn4+1LL8Wh994zeUreUgaJWlhEZX+zv8kBcoAcyC0OZFxASAfX7NplRIR4ImQ5Q/7w1e/+4i/w8vnnm19eyN4IWcKwBYR840F+plkzbgIaJ05E/fnn472vfQ2rS+eiv6nJeDVEPEjeJFFukYj9wf4gB8gBcqDwOJAVASFEEi+BLGfInoiB06dxuLoa2//hH/HaJZfipQsuwBtf+xpWFBWhavx4rBk/Hhvkj2xNnIhVkybhzfPPx/of/xhdK981aSUPyYueh8IjKAcl9jk5QA6QA7nJgawJCOlw2acgGyt//dxz5oNP/SdP4mR7Ow6uXYuGZ5/FugXzseK67+ONq67EqtK52PKzn2F/RTlOtLSg/9QpVG/ebNJKHtzzkJsE4ovNfiEHyAFyoDA5kFUBoaSSn3jKNxue+uUvUV5ebr4X0dHRYT4SJX8GXMLZM2cg9+RbEhJH4koaSav58Ji/JB1oKENJSRkaBgZypj/TrVO66fKJv/nexoayEkSiVaiKRlBSlvk9U5nAJxN5pMqpTJSViTxSrW+68bLd7+nWa7SmGxEBoeDJFyvls9fytzPkj2DJX9KUP8ctQc7lnv5dDYmr6TJ1LIlEEEkIJShryLxBS+dFG6iKJtYtWpXx9mcKx2T5BLU96L7kleyZlpVKHI2b6tHO05xb3EhmdOx0qZaVarxs5u1XB7u8oHO/dJm8l41yzfsUrYIYlIW//VXGxatdZxsLcz/LPAoq266H9zwozUjU11sXv+ug+vnFTXbP7vdoVebH9mRlF+KzERUQ5xrgXJsBKx5GNUeiqLJm51XRxGuNm+vHoIEg6L60J9kzbW8qcTRuqkfNs/5sJaKRuJgcGKhCNImA03TZ8KZkM++hcLHLts+HSjfc59koSwyJiMCRFBCGNyPAo3Tw8kszUvVNhR9+9UslnTeO3e8UENn3WBe8gFDilkXFOxFFZZ0zW9FrMeomjjurcAy7N51t/PVZfUJejvfDS+qBgQaUlcSN16AXQlz/vmVHES3RPCUPPY/VtyT+XLwuWu7QbYnnI3VJjO/UU9vnYBSP77TFuZYy7Vm8k8auUywv0/54mik/++9mtjgo74AlkMT6xUWXI8o03zi+ifEjiJSUwREQ8bTaB9pOFQp67fTr4LZIuoRyTd51pm9c/EWcxIxMUFz1kgl+ifW18Y+XH61K7H+tv9t/saUjJ68Yfw3ucb7Xn3XqqWUH9YOdt8nftEdxdniW0K5YWx3s4nVWTno5o+UK5olt93vvnHIVW2/d9Nope/DymV/+ksav/qatCe+iwx3lhnlusBjMo8Fp7X506pVYF4uvHnwXVib2UxBHBpeZen29eOl1PvFe2s+QfQwKS0C4hjg24MkAL0bex8DqoOSo9LgBNoNLtMod3DSeTdaEF87OW5YpPPsAnIEjYNCJDR5aRmLZsUHILH1Y526brEHIxImi0sy0h26LcQP6GNZU2qVx7IE1PpjF62TaYhs2+9wHMxVjdr5BfWP3hSlb2i995sHTrquslRvjaXke7OduG3zw1bY4XIr3pXqR1K2aUBdjjHziWkLJqW88jtbHKcfqczXSfvyyjJrUMxqNGjFp8ta22Njb5z79kIi/I1yUn17cB7c33v8Gk5jXTdsleeu5I+pS56pdL289NE87jpcL+m4NSpsCd+w0vjyy+sBgEutj5bRXwGp9VdR58dXnBq+gvD3vup1myPpaHBxUX8vDksu8t9vI8+wJicISELHB0SaU98VK6dryVNiDkuareegAoXH0vl5LfL973nw0vonrKdtOr+eDyjWDTAl+9V7iWrBffnadHEMVn106s9P4rDWhXrbhSRXnJAbEm7e3TXY9E+LaedqC0WMs/dKbe0ZsRRzBkWwgtdro4hgbtMWTleCRsgZ5MTBiENSADYprlenkmxx/7XPBwD6XtmioijqG2wgayV8FsB59+s6bl/c6CD/3/lDYxzgpe5DsvPXc29/mvof7bllWX2ib7aPmqTzxS6f5D/Y4xrxUMW+i5uGXZ0KZXh7ZeJjz+HuU6num+dtlO/VOzhG/9mpeenQE3ejivbaNx/hYkGksKCCsAVvAtV/OwGufgczuGM3DdxD0DHaOIYnPzPzySRi0PGVrWbYBGVTucASEp76BmPgYoVTa4g7YAem1fd42BdZD8bFmSkF56H3FV+vr9El8gNfnGt9bF3PfEg1+4sARDrJ84ScuxAA497UMuz+1fLd+FmdTiW88D1VViBqMxWsQRVVVzBORYl52OX71SLiXCvY5KiDMEmYq9bdw07Z7j0E80niKqZdP3uep9r+mk6PmrWm913ZcPQ+qr6b11tPct/ica7zXdvFIAeHOpoZDBr9NlPpyBL1o+lKoG1Fdnd50dr30me8L52OQTZ7Wiyh5yWwx6ZKDj8ENLDfm2k7qFrbq5ebjcYNqG/W5H2bmmactks6bRnF0n/kYUPeZj/fAPDNGKMDNbbXHlCV5mPbExZp7X2aXPksXpv+stiTE9+Yfm81HYz8Z9O5tcXCJ7wuRa7+4Nn5e7kmbbUwEfxtX+1zjavxoSYm7J6WhLGqWMnxn/0P0g/a5yTe2f0XfDS3Lfs+CMNNlMrcNnnLDctWul912vzo5dRcxN3zu2OUa/P14NMR75G2r1l/3h9j4uu1RvDzvQDxtfK+N3NN+SKm+Zlk3LnQ1rXc8M/dzmPeKBY8UEJkREIPciAFufcs4CPmcQV3dhINnil6C6kDufeH0vv0Sa1rzMtr1iw1EQ5Vt56nnjuHT+sZnt6m2RfOReiaWn5o7V9eBB22itNvnwVjT2Jvo3PqqgLDT6wAqM0H3fnzQ0/xk2aUkGnV/xue6aq37utbsLNEIXh6REctf8xmEb6wtavA1n4T2ezbLJourdR+8QW4w/oP6yoOrwdCa7ZvrmKB0+9dKo2UH9YOXu15+iLHTPGzsB2EW6z+pjwRNY5ebmLf/e2e3X/PyHhPzib8PiffT446Nhxp87X+bR4llBfSjy2Pnuds/1n0VE4pXEEdMWl1Gsbiean3t8Shfee/lAa8zLyQKagmjUAiUyqBaKFjkSjvtGXeu1Gkk60FOZn7wHsn+S+NnXYMAAAnNSURBVLesQud9urjlSzoKCGuzWb502lD15GCde4O1zBh19jhU/43G5+Rk7nFyJHhW6LwfCYzPZRkUEKNQQJxLQrHswjQU7Hf2OzlQeByggKCAyMj+Eg4ehTd4sM/Z5+RAYXOAAoICggKCHCAHyAFygBwIzQEKCJImNGk46yjsWQf7n/1PDpADwgEKCAoICghygBwgB8gBciA0ByggSJrQpOHsg7MPcoAcIAfIAQoICggKCHKAHCAHyAFyIDQHKCBImtCk4cyDMw9ygBwgB8gBCggKCAoIcoAcIAfIAXIgNAcoIEia0KThzIMzD3KAHCAHyAEKCAoICghygBwgB8gBciA0ByggSJrQpOHMgzMPcoAcIAfIAQoICggKCHKAHCAHyAFyIDQHKCBImtCk4cyDMw9ygBwgB8gBCggKCAoIcoAcIAfIAXIgNAcoIEia0KThzIMzD3KAHCAHyAEKCAoICghygBwgB8gBciA0ByggSJrQpCmEmUfk5/vBkB0MkvFn5cqVyLeQrD18xln6aOYABQQFBAWEDwdEPPxmxxlUNHzKkEEMBNdkA6qIh56enrwJUt9k7eEzCojRzAEjIP5y1v18CXyMyGjueLYt+cAmhk7EQyQSQd/p/+AxAzgYPCkgONZyrB01HKCAIJlHDZkzKYpUQIh4YMgMBhQQyUVrJvnLvIj1SHCAAoICggLChwMqINQDQRExPBEhOFJA0KiNhFFjGSPHMwoIH+NBAo4cAXMVaxUQIyEcemufQfGUZ7Ct//Oc8HZkqz4UEHyvcvV9Z73S4yYFBAUEPRA+HFABEdYD4Wd89d7W3f/iKxT0eSoCwsSNRMyeDKmbhAVvDy08UilD4wTVczhiaqQ8ENVPFidgU/xktdmQ2V39JIqLn0R1d7dzXT7fxJtf7lynu3GTmyjTMzw02KMDNwoIH+NBco8Ocg+nH1VAhDWaaoRtMeB3z853qOfJ4pq0KYiI4ZRhlz+c82x7IIx4sEVCdznmRyIQEWELCHMeKcaT1cMTDyI6KCA4VgxnnMn3tBQQFBD0QPhwQAVEtjwQavjVixCJLWEk3i/BU7WJ3gU/IWDf80vf29+Mp6bEvRbFTzdj29Ml1kzdKUfzsT0QCfGGscySbQ9EtxELg0WBCofNm2MeCPFEZEg8UEBQPOS7ABhu/SkgfIzHcEFl+vwfWFRAhJ1xJxrwuNEWgaCGeeupKiywvAau4Tb3F6EithdC7w/lzejtX4kFkUUoT5LeLy9tW+/bixB5cCU0jltPWXKJxOtT8WD8XNOGOWbTA6FCQZcodEnCERbz8ZoREMUZFQ8UEPn/nnOsHl4fUkBQQNAD4cMBFRDZ8ECogVZhkGC4PfsbIpYBF2OtcTWtuacCwhh8S7SYvByj701nru2ybIET26uhQsdbhzCiQeNm3QPh2ePgKyDE8/DkfESsZQ6Nl+6RSxjDM0A04PmNHwWEj/EgqfOb1JnoPxUQagBTPXoNtaTTeyoc9KgiwPtc7/uVqXHtOHrPm6+dXuNIOnMeiS+P6DNNr0ctw/FwiDDJYQ9EqksY3d0weyXml2fka5cUEBwrMjHe5GseRkDIf/naANabL3A2OKACIiseCLPUEDfgZp+BeAA8Sxu2ANBzNfZe4y6/xFBD7/erDEc0+Hsj3PLV82AdFzzdbH5a6uyjiNdZ65PqMdseCPEgpLyJsrsaTxY7myvT9TxoOgoIjj/ZGH/yJU8KCHogKB59OKACIlUDqfG8Bl7u6z17Zm/2HcSWEIofXOT+vNMx9NYyhGfj4qDnlifBLcuzNKFio+JBJ1/ZRKnnYti1fK2fe4wJGolj4sXEhLY17DGbeyDUoHt/xqk/0/TukXD2RgxfRFBAUEDki7HPRj0pIHyMRzaAZp75NdCogBDDGdZQMv7gr1YKjiMhIFRIjNSRAiK/3muOw5ntLwoICgh6IHw4oAKCYmCwGEgXk2wLCPWUBB2zISooIDJrkGjg8wtPCggf40ES5xeJs9FfKiDogciMgKAHgu9UNt5T5nlueUUBQQFBD4QPB1RApDvbZrrBwiPbHohseBiGypMeiHNrwCggzi3+FBA+xoOkPLekzAX8VUCoB4JHZy/IcHCggOB7lQvvNuuQOR5SQFBA0APhwwEVEGL0GDKHgeCabACXGf1Qs/5cek4PROaMUTJe8Flu4kwB4WM8SNbcJOtI9osYOobsYJCsH8Ug51tI1h4+41gymjlAAUEBkXRGOJrJz7ZxcCcHyAFyIH0OUEBQQFBAkAPkADlADpADoTlAAUHShCYNFXv6ip3YETtygBwYLRyggKCAoIAgB8gBcoAcIAdCc4ACgqQJTZrRop7ZDs4EyQFygBxInwMUEBQQFBDkADlADpAD5EBoDlBAkDShSUPFnr5iJ3bEjhwgB0YLByggKCAoIMgBcoAcIAfIgdAcoIAgaUKTZrSoZ7aDM0FygBwgB9LnAAUEBQQFBDlADpAD5AA5EJoDFBAkTWjSULGnr9iJHbEjB8iB0cIBV0DICUP+YPD444/DDsuXL4eExx57zIRHH30Uy5YtwyOPPIKlS5diyZIlWLx4MR566CH89Kc/NeEnP/kJGIgBOUAOZIIDOq7oUcYaCTL2yBj08MMPmzFJxygZr+wxTM5pg/LHBmlfRQ4dOoT29na0tbWhpaUFzc3NaGxsRH19Perq6rB7927U1NRg586d2LFjB7Zv345t27YxnEMMtmzZAg3V1dWQsGnTJhM2btyIjz/+2IT169dj3bp1WLNmDVavXo33338/4Y8VVVZWQsM777wDBmJADpADqXBAxw052n8A7d1334UEGWtWrVplxh4Zg2QsknFJxicZq3Tc0nFMjrQruWVXxdaLzRfbLxpAtIBogoaGBqMT9u3bh0hvby8OHz6Mrq4udHR0YP/+/WhtbYU83Lt3r4nY1NRkEklCFRaSEcO5w0A6U4N0roo8FXrS8fJC6guqAkPFhRw3bNjAQAzIAXJgWBywxxQRCCoSZMxRYaCGSI2RGiQdw2hLzp0tCcJebL3YfAmiAcS5IJpA9IHoBNELkePHj6Ovrw9HjhwxQuLgwYPo7Ow0Dw8cOGA8E5JAvBMSJIM9e/YwnGMMpEPtIF4jDdLxEmpra02Ql3TXrl1ukJeYgRiQA+RAJjlgjzFyruJAxiEZj3R8kqM9dsk5bUru2VSx9Wr3RQPIKoVoAtEH4nCQ1YvIqVOncOLECRw7dgzijRAh0d3dbR7aYkKWOSSxKA+G3MBAOtUO4jWygxBAgihHO3hfXl4nijHiQTzIgfAcsMcYna3K+GOPSXJuj1lyTnuSG/ZEBIIG7ROx+WL7xdsgwkE0gaxYiEYQrfD/ASuAFfyq86YCAAAAAElFTkSuQmCC"&gt;&lt;/p&gt;
</itunes:summary>
      <description>&lt;p&gt;Hi,&lt;/p&gt;

&lt;p&gt;I am trying to convert from MapleSim to Simulink Matlab by using the S-function code Generation connector, but I got the above message when I uploaded the selected subsystem and I have no idea how can I fix it. Please help me&lt;/p&gt;

&lt;p&gt;&lt;img src="data:image/png;base64,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" /&gt;&lt;/p&gt;
</description>
      <guid>238014</guid>
      <pubDate>Fri, 15 Mar 2024 10:50:50 Z</pubDate>
      <itunes:author>bachtdh1</itunes:author>
      <author>bachtdh1</author>
    </item>
    <item>
      <title>System of equations solve, solutions may be lost.  Any suggestions?</title>
      <link>http://www.mapleprimes.com/questions/201179-System-Of-Equations-Solve-Solutions?ref=Feed:MaplePrimes:Version MapleSim Connector</link>
      <itunes:summary>&lt;p&gt;Hi MaplePrime-ers!&lt;/p&gt;
&lt;p&gt;I've been using the Maple(17) toolbox in Matlab(2012b) to quickly enumerate systems of equations by: (i) solving them symbolically, (ii) using unapply to make them functions, (iii) then supplying the points (driver equations) to get the system solution. &amp;nbsp;Speed is a must, because there may be 3 million+ systems to solve. &amp;nbsp;Symbolics is also very important because I am evaluating topology, so the structure of the equations may change, and therefore a functional approach will not work.&lt;/p&gt;
&lt;p&gt;I have had success (seen in the first code snippet). &amp;nbsp;I would like similiar behaviour in the second code snippet, but sometimes I get&amp;nbsp;'&lt;strong&gt;solutions may be lost'&lt;/strong&gt;&amp;nbsp;as an error message, &amp;nbsp;or '&lt;strong&gt;Error, (in unapply) variables must be unique and of type name'&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;The system of equations include: &amp;nbsp;Linear equations, 5th order polynomials, absolute functions, and pieceiwse functions.&lt;/p&gt;
&lt;p&gt;Here is code with a topology that solves:&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;#Interconnection Equations&lt;br&gt;eq2[1] := FD_T + EM2_T = 0;&lt;br&gt;eq2[2] := ICE_T + GEN_T = 0;&lt;br&gt;eq2[3] := EM2_A + GEN_A + BAT_A = 0;&lt;br&gt;eq2[4] := -FD_W + EM2_W = 0;&lt;br&gt;eq2[5] := -ICE_W + GEN_W = 0;&lt;br&gt;eq2[6] := -EM2_V + GEN_V = 0;&lt;br&gt;eq2[7] := -EM2_V + BAT_V = 0;&lt;/p&gt;
&lt;p&gt;#ICE&lt;br&gt;eq_c[1] := ICE_mdot_g=((671.5) + (-21.94)*ICE_T + (0.1942)*ICE_W + (0.5113)*ICE_T^2 + (-0.01271)*ICE_T*ICE_W + ( -0.0008761)*ICE_W^2 + (-0.006071)*ICE_T^3 + (9.867e-07)*ICE_T^2*ICE_W + (5.616e-05)*ICE_T*ICE_W^2 + (1.588e-06)*ICE_W^3 + (3.61e-05)*ICE_T^4 + (8.98e-07)*ICE_T^3*ICE_W + (-2.814e-07)*ICE_T^2*ICE_W^2 + (-8.121e-08)*ICE_T*ICE_W^3 + ( -8.494e-08 )*ICE_T^5 + (-2.444e-09)*ICE_T^4*ICE_W + (-9.311e-10)*ICE_T^3*ICE_W^2 + ( 5.835e-10)*ICE_T^2*ICE_W^3 ) *1/3600/1000 * ICE_T * ICE_W;&lt;/p&gt;
&lt;p&gt;#BAT&lt;br&gt;eq_c[2] := BAT = 271;&lt;/p&gt;
&lt;p&gt;#EM2&lt;br&gt;EM2_ReqPow_eq := (-148.3) + (4.267)*abs(EM2_W) + (12.77)*abs(EM2_T) + (-0.0364)*abs(EM2_W)^2 + ( 1.16)*abs(EM2_W)*abs(EM2_T) + (-0.258)*abs(EM2_T)^2 + ( 0.0001181)*abs(EM2_W)^3 + (-0.0005994)*abs(EM2_W)^2*abs(EM2_T) + ( 0.0001171)*abs(EM2_W)*abs(EM2_T)^2 + (0.001739 )*abs(EM2_T)^3 + (-1.245e-07 )*abs(EM2_W)^4 + ( 1.2e-06)*abs(EM2_W)^3*abs(EM2_T) + ( -1.584e-06)*abs(EM2_W)^2*abs(EM2_T)^2 + ( 4.383e-07)*abs(EM2_W)*abs(EM2_T)^3 + (-2.947e-06)*abs(EM2_T)^4;&lt;br&gt;eq_c[3] := EM2_P = piecewise( EM2_T = 0, 0, EM2_W = 0, 0, EM2_W*EM2_T &amp;lt; 0,-1 * EM2_ReqPow_eq, EM2_ReqPow_eq);&lt;br&gt;eq_c[4] := EM2_A = EM2_P/EM2_V;&lt;/p&gt;
&lt;p&gt;#GEN&lt;br&gt;GEN_ReqPow_eq:= (-5.28e-12) + ( 3.849e-14)*abs(GEN_W) + (-71.9)*abs(GEN_T) + (-1.168e-16)*abs(GEN_W)^2 +(1.296)*abs(GEN_W)*abs(GEN_T) + (2.489)*abs(GEN_T)^2 + (1.451e-19)*abs(GEN_W)^3 + (0.0001326)*abs(GEN_W)^2*abs(GEN_T) + (-0.008141)*abs(GEN_W)*abs(GEN_T)^2 + (-0.004539)*abs(GEN_T)^3 +(-6.325e-23)*abs(GEN_W)^4 + (-2.091e-07)*abs(GEN_W)^3*abs(GEN_T) + ( 3.455e-06)*abs(GEN_W)^2*abs(GEN_T)^2 + ( 2.499e-05)*abs(GEN_W)*abs(GEN_T)^3 + (-5.321e-05)*abs(GEN_T)^4;&lt;br&gt;eq_c[5] := GEN_P = piecewise( GEN_T = 0, 0, GEN_W = 0, 0, GEN_W*GEN_T &amp;lt; 0,-1 * GEN_ReqPow_eq, GEN_ReqPow_eq);&lt;br&gt;eq_c[6] := GEN_A = GEN_P/GEN_V;&lt;/p&gt;
&lt;p&gt;#ASSUMPTIONS&lt;br&gt;assume(BAT_V::nonnegative);&lt;br&gt;assume(FD_W::nonnegative);&lt;br&gt;&lt;br&gt;#FINAL EQUATIONS&lt;/p&gt;
&lt;p&gt;sys_eqs2 := convert(eq2,set) union {eq_c[1],eq_c[2],eq_c[3],eq_c[4],eq_c[5],eq_c[6]};&lt;/p&gt;
&lt;p&gt;#Selecting which variables to solve for:&lt;/p&gt;
&lt;p&gt;drivers2:= { ICE_T,ICE_W,FD_T,FD_W};&lt;br&gt;symvarnames2:=select(type,indets(convert(sys_eqs2,list)),name);&lt;br&gt;notdrivers2:=symvarnames2 minus drivers2;&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;/p&gt;
&lt;p&gt;#Symbolic solve&lt;/p&gt;
&lt;p&gt;sol2:=solve(sys_eqs2,notdrivers2) assuming real:&lt;br&gt;symb_sol2:=unapply(sol2,convert(drivers2,list)):&lt;br&gt;&lt;br&gt;&lt;br&gt;#Enumerate (there will generally be about 40, not 6)&lt;/p&gt;
&lt;p&gt;count := 0;&lt;br&gt;for i1 from 1 to 40 do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;for i2 from 1 to 40&amp;nbsp;do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; for i3 from 1 to 40&amp;nbsp;do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;for i4 from 1 to 40&amp;nbsp;do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; count := count + 1;&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;&amp;nbsp;solsol2(count) := symb_sol2(i1,i2,i3,i4);&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;od; &lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; od;&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;od;&lt;br&gt;od;&lt;br&gt;count;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;&lt;br&gt;&lt;br&gt;&lt;/p&gt;
&lt;p&gt;This works great! &amp;nbsp;I would like simliar output in my second code snippet, but this time with more inputs to symb_sol. &amp;nbsp;However, if I try and change the interconnection equations a little, and add a piecewise function, and another driver... &lt;strong&gt;(differences in bold)&lt;/strong&gt;&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;#Interconnection Equations&lt;br&gt;eq1[1] := FD_T+EM2_T = 0;&lt;br&gt;&lt;strong&gt;eq1[2] := ICE_T+GBb_T = 0;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq1[3] := GEN_T+GBa_T = 0;&lt;/strong&gt;&lt;br&gt;eq1[4] := EM2_A+GEN_A+BAT_A = 0;&lt;br&gt;eq1[5] := -FD_W+EM2_W = 0;&lt;br&gt;&lt;strong&gt;eq1[6] := -GEN_W+GBa_W = 0;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq1[7] := -ICE_W+GBb_W = 0;&lt;/strong&gt;&lt;br&gt;eq1[8] := -EM2_V+GEN_V = 0;&lt;br&gt;eq1[9] := -EM2_V+BAT_V = 0;&lt;/p&gt;
&lt;p&gt;#ICE&lt;br&gt;eq_c[1] := ICE_mdot_g=((671.5) + (-21.94)*ICE_T + (0.1942)*ICE_W + (0.5113)*ICE_T^2 + (-0.01271)*ICE_T*ICE_W + ( -0.0008761)*ICE_W^2 + (-0.006071)*ICE_T^3 + (9.867e-07)*ICE_T^2*ICE_W + (5.616e-05)*ICE_T*ICE_W^2 + (1.588e-06)*ICE_W^3 + (3.61e-05)*ICE_T^4 + (8.98e-07)*ICE_T^3*ICE_W + (-2.814e-07)*ICE_T^2*ICE_W^2 + (-8.121e-08)*ICE_T*ICE_W^3 + ( -8.494e-08 )*ICE_T^5 + (-2.444e-09)*ICE_T^4*ICE_W + (-9.311e-10)*ICE_T^3*ICE_W^2 + ( 5.835e-10)*ICE_T^2*ICE_W^3 ) *1/3600/1000 * ICE_T * ICE_W;&lt;/p&gt;
&lt;p&gt;#BAT&lt;br&gt;eq_c[2] := BAT = 271;&lt;/p&gt;
&lt;p&gt;#EM2&lt;br&gt;EM2_ReqPow_eq := (-148.3) + (4.267)*abs(EM2_W) + (12.77)*abs(EM2_T) + (-0.0364)*abs(EM2_W)^2 + ( 1.16)*abs(EM2_W)*abs(EM2_T) + (-0.258)*abs(EM2_T)^2 + ( 0.0001181)*abs(EM2_W)^3 + (-0.0005994)*abs(EM2_W)^2*abs(EM2_T) + ( 0.0001171)*abs(EM2_W)*abs(EM2_T)^2 + (0.001739 )*abs(EM2_T)^3 + (-1.245e-07 )*abs(EM2_W)^4 + ( 1.2e-06)*abs(EM2_W)^3*abs(EM2_T) + ( -1.584e-06)*abs(EM2_W)^2*abs(EM2_T)^2 + ( 4.383e-07)*abs(EM2_W)*abs(EM2_T)^3 + (-2.947e-06)*abs(EM2_T)^4;&lt;br&gt;eq_c[3] := EM2_P = piecewise( EM2_T = 0, 0, EM2_W = 0, 0, EM2_W*EM2_T &amp;lt; 0,-1 * EM2_ReqPow_eq, EM2_ReqPow_eq);&lt;br&gt;eq_c[4] := EM2_A = EM2_P/EM2_V;&lt;/p&gt;
&lt;p&gt;#GEN&lt;br&gt;GEN_ReqPow_eq:= (-5.28e-12) + ( 3.849e-14)*abs(GEN_W) + (-71.9)*abs(GEN_T) + (-1.168e-16)*abs(GEN_W)^2 +(1.296)*abs(GEN_W)*abs(GEN_T) + (2.489)*abs(GEN_T)^2 + (1.451e-19)*abs(GEN_W)^3 + (0.0001326)*abs(GEN_W)^2*abs(GEN_T) + (-0.008141)*abs(GEN_W)*abs(GEN_T)^2 + (-0.004539)*abs(GEN_T)^3 +(-6.325e-23)*abs(GEN_W)^4 + (-2.091e-07)*abs(GEN_W)^3*abs(GEN_T) + ( 3.455e-06)*abs(GEN_W)^2*abs(GEN_T)^2 + ( 2.499e-05)*abs(GEN_W)*abs(GEN_T)^3 + (-5.321e-05)*abs(GEN_T)^4;&lt;br&gt;eq_c[5] := GEN_P = piecewise( GEN_T = 0, 0, GEN_W = 0, 0, GEN_W*GEN_T &amp;lt; 0,-1 * GEN_ReqPow_eq, GEN_ReqPow_eq);&lt;br&gt;eq_c[6] := GEN_A = GEN_P/GEN_V;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;#GB&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;FiveSpeedGearbox_R := proc(ig) &lt;/strong&gt;&lt;br&gt;&lt;strong&gt;local i ,eq;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[1]:=3.32;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[2]:=2;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[3]:=1.36;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[4]:=1.01;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[5]:=0.82;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq:= piecewise(ig=1,i[1],ig=2, i[2],ig=3,i[3],ig=4,i[4],ig=5,i[5],1); &lt;/strong&gt;&lt;br&gt;&lt;strong&gt;return eq(ig);&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;end proc;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;br&gt;&lt;strong&gt;eq_c[7] := GBb_T = -1/GB_R * GBa_T;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq_c[8] := GBb_W = GB_R * GBa_W;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq_c[9] := GB_R = FiveSpeedGearbox_R(ig);&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;#System Equations&lt;br&gt;sys_eqs := convert(eq1,set) union convert(eq_c,set);&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;&amp;nbsp;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;#Solve for variables&lt;br&gt;symvarnames:=select(type,indets(convert(sys_eqs,list)),name);&lt;br&gt;&lt;strong&gt;drivers:= {ig, ICE_T,ICE_W,FD_T,FD_W};&lt;/strong&gt;&lt;br&gt;not_drivers := symvarnames minus drivers;&lt;br&gt;&lt;br&gt;#Assumptinons&lt;/p&gt;
&lt;p&gt;assume(BAT_V::nonnegative);&lt;br&gt;assume(FD_W::nonnegative);&lt;br&gt;&lt;br&gt;&lt;/p&gt;
&lt;p&gt;sol:=(solve(sys_eqs,not_drivers) assuming real);&lt;/p&gt;
&lt;p&gt;symb_sol:=unapply(sol,convert(drivers,list)): ---&amp;gt; &lt;strong&gt;Error, (in unapply) variables must be unique and of type name&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Subsequent parts don't work...&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;count := 0;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;for i1 from 1 to 40 do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;for i2 from 1 to&amp;nbsp;40&amp;nbsp;do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; for i3 from 1 to&amp;nbsp;40&amp;nbsp;do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;for i4 from 1 to&amp;nbsp;40&amp;nbsp;do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; for i5 from 1 to 40 do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;count := count + 1;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;solsol2(count) := symb_sol2(i1,i2,i3,i4,5);&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;od;&amp;nbsp;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;count;&lt;/strong&gt;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;While running the last line sol:, 1 of 2 things will happen, depending on the solver. Maple17 will take a long time (30+ minutes) to solve, then report nothing, or sol will solve, but will report "some solutions have been lost".&lt;/p&gt;
&lt;p&gt;Afterwards, evaluating symb_sol(0,0,0,0,0) will return a viable solution (real values for each of the variables). &amp;nbsp;Whereas&amp;nbsp;evaluating symb_sol(0,X,0,0,0), where X &amp;lt;&amp;gt; 0, will return and empty list [].&lt;/p&gt;
&lt;p&gt;Does anyone know how to (i) speed up the symbolic solve time? &amp;nbsp;(ii) Return ALL of the solutions?&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;Thanks in advance for reading this. &amp;nbsp;I've really no idea why this isn't working. &amp;nbsp;I've also attached two worksheets with the code:&amp;nbsp;&lt;a href="/view.aspx?sf=201179_question/noGB.mw"&gt;noGB.mw&lt;/a&gt;&amp;nbsp; &amp;nbsp;&lt;a href="/view.aspx?sf=201179_question/withGB.mw"&gt;withGB.mw&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;Adam&lt;/p&gt;</itunes:summary>
      <description>&lt;p&gt;Hi MaplePrime-ers!&lt;/p&gt;
&lt;p&gt;I've been using the Maple(17) toolbox in Matlab(2012b) to quickly enumerate systems of equations by: (i) solving them symbolically, (ii) using unapply to make them functions, (iii) then supplying the points (driver equations) to get the system solution. &amp;nbsp;Speed is a must, because there may be 3 million+ systems to solve. &amp;nbsp;Symbolics is also very important because I am evaluating topology, so the structure of the equations may change, and therefore a functional approach will not work.&lt;/p&gt;
&lt;p&gt;I have had success (seen in the first code snippet). &amp;nbsp;I would like similiar behaviour in the second code snippet, but sometimes I get&amp;nbsp;'&lt;strong&gt;solutions may be lost'&lt;/strong&gt;&amp;nbsp;as an error message, &amp;nbsp;or '&lt;strong&gt;Error, (in unapply) variables must be unique and of type name'&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;The system of equations include: &amp;nbsp;Linear equations, 5th order polynomials, absolute functions, and pieceiwse functions.&lt;/p&gt;
&lt;p&gt;Here is code with a topology that solves:&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;#Interconnection Equations&lt;br&gt;eq2[1] := FD_T + EM2_T = 0;&lt;br&gt;eq2[2] := ICE_T + GEN_T = 0;&lt;br&gt;eq2[3] := EM2_A + GEN_A + BAT_A = 0;&lt;br&gt;eq2[4] := -FD_W + EM2_W = 0;&lt;br&gt;eq2[5] := -ICE_W + GEN_W = 0;&lt;br&gt;eq2[6] := -EM2_V + GEN_V = 0;&lt;br&gt;eq2[7] := -EM2_V + BAT_V = 0;&lt;/p&gt;
&lt;p&gt;#ICE&lt;br&gt;eq_c[1] := ICE_mdot_g=((671.5) + (-21.94)*ICE_T + (0.1942)*ICE_W + (0.5113)*ICE_T^2 + (-0.01271)*ICE_T*ICE_W + ( -0.0008761)*ICE_W^2 + (-0.006071)*ICE_T^3 + (9.867e-07)*ICE_T^2*ICE_W + (5.616e-05)*ICE_T*ICE_W^2 + (1.588e-06)*ICE_W^3 + (3.61e-05)*ICE_T^4 + (8.98e-07)*ICE_T^3*ICE_W + (-2.814e-07)*ICE_T^2*ICE_W^2 + (-8.121e-08)*ICE_T*ICE_W^3 + ( -8.494e-08 )*ICE_T^5 + (-2.444e-09)*ICE_T^4*ICE_W + (-9.311e-10)*ICE_T^3*ICE_W^2 + ( 5.835e-10)*ICE_T^2*ICE_W^3 ) *1/3600/1000 * ICE_T * ICE_W;&lt;/p&gt;
&lt;p&gt;#BAT&lt;br&gt;eq_c[2] := BAT = 271;&lt;/p&gt;
&lt;p&gt;#EM2&lt;br&gt;EM2_ReqPow_eq := (-148.3) + (4.267)*abs(EM2_W) + (12.77)*abs(EM2_T) + (-0.0364)*abs(EM2_W)^2 + ( 1.16)*abs(EM2_W)*abs(EM2_T) + (-0.258)*abs(EM2_T)^2 + ( 0.0001181)*abs(EM2_W)^3 + (-0.0005994)*abs(EM2_W)^2*abs(EM2_T) + ( 0.0001171)*abs(EM2_W)*abs(EM2_T)^2 + (0.001739 )*abs(EM2_T)^3 + (-1.245e-07 )*abs(EM2_W)^4 + ( 1.2e-06)*abs(EM2_W)^3*abs(EM2_T) + ( -1.584e-06)*abs(EM2_W)^2*abs(EM2_T)^2 + ( 4.383e-07)*abs(EM2_W)*abs(EM2_T)^3 + (-2.947e-06)*abs(EM2_T)^4;&lt;br&gt;eq_c[3] := EM2_P = piecewise( EM2_T = 0, 0, EM2_W = 0, 0, EM2_W*EM2_T &amp;lt; 0,-1 * EM2_ReqPow_eq, EM2_ReqPow_eq);&lt;br&gt;eq_c[4] := EM2_A = EM2_P/EM2_V;&lt;/p&gt;
&lt;p&gt;#GEN&lt;br&gt;GEN_ReqPow_eq:= (-5.28e-12) + ( 3.849e-14)*abs(GEN_W) + (-71.9)*abs(GEN_T) + (-1.168e-16)*abs(GEN_W)^2 +(1.296)*abs(GEN_W)*abs(GEN_T) + (2.489)*abs(GEN_T)^2 + (1.451e-19)*abs(GEN_W)^3 + (0.0001326)*abs(GEN_W)^2*abs(GEN_T) + (-0.008141)*abs(GEN_W)*abs(GEN_T)^2 + (-0.004539)*abs(GEN_T)^3 +(-6.325e-23)*abs(GEN_W)^4 + (-2.091e-07)*abs(GEN_W)^3*abs(GEN_T) + ( 3.455e-06)*abs(GEN_W)^2*abs(GEN_T)^2 + ( 2.499e-05)*abs(GEN_W)*abs(GEN_T)^3 + (-5.321e-05)*abs(GEN_T)^4;&lt;br&gt;eq_c[5] := GEN_P = piecewise( GEN_T = 0, 0, GEN_W = 0, 0, GEN_W*GEN_T &amp;lt; 0,-1 * GEN_ReqPow_eq, GEN_ReqPow_eq);&lt;br&gt;eq_c[6] := GEN_A = GEN_P/GEN_V;&lt;/p&gt;
&lt;p&gt;#ASSUMPTIONS&lt;br&gt;assume(BAT_V::nonnegative);&lt;br&gt;assume(FD_W::nonnegative);&lt;br&gt;&lt;br&gt;#FINAL EQUATIONS&lt;/p&gt;
&lt;p&gt;sys_eqs2 := convert(eq2,set) union {eq_c[1],eq_c[2],eq_c[3],eq_c[4],eq_c[5],eq_c[6]};&lt;/p&gt;
&lt;p&gt;#Selecting which variables to solve for:&lt;/p&gt;
&lt;p&gt;drivers2:= { ICE_T,ICE_W,FD_T,FD_W};&lt;br&gt;symvarnames2:=select(type,indets(convert(sys_eqs2,list)),name);&lt;br&gt;notdrivers2:=symvarnames2 minus drivers2;&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;/p&gt;
&lt;p&gt;#Symbolic solve&lt;/p&gt;
&lt;p&gt;sol2:=solve(sys_eqs2,notdrivers2) assuming real:&lt;br&gt;symb_sol2:=unapply(sol2,convert(drivers2,list)):&lt;br&gt;&lt;br&gt;&lt;br&gt;#Enumerate (there will generally be about 40, not 6)&lt;/p&gt;
&lt;p&gt;count := 0;&lt;br&gt;for i1 from 1 to 40 do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;for i2 from 1 to 40&amp;nbsp;do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; for i3 from 1 to 40&amp;nbsp;do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;for i4 from 1 to 40&amp;nbsp;do&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; count := count + 1;&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;&amp;nbsp;solsol2(count) := symb_sol2(i1,i2,i3,i4);&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;od; &lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; od;&lt;br&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;od;&lt;br&gt;od;&lt;br&gt;count;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;&lt;br&gt;&lt;br&gt;&lt;/p&gt;
&lt;p&gt;This works great! &amp;nbsp;I would like simliar output in my second code snippet, but this time with more inputs to symb_sol. &amp;nbsp;However, if I try and change the interconnection equations a little, and add a piecewise function, and another driver... &lt;strong&gt;(differences in bold)&lt;/strong&gt;&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;#Interconnection Equations&lt;br&gt;eq1[1] := FD_T+EM2_T = 0;&lt;br&gt;&lt;strong&gt;eq1[2] := ICE_T+GBb_T = 0;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq1[3] := GEN_T+GBa_T = 0;&lt;/strong&gt;&lt;br&gt;eq1[4] := EM2_A+GEN_A+BAT_A = 0;&lt;br&gt;eq1[5] := -FD_W+EM2_W = 0;&lt;br&gt;&lt;strong&gt;eq1[6] := -GEN_W+GBa_W = 0;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq1[7] := -ICE_W+GBb_W = 0;&lt;/strong&gt;&lt;br&gt;eq1[8] := -EM2_V+GEN_V = 0;&lt;br&gt;eq1[9] := -EM2_V+BAT_V = 0;&lt;/p&gt;
&lt;p&gt;#ICE&lt;br&gt;eq_c[1] := ICE_mdot_g=((671.5) + (-21.94)*ICE_T + (0.1942)*ICE_W + (0.5113)*ICE_T^2 + (-0.01271)*ICE_T*ICE_W + ( -0.0008761)*ICE_W^2 + (-0.006071)*ICE_T^3 + (9.867e-07)*ICE_T^2*ICE_W + (5.616e-05)*ICE_T*ICE_W^2 + (1.588e-06)*ICE_W^3 + (3.61e-05)*ICE_T^4 + (8.98e-07)*ICE_T^3*ICE_W + (-2.814e-07)*ICE_T^2*ICE_W^2 + (-8.121e-08)*ICE_T*ICE_W^3 + ( -8.494e-08 )*ICE_T^5 + (-2.444e-09)*ICE_T^4*ICE_W + (-9.311e-10)*ICE_T^3*ICE_W^2 + ( 5.835e-10)*ICE_T^2*ICE_W^3 ) *1/3600/1000 * ICE_T * ICE_W;&lt;/p&gt;
&lt;p&gt;#BAT&lt;br&gt;eq_c[2] := BAT = 271;&lt;/p&gt;
&lt;p&gt;#EM2&lt;br&gt;EM2_ReqPow_eq := (-148.3) + (4.267)*abs(EM2_W) + (12.77)*abs(EM2_T) + (-0.0364)*abs(EM2_W)^2 + ( 1.16)*abs(EM2_W)*abs(EM2_T) + (-0.258)*abs(EM2_T)^2 + ( 0.0001181)*abs(EM2_W)^3 + (-0.0005994)*abs(EM2_W)^2*abs(EM2_T) + ( 0.0001171)*abs(EM2_W)*abs(EM2_T)^2 + (0.001739 )*abs(EM2_T)^3 + (-1.245e-07 )*abs(EM2_W)^4 + ( 1.2e-06)*abs(EM2_W)^3*abs(EM2_T) + ( -1.584e-06)*abs(EM2_W)^2*abs(EM2_T)^2 + ( 4.383e-07)*abs(EM2_W)*abs(EM2_T)^3 + (-2.947e-06)*abs(EM2_T)^4;&lt;br&gt;eq_c[3] := EM2_P = piecewise( EM2_T = 0, 0, EM2_W = 0, 0, EM2_W*EM2_T &amp;lt; 0,-1 * EM2_ReqPow_eq, EM2_ReqPow_eq);&lt;br&gt;eq_c[4] := EM2_A = EM2_P/EM2_V;&lt;/p&gt;
&lt;p&gt;#GEN&lt;br&gt;GEN_ReqPow_eq:= (-5.28e-12) + ( 3.849e-14)*abs(GEN_W) + (-71.9)*abs(GEN_T) + (-1.168e-16)*abs(GEN_W)^2 +(1.296)*abs(GEN_W)*abs(GEN_T) + (2.489)*abs(GEN_T)^2 + (1.451e-19)*abs(GEN_W)^3 + (0.0001326)*abs(GEN_W)^2*abs(GEN_T) + (-0.008141)*abs(GEN_W)*abs(GEN_T)^2 + (-0.004539)*abs(GEN_T)^3 +(-6.325e-23)*abs(GEN_W)^4 + (-2.091e-07)*abs(GEN_W)^3*abs(GEN_T) + ( 3.455e-06)*abs(GEN_W)^2*abs(GEN_T)^2 + ( 2.499e-05)*abs(GEN_W)*abs(GEN_T)^3 + (-5.321e-05)*abs(GEN_T)^4;&lt;br&gt;eq_c[5] := GEN_P = piecewise( GEN_T = 0, 0, GEN_W = 0, 0, GEN_W*GEN_T &amp;lt; 0,-1 * GEN_ReqPow_eq, GEN_ReqPow_eq);&lt;br&gt;eq_c[6] := GEN_A = GEN_P/GEN_V;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;#GB&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;FiveSpeedGearbox_R := proc(ig) &lt;/strong&gt;&lt;br&gt;&lt;strong&gt;local i ,eq;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[1]:=3.32;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[2]:=2;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[3]:=1.36;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[4]:=1.01;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;i[5]:=0.82;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq:= piecewise(ig=1,i[1],ig=2, i[2],ig=3,i[3],ig=4,i[4],ig=5,i[5],1); &lt;/strong&gt;&lt;br&gt;&lt;strong&gt;return eq(ig);&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;end proc;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;br&gt;&lt;strong&gt;eq_c[7] := GBb_T = -1/GB_R * GBa_T;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq_c[8] := GBb_W = GB_R * GBa_W;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;eq_c[9] := GB_R = FiveSpeedGearbox_R(ig);&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;#System Equations&lt;br&gt;sys_eqs := convert(eq1,set) union convert(eq_c,set);&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;&amp;nbsp;&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;#Solve for variables&lt;br&gt;symvarnames:=select(type,indets(convert(sys_eqs,list)),name);&lt;br&gt;&lt;strong&gt;drivers:= {ig, ICE_T,ICE_W,FD_T,FD_W};&lt;/strong&gt;&lt;br&gt;not_drivers := symvarnames minus drivers;&lt;br&gt;&lt;br&gt;#Assumptinons&lt;/p&gt;
&lt;p&gt;assume(BAT_V::nonnegative);&lt;br&gt;assume(FD_W::nonnegative);&lt;br&gt;&lt;br&gt;&lt;/p&gt;
&lt;p&gt;sol:=(solve(sys_eqs,not_drivers) assuming real);&lt;/p&gt;
&lt;p&gt;symb_sol:=unapply(sol,convert(drivers,list)): ---&amp;gt; &lt;strong&gt;Error, (in unapply) variables must be unique and of type name&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Subsequent parts don't work...&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;count := 0;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;for i1 from 1 to 40 do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;for i2 from 1 to&amp;nbsp;40&amp;nbsp;do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; for i3 from 1 to&amp;nbsp;40&amp;nbsp;do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;for i4 from 1 to&amp;nbsp;40&amp;nbsp;do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; for i5 from 1 to 40 do&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;count := count + 1;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;solsol2(count) := symb_sol2(i1,i2,i3,i4,5);&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp;od;&amp;nbsp;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;od;&lt;/strong&gt;&lt;br&gt;&lt;strong&gt;count;&lt;/strong&gt;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;While running the last line sol:, 1 of 2 things will happen, depending on the solver. Maple17 will take a long time (30+ minutes) to solve, then report nothing, or sol will solve, but will report "some solutions have been lost".&lt;/p&gt;
&lt;p&gt;Afterwards, evaluating symb_sol(0,0,0,0,0) will return a viable solution (real values for each of the variables). &amp;nbsp;Whereas&amp;nbsp;evaluating symb_sol(0,X,0,0,0), where X &amp;lt;&amp;gt; 0, will return and empty list [].&lt;/p&gt;
&lt;p&gt;Does anyone know how to (i) speed up the symbolic solve time? &amp;nbsp;(ii) Return ALL of the solutions?&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;Thanks in advance for reading this. &amp;nbsp;I've really no idea why this isn't working. &amp;nbsp;I've also attached two worksheets with the code:&amp;nbsp;&lt;a href="/view.aspx?sf=201179_question/noGB.mw"&gt;noGB.mw&lt;/a&gt;&amp;nbsp; &amp;nbsp;&lt;a href="/view.aspx?sf=201179_question/withGB.mw"&gt;withGB.mw&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;Adam&lt;/p&gt;</description>
      <guid>201179</guid>
      <pubDate>Wed, 19 Mar 2014 20:56:01 Z</pubDate>
      <itunes:author>teh_allchemist</itunes:author>
      <author>teh_allchemist</author>
    </item>
    <item>
      <title>MapleSim Connector C code api?</title>
      <link>http://www.mapleprimes.com/questions/145427-MapleSim-Connector-C-Code-Api?ref=Feed:MaplePrimes:Version MapleSim Connector</link>
      <itunes:summary>&lt;p&gt;Hello,&lt;/p&gt;
&lt;p&gt;I have a model in MapleSim for which I've generated the optimized C code using the connector toolbox, and I'd like to work with it directly. I was wondering if there is any documentation or examples of how to do this? I haven't been able to find any online.&lt;/p&gt;
&lt;p&gt;Thanks!&amp;nbsp;&lt;/p&gt;</itunes:summary>
      <description>&lt;p&gt;Hello,&lt;/p&gt;
&lt;p&gt;I have a model in MapleSim for which I've generated the optimized C code using the connector toolbox, and I'd like to work with it directly. I was wondering if there is any documentation or examples of how to do this? I haven't been able to find any online.&lt;/p&gt;
&lt;p&gt;Thanks!&amp;nbsp;&lt;/p&gt;</description>
      <guid>145427</guid>
      <pubDate>Wed, 03 Apr 2013 19:53:21 Z</pubDate>
      <itunes:author>tdewolf</itunes:author>
      <author>tdewolf</author>
    </item>
    <item>
      <title>maplesim connector sfunction</title>
      <link>http://www.mapleprimes.com/questions/97081-Maplesim-Connector-Sfunction?ref=Feed:MaplePrimes:Version MapleSim Connector</link>
      <itunes:summary>&lt;p&gt;Hi,&lt;/p&gt;
&lt;p&gt;I have downloaded the lead acid battery model from the link &lt;a href="http://www.maplesoft.com/applications/view.aspx?SID=34125"&gt;http://www.maplesoft.com/applications/view.aspx?SID=34125&lt;/a&gt;. I have made the whole system as a subsystem block and tried to generate a simulink sfunction block, but I was not successful. I am getting the below error while doing so.&lt;/p&gt;
&lt;p&gt;&amp;nbsp;Error in Component Button43 with caption "Generate to Simulink":&lt;br&gt;(in MapleSim:-GetInitialConditions:-GetInitialConditions...</itunes:summary>
      <description>&lt;p&gt;Hi,&lt;/p&gt;
&lt;p&gt;I have downloaded the lead acid battery model from the link &lt;a href="http://www.maplesoft.com/applications/view.aspx?SID=34125"&gt;http://www.maplesoft.com/applications/view.aspx?SID=34125&lt;/a&gt;. I have made the whole system as a subsystem block and tried to generate a simulink sfunction block, but I was not successful. I am getting the below error while doing so.&lt;/p&gt;
&lt;p&gt;&amp;nbsp;Error in Component Button43 with caption "Generate to Simulink":&lt;br&gt;(in MapleSim:-GetInitialConditions:-GetInitialConditions) non-constant values.&lt;/p&gt;
&lt;p&gt;Can someone help me out in generating the equvalent sfunction block for the ablove example.&lt;/p&gt;
&lt;p&gt;Thanks in advance.&lt;/p&gt;
&lt;p&gt;Regards,&lt;br&gt;Venky&lt;/p&gt;</description>
      <guid>97081</guid>
      <pubDate>Tue, 21 Sep 2010 15:48:59 Z</pubDate>
      <itunes:author>venky</itunes:author>
      <author>venky</author>
    </item>
    <item>
      <title>How to get in ports on Simulink S function block?</title>
      <link>http://www.mapleprimes.com/questions/89809-How-To-Get-In-Ports-On-Simulink-S-Function-Block?ref=Feed:MaplePrimes:Version MapleSim Connector</link>
      <itunes:summary>&lt;p&gt;I am trying to create a Simulink component block from a MapleSim subsystem. I have one input to the subsystem, and the Specified Inputs and Outputs section of the MapleSim Connector worksheet also shows that the subsystem has one input. However, When  I export the model to Simulink, there is no input port, just one output. How can I fix this?&lt;/p&gt;</itunes:summary>
      <description>&lt;p&gt;I am trying to create a Simulink component block from a MapleSim subsystem. I have one input to the subsystem, and the Specified Inputs and Outputs section of the MapleSim Connector worksheet also shows that the subsystem has one input. However, When  I export the model to Simulink, there is no input port, just one output. How can I fix this?&lt;/p&gt;</description>
      <guid>89809</guid>
      <pubDate>Thu, 17 Jun 2010 20:43:56 Z</pubDate>
      <itunes:author>mskeen</itunes:author>
      <author>mskeen</author>
    </item>
  </channel>
</rss>