{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-04-06T14:01:22.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2026-04-06T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":49820,"title":"Area of Cylindrical Shell","description":"Consider a cylinder with a non-zero thickness with an inner radius of r1 and an outer radius of r2. If the height of the cylinder is h, determine the surface area of this cylindrical shell.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 332px 21px; transform-origin: 332px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 309px 21px; text-align: left; transform-origin: 309px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 307px 8px; transform-origin: 307px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConsider a cylinder with a non-zero thickness with an inner radius of r1 and an outer radius of r2. If the height of the cylinder is h, determine the surface area of this cylindrical shell.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function a1 = cy(r1,r2,h)\r\n  y = r1/r2/h;\r\nend","test_suite":"%%\r\nr1=0.37;\r\nr2=3.64;\r\nh=7;\r\na_corr=258.7585;\r\nassert(abs(cy(r1,r2,h) - a_corr) \u003c 1e-4)\r\n%%\r\nr1=3/4*pi;\r\nr2=pi;\r\nh=5;\r\na_corr=199.8486;\r\nassert(abs(cy(r1,r2,h) - a_corr) \u003c 1e-4)\r\n%%\r\nr1=21;\r\nr2=21.1;\r\nh=pi;\r\na_corr=857.4729;\r\nassert(abs(cy(r1,r2,h) - a_corr) \u003c 1e-4)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":29,"test_suite_updated_at":"2021-08-24T16:15:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-15T01:35:10.000Z","updated_at":"2026-02-11T18:47:25.000Z","published_at":"2021-01-15T01:35:10.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider a cylinder with a non-zero thickness with an inner radius of r1 and an outer radius of r2. If the height of the cylinder is h, determine the surface area of this cylindrical shell.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":2963,"title":"find the surface area of a cube","description":"given cube side length x, find the surface area of the cube, set it equal to y","description_html":"\u003cp\u003egiven cube side length x, find the surface area of the cube, set it equal to y\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 7;\r\ny_correct = 294;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":7,"comments_count":1,"created_by":33982,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":567,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-02-06T23:53:19.000Z","updated_at":"2026-02-11T12:16:30.000Z","published_at":"2015-02-06T23:53:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003egiven cube side length x, find the surface area of the cube, set it equal to y\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44618,"title":"surface areas of a cylinder","description":"There are 3 inputs: option, radius and height. If option= '1', compute the lateral surface area of the cylinder, for option 2 calculate the total surface area of the cylinder. For any other option, compute the total area of both flat sides of the cylinder.","description_html":"\u003cp\u003eThere are 3 inputs: option, radius and height. If option= '1', compute the lateral surface area of the cylinder, for option 2 calculate the total surface area of the cylinder. For any other option, compute the total area of both flat sides of the cylinder.\u003c/p\u003e","function_template":"function y = surface_area_cyl(optn,r,h)\r\n  y = r*h;\r\nend","test_suite":"%%\r\noptn=1;\r\nr=3;\r\nh=6;\r\ny_correct = 36*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=5;\r\nr=3;\r\nh=6;\r\ny_correct = 18*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=2;\r\nr=2;\r\nh=2;\r\ny_correct = 16*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=0;\r\nr=5;\r\nh=10;\r\ny_correct = 50*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=1;\r\nr=5;\r\nh=10;\r\ny_correct = 100*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=2;\r\nr=5;\r\nh=10;\r\ny_correct = 150*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=42;\r\nr=3;\r\nh=7;\r\ny_correct = 18*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=2;\r\nr=3\r\nh=7;\r\ny_correct = 60*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=1;\r\nr=3;\r\nh=7;\r\ny_correct = 42*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":171559,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":"2018-07-16T16:54:54.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-04-20T05:49:29.000Z","updated_at":"2026-04-03T06:59:13.000Z","published_at":"2018-04-20T05:49:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere are 3 inputs: option, radius and height. If option= '1', compute the lateral surface area of the cylinder, for option 2 calculate the total surface area of the cylinder. For any other option, compute the total area of both flat sides of the cylinder.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":59104,"title":"Design a capture zone","description":"One approach to remediating a contaminated site is to pump and treat the contaminated groundwater. If the site has background flow, then an extraction well will create a capture zone. In other words, there will be a streamline that divides the water pumped by the well from the water that continues downgradient (i.e., downstream) of the well. \r\nIf the background flow (with flow per unit width* ) is left to right, then the coordinates  of a point on the capture zone are given by , where the well is at (0,0) and  is the distance to the stagnation point downstream of the well. The distance  can be determined by finding the distance at which the specific discharge of the background flow equals the specific discharge of the well. \r\nWrite a function that takes the coordinates of a contaminated area and the background flow per unit width and determines the pumping rate needed to capture the entire area. \r\n*Recall that specific discharge  is flow per area over which the flow is occurring. Then flow per unit width is , where  is the thickness of the confined aquifer. \r\n\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 777.7px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 388.85px; transform-origin: 407px 388.85px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 360.567px 8px; transform-origin: 360.567px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOne approach to remediating a contaminated site is to pump and treat the contaminated groundwater. If the site has background flow, then an extraction well will create a capture zone. In other words, there will be a streamline that divides the water pumped by the well from the water that continues downgradient (i.e., downstream) of the well. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 87px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 43.5px; text-align: left; transform-origin: 384px 43.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 147.808px 8px; transform-origin: 147.808px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the background flow (with flow per unit width* \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"18\" height=\"18\" alt=\"Q'\" style=\"width: 18px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 113.175px 8px; transform-origin: 113.175px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is left to right, then the coordinates \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"43\" height=\"20\" alt=\"(xc, yc)\" style=\"width: 43px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 79.3417px 8px; transform-origin: 79.3417px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e of a point on the capture zone are given by \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"115\" height=\"20\" alt=\"xc = yc/tan(yc/x0)\" style=\"width: 115px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 95.2917px 8px; transform-origin: 95.2917px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, where the well is at (0,0) and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"14.5\" height=\"20\" alt=\"x0\" style=\"width: 14.5px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 166.658px 8px; transform-origin: 166.658px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the distance to the stagnation point downstream of the well. The distance \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"14.5\" height=\"20\" alt=\"x0\" style=\"width: 14.5px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 302.633px 8px; transform-origin: 302.633px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e can be determined by finding the distance at which the specific discharge of the background flow equals the specific discharge of the well. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 377.958px 8px; transform-origin: 377.958px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes the coordinates of a contaminated area and the background flow per unit width and determines the pumping rate needed to capture the entire area. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 95.3083px 8px; transform-origin: 95.3083px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e*Recall that specific discharge \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 235.325px 8px; transform-origin: 235.325px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is flow per area over which the flow is occurring. Then flow per unit width is \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"51\" height=\"18\" alt=\"Q' = vb\" style=\"width: 51px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 23.0583px 8px; transform-origin: 23.0583px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, where \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eb\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 124.458px 8px; transform-origin: 124.458px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the thickness of the confined aquifer. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 477.7px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 238.85px; text-align: left; transform-origin: 384px 238.85px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"620\" height=\"472\" style=\"vertical-align: baseline;width: 620px;height: 472px\" 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\" alt=\"Capture zone\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Q0 = captureZone(x,y,Qp)\r\n% x,y = coordinates of contaminated area\r\n% Qp  = background flow per unit width\r\n% Q0  = required pumping rate\r\n  Q0 = Qp*max(abs(y));\r\nend","test_suite":"%% \r\nx  = -100;                                      %  x-coordinate of contaminated area (m)\r\ny  = 75;                                        %  y-coordinate of contaminated area (m)\r\nQp = 2;                                         %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 377.3;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% \r\nx  = [-100 -100 -300 -300];                     %  x-coordinates of contaminated area (m)\r\ny  = [75 -75 -75 75];                           %  y-coordinates of contaminated area (m)\r\nQp = 2;                                         %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 377.3;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = [-100 -100 -200 -300 -300 -200];           %  x-coordinates of contaminated area (m)\r\ny  = [75 -75 -100 -75 75 100];                  %  y-coordinates of contaminated area (m)\r\nQp = 2;                                         %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 469.3;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2021 exam 2 problem 5\r\nx  = [-47.1 -48.9 22.4];                        %  x-coordinates of contaminated area (m)\r\ny  = [10 -10 -30];                              %  y-coordinates of contaminated area (m)    \r\nQp = 0.048;                                     %  Background flow per unit width (m2/d)    \r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 9.73;                              %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2022 exam 2 problem 3\r\nx  = -18.5;                                     %  x-coordinate of contaminated area (m)\r\ny  = -25;                                       %  y-coordinate of contaminated area (m)\r\nQp = 0.45;                                      %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 32;                                %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2020 exam 2a problem 5\r\nx  = -25;                                       %  x-coordinate of contaminated area (m)\r\ny  = 60;                                        %  y-coordinate of contaminated area (m)    \r\nQp = 0.231;                                     %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 44.3;                              %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2020 exam 2b problem 5\r\nx  = -10;                                       %  x-coordinate of contaminated area (m)\r\ny  = 20;                                        %  y-coordinate of contaminated area (m)    \r\nQp = 0.231;                                     %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 14.27;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2020 exam 2c problem 5\r\nx  = -25;                                       %  x-coordinate of contaminated area (m)\r\ny  = 20;                                        %  y-coordinate of contaminated area (m)    \r\nQp = 0.231;                                     %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 11.77;                             %  Pumping rate (m3/d)    \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% \r\nx  = [15 -50 -100 -45];                         %  x-coordinates of contaminated area (m)\r\ny  = [20 40 32 5];                              %  y-coordinates of contaminated area (m)\r\nQp = 0.3;                                       %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 40.65;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% \r\nx  = [15 -50 -100 -45];                         %  x-coordinates of contaminated area (m)\r\ny  = [20 53 32 5];                              %  y-coordinates of contaminated area (m)\r\nQp = 0.3;                                       %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 42.93;                             %  Pumping rate (m3/d)    \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = 200;                                       %  x-coordinate of contaminated area (m)\r\ny  = 0;                                         %  y-coordinate of contaminated area (m)    \r\nQp = 3.6;                                       %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 4523.9;                            %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = [200 110   0 -100 -175 -220 -160  -80   40];      %  x-coordinates of contaminated area (m)\r\ny  = [  0 125 300  320  180   40 -195 -280 -250];      %  y-coordinates of contaminated area (m) \r\nQp = 0.5;                                              %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 628.3;                                    %  Pumping rate (m3/d) \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = [200 110   0 -100 -175 -220 -160  -80  100];      %  x-coordinates of contaminated area (m)\r\ny  = [  0 125 300  320  180   40 -195 -280 -250];      %  y-coordinates of contaminated area (m) \r\nQp = 0.5;                                              %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 659.8;                                    %  Pumping rate (m3/d) \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nfiletext = fileread('captureZone.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'assert') || contains(filetext,'regexp'); \r\nassert(~illegal)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":46909,"edited_by":46909,"edited_at":"2023-12-30T14:16:43.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-10-14T20:07:58.000Z","updated_at":"2026-02-12T14:46:59.000Z","published_at":"2023-10-14T20:08:08.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne approach to remediating a contaminated site is to pump and treat the contaminated groundwater. If the site has background flow, then an extraction well will create a capture zone. In other words, there will be a streamline that divides the water pumped by the well from the water that continues downgradient (i.e., downstream) of the well. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the background flow (with flow per unit width* \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"Q'\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eQ\\\\prime\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) is left to right, then the coordinates \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"(xc, yc)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e(x_c,y_c)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e of a point on the capture zone are given by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"xc = yc/tan(yc/x0)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ex_c = y_c/\\\\tan(y_c/x_0)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, where the well is at (0,0) and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"x0\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ex_0\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the distance to the stagnation point downstream of the well. The distance \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"x0\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ex_0\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e can be determined by finding the distance at which the specific discharge of the background flow equals the specific discharge of the well. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes the coordinates of a contaminated area and the background flow per unit width and determines the pumping rate needed to capture the entire area. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e*Recall that specific discharge \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is flow per area over which the flow is occurring. Then flow per unit width is \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"Q' = vb\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eQ\\\\prime = vb\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, where \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"b\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eb\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the thickness of the confined aquifer. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":47864,"title":"Calculate the Surface Area of an Ellipsoid","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCalculate the Surface Area of an Ellipsoid: (x/a)^2+(y/b)^2+(z/c)^2=1. Input will be a matrix [a,b,c]. Round output to four decimal places.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = surfaceAreaEllipsoid(a)\r\n  s=a;\r\nend","test_suite":"%%\r\na =       [1          10         100\r\n           1           2         100\r\n           2           3        1000];\r\ns = [6384.7971,1521.9917,24921.4459];\r\nassert(isequal(surfaceAreaEllipsoid(a),s))\r\n%%\r\na =[23.4094   25.3969   17.6635\r\n   17.2337   19.4679   30.3974\r\n   27.2947   28.4956   20.7605\r\n   13.7477   23.0868   13.6015\r\n   26.2107   18.7350   30.0832\r\n   13.5647   30.6594   31.3050\r\n   19.2094   29.5973   20.9523\r\n   25.0200   23.4734   10.5830\r\n   27.9464   24.9600   16.0935\r\n    9.0554   24.2487   20.2237\r\n   30.4959   14.4222   24.3926\r\n   27.8568   17.3781   16.2173\r\n   22.0681   21.7025   24.5561\r\n   20.8806   15.1987   26.6833\r\n   21.1424   29.0689   14.8997\r\n   17.5214   13.9642   10.8628\r\n   22.5610   15.0333   17.2337\r\n   22.6053   13.0767   17.8606\r\n   28.6007   15.0997   20.6155\r\n   28.1957   20.8806   22.5389];\r\ns=114878.3893;\r\nassert(isequal(round(sum(surfaceAreaEllipsoid(a)),4),s))\r\n%%\r\na =[2.2361    1.4142    1.4142\r\n    3.7417    6.7082    6.1644\r\n    6.4031    6.7823    5.0990\r\n    1.4142    6.3246    4.8990\r\n    6.8557    2.2361    6.7823\r\n    6.0828    3.7417    5.5678\r\n    5.0000    4.1231    5.5678\r\n    5.3852    5.8310    6.5574\r\n    3.4641    2.6458    6.4031\r\n    4.7958    6.0828    5.3852\r\n    7.0000    2.4495    3.1623\r\n    5.2915    5.7446    3.4641\r\n    5.1962    5.0000    6.7082\r\n    3.4641    6.2450    1.4142\r\n    5.0000    6.0000    5.0000\r\n    5.6569    6.7823    3.0000\r\n    5.8310    6.7082    7.0000\r\n    4.4721    4.1231    6.0000\r\n    4.3589    5.9161    5.0990\r\n    7.0711    3.1623    4.8990];\r\ns=6319.9914;\r\nassert(isequal(round(sum(surfaceAreaEllipsoid(a)),4),s))\r\n%%\r\na =[815   656   439\r\n   906    36   382\r\n   127   850   766\r\n   914   934   796\r\n   633   679   187\r\n    98   758   490\r\n   279   744   446\r\n   547   393   647\r\n   958   656   710\r\n   965   172   755\r\n   158   707   277\r\n   971    32   680\r\n   958   277   656\r\n   486    47   163\r\n   801    98   119\r\n   142   824   499\r\n   422   695   960\r\n   916   318   341\r\n   793   951   586\r\n   960    35   224]\r\ns=[5044536.4000,2211672.3438,4352237.2825,9752711.8853,3142934.7619,2498034.8411,2902467.0124,3493778.3292,7487103.0719,5020531.2388,1596267.5211,4175258.0564,4870849.7171,548197.4954,866709.4797,2892741.9879,5916340.2965,3127474.1105,7530645.3854,1399379.0343];\r\nassert(isequal(surfaceAreaEllipsoid(a),s))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":145982,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2020-12-18T14:43:49.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2020-12-10T00:32:35.000Z","updated_at":"2020-12-18T14:43:49.000Z","published_at":"2020-12-10T00:43:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the Surface Area of an Ellipsoid: (x/a)^2+(y/b)^2+(z/c)^2=1. Input will be a matrix [a,b,c]. Round output to four decimal places.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":49820,"title":"Area of Cylindrical Shell","description":"Consider a cylinder with a non-zero thickness with an inner radius of r1 and an outer radius of r2. If the height of the cylinder is h, determine the surface area of this cylindrical shell.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 332px 21px; transform-origin: 332px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 309px 21px; text-align: left; transform-origin: 309px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 307px 8px; transform-origin: 307px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConsider a cylinder with a non-zero thickness with an inner radius of r1 and an outer radius of r2. If the height of the cylinder is h, determine the surface area of this cylindrical shell.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function a1 = cy(r1,r2,h)\r\n  y = r1/r2/h;\r\nend","test_suite":"%%\r\nr1=0.37;\r\nr2=3.64;\r\nh=7;\r\na_corr=258.7585;\r\nassert(abs(cy(r1,r2,h) - a_corr) \u003c 1e-4)\r\n%%\r\nr1=3/4*pi;\r\nr2=pi;\r\nh=5;\r\na_corr=199.8486;\r\nassert(abs(cy(r1,r2,h) - a_corr) \u003c 1e-4)\r\n%%\r\nr1=21;\r\nr2=21.1;\r\nh=pi;\r\na_corr=857.4729;\r\nassert(abs(cy(r1,r2,h) - a_corr) \u003c 1e-4)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":180632,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":29,"test_suite_updated_at":"2021-08-24T16:15:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2021-01-15T01:35:10.000Z","updated_at":"2026-02-11T18:47:25.000Z","published_at":"2021-01-15T01:35:10.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider a cylinder with a non-zero thickness with an inner radius of r1 and an outer radius of r2. If the height of the cylinder is h, determine the surface area of this cylindrical shell.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":2963,"title":"find the surface area of a cube","description":"given cube side length x, find the surface area of the cube, set it equal to y","description_html":"\u003cp\u003egiven cube side length x, find the surface area of the cube, set it equal to y\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 7;\r\ny_correct = 294;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":7,"comments_count":1,"created_by":33982,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":567,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-02-06T23:53:19.000Z","updated_at":"2026-02-11T12:16:30.000Z","published_at":"2015-02-06T23:53:46.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003egiven cube side length x, find the surface area of the cube, set it equal to y\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44618,"title":"surface areas of a cylinder","description":"There are 3 inputs: option, radius and height. If option= '1', compute the lateral surface area of the cylinder, for option 2 calculate the total surface area of the cylinder. For any other option, compute the total area of both flat sides of the cylinder.","description_html":"\u003cp\u003eThere are 3 inputs: option, radius and height. If option= '1', compute the lateral surface area of the cylinder, for option 2 calculate the total surface area of the cylinder. For any other option, compute the total area of both flat sides of the cylinder.\u003c/p\u003e","function_template":"function y = surface_area_cyl(optn,r,h)\r\n  y = r*h;\r\nend","test_suite":"%%\r\noptn=1;\r\nr=3;\r\nh=6;\r\ny_correct = 36*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=5;\r\nr=3;\r\nh=6;\r\ny_correct = 18*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=2;\r\nr=2;\r\nh=2;\r\ny_correct = 16*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=0;\r\nr=5;\r\nh=10;\r\ny_correct = 50*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=1;\r\nr=5;\r\nh=10;\r\ny_correct = 100*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=2;\r\nr=5;\r\nh=10;\r\ny_correct = 150*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=42;\r\nr=3;\r\nh=7;\r\ny_correct = 18*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=2;\r\nr=3\r\nh=7;\r\ny_correct = 60*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n\r\n%%\r\noptn=1;\r\nr=3;\r\nh=7;\r\ny_correct = 42*pi;\r\nassert(isequal(surface_area_cyl(optn,r,h),y_correct))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":171559,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":"2018-07-16T16:54:54.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-04-20T05:49:29.000Z","updated_at":"2026-04-03T06:59:13.000Z","published_at":"2018-04-20T05:49:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere are 3 inputs: option, radius and height. If option= '1', compute the lateral surface area of the cylinder, for option 2 calculate the total surface area of the cylinder. For any other option, compute the total area of both flat sides of the cylinder.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":59104,"title":"Design a capture zone","description":"One approach to remediating a contaminated site is to pump and treat the contaminated groundwater. If the site has background flow, then an extraction well will create a capture zone. In other words, there will be a streamline that divides the water pumped by the well from the water that continues downgradient (i.e., downstream) of the well. \r\nIf the background flow (with flow per unit width* ) is left to right, then the coordinates  of a point on the capture zone are given by , where the well is at (0,0) and  is the distance to the stagnation point downstream of the well. The distance  can be determined by finding the distance at which the specific discharge of the background flow equals the specific discharge of the well. \r\nWrite a function that takes the coordinates of a contaminated area and the background flow per unit width and determines the pumping rate needed to capture the entire area. \r\n*Recall that specific discharge  is flow per area over which the flow is occurring. Then flow per unit width is , where  is the thickness of the confined aquifer. \r\n\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 777.7px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 388.85px; transform-origin: 407px 388.85px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 360.567px 8px; transform-origin: 360.567px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOne approach to remediating a contaminated site is to pump and treat the contaminated groundwater. If the site has background flow, then an extraction well will create a capture zone. In other words, there will be a streamline that divides the water pumped by the well from the water that continues downgradient (i.e., downstream) of the well. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 87px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 43.5px; text-align: left; transform-origin: 384px 43.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 147.808px 8px; transform-origin: 147.808px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the background flow (with flow per unit width* \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"18\" height=\"18\" alt=\"Q'\" style=\"width: 18px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 113.175px 8px; transform-origin: 113.175px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e) is left to right, then the coordinates \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"43\" height=\"20\" alt=\"(xc, yc)\" style=\"width: 43px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 79.3417px 8px; transform-origin: 79.3417px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e of a point on the capture zone are given by \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"115\" height=\"20\" alt=\"xc = yc/tan(yc/x0)\" style=\"width: 115px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 95.2917px 8px; transform-origin: 95.2917px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, where the well is at (0,0) and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"14.5\" height=\"20\" alt=\"x0\" style=\"width: 14.5px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 166.658px 8px; transform-origin: 166.658px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the distance to the stagnation point downstream of the well. The distance \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-6px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"14.5\" height=\"20\" alt=\"x0\" style=\"width: 14.5px; height: 20px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 302.633px 8px; transform-origin: 302.633px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e can be determined by finding the distance at which the specific discharge of the background flow equals the specific discharge of the well. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 377.958px 8px; transform-origin: 377.958px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes the coordinates of a contaminated area and the background flow per unit width and determines the pumping rate needed to capture the entire area. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 95.3083px 8px; transform-origin: 95.3083px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e*Recall that specific discharge \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003ev\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 235.325px 8px; transform-origin: 235.325px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is flow per area over which the flow is occurring. Then flow per unit width is \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"51\" height=\"18\" alt=\"Q' = vb\" style=\"width: 51px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 23.0583px 8px; transform-origin: 23.0583px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, where \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eb\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 124.458px 8px; transform-origin: 124.458px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is the thickness of the confined aquifer. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 8px; transform-origin: 0px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 477.7px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 238.85px; text-align: left; transform-origin: 384px 238.85px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"620\" height=\"472\" style=\"vertical-align: baseline;width: 620px;height: 472px\" 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\" alt=\"Capture zone\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Q0 = captureZone(x,y,Qp)\r\n% x,y = coordinates of contaminated area\r\n% Qp  = background flow per unit width\r\n% Q0  = required pumping rate\r\n  Q0 = Qp*max(abs(y));\r\nend","test_suite":"%% \r\nx  = -100;                                      %  x-coordinate of contaminated area (m)\r\ny  = 75;                                        %  y-coordinate of contaminated area (m)\r\nQp = 2;                                         %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 377.3;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% \r\nx  = [-100 -100 -300 -300];                     %  x-coordinates of contaminated area (m)\r\ny  = [75 -75 -75 75];                           %  y-coordinates of contaminated area (m)\r\nQp = 2;                                         %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 377.3;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = [-100 -100 -200 -300 -300 -200];           %  x-coordinates of contaminated area (m)\r\ny  = [75 -75 -100 -75 75 100];                  %  y-coordinates of contaminated area (m)\r\nQp = 2;                                         %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 469.3;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2021 exam 2 problem 5\r\nx  = [-47.1 -48.9 22.4];                        %  x-coordinates of contaminated area (m)\r\ny  = [10 -10 -30];                              %  y-coordinates of contaminated area (m)    \r\nQp = 0.048;                                     %  Background flow per unit width (m2/d)    \r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 9.73;                              %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2022 exam 2 problem 3\r\nx  = -18.5;                                     %  x-coordinate of contaminated area (m)\r\ny  = -25;                                       %  y-coordinate of contaminated area (m)\r\nQp = 0.45;                                      %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 32;                                %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2020 exam 2a problem 5\r\nx  = -25;                                       %  x-coordinate of contaminated area (m)\r\ny  = 60;                                        %  y-coordinate of contaminated area (m)    \r\nQp = 0.231;                                     %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 44.3;                              %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2020 exam 2b problem 5\r\nx  = -10;                                       %  x-coordinate of contaminated area (m)\r\ny  = 20;                                        %  y-coordinate of contaminated area (m)    \r\nQp = 0.231;                                     %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 14.27;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% Fall 2020 exam 2c problem 5\r\nx  = -25;                                       %  x-coordinate of contaminated area (m)\r\ny  = 20;                                        %  y-coordinate of contaminated area (m)    \r\nQp = 0.231;                                     %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 11.77;                             %  Pumping rate (m3/d)    \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% \r\nx  = [15 -50 -100 -45];                         %  x-coordinates of contaminated area (m)\r\ny  = [20 40 32 5];                              %  y-coordinates of contaminated area (m)\r\nQp = 0.3;                                       %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 40.65;                             %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%% \r\nx  = [15 -50 -100 -45];                         %  x-coordinates of contaminated area (m)\r\ny  = [20 53 32 5];                              %  y-coordinates of contaminated area (m)\r\nQp = 0.3;                                       %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 42.93;                             %  Pumping rate (m3/d)    \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = 200;                                       %  x-coordinate of contaminated area (m)\r\ny  = 0;                                         %  y-coordinate of contaminated area (m)    \r\nQp = 3.6;                                       %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 4523.9;                            %  Pumping rate (m3/d)\r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = [200 110   0 -100 -175 -220 -160  -80   40];      %  x-coordinates of contaminated area (m)\r\ny  = [  0 125 300  320  180   40 -195 -280 -250];      %  y-coordinates of contaminated area (m) \r\nQp = 0.5;                                              %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 628.3;                                    %  Pumping rate (m3/d) \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nx  = [200 110   0 -100 -175 -220 -160  -80  100];      %  x-coordinates of contaminated area (m)\r\ny  = [  0 125 300  320  180   40 -195 -280 -250];      %  y-coordinates of contaminated area (m) \r\nQp = 0.5;                                              %  Background flow per unit width (m2/d)\r\nQ0 = captureZone(x,y,Qp);\r\nQ0_correct = 659.8;                                    %  Pumping rate (m3/d) \r\nassert(abs(Q0-Q0_correct)/Q0_correct\u003c1e-3)\r\n\r\n%%\r\nfiletext = fileread('captureZone.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'assert') || contains(filetext,'regexp'); \r\nassert(~illegal)\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":46909,"edited_by":46909,"edited_at":"2023-12-30T14:16:43.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-10-14T20:07:58.000Z","updated_at":"2026-02-12T14:46:59.000Z","published_at":"2023-10-14T20:08:08.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOne approach to remediating a contaminated site is to pump and treat the contaminated groundwater. If the site has background flow, then an extraction well will create a capture zone. In other words, there will be a streamline that divides the water pumped by the well from the water that continues downgradient (i.e., downstream) of the well. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the background flow (with flow per unit width* \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"Q'\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eQ\\\\prime\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e) is left to right, then the coordinates \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"(xc, yc)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e(x_c,y_c)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e of a point on the capture zone are given by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"xc = yc/tan(yc/x0)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ex_c = y_c/\\\\tan(y_c/x_0)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, where the well is at (0,0) and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"x0\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ex_0\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the distance to the stagnation point downstream of the well. The distance \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"x0\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ex_0\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e can be determined by finding the distance at which the specific discharge of the background flow equals the specific discharge of the well. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes the coordinates of a contaminated area and the background flow per unit width and determines the pumping rate needed to capture the entire area. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e*Recall that specific discharge \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"v\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is flow per area over which the flow is occurring. Then flow per unit width is \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"Q' = vb\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eQ\\\\prime = vb\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, where \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"b\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eb\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e is the thickness of the confined aquifer. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":47864,"title":"Calculate the Surface Area of an Ellipsoid","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eCalculate the Surface Area of an Ellipsoid: (x/a)^2+(y/b)^2+(z/c)^2=1. Input will be a matrix [a,b,c]. Round output to four decimal places.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s = surfaceAreaEllipsoid(a)\r\n  s=a;\r\nend","test_suite":"%%\r\na =       [1          10         100\r\n           1           2         100\r\n           2           3        1000];\r\ns = [6384.7971,1521.9917,24921.4459];\r\nassert(isequal(surfaceAreaEllipsoid(a),s))\r\n%%\r\na =[23.4094   25.3969   17.6635\r\n   17.2337   19.4679   30.3974\r\n   27.2947   28.4956   20.7605\r\n   13.7477   23.0868   13.6015\r\n   26.2107   18.7350   30.0832\r\n   13.5647   30.6594   31.3050\r\n   19.2094   29.5973   20.9523\r\n   25.0200   23.4734   10.5830\r\n   27.9464   24.9600   16.0935\r\n    9.0554   24.2487   20.2237\r\n   30.4959   14.4222   24.3926\r\n   27.8568   17.3781   16.2173\r\n   22.0681   21.7025   24.5561\r\n   20.8806   15.1987   26.6833\r\n   21.1424   29.0689   14.8997\r\n   17.5214   13.9642   10.8628\r\n   22.5610   15.0333   17.2337\r\n   22.6053   13.0767   17.8606\r\n   28.6007   15.0997   20.6155\r\n   28.1957   20.8806   22.5389];\r\ns=114878.3893;\r\nassert(isequal(round(sum(surfaceAreaEllipsoid(a)),4),s))\r\n%%\r\na =[2.2361    1.4142    1.4142\r\n    3.7417    6.7082    6.1644\r\n    6.4031    6.7823    5.0990\r\n    1.4142    6.3246    4.8990\r\n    6.8557    2.2361    6.7823\r\n    6.0828    3.7417    5.5678\r\n    5.0000    4.1231    5.5678\r\n    5.3852    5.8310    6.5574\r\n    3.4641    2.6458    6.4031\r\n    4.7958    6.0828    5.3852\r\n    7.0000    2.4495    3.1623\r\n    5.2915    5.7446    3.4641\r\n    5.1962    5.0000    6.7082\r\n    3.4641    6.2450    1.4142\r\n    5.0000    6.0000    5.0000\r\n    5.6569    6.7823    3.0000\r\n    5.8310    6.7082    7.0000\r\n    4.4721    4.1231    6.0000\r\n    4.3589    5.9161    5.0990\r\n    7.0711    3.1623    4.8990];\r\ns=6319.9914;\r\nassert(isequal(round(sum(surfaceAreaEllipsoid(a)),4),s))\r\n%%\r\na =[815   656   439\r\n   906    36   382\r\n   127   850   766\r\n   914   934   796\r\n   633   679   187\r\n    98   758   490\r\n   279   744   446\r\n   547   393   647\r\n   958   656   710\r\n   965   172   755\r\n   158   707   277\r\n   971    32   680\r\n   958   277   656\r\n   486    47   163\r\n   801    98   119\r\n   142   824   499\r\n   422   695   960\r\n   916   318   341\r\n   793   951   586\r\n   960    35   224]\r\ns=[5044536.4000,2211672.3438,4352237.2825,9752711.8853,3142934.7619,2498034.8411,2902467.0124,3493778.3292,7487103.0719,5020531.2388,1596267.5211,4175258.0564,4870849.7171,548197.4954,866709.4797,2892741.9879,5916340.2965,3127474.1105,7530645.3854,1399379.0343];\r\nassert(isequal(surfaceAreaEllipsoid(a),s))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":145982,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2020-12-18T14:43:49.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2020-12-10T00:32:35.000Z","updated_at":"2020-12-18T14:43:49.000Z","published_at":"2020-12-10T00:43:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCalculate the Surface Area of an Ellipsoid: (x/a)^2+(y/b)^2+(z/c)^2=1. Input will be a matrix [a,b,c]. Round output to four decimal places.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"term":"tag:\"surface 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