Stone impact damage to automotive paint finishes—A statistical and neural net analysis of electrochemical impedance data
Automotive car bodies are subject to impact by stones either lofted from tires or launched by other passing vehicles. Impact can result either in physical loss of paint or the possibility of failure at the metal/phosphate—polymer interface. Corrosion brought about as a result of impact is referred t...
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| Veröffentlicht in: | Electrochimica acta 1993-10, Vol.38 (14), p.2083-2091 |
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| container_issue | 14 |
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| container_title | Electrochimica acta |
| container_volume | 38 |
| creator | Ramamurthy, A.C. Lorenzen, Wendy I. Uriquidi-Macdonald, Mirna |
| description | Automotive car bodies are subject to impact by stones either lofted from tires or launched by other passing vehicles. Impact can result either in physical loss of paint or the possibility of failure at the metal/phosphate—polymer interface. Corrosion brought about as a result of impact is referred to as Impact Induced Corrosion or IIC. Electrochemical impedance is very sensitive to delamination at the metal—polymer interface and is able to discern the influence of velocity, angle of impact, the type of coating and ambient temperature on stone impact damage. Application of both statistical and Artificial Neural Network (ANN) analysis are presented. |
| doi_str_mv | 10.1016/0013-4686(93)80344-Y |
| format | Article |
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Impact can result either in physical loss of paint or the possibility of failure at the metal/phosphate—polymer interface. Corrosion brought about as a result of impact is referred to as Impact Induced Corrosion or IIC. Electrochemical impedance is very sensitive to delamination at the metal—polymer interface and is able to discern the influence of velocity, angle of impact, the type of coating and ambient temperature on stone impact damage. Application of both statistical and Artificial Neural Network (ANN) analysis are presented.</description><subject>Applied sciences</subject><subject>automotive coatings</subject><subject>Coatings. Paints, varnishes and inks</subject><subject>Exact sciences and technology</subject><subject>Film formation and curing, properties, testing</subject><subject>impact induced corrosion and neural nets</subject><subject>Polymer industry, paints, wood</subject><subject>stone impact damage</subject><issn>0013-4686</issn><issn>1873-3859</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1993</creationdate><recordtype>article</recordtype><recordid>eNp9kL9uFDEQhy0EEkfgDShcIESKDfbat-ttIkVR_kmRKIAilTVnj4nR7vri8UUKFQ_BE-ZJ4ruLUlLZI30zP_0-xj5KcSSF7L4KIVWjO9N9GdShEUrr5uYVW0jTq0aZ5fCaLV6Qt-wd0W8hRN_1YsH-fC9pRh6nNbjCPUzwC3lJHDYlTanEe-RriHPhIc6RbpEe__474VSgRCrRwchh9nzGTa7fGUsdYXygSDwFjiO6kpO7xWmH1hT0MDusQQXeszcBRsIPz-8B-3l-9uP0srn-dnF1enLdONXp0gSvvQO_FEtvjPIi9EINK9O6oDpAJUFoaI2SvgJyN4VW9V441a7ksl2pA_Z5f3ed090GqdgpksNxhBnThmzbtXrQfVdBvQddTkQZg13nOEF-sFLYrWi7tWi3Fu2g7E60valrn57vA9WWIdeGkV52tTFCq7Zix3sMa9f7iNmSi1hl-JirJutT_H_OE6dHlQM</recordid><startdate>19931001</startdate><enddate>19931001</enddate><creator>Ramamurthy, A.C.</creator><creator>Lorenzen, Wendy I.</creator><creator>Uriquidi-Macdonald, Mirna</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8BQ</scope><scope>8FD</scope><scope>FR3</scope><scope>JG9</scope></search><sort><creationdate>19931001</creationdate><title>Stone impact damage to automotive paint finishes—A statistical and neural net analysis of electrochemical impedance data</title><author>Ramamurthy, A.C. ; Lorenzen, Wendy I. ; Uriquidi-Macdonald, Mirna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-fd4dcad505d883d0f7039b82cf36ae31a04a2831d05d11a04af237d0c32b152b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1993</creationdate><topic>Applied sciences</topic><topic>automotive coatings</topic><topic>Coatings. Paints, varnishes and inks</topic><topic>Exact sciences and technology</topic><topic>Film formation and curing, properties, testing</topic><topic>impact induced corrosion and neural nets</topic><topic>Polymer industry, paints, wood</topic><topic>stone impact damage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ramamurthy, A.C.</creatorcontrib><creatorcontrib>Lorenzen, Wendy I.</creatorcontrib><creatorcontrib>Uriquidi-Macdonald, Mirna</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><jtitle>Electrochimica acta</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ramamurthy, A.C.</au><au>Lorenzen, Wendy I.</au><au>Uriquidi-Macdonald, Mirna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stone impact damage to automotive paint finishes—A statistical and neural net analysis of electrochemical impedance data</atitle><jtitle>Electrochimica acta</jtitle><date>1993-10-01</date><risdate>1993</risdate><volume>38</volume><issue>14</issue><spage>2083</spage><epage>2091</epage><pages>2083-2091</pages><issn>0013-4686</issn><eissn>1873-3859</eissn><coden>ELCAAV</coden><abstract>Automotive car bodies are subject to impact by stones either lofted from tires or launched by other passing vehicles. 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| ispartof | Electrochimica acta, 1993-10, Vol.38 (14), p.2083-2091 |
| issn | 0013-4686 1873-3859 |
| language | eng |
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| source | Elsevier ScienceDirect Journals Complete |
| subjects | Applied sciences automotive coatings Coatings. Paints, varnishes and inks Exact sciences and technology Film formation and curing, properties, testing impact induced corrosion and neural nets Polymer industry, paints, wood stone impact damage |
| title | Stone impact damage to automotive paint finishes—A statistical and neural net analysis of electrochemical impedance data |
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