Contents 2016a - Revision history

Complascontents at 13:36, 19 July 2016

2016-07-19T13:36:00Z

Scipediacontent at 11:12, 19 July 2016

2016-07-19T11:12:48Z

Complascontents at 09:43, 29 June 2016

2016-06-29T09:43:22Z

Scipediacontent at 11:48, 15 June 2016

2016-06-15T11:48:25Z

Complascontents at 07:13, 10 June 2016

2016-06-10T07:13:45Z

Scipediacontent at 15:15, 9 June 2016

2016-06-09T15:15:23Z

Scipediacontent at 15:14, 9 June 2016

2016-06-09T15:14:02Z

Scipediacontent at 15:13, 9 June 2016

2016-06-09T15:13:04Z

Scipediacontent at 15:03, 9 June 2016

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Scipediacontent at 15:02, 9 June 2016

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 ==Abstract==
-Additive manufacturing (AM) processes have the ability to build complex geometries from a wide variety of materials. A popular approach for metal-based AM processes involves the deposition of material particles on a substrate followed by fusion of those particles together using a high intensity heat source, e.g. a laser or an electron beam, in order to fabricate a solid part. These methods are of high priority in engineering research, especially in applications for the energy, health, and defense sectors. The primary reasons behind the rapid growth in interest for AM include: (1) the ability to create complex geometries which are otherwise cost-prohibitive or difficult to manufacture, (2) increased freedom of material composition design through the adjustment of the ratios of the composing powders, (3) a reduction in wasted materials, and (4) the fast, low-volume, production of prototype and functional parts without the additional tooling and die requirements of conventional manufacturing methods. However, the highly localized and intense nature of these processes elicits many experimental and computational challenges. These challenges motivate a strong need for computational investigation, as does the need to more accurately characterize the response of parts built using AM. The present work will discuss these challenges and methods for creating multiscale material models that account for the complex phenomena observed in the AM production environment. The linkage between process, structure, and property of AM components, e.g., anisotropic plastic behavior combined anisotropic microstructural descriptors afforded through enhanced data compression techniques, will also be discussed.
+Additive manufacturing (AM) processes have the ability to build complex geometries from a wide variety of materials. A popular approach for metal-based AM processes involves the deposition of material particles on a substrate followed by fusion of those particles together using a high intensity heat source, e.g. a laser or an electron beam [<span id='cite-1'></span>[[#1|1]]], in order to fabricate a solid part. These methods are of high priority in engineering research, especially in applications for the energy, health, and defense sectors. The primary reasons behind the rapid growth in interest for AM include: (1) the ability to create complex geometries which are otherwise cost-prohibitive or difficult to manufacture, (2) increased freedom of material composition design through the adjustment of the ratios of the composing powders, (3) a reduction in wasted materials, and (4) the fast, low-volume, production of prototype and functional parts without the additional tooling and die requirements of conventional manufacturing methods. However, the highly localized and intense nature of these processes elicits many experimental and computational challenges. These challenges motivate a strong need for computational investigation, as does the need to more accurately characterize the response of parts built using AM. The present work will discuss these challenges and methods for creating multiscale material models that account for the complex phenomena observed in the AM production environment. The linkage between process, structure, and property [<span id='cite-2'></span>[[#2|2]]] of AM components, e.g., anisotropic plastic behavior [<span id='cite-3'></span>[[#3|3]]],[<span id='cite-4'></span>[[#4|4]]] combined anisotropic microstructural descriptors afforded through enhanced data compression techniques, will also be discussed.
 == Recording of the presentation ==
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 * [//congress.cimne.com/complas2015/frontal/default.asp Complas XIII] Official Website of the Conference.
 * [//www.cimnemultimediachannel.com/ CIMNE Multimedia Channel]

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 {| style="font-size:120%; color: #222222; border: 1px solid darkgray; background: #f3f3f3; table-layout: fixed; width:100%;"
 |-
 | {{#evt:service=youtube|id=https://www.youtube.com/watch?v=t6tr73POWZ0|alignment=center}}
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 | Date: 1 - 3 September 2015, Barcelona, Spain.
 |}
 == General Information ==
 * Location: Technical University of Catalonia (UPC), Barcelona, Spain.
 * Date: 1 - 3 September 2015
-* Secretariat: [//www.cimne.com/ CIMNE] Centre Internacional de Metodes Numerics.
+* Secretariat: [//www.cimne.com/ International Center for Numerical Methods in Engineering (CIMNE)].
 == External Links ==
 * [//congress.cimne.com/complas2015/frontal/default.asp Complas XIII] Official Website of the Conference.
 * [//www.cimnemultimediachannel.com/ CIMNE Multimedia Channel]

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 |-
 | {{#evt:service=youtube|id=https://www.youtube.com/watch?v=t6tr73POWZ0|alignment=center}}
 |}

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-{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"
+{| style="font-size:120%; color: #222222; border: 1px solid darkgray; background: #f3f3f3; table-layout: fixed; width:100%;"
-|-
+|- style="border-bottom: 1px solid darkgray; text-align: center;"
-! Recording of the presentation
+| Recording of the presentation
 |-
-| <embedvideo service="youtube">https://www.youtube.com/watch?v=t6tr73POWZ0</embedvideo>
+| {{#evt:service=youtube|id=https://www.youtube.com/watch?v=t6tr73POWZ0|alignment=center}}
 |}

← Older revision		Revision as of 07:13, 10 June 2016
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−	Additive manufacturing (AM) processes have the ability to build complex geometries from a wide variety of materials. A popular approach for metal-based AM processes involves the deposition of material particles on a substrate followed by fusion of those particles together using a high intensity heat source, e.g. a laser or an electron beam, in order to fabricate a solid part. These methods are of high priority in engineering research,
−	especially in applications for the energy, health, and defense sectors. The primary reasons behind the rapid growth in interest for AM include: (1) the ability to create complex geometries that are otherwise cost-prohibitive or difficult to manufacture, (2) increased freedom of material composition design through the adjustment of the elemental ratios of the composing powders, (3) a reduction in wasted materials, and (4) fast, low-volume, production of prototype and functional parts without the additional tooling and die requirements of conventional manufacturing methods. However, the highly localized and intense nature of these processes elicits many experimental and computational challenges. These challenges motivate a strong need for computational investigation, as does the need to more accurately characterize the response of parts built using AM. The present work will discuss these challenges and methods for creating multiscale material models that account for the complex phenomena observed in
−	additively manufactured products. The linkage between process, structure, and property of AM components, e.g., anisotropic plastic behavior combined with anisotropic microstructural descriptors afforded through enhanced data compression techniques, will also be discussed.
−
−
	{\| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"		{\| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"
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