Study on Thermal Mechanical Design and Optimization Analysis for the ALBA Infrared Microspectroscopy Beamline (MIRAS) Extraction Mirror Based on Finite Element Analysis Article Swipe
YOU?
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· 2017
· Open Access
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· DOI: https://doi.org/10.18429/jacow-medsi2016-tupe11
This paper reports design, modelling, simulation and optimization results for the ALBA MIRAS infrared radiation extraction mirror. Finite element analysis (FEA) was used to simulate the thermal mechanical behaviour of the device. With the aim to ensure a good thermal performance, conservative assumptions were applied: all of the incident Bending Magnet (BM) radiation is absorbed at the mirror surface, constant bending magnetic field and low thermal contact between the mirror Al 6061 and the OFHC copper arm. A novel solution has been implemented in order to provide an effective cooling by a natural convection on the in-air part of extraction mirror assembly. This has voided the necessity for a water cooling that often causes problems due to the associated vibrations. The power conditions were calculated by using SynRad+. The main ALBA Storage Ring design parameters are: 3 GeV, 400 mA and 1.42 T. According to these conditions, the mirror absorbs 15 W with a peak power density of 0.51 W/mm2. The peak temperature calculated was 63.2 °C. The real measurements reported during the commissioning stage showed a good thermal performance, in agreement with the results predicted by FEA.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.18429/jacow-medsi2016-tupe11
- OA Status
- green
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3046174334
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3046174334Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.18429/jacow-medsi2016-tupe11Digital Object Identifier
- Title
-
Study on Thermal Mechanical Design and Optimization Analysis for the ALBA Infrared Microspectroscopy Beamline (MIRAS) Extraction Mirror Based on Finite Element AnalysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-01-01Full publication date if available
- Authors
-
M. Quispe, Antonio Carballedo, Joan R. Casas, Carles Colldelram, Alejandro Crisol, Gabriel Peña, Llibert Ribó, Igors Šics, Ibraheem YousefList of authors in order
- Landing page
-
https://doi.org/10.18429/jacow-medsi2016-tupe11Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.18429/jacow-medsi2016-tupe11Direct OA link when available
- Concepts
-
Beamline, Finite element method, Optics, Infrared, Extraction (chemistry), Thermal analysis, Thermal, Materials science, Mechanical engineering, Computer science, Physics, Engineering, Structural engineering, Chemistry, Chromatography, Meteorology, Beam (structure)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.design | 133 |
| abstract_inverted_index.during | 171 |
| abstract_inverted_index.ensure | 36 |
| abstract_inverted_index.in-air | 96 |
| abstract_inverted_index.mirror | 57, 69, 100, 148 |
| abstract_inverted_index.showed | 175 |
| abstract_inverted_index.voided | 104 |
| abstract_inverted_index.Bending | 49 |
| abstract_inverted_index.Storage | 131 |
| abstract_inverted_index.absorbs | 149 |
| abstract_inverted_index.bending | 60 |
| abstract_inverted_index.between | 67 |
| abstract_inverted_index.contact | 66 |
| abstract_inverted_index.cooling | 89, 110 |
| abstract_inverted_index.density | 156 |
| abstract_inverted_index.design, | 3 |
| abstract_inverted_index.device. | 31 |
| abstract_inverted_index.element | 18 |
| abstract_inverted_index.mirror. | 16 |
| abstract_inverted_index.natural | 92 |
| abstract_inverted_index.provide | 86 |
| abstract_inverted_index.reports | 2 |
| abstract_inverted_index.results | 8, 184 |
| abstract_inverted_index.thermal | 26, 39, 65, 178 |
| abstract_inverted_index.SynRad+. | 127 |
| abstract_inverted_index.absorbed | 54 |
| abstract_inverted_index.analysis | 19 |
| abstract_inverted_index.applied: | 44 |
| abstract_inverted_index.constant | 59 |
| abstract_inverted_index.incident | 48 |
| abstract_inverted_index.infrared | 13 |
| abstract_inverted_index.magnetic | 61 |
| abstract_inverted_index.problems | 114 |
| abstract_inverted_index.reported | 170 |
| abstract_inverted_index.simulate | 24 |
| abstract_inverted_index.solution | 79 |
| abstract_inverted_index.surface, | 58 |
| abstract_inverted_index.According | 143 |
| abstract_inverted_index.agreement | 181 |
| abstract_inverted_index.assembly. | 101 |
| abstract_inverted_index.behaviour | 28 |
| abstract_inverted_index.effective | 88 |
| abstract_inverted_index.necessity | 106 |
| abstract_inverted_index.predicted | 185 |
| abstract_inverted_index.radiation | 14, 52 |
| abstract_inverted_index.associated | 118 |
| abstract_inverted_index.calculated | 124, 163 |
| abstract_inverted_index.conditions | 122 |
| abstract_inverted_index.convection | 93 |
| abstract_inverted_index.extraction | 15, 99 |
| abstract_inverted_index.mechanical | 27 |
| abstract_inverted_index.modelling, | 4 |
| abstract_inverted_index.parameters | 134 |
| abstract_inverted_index.simulation | 5 |
| abstract_inverted_index.assumptions | 42 |
| abstract_inverted_index.conditions, | 146 |
| abstract_inverted_index.implemented | 82 |
| abstract_inverted_index.temperature | 162 |
| abstract_inverted_index.vibrations. | 119 |
| abstract_inverted_index.conservative | 41 |
| abstract_inverted_index.measurements | 169 |
| abstract_inverted_index.optimization | 7 |
| abstract_inverted_index.performance, | 40, 179 |
| abstract_inverted_index.commissioning | 173 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile.value | 0.2696794 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |