Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology
Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro el...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mohammed, Ayman R. [verfasserIn] Saleh, Zead [verfasserIn] Aldabbagh, Alhassan M. [verfasserIn] Al Hanbali, Ahmad [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2024 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© The Author(s) 2024 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Discover applied sciences - Springer International Publishing, 2024, 6(2024), 10 vom: 15. Okt. |
|---|---|
| Übergeordnetes Werk: |
volume:6 ; year:2024 ; number:10 ; day:15 ; month:10 |
| Links: |
|---|
| DOI / URN: |
10.1007/s42452-024-06219-z |
|---|
| Katalog-ID: |
SPR057805296 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | SPR057805296 | ||
| 003 | DE-627 | ||
| 005 | 20241016064820.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 241016s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s42452-024-06219-z |2 doi | |
| 035 | |a (DE-627)SPR057805296 | ||
| 035 | |a (SPR)s42452-024-06219-z-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Mohammed, Ayman R. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a © The Author(s) 2024 | ||
| 520 | |a Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. | ||
| 520 | |a Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. | ||
| 650 | 4 | |a Ergonomics design |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Response surface methodology |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Ergonomics assessments |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Micro electric car |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Saleh, Zead |e verfasserin |4 aut | |
| 700 | 1 | |a Aldabbagh, Alhassan M. |e verfasserin |4 aut | |
| 700 | 1 | |a Al Hanbali, Ahmad |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Discover applied sciences |d Springer International Publishing, 2024 |g 6(2024), 10 vom: 15. Okt. |h Online-Ressource |w (DE-627)1882945751 |w (DE-600)3181295-8 |x 3004-9261 |7 nnns |
| 773 | 1 | 8 | |g volume:6 |g year:2024 |g number:10 |g day:15 |g month:10 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s42452-024-06219-z |m X:SPRINGER |x Resolving-System |z kostenfrei |3 Volltext |
| 912 | |a SYSFLAG_0 | ||
| 912 | |a GBV_SPRINGER | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_72 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_171 | ||
| 912 | |a GBV_ILN_213 | ||
| 912 | |a GBV_ILN_230 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_2050 | ||
| 912 | |a GBV_ILN_2190 | ||
| 912 | |a GBV_ILN_4012 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4126 | ||
| 912 | |a GBV_ILN_4249 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4306 | ||
| 912 | |a GBV_ILN_4307 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4322 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4335 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4367 | ||
| 912 | |a GBV_ILN_4700 | ||
| 951 | |a AR | ||
| 952 | |d 6 |j 2024 |e 10 |b 15 |c 10 | ||
| author_variant |
a r m ar arm z s zs a m a am ama h a a ha haa |
|---|---|
| matchkey_str |
article:30049261:2024----::utojcierooiseinoeotmztofrireeticrvae |
| hierarchy_sort_str |
2024 |
| publishDate |
2024 |
| allfields |
10.1007/s42452-024-06219-z doi (DE-627)SPR057805296 (SPR)s42452-024-06219-z-e DE-627 ger DE-627 rakwb eng Mohammed, Ayman R. verfasserin aut Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. Ergonomics design (dpeaa)DE-He213 Response surface methodology (dpeaa)DE-He213 Ergonomics assessments (dpeaa)DE-He213 Micro electric car (dpeaa)DE-He213 Saleh, Zead verfasserin aut Aldabbagh, Alhassan M. verfasserin aut Al Hanbali, Ahmad verfasserin aut Enthalten in Discover applied sciences Springer International Publishing, 2024 6(2024), 10 vom: 15. Okt. Online-Ressource (DE-627)1882945751 (DE-600)3181295-8 3004-9261 nnns volume:6 year:2024 number:10 day:15 month:10 https://dx.doi.org/10.1007/s42452-024-06219-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_72 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2024 10 15 10 |
| spelling |
10.1007/s42452-024-06219-z doi (DE-627)SPR057805296 (SPR)s42452-024-06219-z-e DE-627 ger DE-627 rakwb eng Mohammed, Ayman R. verfasserin aut Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. Ergonomics design (dpeaa)DE-He213 Response surface methodology (dpeaa)DE-He213 Ergonomics assessments (dpeaa)DE-He213 Micro electric car (dpeaa)DE-He213 Saleh, Zead verfasserin aut Aldabbagh, Alhassan M. verfasserin aut Al Hanbali, Ahmad verfasserin aut Enthalten in Discover applied sciences Springer International Publishing, 2024 6(2024), 10 vom: 15. Okt. Online-Ressource (DE-627)1882945751 (DE-600)3181295-8 3004-9261 nnns volume:6 year:2024 number:10 day:15 month:10 https://dx.doi.org/10.1007/s42452-024-06219-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_72 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2024 10 15 10 |
| allfields_unstemmed |
10.1007/s42452-024-06219-z doi (DE-627)SPR057805296 (SPR)s42452-024-06219-z-e DE-627 ger DE-627 rakwb eng Mohammed, Ayman R. verfasserin aut Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. Ergonomics design (dpeaa)DE-He213 Response surface methodology (dpeaa)DE-He213 Ergonomics assessments (dpeaa)DE-He213 Micro electric car (dpeaa)DE-He213 Saleh, Zead verfasserin aut Aldabbagh, Alhassan M. verfasserin aut Al Hanbali, Ahmad verfasserin aut Enthalten in Discover applied sciences Springer International Publishing, 2024 6(2024), 10 vom: 15. Okt. Online-Ressource (DE-627)1882945751 (DE-600)3181295-8 3004-9261 nnns volume:6 year:2024 number:10 day:15 month:10 https://dx.doi.org/10.1007/s42452-024-06219-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_72 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2024 10 15 10 |
| allfieldsGer |
10.1007/s42452-024-06219-z doi (DE-627)SPR057805296 (SPR)s42452-024-06219-z-e DE-627 ger DE-627 rakwb eng Mohammed, Ayman R. verfasserin aut Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. Ergonomics design (dpeaa)DE-He213 Response surface methodology (dpeaa)DE-He213 Ergonomics assessments (dpeaa)DE-He213 Micro electric car (dpeaa)DE-He213 Saleh, Zead verfasserin aut Aldabbagh, Alhassan M. verfasserin aut Al Hanbali, Ahmad verfasserin aut Enthalten in Discover applied sciences Springer International Publishing, 2024 6(2024), 10 vom: 15. Okt. Online-Ressource (DE-627)1882945751 (DE-600)3181295-8 3004-9261 nnns volume:6 year:2024 number:10 day:15 month:10 https://dx.doi.org/10.1007/s42452-024-06219-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_72 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2024 10 15 10 |
| allfieldsSound |
10.1007/s42452-024-06219-z doi (DE-627)SPR057805296 (SPR)s42452-024-06219-z-e DE-627 ger DE-627 rakwb eng Mohammed, Ayman R. verfasserin aut Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. Ergonomics design (dpeaa)DE-He213 Response surface methodology (dpeaa)DE-He213 Ergonomics assessments (dpeaa)DE-He213 Micro electric car (dpeaa)DE-He213 Saleh, Zead verfasserin aut Aldabbagh, Alhassan M. verfasserin aut Al Hanbali, Ahmad verfasserin aut Enthalten in Discover applied sciences Springer International Publishing, 2024 6(2024), 10 vom: 15. Okt. Online-Ressource (DE-627)1882945751 (DE-600)3181295-8 3004-9261 nnns volume:6 year:2024 number:10 day:15 month:10 https://dx.doi.org/10.1007/s42452-024-06219-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_72 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2024 10 15 10 |
| language |
English |
| source |
Enthalten in Discover applied sciences 6(2024), 10 vom: 15. Okt. volume:6 year:2024 number:10 day:15 month:10 |
| sourceStr |
Enthalten in Discover applied sciences 6(2024), 10 vom: 15. Okt. volume:6 year:2024 number:10 day:15 month:10 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Ergonomics design Response surface methodology Ergonomics assessments Micro electric car |
| isfreeaccess_bool |
true |
| container_title |
Discover applied sciences |
| authorswithroles_txt_mv |
Mohammed, Ayman R. @@aut@@ Saleh, Zead @@aut@@ Aldabbagh, Alhassan M. @@aut@@ Al Hanbali, Ahmad @@aut@@ |
| publishDateDaySort_date |
2024-10-15T00:00:00Z |
| hierarchy_top_id |
1882945751 |
| id |
SPR057805296 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR057805296</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20241016064820.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">241016s2024 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s42452-024-06219-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR057805296</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s42452-024-06219-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mohammed, Ayman R.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2024</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ergonomics design</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Response surface methodology</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ergonomics assessments</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Micro electric car</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Saleh, Zead</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Aldabbagh, Alhassan M.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Al Hanbali, Ahmad</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Discover applied sciences</subfield><subfield code="d">Springer International Publishing, 2024</subfield><subfield code="g">6(2024), 10 vom: 15. Okt.</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)1882945751</subfield><subfield code="w">(DE-600)3181295-8</subfield><subfield code="x">3004-9261</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:6</subfield><subfield code="g">year:2024</subfield><subfield code="g">number:10</subfield><subfield code="g">day:15</subfield><subfield code="g">month:10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s42452-024-06219-z</subfield><subfield code="m">X:SPRINGER</subfield><subfield code="x">Resolving-System</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_0</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_72</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">6</subfield><subfield code="j">2024</subfield><subfield code="e">10</subfield><subfield code="b">15</subfield><subfield code="c">10</subfield></datafield></record></collection>
|
| author |
Mohammed, Ayman R. |
| spellingShingle |
Mohammed, Ayman R. misc Ergonomics design misc Response surface methodology misc Ergonomics assessments misc Micro electric car Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| authorStr |
Mohammed, Ayman R. |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)1882945751 |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut |
| collection |
springer |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
3004-9261 |
| topic_title |
Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology Ergonomics design (dpeaa)DE-He213 Response surface methodology (dpeaa)DE-He213 Ergonomics assessments (dpeaa)DE-He213 Micro electric car (dpeaa)DE-He213 |
| topic |
misc Ergonomics design misc Response surface methodology misc Ergonomics assessments misc Micro electric car |
| topic_unstemmed |
misc Ergonomics design misc Response surface methodology misc Ergonomics assessments misc Micro electric car |
| topic_browse |
misc Ergonomics design misc Response surface methodology misc Ergonomics assessments misc Micro electric car |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
Discover applied sciences |
| hierarchy_parent_id |
1882945751 |
| hierarchy_top_title |
Discover applied sciences |
| isfreeaccess_txt |
true |
| familylinks_str_mv |
(DE-627)1882945751 (DE-600)3181295-8 |
| title |
Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| ctrlnum |
(DE-627)SPR057805296 (SPR)s42452-024-06219-z-e |
| title_full |
Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| author_sort |
Mohammed, Ayman R. |
| journal |
Discover applied sciences |
| journalStr |
Discover applied sciences |
| lang_code |
eng |
| isOA_bool |
true |
| recordtype |
marc |
| publishDateSort |
2024 |
| contenttype_str_mv |
txt |
| author_browse |
Mohammed, Ayman R. Saleh, Zead Aldabbagh, Alhassan M. Al Hanbali, Ahmad |
| container_volume |
6 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Mohammed, Ayman R. |
| doi_str_mv |
10.1007/s42452-024-06219-z |
| author2-role |
verfasserin |
| title_sort |
multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| title_auth |
Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| abstract |
Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. © The Author(s) 2024 |
| abstractGer |
Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. © The Author(s) 2024 |
| abstract_unstemmed |
Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency. Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs. © The Author(s) 2024 |
| collection_details |
SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_72 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2050 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
| container_issue |
10 |
| title_short |
Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology |
| url |
https://dx.doi.org/10.1007/s42452-024-06219-z |
| remote_bool |
true |
| author2 |
Saleh, Zead Aldabbagh, Alhassan M. Al Hanbali, Ahmad |
| author2Str |
Saleh, Zead Aldabbagh, Alhassan M. Al Hanbali, Ahmad |
| ppnlink |
1882945751 |
| mediatype_str_mv |
c |
| isOA_txt |
true |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s42452-024-06219-z |
| up_date |
2024-10-16T04:50:39.647Z |
| _version_ |
1813044778395238400 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR057805296</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20241016064820.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">241016s2024 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s42452-024-06219-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR057805296</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s42452-024-06219-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mohammed, Ayman R.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multi-objective ergonomics design model optimization for micro electric cars via response surface methodology</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2024</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Despite advancements in ergonomic comfort assessments in automotive design, optimizing seat dimensions within the constrained spaces of micro-electric cars presents a substantial challenge. In this study, response surface methodology (RSM) is utilized for the ergonomics design of a micro electric car in the conceptual design phase. Specifically, five critical seat dimensions are analyzed: Seatback Angle, Seat Base Angle, Steering Wheel Height from Car Base, Distance from Seat Base to Pedals, and Distance from Seat Base to Steering Wheel. The analysis took place using a 2-level full factorial design L32 orthogonal array. The optimal dimensions are determined using RSM, such as the mean comfort level and signal-to-noise ratio are maximized, and the standard deviation for multiple drivers is minimized. Three regression models are formulated for the three responses, and their adequacy is checked using different methods. The optimal dimensions are obtained and verified through digital human modeling simulation. This research offers practical guidelines for the ergonomic seating design in micro-electric vehicles, enhancing comfort without compromising space efficiency.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Article highlights This study creates better car seats for small electric cars, making rides more comfortable.It uses a unique mix of methods to find the best seat design, verified by software.Findings help car companies design seats that fit more people’s comfort needs.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ergonomics design</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Response surface methodology</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ergonomics assessments</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Micro electric car</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Saleh, Zead</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Aldabbagh, Alhassan M.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Al Hanbali, Ahmad</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Discover applied sciences</subfield><subfield code="d">Springer International Publishing, 2024</subfield><subfield code="g">6(2024), 10 vom: 15. Okt.</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)1882945751</subfield><subfield code="w">(DE-600)3181295-8</subfield><subfield code="x">3004-9261</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:6</subfield><subfield code="g">year:2024</subfield><subfield code="g">number:10</subfield><subfield code="g">day:15</subfield><subfield code="g">month:10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s42452-024-06219-z</subfield><subfield code="m">X:SPRINGER</subfield><subfield code="x">Resolving-System</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_0</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_72</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">6</subfield><subfield code="j">2024</subfield><subfield code="e">10</subfield><subfield code="b">15</subfield><subfield code="c">10</subfield></datafield></record></collection>
|
| score |
7.4003057 |