Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers
The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have...
Ausführliche Beschreibung
Autor*in: |
Mário Santos [verfasserIn] Jaime Santos [verfasserIn] Lorena Petrella [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2022 |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
In: Electronics - MDPI AG, 2013, 11(2022), 18, p 2836 |
---|---|
Übergeordnetes Werk: |
volume:11 ; year:2022 ; number:18, p 2836 |
Links: |
---|
DOI / URN: |
10.3390/electronics11182836 |
---|
Katalog-ID: |
DOAJ00779035X |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ00779035X | ||
003 | DE-627 | ||
005 | 20240414204936.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230225s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.3390/electronics11182836 |2 doi | |
035 | |a (DE-627)DOAJ00779035X | ||
035 | |a (DE-599)DOAJ3739b0adbb0a454285e66181be42919d | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
050 | 0 | |a TK7800-8360 | |
100 | 0 | |a Mário Santos |e verfasserin |4 aut | |
245 | 1 | 0 | |a Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers |
264 | 1 | |c 2022 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. | ||
650 | 4 | |a carbon-fiber-reinforced polymer | |
650 | 4 | |a modelling | |
650 | 4 | |a pulse-echo | |
650 | 4 | |a simulation | |
650 | 4 | |a ultrasounds | |
650 | 4 | |a microflaw | |
653 | 0 | |a Electronics | |
700 | 0 | |a Jaime Santos |e verfasserin |4 aut | |
700 | 0 | |a Lorena Petrella |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t Electronics |d MDPI AG, 2013 |g 11(2022), 18, p 2836 |w (DE-627)718626478 |w (DE-600)2662127-7 |x 20799292 |7 nnns |
773 | 1 | 8 | |g volume:11 |g year:2022 |g number:18, p 2836 |
856 | 4 | 0 | |u https://doi.org/10.3390/electronics11182836 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/3739b0adbb0a454285e66181be42919d |z kostenfrei |
856 | 4 | 0 | |u https://www.mdpi.com/2079-9292/11/18/2836 |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/2079-9292 |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
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_170 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2014 | ||
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 11 |j 2022 |e 18, p 2836 |
author_variant |
m s ms j s js l p lp |
---|---|
matchkey_str |
article:20799292:2022----::opttoasmltoomcolweetoicrofb |
hierarchy_sort_str |
2022 |
callnumber-subject-code |
TK |
publishDate |
2022 |
allfields |
10.3390/electronics11182836 doi (DE-627)DOAJ00779035X (DE-599)DOAJ3739b0adbb0a454285e66181be42919d DE-627 ger DE-627 rakwb eng TK7800-8360 Mário Santos verfasserin aut Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw Electronics Jaime Santos verfasserin aut Lorena Petrella verfasserin aut In Electronics MDPI AG, 2013 11(2022), 18, p 2836 (DE-627)718626478 (DE-600)2662127-7 20799292 nnns volume:11 year:2022 number:18, p 2836 https://doi.org/10.3390/electronics11182836 kostenfrei https://doaj.org/article/3739b0adbb0a454285e66181be42919d kostenfrei https://www.mdpi.com/2079-9292/11/18/2836 kostenfrei https://doaj.org/toc/2079-9292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 11 2022 18, p 2836 |
spelling |
10.3390/electronics11182836 doi (DE-627)DOAJ00779035X (DE-599)DOAJ3739b0adbb0a454285e66181be42919d DE-627 ger DE-627 rakwb eng TK7800-8360 Mário Santos verfasserin aut Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw Electronics Jaime Santos verfasserin aut Lorena Petrella verfasserin aut In Electronics MDPI AG, 2013 11(2022), 18, p 2836 (DE-627)718626478 (DE-600)2662127-7 20799292 nnns volume:11 year:2022 number:18, p 2836 https://doi.org/10.3390/electronics11182836 kostenfrei https://doaj.org/article/3739b0adbb0a454285e66181be42919d kostenfrei https://www.mdpi.com/2079-9292/11/18/2836 kostenfrei https://doaj.org/toc/2079-9292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 11 2022 18, p 2836 |
allfields_unstemmed |
10.3390/electronics11182836 doi (DE-627)DOAJ00779035X (DE-599)DOAJ3739b0adbb0a454285e66181be42919d DE-627 ger DE-627 rakwb eng TK7800-8360 Mário Santos verfasserin aut Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw Electronics Jaime Santos verfasserin aut Lorena Petrella verfasserin aut In Electronics MDPI AG, 2013 11(2022), 18, p 2836 (DE-627)718626478 (DE-600)2662127-7 20799292 nnns volume:11 year:2022 number:18, p 2836 https://doi.org/10.3390/electronics11182836 kostenfrei https://doaj.org/article/3739b0adbb0a454285e66181be42919d kostenfrei https://www.mdpi.com/2079-9292/11/18/2836 kostenfrei https://doaj.org/toc/2079-9292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 11 2022 18, p 2836 |
allfieldsGer |
10.3390/electronics11182836 doi (DE-627)DOAJ00779035X (DE-599)DOAJ3739b0adbb0a454285e66181be42919d DE-627 ger DE-627 rakwb eng TK7800-8360 Mário Santos verfasserin aut Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw Electronics Jaime Santos verfasserin aut Lorena Petrella verfasserin aut In Electronics MDPI AG, 2013 11(2022), 18, p 2836 (DE-627)718626478 (DE-600)2662127-7 20799292 nnns volume:11 year:2022 number:18, p 2836 https://doi.org/10.3390/electronics11182836 kostenfrei https://doaj.org/article/3739b0adbb0a454285e66181be42919d kostenfrei https://www.mdpi.com/2079-9292/11/18/2836 kostenfrei https://doaj.org/toc/2079-9292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 11 2022 18, p 2836 |
allfieldsSound |
10.3390/electronics11182836 doi (DE-627)DOAJ00779035X (DE-599)DOAJ3739b0adbb0a454285e66181be42919d DE-627 ger DE-627 rakwb eng TK7800-8360 Mário Santos verfasserin aut Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw Electronics Jaime Santos verfasserin aut Lorena Petrella verfasserin aut In Electronics MDPI AG, 2013 11(2022), 18, p 2836 (DE-627)718626478 (DE-600)2662127-7 20799292 nnns volume:11 year:2022 number:18, p 2836 https://doi.org/10.3390/electronics11182836 kostenfrei https://doaj.org/article/3739b0adbb0a454285e66181be42919d kostenfrei https://www.mdpi.com/2079-9292/11/18/2836 kostenfrei https://doaj.org/toc/2079-9292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 11 2022 18, p 2836 |
language |
English |
source |
In Electronics 11(2022), 18, p 2836 volume:11 year:2022 number:18, p 2836 |
sourceStr |
In Electronics 11(2022), 18, p 2836 volume:11 year:2022 number:18, p 2836 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw Electronics |
isfreeaccess_bool |
true |
container_title |
Electronics |
authorswithroles_txt_mv |
Mário Santos @@aut@@ Jaime Santos @@aut@@ Lorena Petrella @@aut@@ |
publishDateDaySort_date |
2022-01-01T00:00:00Z |
hierarchy_top_id |
718626478 |
id |
DOAJ00779035X |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ00779035X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414204936.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/electronics11182836</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ00779035X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ3739b0adbb0a454285e66181be42919d</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="050" ind1=" " ind2="0"><subfield code="a">TK7800-8360</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Mário Santos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</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="520" ind1=" " ind2=" "><subfield code="a">The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">carbon-fiber-reinforced polymer</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modelling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">pulse-echo</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">ultrasounds</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">microflaw</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Electronics</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jaime Santos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lorena Petrella</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Electronics</subfield><subfield code="d">MDPI AG, 2013</subfield><subfield code="g">11(2022), 18, p 2836</subfield><subfield code="w">(DE-627)718626478</subfield><subfield code="w">(DE-600)2662127-7</subfield><subfield code="x">20799292</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:18, p 2836</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/electronics11182836</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/3739b0adbb0a454285e66181be42919d</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2079-9292/11/18/2836</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2079-9292</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</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_23</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_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_60</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_70</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_170</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_370</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_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">11</subfield><subfield code="j">2022</subfield><subfield code="e">18, p 2836</subfield></datafield></record></collection>
|
callnumber-first |
T - Technology |
author |
Mário Santos |
spellingShingle |
Mário Santos misc TK7800-8360 misc carbon-fiber-reinforced polymer misc modelling misc pulse-echo misc simulation misc ultrasounds misc microflaw misc Electronics Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers |
authorStr |
Mário Santos |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)718626478 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut |
collection |
DOAJ |
remote_str |
true |
callnumber-label |
TK7800-8360 |
illustrated |
Not Illustrated |
issn |
20799292 |
topic_title |
TK7800-8360 Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers carbon-fiber-reinforced polymer modelling pulse-echo simulation ultrasounds microflaw |
topic |
misc TK7800-8360 misc carbon-fiber-reinforced polymer misc modelling misc pulse-echo misc simulation misc ultrasounds misc microflaw misc Electronics |
topic_unstemmed |
misc TK7800-8360 misc carbon-fiber-reinforced polymer misc modelling misc pulse-echo misc simulation misc ultrasounds misc microflaw misc Electronics |
topic_browse |
misc TK7800-8360 misc carbon-fiber-reinforced polymer misc modelling misc pulse-echo misc simulation misc ultrasounds misc microflaw misc Electronics |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Electronics |
hierarchy_parent_id |
718626478 |
hierarchy_top_title |
Electronics |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)718626478 (DE-600)2662127-7 |
title |
Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers |
ctrlnum |
(DE-627)DOAJ00779035X (DE-599)DOAJ3739b0adbb0a454285e66181be42919d |
title_full |
Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers |
author_sort |
Mário Santos |
journal |
Electronics |
journalStr |
Electronics |
callnumber-first-code |
T |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2022 |
contenttype_str_mv |
txt |
author_browse |
Mário Santos Jaime Santos Lorena Petrella |
container_volume |
11 |
class |
TK7800-8360 |
format_se |
Elektronische Aufsätze |
author-letter |
Mário Santos |
doi_str_mv |
10.3390/electronics11182836 |
author2-role |
verfasserin |
title_sort |
computational simulation of microflaw detection in carbon-fiber-reinforced polymers |
callnumber |
TK7800-8360 |
title_auth |
Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers |
abstract |
The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. |
abstractGer |
The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. |
abstract_unstemmed |
The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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 |
18, p 2836 |
title_short |
Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers |
url |
https://doi.org/10.3390/electronics11182836 https://doaj.org/article/3739b0adbb0a454285e66181be42919d https://www.mdpi.com/2079-9292/11/18/2836 https://doaj.org/toc/2079-9292 |
remote_bool |
true |
author2 |
Jaime Santos Lorena Petrella |
author2Str |
Jaime Santos Lorena Petrella |
ppnlink |
718626478 |
callnumber-subject |
TK - Electrical and Nuclear Engineering |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.3390/electronics11182836 |
callnumber-a |
TK7800-8360 |
up_date |
2024-07-03T14:07:44.243Z |
_version_ |
1803567145151365120 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ00779035X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414204936.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/electronics11182836</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ00779035X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ3739b0adbb0a454285e66181be42919d</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="050" ind1=" " ind2="0"><subfield code="a">TK7800-8360</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Mário Santos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Computational Simulation of Microflaw Detection in Carbon-Fiber-Reinforced Polymers</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</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="520" ind1=" " ind2=" "><subfield code="a">The evaluation of microflaws in carbon-fiber-reinforced composite laminate (CFRP) via ultrasound requires the knowledge of some important factors in addition to its structural composition. Since the laminates are heterogeneous, the high-frequency requirements to acquire high-resolution signals have limitations due to the great scattering that prevents good signal-to-noise ratios. Additionally, the ultrasonic probe’s spatial and lateral resolution characteristics are important parameters for determining the detectability level of microflaws. Modelling appears as a good approach to evaluating the abovementioned factors and the probability of detection of defects in the micron range because it makes it possible to reduce the time and cost associated with developments based on experimental tests. Concerning the subject of this work, simulation is the best way to evaluate the detectability level of the proposed defects since experimental samples are not available. In this work, the simulation was implemented using the Matlab k-Wave toolbox. A 2D matrix for mimicking a CFRP was constructed with 1 μm of resolution. Four different defect types in the micron range were created in the matrix. The simulated and experimental results presented good agreement. It was concluded that the highest frequency probe that could be used to detect the simulated defects without ambiguity was 25 MHz.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">carbon-fiber-reinforced polymer</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modelling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">pulse-echo</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">ultrasounds</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">microflaw</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Electronics</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jaime Santos</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lorena Petrella</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Electronics</subfield><subfield code="d">MDPI AG, 2013</subfield><subfield code="g">11(2022), 18, p 2836</subfield><subfield code="w">(DE-627)718626478</subfield><subfield code="w">(DE-600)2662127-7</subfield><subfield code="x">20799292</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:11</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:18, p 2836</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/electronics11182836</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/3739b0adbb0a454285e66181be42919d</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/2079-9292/11/18/2836</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2079-9292</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</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_23</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_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_60</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_70</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_170</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_370</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_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">11</subfield><subfield code="j">2022</subfield><subfield code="e">18, p 2836</subfield></datafield></record></collection>
|
score |
7.3993673 |