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description Publicationkeyboard_double_arrow_right Article 2023Publisher:MDPI AG Chaehyeon Kim; Yooseob Song; Junhwi Cho; Julian Kang; Jaeheum Yeon;doi: 10.3390/su151410772
Embedded sensors are widely employed for the structural health monitoring of structures constructed with concrete or mortar. Despite embedded sensors being actively used, there has been no study on whether or not the sensor probe placement within structures made of concrete or mortar influences their structural stability. The strength of small structures in particular could be affected by sensor probes embedded within them. To address the lack of research in this area, this study analyzed the effect of embedding positions of sensor probes on the compressive strength development of mortar. After the production of mortar specimens with the depth of the embedded sensor being controlled by the developed mold, compressive strength tests were conducted, and then test results were verified through finite element analysis. For testing, copper–nickel-plated sensor probes were embedded within the mortar because these sensor probes are popular commercial probes. The test results show that the compressive strength was 7.1 MPa when the sensor probe was embedded at a depth of 5 mm. In contrast, the compressive strength was 28.2 MPa at a depth of 30 mm. Since the compressive strength without the embedded sensor probe was 29.8 MPa, considering the results of this study, it is highly recommended that copper–nickel-plated sensor probes be embedded at least 30 mm from the surface of mortar structures.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su151410772&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 1 citations 1 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su151410772&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023Publisher:MDPI AG Junhwi Cho; Julian Kang; Yooseob Song; Seungjoo Lee; Jaeheum Yeon;doi: 10.3390/su16010112
Traditional spalling repair on concrete pavement roads is labor-intensive. It involves traffic blockages and the manual calculation of repair areas, leading to time-consuming processes with potential discrepancies. This study used a line scan camera to photograph road surface conditions to analyze spalling without causing traffic blockage in an indoor setting. By using deep learning algorithms, specifically a region-based convolutional neural network (R-CNN) in the form of the Mask R-CNN algorithm, the system detects spalling and calculates its area. The program processes data based on the Federal Highway Administration (FHWA) spalling repair standards. Accuracy was assessed using root mean square error (RMSE) and Pearson correlation coefficient (PCC) via comparisons with actual field calculations. The RMSE values were 0.0137 and 0.0167 for the minimum and maximum repair areas, respectively, showing high accuracy. The PCC values were 0.987 and 0.992, indicating a strong correlation between the actual and calculated repair areas, confirming the high calculation accuracy of the method.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16010112&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16010112&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019Publisher:MDPI AG Authors: Kwan Kyu Kim; Jaeheum Yeon; Hee Jun Lee; Kyu-Seok Yeon;doi: 10.3390/su11154164
The properties of normal cementitious mixtures currently employed to the construction projects cannot be used to the three-dimensional concrete printing technology. This study experimentally investigated the compressive and flexural strength development of styrene-butadiene rubber (SBR)-modified cementitious mixtures for use as basic three-dimensional concrete printing (3DCP) materials. The SBR/cement ratio was a variable of the mix proportion used to produce cast and printed specimens. Experiments were conducted using these specimens to determine the compressive and flexural strength levels of the SBR-modified cementitious mixtures. The results indicated that the compressive strengths of the SBR-modified cementitious mixtures proposed in this study were never less than those of existing 3D concrete printing materials previously introduced for 3DCP applications. It was confirmed that the addition of SBR latex effectively improved the strength of the cementitious mixtures because the relative compressive and flexural strengths increased with increases in the SBR/cement ratio. Moreover, the higher early (i.e., 1-day) strength indicates that the SBR-modified cementitious mixtures would be advantageous to the 3DCP process. However, the compressive and flexural strengths of the printed specimens were weaker than those of the cast specimens.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su11154164&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 8 citations 8 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su11154164&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
description Publicationkeyboard_double_arrow_right Article 2023Publisher:MDPI AG Chaehyeon Kim; Yooseob Song; Junhwi Cho; Julian Kang; Jaeheum Yeon;doi: 10.3390/su151410772
Embedded sensors are widely employed for the structural health monitoring of structures constructed with concrete or mortar. Despite embedded sensors being actively used, there has been no study on whether or not the sensor probe placement within structures made of concrete or mortar influences their structural stability. The strength of small structures in particular could be affected by sensor probes embedded within them. To address the lack of research in this area, this study analyzed the effect of embedding positions of sensor probes on the compressive strength development of mortar. After the production of mortar specimens with the depth of the embedded sensor being controlled by the developed mold, compressive strength tests were conducted, and then test results were verified through finite element analysis. For testing, copper–nickel-plated sensor probes were embedded within the mortar because these sensor probes are popular commercial probes. The test results show that the compressive strength was 7.1 MPa when the sensor probe was embedded at a depth of 5 mm. In contrast, the compressive strength was 28.2 MPa at a depth of 30 mm. Since the compressive strength without the embedded sensor probe was 29.8 MPa, considering the results of this study, it is highly recommended that copper–nickel-plated sensor probes be embedded at least 30 mm from the surface of mortar structures.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su151410772&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 1 citations 1 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su151410772&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023Publisher:MDPI AG Junhwi Cho; Julian Kang; Yooseob Song; Seungjoo Lee; Jaeheum Yeon;doi: 10.3390/su16010112
Traditional spalling repair on concrete pavement roads is labor-intensive. It involves traffic blockages and the manual calculation of repair areas, leading to time-consuming processes with potential discrepancies. This study used a line scan camera to photograph road surface conditions to analyze spalling without causing traffic blockage in an indoor setting. By using deep learning algorithms, specifically a region-based convolutional neural network (R-CNN) in the form of the Mask R-CNN algorithm, the system detects spalling and calculates its area. The program processes data based on the Federal Highway Administration (FHWA) spalling repair standards. Accuracy was assessed using root mean square error (RMSE) and Pearson correlation coefficient (PCC) via comparisons with actual field calculations. The RMSE values were 0.0137 and 0.0167 for the minimum and maximum repair areas, respectively, showing high accuracy. The PCC values were 0.987 and 0.992, indicating a strong correlation between the actual and calculated repair areas, confirming the high calculation accuracy of the method.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16010112&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su16010112&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019Publisher:MDPI AG Authors: Kwan Kyu Kim; Jaeheum Yeon; Hee Jun Lee; Kyu-Seok Yeon;doi: 10.3390/su11154164
The properties of normal cementitious mixtures currently employed to the construction projects cannot be used to the three-dimensional concrete printing technology. This study experimentally investigated the compressive and flexural strength development of styrene-butadiene rubber (SBR)-modified cementitious mixtures for use as basic three-dimensional concrete printing (3DCP) materials. The SBR/cement ratio was a variable of the mix proportion used to produce cast and printed specimens. Experiments were conducted using these specimens to determine the compressive and flexural strength levels of the SBR-modified cementitious mixtures. The results indicated that the compressive strengths of the SBR-modified cementitious mixtures proposed in this study were never less than those of existing 3D concrete printing materials previously introduced for 3DCP applications. It was confirmed that the addition of SBR latex effectively improved the strength of the cementitious mixtures because the relative compressive and flexural strengths increased with increases in the SBR/cement ratio. Moreover, the higher early (i.e., 1-day) strength indicates that the SBR-modified cementitious mixtures would be advantageous to the 3DCP process. However, the compressive and flexural strengths of the printed specimens were weaker than those of the cast specimens.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su11154164&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 8 citations 8 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su11154164&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu