Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT)
Workability, determines whether the concrete is suitable to cast in-situ for specified job. In practice it is determine by multiple test methods to find the workability properties by following EFNARC guidelines. To evaluate these properties in single test Ultrasonic sensors (hc-sr04) and Ultrasonic...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Subjects: | |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/28/e3sconf_icmed-icmpc2023_01195.pdf |
| _version_ | 1797807787903811584 |
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| author | Ashwini Mittapalli Naga Reddy V. Mallikarjuna |
| author_facet | Ashwini Mittapalli Naga Reddy V. Mallikarjuna |
| author_sort | Ashwini Mittapalli Naga |
| collection | DOAJ |
| description | Workability, determines whether the concrete is suitable to cast in-situ for specified job. In practice it is determine by multiple test methods to find the workability properties by following EFNARC guidelines. To evaluate these properties in single test Ultrasonic sensors (hc-sr04) and Ultrasonic pulse velocity (UPV) test are used. The float glass box of dimensions 300×300×400 mm with reinforcement inside 16mm dia with spacing 46mm and clear cover 40mm is used for simulation. The hc-sr04 sensors are placed at the corners of the glass column for determining the concrete filled into the box and monitor through Arduino.ide software. The filling ability is determined by the time taken to fill the column and classified into FA1, FA2 & FA3 classes. The passing ability is determined by the difference of concrete height at inside the reinforcement and at the corners after filling and classified into PA1, PA2 & PA3. Ultrasonic velocity measurements are taken by direct mode and based on the variations at different locations segregation resistance is classified into SR1, SR2 & SR3. The aim of this simulation was to establish the relation between experimental tests and simulation IoT test results. Comparison between empirical tests and stimulation model shows that this model can used to check the workability at in-situ to meet the job specification. |
| first_indexed | 2024-03-13T06:27:53Z |
| format | Article |
| id | doaj.art-6af220e9889549ee9ffb0e813e7433e1 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-13T06:27:53Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-6af220e9889549ee9ffb0e813e7433e12023-06-09T09:12:20ZengEDP SciencesE3S Web of Conferences2267-12422023-01-013910119510.1051/e3sconf/202339101195e3sconf_icmed-icmpc2023_01195Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT)Ashwini Mittapalli Naga0Reddy V. Mallikarjuna1Department of Civil Engineering, GRIETDepartment of Civil Engineering, GRIETWorkability, determines whether the concrete is suitable to cast in-situ for specified job. In practice it is determine by multiple test methods to find the workability properties by following EFNARC guidelines. To evaluate these properties in single test Ultrasonic sensors (hc-sr04) and Ultrasonic pulse velocity (UPV) test are used. The float glass box of dimensions 300×300×400 mm with reinforcement inside 16mm dia with spacing 46mm and clear cover 40mm is used for simulation. The hc-sr04 sensors are placed at the corners of the glass column for determining the concrete filled into the box and monitor through Arduino.ide software. The filling ability is determined by the time taken to fill the column and classified into FA1, FA2 & FA3 classes. The passing ability is determined by the difference of concrete height at inside the reinforcement and at the corners after filling and classified into PA1, PA2 & PA3. Ultrasonic velocity measurements are taken by direct mode and based on the variations at different locations segregation resistance is classified into SR1, SR2 & SR3. The aim of this simulation was to establish the relation between experimental tests and simulation IoT test results. Comparison between empirical tests and stimulation model shows that this model can used to check the workability at in-situ to meet the job specification.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/28/e3sconf_icmed-icmpc2023_01195.pdfsccworkability propertiesultrasonic sensor (hc sr04)ultrasonic pulse velocity test and iot |
| spellingShingle | Ashwini Mittapalli Naga Reddy V. Mallikarjuna Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT) E3S Web of Conferences scc workability properties ultrasonic sensor (hc sr04) ultrasonic pulse velocity test and iot |
| title | Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT) |
| title_full | Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT) |
| title_fullStr | Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT) |
| title_full_unstemmed | Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT) |
| title_short | Monitoring workability properties of self-compacting concrete (SCC) using Internet of Things (IoT) |
| title_sort | monitoring workability properties of self compacting concrete scc using internet of things iot |
| topic | scc workability properties ultrasonic sensor (hc sr04) ultrasonic pulse velocity test and iot |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/28/e3sconf_icmed-icmpc2023_01195.pdf |
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