The influence of CBRvalue on the cost of optimal flexible pavement design

Publicado 2023-01-25
Seção Research Articles

Autores

  • Venkatesh Baskaran Government College Of Engineering, Tirunelveli, India
  • Raj C Subash Government College of Engineering, Tirunelveli, India
  • V.R. Subbu Sankar Government College of Engineering, Tirunelveli, India
  • K. Blessy Government College of Engineering, Tirunelveli, India

DOI:

https://doi.org/10.7770/safer-V12N1-art2780

Resumo

Road transport would be arteries for the economy pulse. As a developing nation, India focuses on connecting all partsof thecountry through this road network. Flexible pavement is generally preferred for the road with low to medium traffic conditions. The flexible pavement design depends on the CBR of subgrade soiland design traffic for the selected road specified in IRC 37-2018. The study is limited to the road link at Tirunelveli City paved with a bituminous surface course with a granular base and sub-base between South Bypass road Junction near New bus stand –NH 44 service road intersection. Effective subgrade CBRvalue consideredfrom 9% to 15% inthe study area. The traffic volume detail and vehicle classification were collected with the help of an automatic vehicle classifier called MetroCount. The design starts with selecting a trial profile by considering CBR and MSA from the appropriate catalog. The stress and strain were estimated at critical locations of pavement by performing Structural Analysis in IITPAVE software. The optimal design is achieved by altering the layer thickness to minimize the gap between actual and allowable strain. An increase in CBR value decreases the thickness of the functional layer of pavement. Cost estimation has arrived from rate analysis for various work items as per IRC specification and schedule of rates. Similar studies were identified in evaluating the construction cost corresponding to different design methods. This study concluded that improvement in 1 % CBR saves about 1 to 2% of overall construction cost in optimal design.