Search Results - "Veeraragavan, Ram Kumar" :: K.UTB vyhledávací portál

Development of Macrotexture Test Method for Dense-Graded Asphalt Mixtures

by Mergenmeier, Andy, Mensching, David J., Sakhaeifar, Maryam S., Ann Myers, Leslie, Kumar Veeraragavan, Ram
Published in Transportation research record (15.05.2024)

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Balanced Mix Design Production Analysis of Asphalt Mixtures in Vermont

by Nener-Plante, Derek, Schwartz, Aaron, Veeraragavan, Ram Kumar, Tran, Nam, Myers, Leslie
Published in Transportation research record (01.11.2023)

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Balanced Mix Design Benchmarking of Field-Produced Asphalt Mixtures in Maine, U.S

by Veeraragavan, Ram Kumar, Nener-Plante, Derek, Myers, Leslie, Nash, Casey, Tran, Nam H.
Published in Transportation research record (01.05.2022)

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Balanced Mix Design Benchmarking of Asphalt Mixtures Produced in Vermont

by Veeraragavan, Ram Kumar, Nener-Plante, Derek, Schwartz, Aaron, Tran, Nam H., Myers, Leslie
Published in Transportation research record (01.12.2023)

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Laboratory Comparison of Rejuvenated 50% Reclaimed Asphalt Pavement Hot-Mix Asphalt with Conventional 20% RAP Mix

by Veeraragavan, Ram Kumar, Mallick, Rajib B., Tao, Mingjiang, Zaumanis, Martins, Frank, Robert, Bradbury, Richard L.
Published in Transportation research record (2017)

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Accurate identification of pavement materials that are susceptible to moisture damage with the use of advanced conditioning and test methods and the use of machine learning techniques

by Veeraragavan, Ram Kumar, M. K., Nivedya, Mallick, Rajib B.
Published in SN applied sciences (2019)

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Journal Article

Development of Macrotexture Test Method for Dense-Graded Asphalt Mixtures

Balanced Mix Design Production Analysis of Asphalt Mixtures in Vermont

Balanced Mix Design Benchmarking of Field-Produced Asphalt Mixtures in Maine, U.S

Balanced Mix Design Benchmarking of Asphalt Mixtures Produced in Vermont

Laboratory Comparison of Rejuvenated 50% Reclaimed Asphalt Pavement Hot-Mix Asphalt with Conventional 20% RAP Mix

Accurate identification of pavement materials that are susceptible to moisture damage with the use of advanced conditioning and test methods and the use of machine learning techniques

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