0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

Suraj Kumar Parhi

The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Kumar Parhi, Suraj / Dwibedy, Saswat / Kumar Panigrahi, Saubhagya (2024): AI-driven critical parameter optimization of sustainable self-compacting geopolymer concrete. In: Journal of Building Engineering, v. 86 (June 2024).

    https://doi.org/10.1016/j.jobe.2024.108923

  2. Kumar Dash, Pankaj / Kumar Parhi, Suraj / Patro, Sanjaya Kumar / Panigrahi, Ramakanta (2023): Efficient machine learning algorithm with enhanced cat swarm optimization for prediction of compressive strength of GGBS-based geopolymer concrete at elevated temperature. In: Construction and Building Materials, v. 400 (October 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.132814

  3. Kumar Parhi, Suraj / Patro, Sanjaya Kumar (2023): Prediction of compressive strength of geopolymer concrete using a hybrid ensemble of grey wolf optimized machine learning estimators. In: Journal of Building Engineering, v. 71 (July 2023).

    https://doi.org/10.1016/j.jobe.2023.106521

  4. Kumar Parhi, Suraj / Patro, Sanjaya Kumar (2024): Application of R-curve, ANCOVA, and RSM techniques on fracture toughness enhancement in PET fiber-reinforced concrete. In: Construction and Building Materials, v. 411 (January 2024).

    https://doi.org/10.1016/j.conbuildmat.2023.134644

  5. Pradhan, Jharana / Panda, Soumyaranjan / Kumar Parhi, Suraj / Pradhan, Priyanka / Kumar Panigrahi, Saubhagya (2024): GGBFS-Based Self-Compacting Geopolymer Concrete with Optimized Mix Parameters Established on Fresh, Mechanical, and Durability Characteristics. In: Journal of Materials in Civil Engineering (ASCE), v. 36, n. 2 (February 2024).

    https://doi.org/10.1061/jmcee7.mteng-16669

  6. Kumar Parhi, Suraj / Patro, Sanjaya Kumar (2023): Compressive strength prediction of PET fiber-reinforced concrete using Dolphin echolocation optimized decision tree-based machine learning algorithms. In: Asian Journal of Civil Engineering, v. 25, n. 1 (July 2023).

    https://doi.org/10.1007/s42107-023-00826-8

  7. Kumar Parhi, Suraj / Kumar Panigrahi, Saubhagya (2023): Alkali–silica reaction expansion prediction in concrete using hybrid metaheuristic optimized machine learning algorithms. In: Asian Journal of Civil Engineering, v. 25, n. 1 (July 2023).

    https://doi.org/10.1007/s42107-023-00799-8

  8. Kumar Parhi, Suraj / Dwibedy, Saswat / Panda, Soumyaranjan / Kumar Panigrahi, Saubhagya (2023): A comprehensive study on Controlled Low Strength Material. In: Journal of Building Engineering, v. 76 (October 2023).

    https://doi.org/10.1016/j.jobe.2023.107086

  9. Singh, Sourav / Patro, Sanjaya Kumar / Kumar Parhi, Suraj (2023): Evolutionary optimization of machine learning algorithm hyperparameters for strength prediction of high-performance concrete. In: Asian Journal of Civil Engineering, v. 24, n. 8 (June 2023).

    https://doi.org/10.1007/s42107-023-00698-y

  10. Pradhan, Priyanka / Panda, Soumyaranjan / Kumar Parhi, Suraj / Kumar Panigrahi, Saubhagya (2022): Factors affecting production and properties of self-compacting geopolymer concrete – A review. In: Construction and Building Materials, v. 344 (August 2022).

    https://doi.org/10.1016/j.conbuildmat.2022.128174

Search for a publication...

Only available with
My Structurae

Full text
Structurae cooperates with
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine