Rajpal Singh Bhoopal

Employment

• University of Rajasthan, Jaipur

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (19)

• An analysis of single conductive filler-reinforced HDPE composites: a material-centric pathway toward metal-based conductivity enhancement
  Polymer Bulletin 2026 2 citations DOI: 10.1007/s00289-026-06421-6
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• Mechanical properties of HDPE/oxidized Fischer–Tropsch wax composites: Statistical and computational approximation analysis of ANNs and PRA
  Journal of Thermoplastic Composite Materials 2026 0 citations DOI: 10.1177/08927057261471573
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• Theoretical assessment of mechanical behaviour of LDPE/Cu composites using nonlinear polynomial regression analysis
  Advances in Mechanical Engineering 2025 11 citations DOI: 10.1177/16878132251323156
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• Estimation of Mechanical Properties of Copper Powder Filled Linear Low-Density Polyethylene Composites
  Journal of Vibration Engineering & Technologies, Springer Nature Singapore 2022
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• Estimation of Mechanical Properties of Copper Powder Filled Linear Low-Density Polyethylene Composites
  Journal of Vibration Engineering and Technologies 2022 4 citations DOI: 10.1007/s42417-022-00496-x
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• Computational studies for the effective electrical conductivity of copper powder filled LDPE/LLDPE composites
  Indian Journal of Pure & Applied Physics (IJPAP) 2020
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• Computational studies for the effective electrical conductivity of copper powder filled LDPE/LLDPE composites
  Indian Journal of Pure and Applied Physics 2020
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• Effect of black and white color on HDPE geomembranes and formation of wrinkles
  Aip Conference Proceedings 2019 0 citations DOI: 10.1063/1.5122570
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• PREDICTION OF THE MECHANICAL PROPERTIES OF COPPER POWDER-FILLED LOW-DENSITY POLYETHYLENE COMPOSITES. A COMPARISON BETWEEN THE ANN AND THEORETICAL MODELS
  Composites: Mechanics, Computations, Applications: An International Journal 2015 2 citations DOI: 10.1615/compmechcomputapplintj.v6.i1.30
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• APPLICABILITY OF ARTIFICIAL NEURAL NETWORKS TO PREDICT EFFECTIVE THERMAL CONDUCTIVITY OF HIGHLY POROUS METAL FOAMS
  Journal of Porous Media 2013 11 citations DOI: 10.1615/jpormedia.v16.i7.10
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