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Experimental investigation of the mechanical and thermal behavior of a PT6A-61A engine using mixtures of JETA-1 and biodiesel

  • Alberth Renne Gonzalez Caranton
  • , Vladimir Silva Leal
  • , Camilo Bayona-Roa
  • , Manuel Alejandro Mayorga Betancourt
  • , Carolina Betancourt
  • , Deiver Cortina
  • , Nelson Jimenez Acuña
  • , Mauricio López

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Biofuels are important additives to conventional fuels in combustion engines of the transport sector, as they reduce atmospheric emissions and promote environmental-friendly production chains. The mechanical and thermal performance of a PT6A-61A engine on a test bench of the Colombian Air Force operating with blends of JETA-1 and Biodiesel up to 25% volume values of substitution is evaluated in this work. Experimental results show that blends are operationally reliable up to 15% volume content. In that range, the engine operation is not compromised in terms of response variables. Moreover, experimental properties of fuel blends show that the freezing point—which is the most critical variable, does not comply with aeronautical regulations. The system dynamics are subject to several variations in the test parameters, which mainly affected fuel flow, Inter-Turbine Temperature (ITT), and engine performance. A Principal Component Analysis (PCA) is performed over the experimental results to quantify possible disturbances on the bench measurements. This is based on the fact that the study is restrained to stationary test bench conditions.

Original languageEnglish
Article number3282
JournalEnergies
Volume14
Issue number11
DOIs
StatePublished - 01 Jun 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Biodiesel
  • Experimental fluctuations
  • Fuel blending
  • JETA-1
  • Mechanical behavior
  • PT6A-61A engine
  • Principal component analysis (PCA)

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