de Carvalho Rocha Werickson Fortunato, Presser Cary, Bernier Shannon, Nazarian Ashot, Sheen David A
NIST Associate, National Institute of Metrology, Quality and Technology (Inmetro), 25250-020 Duque de Caxias, RJ, Brazil.
Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.
Fuel (Lond). 2020;281. doi: 10.1016/j.fuel.2020.118720.
Requirements for blends of drop-in petroleum/bio-derived fuels with specific thermophysical and thermochemical properties highlights the need for chemometric models that can predict these properties. Multivariate calibration methods were evaluated using the measured thermograms (i.e., change in temperature with time) of 11 diesel/biodiesel fuel blends (including four repeated runs for each fuel blend). Two National Institute of Standards and Technology Standard Reference Material (SRM) pure fuels were blended by serial dilution to produce fuels having diesel/biodiesel volumetric fractions between (0 to 100) %. The fuels were evaluated for the prepared fuel-blend volume fraction and total specific energy release (heating value), using a laser-driven calorimetry technique, termed 'laser-driven thermal reactor'. The experimental apparatus consists of a copper sphere-shaped reactor (mounted at the center of a stainless-steel chamber) that is heated by a high-power continuous wave Nd:YAG laser. Prior to heating by the laser, liquid sample is injected onto a copper pan substrate that rests near the center of the reactor and is in contact with a fine-wire thermocouple. A second thermocouple is in contact with the sphere-reactor inner surface. The thermograms are then used to evaluate for the thermochemical characteristic of interest. Partial least squares (PLS) and support vector machine (SVM) models were constructed and evaluated for SRM-fuel-blend quantification, and determination of prepared fuel-blend volume fraction and heating value. Quantification of the fuel-blend thermograms by the SVM method was found to better correlate with the experimental results than PLS. The combination of laser-driven calorimetry and multivariate calibration methods has demonstrated the potential application of using thermograms for fuels quantification and analysis of fuel-blend properties.
对具有特定热物理和热化学性质的直接替代石油/生物衍生燃料混合物的要求凸显了对能够预测这些性质的化学计量模型的需求。使用11种柴油/生物柴油燃料混合物（每种燃料混合物包括四次重复运行）的测量热谱图（即温度随时间的变化）评估多元校准方法。将两种美国国家标准与技术研究院标准参考物质（SRM）纯燃料通过连续稀释进行混合，以生产柴油/生物柴油体积分数在（0至100）%之间的燃料。使用一种称为“激光驱动热反应器”的激光驱动量热技术，对制备的燃料混合物体积分数和总比能量释放（热值）进行评估。实验装置由一个铜球形反应器（安装在不锈钢腔室的中心）组成，该反应器由高功率连续波Nd:YAG激光加热。在由激光加热之前，将液体样品注入放置在反应器中心附近并与细金属丝热电偶接触的铜盘基板上。第二个热电偶与球形反应器内表面接触。然后使用热谱图评估感兴趣的热化学特性。构建并评估了偏最小二乘法（PLS）和支持向量机（SVM）模型，用于SRM燃料混合物定量以及确定制备的燃料混合物体积分数和热值。发现通过SVM方法对燃料混合物热谱图进行定量与实验结果的相关性比PLS更好。激光驱动量热法和多元校准方法的结合证明了使用热谱图进行燃料定量和燃料混合物性质分析的潜在应用。
