产物导向与机器学习驱动的富油煤热解提油热效应评估

煤炭热解过程的热效应是煤炭热解机理研究、反应器设计等过程的关键参数。目前关于煤炭热解热效应的评估方法之间精度差异较大,其中应用最多且可行性最大的方法为基于同步热分析仪(TG-DSC同步联用)来进行测定,但该方法依然对仪器的测量精度依赖较大,且在得到热流曲线之后的热效应计算方法之间精度也存在差异,导致数据的可重复性差,难以适应大规模生产及工艺设计的需要。富油煤含有较多的脂肪侧链、桥键等富氢结构,在热解过程中受热裂解生成更多的焦油,是良好的煤制油原材料。热解工艺的调控是影响富油煤热解所制焦油品质的关键因素,这其中热解过程的热效应又是热解工艺开发的重要参数,因此无论是对富油煤热解还是对广义的煤炭转化来说,都迫切需要开发准确、高效的煤炭热解热效应评估方法。基于富油煤慢速热解实验结果并结合热解反应机理和经验公式,以产物为导向构建富油煤热解反应体系,利用经典热力学分析方法进行反应体系的热力学计算,得到富油煤热解过程的化学反应热,再结合热解过程中的物理吸热量,得到了富油煤中低温慢速热解过程中的热效应。结合已报道的煤炭热解实验结果和热解热效应测定值,利用机器学习方法中的随机森林模型对煤炭热解热效应进行非线性建模和预测。结果表明:基于实验结果,以产物为导向计算得到的富油煤慢速热解热效应数值总体要低于利用TG-DSC同步联用测得的数值,误差均在10%以内。基于机器学习算法预测得到的富油煤热解热效应的预测精度达到0.9352。综合来看,所构建的2种富油煤热解热效应预测模型具有实用性和适用性。

Study on Vitalizing Port Operation at Ulsan Port： Focused on Main Port of Ulsan

Ulsan port is the hugest industry-oriented port in South Korea. It has the third highest traffic volume of cargo, and also it has the most liquid bulk in Korea. However, on account of thoughtless development, there are other cases like Ulsan port that liquid cargo and general cargo are simultaneously handled. The demurrage ratio takes up to 12.5% of probability on average. In 2010, it has less room at berths for liquid bulk than general cargo and it totally has 107% of processing ratio （throughput）. This indicates that Ulsan port concentrates on liquid cargo more than general cargo depending on the characteristics of the port. This research suggests the effects as alternatives for efficiency and effectivity at both ports, Ulsan port and Pohang port in the case that the general cargo handled in Ulsan port is relocated to Pohang port in terms of the characteristics of products which Pohang port and its hinterland the most focused on. Namely, we estimate volume of relocated volume suitable for relocation in assumption that volume handled in Ulsan port is relocated to Pohang port scenario by scenario, analyze the effects of relocated volume, and suggest alternatives for vitalizing Ulsan port.