Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 2nd World Congress on Petroleum and Refinery Osaka, Japan.

Day 2 :

Keynote Forum

Fabrizio Paolacci

Roma Tre University, Italy

Keynote: A probabilistic risk assessment of process plants under seismic loading

Time : 9:15-10:00

OMICS International Petroleum Congress 2017 International Conference Keynote Speaker Fabrizio Paolacci photo

Fabrizio Paolacci graduated in Civil Engineering in 1992 at the University of Rome "La Sapienza" and completed his PhD in Structural Engineering in 1997. He is currently working as an Assistant Professor in Structural Engineering at University Roma Tre, Department of Engineering. He gained a long standing experience in the management of research projects about experimental assessment of the seismic response of structures. He is currently PI of many European projects. From 2008 to 2013, he assumed the role of Scientific Coordinator of the Laboratory of Testing Materials and Structures of the Department of Structures of the University Roma Tre. He has received a Fellowship provided by CNR (National Research Council) for a research activity of six months at the Department of Civil and Environmental Engineering of University of California at Berkeley from September 1999 to February 2000 as a Visiting Scholar. He is author of more than 100 publications in international peer-reviewed journals and conferences.


The vulnerability of the urbanized territory against Na-Tech events represents a strategic issue because of the general unpreparedness of the countries in predicting effects and consequences in the aftermath of a disaster. Unfortunately, despite the continuous evolution of the knowledge on this matter there is lack of information about possible procedures to predict damage propagation within a process plant and in the surrounding areas and the quantification of the risk under Na-Tech events. The effects of earthquakes on chemical plants may be important, as demonstrated by the recent 2011 Tohoku Earthquake, where many industrial plants suffered to important damages and losses. It is known that the classical Quantitative Risk Assessment (QRA) methods cannot be applied to evaluate consequence in case of earthquakes, because of the presence of multi-damage conditions in more than one equipment and generation of multiple-chains of events and consequences. In literature, several attempts to modify the classic QRA approach have been formalized but without converging toward a unified approach. In this paper, a new tool for the probabilistic risk assessment of process plants under seismic loading is proposed, which is based on Monte Carlo simulations. In particular, starting from the seismic hazard curve of the site, a multi-level approach is proposed, in which the first level is represented by the components seismically damaged, whereas the following levels are treated through a classical consequence analysis, but including propagation of multiple simultaneous and interacting chains of accidents. The procedure has been implemented in the PRIAMUS software, which assumes that the accident may be represented by a sequence of propagation levels. With a series of automatically generated samples of damage propagation scenarios, the risk of the plant can be easily quantified. The application to a petrochemical plant shows the potentiality of the method and envisages possible further evolutions.

OMICS International Petroleum Congress 2017 International Conference Keynote Speaker Tatsushi Nishi  photo

Tatsushi Nishi received the BS degree in Chemical Engineering from Kyoto University, Kyoto, Japan and PhD degree in Process Systems Engineering from Kyoto University, Kyoto, Japan. He became a Research Associate with the Department of Electrical and Electronic Engineering at Okayama University, Okayama, Japan. Currently, he is an Associate Professor with the Department of Mathematical Science for Social Systems, Graduate School of Engineering Science at Osaka University, Japan. His research interests include discrete optimization, discrete event systems, production scheduling, decentralized optimization algorithms, supply chain optimization, multiple mobile robots control and manufacturing systems. He has authored or coauthored more than 100 technical publications. He has won several awards including National Instruments Corporation Young Investigator Award from the 2006 International Symposium on Flexible Automation; 2014, 2015 Outstanding Paper award from the IEEE International Conference on Industrial Engineering and Engineering Management. 


The global logistics strategy is driven by the new economic structure. Oil is considered as one of the most consumed energy resource in Japan. Due to lack of the domestic resource, Japan was the second-largest importer of oil in the world after the United States in 2009. This country is primarily dependent on the Middle East for its oil imports, as roughly 80 percent of Japanese crude oil imports originate in the region up from 70 percent in the mid-1980. In this paper, we propose an optimization approach to solve the international crude oil transportation problem. In order to increase the efficiency, the assignment, the sequence and the loading volume of demands should be optimized simultaneously. In many practical situations, these decisions are executed manually by the negotiation between the human operators based on the contract with suppliers individually. In order to help the decision of human operators, the automatic generation of the practical ship scheduling is highly required to avoid the human errors and increase the efficiency of decision making. In this paper, we present matheuristics application to propose a solution approach to the international crude oil transportation problem based on a real loading planning case in Japanese oil industry. A column generation approach together with partial optimization metaheuristics under special intensification conditions is proposed to solve the problem efficiently. Computational results demonstrate the effectiveness of the proposed method.