XIAO Wu, ZHANG Yi, LÜ Junfeng, et al. Progress of research and application of P-graph theory in process network synthesis[J]. CIESC Journal, 2016, 67(10): 4029-4039.
DOI:
XIAO Wu, ZHANG Yi, LÜ Junfeng, et al. Progress of research and application of P-graph theory in process network synthesis[J]. CIESC Journal, 2016, 67(10): 4029-4039.DOI: 10.11949/j.issn.0438-1157.20160154.
Progress of research and application of P-graph theory in process network synthesis
complexifying and unifying in modern petro-chemical systems
the combined complexity among streams of mass
energy and information as well as among unit operations keeps increasing exponentially. P-graph theory has found widespread applications by generation of rigorous superstructures as a result of axiom constraints which may reduce creation of redundant structures. This review on P-graph theory began with the mathematical definition
fundamental axioms
solution algorithms and workflow
and a case study to show the modeling framework and graphic representation. A literature study of past 20 years' publications systemically summarized application of P-graph theory in traditional process system engineering of separation network synthesis
reaction path synthesis and heat exchange synthesis
and recent expansion in new areas of process technology selection
supply chain and process optimization. The advantages and disadvantages of P-graph theory and mathematical programming were compared
and improving ideas were proposed to solve nonlinear problems with P-graph theory. The prospective research and application of P-graph theory were forecasted
including multi-objective optimization in consideration of economic and environmental factors
effective solution of large complex nonlinear programming problems by the combination of both P-graph and mathematical programming
Optimization method of coal-based cooling, heating and power co-generation
Damping optimization method for heat exchange network synthesis
Research progress on crude oil operation optimization
Application of adaptive algorithm of online reduced KECA in fault detection
Multi factor production cost modeling method for intelligent manufacturing
Related Author
DUAN Wenting
ZHANG Qiao
Weiwei LIU
Guomin CUI
Lu ZHANG
Yuan XIAO
Qiguo YANG
Guanhua ZHANG
Related Institution
School of Chemical Engineering and Technology, Xi’an Jiaotong University
School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering
Department of Automation, College of Information Science and Engineering, China University of Petroleum
College of Information Engineering, Shenyang University of Chemical Technology
Institute of Cyber-Systems and Control, Zhejiang University