The Experts below are selected from a list of 57 Experts worldwide ranked by ideXlab platform
Bing J Zhang - One of the best experts on this subject based on the ideXlab platform.
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operational strategy and planning for raw natural Gas Refining complexes process modeling and global optimization
Aiche Journal, 2017Co-Authors: Bing J Zhang, Qing L Chen, Christodoulos A FloudasAbstract:Optimal operational strategy and planning of a raw natural Gas Refining complex (RNGRC) is very challenging since it involves highly nonlinear processes, complex thermodynamics, blending, and utility systems. In this article, we first propose a superstructure integrating a utility system for the RNGRC, involving multiple Gas feedstocks, and different product specifications. Then, we develop a large-scale nonconvex mixed-integer nonlinear programming (MINLP) optimization model. The model incorporates rigorous process models for input and output relations based on fundamentals of thermodynamics and unit operations and accurate models for utility systems. To reduce the noncovex items in the proposed MINLP model, equivalent reformulation techniques are introduced. Finally, the reformulated nonconvex MINLP model is solved to global optimality using state of the art deterministic global optimization approaches. The computational results demonstrate that a significant profit increase is achieved using the proposed approach compared to that from the real operation. © 2016 American Institute of Chemical Engineers AIChE J, 63: 652–668, 2017
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material stream network modeling retrofit and optimization for raw natural Gas Refining systems
Journal of Cleaner Production, 2017Co-Authors: Bing J Zhang, Qing L Chen, Xiang L LuoAbstract:Abstract The demand for natural Gas is increasing in the energy market because of its lower emissions and sustainable development. This increasing demand for natural Gas promotes the capacity expansion of raw natural Gas Refining systems (RNGRSs), resulting in parallel Refining processes in a RNGRS. Optimizing the material stream network between these Refining processes is very challenging because of the complex thermodynamics, unit operations and utility configurations. An optimization framework is presented for the retrofit of the material stream network between these Refining processes to improve the economic performance. The retrofit framework integrates raw natural Gas supply, Refining processes, utility subsystems and product delivery and is formulated as a mixed-integer nonlinear programming (MINLP) optimization model to obtain an optimal material stream network to increase profit. The model presented here is applied to a Chinese industrial RNGRS and results in an optimal retrofit. A comparison before and after the retrofit demonstrates a significant increase in profit.
Duisembiyeva Akzharkyn - One of the best experts on this subject based on the ideXlab platform.
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Automated security analysis in a SCADA system
2020Co-Authors: Duisembiyeva AkzharkynAbstract:Supervisory control and data acquisition (SCADA) is a computer system for analysing, and monitoring data, as well as, controlling a plant in industries such as power grids, oil, Gas Refining, and water control. SCADA belongs to the category of critical systems that are needed to maintain the infrastructure of cities and households. Therefore, the security aspect of such a system has a significant role. The early SCADA systems were designed with the operation as the primary concern rather than security since they were a monolithic networked system without external access. However, the systems evolved, and SCADA systems were embedded with web technologies for users to monitor the data externally. These changes improved the efficiency of monitoring and productivity; however, this caused a problem of potential cyber-attacks to a SCADA system. One such example was Ukraine's power grid blackout in 2015. Therefore, it is beneficial for the security of a SCADA system to create a threat modeling technique that can understand the critical components of SCADA, discover potential threats, and propose possible mitigation strategies. One issue when creating a threat model is the significant difference of SCADA from traditional Operational Technology (OT) systems. Another significant issue is that SCADA is a highly customisable system, and each SCADA instance can have different components. Therefore, for this work, we implemented a threat modeling language scadaLang, which is specific to the domain of a SCADA system. We started by defining the major assets of a SCADA system, attackers, entry surfaces, and built attacks and defense strategies. Then we developed a threat modeling domain-specific language scadaLang that can create a threat model for a particular instance of SCADA taking the differences in components and connections into account. As a result, we achieved a threat modeling language for SCADA, ensured the reliability of the results by peer-reviewing of an engineer familiar with the domain of the problem, and proposed a Turing test to ensure the validity of the result of scadaLang as the future development of the project
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Automated security analysis of a SCADA system
KTH Skolan för elektroteknik och datavetenskap (EECS), 2020Co-Authors: Duisembiyeva AkzharkynAbstract:Supervisory control and data acquisition (SCADA) is a computer system for analysing, and monitoring data, as well as, controlling a plant in industries such as power grids, oil, Gas Refining, and water control. SCADA belongs to the category of critical systems that are needed to maintain the infrastructure of cities and households. Therefore, the security aspect of such a system has a significant role. The early SCADA systems were designed with the operation as the primary concern rather than security since they were a monolithic networked system without external access. However, the systems evolved, and SCADA systems were embedded with web technologies for users to monitor the data externally. These changes improved the efficiency of monitoring and productivity; however, this caused a problem of potential cyber-attacks to a SCADA system. One such example was Ukraine’s power grid blackout in 2015. Therefore, it is beneficial for the security of a SCADA system to create a threat modeling technique that can understand the critical components of SCADA, discover potential threats, and propose possible mitigation strategies. One issue when creating a threat model is the significant difference of SCADA from traditional Operational Technology (OT) systems. Another significant issue is that SCADA is a highly customisable system, and each SCADA instance can have different components. Therefore, for this work, we implemented a threat modeling language scadaLang, which is specific to the domain of a SCADA system. We started by defining the major assets of a SCADA system, attackers, entry surfaces, and built attacks and defense strategies. Then we developed a threat modeling domain-specific language scadaLang that can create a threat model for a particular instance of SCADA taking the differences in components and connections into account. As a result, we achieved a threat modeling language for SCADA, ensured the reliability of the results by peer-reviewing of an engineer familiar with the domain of the problem, and proposed a Turing test to ensure the validity of the result of scadaLang as the future development of the project.Supervisory control and data acquisition (SCADA) är ett datorsystem för att analysera och monitorera data samt kontrollera anläggningar för industrier såsom energisystem, olja, raffinering av Gas och vatten. SCADA tillhör den kategori av kritiska system som krävs för att bibehålla städer och hushålls infrastruktur. Därför är säkerhetsaspekten av ett sådant system av stor roll. De tidiga SCADA systemen var utformade med funktionen som huvudsaklig oro istället för säkerheten då de var monolitiska nätverkssystem utan extern åtkomst. Systemen utvecklades emellertid och SCADA systemen blev inbyggda med webbteknologier så att användare kan monitorera data externt. De här förändringarna förbättrade effektiviteten av monitorering och produktivitet men skapade problemet med potentiella cyber-attacker mot SCADA systemen. Ett sådant exempel är Ukrainas energy systems elavbrott som skedde 2015. Därför är det fördelaktigt för säkerheten av SCADA systemen att skapa en hotmodelleringsteknik för att bättre förstå de kritiska komponenterna av SCADA, hitta potentiella hot och föreslå potentiella förmildrande strategier. Ett problem för utvecklingen av en hotmodell är den stora skillnaden mellan SCADA från traditionella nätverkssystem inom industri. Ett annat stort problem är att SCADA är ett justerbart system och varje SCADA instans kan ha olika komponenter. Därför utvecklar vi i detta arbete ett språk för hotmodellering scadaLang som är specifikt för domänen SCADA system. Vi började med att definiera de huvudsakliga komponenterna av SCADA system, angriparna, attack ytorna och även bygga attacker samt försvarsstrategier. Sen utvecklade vi ett språk för hotmodelleringen som är domänspecifikt, scadaLang som kan skapa en hotmodell för en specifik instans av SCADA där skillnaderna på komponenter och sammankopplingar tas till hänsyn. Som resultat har vi skapat ett språk för hotmodellering för SCADA,verifierat resultat med hjälp av en ingenjör med domänkännedom och föreslagit ett Turing test för att förbättra verifieringen av resultatet som ett framtida arbete
Xiang L Luo - One of the best experts on this subject based on the ideXlab platform.
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material stream network modeling retrofit and optimization for raw natural Gas Refining systems
Journal of Cleaner Production, 2017Co-Authors: Bing J Zhang, Qing L Chen, Xiang L LuoAbstract:Abstract The demand for natural Gas is increasing in the energy market because of its lower emissions and sustainable development. This increasing demand for natural Gas promotes the capacity expansion of raw natural Gas Refining systems (RNGRSs), resulting in parallel Refining processes in a RNGRS. Optimizing the material stream network between these Refining processes is very challenging because of the complex thermodynamics, unit operations and utility configurations. An optimization framework is presented for the retrofit of the material stream network between these Refining processes to improve the economic performance. The retrofit framework integrates raw natural Gas supply, Refining processes, utility subsystems and product delivery and is formulated as a mixed-integer nonlinear programming (MINLP) optimization model to obtain an optimal material stream network to increase profit. The model presented here is applied to a Chinese industrial RNGRS and results in an optimal retrofit. A comparison before and after the retrofit demonstrates a significant increase in profit.
Qing L Chen - One of the best experts on this subject based on the ideXlab platform.
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operational strategy and planning for raw natural Gas Refining complexes process modeling and global optimization
Aiche Journal, 2017Co-Authors: Bing J Zhang, Qing L Chen, Christodoulos A FloudasAbstract:Optimal operational strategy and planning of a raw natural Gas Refining complex (RNGRC) is very challenging since it involves highly nonlinear processes, complex thermodynamics, blending, and utility systems. In this article, we first propose a superstructure integrating a utility system for the RNGRC, involving multiple Gas feedstocks, and different product specifications. Then, we develop a large-scale nonconvex mixed-integer nonlinear programming (MINLP) optimization model. The model incorporates rigorous process models for input and output relations based on fundamentals of thermodynamics and unit operations and accurate models for utility systems. To reduce the noncovex items in the proposed MINLP model, equivalent reformulation techniques are introduced. Finally, the reformulated nonconvex MINLP model is solved to global optimality using state of the art deterministic global optimization approaches. The computational results demonstrate that a significant profit increase is achieved using the proposed approach compared to that from the real operation. © 2016 American Institute of Chemical Engineers AIChE J, 63: 652–668, 2017
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material stream network modeling retrofit and optimization for raw natural Gas Refining systems
Journal of Cleaner Production, 2017Co-Authors: Bing J Zhang, Qing L Chen, Xiang L LuoAbstract:Abstract The demand for natural Gas is increasing in the energy market because of its lower emissions and sustainable development. This increasing demand for natural Gas promotes the capacity expansion of raw natural Gas Refining systems (RNGRSs), resulting in parallel Refining processes in a RNGRS. Optimizing the material stream network between these Refining processes is very challenging because of the complex thermodynamics, unit operations and utility configurations. An optimization framework is presented for the retrofit of the material stream network between these Refining processes to improve the economic performance. The retrofit framework integrates raw natural Gas supply, Refining processes, utility subsystems and product delivery and is formulated as a mixed-integer nonlinear programming (MINLP) optimization model to obtain an optimal material stream network to increase profit. The model presented here is applied to a Chinese industrial RNGRS and results in an optimal retrofit. A comparison before and after the retrofit demonstrates a significant increase in profit.
Luciano Morselli - One of the best experts on this subject based on the ideXlab platform.
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auto shredder residue recycling mechanical separation and pyrolysis
Waste Management, 2012Co-Authors: Alessandro Santini, Fabrizio Passarini, Ivano Vassura, D P Serrano, Javier Dufour, Luciano MorselliAbstract:Abstract Directive 2000/53/EC sets a goal of 85% material recycling from end-of-life vehicles (ELVs) by the end of 2015. The current ELV recycling rate is around 80%, while the remaining waste is called automotive shredder residue (ASR), or car fluff. In Europe, this is mainly landfilled because it is extremely heterogeneous and often polluted with car fluids. Despite technical difficulties, in the coming years it will be necessary to recover materials from car fluff in order to meet the ELV Directive requirement. This study deals with ASR pretreatment and pyrolysis, and aims to determine whether the ELV material recycling target may be achieved by car fluff mechanical separation followed by pyrolysis with a bench scale reactor. Results show that flotation followed by pyrolysis of the light, organic fraction may be a suitable ASR recycling technique if the oil can be further refined and used as a chemical. Moreover, metals are liberated during thermal cracking and can be easily separated from the pyrolysis char, amounting to roughly 5% in mass. Lastly, pyrolysis can be a good starting point from a “waste-to-chemicals” perspective, but further research should be done with a focus on oil and Gas Refining, in order both to make products suitable for the chemical industry and to render the whole recycling process economically feasible.
