Ferenc Friedler

University of Pannonia, Veszprém, Gyulafirátót, Veszprém, Hungary

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Publications (110)97.47 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: A new modeling technique is presented here for handling multi-period operations in the process-network synthesis (PNS) problem by the P-graph (process graph) framework. The P-graph is both a representation and a methodology. It has been demonstrated by several applications that P-graphs are useful modeling tools in various areas. The unambiguous representation of processes by P-graphs and the availability of the axioms defining the combinatorially feasible structures have facilitated the development of efficient algorithms to determine the maximal structure, the solution structures, and the optimal structure of the network for the process of interest. Until now, it was implicitly assumed that single-period operations prevail. This implicitly means that the operating conditions and the load remain unchanged throughout its operation, i.e., steady-state operation is maintained. This assumption is usually true for the chemical industry, but it may be false in other areas where seasonal effects are important such as agriculture. The current work proposes the use the P-graph framework with multi-period operation wherein the load of operating units may vary from period to period to accommodate the changing demands under the premise that the operating conditions remain steady within each period. Subsequently, a modeling technique is proposed to represent operating units in the multi-period operation. The basic concept is to separately represent the physical body of operating units and the operations themselves in each period. The investment and the operating cost must also be separated for operating units, and we have to make sure that the maximum capacity of the multi-period unit is not violated. Surprisingly, no need to dramatically change or augment the basic structure of the P-graph methodology, e.g. with a new type of multi-period unit, but the already available constituents are adequate. This also demonstrates the generality of the framework. A simple example of evaluating the investment in a single equipment unit applicable is presented. This is followed by a more complex case study on optimal planning of the energy production system appropriate for an agricultural region in Central Europe. Together both illustrate the new modeling technique. Energy production as well as available feedstock vary with the seasons raising a very interesting design problem. Acknowledgement: we acknowledge the support of the U.S. EPA, Office of Research and Development, and the Hungarian State and the European Union under the TAMOP-4.2.2.A-11/1/ KONV-2012-0072.
    14 AIChE Annual Meeting; 11/2014
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    ABSTRACT: Glycerol is a waste by-product from the transesterification involved in biodiesel synthesis. Converting it to high value-added products can ease its over-supply. This can be accomplished by reforming glycerol into high purity hydrogen for which nickel-based catalysts are most often deployed. Nevertheless, the coexistence of both acidic and basic active sites renders it difficult to gain in-depth understanding of its reaction pathways. Exhaustive identification of feasible pathways allows us to design a Ni catalyst, thereby facilitating the practical implementation of glycerol steam reforming. The current contribution explores nineteen reaction steps, including the most abundant intermediates derived from glycerol, based on a dual-active site mechanism adapted from Cheng et al. (2011). Six independent pathways and twenty-one acyclic pathways have been generated through a graph-theoretic method based on P-graphs within one second on a PC (Pentium 4, CPU 3.06 GHz, and 1 GB RAM). This makes it possible to establish a kinetic model via analysis based on the Langmuir-Hinshelwood formalism, thereby providing a platform for rational catalyst design. Reference: K.C. Cheng, Y. F. Say, and A. A. Adesina, Catalysis Today 178 (2011) 25-33.
    13 AIChE Annual Meeting; 11/2013
  • Ferenc Friedler, Ka Ming Ng
    Current Opinion in Chemical Engineering. 11/2013;
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    ABSTRACT: Methodology and computer aid are proposed for designing sustainable supply chains in terms of sustainability metrics by utilizing the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the creators of the P-graph framework at the University of Pannonia. The integration of supply chain design and sustainability is the main focus of this collaboration. A recent extension to the P-graph framework provides a mathematically rigorous procedure for synthesizing the complete set of Pareto optimal networks subject to multiple objectives and constraints, which include profitability and sustainability in the proposed methodology. Specifically, to evaluate the sustainability of a given process under construction including its supply chain, sustainability metrics are incorporated into the design procedure. The proposed methodology and the software are demonstrated with the optimal design of a supply chain for providing heat and electric power to an agricultural region with relatively limited land area where agricultural wastes can potentially be recovered as renewable resources. Possible sources of heat and electricity included electricity from the Hungarian grid, and heat and electricity generated from natural gas, corn, corn silage, grass silage, or wood or some combination of these sources. Each supply chain was ranked according to cost, and assessed environmental impacts using the ecological footprint (representing land use burden), and emergy (representing energy resource burden). Decisively feasible supply chains were found with cost variations of +2% to -17% compared to “business as usual” scenarios, i.e., using only natural gas and electricity from the Hungarian grid. For these supply chains, the sustainability profile as represented by the ecological footprint varied from +8% to -78%, and the emergy results ranged from -54% to -93%. Most importantly, it appeared feasibly possible to design supply chains for heat and electricity generation which were both cheaper and more sustainable than the supply chain currently in use.
    2013 AIChE Spring National Meeting; 05/2013
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    ABSTRACT: The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by utilizing the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the creators of the P-graph framework at the University of Pannonia. The integration of supply chain design and sustainability is the main focus of this collaboration. The P-graph framework provides a mathematically rigorous procedure for synthesizing optimal and alternative suboptimal networks subject to multiple objectives and constraints, which include profitability and sustainability in the proposed methodology. Specifically, to evaluate the sustainability of a given process under construction including its supply chain, sustainability metrics are incorporated into the design procedure. The proposed methodology is demonstrated with the optimal design of a supply chain for providing heat and electric power to an agricultural region with relatively limited land area where agricultural wastes can potentially be recovered as renewable resources. The objective functions for optimization comprise the profit and the ecological footprint. The results of the study indicate that, compared to using electricity from the grid and/or natural gas, using renewable energy resources can yield substantial cost reductions of up to 5%, as well as significant ecological footprint reductions of up to 77%. It may, therefore, be possible to design more sustainable supply chains that are both cost-effective and less environmentally damaging.
    Industrial & Engineering Chemistry Research. 11/2012; 52(1):266–274.
  • Mate Barany, Botond Bertok, L T Fan, Ferenc Friedler
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    ABSTRACT: The determination of reaction pathways is one of the most important functions that should be performed in exploring the kinetics of catalyzed chemical reactions or biochemical reactions, the latter being generally catalyzed by enzymes. It is proven that the terms, "type-I extreme pathway" and "structurally minimal pathway", both introduced to characterize the kinetics of a catalyzed reaction are equivalent. These two terms are based on two distinct methodologies, one mainly rooted in convex analysis and the other in graph theory. The equivalence promises further even more effective methods for reaction-pathway identification by synergistic integration of existing ones.
    Bioprocess and Biosystems Engineering 11/2012; · 1.87 Impact Factor
  • Ferenc Friedler, Ka Ming Ng
    Current Opinion in Chemical Engineering. 11/2012; 1(4):418–420.
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    ABSTRACT: A collaboration consisting of the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the founders of the P-graph framework at the University of Pannoniahas developed a methodology for designing sustainable supply chains based on an optimization using the p-graph framework constrained by integrated sustainability indicators and engineering costs. The result was a powerful methodology for designing cost-effective and environmentally sustainable supply chains. We illustrated the methodology with a prototype supply chain designed to produce heat and electricity for a generic district in Hungary. Possible sources of heat and electricity included electricity from the Hungarian grid, and heat and electricity generated from natural gas, corn, corn silage, grass silage, or wood or some combination of these sources. Twenty-one different supply chains, each capable of producing 18 TJ per year of heat and 7.2 TJ per year of electricity were found. Each supply chain was ranked according to cost, and assessed environmental impacts using the ecological footprint (representing land use burden), and emergy (representing energy resource burden). Decisively feasible supply chains were found with cost variations of +2% to -17% compared to “business as usual” scenarios i.e. using only natural gas and electricity from the Hungarian grid. For these supply chains, the sustainability profile as represented by the ecological footprint varied from +8% to -78%, and the emergy results ranged from -54% to -93%. Both comparisons were done in contrast to the conventional natural gas/electricity from the Hungarian grid. Most importantly, it appeared feasibly possible to design supply chains for heat and electricity generation which were both cheaper and more sustainable than the supply chain currently in use.
    12 AIChE Annual Meeting; 10/2012
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    ABSTRACT: The formation of HBr has long been widely regarded as proceeding via a chain-reaction pathway comprising the initiation step, activated catalytically, thermally, electrically, photonically or collisionally, the propagation steps, and termination step. In recent years, however, it has been recognized that this chain-reaction pathway or mechanism does not give rise to stoichiometrically closure, thereby violating the axiomatic laws of mass conservation and stoichiometric constraint of chemical reactions. Proposed herein is a novel chain-reaction mechanism involving the activation of hydrogen in addition to that of bromine to initiate the chain. By resorting to the mathematically rigorous, graph-theoretic algorithmic method based on a unique bipartite graph, P-graph (process graph), two stoichiometrically feasible independent pathways and one acyclic combined pathway have been obtained from this novel chain-reaction mechanism. The algorithmic method deployed is based on the two sets of axioms, one being the set of 6 axioms of feasible reaction pathways and the other being the set of 7 axioms of combinatorially feasible networks, and graph representation of reaction steps in terms of P-graphs.
    12 AIChE Annual Meeting; 10/2012
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    ABSTRACT: The current work reveals a methodology that provides an adequate basis to portray and model supply chains mathematically and formally as well as to synthesize optimal and alternative supply scenarios algorithmically while taking into account structural redundancy. The proposed methodology is based on the combinatorial foundations of algorithmic process synthesis or more specifically on the P-graph framework. A biodiesel supply network involving blending and transportation serves as an illustrative example. A novel algorithm generates the mathematical model and alternative solutions to increase reliability of supply scenarios. Major steps of the generation are the structure generation and estimation of reliability of a supply scenario.
    Industrial & Engineering Chemistry Research. 10/2012; 52(1):181–186.
  • Botond Bertok, Mate Barany, Ferenc Friedler
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    ABSTRACT: The primary aim of process-network synthesis, or PNS in short, is to determine the best process network achieving a desired goal, e.g., producing a set of desired products or satisfy demands. PNS has a long history, and numerous methods for executing it are available. Its acceleratedly increasing importance can be attributed to the need to respond to the rapid emergence of new technologies and fast changes in the economic environment. It is highly desirable that any corporation be able to ascertain if a new technology is viable for its business as well as to assess if its current technology remains sustainable in the changing environment. Herein, a novel method and software for PNS are proposed for generating, optimizing, and analyzing alternative process designs at the conceptual level. The method is illustrated by synthesizing alternative process designs with different network structures for the production of butanol, ethanol, and acetone from grains. Furthermore, the sustainability of the resultant process designs is analyzed. This is executed by varying the payout period and the production rate, i.e., load.
    Industrial & Engineering Chemistry Research. 10/2012; 52(1):166–171.
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    ABSTRACT: An effective strategy comprising two phases is proposed to determine the thermodynamically dominant pathways in a metabolic network of a given phenotype, involving several metabolic reactions. In the first phase, stoichiometrically feasible metabolic pathways are exhaustively identified through the flux balance analysis and the graph-theoretic method based on P-graphs. In the second phase, thermodynamically dominant pathways are selected from these stoichiometrically feasible metabolic pathways on the basis of the Gibbs free energy change of reaction. The proposed strategy’s efficacy is demonstrated by applying it to two E. coli models: one is for maximal acetate and ethanol production, and the other is for maximalpoly(3-hydroxybutyrate) production.
    Industrial & Engineering Chemistry Research. 07/2012; 52(1):222–229.
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    ABSTRACT: Hitherto, no attempt has been made to identify exhaustively feasible pathways for any mechanism of a given reaction catalyzed by a catalyst with multiactive sites. Two stoichiometically exact and definitely feasible mechanisms have been proposed to date for the hydrogenation of ethylene to ethane on biactive-site or triactive-site platinum catalysts. One comprises seven elementary reactions, and the other comprises eight elementary reactions; nevertheless, both mechanisms involve competitive as well as noncompetitive adsorption. Any of these mechanisms gives rise to a multitude of feasible catalytic pathways. The present work exhaustively identifies such feasible pathways by resorting to the inordinately efficient graph-theoretic algorithm based on P-graphs (process graphs). The efficacy of this algorithm has been amply demonstrated by successfully deploying it for several catalysts with single-active sites, but has never been deployed for catalysts with multiactive sites as in the current work. The availability of exhaustively identified feasible pathways for both mechanisms renders it possible to stipulate that the hydrogenation of chemisorbed chemisorbed C2H5 is the rate-controlling step: This step is contained in either mechanism.
    Industrial & Engineering Chemistry Research 01/2012; 51:2548-2552. · 2.24 Impact Factor
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    ABSTRACT: A reaction-pathway identification procedure has two distinct phases. The first phase enumerates exhaustively the feasible candidate pathways, and the second phase identifies the ultimate feasible pathway or pathways among them. Probably the most efficient way to execute the first phase is to algorithmically generate the networks of feasible candidate pathways from a predefined set of plausible elementary reactions. The available algorithmic methods for this purpose can be roughly grouped into two major classes, one based on graph theory and the other on linear algebra. Both classes of methods consider any chemical reaction system as a network of elementary reactions, thereby implying that the two classes are interrelated. This paper studies the linear algebraic concept termed direct mechanism introduced in the mid-eighties and the graph-theoretical concept termed structurally minimal pathway introduced two decades later. Herein, it has been formally proven that the two concepts are equivalent.
    Journal of Mathematical Chemistry 01/2012; 50(5). · 1.23 Impact Factor
  • van Heckl, Heriberto Cabezas, Ferenc Friedler
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    ABSTRACT: The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by resorting to the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the founders of the P-graph framework. U.S. EPA/ORD has substantial creditable experience with the development of indicators and metrics for sustainability, while the P-graph framework is deemed to be highly effective for algorithmic design of process networks including supply chains. The integration of supply chain design and sustainability is the main focus of the collaboration. The P-graph framework provides a mathematically rigorous procedure for synthesizing optimal and alternative suboptimal networks subject to multiple objectives and constraints, which include profitability and sustainability in the proposed methodology. Specifically, to evaluate the sustainability of a given process under construction including its supply chain, sustainability metrics are incorporated into the design procedure. The proposed methodology is demonstrated with the optimal design of a supply chain for the infrastructure providing heat and electric power to an agricultural region with relatively limited area where agricultural wastes can potentially be recovered as renewable resources. The objective functions for optimization comprise the profit, ecological footprint, exergy dissipation, green net regional product, and ratio between renewable and total emergies.
    2011 AIChE Annual Meeting; 10/2011
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    M At, Hegyh Ati, Ferenc Friedler
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    ABSTRACT: Methods for solving batch process scheduling problems have gone through a vast development in the last 2 decades. Most of the published approaches are based on a mixed integer programming formulation. Since the difficulty of scheduling is originated from its combinatorial nature, graphs and combinatorial algorithms are more adequate to represent and solve the problem. Although, combinatorial algorithms and data structures have an enormous literature, these algorithms can not be directly applied to scheduling and further elaboration is needed. In the present work, the combinatorial nature of batch scheduling problems is analyzed. Several combinatorial algorithms are listed that can be considered for the scheduling of batch processes. Their proper adaptation is illustrated via the S-graph framework, in which the main emphasis lies on the combinatorial tools. Furthermore, Place Petri Nets and Timed Automata are also briefly described. An S-graph algorithm has been extensively compared with well-known MILP formulations. ' COMBINATORIAL NATURE OF BATCH PROCESS SCHEDULING Scheduling is a key problem in the operation of batch plants. The industry generates a wide range of batch scheduling problems, where the goal in general is to allocate the tasks of the process to the available equipment units in the most favorable way. 1,2 An ordinary batch scheduling problem is given by the master recipe of the process, the objective, and the intermediate storage policy. The most common objectives are the minimization of the whole processing time, i.e., makespan, or the maximization of the throughput or profit over a fixed time horizon. According to different problems, the storage policy can vary between unlimited intermediate storage (UIS), finite intermediate storage (FIS), common intermediate storage (CIS), nonintermediate storage (NIS), and zero-wait (ZW). 3,4 Problem specification may include further parameters, e.g., transfer times, changeover times, or variable processing times. 5 The recipe defines the set of products to be produced, the network of tasks to produce the desired products, the available equipment units, processing times, stoi-chiometric data, etc. In the case of a complex recipe, i.e., when the process does not have sequential characteristics, the unambiguous representation of the network of the tasks is not evident. 6 In batch process scheduling, mostly directed graphs, e.g., State-Task-Net-work (STN), 7 Resource-Task-Network (RTN), 8 State-Sequence-Network (SSN), 9 S-graph, 10 Timed Place Petri Net (TPPN), 11 or Priced Timed Automata (PTA) 12 are applied for this purpose. Despite the wide range of available graph representations, most of the approaches consider them only as a graphical representation and not as the model for the optimization. The combinatorial nature of batch scheduling problems derives from the two main decisions to be made during the optimization process: (i) which processing unit is assigned to a task (if more than one is available) and (ii) what is the order of the tasks to be performed in an equipment unit. Moreover, if the objective is to maximize the throughput, the optimal number of batches has to be also identified, which is an additional computational issue. Even though the major decisions are made in discrete space, the problems may involve decisions on continuous variables, e.g., batch sizing, that can usually be handled with an LP model, which requires much less computational effort compared to the combi-natorial part of the problem.
    Eng. Chem. Res. 05/2011; 50:5169-5174.
  • Máté Hegyháti, Ferenc Friedler
    [Show abstract] [Hide abstract]
    ABSTRACT: Methods for solving batch process scheduling problems have gone through a vast development in the last 2 decades. Most of the published approaches are based on a mixed integer programming formulation. Since the difficulty of scheduling is originated from its combinatorial nature, graphs and combinatorial algorithms are more adequate to represent and solve the problem. Although, combinatorial algorithms and data structures have an enormous literature, these algorithms can not be directly applied to scheduling and further elaboration is needed. In the present work, the combinatorial nature of batch scheduling problems is analyzed. Several combinatorial algorithms are listed that can be considered for the scheduling of batch processes. Their proper adaptation is illustrated via the S-graph framework, in which the main emphasis lies on the combinatorial tools. Furthermore, Place Petri Nets and Timed Automata are also briefly described. An S-graph algorithm has been extensively compared with well-known MILP formulations.
    Industrial & Engineering Chemistry Research. 04/2011; 50(9):5169–5174.
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    ABSTRACT: Large amounts of thermal energy are transferred between fluids for heating or cooling in industry as well as in the residential and service sectors. Typical examples are crude oil preheating, ethylene plants, pulp and paper plants, breweries, plants with exothermic and endothermic reactions, space heating, and cooling or refrigeration of food and beverages. Heat exchangers frequently operate under varying conditions. Their appropriate use in flexible heat exchanger networks as well as maintenance/reliability related calculations requires adequate models for estimating their dynamic behaviour. Cell-based dynamic models are very often used to represent heat exchangers with varying arrangements. The current paper describes a direct method and a visualisation technique for determining the number of the modelling cells and their size.
    Computers & Chemical Engineering. 01/2011; 35:943-948.
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    Petar Sabev Varbanov, Ferenc Friedler
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    ABSTRACT: Fuel cells (FCs) are important for building combined energy systems due to their high efficiency. Molten Carbonate FCs (MCFC) and Solid Oxide FCs (SOFC) have been identified as best candidates for FC Combined Cycles (FCCC). This paper presents a procedure for evaluating the trends in emission levels and economics of FCCC based energy conversion systems, utilising biomass and/or fossil fuels. This involves significant combinatorial complexity, efficiently handled by the P-graph algorithms. A procedure for the synthesis of cost-optimal FCCC configurations is developed, accounting for the carbon footprint of the technology and fuel options. The results show that such systems employing renewables can be viable for wide range of economic conditions, due to the high energy efficiency of the FC-based systems.
    Applied Thermal Engineering 01/2011; 28(16). · 2.13 Impact Factor
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    B. Bertok, R. Adonyi, F. Friedler, L. T. Fan
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    ABSTRACT: Scheduling plays a key role in batch process operation; it has a major effect on the process' performance. Available methods for determining the optimal schedule are primarily based on either MILP/MINLP formulation in conjunction with mathematical programming (Floudas and Lin, 2004; Vaklieva-Bancheva and Kirilova, 2010) or graph representation in conjunction with combinatorial algorithms (Sanmarti et al., 2002).The current work comprises three major contributions. First, an algorithm has been crafted to generate a superstructure for a scheduling problem. The problem is defined in the form of an S-graph representing the recipe. The superstructure contains exclusively every step potentially performed by any of the functional or operating facilities or equipment units capable of completing at least one task to be scheduled. These steps involve executions of tasks and changeovers from one task to another. Second, an MILP formulation is elaborated on the basis of the superstructure, which guarantees the optimal solution of the scheduling problem. Third, a relaxation of the MILP model is incorporated into the S-graph algorithms to support the selection of subproblems and decision variables in the branch-and-bound procedure.
    01/2011;

Publication Stats

721 Citations
97.47 Total Impact Points

Institutions

  • 1995–2014
    • University of Pannonia, Veszprém
      • • Department of Computer Science and Systems Technology
      • • Faculty of Information Technology
      Gyulafirátót, Veszprém, Hungary
  • 2012
    • Lands Department of The Government of the Hong Kong Special Administrative Region
      Hong Kong, Hong Kong
  • 2010
    • Yuan Ze University
      • Department of Chemical Engineering & Materials Science
      Taoyuan City, Taiwan, Taiwan
  • 1992–2010
    • Kansas State University
      • Department of Chemical Engineering
      Manhattan, KS, United States
  • 2006
    • University of Pretoria
      • Department of Chemical Engineering
      Pretoria, Gauteng, South Africa
  • 2005
    • Korea Advanced Institute of Science and Technology
      • Metabolic and Biomolecular Engineering National Research Laboratory
      Seoul, Seoul, South Korea
  • 2002–2003
    • Polytechnic University of Catalonia
      • Department of Chemical Engineering (EQ)
      Barcelona, Catalonia, Spain
  • 1993–1995
    • Hungarian Academy of Sciences
      Budapeŝto, Budapest, Hungary