Botond Bertok

Downstream process synthesis for biochemical production of butanol, ethanol, and acetone from grains: generation of optimal and near-optimal flowsheets with conventional operating units.

Manufacturing butanol, ethanol, and acetone through grain fermentation has been attracting increasing research interest. In the production of these chemicals from fermentation, the cost of product recovery constitutes the major portion of the total production cost. Developing cost‐effective flowsheets for the downstream processing is, therefore, crucial to enhancing the economic viability of this manufacturing method. The present work is concerned with the synthesis of such a process that minimizes the cost of the downstream processing. At the outset, a wide variety of processing equipment and unit operations, i.e., operating units, is selected for possible inclusion in the process. Subsequently, the exactly defined superstructure with minimal complexity, termed maximal structure, is constructed from these operating units with the rigorous and highly efficient graph‐theoretic method for process synthesis based on process graphs (P‐graphs). Finally, the optimal and near‐optimal flowsheets in terms of cost are identified.

A graph-theoretic method to identify candidate mechanisms for deriving the rate law of a catalytic reaction

Stoichiometrically, exact candidate pathways or mechanisms for deriving the rate law of a catalytic or complex reaction can be determined through the synthesis of networks of plausible elementary reactions constituting such pathways. A rigorous algorithmic method is proposed for executing this synthesis, which is exceedingly convoluted due to its combinatorial complexity. Such a method for synthesizing networks of reaction pathways follows the general framework of a highly exacting combinatorial method established by us for process-network synthesis. It is based on the unique graph-representation in terms of P-graphs, a set of axioms, and a group of combinatorial algorithms. In the method, the inclusion or exclusion of a step of each elementary reaction in the mechanism of concern hinges on the general combinatorial properties of feasible reaction networks. The decisions are facilitated by solving linear programming problems comprising a set of mass-balance constraints to determine the existence or absence of any feasible solution. The search is accelerated further by exploiting the inferences of preceding decisions, thereby eliminating redundancy. As a result, all feasible independent reaction networks, i.e. pathways, are generated only once; the pathways violating any first principle of either stoichiometry or thermodynamics are eliminated. The method is also capable of generating those combinations of independent pathways directly, which are not microscopically reversible. The efficiency and efficacy of the method are demonstrated with the identification of the feasible mechanisms of ammonia synthesis involving as many as 14 known elementary reactions.

Graph-theoretical identification of pathways for biochemical reactions

A rigorous method for identifying biochemical reaction or metabolic pathways through its systematic synthesis has been established. The current method for synthesizing networks of metabolic pathways follows the general framework of a highly exacting combinatorial method. The method is capable of generating not only all combinatorially independent, feasible reaction networks only once, but also those combinations of independent pathways. A case study involving the conversion of glucose to pyruvate with 14 elementary reactions illustrates the efficiency and efficacy of the method. All the results have been obtained with a PC (Pentium-III 550 MHz, 256 MB RAM) within 1 s.

Comparative Life Cycle Analysis of Different Lighting Devices

In the modern era, tremendous technological and sustainable development has forced the societies to adopt modern energy efficient lighting devices instead of old fashioned less efficient incandescent lamps. The examples of such new lamps compact fluorescent lamps (CFLs) and Light Emitting Diode (LED) lamps. These devices can provide similar light output at the expense of only 20 % electricity consumption in comparison to incandescent lamps due to less energy lost as heat during luminance phenomenon. CFLs convert about 45 % energy into visible light, while incandescent lamp converts only 10 % (Tosenstock, 2007). The ecological footprint evaluation for street lighting network in Veszprem County, Hungary has been carried out utilising Sustainable Process Index (SPI) methodology (Narodoslawsky and Krotscheck, 1995). The analysis was carried out considering three different light bulbs i.e. conventional or old fashioned less energy efficient incandescent lamps and high tech more energy efficient CFLs and LED lamps. The analysis results reveal that there is a potential to decrease environmental impacts by 2 to 4 times by changing lamps from conventional incandescent to CFL and LEDs. These results are in coherence with the ecological assessment study conducted by the Department of Energy (DOE, 2012) for replacement of incandescent lamps with more efficient CFLs and LED lamps.

Planning evacuation routes with the P-graph framework

The P-graph framework is proven to be highly effective in solving Process Network Synthesis. In the present work, the P-graph framework has been adopted for solving the routing and scheduling of evacuees, facing a life-threatening situation. First the building evacuation problem is represented by means of a P-graph model, which is then transformed into a time-expanded process network synthesis (PNST) problem that can be algorithmically handled by the P-graph framework. In the proposed method, each location in the building and their passages are given by a set of attributes to be taken in the evacuation route planning. In addition to the globally optimal solution of the building evacuation problem, the P-graph framework provides the n-best suboptimal solutions, when computational possible. The viability of the proposed model is illustrated by an example.

Optimal design of supply chains by P-graph framework under uncertainties

The utilization of renewable resources poses new challenges to process design. Consumption of renewable raw materials, or feedstock, often encounter limitations and uncertainties that are foreign to the design of processes based on fossil fuels whose availability is presumably uninterruptible. The algorithms and software of the graphtheoretic method based on process graphs (P-graphs) are elaborated for generating optimal and near-optimal supply networks for manufacturing a set of products at certain production levels with given reliabilities. Apparently, the sole currently available approach capable of rigorously and efficiently executing optimal process-network synthesis is that based on the P-graph framework. The approach leads to an algorithmically and mathematically proven solution for all steps involved. Such steps comprise superstructure generation, construction of the mathematical model, optimization, and the solution interpretation. The proposed method is illustrated with an example involving the utilization of renewable feedstock, namely agricultural products, whose uninterrupted availability tends to be uncertain.

Optimization software for solving vehicle assignment problems to minimize cost and environmental impact of transportation

Please cite this article as: Barany M., Bertok B., Kovacs Z., Friedler F. and Fan L. T., (2010), Optimization software for solving vehicle assignment problems to minimize costs and environmental impacts of transportation, Chemical Engineering Transactions, 21, 499504 DOI: 10.3303/CET1021084 Optimization software for solving vehicle assignment problems to minimize cost and environmental impact of transportation

Graph-theoretic approach for identifying catalytic or metabolic pathways

Abstract Stoichiometrically exact and potentially feasible catalytic or metabolic pathways can be found by synthesizing the networks of plausible elementary or metabolic reactions constituting such pathways, respectively. The current contribution presents a mathematically exact algorithmic approach for carrying out the necessary synthesis, which is profoundly complex combinatorially. The approach is based on the unique graph‐representation in terms of P‐graphs (process graphs), a set of axioms, and a group of combinatorial algorithms. The inclusion or exclusion of a step of each elementary or metabolic reaction in the pathway of interest hinges on the general combinatorial properties of feasible reaction networks. At the outset, a brief overview is given of successful applications to date, followed by an outline of the methodology, on which the approach is based. The approach is illustrated by implementing it to three new examples comprising two catalytic reactions, catalytic combustion of hydrogen and reduction of nitrogen oxide, and one metabolic reaction, involved in the production of ethanol by yeast. The efficacy of the approach is discussed in light of the results obtained from these examples. Finally, a brief discourse is given of our current and future efforts.

Systematic generation of the optimal and alternative flowsheets for azeotropic-distillation systems

Publisher Summary A systematic and rigorous method for synthesizing azeotropic-distillation systems, which is of utmost practical importance, is yet to be fully established. The available methods are based mainly on heuristics and graphical procedures. In synthesizing a simple separation network, the structure of the optimal solution may be counterintuitive. For synthesizing a complex network structure necessary for an azeotropic-distillation system, therefore, the probability is very high that the solution generated would be far from the optimal one unless the method is systematic and rigorous. The proposed method is capable of algorithmically synthesizing optimal, near optimal, and other feasible structures for an azeotropic-distillation system from a set of candidate operating units. The residue curve map of the system is transformed to a unique multidimensional representation to facilitate the systematic partitioning of the feasible regions into lumped materials bounded by the thermodynamic boundaries and pinches. The process graph (P-graph) representation of these operating units serves as a basis for the synthesis procedure, including combinatorial algorithms. The method is equally applicable to various other complex processes with phase transition and/or phase separation with any number of components. Crystallization, extraction, reactive distillation, and their combinations are examples of such processes. A case study is given in which ethanol is separated from its aqueous solution with toluene as the entrainer.

Waste to energy for small cities: Economics versus carbon footprint

The main activities in Waste to Energy processing include waste generation, collection, separation, transportation, conversion, energy distribution, and ultimate waste disposal. Waste to Energy carries a trade-off between energy generation and the energy spent on collection, transport and treatment. Major performance indicators are cost, Waste Energy Potential Utilisation, and Carbon Footprint. This presentation analyses the potential of small cities to substitute part of their fossil fuels use by energy derived from Municipal Solid Waste. Several factors are considered in the study. The impact of waste logistics and the losses from energy distribution systems – natural gas pipeline and electricity grid are the most significant ones on the side of the supply chain. Further, the waste processing part, including the energy recovery from the waste involves the evaluation of a number of technologies linked with each other to form a distributed integrated processing system. In this study, the options for converting waste into thermal energy include (a) biogas digestion and burning and (b) waste incineration with off-gas cleaning. It is also possible to use the biogas in advanced cogeneration systems based on engines or fuel cells. The proposed procedure takes all these options into account and derives the optimal processing configuration from the waste generation to energy supply and residual waste deposition to landfill.