Projects

All research projects in the KT Consortium are conducted in close collaboration with the industrial company members of the consortium.

Current projects

Objective

In close synergy and collaboration with CERE we are working on a number of projects, aiming at a further development and understanding of advanced thermodynamic models like CPA and PC-SAFT for various applications (see under description of the project).

Many of these projects are of "exploratory" character. Upon completion and/or/if/when results are in form suitable for practical engineering applications, they may be included in ICAS, if appropriate.

Background

This is a generic project (actually a list of diverse projects under the same headline), in close collaboration and synergy with CERE.

The project

Applications we consider for CPA and PC-SAFT:

  • mixtures with hydrogen bonding compounds like water and alcohols/glycols
    http://www.cere.dtu.dk/Research-and-Projects/Research-Projects/CHIGP
  • electrolytes
    http://www.cere.dtu.dk/Research-and-Projects/PhD-Projects/Archive--PhD/Development-of-an-Electrolyte-CPA-Equation-of-state-for-App-in-the-Petroleum-and-Chemical-Industries
    http://www.cere.dtu.dk/research-and-projects/phd-projects/development-of-the-electrolyte-cpa-equation-of-state
  • asphaltenes
    http://www.cere.dtu.dk/research-and-projects/phd-projects/modelling-of-asphaltene-systems-with-association-models
  • surface and interfacial tensions
    http://www.cere.dtu.dk/research-and-projects/phd-projects/phase-behavior-of-inhomogeneous-fluids
  • chemicals of relevance to CO2 capture
    http://www.cere.dtu.dk/research-and-projects/phd-projects/thermodynamic-modeling-of-ionic-liquid-containing-co2-gas-hydrate-formation-systems
  • simulation of biofuel processes
    http://www.cere.dtu.dk/research-and-projects/phd-projects/thermodynamics-design-simulation-and-benchmarking-of-biofuel-processes
  • critical point investigations
    http://www.cere.dtu.dk/research-and-projects/phd-projects/application-of-the-cubic-plus-association-equation-of-state-in-reservoir-simulation

Contact.

Georgios Kontogeorgis

Georgios Kontogeorgis Professor Department of Chemical and Biochemical Engineering Phone: +45 45252859

Contact

Xiaodong Liang

Xiaodong Liang Associate Professor Department of Chemical and Biochemical Engineering Phone: +45 45252877

Objective

The project’s overall target is to arrive at a fundamental understanding of electrolyte thermodynamics and thus enable the engineering of a new generation of useful, physically sound models for electrolyte solutions.

These models should be general and applicable to a very wide range of conditions so that they can be potentially used for a wide range of applications.

Electrolyte solutions are present almost anywhere and find numerous applications in physical sciences including chemistry, geology, material science, medicine, biochemistry and physiology as well as in many engineering fields especially chemical & biochemical, electrical and petroleum engineering.

In all these applications the thermodynamics plays a crucial role over wide ranges of temperature, pressure and composition. As the subject is important, a relatively large body of knowledge has been accumulated with lots of data and models.

However, disappointingly the state-of-the art thermodynamic models used today in engineering practice are semi-empirical and require numerous experimental data. They lack generality and have not enhanced our understanding of electrolyte thermodynamics.

Going beyond the current state of the art, we will create the scientific foundation for studying, at their extremes, both “primitive” and “non-primitive” approaches for electrolyte solutions and identify strengths and limitations.

The ambition is to make new advances to clarify major questions and misunderstandings in electrolyte thermodynamics, some remaining for over 100 years, which currently prevent real progress from being made, and create a new paradigm which will ultimately pave the way for the development of new engineering models for electrolyte solutions.

This is a risky, ambitious and crucial task, but a successful completion will have significant benefits in many industrial sectors as well as in environmental studies and biotechnology.
The project is founded on a well-structured connection between fundamental understanding and macroscopic modeling.

At a practical level, the ambition is to yield a roadmap of what is possible and what not and when for engineering applications in electrolyte solutions and also, at a more fundamental level, to make new advances which will clarify some of the major confusions and misunderstandings in electrolyte thermodynamics which currently prevent real progress from taking place.

External collaborators:

Professor Athanassios Z. Panagiotopoulos (University of Princeton, USA)
Professor Ioannis Economou (NCSR “Demokritos”, Greece)
Professor Jean-Charles de Hemptinne (IFP Energies Nouvelles, France)

Contact.

Georgios Kontogeorgis

Georgios Kontogeorgis Professor Department of Chemical and Biochemical Engineering Phone: +45 45252859

Contact

Xiaodong Liang

Xiaodong Liang Associate Professor Department of Chemical and Biochemical Engineering Phone: +45 45252877

Contact

Nicolas von Solms

Nicolas von Solms Professor Department of Chemical and Biochemical Engineering Phone: +45 45252867

Contact

Kaj Thomsen

Kaj Thomsen Department of Chemical and Biochemical Engineering

Ionic liquid (IL) database and property models update IL-based tools development (collaborate with Guoliang) IL-based aqueous biphasic system (ABS) study and design

Properties of ILs are required for the design of products and processes involving ILs.

Although innumerable ILs may be generated through the combination of a variety of cations, anions and substituents, only a small part of them have been reported to exist (have been synthesized).

The available experimental data are generally limited and sometimes even contradictory. A detailed knowledge about the properties of ILs is critically important, especially for ILs not yet available.

Based on collected experimental data from numerous literature sources, a series of group contribution (GC)-based models have been developed for estimating various properties.

On the other hand, prediction of thermodynamic behavior is essential for the early design stage of separation processes including solvent selection, process optimization and its performance evaluation. A UINIFAC-IL-Gas model has been developed for such a purpose.

The developed database and property models can be used easily in IL-based tools. In addition, IL-based ABS has many advantages in bio-separations, but its optimal design is very difficult due to the limited property knowledge.

A systematic study of these systems is of great importance for the applications of ABS involving ILs.

Main supervisor:
Georgios M. Kontogeorgis

Co- supervisor:
Xiaodong Liang

Contact.

Georgios Kontogeorgis

Georgios Kontogeorgis Professor Department of Chemical and Biochemical Engineering Phone: +45 45252859

Contact

Xiaodong Liang

Xiaodong Liang Associate Professor Department of Chemical and Biochemical Engineering Phone: +45 45252877

The Fermentation Based Biomanufacturing initiative offers a comprehensive research-based education and training program in Fermentation Based Biomanufacturing (FBM) at the Technical University of Denmark (DTU) with the mission to deliver world-class research-based education in biomanufacturing, tailor-made towards the needs of the fermentation industry.

Learn more about the project

The project aims to improve our understanding of enzyme stability and broaden the field of potential applications for biocatalysis.

Learn more about the project

Accelerated Innovation in Manufacturing Biologics (AIM-Bio) project funded by the Novo Nordisk Fundation brings together two leading academic institutions, NC State University (US) and the Technical University of Denmark, aiming to create an international collaborative enterprise engaged in education, lifelong learning, and process research and development in biomanufacturing science and technology.

Learn more about the project

Completed projects

Abstract

As per most experts, the global market of chemicals is expected to grow to 5.6 trillion Euros by 2035. In recent times, chemical and biochemical process industry has faced enormous pressure in terms of process efficiency, resource availability, regulatory and environmental fronts. On the other hand, bio-resources remain un-economical to be incorporated in large scale biochemical industrial processes. Also, the global rise in temperature has been directly associated with carbon dioxide (CO2) emissions. The development of sustainable process synthesis intensification methods is expected to yield a net zero or net negative CO2 emission. These problems can be overcome by Process Intensification methods i.e. an integrated approach for process and product innovation and development of new technologies. Such approaches are often sustainable, efficient and lead to significantly reduced energy and resource consumption. During the last decade, process intensification (PI) has become a major potential method in the bulk and fine chemicals and pharmaceutical industries by which the overall improvement of a process can be achieved sustainably while improving its overall efficiency (e.g. energy efficiency, waste reduction etc.). Initially, PI existed at the unit operations level [1] which has further been developed to a process level [2]. The industry is limited to those intensified unit operations which have been implemented and deemed successful from an industrial perspective e.g. reactive distillation, dividing wall columns, membrane reactor etc. A systematic synthesis and design methodology for the selection of intensified unit operations for a given process has been developed further at the process level by Deenesh et al. [2]. Still, the PI database needs to be expanded to yield better results. Therefore, the need arises for the further development of a systematic phenomena-based synthesis and design methodology which not only goes beyond the existing methodology but also provides the opportunity for the expanded database for the generation of novel intensified equipment’s and sustainable processes. This methodology by Deenesh et al [2] has been developed by proceeding one fundamental step lower than the unit operations level, this being the phenomena level. Thus, the major task of this work is to find the integrated solutions and further expand the PI database and enhance the methodology resulting in the creation of a computer-aided tool to automatize the steps involved when applying the methodology for the intensification of a given process.

Introduction

Process intensification (PI) has been receiving increased attention and importance because of its potential to obtain innovative and more sustainable process design alternatives. PI has been defined as the improvement of an entire process through the enhancement of the involved phenomena in terms of the integration of unit operations, functions, phenomena’s and the targeted enhancements of phenomena for a given operation. PI aims to improve processes without sacrificing product quality, by increasing efficiency, reducing energy consumption, costs, volume and waste as well as the overall improvement of plant safety. Recently, Deenesh et al. [2] built on the work done by Lutze et al [1] which reported the development of a systematic phenomenon based synthesis and design methodology incorporating PI at the process level. It was initially limited to the unit operation level. Here in this methodology the phenomena have been combined to form simultaneous building blocks (SPB’s). To be novel by design that is going beyond the existing PI unit operations one must proceed at a lower level of aggregation, namely the phenomenon level and investigate the underlying driving forces associated with the unit operations. Then these phenomenon’s can be combined to generate new alternatives. This is exactly the approach followed by Deenesh et al [2]. Using the analysis of the underlying phenomena of the flowsheet, the synthesis and designmethodology process options has been generated and reduced the number systematically through several screening steps until to find the optimal flowsheet solution.

Objective

The research conducted in this field is majorly within the field of process systems engineering (PSE). This work seeks to further develop Process Intensification database, extend the phenomenon based synthesis and design methodology and develop a computer-aided software tool for the intensification of processes via a systematic approach. Within the framework all possible flowsheet options should be generated even for bio processes and reduce systematically via logical and structural constraints and performance metrics to find the optimal intensified flowsheet option.

Methodology

The synthesis, design and intensification methodology is presented in Figure 1. This methodology is a built on previous work done by Lutze et al. [1] and Deenesh et al. [2]. It is operated at two scales on a bigger picture. These scales are Unit operation level and phenomenon level. The required information for the application of the methodology is either the base case flowsheet design of an existing or conceptual process or the input/output specifications of the existing/conceptual process. To start with the problem must be defined i.e. the process which needs to be intensified is defined and then the base case is designed. Here the base case can also be taken from the literature and then the analysis is performed to find the bottlenecks and design hotspots that can be improved. The whole methodology followed until this point is under the unit operation level. Thought the thermodynamic data would still be required to have the base case design. These steps can also be achieved quickly by using Computer aided flowsheet design tool (CAFD) by Anjan et al. [4]. Now, the second scale of the methodology comes in the picture. The unit operations are used to identify the tasks and further broken into the phenomenon’s. here as strengthen the PI database is, more detailed will be the phenomenon validity. This is the major objective which will be worked upon during the PhD work. After this the next step is to combine the phenomenon’s to SPB’s and generate new alternatives or may be novel unit operations which combine to make alternative flowsheets. These alternatives are then verified and then screened based on the operational constraints and performance metrics to find the final intensified flowsheet. This methodology has been applied to various case studies by Deenesh et al. [2] including one bio process.

Conclusion

In conclusion, an overview of the systematic approach based on phenomena’s and design methodology has been shown for the intensification of processes [1,2]. The phenomena based approach has been extended from unit operation level [1] to the process level [2]. Further work is intended to be done for the extension of the database and a general methodology has been defined. Here, phenomena can then be combined to form stages which can be combined to form flowsheets. The concept of phenomena based PI is promising because it is believed that all intensified flowsheet options can be generated if one operates at this level of aggregation. These flowsheets can then be screened to find those flowsheets which provide the highest benefit with respect to operational constraints and performance metrics and these are then further optimized to find the optimal intensified flowsheet.

Future Work

Currently, a systematic methodology for the Process Intensification has been developed by Deenesh et al. [2]. The future work related to this work is as follows:

  • An enhancement of PI database and an existing methodology.
  • Further application of the methodology to other case studies including bio processes.
  • Development of a computer aided tool for the automation of the methodology.

Supervisors

Prof. John M. Woodley (Principal supervisor)
Prof. Georgios M. Kontogeorgis

PhD Study Started: October 2016 To be completed: October 2019

To see figures and references for this text, please find the original in the Graduate School Yearbook 2017

Abstract

Hybrid gas separation processes, combining absorption and membranes together with distillation require less energy and have attracted much attention. With the property of non-volatility and good stability, ionic liquids (ILs) have been considered as new potential solvents for the absorption step. In this PhD study, a systematic screening model for ILs is established by considering the needed properties for gas absorption process design. Rigorous thermodynamic model of IL-absorbed gas systems is established for process design-analysis. Then a strategy for hybrid gas separation process synthesis where distillation or other gas separation processes and IL-based absorption are employed for energy efficient gas processing is developed.

Introduction

Gas separation processes have been one of the most important operations in the oil and gas related industries, where gases of interest are present in significant amounts to justify their separation for use as raw gas in chemical production utilization. Distillation based gas separation processes is very common in the oil and gas industry. They however, consume large amounts of energy. Therefore, an alternative energy-saving and “green” technology is to replace, where possible, the distillation step with gas absorption employing IL as a solvent in a hybrid scheme. However, the enormous number of potential ILs that can be synthesized makes it a challenging task to search for the best one for a specific gas separation. In order to solve this problem, a systematic screening method is established by considering important properties for separation. Then rigorous thermodynamic model of IL-based system could be established. The hybrid gas separation process combining traditional technology with IL-based technology together could be designed for energy efficiency and economy-saving.

In this project, a three-stage methodology is proposed for hybrid gas separation process design and evaluation. The first stage involves IL screening, where a systematic screening method together with a database tool is established to identify suitable ILs based on a collection of gas solubility data, Henry’s constant data as well as data estimated through reliable predictive models (for example, COSMOS-RS). The second stage is process design, where the important design issues (amount of solvent needed, operating temperatures and pressure, evaporation conditions, etc.) are determined. A hybrid gas separation scheme is designed to replace the conventional distillation process. Since the only energy requiring step in the hybrid process is the flash-evaporation step (and the low energy consuming pre-distillation step, if employed), potentially a large reduction of energy consumption is possible by switching from distillation to the hybrid-absorption scheme the selective gas separation tasks. For example, replace distillation by absorption to remove only the gases present in smaller amounts in the gas mixture, thereby letting the larger amounts free to go out as the exit (raffinate) gas. This small amount absorbed gas is then easily separated through evaporation or distillation, which only consumes a small fraction of the total energy of the conventional distillation based process. The third stage involves verification and sustainability analysis based on rigorous process simulation of the generated hybrid gas separation process strategy.

Conclusion

The predictive Henry’s constant models have been found to be in good agreement with experimental data. On the basis of these validated models, a method for selection of the potential IL-solvent for gas separation by absorption has been highlighted. An IL-based hybrid separation scheme for significantly reduced energy has been introduced and the potential benefits highlighted through a conceptual example. Further work is necessary to fine-tune the IL screening tool (database, model, search engine). More detailed analysis is necessary to account for all possible performance criteria to establish the hybrid gas separation scheme.

Supervisors

Prof. Georgios M. Kontogeorgis (Principal supervisor)
Assistant Prof. Xiaodong Liang

PhD Study started: September 2016 to be completed: August 2019

Abstract

This work presents a systematic framework for a simultaneous synthesis of process and wastewater treatment network using superstructure-based optimization method. The overall superstructure is composed of i) the process network ii) the wastewater treatment network that connected by converter intervals. In this approach, the problem is generally expressed as a mixed-integer nonlinear programming (MINLP), which is solved to identify the optimal configurations for the process and water network, among a set of feasible alternatives, according to selected performance criteria. A solution strategy to solve the multi-network problem accounts explicitly the interactions between the networks by selecting suitable technologies in order to transform raw materials into products and produce cleaned water to be reused in the process. The features of the developed synthesis method has been demonstrated on conceptual and bioethanol production case studies.

Introduction

Process synthesis offers an attractive framework for undertaking various design problems through a systematic framework, either using sequential or simultaneous optimization approach. For the former, the overall process system is decomposed into different subsystems for ease of analysis. However, these subsystems (i.e., resource conservation network, heat exchanger network, water network etc.) may not guarantee a truly optimized system as they are synthesized separately after the process flowsheet is obtained. On the other hand, the simultaneous approach gives a better solution as all interactions and economics trade-offs are taken into consideration explicitly [1-3]. The solution strategies of an integrated network problem are able to find the optimal raw material, product portfolio, process and wastewater treatment technology by simultaneously screening various alternatives included in the search space, while minimizing fresh water intake and satisfying environmental regulations [4]. In addition, various water minimization strategies (i.e. reuse, recycle, regeneration and treatment-reuse) are considered in order to reduce the amount of freshwater intake.

Systematic Framework

The framework is supplemented by a software infrastructure based on Ms EXCEL for gathering required input data and General Algebraic Modeling System (GAMS) for the solution of the formulated optimization problem. The framework has been developed in an earlier work and the details of the framework can be found in Handani et al. [4]. The systematic framework consists of four main steps.
After defining the goal and scope of optimization problem as well as objective function in the first step, one can define a superstructure that consist of various alternatives for the process and wastewater treatment networks are specified with respect to raw materials, technologies and products. The treated wastewater in the treatment tasks can be either discharged into the environment and/or it can be recycled for use in the same processes or in neighboring processes. Then, generic models based on mass input-output describing each of the elements of the superstructure are developed. Generic model parameters require to represent the activity of each interval includes chemical and utility consumption, reaction conversion, split fraction and separation efficiency are collected from various sources i.e. open literature, simulation and technical report. Finally, the optimal process and wastewater treatment network are then formulated as MI(N)LP and solved under different process synthesis-design scenarios.

Supervisors

Prof. Kim Dam-Johansen
Prof. Georgios M. Kontogeorgis

Objective

1. IL screening method development
2. IL database and software tool development
3. IL-based hybrid separation schemes design
4. IL-based ISPR design

Background

Base on the advantages of hybrid reaction-separation schemes and the benefits of ionic liquid as media for bioreaction, integration of IL into hybrid reaction-separation schemes for bioprocesses, namely IL-based ISPR, is a promising area which holds potentials of opening up a new field of bio-chemical industry. However, these IL solvents present other challenges, among them difficulties in controlling water activity and pH, higher viscosity and problems with product isolation. Therefore, finding optimal ILs for specific bio-reaction tasks confidently and rapidly is essential.

The Project

In this PhD project, we will focus on developing a timely and systematic method of IL-based ISPR design including IL identification and process synthesis. Because the usual trial and error approach can be time consuming and expensive due to numerous ILs that may be considered as potential solvents, techniques such as computer aided molecular design (CAMD) is ideally suited as tailor-made ILs can be generated by adjusting the cation, anion, and side chains on the cation. Consequently, both comprehensive IL database and efficient IL screening method are needed. Meanwhile, a software tool will be developed for IL containing system.

Supervisors

Prof. John M. Woodley (Principal supervisor)
Prof. Georgios M. Kontogeorgis

The project is funded by Technical University of Denmark (DTU) and Chinese Scholarship Council (CSC), and will be running from October 2017 to October 2018.

Abstract

Emissions result from most chemical processes and from the use of chemicals based products. Industrial companies and more specifically, Danish companies need to carefully estimate and analyze the emissions from their processes and products. Use of measured data is a reliable but insufficient method as the needed data may not be available and/or cannot be measured due to cost, safety and time concerns. Models capable of estimating and predicting chemicals emissions from industrial processes can be used as a tool for comparison of alternative substances, evaluation of undesired emissions or for design of processes aiming to employ sustainable solutions. That is, develop a model based method to generate and evaluate suitable alternatives for substitution of undesired chemicals.

Introduction

The background for the project is the REACH regulation with the obligation to companies to perform a chemical safety assessment of their uses and handling of chemical substances. For the assessment of chemical substances under the REACH regulation, several industry associations have developed industry-related environmental release categories as shown in Figure 1. However, the emission estimations are very conservative and the methods are not suited to select and deselect raw materials or processes in companies aiming at circular product design. Therefore, a model-based approach coupled with the use of appropriate databases containing available data is a better approach. The necessary models, however, need to be developed and validated. Group contribution based models1-2 because of their predictive capabilities and eases of use will be used as the basic model from which the final versions of the models will be developed. Based on the developed models, a systematic, efficient and reliable chemical substitution and evaluation system will be developed.
The overall aim of the project is to develop models for estimation of chemicals emissions from industrial processes to be used in circular product design. Models for estimation of chemical emissions from different industrial processes will be developed using published data from measurements of substance emissions from chemical unit operations or relevant sub-processes and tested. The data will either be provided by the industry or be collected from published data or databases. Focus will be on - but not limited to - emissions to industrial water environments.
Besides emissions from processes, the design of products also needs to be such that it does not make use of any hazardous substances. The first case-study would be developing paint formulations that serve a variety of purposes eg. home décor, marine paints etc. The base case for an insoluble white paint has been developed in the previous work DTU’s Chemical Engineering Department (4).

Specific objectives

The specific objectives of this project can be classified into four different tasks comprising the project workflow:

1.Development of models for the prediction of 22 environmental related properties: Property models, for the prediction of LD50, fathead minnow, bioconcentration factor etc. for all substances/chemicals constituting a product or being emitted from any process being studied, have been developed using group contribution and atom connectivity index methods previously1-2 by our group.

2.Comparison of predicted values of the environment-related properties with their values in REACH databases by the EChA (European Chemical Agency): For the purpose of identification of the substances/ mixtures which are toxic and hence need to be substituted, the databases prepared by the EChA will be compared with the values predicted using the models.

3.Identification of alternatives/ substitutes: Identify the substitutes, using property models for evaporation rate, dynamic viscosity, surface tension etc. and Computer Aided Mixture Design (CAMD) approach3 to deliver similar set of needs or target properties as present in the original product constraint to meeting the toxicity conditions

4.Implementation and Improvement: Design an environmentally benign, safe product and/or a process with emissions in compliance with REACH regulations.

Potential areas of Application

Chemical substitution can have a very wide range of application shown in Figure 2. The chemicals being used today to design mixtures/ products that we desire, have only played there service role. Their compliance with the regulations from the environment perspective have not been considered.
Hence, practically every chemical industry will require a systematic methodology for chemical substitution, which is a way to combine environmental improvements with advanced technologies and turn environmental issues into a competitive advantage (5).

Conclusions and Future work

Although the group contribution models for property prediction are available, more complex models which can take into consideration all phenomena for prediction of properties like evaporation rate and solubility, need to be developed. Once, the models are ready, a framework for the purpose of systematic chemical substitution followed by safe and circular product design is required to be made. Besides this, also certain processes resulting in highly toxic emissions need to be  studied and substitutes or alternative chemicals to reduce such emissions must be recognized. Hence, as a result of this study, a versatile methodology for chemical substitution, circular product design and reduced-emissions process will be developed.

Supervisors

Georgios M. Kontogeorgis (Principal supervisor)
Prof. Kim Dam-Johansen
Assistant Prof. Xiaodong Liang

PhD Study Started: October 2016 To be completed: September 2019

Abstract

The production of fuels and chemicals is primarily based on crude oil. The use of biomass as raw material represents a sustainable alternative. In order to establish a new industrial system on the basis of biomass, a systematic approach to generating, evaluating and selecting biorefinery processing networks is needed. In this PhD study, a generic computer-aided methodology for synthesis and design of different processing networks, including biorefinery networks, is developed, along with the associated methods and tools

Introduction

Innovation in process synthesis-design is motivated by the current and projected increase in commodities, water and energy demand caused by the growing world population. The use of the present technologies and processes to satisfy the stated demands is causing an undesired raise in greenhouse gas emissions (especially carbon dioxide). Therefore, new process synthesisdesign methods are needed towards finding more sustainable processes in terms of using alternative raw materials (from renewable sources, such as biomass), incorporating new process technologies and satisfying new design objectives and constraints, including sustainability. In this project, a computer-aided framework has been developed for biorefinery processes, which includes specific tools, i.e. a database and a software interface. The framework is based on a superstructure optimization approach, including four key elements: (i) a superstructure representation named Process StepInterval Network (PSIN); (ii) a generic process model; (iii) a solver from an optimization environment; and (iv) a database for data management. Two special tools have been created: a database and a software implementation of the framework. The biorefinery database contains 10 types of biomass, over 100 processing alternatives and 9 products, which generate over 7∙1014 theoretical alternative routes. The software implementation named Super-O integrates the necessary in-house and commercial tools.

Synthesis framework

The framework for synthesis of biorefinery networks consists of a workflow and methods, algorithms and tools that are used in different steps. They key elements of the framework are shown in Figure 1.Figure 1: Three key elements of the framwork (superstructure, model, and solution strategy) and database as the fourth key element, which enables storage and retrieval of data for its use in new problems.
The synthesis workflow consists of three main steps: (1) problem formulation; (2) superstructure generation; and (3) solution of the optimization problem. Step 1: Problem formulation The objective of this step is to define the synthesis problem that needs to be solved by specifying raw materials, products, locations, processing steps, and available technologies in each of the considered steps. Step 2: Data collection and superstructure generation The objective is to collect all the necessary data for the problem that has been defined and to generate a superstructure of alternatives. Step 3: Solution of the optimization problem. The optimization problem is solved by employing solvers from an external optimization environment (GAMS) through Super-O.

Computer-aided tools

Biorefinery database.
The purpose of the database is to provide a common platform for different users to store, search and retrieve data for the formulation and solution of biorefinery synthesis problems. Table 1 lists some of the statistics related to the data available in the biorefinery database. The database is built on a specifically designed data structure that consists of three main data sections, namely a basic data section, a section for data related to the material, and a section containing process data.

Super-O: Software implementation
The software implementation of the framework, named Super-O, guides the user through the steps for formulating and solving synthesis problems of different processing networks. It allows for the reduction of the time needed for the formulation and solution of network optimization problems. A schematic representation of the workflow implemented in Super-O including the data flow and tools integration is shown in Figure 2.

Application example: Ethanol biorefinery

Ethanol is an attractive biofuel that can be used in blends with gasoline. It is therefore a good solution for reducing emissions and many countries have policieswhere it is required to use a percentage of ethanol from renewable sources in blends with gasoline [1]. The type, characteristics and availability of biomassbased feedstocks in different geographic locations is not homogeneous, which makes the problem of planning and designing production processes for this biofuel a location-dependent problem. Step 1: Problem formulation. The desired product is specified as fuel grade ethanol. Various alternatives in terms of biomass-based feedstocks and locations should be considered. The objective is to determine the most suitable locationfeedstock-process combination. Step 2: Data collection and superstructure generation. Six feedstocks and seven geographic locations are considered; the superstructure is shown in Figure 3.

Conclusions

A framework for synthesis of biorefinery networks has been developed, which can handle various types of problems efficiently and considers location-dependency of data and solution. Its software implementation guides users through the workflow, thus reducing time and minimizing errors.

Supervisors

Prof. Rafiqul Gani
Prof. John Woodley
Prof. Anker D. Jensen

PhD Study started: September 2014 to be completed: August 2017

Abstract

Lipids are naturally occurring compounds which cover a wide applications range: from biofuels to food, health and personal care products, and which involve different industries, such as biodiesel, edible oils and oleochemical industry. Expansion of lipids related industries led to new challenges regarding the design and development of better performing processes and products. Despite the advances in property modelling and process design techniques available in different computer-aided methods and tools for the petrochemical and chemical industries, the lipids related industries were not able to exploit this knowledge. The main reason is the lack of experimental data and lack of available property models within commercial software tools. An essential aspect of process synthesis, modelling and simulation is represented by phase equilibria prediction, which is highly dependent on data used for regression of model parameters. The objectives of this PhD project are to further extent SPEED lipids data base, to develop and apply a systematic identification method for thermodynamic property modelling for improving the phase equilibria prediction for lipids systems, and then apply the new thermodynamic models for process design.

Introduction

Process synthesis, design, optimization, control as well as energy, economic and environmental impact analysis are performed through model-based tools, where for a class of systems, accurate and consistent prediction of phase equilibrium is very important. While experimental determination of phase equilibrium is accurate, it is time consuming, expensive and not suitable for multiple requirements. In this case, it is better to use collected experimental data to fit the parameters for a suitable thermodynamic model. The important issues are however, the amount and consistency of data, the selection of the appropriate model and its parameters. For the scope of the model-based system, the models need to be predictive and it should be possible to extrapolate from regressed model parameters. Also, it should be possible to obtain the best identified models with a minimum of the available data, since there may be limitations on data availability.
The demand of oils and fats has grown from 40.8 million tons in 1980 to more than 210 million tons 2016 [1]. The consumption of 17 vegetable oils for bio fuels and food and other applications are presented in Figure 1. Limited availability of physical and thermodynamic properties for lipids compounds and their mixtures lead to difficulties in providing models to accurately describe their phase behaviour. VLE predictions for lipid systems with original UNIFAC model have been found to be poor [2]. Also, in addition to phase equilibrium models, pure component property models are also needed. Therefore development of accurate and consistent thermodynamic models is needed for oleochemical systems. In this work, development and application of a systematic method for identification of thermodynamic models is presented. The aim of the method is to improve the phase equilibria predictions by providing reliable and correctly identified parameter sets for predictive group contribution models. The main steps of the method are: data collection and organisation, data analysis-selection, and parameter estimation and validation, Figure 2. The method is applied for improvement of VLE predictions involving lipid systems with the original UNIFAC model. First, all available binary VLE data sets are collected from SPEED Lipids Database, and organised into groups according to the binary interaction parameters that need to be identified. Next, the datasets with the best consistency test performances are selected for parameter estimation, which is performed according to an established sequence as presented in Figure 3. The calculation sequence of the parameters results from the first part of the methodology.The new set of the parameters is analysed by comparing the model performance for all available VLE datasets as well as their extrapolation to SLE data. The results show significant improvement in the performance of original UNIFAC model. The same procedure is applied to fit the model parameters for LLE data as well as group contribution models for pure component properties. In principle, the systematic model identification method should be applicable for all thermodynamic model development.

Conclusions and future work

Development of lipids property modelling with emphasis on process simulation, presents a big evolution in the last years [3]. However, there are still a lot of research areas to cover within the lipids modelling and technology development. The future steps of this project will try to cover some of these aspects: extension of available lipids data base, lipids property models improving, generation of a systematic framework for oils and fats able to improve the research within lipids related industries.

Supervisors

Prof. John M. Woodley (Principal supervisor)
Bent Sarup
Prof. Georgios M. Kontogeorgis

PhD Study started: September 2015 to be completed: September 2018

Objective

This project focuses on exergy efficiency based design and analysis of utilization pathways of biomasses.

Background

Fossil energy depletion and environmental pollution are two major problems that greatly plagued the world, and "energy-saving emission reduction" has become the focus of attention. Biomass energy is a CO2-zero energy that does not interfere with the global carbon itself. However, if the biomass is not used effectively, it will cause serious environmental pollution. Therefore, the utilization of biomass has triple advantage of energy conservation, emission reduction and resource utilization. However, there are many problems such as more routes, complicated way and the lack of scientific criteria.

The project

A systematic computer aided model based exergy efficiency method employing output to input ratio (the ratio of produced exergy to the exergy used) will be proposed in this project as a unified scale for evaluating the effective utilization of energy for three different biomass utilization processes (pyrolysis, gasification and anaerobic digestion). Based on established estimation model of higher heat value (HHV) for biomass, the Gibbs free energy minimization method will be used to simulate the pyrolysis and gasification processes of biomass, while a new model for anaerobic digestion model 1 (ADM1) will be used to generate the biogas data for the analysis. Then, based on chemical exergy estimation model of biomass, different biomass utilization processes (three kinds of straws and three kinds of manures are considered) will be analyzed for exergy efficiency.

Supervisors

Prof. Georgios Kontogeorgis
Assistant Prof. Xiaodong Liang

The project started on July 2, 2017 and will be completed on June 29, 2018. 

Objective

The objective of the project is to develop a systematic method and associated tools that can analyze and design innovative biorefinery networks based on chemical and biological approaches to convert biomass feedstock into valuable chemicals and biofuels. The project would be considered a success if the developed method is able to:

  • Satisfy the sustainability criteria (including environmental, social and economic issues)
  • Understand and analyze the geographical and supply chain constraints
  • Create superstructures of biorefinery networks based on current and future conversion technologies
  • Combine different sources of data, models, techniques, into a comprehensive method
  • Educate and train students, engineers, researchers on the science of biorefinery network generation, implementation and optimization
  • Systematically and efficiently manage the complexity
  • Successfully identify the best possible synthesis route for a given set of biomass and products (fuels & chemicals)

Background

Concerns about diminishing petroleum reserves, enhanced worldwide demand for fuels and fluctuations in the global oil market, together with climate change and national security have promoted many initiatives for exploring alternative, non-petroleum based processes. At the same time, it is well-known that biomass is the most abundant and promising renewable source of organic carbon for the production of transportation liquid fuels, value-added chemicals and biomaterials. Carbohydrates, such as lignocellulose (cellulose) and starch, comprise as much as 75% of available biorenewable sources, and are typically obtained from corn, trees and grasses. The aim of biorenewable processing, namely biorefinery networks, is to convert a broad range of biorenewable carbon resources into liquid fuels, power and value-added chemicals. However, different geographical locations have different amounts and types of biomass and therefore, unlike the optimal petrochemical refinery, the optimal biorefinery network will be dependent on the specific geographical location.

The project

A new initiative on biorefinery, the ProBioRefine project has been launched at DTU (Chemical & Biochemical Engineering) and KAIST (Chemical & Biomolecular Engineering) with funding from various sources. The ProBioRefine project brings together highly qualified researchers from DTU and KAIST to develop a very important aspect of biorefineries, namely, the optimal processing route (network) for the conversion of specific biomass into a set of desired products (fuels & chemicals) taking into account the currently available technologies and future developments. ProBioRefine is jointly led by Professors Jay H Lee and Rafiqul Gani.

The project is divided into the following four tasks:

  • Conversion of biomass to valuable chemical products (fuels & chemicals)
  • Generic synthesis methodology for biorefinery network
  • Generic methods and tools for biorefinery studies
  • Validation and Demonstration

The ProBioRefine project was launched on 1-2 December 2014 with a workshop at KAIST in Daejeon, Korea.

Older projects

If you have questions about older projects, please contact Head of KT Consortium and Professor, Georgios Kontogeorgis.

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Kim Dam-Johansen

Kim Dam-Johansen Professor, Head of Department Department of Chemical and Biochemical Engineering Phone: +45 45252845

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Georgios Kontogeorgis

Georgios Kontogeorgis Professor Department of Chemical and Biochemical Engineering Phone: +45 45252859

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Eva Mikkelsen

Eva Mikkelsen Research Co-ordinator Department of Chemical and Biochemical Engineering