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Scale-up and multiphase reaction engineering
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ScienceDirect Scale-up and multiphase reaction engineering MP Dudukovic´1 and PL Mills2 Successful scale-up of new multiphase reactions from the laboratory into practical processes is important to all sectors of the process industry. Business demands that process technologies involving molecular transformations maintain high profitability and operate safely within existing environmentally regulations. Current societal expectations and regulations require that all process technology should be environmentally responsible [1]. One key question to be answered is whether or not these expectations can be met in the foreseeable future with the current approaches to scale-up and technological workforce. In addition, advances in chemistry, physics, materials, and biology will continue to generate new potential reaction pathways for more efficient utilization of nonrenewable and renewable resources. Another key question is whether the current methods for process scale-up incorporate the relevant scientific advances to ensure ‘green technologies’, or are they just extensions of previous largely empirical approaches having limited utility and reliability? Evidence suggests that only a science-based scale-up methodology can substantially reduce the risk of new process commercialization and provide reliable estimates of both profitability and environmental impact. We review briefly here the historical approach to scale-up and opine on the challenges of implementing improved approaches. Addresses 1 Chemical Reaction Engineering Laboratory (CREL), Energy, Environmental and Chemical Engineering Department (EECE), Washington University in St. Louis (WUStL), St. Louis, MO 63130-4899, USA 2 Department of Chemical and Natural Gas Engineering, Texas A&M University-Kingsville, Kingsville, TX 78363-8202, USA Corresponding author: Dudukovic´, MP ([email protected], [email protected])
Current Opinion in Chemical Engineering 2015, 9:49–58 This review comes from a themed issue on Reaction engineering and catalysis Edited by Marc-Olivier Coppens and Theodore T Tsotsis
http://dx.doi.org/10.1016/j.coche.2015.08.002 2211-3398/Published by Elsevier Ltd.
Introduction Multiphase chemistries involving reactions between gases, liquids, and solid reactants that are catalyzed by homogeneous organometallic complexes [2], heterogeneous www.sciencedirect.com
inorganic solids [3] or biocatalysts [4–6] are the basis for nearly all processes used to manufacture organic and inorganic intermediates and end-use products, such as fuels and chemicals from petroleum feed-stocks [7], bulk commodity, specialty and fine chemicals [8], medicinal intermediates and pharmaceuticals [9,10], and various polymers [11–13]. End-of-pipe processes for environmental remediation also rely upon multiphase catalyzed chemistries for emissions control [14–16]. Various handbooks provide reviews of the science and technologies associated with heterogeneous catalysis [17], homogeneous catalysis [18], industrial biocatalysts [19] and multiphase polymers [20]. In addition, several monographs [21,22] also review the scope of industrial catalysts and processes, and consider their environmental footprint [1]. These collective works suggest that catalyst science and technology is a critical component of every industrial sector and also plays a major role in enabling existing global lifestyles. Hence, the practical catalytic reactor that converted crude raw materials into useful products should be given notable attention. To maintain the lead over their competition, catalyst vendors must provide replacement catalysts having improved measures of performance, such as higher activity, better selectivity, extended life, lower pressure drop, better mechanical integrity, improved thermal stability, and reduced catalyst fines with competitive pricing. The approaches used for scale-up of catalyst recipes and the challenges encountered with evaluating their performance in commercial reactors are proprietary, although information is sometimes reported when a notable success or a disaster occurs. Anecdotal evidence suggests that old scale-up rules based on empiricism prevail in practice, since little or no investment has been made in adding more science to scale-up. In addition, utilization of an improved catalyst by various customers across various reactor configurations for a given technology allows the catalyst supplier to assemble a significant data base on reactor performance that can be used in look-up tables to make empirically-based suggestions on how to handle particular process situations. Most replacement catalysts in an existing process lead only to incremental improvement in practical reactor performance, so the risk is much smaller when compared to a new process. Invention of new or improved catalysts for more economical processes with a reduced environmental footprint [23] is a leading research topic. Examples of catalytic technologies that are receiving increased emphasis include those that: (1) produce cleaner energy sources from various feedstocks [24]; (2) create higher quality lubricants [25,26]; (3) capture, control, or utilize greenhouse gases [27,28]; (4) convert Current Opinion in Chemical Engineering 2015, 9:49–58
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natural gas or bio-based methane gas to chemicals and fuels [29]; (5) minimize environmental impact or reduce the environmental footprint [30–32]; (6) transform biobased feedstocks to either hydrogen or targeted organic chemicals [33–35]; (7) gasify biomass for production of either hydrogen [36], synthesis gas [37], chemicals and other products [38]; and (8) generate power using fuelcells [39]. One conclusion that emerges is that the likelihood of successful translation and scale-up of these new catalytic technologies from laboratory research to commercial-scale processes is notably enhanced when reaction engineering principles are closely integrated with other ongoing science, engineering and business development activities [40,41].
Reactor scale-up: current status The state-of-the-art of multiphase reaction engineering (MRE) has been the subject of various reviews over the past 30 or so years [40,42,43,44,45,46–51,52,53,54]. Although the installed cost of catalytic process reactors typically account for about 5–15% of the total capital, reactor performance always dictates the cost of downstream product refining as well as the flow rates and composition of recycle streams. A successful commercial catalytic process will retain favorable performance
metrics as the catalytic chemistry upon which it was based is translated from laboratory reactors to commercial practice [55]. Classic monographs on chemical process scale-up [56,57] describe customary practices, which are based on both heuristics and engineering-based models. We focus here on the evolution of reactor scale-up practices that allow increased incorporation of sound scientific and engineering principles. The key phenomena that affect multiphase reactor performance occur on a large range of length and temporal scales and are illustrated in Figure 1 [6]. These include molecular-scale transport-kinetic interactions, eddy or particle-scale transport processes, and fluid flow patterns, hydrodynamics and transport on the reactor scale. These phenomena are subject to events that occur on the process scale, such as disturbances in reactor inlet flow rates, specie compositions, temperatures, pressures, and reactor heat transfer systems, to name a few. The rates for these phenomena can be quantitatively described at the indicated length and temporal scales using models that start from an intuitive basic level, such as empirical power-law reaction kinetic models, and then evolve to a more sophisticated level based on fundamental
Figure 1
REACTOR PERFORMANCE = f (input & operating variables; rates; mixing pattern) Eddy/particle Scale
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Key phenomena that affect reactor performance. Current Opinion in Chemical Engineering 2015, 9:49–58
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principles, such as those based upon detailed micro-kinetics [58,59]. A robust scale-up methodology relates the key metrics or observables of reactor performance (e.g., reactant conversion, product selectivity, volumetric productivity or space-time yield, energy efficiency and environmental footprint), as defined below in Table 1, to rates of these multi-scale transport-kinetic interactions. The modern reaction engineering model combines sub-models from the various scales through the various coupling variables [45,60]. This approach should be followed as the targeted catalytic reaction is conducted in laboratory, pilot, demonstration and commercial-scale reactor configurations. Mathematical models for larger-scale reactors, such as those that are part of integrated pilot plants, demonstration-scale systems and commercial plants, should preferably account for reactor process dynamics since these processes are inherently transient in nature, and reactor start-ups and shut-downs are both a critical aspect of reactor operations. In addition to satisfying mass, energy and momentum balances, these models incorporate the state-of-the art information on the reaction kinetics, transport processes, fluid flow patterns, and hydrodynamics of the various reaction fluids.
a sulfuric acid contact convertor contained more than 20 fitted parameters. Evaluation of process economic potential and environmental impact is performed using selected algorithms, such as WAR [63], which have the same mass conservation basis as above cited simulators. These empirical models do not incorporate the current state of science that describes the multi-scale phenomena shown jointly in both Figure 1 and Table 1.
The goal of developing a multi-scale reactor model that accounts for the phenomena described above has been rarely achieved for most reactors in commercial practice based upon our combined 70+ years’ experience. In fact, many operating processes do not even have kinetic models for prediction of reaction rates. Simpler approaches are often used, such as fitting nonlinear empirical models based upon plant reactor data that describe the reactor performance phenomena within defined operating process windows. These empirical models are then embedded as module into a chemical process simulator, such as Aspen Plus, Aspen HYSYS, Design II for Windows, ProMax, or SuperPro Designer [61]. In some cases, the available reactor models in these simulators, which are based upon ideal plug-flow or ideal stirred tanks, are adapted by using plant reactor performance data to extract the observed rates. An example of this empirical approach is described by Fariss [62] whose rate model for SO2 oxidation to SO3 used to describe the performance of
The Vision 2020 Reaction Engineering Roadmap [61], which was published by the AIChE in 2001, was part of an industry-wide effort to create a blueprint of the research and development that was necessary to achieve long-term industry goals. It defined linkages between key research needs identified in the following four cross-cutting areas: (1) experimental tools; (2) modeling and property estimation; (3) sensors; and (4) systems integration. It also specified the time frame for achieving the targeted results. Inspection of the indicated long-term (>10 year) goals listed in Table 1 of the report suggests that none have really been reached. The lack of progress in reaction engineering design and scale-up was recently discussed by Stitt et al. [69]. It was pointed out that while notable advances have been achieved in computational speed, due to advances in computer hardware and algorithms, the models being utilized for reactor and process design are still rather primitive! In other words, advances in science are not reflected in conceptual and mechanistic
Evolution of models based on fundamentals and the development of specialized experimental tools to support each of the temporal-spatial scale-dependent phenomena shown in Figure 1 continue to generate improved insight and understanding [64,65,66,67,68]. However, integration of these models into predictive models for reactor design and scale up is still lagging [60]. Hence, in spite of advances in science and computational techniques, the methods and models available for reactor scale-up and design applicable to realistic process conditions have not advanced much in the new millennium, and may have even regressed in some instances. This lack of traction in technology advancement was highlighted in a perspective article in Science [44].
Table 1 Key metrics of reactor performance Reactor volumetric productivity Rate of product generation per unit time Average process rate for the reactor Average reactor process rate is a function of Kinetic rate, which in turn depends on catalyst turnover number and local temperature and composition and their distributions Effect of local mass and heat transfer on the intrinsic kinetic rate Reactor flow and fluid contacting patterns, which affect the composition-temperature field in the reactor Reactor selectivity (moles of desired product produced)/(moles of undesired products made) is determined by kinetics, local transport effects and global contacting pattern.
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models used for reactor scale-up or design. The reaction engineering community was challenged to embark on the replacement of heuristics with the proper use of multiscale reaction engineering methodology leading to a quantitative description of kinetics and transport in reactor design, scale-up and operation. Most importantly, the need for vigorous validation of models on all scales with properly designed and executed experiments was emphasized. This science-based approach is what all of the reaction engineering community championed as the right path to follow already decades ago! The key focus areas were also well-documented in 1999 by the 46 industrial and academic experts who contributed to the Vision 2020 Reaction Engineering Roadmap report. We opine here as to why we departed from this goal, and what should be done to change the direction of this highly undesirable situation into a positive one.
Challenges in implementing science-based modern scale-up methodology Past developments that impacted practice
Reactor scale-up effort over half a century ago, when the process industries were undergoing significant growth, involved a large number of skilled professionals, technical support and large-scale facilities to support it. Company management possessed a strong technical backgrounds and commitment to a long-term pursuit of science-based scale-up. Faster digital computers and new numerical techniques made possible the solution of previously intractable conservation equations for single and multiphase flows in complex geometries culminating in the present CFD algorithms [58,59]. The realization that the reaction engineering methodology offered considerable rewards when related to industrial practice led to cooperative efforts between academics and industry. This effort was financed by industrial support and grants from the federal government, for example, precompetitive research in our Chemical Reaction Engineering Laboratory (CREL) was promoted since 1974 by many diverse industrial sectors [70]. It produced generic tools for science and engineering-based scale-up and modeling that could be used in many technologies. It also produced many graduates that collectively represented a strong reaction engineering workforce and individually accomplished notable technical advances in a host of diverse industries [70]. Validation of new generic scale-up concepts on cold flow units was often shared in joint ventures. Appropriate refinements for specific processes were then performed by individual companies and kept as proprietary. From the 1980s onward, the management of many technology companies embraced the more immediate higher returns by licensing their existing processes in the rapidly developing parts of the world. This growth hardly generated any new innovations in the process industries. Instead, the ‘Best Available (process) Technology’ or BAT [71] spread globally, which was not encouraging the use of Current Opinion in Chemical Engineering 2015, 9:49–58
fundamentals. The departure from the rational approach was further accelerated by universities changing both the names and curricula of chemical engineering departments to pursue applied science in perceived more lucrative fields of biology and nano-materials. This significantly decreased the production of graduates that were exposed to the complexities of process synthesis and scale-up interactions depicted in Figure 1. Thus, the qualified manpower base in industry for performing and managing science-based scale-up was greatly diminished. Scale-up of new processes sometimes resulted in failures, although these were not disclosed, or was abandoned as too risky. Three examples involving a trickle-bed reactor, a liquid– solid riser, and a gas–solid riser were recently presented by the authors that describe the pitfalls of using current scale-up based on heuristics [60]. The key lessons learned are: (1) trickle beds that are scaled-up based on constant liquid-hourly space velocity (LHSV) can lead to over a 50% loss of performance for gas-limited reactions and unanticipated hot spots when a much more active catalyst is used, thereby leading to excessive temperatures and loss of selectivity; (2) the available information on solids flow patterns in liquid–solid risers was quite meager, which lead to wrong assumptions on an accurate model representation. Hence, an accurate riser design was not possible prior to the work of Roy et al. [48,72,73]; and (3) the solids residence time distribution in gas-solid risers was never measured properly until the work of Bhusarapu [74,75,76]. Hence, mean residence times and variations of contact time with reactor scale could not have been predicted properly. It is noteworthy that proper experimental techniques were needed to validate the emerging physically based models [65]. Now, in 2015 and the foreseeable future, companies that have abandoned or neglected the development of a core competency in reaction engineering and in process sciences face a serious shortage of qualified manpower needed for improvement of existing process technologies and scale-up of new ones. It is not evident, at least in certain geographical locations, how the required formal education in reaction engineering fundamentals and subsequent development of expertise through practice will occur so that the required technology leadership to create innovative processes will be developed. Renewed motivation for experimental validation
Noninvasive techniques for measurement of multi-phase flow parameters provide valuable information needed for validation of CFD codes [65,77], especially on larger-scale systems. For example, research on churn-turbulent bubble columns at CREL led to the ability to predict liquid residence time distribution and back-mixing for a number of processes executed in pilot-scale systems, such as the Fischer–Tropsch hydrocarbon synthesis, dimethyl ether and methanol synthesis [78–84]. The three examples described above on the shortcomings of reactor scale-up www.sciencedirect.com
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Figure 2
CARPT & CT applications
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Illustration of the Computer-Automated Radioactive Particle Tracking (CARPT) and Computer Tomography (CT) and their application to various multiphase reactors.
are the consequence of the fact that after a century of using the common reactor types illustrated in Figure 2, industry at present does not have state-of-the-art reactor models for prediction of their performance. Hence, the academic and industrial reaction engineering community should work jointly to develop proper predictive models. This effort involves computing all pertinent parameters on various reactor scales with experimental validation of emerging mechanistic models suing both cold-flow units and hot process systems when possible. Fundamentally-based reactor models should then be used in various technologies where these reactors are employed. These efforts would facilitate reducing the gap between academia and industry and enable more efficient use of available resources.
companies that provide clear evidence of improved environmental performance that was predicted by the models which they had developed. This requires judging each process based on its technical merits and environmental impact, and giving better tax credits for use of non-fossil and non-food based sources for feedstocks and energy. We should also engage in a campaign of educating our profession and the public of the benefits of the long-term planning and use of multi-scale process synthesis. The change in approach to process scale-up must be done soon before the pool of technical people with the required knowledge base and experience shrinks below a critical mass.
Concluding remarks Nontechnical challenges One key challenge is to change the perception that pursuing short-term research goals will lead to long-term profitability and sustained business growth. Long-term science-based research on process synthesis should be rewarded. For example, tax incentives should be given to www.sciencedirect.com
Our focus here was on improvements needed in the industrial practice of scale-up. However, proper credit was not given to many in academia that still hold the reaction engineering banner high and continue to develop better foundations for future reactor scale-up by focusing on a specific scale of scrutiny or a specific process. For Current Opinion in Chemical Engineering 2015, 9:49–58
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example, impressive modeling advances on all scales are pursued by Vlachos’s group at Delaware [85,86] and Kuipers’ group at Eindhoven [87,88,89]. Multi-scale physics models and measurements are pursued by various groups at Delft (Van den Akker, Mudde, Van Ommen, Kreutzer) [90–96] and others. There is considerable expertise and progress in reactive multiphase flows (e.g., Fox at Iowa State [97,98], Ranade at NCL [68,99]), flows in tubular packed bed (e.g., Dixon at WPI [100,101,102]) particulate flows, risers, fluidized bed (e.g., Sundaresan at Princeton [103–105], Sinclair at Florida [106], Van den Akker at Limerick [90,107], Hrenya at U of Colorado [108,109], and Li at Beijing [110,111,112,113]). There are also exciting developments in novel, nature inspired contactors (Coppens at London [114–116,117]), in membrane reactors (Tsotsis at USC [118,119]) and microreactors (Jensen at MIT [120–122]). Scale-up of the important new technology for chemical looping is being pursued at OSU by Fan [123,124,125], and the use of expandable solvents by Balasubramanian at CEBC Kansas at [126,127,128]. However, only a small number of these efforts are directly focused on industrial scale-up needs. In addition, they seldom combine novel computational techniques with validation of key parameters under practical process conditions. Finding a way to integrate these efforts in academia into the development of a comprehensive and validated model for various existing reactor types (Figure 2) would go a long way in pushing the scale-up in the right direction. It will also produce graduates that can implement these models within various companies on diverse technologies and later work on proper modeling of the new reactor types. These aspects are clearly an area of future development and also an important part of the Vision 2020 Reaction Engineering Roadmap [61]. Finally, it should also be noted that despite decreased financial support for reaction engineering in certain geographical locations, significant efforts are still devoted to multiphase reaction engineering as witnessed by continued success of the ISCRE conferences and 122 worldwide contributions to the Festschrift in I&EC Research [129,130]. An interesting indication of recent trends in multiphase reaction engineering in terms of research activity location is provided by the data shown in Figure 3. This shows the geographical distribution of the 120 or so technical contributions to the recent 12th International Conference on Gas-Liquid and Gas-LiquidSolid Reactor Engineering [131]. The results suggest that contributions originating from Asia are dominant since they constitute about 43% of the total number of contributions, which is then followed by contributions from Europe at 34% and North America at 20%. This trend is generally opposite to that observed 20 or so years ago when contributions from North America were leading and it had a more healthy and vivid research effervescence. Additional data collection and analysis would be required Current Opinion in Chemical Engineering 2015, 9:49–58
Figure 3
North America 20% Australia 4%
Europe 34%
Asia 42% Current Opinion in Chemical Engineering
Distribution of contributions to the 12th international conference on gas–liquid and gas–liquid–solid reactor engineering. The total number of presentations was ca. 120.
to determine if this trend is just a relocation of research activity or if total global effort in the discipline is stationary, growing, or in a state of decline. Technology transfer from academia to industrial practice and advancement of the various challenges outlined in the Vision 2020 Reaction Engineering Roadmap [61] still remain as notable opportunities in the future.
Acknowledgements The able assistance of Onkar Manjrekar and Boung Wook Lee in preparation of the original and revised manuscript is greatly appreciated.
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76. RB: Solids Flow Mapping in Gas–solid Risers. Washington University; 2005. 77. Heindel TJ: A review of X-ray flow visualization with applications to multiphase flows. J Fluids Eng-Trans ASME 2011:133. This paper provides a review of the current status of X-ray flow visualization and details various X-ray flow visualization methods that can provide qualitative and quantitative information about the characteristics of complex multiphase flows. 78. Chen P, Gupta P, Dudukovic MP, Toseland BA: Hydrodynamics of slurry bubble column during dimethyl ether (DME) synthesis: gas–liquid recirculation model and radioactive tracer studies. Chem Eng Sci 2006, 61:6553-6570. 79. Degaleesan S: Turbulence and Liquid Mixing in Bubble Columns. Washington University; 1997:. vol D. Sc. 80. Degaleesan S, Dudukovic M, Pan Y: Experimental study of gasinduced liquid-flow structures in bubble columns. AIChE J 2001, 47:1913-1931. 81. Degaleesan S, Dudukovic MP: Liquid backmixing in bubble columns and the axial dispersion coefficient. AIChE J 1998, 44:2369-2378. 82. Degaleesan S, Roy S, Kumar SB, Dudukovic MP: Liquid mixing based on convection and turbulent dispersion in bubble columns. Chem Eng Sci 1996, 51:1967-1976. 83. Gupta P, Al-Dahhan MH, Dudukovic MP, Toseland BA: Comparison of single- and two-bubble class gas-liquid recirculation models – application to pilot-plant radioactive tracer studies during methanol synthesis. Chem Eng Sci 2001, 56:1117-1125. 84. Gupta P, Ong B, Al-Dahhan MH, Dudukovic MP, Toseland BA: Hydrodynamics of churn turbulent bubble columns: gas–liquid recirculation and mechanistic modeling. Catal Today 2001, 64:253-269. 85. Salciccioli M, Stamatakis M, Caratzoulas S, Vlachos DG: A review of multiscale modeling of metal-catalyzed reactions: mechanism development for complexity and emergent behavior. Chem Eng Sci 2011, 66:4319-4355. 86. Vlachos DG: A review of multiscale analysis: examples from systems biology, materials engineering, and other fluid–surface interacting systems. In Advances in Chemical Engineering, Vol 30. Edited by Guy BM. Academic Press; 2005: 1-61. An overview of deterministic, continuum models and discrete, particle models is then given and the importance of systems-level tools such as sensitivity analysis, parameter estimation, optimization, control, model reduction, and bifurcation in multiscale analysis is underscored. 87. Deen NG, Annaland MVS, Van der Hoef MA, Kuipers JAM: Review of discrete particle modeling of fluidized beds. Chem Eng Sci 2007, 62:28-44. This paper reviews the use of discrete particle models (DPMs) for the study of the flow phenomena prevailing in fluidized beds. 88. van der Hoef MA, Annaland MvS, Deen NG, Kuipers JAM: Numerical simulation of dense gas-solid fluidized beds: a multiscale modeling strategy. Annual Review of Fluid Mechanics. 2008:47-70:. Annual Review of Fluid Mechanics, vol 40. 89. Tang Y, Peters EAJF, Kuipers JAM, Kriebitzsch SHL, van der Hoef MA: A New Drag Correlation from Fully Resolved Simulations of Flow Past Monodisperse Static Arrays of Spheres. Aiche Journal 2015, 61:688-698. 90. Kamali MR, Gillissen JJJ, van den Akker HEA, Sundaresan S: Lattice-Boltzmann-based two-phase thermal model for simulating phase change. Physical Review E 2013, 88:033302. 91. Mousazadeh F, van Den Akker HEA, Mudde RF: Direct numerical simulation of an exothermic gas-phase reaction in a packed bed with random particle distribution. Chemical Engineering Science 2013, 100:259-265. 92. Yang X, van Ommen JR, Mudde RF: Comparison of genetic algorithm and algebraic reconstruction for X-ray tomography in bubbling fluidized beds. Powder Technol 2014, 253:626-637. www.sciencedirect.com
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93. Hooshyar N, van Ommen JR, Hamersma PJ, Sundaresan S, Mudde RF: Dynamics of single rising bubbles in neutrally buoyant liquid-solid suspensions. Phys Rev Lett 2013, 110:244501. 94. Motegh M, Cen J, Appel PW, van Ommen JR, Kreutzer MT: Diffusion limitations in stagnant photocatalytic reactors. Chem Eng J 2014, 247:314-319. 95. Motegh M, van Ommen JR, Appel PW, Kreutzer MT: Scale-up study of a multiphase photocatalytic reactor—degradation of cyanide in water over TiO2. Environ Sci Technol 2014, 48:15741581. 96. Hoang DA, Haringa C, Portela LM, Kreutzer MT, Kleijn CR, van Steijn V: Design and characterization of bubble-splitting distributor for scaled-out multiphase microreactors. Chem Eng J 2014, 236:545-554. 97. Fox RO: Computational Models for Turbulent Reacting Flows. Cambridge University Press; 2003. This book gives overview of the current state of the art in computational models for turbulent reacting flows carefully analyzes the strengths and weaknesses of the various techniques described. 98. Fox RO: CFD models for analysis and design of chemical reactors. In Advances in Chemical Engineering, vol 31. Edited by Guy BM. Academic Press; 2006:231-305. The article summarizes current state of art of CFD models for design and analysis of chemical reactors. 99. Buwa VV, Ranade VV: Dynamics of gas-liquid flow in a rectangular bubble column: experiments and single/ multi-group CFD simulations. Chem Eng Sci 2002, 57: 4715-4736. 100. Dixon AG, Nijemeisland M, Stitt EH: Packed tubular reactor modeling and catalyst design using computational fluid dynamics. In Advances in Chemical Engineering, Vol 31. Edited by Guy BM. Academic Press; 2006:307-389. The article chapter presents the application of CFD to the simulation of three-dimensional interstitial flow in packed tubes, with and without catalytic reaction.
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ScienceDirect Scale-up and multiphase reaction engineering MP Dudukovic´1 and PL Mills2 Successful scale-up of new multiphase reactions from the laboratory into practical processes is important to all sectors of the process industry. Business demands that process technologies involving molecular transformations maintain high profitability and operate safely within existing environmentally regulations. Current societal expectations and regulations require that all process technology should be environmentally responsible [1]. One key question to be answered is whether or not these expectations can be met in the foreseeable future with the current approaches to scale-up and technological workforce. In addition, advances in chemistry, physics, materials, and biology will continue to generate new potential reaction pathways for more efficient utilization of nonrenewable and renewable resources. Another key question is whether the current methods for process scale-up incorporate the relevant scientific advances to ensure ‘green technologies’, or are they just extensions of previous largely empirical approaches having limited utility and reliability? Evidence suggests that only a science-based scale-up methodology can substantially reduce the risk of new process commercialization and provide reliable estimates of both profitability and environmental impact. We review briefly here the historical approach to scale-up and opine on the challenges of implementing improved approaches. Addresses 1 Chemical Reaction Engineering Laboratory (CREL), Energy, Environmental and Chemical Engineering Department (EECE), Washington University in St. Louis (WUStL), St. Louis, MO 63130-4899, USA 2 Department of Chemical and Natural Gas Engineering, Texas A&M University-Kingsville, Kingsville, TX 78363-8202, USA Corresponding author: Dudukovic´, MP ([email protected], [email protected])
Current Opinion in Chemical Engineering 2015, 9:49–58 This review comes from a themed issue on Reaction engineering and catalysis Edited by Marc-Olivier Coppens and Theodore T Tsotsis
http://dx.doi.org/10.1016/j.coche.2015.08.002 2211-3398/Published by Elsevier Ltd.
Introduction Multiphase chemistries involving reactions between gases, liquids, and solid reactants that are catalyzed by homogeneous organometallic complexes [2], heterogeneous www.sciencedirect.com
inorganic solids [3] or biocatalysts [4–6] are the basis for nearly all processes used to manufacture organic and inorganic intermediates and end-use products, such as fuels and chemicals from petroleum feed-stocks [7], bulk commodity, specialty and fine chemicals [8], medicinal intermediates and pharmaceuticals [9,10], and various polymers [11–13]. End-of-pipe processes for environmental remediation also rely upon multiphase catalyzed chemistries for emissions control [14–16]. Various handbooks provide reviews of the science and technologies associated with heterogeneous catalysis [17], homogeneous catalysis [18], industrial biocatalysts [19] and multiphase polymers [20]. In addition, several monographs [21,22] also review the scope of industrial catalysts and processes, and consider their environmental footprint [1]. These collective works suggest that catalyst science and technology is a critical component of every industrial sector and also plays a major role in enabling existing global lifestyles. Hence, the practical catalytic reactor that converted crude raw materials into useful products should be given notable attention. To maintain the lead over their competition, catalyst vendors must provide replacement catalysts having improved measures of performance, such as higher activity, better selectivity, extended life, lower pressure drop, better mechanical integrity, improved thermal stability, and reduced catalyst fines with competitive pricing. The approaches used for scale-up of catalyst recipes and the challenges encountered with evaluating their performance in commercial reactors are proprietary, although information is sometimes reported when a notable success or a disaster occurs. Anecdotal evidence suggests that old scale-up rules based on empiricism prevail in practice, since little or no investment has been made in adding more science to scale-up. In addition, utilization of an improved catalyst by various customers across various reactor configurations for a given technology allows the catalyst supplier to assemble a significant data base on reactor performance that can be used in look-up tables to make empirically-based suggestions on how to handle particular process situations. Most replacement catalysts in an existing process lead only to incremental improvement in practical reactor performance, so the risk is much smaller when compared to a new process. Invention of new or improved catalysts for more economical processes with a reduced environmental footprint [23] is a leading research topic. Examples of catalytic technologies that are receiving increased emphasis include those that: (1) produce cleaner energy sources from various feedstocks [24]; (2) create higher quality lubricants [25,26]; (3) capture, control, or utilize greenhouse gases [27,28]; (4) convert Current Opinion in Chemical Engineering 2015, 9:49–58
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natural gas or bio-based methane gas to chemicals and fuels [29]; (5) minimize environmental impact or reduce the environmental footprint [30–32]; (6) transform biobased feedstocks to either hydrogen or targeted organic chemicals [33–35]; (7) gasify biomass for production of either hydrogen [36], synthesis gas [37], chemicals and other products [38]; and (8) generate power using fuelcells [39]. One conclusion that emerges is that the likelihood of successful translation and scale-up of these new catalytic technologies from laboratory research to commercial-scale processes is notably enhanced when reaction engineering principles are closely integrated with other ongoing science, engineering and business development activities [40,41].
Reactor scale-up: current status The state-of-the-art of multiphase reaction engineering (MRE) has been the subject of various reviews over the past 30 or so years [40,42,43,44,45,46–51,52,53,54]. Although the installed cost of catalytic process reactors typically account for about 5–15% of the total capital, reactor performance always dictates the cost of downstream product refining as well as the flow rates and composition of recycle streams. A successful commercial catalytic process will retain favorable performance
metrics as the catalytic chemistry upon which it was based is translated from laboratory reactors to commercial practice [55]. Classic monographs on chemical process scale-up [56,57] describe customary practices, which are based on both heuristics and engineering-based models. We focus here on the evolution of reactor scale-up practices that allow increased incorporation of sound scientific and engineering principles. The key phenomena that affect multiphase reactor performance occur on a large range of length and temporal scales and are illustrated in Figure 1 [6]. These include molecular-scale transport-kinetic interactions, eddy or particle-scale transport processes, and fluid flow patterns, hydrodynamics and transport on the reactor scale. These phenomena are subject to events that occur on the process scale, such as disturbances in reactor inlet flow rates, specie compositions, temperatures, pressures, and reactor heat transfer systems, to name a few. The rates for these phenomena can be quantitatively described at the indicated length and temporal scales using models that start from an intuitive basic level, such as empirical power-law reaction kinetic models, and then evolve to a more sophisticated level based on fundamental
Figure 1
REACTOR PERFORMANCE = f (input & operating variables; rates; mixing pattern) Eddy/particle Scale
Reactor scale
L (Cb) = η R (Cb,Tb)
feed,Q
Molecular Scale
T , C, P
Lh (Tb) = ∑ (– ΔHRj )ηjRj (Cb,Tb)
product, Q
j
T , C0, P0
η = f (kinetics;transport )
MOLECULAR SCALE (KINETIC RATE FORMS)
10–10 m
10–16 (s) Strictly Empirical
Mechanism Based
Elementary Steps
EDDY OR PARTICLE SCALE (INTER & INTRA PHASE TRANSPORT RATES) Empirical
Micromixing Models
DNS / CFD
REACTOR SCALE (RESIDENCE AND CONTACT TIME, PHASE DISTRIBUTIONS, AND INTERACTION RATES) PFR/CSTR
Axial Dispersion
Phenomenological Models
CFD
PROCESS SCALE (EFFECT OF MODE OF OPERATIONS, ON SCALE-UP AND SAFETY)
102 m
Steady State Balances
Dynamic Models for Control & Optimization
104 (s)
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Key phenomena that affect reactor performance. Current Opinion in Chemical Engineering 2015, 9:49–58
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MRE via advanced characterization techniques Dudukovic´ and Mills 51
principles, such as those based upon detailed micro-kinetics [58,59]. A robust scale-up methodology relates the key metrics or observables of reactor performance (e.g., reactant conversion, product selectivity, volumetric productivity or space-time yield, energy efficiency and environmental footprint), as defined below in Table 1, to rates of these multi-scale transport-kinetic interactions. The modern reaction engineering model combines sub-models from the various scales through the various coupling variables [45,60]. This approach should be followed as the targeted catalytic reaction is conducted in laboratory, pilot, demonstration and commercial-scale reactor configurations. Mathematical models for larger-scale reactors, such as those that are part of integrated pilot plants, demonstration-scale systems and commercial plants, should preferably account for reactor process dynamics since these processes are inherently transient in nature, and reactor start-ups and shut-downs are both a critical aspect of reactor operations. In addition to satisfying mass, energy and momentum balances, these models incorporate the state-of-the art information on the reaction kinetics, transport processes, fluid flow patterns, and hydrodynamics of the various reaction fluids.
a sulfuric acid contact convertor contained more than 20 fitted parameters. Evaluation of process economic potential and environmental impact is performed using selected algorithms, such as WAR [63], which have the same mass conservation basis as above cited simulators. These empirical models do not incorporate the current state of science that describes the multi-scale phenomena shown jointly in both Figure 1 and Table 1.
The goal of developing a multi-scale reactor model that accounts for the phenomena described above has been rarely achieved for most reactors in commercial practice based upon our combined 70+ years’ experience. In fact, many operating processes do not even have kinetic models for prediction of reaction rates. Simpler approaches are often used, such as fitting nonlinear empirical models based upon plant reactor data that describe the reactor performance phenomena within defined operating process windows. These empirical models are then embedded as module into a chemical process simulator, such as Aspen Plus, Aspen HYSYS, Design II for Windows, ProMax, or SuperPro Designer [61]. In some cases, the available reactor models in these simulators, which are based upon ideal plug-flow or ideal stirred tanks, are adapted by using plant reactor performance data to extract the observed rates. An example of this empirical approach is described by Fariss [62] whose rate model for SO2 oxidation to SO3 used to describe the performance of
The Vision 2020 Reaction Engineering Roadmap [61], which was published by the AIChE in 2001, was part of an industry-wide effort to create a blueprint of the research and development that was necessary to achieve long-term industry goals. It defined linkages between key research needs identified in the following four cross-cutting areas: (1) experimental tools; (2) modeling and property estimation; (3) sensors; and (4) systems integration. It also specified the time frame for achieving the targeted results. Inspection of the indicated long-term (>10 year) goals listed in Table 1 of the report suggests that none have really been reached. The lack of progress in reaction engineering design and scale-up was recently discussed by Stitt et al. [69]. It was pointed out that while notable advances have been achieved in computational speed, due to advances in computer hardware and algorithms, the models being utilized for reactor and process design are still rather primitive! In other words, advances in science are not reflected in conceptual and mechanistic
Evolution of models based on fundamentals and the development of specialized experimental tools to support each of the temporal-spatial scale-dependent phenomena shown in Figure 1 continue to generate improved insight and understanding [64,65,66,67,68]. However, integration of these models into predictive models for reactor design and scale up is still lagging [60]. Hence, in spite of advances in science and computational techniques, the methods and models available for reactor scale-up and design applicable to realistic process conditions have not advanced much in the new millennium, and may have even regressed in some instances. This lack of traction in technology advancement was highlighted in a perspective article in Science [44].
Table 1 Key metrics of reactor performance Reactor volumetric productivity Rate of product generation per unit time Average process rate for the reactor Average reactor process rate is a function of Kinetic rate, which in turn depends on catalyst turnover number and local temperature and composition and their distributions Effect of local mass and heat transfer on the intrinsic kinetic rate Reactor flow and fluid contacting patterns, which affect the composition-temperature field in the reactor Reactor selectivity (moles of desired product produced)/(moles of undesired products made) is determined by kinetics, local transport effects and global contacting pattern.
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models used for reactor scale-up or design. The reaction engineering community was challenged to embark on the replacement of heuristics with the proper use of multiscale reaction engineering methodology leading to a quantitative description of kinetics and transport in reactor design, scale-up and operation. Most importantly, the need for vigorous validation of models on all scales with properly designed and executed experiments was emphasized. This science-based approach is what all of the reaction engineering community championed as the right path to follow already decades ago! The key focus areas were also well-documented in 1999 by the 46 industrial and academic experts who contributed to the Vision 2020 Reaction Engineering Roadmap report. We opine here as to why we departed from this goal, and what should be done to change the direction of this highly undesirable situation into a positive one.
Challenges in implementing science-based modern scale-up methodology Past developments that impacted practice
Reactor scale-up effort over half a century ago, when the process industries were undergoing significant growth, involved a large number of skilled professionals, technical support and large-scale facilities to support it. Company management possessed a strong technical backgrounds and commitment to a long-term pursuit of science-based scale-up. Faster digital computers and new numerical techniques made possible the solution of previously intractable conservation equations for single and multiphase flows in complex geometries culminating in the present CFD algorithms [58,59]. The realization that the reaction engineering methodology offered considerable rewards when related to industrial practice led to cooperative efforts between academics and industry. This effort was financed by industrial support and grants from the federal government, for example, precompetitive research in our Chemical Reaction Engineering Laboratory (CREL) was promoted since 1974 by many diverse industrial sectors [70]. It produced generic tools for science and engineering-based scale-up and modeling that could be used in many technologies. It also produced many graduates that collectively represented a strong reaction engineering workforce and individually accomplished notable technical advances in a host of diverse industries [70]. Validation of new generic scale-up concepts on cold flow units was often shared in joint ventures. Appropriate refinements for specific processes were then performed by individual companies and kept as proprietary. From the 1980s onward, the management of many technology companies embraced the more immediate higher returns by licensing their existing processes in the rapidly developing parts of the world. This growth hardly generated any new innovations in the process industries. Instead, the ‘Best Available (process) Technology’ or BAT [71] spread globally, which was not encouraging the use of Current Opinion in Chemical Engineering 2015, 9:49–58
fundamentals. The departure from the rational approach was further accelerated by universities changing both the names and curricula of chemical engineering departments to pursue applied science in perceived more lucrative fields of biology and nano-materials. This significantly decreased the production of graduates that were exposed to the complexities of process synthesis and scale-up interactions depicted in Figure 1. Thus, the qualified manpower base in industry for performing and managing science-based scale-up was greatly diminished. Scale-up of new processes sometimes resulted in failures, although these were not disclosed, or was abandoned as too risky. Three examples involving a trickle-bed reactor, a liquid– solid riser, and a gas–solid riser were recently presented by the authors that describe the pitfalls of using current scale-up based on heuristics [60]. The key lessons learned are: (1) trickle beds that are scaled-up based on constant liquid-hourly space velocity (LHSV) can lead to over a 50% loss of performance for gas-limited reactions and unanticipated hot spots when a much more active catalyst is used, thereby leading to excessive temperatures and loss of selectivity; (2) the available information on solids flow patterns in liquid–solid risers was quite meager, which lead to wrong assumptions on an accurate model representation. Hence, an accurate riser design was not possible prior to the work of Roy et al. [48,72,73]; and (3) the solids residence time distribution in gas-solid risers was never measured properly until the work of Bhusarapu [74,75,76]. Hence, mean residence times and variations of contact time with reactor scale could not have been predicted properly. It is noteworthy that proper experimental techniques were needed to validate the emerging physically based models [65]. Now, in 2015 and the foreseeable future, companies that have abandoned or neglected the development of a core competency in reaction engineering and in process sciences face a serious shortage of qualified manpower needed for improvement of existing process technologies and scale-up of new ones. It is not evident, at least in certain geographical locations, how the required formal education in reaction engineering fundamentals and subsequent development of expertise through practice will occur so that the required technology leadership to create innovative processes will be developed. Renewed motivation for experimental validation
Noninvasive techniques for measurement of multi-phase flow parameters provide valuable information needed for validation of CFD codes [65,77], especially on larger-scale systems. For example, research on churn-turbulent bubble columns at CREL led to the ability to predict liquid residence time distribution and back-mixing for a number of processes executed in pilot-scale systems, such as the Fischer–Tropsch hydrocarbon synthesis, dimethyl ether and methanol synthesis [78–84]. The three examples described above on the shortcomings of reactor scale-up www.sciencedirect.com
MRE via advanced characterization techniques Dudukovic´ and Mills 53
Figure 2
CARPT & CT applications
CARPT
CT
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G
G
S
L
S
S
G G
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Risers
Bubble Column
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G L
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Stirred Tanks Current Opinion in Chemical Engineering
Illustration of the Computer-Automated Radioactive Particle Tracking (CARPT) and Computer Tomography (CT) and their application to various multiphase reactors.
are the consequence of the fact that after a century of using the common reactor types illustrated in Figure 2, industry at present does not have state-of-the-art reactor models for prediction of their performance. Hence, the academic and industrial reaction engineering community should work jointly to develop proper predictive models. This effort involves computing all pertinent parameters on various reactor scales with experimental validation of emerging mechanistic models suing both cold-flow units and hot process systems when possible. Fundamentally-based reactor models should then be used in various technologies where these reactors are employed. These efforts would facilitate reducing the gap between academia and industry and enable more efficient use of available resources.
companies that provide clear evidence of improved environmental performance that was predicted by the models which they had developed. This requires judging each process based on its technical merits and environmental impact, and giving better tax credits for use of non-fossil and non-food based sources for feedstocks and energy. We should also engage in a campaign of educating our profession and the public of the benefits of the long-term planning and use of multi-scale process synthesis. The change in approach to process scale-up must be done soon before the pool of technical people with the required knowledge base and experience shrinks below a critical mass.
Concluding remarks Nontechnical challenges One key challenge is to change the perception that pursuing short-term research goals will lead to long-term profitability and sustained business growth. Long-term science-based research on process synthesis should be rewarded. For example, tax incentives should be given to www.sciencedirect.com
Our focus here was on improvements needed in the industrial practice of scale-up. However, proper credit was not given to many in academia that still hold the reaction engineering banner high and continue to develop better foundations for future reactor scale-up by focusing on a specific scale of scrutiny or a specific process. For Current Opinion in Chemical Engineering 2015, 9:49–58
54 Reaction engineering and catalysis
example, impressive modeling advances on all scales are pursued by Vlachos’s group at Delaware [85,86] and Kuipers’ group at Eindhoven [87,88,89]. Multi-scale physics models and measurements are pursued by various groups at Delft (Van den Akker, Mudde, Van Ommen, Kreutzer) [90–96] and others. There is considerable expertise and progress in reactive multiphase flows (e.g., Fox at Iowa State [97,98], Ranade at NCL [68,99]), flows in tubular packed bed (e.g., Dixon at WPI [100,101,102]) particulate flows, risers, fluidized bed (e.g., Sundaresan at Princeton [103–105], Sinclair at Florida [106], Van den Akker at Limerick [90,107], Hrenya at U of Colorado [108,109], and Li at Beijing [110,111,112,113]). There are also exciting developments in novel, nature inspired contactors (Coppens at London [114–116,117]), in membrane reactors (Tsotsis at USC [118,119]) and microreactors (Jensen at MIT [120–122]). Scale-up of the important new technology for chemical looping is being pursued at OSU by Fan [123,124,125], and the use of expandable solvents by Balasubramanian at CEBC Kansas at [126,127,128]. However, only a small number of these efforts are directly focused on industrial scale-up needs. In addition, they seldom combine novel computational techniques with validation of key parameters under practical process conditions. Finding a way to integrate these efforts in academia into the development of a comprehensive and validated model for various existing reactor types (Figure 2) would go a long way in pushing the scale-up in the right direction. It will also produce graduates that can implement these models within various companies on diverse technologies and later work on proper modeling of the new reactor types. These aspects are clearly an area of future development and also an important part of the Vision 2020 Reaction Engineering Roadmap [61]. Finally, it should also be noted that despite decreased financial support for reaction engineering in certain geographical locations, significant efforts are still devoted to multiphase reaction engineering as witnessed by continued success of the ISCRE conferences and 122 worldwide contributions to the Festschrift in I&EC Research [129,130]. An interesting indication of recent trends in multiphase reaction engineering in terms of research activity location is provided by the data shown in Figure 3. This shows the geographical distribution of the 120 or so technical contributions to the recent 12th International Conference on Gas-Liquid and Gas-LiquidSolid Reactor Engineering [131]. The results suggest that contributions originating from Asia are dominant since they constitute about 43% of the total number of contributions, which is then followed by contributions from Europe at 34% and North America at 20%. This trend is generally opposite to that observed 20 or so years ago when contributions from North America were leading and it had a more healthy and vivid research effervescence. Additional data collection and analysis would be required Current Opinion in Chemical Engineering 2015, 9:49–58
Figure 3
North America 20% Australia 4%
Europe 34%
Asia 42% Current Opinion in Chemical Engineering
Distribution of contributions to the 12th international conference on gas–liquid and gas–liquid–solid reactor engineering. The total number of presentations was ca. 120.
to determine if this trend is just a relocation of research activity or if total global effort in the discipline is stationary, growing, or in a state of decline. Technology transfer from academia to industrial practice and advancement of the various challenges outlined in the Vision 2020 Reaction Engineering Roadmap [61] still remain as notable opportunities in the future.
Acknowledgements The able assistance of Onkar Manjrekar and Boung Wook Lee in preparation of the original and revised manuscript is greatly appreciated.
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