Dimitrios Gerogiorgis | University of Edinburgh (original) (raw)

Papers by Dimitrios Gerogiorgis

Continuous Pharmaceutical Manufacturing (CPM) is a rapidly expanding research field with growing ... more Continuous Pharmaceutical Manufacturing (CPM) is a rapidly expanding research field with growing industrial importance: challenging the current batch production paradigm, it has a documented potential to deliver key cost, efficiency and environmental benefits. Ibuprofen, the potent painkiller, and artemisinin, a highly effective anti-malarial drug, have been identified as promising CPM candidates, and steady-state flowsheet models have been developed on the basis of published continuous organic synthesis pathways. Reactor design has been conducted using original kinetic parameter estimation results. A comparative economic analysis via published recoveries has computed performance indices which indicate that both CPM designs exhibit high economic potential, even if conservative profit and climate estimates are used to derive capital and operating costs. More detailed technoeconomic analyses can facilitate quicker CPM implementations.

Smart drilling fluids containing Fe3O4 nanoparticles have advantages toward increasing the hydrau... more Smart drilling fluids containing Fe3O4 nanoparticles have advantages toward increasing the hydraulic efficiency of drilling operations in a variety of reservoir environments. Exploring and optimizing the rheological behavior of such new drilling fluids is critical, implying direct and significant economic savings in developing new oil and gas fields. A experimental campaign analyzing the rheology of a bentonite-based fluid produced a new multiparametric dataset, considering a wide range of realistic reservoir conditions. Non-Newtonian behaviour is confirmed by yield stress computation for all these cases. Heating and rotation induce temperature and concentration gradients at drilling depth: it is hence essential to obtain an accurate but also versatile multivariate rheological model, which will enable viscosity prediction for the analyzed and other similar drilling fluids. The enhanced Herschel-Bulkley model is developed on a multiplicative assumption, postulating and analysing candidate equations which quantify the effect of shear rate, temperature and nanoparticle concentration on drilling fluid shear stress and viscosity. Parameter estimates have been subsequently determined via systematic optimisation, using statistical metrics to quantify and compare uncertainty and predictive potential. The trivariate shear stress and viscosity models proposed are similar in form: each requires six parameters used to combine a Herschel-Bulkley yield stress expression, an Arrhenius exponential of temperature and a linear model for nanoparticle concentration.

Fermentation is the central, most important unit operation in alcoholic beverage manufacturing an... more Fermentation is the central, most important unit operation in alcoholic beverage manufacturing and has already been studied by means of first-principles dynamic models which explicitly consider temperature effects and employ parameterisations obtained using industrial beer brewing campaign data. Nevertheless, the precise effect of initial conditions on beer quality and flavour has not been documented. Multi-objective optimisation encompasses ethyl alcohol maximization and batch duration minimisation, but must also quantitatively monitor the crucial flavour components (Rodman & Gerogiorgis, 2015). Dynamic simulation and visualisation of the key (ethyl alcohol, ethyl acetate, diacetyls) concentrations is pursued for varying initial condition (sugar concentration, pitching rate, active yeast fraction) parameters, and hundreds of thousands of possible temperature manipulation profiles over the entire brewing horizon. Feed sugar content obviously governs attainable alcohol concentration: what is not evident is that pitching rate is a very efficient manipulation, in contrast to the weak effect of initial active yeast fraction.

Continuous Pharmaceutical Manufacturing (CPM) is a strategy which can secure the economic competi... more Continuous Pharmaceutical Manufacturing (CPM) is a strategy which can secure the economic competitiveness hampered by the innate drawbacks of batch production: this mature technology is the current norm for therapeutic molecules, but its key advantages are frequently outweighed by poor mixing and heat transfer, limited scalability and low Overall Equipment Effectiveness (OEE). Moreover, in an environment of expanding economic pressure from generics manufacturers, ever-increasing R&D costs and high societal demand for sustainability and waste minimisation, systematic evaluation of continuous process alternatives in early design stages is critical toward ensuring feasibility and profitability. Artemisinin is an essential anti-malarial substance in high global demand, with many recent advances toward its continuous synthesis. This paper presents a comprehensive analysis of a wide range of solvents for continuous artemisinin recovery. Continuous crystallisation has been simulated using predictive UNIFAC modelling for artemisinin solubility; several technical and green chemistry metrics (product recovery, E-factor) have then been employed in order to comparatively evaluate solvent performance and elucidate relative advantages. Ethyl acetate emerges as a promising crystallisation candidate antisolvent: with high potential product recoveries and good E-factor values, it has a potential to enhance process sustainability via increased material efficiency and reduced waste generation. The clear identification of strong CPM advantages indicates the merit of investigating solvent compatibility in upstream (continuous flow chemistry) as well as downstream (product formulation) operations, toward pursuing the global optimisation of novel, integrated CPM processes.

Fermentation is an essential step in beer brewing: when yeast is added to hopped wort, sugars fer... more Fermentation is an essential step in beer brewing: when yeast is added to hopped wort, sugars ferment into ethanol and higher alcohols. Progression is highly sensitive to the temperature manipulation invoked, influencing batch time and product quality. A novel computational implementation of a published kinetic model has been produced, rapidly generating temperature manipulations and simulating the operation of each candidate profile. Ethanol and key harmful by-product (diacetyl, ethyl acetate) concentrations are monitored in order to minimize fermentation time while ensuring product quality is maintained. Visualisation of the entire operational envelope clearly illustrates Pareto fronts and trade-offs among these design objectives. Comparing these simulation results with those of an industrial operational profile reveals that batch time can be reduced by as much as 15 hours when an acceptable sacrifice is made to by-product concentrations.

Drilling fluids serve many applications in the oil-drilling process, including the removing of cu... more Drilling fluids serve many applications in the oil-drilling process, including the removing of cuttings, drill bit cooling and the prevention of fluid transfer to and from the rock strata. With the addition of nanoparticles it is possible to facilitate in-situ control of the drilling fluid rheology, increasing the hydraulic efficiency of drilling campaigns and reducing costs in a variety of reservoir environments. This paper proposes a first-principles approach to the rheology of smart drilling fluids containing Fe 3 O 4 nanoparticles which have shown advantages to increasing drilling efficiency in a variety of reservoir environments. The model for shear stress is developed based on a force balance between the Van der Waals attractions of monodispersed Fe 3 O 4 nanoparticle spheres. The model for viscosity is developed by considering the force required to maintain the nanoparticles in suspension being equal to the drag force as calculated for Stokes flow approximation about a sphere. Both models had a candidate equation for interparticle distance under increasing shear rate. A bivariate model described the rheological effects of shear rate and Fe 3 O 4 nanoparticle concentration with a high predictive potential (R 2 τ(γ̇ ,ϕ) = 0.993, R 2 µ(γ̇ ,ϕ) =0.999). The trivariate model accounts for temperature with high predicative potential (R 2 τ(γ̇ ,ϕ,T) = 0.983, R 2 µ(γ̇ ,ϕ,T) =0.986). Heating effects and low nanoparticle concentrations increase standard correlation error.

Increasing Research and Development (R&D) costs, growing competition from generic manufacturers a... more Increasing Research and Development (R&D) costs, growing competition from generic manufacturers and dwindling market introduction rates for novel drug products bolster the efforts of pharmaceutical firms to secure competitiveness by investigating Continuous Pharmaceutical Manufacturing (CPM). The present paper explores the CPM of two key Active Pharmaceutical Ingredients (APIs), ibuprofen and artemisinin: cost savings and material efficiency benefits are evaluated for CPM vs. batch processing, with two continuous options for each API. Capital Expenditure (CapEx) savings of up to 57.0% and 19.6% and corresponding Operating Expenditure (OpEx) savings of up to 51.6% and 29.3% have been determined for ibuprofen and artemisinin, respectively. Total projected cost savings for a 20-year plant lifetime can reach 54.5% and 20.1%, respectively. Environmental (E)-factors (mass of waste generated per unit mass of product) of 43.4 (for ibuprofen) and 12.2 (for artemisinin) have been computed, indicating environmental and material efficiency advantages for these conceptual continuous pharmaceutical processes.

The global pharmaceutical industry faces high R&D, regulatory and cost pressure which can be alle... more The global pharmaceutical industry faces high R&D, regulatory and cost pressure which can be alleviated by the advent of Continuous Pharmaceutical Manufacturing (CPM). Embarking upon demonstrating and commissioning continuous processes is not trivial: judicious product selection and process design is quintessential for viable investments. Technological as well as economic considerations must be inseparably combined, but a quantitative method for elucidating only the most viable candidates has yet to emerge. This study illustrates how systematic statistical analysis can support business decisions and process R&D for the synthesis and design of continuous pharmaceutical processes. A systematic statistical evaluation of UK economic data has been performed to identify viable drug substances (DS) and drug products (DP) for continuous manufacturing. Product classification and ranking is employed to select those with the highest demand, and statistical hypothesis testing explores causality and correlations of key parameters. Molecular weight and complexity have been correlated with trade and value statistics, indicating that amides, lactones, antibiotics and hormones have high CPM potential.

Conventional perlite expansion suffers shortcomings which compromise its viability and the adhere... more Conventional perlite expansion suffers shortcomings which compromise its viability and the adherence of expanded perlite to modern high-quality technical specifications. A new perlite expansion process has been designed and a vertical electrical furnace for perlite expansion has been constructed in our laboratory to overcome drawbacks. Having already accomplished the production of various expanded perlite grades for a range of different applications, it is important to explore the complete state space of product quality against key manipulated variables; identifying optimal experimental condition ranges thus ensures technically and economically optimal process operation. Response Surface Methodologies (RSM) have an long track record of contribution to substantial improvements in advanced chemical and material products and processes. Their fundamental principle is the systematic exploration and statistical correlation of input (conditional) and output (response) variables with respec...

Expanded perlite has outstanding thermal and acoustic insulating properties and is widely used in... more Expanded perlite has outstanding thermal and acoustic insulating properties and is widely used in the manufacturing and construction industries. The conventional perlite expansion method has certain disadvantages which affect the quality of expanded perlite products, thus limiting their performance and range of applications. A new perlite expansion process has been designed and a vertical electrical furnace for perlite expansion has been constructed in our laboratory in order to overcome these drawbacks, enabling precise control of experimental conditions in order to prescribe the temperature profile and residence time within the new heating chamber. A novel dynamic model for perlite grain expansion has been developed and validated so as to study and optimize the new furnace operation. Perlite ore origin, size distribution and water content are key parameters affecting expanded perlite quality. Moreover, air feed flow rate and temperature, as well as the imposed wall temperature distribution along the heating chamber are experimentally known to have a profound, measurable effect on grain residence time and expansion. A detailed sensitivity analysis has been performed so as to quantitatively understand the effect and relative importance of all foregoing operational parameters on macroscopic furnace operation (perlite particle velocity and temperature evolution) as well as on inaccessible microscopic characteristics (internal steam bubble pressure and size). Perlite grain radius and expansion ratio are probed in detail as a function of time, and furnace operation can be tuned vs. feed variation toward optimal product quality. Particle critical characteristics along trajectories as well as final particle size plots are presented; also, optimal furnace operating condition ranges are determined for variable initial size and water content.

Food and Bioproducts Processing, 2016

Oil and gas production is the cornerstone of the modern petrochemical industry, and its upstream ... more Oil and gas production is the cornerstone of the modern petrochemical industry, and its upstream as well as downstream processing provides many challenges to the process modeling, optimization and control areas. Mixed-integer optimization is a research field with a strong implementation record, having already been used to solve a wide spectrum of crude oil production, transport, distribution, planning and scheduling problems. Production optimization challenges are however perplexed by multiphase flow of oil, gas and water in the sub-surface circuits: the respective elements (reservoirs, wells) induce complexity in oil and gas transport which can only be handled suboptimally by use of linearized approximations of true pressure-flowrate curves. This paper addresses the problem of oil production maximization from a particular oilfield with several oil wells, all connected to one production platform and operating assisted by gas injection (secondary extraction). The proposed approach explicitly takes into account multiphase flow (based on a previously presented model) and relies on an MINLP model formulation toward calculating: (a) the operation (or shutting-in) of each well, (b) the volumetric flows of gas injection required in order to operate open production wells in gas-lift mode. An improved oil production optimum has been obtained for a case study considering a set of 6 gas-lift wells. This MINLP model can also be used for multiperiod optimization under additional cost and price constraints.

... The present study focuses on plantwide dynamics and control of a novel upstream (DS) process ... more ... The present study focuses on plantwide dynamics and control of a novel upstream (DS) process which is aimed at the continuous production of a novel Active Pharmaceutical Ingredient (API). ... Curr. Pharm. Anal. 2(4): 405-414 (2006). ...

ABSTRACT Managed Pressure Drilling (MPD) addresses a multitude of technical problems encountered ... more ABSTRACT Managed Pressure Drilling (MPD) addresses a multitude of technical problems encountered in carbonate reservoirs of numerous oil fields. The solid cuttings transport flowrate, stability and cost of cuttings transport from the carbonate rock formation towards the surface must be monitored accurately, because drilling safety and efficiency is of paramount importance. A profound understanding of the effect of the geometry and rheology on the pressure profile along the wellbore is essential, so appropriate rheological models (Rooki et al., 2012) of the drilling fluids (derived from viscometric studies) must be used toward technically relevant and numerically reliable CFD modeling studies. Drilling fluids perform several simultaneous tasks during MPD, offering hydrostatic pressure, cooling the bit, transporting cuttings to surface, maintaining wellbore stability and preventing contamination of the formation. Thus, they must possess acceptable stability in terms of density and rheology over a range of external conditions. Industrial demand is trending towards advanced drilling fluids with tailor-made properties, which can alleviate problems as they arise. Current high-performance requirements foster the development of smart drilling fluids, which are stable at downhole conditions, can perform the required tasks and have a much lower environmental footprint. Computational Fluid Dynamics (CFD) modeling of cuttings transport during MPD drilling operations can potentially have a strong impact on exploring numerically the attainable envelope of MPD drilling operations, and it has been attempted in very few cases (Nakagawa et al., 1999; Li & Kuru, 2003; Rooki et al., 2013). Research studies for gas-solid-liquid flows (the fundamental cuttings transport mechanism) have been published in the past, but most are not concerned with the elucidation of flow patterns and cuttings distributions, particularly for smart drilling fluids. Modern commercial and/or open-source CFD codes can tackle these problems successfully, yielding detailed state variable (pressure, slip velocity, solids loading) profiles as a function of drilling configuration and pipe position. This paper aims to present relevant case studies for non-Newtonian (e.g. Herschel-Bulkley) drilling fluids, which can be very efficient in MPD implementations. REFERENCES Li, Y., Kuru E., Numerical modeling of cuttings transport with foam in horizontal wells, Journal of Canadian Petroleum Technology 42: 54-61 (2003). Nakagawa E.Y., Silva V., Boas M.B.V., Silva P.R.C., Shayegi S., Comparison of aerated fluids/foam drilling hydraulics simulators against field data, SPE Paper 54319 presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Jakarta, Indonesia (1999). Rooki, R., Doulati Ardejani, F., Moradzadeh, A., Mirzaei, H., Kelessidis, V.C., Maglione, R., Nourozi, M., Optimal determination of rheological parameters for Herschel–Bulkley drilling fluids using genetic algorithms, Korea Australia Rheology Journal 24: 163-170 (2012). Rooki, R., Doulati Ardejani, F., Moradzadeh, A., Norouzi, M., Simulation of cuttings transport with foam in deviated wellbores using computational fluid dynamics, Journal of Petroleum Exploration & Production Technology 3(3): 1-11 (2013).

Multiscale modeling is a tool aimed at combining mathematical descriptions of different process s... more Multiscale modeling is a tool aimed at combining mathematical descriptions of different process scales into properly tailored scale integration hierarchies facilitating design-relevant modeling and simulation. This concept has been successfully applied in deriving state variable distributions of complex processes; in a relevant paper, we discuss its implementation in the field of carbothermic aluminium production. The three-level multiscale model proposed therein (Gerogiorgis and Ydstie, 2003a) is aimed at deriving state variable profiles for a conceptual high-temperature multiphase carbothermic aluminium reactor, its objective being to simultaneously solve the electric charge, heat, momentum, mass and molar balances and hence enhance our understanding of this spatially distributed, endothermic electrochemical process. The present paper presents our work on reactor electrode voltage optimization via MINLP modeling and validates the suitability of this approach via explicit two-dimensional multiphase flow CFD modeling.

Multiscale modeling is a tool aimed at combining mathematical descriptions of different process s... more Multiscale modeling is a tool aimed at combining mathematical descriptions of different process scales into a single, properly tailored scale integration hierarchy allowing for reliable modeling and simulation. This concept has already been successfully applied in deriving accurate state variable distributions for processes that exhibit full spatiotemporal variation and thus do not allow for the standard simplifications. This paper discusses the fundamental considerations required for the development of a multiscale model and presents the main implementation challenges for a conceptual high-temperature multiphase reactor. The objective is to simultaneously solve the electric charge, heat, momentum, mass and molar balances for the carbothermic reduction of alumina, a complex electrochemical process for aluminium production. This multiscale model relies on a decomposition of the PDE (mass, heat and momentum) balances into two levels: the first modeling level consists of a series of CS...

Multiscale modeling is a powerful idea for accurate and efficient simulation of challenging chemi... more Multiscale modeling is a powerful idea for accurate and efficient simulation of challenging chemical processes characterized by significant complexity at several length and time scales. A plethora of emerging and future chemical processes is of extreme industrial importance and cannot be satisfactorily studied using the arsenal of standard modeling simplifications. Accurate process representations need rely on nonlinear partial differential equation systems that exhibit spatiotemporal variation and fluid flow, not allowing for model order reduction. A variety of further challenges may significantly perplex reliable process modeling efforts: poor understanding of underlying physics inherently limits the scope and potential of models; computational expense is frequently prohibitive in terms of cost, CPU time and applicability; outsourcing and intellectual property restrictions result in distributed, inadequate knowledge; poorly documented legacy computer codes with are not easily inte...

Food and Bioproducts Processing, 2016

Multiscale modeling is a tool aimed at combining mathematical descriptions of different process s... more Multiscale modeling is a tool aimed at combining mathematical descriptions of different process scales into a single, properly tailored scale integration hierarchy allowing for reliable modeling and simulation. This concept has already been successfully applied in deriving accurate state variable distributions for processes that exhibit full spatiotemporal variation and thus do not allow for the standard simplifications. This paper discusses the fundamental considerations required for the development of a multiscale model and presents the main implementation challenges for a conceptual high-temperature multiphase reactor. The objective is to simultaneously solve the electric charge, heat, momentum, mass and molar balances for the carbothermic reduction of alumina, a complex electrochemical process for aluminium production. This multiscale model relies on a decomposition of the PDE (mass, heat and momentum) balances into two levels: the first modeling level consists of a series of CS...