Publications
13 results found
Panoutsou C, Giarola S, Ibrahim D, et al., 2022, Opportunities for low indirect land use biomass for biofuels in Europe, Applied Sciences-Basel, Vol: 12, ISSN: 2076-3417
Sustainable biofuels are an important tool for the decarbonisation of transport. This is especially true in aviation, maritime, and heavy-duty sectors with limited short-term alternatives. Their use by conventional transport fleets requires few changes to the existing infrastructure and engines, and thus their integration can be smooth and relatively rapid. Provision of feedstock should comply with sustainability principles for (i) producing additional biomass without distorting food and feed markets and (ii) addressing challenges for ecosystem services, including biodiversity, and soil quality. This paper performs a meta-analysis of current research for low indirect land use change (ILUC) risk biomass crops for sustainable biofuels that benefited either from improved agricultural practices or from cultivation in unused, abandoned, or severely degraded land. Two categories of biomass crops are considered here: oil and lignocellulosic. The findings confirm that there are significant opportunities to cultivate these crops in European agro-ecological zones with sustainable agronomic practices both in farming land and in land with natural constraints (unused, abandoned, and degraded land). These could produce additional low environmental impact feedstocks for biofuels and deliver economic benefits to farmers
Kis Z, Tak K, Ibrahim D, et al., 2022, Pandemic-response adenoviral vector and RNA vaccine manufacturing, npj Vaccines, Vol: 7, ISSN: 2059-0105
Rapid global COVID-19 pandemic response by mass vaccination is currently limited by the rate of vaccine manufacturing. This study presents a techno-economic feasibility assessment and comparison of three vaccine production platform technologies deployed during the COVID-19 pandemic: (1) adenovirus-vectored (AVV) vaccines, (2) messenger RNA (mRNA) vaccines, and (3) the newer self-amplifying RNA (saRNA) vaccines. Besides assessing the baseline performance of the production process, impact of key design and operational uncertainties on the productivity and cost performance of these vaccine platforms is evaluated using variance-based global sensitivity analysis. Cost and resource requirement projections are computed for manufacturing multi-billion vaccine doses for covering the current global demand shortage and for providing annual booster immunisations. The model-based assessment provides key insights to policymakers and vaccine manufacturers for risk analysis, asset utilisation, directions for future technology improvements and future pidemic/pandemic preparedness, given the disease-agnostic nature of these vaccine production platforms.
Kis Z, Tak K, Ibrahim D, et al., 2022, Quality by design and techno-economic modelling of RNA vaccine production for pandemic-response, Computer Aided Chemical Engineering, Pages: 2167-2172
Vaccine production platform technologies have played a crucial role in rapidly developing and manufacturing vaccines during the COVID-19 pandemic. The role of disease agnostic platform technologies, such as the adenovirus-vectored (AVV), messenger RNA (mRNA), and the newer self-amplifying RNA (saRNA) vaccine platforms is expected to further increase in the future. Here we present modelling tools that can be used to aid the rapid development and mass-production of vaccines produced with these platform technologies. The impact of key design and operational uncertainties on the productivity and cost performance of these vaccine platforms is evaluated using techno-economic modelling and variance-based global sensitivity analysis. Furthermore, the use of the quality by digital design framework and techno-economic modelling for supporting the rapid development and improving the performance of these vaccine production technologies is also illustrated.
Ibrahim D, Kis Z, Tak K, et al., 2022, Optimal design and planning of supply chains for viral vectors and RNA vaccines, Computer Aided Chemical Engineering, Pages: 1633-1638
This work develops a multi-product MILP vaccine supply chain model that supports planning, distribution, and administration of viral vectors and RNA-based vaccines. The capability of the proposed vaccine supply chain model is illustrated using a real-world case study on vaccination against SARS-CoV-2 in the UK that concerns both viral vectors (e.g., AZD1222 developed by Oxford-AstraZeneca) and RNA-based vaccine (e.g., BNT162b2 developed by Pfizer-BioNTech). A comparison is made between the resources required and logistics costs when viral vectors and RNA vaccines are used during the SARS-CoV-2 vaccination campaign. Analysis of results shows that the logistics cost of RNA vaccines is 85% greater than that of viral vectors, and that transportation cost dominates logistics cost of RNA vaccines compared to viral vectors.
Ibrahim D, Kis Z, Tak K, et al., 2021, Model-based planning and delivery of mass vaccination campaigns against infectious disease: application to the COVID-19 pandemic in the UK, Vaccines, Vol: 9, Pages: 1-19, ISSN: 2076-393X
Vaccination plays a key role in reducing morbidity and mortality caused by infectious diseases, including the recent COVID-19 pandemic. However, a comprehensive approach that allows the planning of vaccination campaigns and the estimation of the resources required to deliver and administer COVID-19 vaccines is lacking. This work implements a new framework that supports the planning and delivery of vaccination campaigns. Firstly, the framework segments and priorities target populations, then estimates vaccination timeframe and workforce requirements, and lastly predicts logistics costs and facilitates the distribution of vaccines from manufacturing plants to vaccination centres. The outcomes from this study reveal the necessary resources required and their associated costs ahead of a vaccination campaign. Analysis of results shows that by integrating demand stratification, administration, and the supply chain, the synergy amongst these activities can be exploited to allow planning and cost-effective delivery of a vaccination campaign against COVID-19 and demonstrates how to sustain high rates of vaccination in a resource-efficient fashion.
Ibrahim D, Jobson M, Li J, et al., 2021, Optimal design of flexible heat-integrated crude oil distillation units using surrogate models, CHEMICAL ENGINEERING RESEARCH & DESIGN, Vol: 165, Pages: 280-297, ISSN: 0263-8762
Ibrahim D, Oyewunmi O, Haslam A, et al., 2019, Computer-aided working fluid design and optimisation of organic Rankine cycle (ORC) systems under varying heat-source conditions, 32ND INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS
Simpson M, Schuster S, Ibrahim D, et al., 2019, Small-scale, low-temperature ORC systems intime-varying operation: Turbines orreciprocating-piston expanders?, 32ND INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS
Ibrahim D, Oyewunmi O, Haslam A, et al., 2019, COMPUTER-AIDED WORKING FLUID DESIGN AND POWER SYSTEM OPTIMIZATION USING THE SAFT-γ MIE EQUATION OF STATE, 4th Thermal and Fluids Engineering Conference (TFEC)
Ibrahim D, Jobson M, Li J, et al., 2018, Optimization-based design of crude oil distillation units using surrogate column models and a support vector machine, CHEMICAL ENGINEERING RESEARCH & DESIGN, Vol: 134, Pages: 212-225, ISSN: 0263-8762
Ibrahim D, Jobson M, Li J, et al., 2017, Surrogate Models combined with a Support Vector Machine for the Optimized Design of a Crude Oil Distillation Unit using Genetic Algorithms, 27th European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 481-486, ISSN: 1570-7946
Ibrahim D, Jobson M, Guillen-Gosalbez G, 2017, Optimization-Based Design of Crude Oil Distillation Units Using Rigorous Simulation Models, Industrial && Engineering Chemistry Research, Vol: 56, Pages: 6728-6740, ISSN: 0888-5885
The complex nature of crude oil distillation units, including their interactions with the associated heat recovery network and the large number of degrees of freedom, makes their optimization a very challenging task. We address here the design of a complex crude oil distillation unit by integrating rigorous tray-by-tray column simulation using commercial process simulation software with an optimization algorithm. While several approaches were proposed to tackle this problem, most of them relied on simplified models that are unable to deal with the whole complexity of the problem. The design problem is herein formulated to consider both structural variables (the number of trays in each column section) and operational variables (feed inlet temperature, pump-around duties and temperature drops, stripping steam flow rates and reflux ratio). A simulation-optimization approach for designing such a complex system is applied, which searches for the best design while accounting for heat recovery opportunities using pinch analysis. The approach is illustrated by its application to a specific distillation unit, in which numerical results demonstrate that the new approach is capable of identifying appealing design options while accounting for industrially relevant constraints.
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