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Journal articleZhang K, Georgiadis A, Trusler JPM, 2022,
Measurements and interpretation of crude Oil-Water/Brine dynamic interfacial tension at subsurface representative conditions
, Fuel, Vol: 315, Pages: 1-14, ISSN: 0016-2361Interfacial tensions (IFTs) between crude oil and water or brine systems are critically important in many processes. Exhibited dynamic behavior often remains poorly studied and requires in-depth analysis. In this study, 27 series of dynamic IFT measurements were conducted for three different crude oils in combination with three different aqueous phases (pure water and two synthetic reservoir brines) at temperatures of 298.15, 343.15 and 393.15 K and pressures up to 30 MPa. This study provides a large database of crude oil-water/brine IFTs encompassing reservoir conditions of temperature and pressure. Specific effects of temperature, pressure, and fluid composition on the crude oil-water and oil-brine IFTs were evaluated. The dynamic evolution of the IFT between the crude oils and aqueous phases was categorized according to typical relationships observed. The most commonly observed evolution was an initial rapid decline in IFT, over a period of 100 to 1,000 s, followed by levelling off at a nearly-constant long-term value. However, in certain cases, the initial rapid decline was followed by a broad minimum and a subsequent slow increase towards a nearly-steady long-time value. In either case, the initial decline is described by a simple model based on diffusion of surface-active components in the oil and their subsequent adsorption at the interface. The longer-term behavior may be further attributed to a combination of saturation, rearrangement and dissolution of the surface-active components.
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Journal articleAl Ghafri SZS, Munro S, Cardella U, et al., 2022,
Hydrogen liquefaction: a review of the fundamental physics, engineering practice and future opportunities
, Energy and Environmental Science, Vol: 15, ISSN: 1754-5692Hydrogen is emerging as one of the most promising energy carriers for a decarbonised global energy system. Transportation and storage of hydrogen are critical to its large-scale adoption and to these ends liquid hydrogen is being widely considered. The liquefaction and storage processes must, however, be both safe and efficient for liquid hydrogen to be viable as an energy carrier. Identifying the most promising liquefaction processes and associated transport and storage technologies is therefore crucial; these need to be considered in terms of a range of interconnected parameters ranging from energy consumption and appropriate materials usage to considerations of unique liquid-hydrogen physics (in the form of ortho–para hydrogen conversion) and boil-off gas handling. This study presents the current state of liquid hydrogen technology across the entire value chain whilst detailing both the relevant underpinning science (e.g. the quantum behaviour of hydrogen at cryogenic temperatures) and current liquefaction process routes including relevant unit operation design and efficiency. Cognisant of the challenges associated with a projected hydrogen liquefaction plant capacity scale-up from the current 32 tonnes per day to greater than 100 tonnes per day to meet projected hydrogen demand, this study also reflects on the next-generation of liquid-hydrogen technologies and the scientific research and development priorities needed to enable them.
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Journal articleHuang Y, Kang J, Liu L, et al., 2022,
A hierarchical coupled optimization approach for dynamic simulation of building thermal environment and integrated planning of energy systems with supply and demand synergy
, ENERGY CONVERSION AND MANAGEMENT, Vol: 258, ISSN: 0196-8904- Cite
- Citations: 29
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Journal articleLeonzio G, Mwabonje O, Fennell PS, et al., 2022,
Environmental performance of different sorbents used for direct air capture
, Sustainable Production and Consumption, Vol: 32, Pages: 101-111, ISSN: 2352-5509Currently, conventional carbon dioxide (CO2) mitigation solutions may be insufficient to achieve the stringent environmental targets set for the coming decades. CO2 removal (CDR) technologies, such as direct air capture (DAC), capturing CO2 from the ambient air, are required.In this research, an independent life cycle assessment (LCA) of DAC adsorption systems based on three physisorbents (metal organic frameworks) and two chemisorbents (amine functionalized sorbents) is presented. These capture processes have been optimised by us in previous work.Results show that for the overall capture process, negative CO2 emissions are ensured by using a cellulose-based amine sorbent (cradle-to-gate) ensuring even the net removal of CO2 from the atmosphere (cradle-to-grave). Processes using physisorbents have poorer performances. Chemisorbents yield operating conditions allowing lower impacts on the environment. In 2050, these processes could reduce climate change but can generate other environmental impacts.With the aim to have better environmental performances of DAC systems, future research should be focused on improving the physical properties of sorbents such as the silica gel based amine sorbent to increase their capture capacities. If metal organic frameworks are to be used, it is necessary to drop their energy consumption (by increasing the loading) and the required mass of sorbent.
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Journal articlePratama YW, Mac Dowell N, 2022,
Carbon capture and storage investment: fiddling while the planet burns
, One Earth, Vol: 5, Pages: 434-442, ISSN: 2590-3322Carbon capture and storage (CCS) has been recognized as a key technology in energy systems decarbonization. However, numerous attempts to deploy CCS failed, and the technology is still viewed as pre-commercial. Consequently, public investment in CCS has been largely limited to research, development, and demonstration (RD&D) in capture technology. While it is understood that private investment will typically focus on the development of intellectual property aimed at delivering a commercial advantage, there is a lack of evidence that public investment in CCS RD&D can deliver commercial viability. Here, we show that, while improved CCS technology in the electricity systems will deliver larger market shares to the technology developers, the benefit on overall system cost is negligible. Thus, public sector efforts should focus primarily on overcoming commercialization failures, such as the absence of CO2 transport and storage infrastructures and other deployment barriers, leaving the development of intellectual property to the private sector.
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Journal articleFennell P, Driver J, Bataille C, et al., 2022,
Going net zero for cement and steel
, NATURE, Vol: 603, Pages: 574-577, ISSN: 0028-0836- Cite
- Citations: 133
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Journal articlePatrizio P, Sunny N, Mac Dowell N, 2022,
Inefficient investments as a key to narrowing regional economic imbalances
, ISCIENCE, Vol: 25- Author Web Link
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- Citations: 1
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Journal articleAnsari H, Gong S, Trusler J, et al., 2022,
Hybrid pore-scale adsorption model for CO2 and CH4 storage in shale
, Energy and Fuels, Vol: 36, ISSN: 0887-0624Making reliable estimates of gas adsorption in shale remains a challenge becausethe variability in their mineralogy and thermal maturity results in a broad distributionof pore-scale properties, including size, morphology and surface chemistry. Here, wedemonstrate the development and application of a hybrid pore-scale model that usessurrogate surfaces to describe supercritical gas adsorption in shale. The model is basedon the lattice Density Functional Theory (DFT) and considers both slits and cylindrical pores to mimic the texture of shale. Inorganic and organic surfaces associatedwith these pores are accounted for by using two distinct adsorbate-adsorbent interaction energies. The model is parameterised upon calibration against experimentaladsorption data acquired on adsorbents featuring either pure clay or pure carbon surfaces. Therefore, in its application to shale, the hybrid lattice DFT model only requiresknowledge of the shale-specific organic and clay content. We verify the reliability ofthe model predictions by comparison against high-pressure CO2 and CH4 adsorptionisotherms measured at 40 ◦C in the pressure range 0.01–30 MPa on four samples fromthree distinct plays, namely the Bowland (UK), Longmaxi (China) and Marcellus shale1(USA). Because it uses only the relevant pore-scale properties, the proposed model canbe applied to the analysis of other shales, minimising the heavy experimental burdenassociated with high pressure experiments. Moreover, the proposed development hasgeneral applicability meaning that the hybrid lattice DFT can be used to the characterisation of any adsorbent featuring morphologically and chemically heterogeneoussurfaces.
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Journal articleKis Z, Tak K, Ibrahim D, et al., 2022,
Pandemic-response adenoviral vector and RNA vaccine manufacturing
, npj Vaccines, Vol: 7, ISSN: 2059-0105Rapid 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.
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Journal articleBahzad H, Fennell P, Shah N, et al., 2022,
Techno-economic assessment for a pumped thermal energy storage integrated with open cycle gas turbine and chemical looping technology
, Energy Conversion and Management, Vol: 255, Pages: 1-23, ISSN: 0196-8904Pumped thermal energy storage offers a high energy density, potentially resulting in a relatively low cost per unit of energy stored. In this study, two novel energy storage systems were developed. The first system was developed by integrating pumped thermal energy storage and chemical looping technologies, whereas the second was formed by merging the first system with an open cycle gas turbine. Both systems used an oxygen depleted stream as a working fluid and iron-based oxygen carriers from a chemical looping water splitting process storage material for the pumped thermal energy storage system. In addition, hydrogen from the chemical looping process was employed for the gas turbine in the second system. Both systems were evaluated thermodynamically via the determination of the roundtrip efficiency. The results presented here indicate that the roundtrip efficiency of both systems developed was 77%. Furthermore, the capital requirements, operating costs, and daily profits from electricity generation were calculated for both systems over several days within the year. The capital and operating costs for the several days that were simulated for the integrated pumped thermal energy storage system were lower than that of a gas turbine based system. Consequently, the daily profit was estimated and found to be between 4.9% and 72.9% higher for the integrated pumped storage relative to the gas turbine based system. Moreover, an economic sensitivity analysis was performed to identify the factors that strongly affect the daily profits of the gas turbine system relative to the pumped storage system. Based on the analysis, the optimal hydrogen fuel percentage fed to the open cycle gas turbine was calculated for the days simulated. Finally, the impact of % error on the estimated capital and fuel production costs on daily profits were investigated. The outcome revealed a higher impact of computational errors on the fuel costs relative to the costs of the capital.
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Journal articleLeonzio G, Fennell PS, Shah N, 2022,
A comparative study of different sorbents in the context of direct air capture (DAC): evaluation of key performance indicators and comparisons
, Applied Sciences-Basel, Vol: 12, ISSN: 2076-3417Direct air capture can be based on an adsorption system, and the used sorbent (chemisorbents or physisorbents) influences process. In this work, two amine-functionalized sorbents, as chemisorbents, and three different metal organic frameworks, as physisorbents, are considered and compared in terms of some key performance indicators. This was carried out by developing a mathematical model describing the adsorption and desorption stages. An independent analysis was carried out in order to verify data reported in the literature. Results show that the equilibrium loading is a critical parameter for adsorption capacity, energy consumption, and cost. The considered metal organic frameworks are characterized by a lower equilibrium loading (10−4 mol/kg) compared to chemisorbents (10−1 mol/kg). For this reason, physisorbents have higher overall energy consumptions and costs, while capturing a lower amount of carbon dioxide. A reasonable agreement is found on the basis of the operating conditions of the Climeworks company, modelling the use of the same amine cellulose-based sorbent. The same order of magnitude is found for total costs (751 USD/tonneCO2 for our analysis, compared to the value of 600 USD/tonneCO2 proposed by this company)
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Conference paperWedler C, Trusler J, 2022,
Viscosity of Alternative and Synthetic Fuel Surrogates
, 20th Meeting of the International Association for Transport Properties -
Journal articleHuang Z, Kurotori T, Pini R, et al., 2022,
Three-Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography
, WATER RESOURCES RESEARCH, Vol: 58, ISSN: 0043-1397- Cite
- Citations: 4
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Book chapterO'Dwyer E, Indranil P, Shah N, 2022,
Decarbonisation of the urban landscape: integration and optimization of energy systems
, Intelligent Decarbonisation: Can Artificial Intelligence and Cyber-PhysicalSystems Help Achieve Climate MitigationTargets?, Editors: Inderwildi, Kraft, Publisher: Springer, ISBN: 978-3030862145We highlight the key pillars of urban energy systems which would leverage on AI and digital technologiesfor a low carbon future. We summarise a couple of real world applications where optimisation, intelligentcontrol systems and cloud based infrastructure have played a transformative role in improving systemperformance, cost effectiveness and decarbonisation. The case studies show that AI and digitaltechnologies can be implemented for standalone unit operations to achieve such benefits. However, moreimportantly as the second case study shows, applying such technologies at a system level by integratingmultiple energy vectors would give much more flexibility in terms of operation, resulting in betterperformance improvements and decarbonisation strategies. We conclude by highlighting the strategictrends in this fast evolving field and giving a broad outlook in terms of cost reductions and emissionssavings for similar intelligent energy systems.
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Journal articleLi L, Wang J, Zhong X, et al., 2022,
Combined multi-objective optimization and agent-based modeling for a 100% renewable island energy system considering power-to-gas technology and extreme weather conditions
, APPLIED ENERGY, Vol: 308, ISSN: 0306-2619- Cite
- Citations: 20
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Journal articleCooper N, Horend C, Roben F, et al., 2022,
A framework for the design & operation of a large-scale wind-powered hydrogen electrolyzer hub
, International Journal of Hydrogen Energy, Vol: 47, Pages: 8671-8686, ISSN: 0360-3199Due to the threat of climate change, renewable feedstocks & alternative energy carriers are becoming more necessary than ever. One key vector is hydrogen, which can fulfil these roles and is a renewable resource when split from water using renewable electricity. Electrolyzers are often not designed for variable operation, such as power from sources like wind or solar. This work develops a framework to optimize the design and operation of a large-scale electrolyzer hub under variable power supply. The framework is a two-part optimization, where designs of repeated, modular units are optimized, then the entire system is optimized based on those modular units. The framework is tested using a case study of an electrolyzer hub powered by a Dutch wind farm to minimize the levelized cost of hydrogen. To understand how the optimal design changes, three power profiles are examined, including a steady power supply, a representative wind farm power supply, and the same wind farm power supply compressed in time. The work finds the compressed power profile uses PEM technology which can ramp up and down more quickly. The framework determines for this case study, pressurized alkaline electrolyzers with large stacks are the cheapest modular unit, and while a steady power profile resulted in the cheapest hydrogen, costing 4.73 €/kg, the typical wind power profile only raised the levelized cost by 2%–4.82 €/kg. This framework is useful for designing large-scale electrolysis plants and understanding the impact of specific design choices on the performance of a plant.
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Journal articlevan de Berg D, Savage T, Petsagkourakis P, et al., 2022,
Data-driven optimization for process systems engineering applications
, Chemical Engineering Science, Vol: 248, Pages: 117135-117135, ISSN: 0009-2509Most optimization problems in engineering can be formulated as ‘expensive’ black box problems whose solutions are limited by the number of function evaluations. Frequently, engineers develop accurate models of physical systems that are differentiable and/or cheap to evaluate. These models can be solved efficiently, and the solution transferred to the real system. In the absence of gradient information or cheap-to-evaluate models, one must resort to efficient optimization routines that rely only on function evaluations. Creating a model can itself be considered part of the expensive black box optimization process. In this work, we investigate how perceived state-of-the-art derivative-free optimization (DFO) algorithms address different instances of these problems in process engineering. On the algorithms side, we benchmark both model-based and direct-search DFO algorithms. On the problems side, the comparisons are made on one mathematical optimization problem and five chemical engineering applications: model-based design of experiments, flowsheet optimization, real-time optimization, self-optimizing reactions, and controller tuning. Various challenges are considered such as constraint satisfaction, uncertainty, problem dimension and evaluation cost. This work bridges the gap between the derivative-free optimization and process systems literature by providing insight into the efficiency of data-driven optimization algorithms in the process systems domain to advance the digitalization of the chemical and process industries.
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Journal articlevan der Spek M, Banet C, Bauer C, et al., 2022,
Perspective on the hydrogen economy as a pathway to reach net-zero CO2 emissions in Europe
, Energy and Environmental Science, Vol: 15, Pages: 1034-1077, ISSN: 1754-5692The envisioned role of hydrogen in the energy transition – or the concept of a hydrogen economy – has varied through the years. In the past hydrogen was mainly considered a clean fuel for cars and/or electricity production; but the current renewed interest stems from the versatility of hydrogen in aiding the transition to CO2 neutrality, where the capability to tackle emissions from distributed applications and complex industrial processes is of paramount importance. However, the hydrogen economy will not materialise without strong political support and robust infrastructure design. Hydrogen deployment needs to address multiple barriers at once, including technology development for hydrogen production and conversion, infrastructure co-creation, policy, market design and business model development. In light of these challenges, we have brought together a group of hydrogen researchers who study the multiple interconnected disciplines to offer a perspective on what is needed to deploy the hydrogen economy as part of the drive towards net-zero-CO2 societies. We do this by analysing (i) hydrogen end-use technologies and applications, (ii) hydrogen production methods, (iii) hydrogen transport and storage networks, (iv) legal and regulatory aspects, and (v) business models. For each of these, we provide key take home messages ranging from the current status to the outlook and needs for further research. Overall, we provide the reader with a thorough understanding of the elements in the hydrogen economy, state of play and gaps to be filled.
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Journal articleGulliford MJS, Orlebar RH, Bird MH, et al., 2022,
Developing a dynamic carbon benchmarking method for large building property estates
, Energy and Buildings, Vol: 256, Pages: 111683-111683, ISSN: 0378-7788As supermarkets are known to be energy intensive, improvements made to their efficiency can enable operators to reduce not only carbon emissions but also costs, in line with corporate and legislative targets. This study presents a novel benchmarking method to appraise emission and cost performances across a portfolio, enabling building managers to identify sites that are underperforming, taking as a case study a large number of food retail stores. Multiple layers, detailed variable selection including weather features and regression technique comparisons (Multivariate Linear Regression (MLR), Artificial Neural Network (ANN) and Decision Tree (DT)), are considered in model construction. Efficiency is evaluated on multiple bases with a focus on emissions. These are clustered together to produce a benchmark to inform investment decision-making across a portfolio. The DT technique was found to be the most effective, producing a benchmark with low average error (1.5 kgCO2 m−2 period−1) and high maximum error (21 kgCO2 m−2 period−1) indicating high accuracy and high discernment respectively. This model also correctly classified buildings known to perform poorly into the worst 30% of buildings in the portfolio. This work highlights the need for further research into natural gas consumption benchmarking and particularly the use of humidity data to better understand the issues in decarbonising heat.
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Journal articleZhang Y, Jackson C, Zahasky C, et al., 2022,
European carbon storage resource requirements of climate change mitigation targets
, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 114, ISSN: 1750-5836- Cite
- Citations: 9
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Journal articleGarfi G, John C, Rücker M, et al., 2022,
Determination of the spatial distribution of wetting in the pore networks of rocks
<jats:p>The macroscopic movement of subsurface fluids involved in CO2 storage, groundwater, and petroleum engineering applications is controlled by interfacial forces in the pores of rocks, micrometre to millimetre in length scale. Recent advances in physics based models of these systems has arisen from approaches simulating flow through a digital representation of the complex pore structure. However, further progress is limited by a lack of approaches to characterising the spatial distribution of the wetting state within the pore structure. In this work, we show how observations of the fluid coverage of mineral surfaces within the pores of rocks can be used as the basis for a quantitative 3D characterisation of heterogeneous wetting states throughout rock pore structures. We demonstrate the approach with water-oil fluid pairs on rocks with distinct lithologies (sandstone and carbonate) and wetting states (hydrophilic, intermediate wetting, or heterogeneously wetting). The resulting 3D maps can be used as a deterministic input to pore scale modelling workflows and applied to all multiphase flow problems in porous media ranging from soil science to fuel cells.</jats:p>
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Working paperZhang Y, Jackson C, Krevor S, et al., 2022,
European carbon storage resource requirements of climate change mitigation targets
<jats:p>As a part of climate change mitigation plans in Europe, CO2 storage scenarios have been reported for the United Kingdom and the European Union with injection rates reaching 75 – 330 MtCO2 yr-1 by 2050. However, these plans are not constrained by geological properties or growth rates with precedent in the hydrocarbon industry. We use logistic models to identify growth trajectories and the associated storage resource base consistent with European targets. All of the targets represent ambitious growth, requiring average annual growth in injection rates 9% – 15% from 2030-2050. Modelled plans are not constrained by CO2 storage availability and can be accommodated by the resources of offshore UK or Norway alone. Only if the resource base is significantly less, around 10% of current estimates, does storage availability limit mitigation plans. We further demonstrate the use of the models to define 2050 rate targets within conservative bounds of both growth rate and storage resource needs.</jats:p>
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Journal articleKusumo K, Kuriyan K, Vaidyaraman S, et al., 2022,
Risk mitigation in model-based experiment design: a continuous-effort approach to optimal campaigns
, Computers and Chemical Engineering, Vol: 159, ISSN: 0098-1354A key challenge in maximizing the effectiveness of model-based design of experiments for calibrating nonlinear process models is the inaccurate prediction of information that is afforded by each new experiment. We present a novel methodology to exploit prior probability distributions of model parameter estimates in a bi-objective optimization formulation, where a conditional-value-at-risk criterion is considered alongside an average information criterion. We implement a tractable numerical approach that discretizes the experimental design space and leverages the concept of continuous-effort experimental designs in a convex optimization formulation. We demonstrate effectiveness and tractability through three case studies, including the design of dynamic experiments. In one case, the Pareto frontier comprises experimental campaigns that significantly increase the information content in the worst-case scenarios. In another case, the same campaign is proven to be optimal irrespective of the risk attitude. An open-source implementation of the methodology is made available in the Python software Pydex.
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Journal articleSiepmann JI, Gardas R, Kofke DA, et al., 2022,
The <i>Journal of Chemical</i> & <i>Engineering Data</i>: Introduction of Topical Sections and Updates from the Editorial Team
, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 67, Pages: 1-2, ISSN: 0021-9568 -
Journal articleJoewondo N, Garbin V, Pini R, 2022,
Nonuniform collective dissolution of bubbles in regular pore networks
, Transport in Porous Media, Vol: 141, Pages: 649-666, ISSN: 0169-3913Understanding the evolution of solute concentration gradients underpins the prediction of porous media processes limited by mass transfer. Here, we present the development of a mathematical model that describes the dissolution of spherical bubbles in two-dimensional regular pore networks. The model is solved numerically for lattices with up to 169 bubbles by evaluating the role of pore network connectivity, vacant lattice sites and the initial bubble size distribution. In dense lattices, diffusive shielding prolongs the average dissolution time of the lattice, and the strength of the phenomenon depends on the network connectivity. The extension of the final dissolution time relative to the unbounded (bulk) case follows the power-law function, Bk/ℓ, where the constant ℓ is the inter-bubble spacing, B is the number of bubbles, and the exponent k depends on the network connectivity. The solute concentration field is both the consequence and a factor affecting bubble dissolution or growth. The geometry of the pore network perturbs the inward propagation of the dissolution front and can generate vacant sites within the bubble lattice. This effect is enhanced by increasing the lattice size and decreasing the network connectivity, yielding strongly nonuniform solute concentration fields. Sparse bubble lattices experience decreased collective effects, but they feature a more complex evolution, because the solute concentration field is nonuniform from the outset.
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Book chapterAcha S, O’Dwyer E, Pan I, et al., 2022,
Decarbonisation of the Urban Landscape: Integration and Optimization of Energy Systems
, Lecture Notes in Energy, Pages: 133-144We highlight the key pillars of urban energy systems which would leverage on AI and digital technologies for a low carbon future. We summarise a couple of real world applications where optimisation, intelligent control systems and cloud-based infrastructure have played a transformative role in improving system performance, cost-effectiveness and decarbonisation. The case studies show that AI and digital technologies can be implemented for standalone unit operations to achieve such benefits. However, more importantly as the second case study shows, applying such technologies at a system level by integrating multiple energy vectors would give much more flexibility in terms of operation, resulting in better performance improvements and decarbonisation strategies. We conclude by highlighting the strategic trends in this fast evolving field and giving a broad outlook in terms of cost reductions and emissions savings for similar intelligent energy systems.
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Journal articleDelle Piane C, Ansari H, Li Z, et al., 2022,
Influence of organic matter type on porosity development in the Wufeng-Longmaxi Shale: A combined microscopy, neutron scattering and physisorption approach
, International Journal of Coal Geology, Vol: 249, Pages: 1-15, ISSN: 0166-5162The upper Ordovician Wufeng Shale and lower Silurian Longmaxi Shale are part of the Fuling shale gas play located in the south-eastern part of the Sichuan Basin, southern China, representing the first commercial shale gas production project outside North America. We studied the occurrence of porosity at the micro- and nano-scale in samples of contrasting organic richness representing the typical lithofacies from the post-mature part of the Wufeng-Longmaxi gas play. Using a combination of site specific, high-resolution scanning and transmission electron microscopy with bulk measurements based on small angle neutron scattering and cryogenic Argon physisorption, along with conventional organic petrology, we highlight the impact of different types of organic matter (OM) (primary versus secondary) on the development of OM-hosted porosity. The results indicate that at the bulk scale the overall porosity in the samples is proportional to their organic content and organic hosted pore account for 30–40% of the total pore volume of the rocks. Nevertheless, most of the pores identified via electron microscopy imaging seem to reside in the organic matter, indicating that potentially a large part of the pores volume detected by neutron scattering and Argon physisorption is visually not detected. Organic matter focused nanoscale imaging revealed that mesopores are preferentially present in the solid bitumen and not in the primary detrital organic particles. Organic lean samples show low porosity and dominance of micropores, while organic-rich samples show higher porosity and a broader spectrum of pore sizes. Importantly, most of the meso pores are located in organic matter petrographically interpreted as solid bitumen, while detrital organic particles like graptolites show minimal visible porosity under high resolution electron microscopy and pore sizes in the micro pore range (i.e. <2 nm).Distinguishing between primary and secondary OM is therefore important for underst
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Journal articleSarabia Escriva EJ, Hart M, Acha Izquierdo S, et al., 2022,
Techno-economic evaluation of integrated energy systems for heat recovery applications in food retail buildings
, Applied Energy, Vol: 305, ISSN: 0306-2619Eliminating the use of natural gas for non-domestic heat supply is an imperative component of net-zero targets. Techno-economic analyses of competing options for low-carbon heat supply are essential for decision makers developing decarbonisation strategies. This paper investigates the impact various heat supply configurations can have in UK supermarkets by using heat recovery principles from refrigeration systems under different climatic conditions. The methodology builds upon a steady-state model that has been validated in previous studies. All refrigeration integrated heating and cooling (RIHC) systems employ CO2 booster refrigeration to recover heat and provide space heating alongside various technologies such as thermal storage, air-source heat pumps (ASHPs) and direct electric heaters. Seven cases evaluating various technology combinations are analysed and compared against a conventional scenario in which the building is heated with a natural gas boiler. The specific combinations of technologies analysed here contrasts trade-offs and is a first in the literature. The capital costs of these projects are considered, giving insights into their business case. Results indicate that electric heaters are not cost-competitive in supermarkets. Meanwhile, RIHC and ASHP configurations are the most attractive option, and if a thermal storage tank system with advanced controls is included, the benefits increase even further. Best solutions have a 6.3% ROI, a payback time of 16 years while reducing energy demand by 62% and CO2 emissions by 54%. Such investments will be difficult to justify unless policy steers decision makers through incentives or the business case changes by implementing internal carbon pricing.
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Conference paperSoh QY, O'Dwyer E, Acha S, et al., 2022,
Stochastic optimal design for large-scale rainwater harvesting and detention systems
, Pages: 575-586In urban centres, large scale rainwater harvesting (RWH) systems are increasingly used as a multipurpose stormwater management strategy. These systems have shown promise as a secondary water resource in addition to acting as a decentralised detention and flood prevention measure. Understanding the specific dynamics of these combined RWH systems is key to ensuring they can meet the desired objectives efficiently, thus requiring careful consideration in the sizing and design for each large-scale implementation. This can be a lengthy process highly dependent on expert knowledge, and therefore significantly slow down new RWH installations. In this paper we present a stochastic optimisation model for the design of passive RWH systems to quickly adjust system sizing parameters for a given environmental context. A high-resolution simulation model is used to assess the system behaviors and provide a performance guarantee for system managers before capital needs to be invested into building specific infrastructure. The optimisation model is applied to a case study for the sizing of a multi-tank RWH system for a residential estate in Singapore, and is assessed based on the system's ability to reduce surface overflow and satisfy irrigation demand. Results demonstrate a reduction in the total time and effort required to derive an efficient and adequate system design, in aid of simplifying the process of designing and implementing RWH systems. The stochastically optimal size for the multi-tank system was found to be capable of completely mitigating surface overflows, and increase water availability by 47% in comparison to the existing configuration located in the estate.
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Book chaptervan de Berg D, Petsagkourakis P, Shah N, et al., 2022,
Data-driven coordination of expensive black-boxes
, Computer Aided Chemical Engineering, Pages: 1159-1164Coordinating decision-making capacities using optimization is a key factor in the success of chemical companies. However, this coordination is often inhibited by expensive, legally-constrained, or proprietary subproblem models. We propose two variations on how model-based (surrogate) derivative-free optimization (DFO) methods can be used to coordinate subproblems with few connecting variables. When these surrogates are convex quadratic, they can be efficiently exploited using semidefinite programming techniques. We compare the performance of these two variations with a distributed optimization solver (ADMM), a model-based, and a direct DFO solver (Py-BOBYQA and DIRECTL). This comparison is done on four variations of an economic-environmental feedstock blending optimization case study. While ADMM seems to display faster initial convergence, explorative DFO optimization solvers seem promising in escaping local minimizers, especially in lower dimensions.
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