2,161 research outputs found
Modelling The Underground Hydrogen Storage : A State-of-the-Art Review of Fundamental Approaches and Findings
The authors gratefully acknowledge the funding support by the Net Zero Technology Centre (NZTC), UK and the industrial sponsors to accomplish this work under the Hydrogen Innovation Grant scheme.Peer reviewedPublisher PD
Climate Change and Critical Agrarian Studies
Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial
Functional Nanomaterials and Polymer Nanocomposites: Current Uses and Potential Applications
This book covers a broad range of subjects, from smart nanoparticles and polymer nanocomposite synthesis and the study of their fundamental properties to the fabrication and characterization of devices and emerging technologies with smart nanoparticles and polymer integration
Numerical simulation of surfactant flooding with relative permeability estimation using inversion method
Surfactant flooding attracts significant interest in the hydrocarbon industry, with a definite
promise to improve oil recovery from depleting oil reserves. In this thesis, surfactant flooding
is the primary area of focus as it has significant potential for integration with other chemical
enhanced oil recovery techniques, including polymer, nanofluid, alkali, and foam. This
combined approach has the potential to reduce interfacial tension to ultralow levels, decrease
adsorption, and offer other benefits. However, due to the various mechanism, surfactant
flooding poses a more complex model for simulators by encountering numerical issues (e.g.,
the appearance of spurious oscillations, erratic pulses, and numerical instabilities), rendering
the methods ineffective. To address these challenges, the analytical modelling technique of
surfactant flooding was studied, leading to the development of a novel inversion method in the
MATLAB programming environment.
Numerical accuracy issues were discovered in 1D models that used typical cell sizes found in
well-scale models, leading to pulses in the oil bank and a dip in water saturation, particularly
for low levels of adsorption, highlighting the need for more refined models. Based on these
findings, we examined the surfactant flooding technique in 2D models to recover viscous oil
in short reservoir aspect ratios. Instabilities such as viscous fingering and gravity tongue were
observed on the flood fronts, and the magnitude of the viscous fingers was influenced by
vertical dispersion, resulting in errors in computed mobility values at the fronts. Interestingly,
introducing heterogeneity only minimally affected the spreading of the front and did not
significantly impact viscous fingering or numerical artifacts. To optimize the nonlinearity of
flow behaviour and degree of mobility control at the fronts, a homogenous model was
considered to develop the inversion method.
In summary, the developed inversion method accurately estimated the two-phase relative
permeability curves, which were validated using fractional flow theory. The precision of the
inverted curves was further improved using the optimization algorithm, demonstrating the
method's ability to predict outcomes closer to the observed values for 2D models with
instabilities. The obtained results are of significant value for core flood analysis, interpretation,
matching, and upscaling, providing insights into the potential of surfactant flooding for
enhanced oil recovery. Additionally, the use of the developed MATLAB Scripts promotes open
innovation and reproducibility, contributing to the benchmarking, analytical, and numerical
method development exercises for tutorials aimed at improving the overall understanding of
surfactant flooding
Analyzing smart city development through an evolutionary approach
Cities have always been places where agglomeration economies attained their highest yields, producing cultural, economic, and social benefits being the main locus of entrepreneurship and innovation. However, rapid urbanization created many problems such as inequality, pollution, diseases, insecurity and so on, that end up restraining the dynamic of value creation in 21st century. This is challenging ‘industrial cities’ to rethink and to reshape their structures to overcome these issues. In this sense, the ‘smart city’ model has gained prominence in urban development. Many cities from different countries are designing strategies and implementing them through initiatives and projects towards smart city development. It is noted that these experiences are idiosyncratic, because cities are inherently different and have different issues that must be solved in a particular way. The first question that arise is: how to make a city smarter? Despite the contrasting view of frameworks and their multitude of dimensions and approaches, the literature points out that cities must have specific elements to induce innovation processes through digital solutions and the collaboration between stakeholders in order to address local challenges and, thus, increase local competitiveness and quality of life. However, it does not an easy task and involves a set of stakeholders that may not prone to collaborate and to promote smart city development. In fact, the main difficulties of a strategy emerge during the implementation phase, because many of the challenges for cities to become or to be smart exceed the scope and capabilities of their current organizations, institutional arrangements, and governance structures. Indeed, the lack of appropriate structural and organizational formations does not foster the involvement of local stakeholders and makes it difficult to organize and coordinate the different activities needed to achieve sustainable urban development. Then, the second question that emerge is: what kind of organization can foster smart city development? In this sense, the literature sheds light on the need to discuss alternative governance models to overcome those challenges by combining political and social support with strategic planning and creative thinking in order to deal with smart city complexity. Some authors point out that it is necessary to create a dedicated organization to lead the collaboration between those stakeholders in this process of urban transformation. From that discussion, what seems clear is that the analysis of the development process of a smart city in its different dimensions and units of analysis demands a theoretical background that enables academia and industry to capture the dynamics of evolution and, therefore, understand how smart cities change over time. It is necessary to incorporate theories and concepts that consider not only the notion of space-time, but especially that delve into how the relationships between the elements of the ecosystem interact and complement each other. Then, our third question is: how to analyze this dynamic, context-dependent, long-term process of urban development so that a city becomes smarter? Some authors point out the possibility of a theoretical approximation between evolutionary approach and smart city literature affirming that due to complexity of smart city development, smart city planning is shaped by evolutionary processes too. Thus, it is necessary to incorporate the notion of evolution in the processes of urban transformation and that they occur in a certain geographical location being conditioned by local contextual factors. As aforementioned, cities are inherently different and have different issues. Thus, to measure the existing level of development is crucial to foresee the right steps to enhance urban smartness. Smartness should be seen as a continuum, in which stakeholders may implement initiatives to create, improve or alter smart city elements across those different city dimensions. The notion of smartness may help cities to understand how this process of urban transformation affects their dimensions and their performance, and, consequently, analyze what should be done to accelerate it. In this sense, it is important that cities assess their current stage of development. The assessment of smart city development may bring multiple benefits for different stakeholders. It enables the identification of city strengths and weaknesses, comparison among cities, monitoring and racking projects implementation, increasing transparency on investments, enabling to make policies based on evidences, enhancing citizen awareness, and so on. The fourth question that emerges is: how to measure the smartness of a city? In terms of smart city assessment, many scholars, organizations and companies have developed indexes, toolkits, and benchmarking to measure and rank smart cities. These assessments schemes may provide a good overview about the city’s characteristics and both its strengths and weaknesses, as well as being used to showcase its competitive position. However, most of them neglect the multiple interrelated processes related to the smart city development by adopting a summative approach. This approach presents some limitations that do not properly capture the smartness of a city. Considering that, the objectives of this study are to (1) identify the dimensions and the driving elements to make a city smarter, (2) to understand the role of smart city dedicated organization on smart city governance, (3) to propose an evolutionary framework for the analysis of smart city development and (4) to create a model to measure the smartness of a city using different methods, considering the type of data, its manipulation and analysis. To achieve these objectives, the research focused on understanding the concept of smart cities and that their development depends on a non-linear process, which should make some steps like designing strategies, implementing them through projects to solve the current urban issues. For that, the establishment of a governance structure is crucial to smart city development succeed since collaboration is needed to create complex solutions and the legitimacy of a vision. Therefore, a dedicated organization is important to articulate the stakeholders and boost the development of projects and initiatives. However, just collaborative networks will not solve the urban issues per se. It should be identified how to create, improve, change the elements from the hard and soft dimensions of a city (i.e., economy, social, environment). It is important to highlight that a smart strategy, project, or solution to be smart in fact must consider that these dimensions are integrated and then affect and are affected by each other. In addition, it is needed to incorporate in this urban planning and management discourse the notion of time and space, because past events can affect the current stage of development and the present decisions will impact future of the city. As an evolutionary process, each city will certainly follow different paths, because the dynamics of its development depends on how the (eco)system is configured and which is his level of smartness. It also should be considered the history of city and its context to define more assertive strategies and projects. Thus, for the analysis of smart city development, it is necessary to apply an evolutionary framework capable to link micro-behavior to macro- processes that occur in each territory over time. By considering smart city development as a process that changes the urban realm and the behavior of stakeholders over time, there is a need to measure how this is in fact helping (or not) the urban performance and, how cities can achieve a sustainable development in a more efficient way. In this study, it focusses on the measurement of smartness of an urban innovation ecosystem, because it provides an overview of the current stage of development and the relationship among the elements and dimensions, which could guide policymakers and the society on what invest, how to design a comprehensive strategy and when to implement it.As cidades sempre foram locais onde as economias de aglomeração atingiram seus maiores rendimentos, produzindo benefícios culturais, econômicos e sociais sendo o principal locus de empreendedorismo e inovação. No entanto, a rápida urbanização criou muitos problemas como desigualdade, poluição, doenças, insegurança e assim por diante, que acabam por restringir a dinâmica de criação de valor no século XXI. Isso está desafiando as "cidades industriais" a repensar e remodelar suas estruturas para superar esses problemas. Nesse sentido, o modelo de 'cidade inteligente' tem ganhado destaque no desenvolvimento urbano. Muitas cidades de diferentes países estão desenhando estratégias e implementando-as por meio de iniciativas e projetos para o desenvolvimento de cidades inteligentes. Nota-se que essas experiências são idiossincráticas, pois as cidades são inerentemente diferentes e possuem questões diversas que devem ser resolvidas de forma particular. A primeira questão que surge é: como tornar uma cidade mais inteligente? Apesar da visão contrastante dos frameworks e de sua multiplicidade de dimensões e abordagens, a literatura aponta que as cidades devem ter elementos específicos para induzir processos de inovação por meio de soluções digitais e da colaboração entre stakeholders para enfrentar os desafios locais e, assim, aumentar a competitividade local e qualidade de vida. No entanto, não é uma tarefa fácil e envolve um conjunto de stakeholders que podem não estar dispostos a colaborar e promover o desenvolvimento de cidades inteligentes. De fato, as principais dificuldades de uma estratégia surgem durante a fase de implementação, pois muitos dos desafios para as cidades se tornarem ou serem inteligentes excedem o escopo e as capacidades de suas atuais organizações, arranjos institucionais e estruturas de governança. De fato, as principais dificuldades de uma estratégia surgem durante a fase de implementação, pois muitos dos desafios para as cidades se tornarem ou serem inteligentes excedem o escopo e as capacidades de suas atuais organizações, arranjos institucionais e estruturas de governança. Com efeito, a falta de formações estruturais e organizativas adequadas não favorece o envolvimento dos atores locais e dificulta a organização e coordenação das diferentes atividades necessárias para alcançar um desenvolvimento urbano sustentável. Então, a segunda questão que surge é: que tipo de organização pode fomentar o desenvolvimento de cidades inteligentes? Nesse sentido, a literatura lança luz sobre a necessidade de discutir modelos alternativos de governança para superar esses desafios, combinando apoio político e social com planejamento estratégico e pensamento criativo para lidar com a complexidade da cidade inteligente. Alguns autores apontam que é necessário criar uma organização dedicada a liderar a colaboração entre as partes interessadas neste processo de transformação urbana. A partir dessa discussão, o que parece claro é que a análise do processo de desenvolvimento de uma smart city em suas diferentes dimensões e unidades de análise demanda um embasamento teórico que permita à academia e à indústria captar a dinâmica da evolução e, assim, compreender como as smart cities mudam com o tempo. É preciso incorporar teorias e conceitos que considerem não apenas a noção de espaço-tempo, mas principalmente que se aprofundem em como as relações entre os elementos do ecossistema interagem e se complementam. Então, nossa terceira pergunta é: como analisar esse processo de desenvolvimento urbano dinâmico, dependente do contexto e de longo prazo para que uma cidade se torne mais inteligente? Alguns autores apontam a possibilidade de uma aproximação teórica entre a abordagem evolutiva e a literatura de cidades inteligentes, afirmando que devido à complexidade do desenvolvimento de cidades inteligentes, o planejamento de cidades inteligentes também é moldado por processos evolutivos. Assim, é necessário incorporar a noção de evolução nos processos de transformação urbana e que eles ocorram em uma determinada localização geográfica sendo condicionados por fatores contextuais locais. Como mencionado anteriormente, as cidades são inerentemente diferentes e têm problemas diferentes. Assim, medir o nível de desenvolvimento existente é crucial para prever os passos certos para aumentar a inteligência urbana. A inteligência deve ser vista como um continuum, no qual as partes interessadas podem implementar iniciativas para criar, melhorar ou alterar os elementos da cidade inteligente nessas diferentes dimensões da cidade. A noção de smartness pode ajudar as cidades a entender como esse processo de transformação urbana afeta suas dimensões e seu desempenho e, consequentemente, analisar o que deve ser feito para acelerá- lo. Nesse sentido, é importante que as cidades avaliem seu atual estágio de desenvolvimento. A avaliação do desenvolvimento de cidades inteligentes pode trazer múltiplos benefícios para diferentes partes interessadas. Permite identificar os pontos fortes e fracos da cidade, comparar cidades, monitorar e acompanhar a implementação de projetos, aumentar a transparência nos investimentos, possibilitar a formulação de políticas com base em evidências, aumentar a conscientização do cidadão e assim por diante. A quarta questão que surge é: como medir a inteligência de uma cidade? Em termos de avaliação de cidades inteligentes, muitos acadêmicos, organizações e empresas desenvolveram índices, kits de ferramentas e benchmarking para medir e classificar cidades inteligentes. Esses esquemas de avaliação podem fornecer uma boa visão geral sobre as características da cidade e seus pontos fortes e fracos, além de serem usados para mostrar sua posição competitiva. No entanto, a maioria deles negligencia os múltiplos processos inter-relacionados relacionados ao desenvolvimento da cidade inteligente, adotando uma abordagem somativa. Essa abordagem apresenta algumas limitações que não capturam adequadamente a inteligência de uma cidade. Considerando isso, os objetivos deste estudo são (1) identificar as dimensões e os elementos impulsionadores para tornar uma cidade mais inteligente, (2) entender o papel da organização dedicada a cidades inteligentes na governança de cidades inteligentes, (3) propor uma abordagem evolutiva framework para a análise do desenvolvimento de cidades inteligentes e (4) criar um modelo para medir a inteligência de uma cidade usando diferentes métodos, considerando o tipo de dados, sua manipulação e análise. Para atingir esses objetivos, a pesquisa se concentrou em entender o conceito de cidades inteligentes e que seu desenvolvimento depende de um processo não linear, que deve seguir algumas etapas como desenhar estratégias, implementá-las por meio de projetos para resolver os problemas urbanos atuais. Para isso, o estabelecimento de uma estrutura de governança é crucial para o sucesso do desenvolvimento de cidades inteligentes, pois é necessária a colaboração para criar soluções complexas e a legitimidade de uma visão. Portanto, uma organização dedicada é importante para articular as partes interessadas e impulsionar o desenvolvimento de projetos e iniciativas. No entanto, apenas redes colaborativas não resolverão os problemas urbanos per se. Deve ser identificado como criar, melhorar, mudar os elementos das dimensões hard e soft de uma cidade (ou seja, econômica, social, ambiental). É importante destacar que uma estratégia, projeto ou solução inteligente para ser inteligente de fato deve considerar que essas dimensões estão integradas e então afetam e são afetadas umas pelas outras. Além disso, é necessário incorporar neste discurso de planejamento e gestão urbana a noção de tempo e espaço, pois eventos passados podem afetar o atual estágio de desenvolvimento e as decisões presentes impactarão o futuro da cidade. Como processo evolutivo, cada cidade certamente seguirá caminhos diferentes, pois a dinâmica de seu desenvolvimento depende de como o (eco)sistema se configura e qual é o seu nível de inteligência. Também deve ser considerada a história da cidade e seu contexto para definir estratégias e projetos mais assertivos. Assim, para a análise do desenvolvimento de cidades inteligentes, é necessário aplicar um quadro evolutivo capaz de vincular o microcomportamento aos macroprocessos que ocorrem em cada território ao longo do tempo. Ao considerar o desenvolvimento de cidades inteligentes como um processo que muda o ambiente urbana e o comportamento dos stakeholders ao longo do tempo, há a necessidade de medir como isso está de fato ajudando (ou não) o desempenho urbano e como as cidades podem alcançar um desenvolvimento sustentável em uma forma mais eficiente. Este artigo tem como foco a mensuração da inteligência de um ecossistema de inovação urbana, pois fornece uma visão geral do estágio atual de desenvolvimento e a relação entre os elementos e dimensões, o que poderá orientar os formuladores de políticas e a sociedade sobre o que investir, como projetar uma estratégia abrangente e quando implementá-la
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Policy options for food system transformation in Africa and the role of science, technology and innovation
As recognized by the Science, Technology and Innovation Strategy for Africa – 2024 (STISA-2024), science, technology and innovation (STI) offer many opportunities for addressing the main constraints to embracing transformation in Africa, while important lessons can be learned from successful interventions, including policy and institutional innovations, from those African countries that have already made significant progress towards food system transformation. This chapter identifies opportunities for African countries and the region to take proactive steps to harness the potential of the food and agriculture sector so as to ensure future food and nutrition security by applying STI solutions and by drawing on transformational policy and institutional innovations across the continent. Potential game-changing solutions and innovations for food system transformation serving people and ecology apply to (a) raising production efficiency and restoring and sustainably managing degraded resources; (b) finding innovation in the storage, processing and packaging of foods; (c) improving human nutrition and health; (d) addressing equity and vulnerability at the community and ecosystem levels; and (e) establishing preparedness and accountability systems. To be effective in these areas will require institutional coordination; clear, food safety and health-conscious regulatory environments; greater and timely access to information; and transparent monitoring and accountability systems
Advanced seismic characterization of a geothermal carbonate reservoir – insight into the structure and diagenesis of a reservoir in the German Molasse Basin
The quality of geothermal carbonate reservoirs is controlled by, for instance, depositional environment, lithology, diagenesis, karstification, fracture networks, and tectonic deformation. Carbonatic rock formations are thus often extremely heterogeneous, and reservoir parameters and their spatial distribution difficult to predict. Using a 3D seismic dataset combined with well data from Munich, Germany, we demonstrate how a comprehensive seismic attribute analysis can significantly improve the understanding of a complex carbonate reservoir. We deliver an improved reservoir model concept and identify possible exploitation targets within the Upper Jurassic carbonates. We use seismic attributes and different carbonate lithologies from well logs to identify parameter correlations. From this, we obtain a supervised neural-network-based 3D lithology model of the geothermal reservoir. Furthermore, we compare fracture orientations measured in seismic (ant-tracking analysis) and well scale (image log analysis) to address scalability. Our results show that, for example, acoustic impedance is suitable to identify reefs and karst-related dolines, and sweetness proves useful to analyse the internal reef architecture, whereas frequency- and phase-related attributes allow the detection of karst. In addition, reef edges, dolines, and fractures, associated with high permeabilities, are characterized by strong phase changes. Fractures are also identified using variance and ant tracking. Morphological characteristics, like dolines, are captured using the shape index. Regarding the diagenetic evolution of the reservoir and the corresponding lithology distribution, we show that the Upper Jurassic carbonate reservoir experienced a complex evolution, consisting of at least three dolomitization phases, two karstification phases, and a phase of tectonic deformation. We observe spatial trends in the degree of dolomitization and show that it is mainly facies-controlled and that karstification is facies- and fault-controlled. Karstification improves porosity and permeability, whereas dolomitization can either increase or decrease porosity. Therefore, reservoir zones should be exploited that experienced only weak diagenetic alteration, i.e. the dolomitic limestone in the upper part of the Upper Jurassic carbonates. Regarding the fracture scalability across seismic and well scales, we note that a general scalability is, due to a combination of methodological limitations and geological reasons, not possible. Nevertheless, both methods provide an improved understanding of the fracture system and possible fluid pathways. By integrating all the results, we are able to improve and adapt recent reservoir concepts, to outline the different phases of the reservoir's structural and diagenetic evolution, and to identify high-quality reservoir zones in the Munich area. These are located southeast at the Ottobrunn Fault and north of the Munich Fault close to the Nymphenburg Fault.</p
Improved thermodynamic investigation of asphaltene precipitation
Asphaltenes are analogous to the “cholesterol” of crude oils, so they may cause significant flow assurance problems to various oil and gas processes and negatively affect the economy of the oil recovery, transportation, and processing by increasing operational expenditures (OPEX). Asphaltenes increase oil viscosity, decrease its market value, and, when they precipitate, cause flow assurance challenges. Understanding asphaltene precipitation and phase behaviour is important to avoid, prevent, and address asphaltene flow assurance challenges. An experimental investigation is time-consuming and requires laboratory expertise with limitations on how many experiments can reasonably be conducted over what range of feasible operating conditions. Furthermore, we need to predict asphaltene and fluid phase behaviour over the full range of operating conditions to avoid flow assurance issues. Therefore, having a thorough knowledge of the phenomenon and applying asphaltene modeling approaches is essential to foresee conditions leading to asphaltene precipitation to treat the phenomenon properly. Despite significant research, asphaltene behaviour in different operating conditions and the application of improved thermodynamic investigations have not been well understood. There is little research on the investigation of the operating conditions and improvement of the thermodynamic models (e.g., application of advanced optimization technique) on asphaltene precipitation. This thesis uses different modeling approaches (e.g., equation of state) to investigate crude oil asphaltene precipitation at operating conditions.
Asphaltene phase separation can be triggered by altering the operating conditions, e.g., temperature, composition, and adding n-alkanes. For instance, decreasing temperature from reservoir conditions leads to asphaltene precipitation due to alteration of the solubility of asphaltene in the oil mixture. Moreover, the composition of crude oil is upgraded or downgraded
by adding different hydrocarbons at the refinery inlet. Yet, the prediction of asphaltene precipitation and the impact of operating conditions are quite uncertain, and detailed thermodynamic investigations and appropriate techniques for adjusting the models are required.
Several research studies have used thermodynamic equations of state (EoS) to model asphaltene precipitation. Recently, advanced EoSs that take into account the association of hydrogen bonding has become popular. For example, Cubic Plus Association (CPA) has shown promising results in modeling asphaltene precipitation. There is uncertainty in using EoSs, e.g., tuning the adjustable parameters. Hence, there is a need to systematically study how to adjust the tunable parameters to predict asphaltene precipitation using advanced EoS.
The objective of this research is to investigate and improve the performance of EoS modeling of asphaltene precipitation. For this purpose, first, a comprehensive literature review was conducted to address asphaltene precipitation from different standpoints. While a comprehensive literature review to study asphaltene precipitation and deposition was missing in the literature, the focus of this research is to provide an overview of the nature and physical properties of asphaltenes, experimental and thermodynamic/simulation tools investigations, operating/fluid/reservoir impact, inhibition/treatment, and economic analysis of flow assurance. The literature review findings highlighted two main gaps in asphaltene thermodynamic modeling; 1) only gradient-based optimization techniques have been used to tune the EoS parameters, and 2) the effect of heteroatoms in asphaltene precipitation has not been considered. Therefore, the two other objectives of this thesis are tailored to address the gaps.
In order to address the fact that only gradient-based methods have been used to tune the parameters, we used a global optimization approach instead of gradient-based optimization to relate and correlate hydrogen bonding to the binary interaction parameters of the Cubic Plus Association
(CPA) EoS model. While the application of advanced optimization methods and a systematic sensitivity analysis of operational conditions/BIPs were missing in the literature, the focus of this section is to consider the association of hydrogen bonding in asphaltene precipitation while developing correlations for binary interactions (BIs) using global optimization. The advantages of using global optimization are to avoid entrapment in local minima while optimizing the parameters of the EoS and to improve the correlation/prediction capability of the EoS by finding the best fit of the adjustable parameters. The CPA EoS is validated by predicting unseen data, comparing with cubic EoSs, i.e., SRK and PR, using different oil characterization, e.g., SARA analysis, and drawing an analogy between scaling equation and CPA. Application of the proposed technique significantly improved the performance of the CPA EoS in modeling asphaltene precipitation (average deviation of less than 0.067 for correlation and prediction). The relative importance analysis revealed that the composition of the mixture (dilution ratio) is the most influential factor contributing to the asphaltene precipitation (other factors are temperature and carbon number of the diluents).
The effect of polar forces due to the presence of heteroatoms on asphaltene phase behaviour is investigated using a Cubic Plus Polar EoS (CPP). To the best of our knowledge, we have not found any literature focused on polar heteroatom forces in asphaltene thermodynamic modeling. In this novel work, we demonstrate how a single term that accounts for polarity can be added to the extension of the cubic EoS and be effectively applied to calculate asphaltene precipitation. Further, a simplified oil characterization method is adapted to reduce the number of adjustable parameters (binary interactions) and reduce the need for experimental measurements. A global optimization approach and molecular dynamic (MD) simulation have also been used to increase the reliability of the optimization and reduce the number of adjustable parameters for polar forces. This section
of the research finds that the CPP approach using global optimization to tune parameters of the EoS is the most reliable approach, followed by CPP EoS using MD to find dipole moment for the aryl-linked core asphaltene structure (average R2 for both modes are above 0.98).
The improved thermodynamic approaches (global optimization and including the effect of heteroatoms) introduced in this research can be used by other researchers to increase the efficiency of the asphaltene thermodynamic modeling
Advanced gasification applications of direct carbon dioxide utilisation in integrated biomass energy cycles
International agreements seek to limit climate warming to no more than 2℃. For this goal to be achieved, drastic reductions in CO2 emissions from fossil fuels must be realised in very short timelines. In fact, most climate modelling predictions indicate CO2 will need to be removed from the atmosphere if the worst effects of climate change are to be avoided. Renewable biomass energy and biomass energy with carbon capture and storage (BECCS) will feature prominently in this substantial decarbonisation regime. Despite this technical forecast, BECCS technologies are unproven at scale. Innovative carbon dioxide utilisation (CDU) strategies are posited as a method for improvement of biomass energy system performance.
Partially recycling CO2-rich exhaust gases from a syngas fuelled internal combustion engine to a biomass gasifier has the capability to realise a new method for direct carbon dioxide utilisation (CDU) within a bioenergy system. Simulation of an integrated, airblown biomass gasification power cycle was used to study thermodynamic aspects of this emerging CDU technology. Analysis of the thermodynamic system model at varying gasifier air ratios and exhaust recycling ratios revealed the potential for modest system improvements under limited recycling ratios. Compared to a representative base thermodynamic case with overall system efficiency of 28.14%, employing exhaust gas recycling (EGR) enhanced gasification improved system efficiency to 29.24% and reduced the specific emissions by 46.2 g-CO2/kWh. Although emissions from biomass power cycles can ultimately be considered CO2-neutral over time, this reduction in specific emissions from the cycle can minimise the “carbon debt” effect incurred during the initial deployment of biomass power sources.
Further investigation of the EGR-enhanced gasification system revealed the important coupling between gasification equilibrium temperature and exhaust gas temperature through the syngas lower heating value (LHV). Major limitations to the thermodynamic conditions of EGR-enhanced gasification as a CDU strategy result from the increased dilution of the syngas fuel by N2 and CO2 at high recycling ratios, restricting equilibrium temperatures and reducing gasification efficiency. N2 dilution in the system reduces the efficiency by up to 2.5% depending on the gasifier air ratio, causing a corresponding increase in specific CO2 emissions. Thermodynamic modelling indicates pre-combustion N2 removal from an EGR gasification system could decrease specific CO2 emissions by 9.73%, emitting 118.5 g/kWh less CO2 than the basic system.
A similar method for improving the efficiency of oxyfuel gasification biomass energy with carbon capture and storage (BECCS) cycles using carbon dioxide recycled from exhaust gases is described and modelled. Thermodynamic simulations show this process can increase the indicated efficiency of a representative cycle by 10.3% in part by reducing the oxygen requirements for the gasification reaction. Exhaust recycling is also shown to have a practical limit beyond which the syngas fuel becomes highly diluted. This diluted syngas results in low combustion and exhaust temperatures which, in turn, negatively influence the gasification process during exhaust recycling. For the system presented here, CO2- enhanced gasification is thermodynamically limited to equivalence ratios above λ = 0.13 and equilibrium temperatures above 576°C. This thermodynamically limited case produced an indicated system efficiency of 26.9% based on supplied biomass lower heating value (LHV). Further simulations using both ideal cycles and detailed numerical models highlight the influence of several operational settings on the thermodynamic conditions of the gasification process. Principally, the coupling between exhaust temperatures, allothermal heat, and syngas quality are shown to govern the performance of the gasification reactions.
Although these simulated equilibrium calculations revealed the fundamental thermodynamic benefit of EGR-gasification cycles, variability in typical gasification processes often produces syngas compositions that differ from chemical equilibrium. An examination of the evolution of syngas from a biomass sample during gasification was needed to assess how these differences occur. Particularly, experimental confirmation that the key CO2 to CO conversion process is achievable under mild temperature conditions was required to verify the feasibility of the novel process described in this work. Results of these experimental investigations have shown the CDU conversion of CO2 into CO under process conditions similar to earlier thermodynamic modelling. Compared to pyrolysis of soda lignin as a representative biomass sample, CO2 gasification produced roughly 69% more CO while consuming 1.1 mmol CO2/g biomass. Although this conversion process performs poorly under the experimental conditions, it does illustrate the viability of the proposed technology. Significant improvement in CO2 conversion and CO production is noted as reaction temperature increases, particularly above 700℃. Additional features of lignin pyrolysis are also illustrated that suggest incomplete conversion of pyrolysis products contribute to a product syngas with higher CH4 content than expected under equilibrium conditions
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