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Controlled application of nanoparticles for remediation in oil and gas application: strategies, challenges, and innovations.
Get PDFThis review provides a detailed examination of strategies for controlling the deposition of nanoparticles in porous media, emphasising the factors influencing their long-term stability and the challenges faced in practical applications. The review explores fundamental mechanisms of nanoparticle retention, including surface modification, intelligent materials, and optimised injection techniques, while discussing environmental and operational variables such as flow velocity, pH, ionic strength, and particle size. The review highlights innovative strategies to maintain nanoparticle stability over time, including responsive ligands, smart nanoparticles, self-healing coatings, and encapsulation techniques. Real-world case studies, including projects from Lockheed Martin, NanoRem, and NANO IRM, illustrate the practical application of these strategies in environmental remediation, emphasising the need for regulatory compliance and long-term monitoring. Overall, this review offers critical insights into the controlled application of nanoparticles for remediation, providing a roadmap for addressing the technical and regulatory challenges associated with their deployment in porous media
Hydrogen at RGU: innovation and supporting it existing ecosystem (Hy-ONE and other projects).
Get PDFAt this SHINe webinar Professor Nadimul Faisal give a presentation detailing the research into hydrogen, its production, storage, utilisation and integration, which is being undertaken at Robert Gordon University. This includes the Hy-One project which is a comprehensive one stop hydrogen storage testing facility, providing plug and play testing demonstrations for hydrogen storage systems
Investigating wire electric-discharge machining (WEDM) parameters for improved machining of D2 steel: a multi-objective optimization study.
Get PDFWire Electric-Discharge Machining (WEDM) represents a non-traditional approach to metal cutting, providing the advantage of precision manufacturing over conventional methods. In recent years, the metal machining industry has witnessed numerous benefits in terms of high speed and accuracy through the utilization of WEDM in both additive and subtractive manufacturing processes. This research focuses on studying the process parameters and their impact on surface roughness, energy consumption, kerf width, and material removal rates in Wire Electric-Discharge Machining of D2 steel. The Taguchi approach to experimental design (L16) was employed to conduct cutting experiments at varying levels of ON Time, OFF Time, Servo Voltage, and Wire Tension. Experimental results were optimized using ANOVA and Grey Relational Analysis to refine the process inputs and achieve performance measures that minimize surface roughness, power consumption, and kerf width while maximizing material removal rate. Statistical analysis revealed that ON Time is the most significant factor (73%) affecting both individual and multiple responses. The optimized model indicates that significant improvements can be simultaneously achieved in all response parameters by selecting the optimal combination of parameters. This not only enhances the part quality but contributes positively towards process sustainability and productivity
Decision-support for offshore oil and gas decommissioning using explainable artificial intelligence.
No full textMany of the 12,000 offshore oil and gas platforms are approaching the end of their lifecycle and the decommissioning decision for these structures is crucial. Multi-criteria Decision Analysis (MCDA) is frequently employed to determine decommissioning options. However, MCDA presents significant inefficiencies including subjectivity, prolonged consultation period and substantial resource requirement. This study proposes an explainable AI (XAI) approach to address these inefficiencies in predicting a suitable decommissioning option using a historical dataset from the United Kingdom. After splitting the dataset into the SURF subset (umbilicals, pipelines and cables) and the Non-SURF subset consisting of all other asset types, five machine learning models- Random Forest, Decision Tree, Neural Networks, Support Vector Machines and K-Nearest Neighbours (kNN) were trained on each subset. The Random Forest model demonstrated superior performance for the Non-SURF subset, achieving a weighted average F1-score of 84%, while the Decision Tree model performed best with the SURF subset with a score of 79%. To further explore the explanation in support of each decommissioning option recommended by the models, Local Interpretable Model-agnostic Explanation (LIME) has been applied. LIME identifies "Position", "Metal", "diameter" and "Residues" as important contributing predictors. In both the SURF and Non-SURF cases, the LIME explainer identified the position of the asset as a key factor in choosing the decommissioning option. Other factors included in the decision-support are the presence of metal for most of the Non-SURF structures and the presence or absence of residues for the SURF structures
Sustainable supply chains: beyond the final product.
No full textGlobally, the fashion industry produces around 92 million tonnes of textile waste annually. This contributes significantly to environmental pollution, with the industry responsible for 10% of global carbon emissions. We consume 62 million tonnes of textiles per year. By 2030, this is expected to reach 102 million tonnes. The fashion industry accounts for 8.1% of global greenhouse gas emissions. The average American throws away approximately 81 pounds of clothing annually, contributing to a total of 26 billion pounds of textile waste in the U.S. alone each year. Globally, 87% of the total fibre input used for clothing is either landfilled or incinerated, with less than 1% being recycled into new garments. The fashion industry is responsible for 20% of global water waste. Government leadership, producer responsibility, and consumer education and awareness will enable market mechanisms that drive higher resource productivity, innovation and economic growth. The phrase "Reduce, Reuse, Recycle" is widely known but this can also be expanded to: Rethink- Be mindful of your consumption, Refuse- Don't consume what you don't need, Reduce- Reduce consumption of energy and materials, Re-use- share with others. Find new uses for old objects, Repair- Fix or upgrade your objects rather than throwing them away, Re-gift- Share, and be a part of the gift economy, Recovery- Energy and materials recovery, Recycle- Close the loop and remake
Experimental study on the effect of biocompetitive exclusion chemical on the unconfined compressive strength of sandstone reservoir rock under static saturation.
Get PDFThe potential impacts of oilfield chemical treatment on the petrophysical and geomechanical properties of reservoir rock are well known. In this paper, the effect of bio-competitive exclusion chemical (sodium nitrate) treatment on sandstone rock properties under static saturation has been examined. A combination of analytical and mechanical testing approaches was used. Analytical methods include scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (SEM/EDX), and X-ray powder diffraction (XRPD) while the mechanical testing method used was unconfined compressive strength (UCS) test. The test results suggest the dissolution and precipitation of new minerals, leading to mineralogical alterations and slightly enhanced porosity from 21.1 ± 0.3% to 21.6 ± 0.1%, indicating an increase of about 2.9%. Results from the unconfined compressive strength (UCS) test show a 0.9% reduction for sandstone. The study suggests that biocompetitive exclusion chemical treatment has an insignificant impact on the geomechanical properties of the sandstone reservoir formation
Animals are my friends: exploring the relationship between animal companionship in childhood and moral concerns in adulthood.
Get PDFResearch on human–animal relationships suggests that close bonds with animals can enhance empathy, reduce speciesism, and improve human physical and psychological health. This study investigated whether pet ownership—particularly attachment to a companion animal during childhood—is associated with differences in moral concerns toward all animals in adulthood. It also aimed to explore the potential effects of empathy and speciesism on overall moral concerns toward animals. Using self-report questionnaires among 72 participants recruited online, the analyses revealed a significant effect of animal categories on moral concerns, F(1, 1.98) = 59.37, p < 0.001. Mean moral concern scores were significantly higher for companion animals (M = 6.04, SD = 1.15) than for food animals (M = 4.90, SD = 1.44), unappealing wild animals (M = 4.20, SD = 1.87), and appealing wild animals (M = 5.73, SD = 1.32), p < 0.05. Additionally, childhood pet owners reported greater moral concerns for all animals, F(1, 1.98) = 4.87, η2 = 0.065, p < 0.05. Attachment to a companion animal in childhood was positively correlated with moral concerns for all animal categories. Finally, although attachment and empathy were both positively related to moral concern, only attachment was a significant predictor (p < 0.05). Further research is needed to understand the psychological mechanisms influencing views on animal rights and welfare
Leveraging ensemble LLMs and contextual embeddings for case-based reasoning in the legal domain.
Get PDFThis research investigates the integration of Case-Based Reasoning (CBR) with Retrieval-Augmented Generation (RAG) for Large Language Models (LLMs) to enhance the reliability of legal question-answering systems. Thus far, we have developed a structured retrieval mechanism using CBR to improve the contextual relevance of generative outputs. Additionally, we introduced two novel alignment-based evaluation metrics—weighted and unweighted—which demonstrated superior performance over existing baselines in assessing QA responses. Our experimental validation on a legal dataset confirmed the effectiveness of the CBR-RAG approach in improving response accuracy. Moving forward, we aim to refine weighting strategies for alignment metrics and enhance textual representations to improve evaluation robustness. Furthermore, we plan to extend our study beyond the legal domain by conducting a comparative analysis across multiple datasets, ensuring broader applicability of the CBR-RAG framework
Integrating corporate social responsibility strategies for sustainable pipeline maintenance in the Niger Delta region of Nigeria.
Get PDFThe Niger Delta area of Nigeria, which are known to be very rich in oil reserves, encounter degradations around the environment, socio-economic disturbances, and conflicts which are as a results of perceived inadequate maintenance of pipeline. Cooperative Social Responsibility (CSR) has emerged as a technique for a supportable development. Despite the strategy, its integration into maintaining pipeline within the region remains unsatisfactory. This study checks CSR- driven pipeline maintenance techniques using a quantitative approach, surveying 150 residents across the Niger Delta region which run over a period of three months. According to findings, it was revealed that there exist serious gaps in CSR execution, with about 66.67% of respondents having the feelings of abandonment by government authorities and oil companies. 50% reported water pollution, and 40% faced the problem of respiratory health issues, putting the blame on inadequate maintenances. Delayed in cooperate answers to reported problems, and absence of sensitizations campaigns have removed the community trust on these institutions. Some of the economic penalties are: loss of jobs (25%), closures of business (20%), and displacement (15%), pointing out the grievous financial and social impacts of ineffectual maintenances of pipelines. To tackle the problems pointed out in this study, sterner cooperate transparency should be imposed by policymakers, demanding oil companies to reveal the activities of maintenance of pipelines and go through independent CSR audits. Community monitoring programs should be implemented, and advance sensitization efforts as regarding environmental risks. These steps will strengthen cooperate-community relations, drive sustainable development in the Niger Delta and boost environmental protection
Overloaded and isolated? Preliminary findings on overcoming information challenges for incarcerated university students.
Get PDFThis paper outlines two tentative themes identified in the initial findings of a project focusing on the information behaviour of a particular group of incarcerated university students. These students are released on licence to attend lectures and study on campus, but are still affected by prison restrictions. Theories of information landscapes, small worlds and information behaviour in transition have informed this work. This paper presents analysis of the first round of data collection, using a combination of progress logs and interviews. The two key themes outlined here relate to issues of inclusion and exclusion in academic spaces. The first theme reveals issues around information overload, particularly during the induction period, while the second relates to how relationships and restrictions on and off campus affect informal information sharing. The identification of these issues can inform support arrangements for these students, with a focus on academic library support. While these issues are unique to a particular group, they have broader implications for other categories of non-traditional higher education (HE) students
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