Collections in this community

Recent Submissions

  • DEM simulation of a single screw granulator: The effect of liquid binder on granule properties

    Arthur, Tony B.; Sekyi, Nana; Rahmanian, Nejat (2024-03)
    The Caleva UK single-screw Variable Density Extruder (VDE) is a continuous powder processing equipment known for spheronization and extrusion. Its suitability for granulation remains uncertain, a common challenge in powder processing industries that deal with granules, pellets, and tablets. This study investigates the VDE's potential for granulation, using 65 µm CaCO3 powder and PEG 4000 as a liquid binder. In order to replicate several experimental setups with varying binder concentrations and liquid-to-solid ratios (L/S) of 0.1 and 0.15, eight DEM simulations were run. Our results indicate that higher binder concentrations yield more consistent products with fewer fines, while lower concentrations result in inconsistent products with increased fines. Low L/S ratios produce fragile, fine-sized products with a broad particle size distribution (PSD). DEM simulations reveal a direct relationship between liquid binder content and contact forces. Analysis of bonds formed, and particle counts in simulations corroborates experimental observations of fines production. Additionally, granule strength appears to be directly proportional to contact force.
  • Parametric analysis on flexural performance of reactive powder concrete frame beams reinforced with steel-FRP composite bars

    Ge, W.; Zhang, F.; Sushant, S.; Yao, S.; Ashour, Ashraf; Luo, L.; Jiang, H.; Zhang, Z. (Elsevier, 2024-02)
    To study the flexural behavior of Steel-FRP (Fiber-Reinforced Polymer) Composite Bars (SFCBs) reinforced Reactive Powder Concrete (RPC) frame beams, the flexural behavior of six frame beams with different types of concrete and reinforcement was simulated and analyzed using the finite element software ABAQUS. The strain behavior of concrete and reinforcement was simulated using real strain models, and the simulation results matched well with the experimental results. Based on the validated model, the effect of mechanical properties of concrete and SFCB, reinforcement ratio, and the dimensions of frame beam on the flexural behavior of frame beams was parametrically analyzed. The results showed that, compared with the steel-reinforced ordinary concrete (OC) frame beam, the ultimate deflection of SFCB-OC frame beam increased by 5%. Compared with the SFCB-OC frame beam, the bearing capacity and ultimate deflection of the SFCB-RPC frame beam increased by 16% and 22%, respectively. Improving the steel content of SFCB reduced the ultimate load and deformation of SFCB-RPC frame beam. The yield strength of SFCB core steel had a significant influence on the yield load of frame beam, but a small influence on the ultimate load and deformation. Enhancing the elastic modulus of SFCB out-wrapped FRP reduced the ultimate deformation of the frame beam. Improving the reinforcement ratio of SFCB increased the bearing capacity and reduced the deformation. When reinforced concrete frame beams had similar bearing capacity, the cross-sectional dimensions of steel-RPC frame beam, FRP-RPC frame beam, and SFCB-RPC frame beam are 90.1%, 61.5%, and 72.7%, respectively, of those of their corresponding respective reinforced OC frame beams. All reinforced RPC frame beams exhibited high bearing capacity, good deformation, ductility, and energy dissipation performance. This research can provide a reference for the design of SFCB-RPC frame beams.
  • Reliability Assessment of IoT-enabled Systems using Fault Trees and Bayesian Networks

    Abdulhamid, Alhassan; Kabir, Sohag; Ghafir, Ibrahim; Lei, Ci (2024-01)
    The Internet of Things (IoT) has brought significant advancements in various domains, providing innovative and efficient solutions. However, ensuring the safe design and operation of IoT devices is crucial, as the consequences of component failure can range from system downtime to dangerous operating states. Several methods have been proposed to evaluate the failure behaviours of IoT-based systems, including Fault Tree Analysis (FTA), a methodology adopted from other safetycritical domains. This study integrated FTA and Bayesian Network (BN) models to assess IoT system reliability based on components’ reliability data and other statistical information. The integrated model achieved efficient predictive failure analysis, considering combinations of 12 basic events to quantify the overall system’s reliability. The model also enables criticality analysis, ranking basic events based on their contributions to system failure and providing a guide for design modification in order to enhance IoT safety. By comparing failure data in FTA and criticality indices obtained using the BN model, the proposed integration offers a probabilistic estimation of IoT system failure and a viable safety guide for designing IoT systems.
  • Electrocatalytic reactors for syngas production from natural gas

    Samiee, L.; Rahmanian, Nejat (Elsevier, 2024-01)
    The emission of greenhouse gases on a global scale is predominantly caused by the utilization of fossil fuels. Various methods have been explored to address the recycling of CO2, which among, the CO2 conversion into high-value chemicals become so promising. The purpose of this book chapter evaluation is CO2 reduction and H2 evolution reactions for producing syngas. A comprehensive analysis shall highlight (i) the technical advantages and impediments of various reactor classifications, (ii) the effect of electrolytes on electrolyzers in the liquid phase, and (iv) the catalysts that are viable for the creation of important products such as CO.
  • Tribological considerations of threaded fastener friction and the importance of lubrication

    Dyson, C.J.; Hopkins, W.A.; Aljeran, D.A.; Fox, M.F.; Priest, Martin (Elsevier Ltd., 2024-03)
    The torque-tension relationship of threaded fasteners affects almost all engineering disciplines. Tribological processes at fastener interfaces manifest as the system's friction coefficient. Lubrication-related influences are usually described empirically using K or μ. The drive towards lightweight fastener materials in engineering systems and lubricants with reduced environmental impact is challenging existing knowledge and industrial practice in a range of applications, many safety critical. More comprehensive understanding is needed to achieve repeatable friction during assembly and re-assembly, resistance to loosening and fretting during operation, and effective anti-seize for disassembly with a growing range of materials and lubricants. The lubricants considered showed three predominant lubrication mechanisms: plastic deformation of metal powders; burnishing/alignment of molybdenum disulphide, MoS2; and adhering/embedding of non-metal particles. Multivariate analysis identified key sensitivities for these mechanisms. Assembly generated changes at fastener surfaces and in the lubricating materials. Re-assembly exhibited significant reductions in friction.
  • Evaluating the irritant factors of silicone and hydrocolloid skin contact adhesives using trans-epidermal water loss, protein stripping, erythema, and ease of removal

    Dyson, Edward; Sikkink, Stephen; Nocita, Davide; Twigg, Peter C.; Westgate, Gillian E.; Swift, Thomas (ACS, 2024-01)
    A composite silicone skin adhesive material was designed to improve its water vapor permeability to offer advantages to wearer comfort compared to existing skin adhesive dressings available (including perforated silicone and hydrocolloid products). The chemical and mechanical properties of this novel dressing were analyzed to show that it has a high creep compliance, offering anisotropic elasticity that is likely to place less stress on the skin. A participant study was carried out in which 31 participants wore a novel silicone skin adhesive (Sil2) and a hydrocolloid competitor and were monitored for physiological response to the dressings. Trans-epidermal water loss (TEWL) was measured pre- and postwear to determine impairment of skin barrier function. Sil2 exhibited a higher vapor permeability than the hydrocolloid dressings during wear. Peel strength measurements and dye counter staining of the removed dressings showed that the hydrocolloid had a higher adhesion to the participants’ skin, resulting in a greater removal of proteins from the stratum corneum and a higher pain rating from participants on removal. Once the dressings were removed, TEWL of the participants skin beneath the Sil2 was close to normal in comparison to the hydrocolloid dressings that showed an increase in skin TEWL, indicating that the skin had been highly occluded. Analysis of the skin immediately after removal showed a higher incidence of erythema following application of hydrocolloid dressings (>60%) compared to Sil2, (
  • Editorial on antennas

    Parchin, N.O.; See, C.H.; Abd-Alhameed, Raed (2023-12)
  • A review of lunar communications and antennas: assessing performance in the context of propagation and radiation

    Serria, E.; Gadhafi, R.; AlMaeeni, S.; Mukhtar, H.; Copiaco, A.; Abd-Alhameed, Raed; Lemieux, F.; Mansoor, W. (2023-12)
    Over the previous two decades, a notable array of space exploration missions have been initiated with the primary aim of facilitating the return of both humans and robots from Earth to the moon. The significance of these endeavors cannot be emphasized enough as numerous entities, both public and private, from across the globe have invested substantial resources into this pursuit. Researchers have committed their efforts to addressing the challenges linked to lunar communication. Even with all of these efforts, only a few of the many suggested designs for communication and antennas on the moon have been evaluated and compared. These designs have also not been shared with the scientific community. To bridge this gap in the existing body of knowledge, this paper conducts a thorough review of lunar surface communication and the diverse antenna designs employed in lunar communication systems. This paper provides a summary of the findings presented in lunar surface communication research while also outlining the assorted challenges that impact lunar communication. Apart from various antenna designs reported in this field, based on their intended usage, two additional classifications are introduced: (a) mission-based antennas-utilized in actual lunar missions-and (b) research-based antennas-employed solely for research purposes. Given the critical need to comprehend and predict lunar conditions and antenna behaviors within those conditions, this review holds immense significance. Its relevance is particularly pronounced in light of the numerous upcoming lunar missions that have been announced.
  • Review of substitutive assistive tools and technologies for people with visual impairments: recent advancements and prospects

    Muhsin, Z.J.; Qahwaji, Rami S.R.; Ghanchi, Faruque; Al-Taee, M. (2024-03)
    The development of many tools and technologies for people with visual impairment has become a major priority in the field of assistive technology research. However, many of these technology advancements have limitations in terms of the human aspects of the user experience (e.g., usability, learnability, and time to user adaptation) as well as difficulties in translating research prototypes into production. Also, there was no clear distinction between the assistive aids of adults and children, as well as between “partial impairment” and “total blindness”. As a result of these limitations, the produced aids have not gained much popularity and the intended users are still hesitant to utilise them. This paper presents a comprehensive review of substitutive interventions that aid in adapting to vision loss, centred on laboratory research studies to assess user-system interaction and system validation. Depending on the primary cueing feedback signal offered to the user, these technology aids are categorized as visual, haptics, or auditory-based aids. The context of use, cueing feedback signals, and participation of visually impaired people in the evaluation are all considered while discussing these aids. Based on the findings, a set of recommendations is suggested to assist the scientific community in addressing persisting challenges and restrictions faced by both the totally blind and partially sighted people.
  • A compact filtering antenna with step and continuous tuning modes for WiMAX cognitive radio communication

    Alnahwi, F.M.; Abdulhameed, A.A.; Ali, N.T.; Al-Yasir, Yasir I.A.; Kubik, Z.; Abdullah, A.S.; Abd-Alhameed, Raed (2023-11)
    This work presents a combination of a cup-shaped monopole antenna and an E-shaped Multi-Mode Resonator (MMR) with the presence of a pair of PIN diodes and a varactor diode to form a compact reconfigurable communication filtering antenna for interweave Cognitive Radio (CR) systems. The proposed filtering antenna operates in the WiMAX band, and it is fabricated on an FR4 substrate with overall dimensions normalized to the wavelength ( λ o ) of the first resonant frequency (0.413λ o × 0.516λ o × 0.0165λ o ). The step and continuous tuning serve the secondary user of the WiMAX CR system to communicate in the absence of the primary users at modifiable resonant frequencies and data rates.When the PIN diodes are OFF, the filtering antenna operates with a fixed odd mode resonant frequency and tunable even mode resonant frequency. This state results in a tunable antenna bandwidth covering a maximum measured frequency range of 3.25-4.02~ GHz and a minimum measured range equal to 3.25-3.58~ GHz. The ON state of the PIN diodes eliminates the antenna matching at the even mode resonant frequency while keeping a strong matching at the odd mode resonant frequency. The resulted operational measured frequency range of the antenna in this state is fixed at 2.9-3.28~ GHz. The filtering antenna has acceptable gain values at the pass band of the E-shaped MMR with a maximum simulated gain value equal to 2.5~ dB and a measured maximum gain equal to 2.48~ dB. The simulated and measured power patterns of the antenna for all diodes states are omnidirectional, which are convenient for portable CR gadgets.
  • Machine Learning for Malware Detection in Network Traffic

    Omopintemi, A.H.; Ghafir, Ibrahim; Eltanani, S.; Kabir, Sohag; Lefoane, Moemedi (2023-12)
    Developing advanced and efficient malware detection systems is becoming significant in light of the growing threat landscape in cybersecurity. This work aims to tackle the enduring problem of identifying malware and protecting digital assets from cyber-attacks. Conventional methods frequently prove ineffective in adjusting to the ever-evolving field of harmful activity. As such, novel approaches that improve precision while simultaneously taking into account the ever-changing landscape of modern cybersecurity problems are needed. To address this problem this research focuses on the detection of malware in network traffic. This work proposes a machine-learning-based approach for malware detection, with particular attention to the Random Forest (RF), Support Vector Machine (SVM), and Adaboost algorithms. In this paper, the model’s performance was evaluated using an assessment matrix. Included the Accuracy (AC) for overall performance, Precision (PC) for positive predicted values, Recall Score (RS) for genuine positives, and the F1 Score (SC) for a balanced viewpoint. A performance comparison has been performed and the results reveal that the built model utilizing Adaboost has the best performance. The TPR for the three classifiers performs over 97% and the FPR performs < 4% for each of the classifiers. The created model in this paper has the potential to help organizations or experts anticipate and handle malware. The proposed model can be used to make forecasts and provide management solutions in the network’s everyday operational activities.
  • Sequential Pattern Mining: A Proposed Approach for Intrusion Detection Systems

    Lefoane, Moemedi; Ghafir, Ibrahim; Kabir, Sohag; Awan, Irfan U. (2023-12)
    Technological advancements have played a pivotal role in the rapid proliferation of the fourth industrial revolution (4IR) through the deployment of Internet of Things (IoT) devices in large numbers. COVID-19 caused serious disruptions across many industries with lockdowns and travel restrictions imposed across the globe. As a result, conducting business as usual became increasingly untenable, necessitating the adoption of new approaches in the workplace. For instance, virtual doctor consultations, remote learning, and virtual private network (VPN) connections for employees working from home became more prevalent. This paradigm shift has brought about positive benefits, however, it has also increased the attack vectors and surfaces, creating lucrative opportunities for cyberattacks. Consequently, more sophisticated attacks have emerged, including the Distributed Denial of Service (DDoS) and Ransomware attacks, which pose a serious threat to businesses and organisations worldwide. This paper proposes a system for detecting malicious activities in network traffic using sequential pattern mining (SPM) techniques. The proposed approach utilises SPM as an unsupervised learning technique to extract intrinsic communication patterns from network traffic, enabling the discovery of rules for detecting malicious activities and generating security alerts accordingly. By leveraging this approach, businesses and organisations can enhance the security of their networks, detect malicious activities including emerging ones, and thus respond proactively to potential threats.
  • Latent Dirichlet Allocation for the Detection of Multi-Stage Attacks

    Lefoane, Moemedi; Ghafir, Ibrahim; Kabir, Sohag; Awan, Irfan U. (2023-12)
    The rapid shift and increase in remote access to organisation resources have led to a significant increase in the number of attack vectors and attack surfaces, which in turn has motivated the development of newer and more sophisticated cyber-attacks. Such attacks include Multi-Stage Attacks (MSAs). In MSAs, the attack is executed through several stages. Classifying malicious traffic into stages to get more information about the attack life-cycle becomes a challenge. This paper proposes a malicious traffic clustering approach based on Latent Dirichlet Allocation (LDA). LDA is a topic modelling approach used in natural language processing to address similar problems. The proposed approach is unsupervised learning and therefore will be beneficial in scenarios where traffic data is not labeled and analysis needs to be performed. The proposed approach uncovers intrinsic contexts that relate to different categories of attack stages in MSAs. These are vital insights needed across different areas of cybersecurity teams like Incident Response (IR) within the Security Operations Center (SOC), the insights uncovered could have a positive impact in ensuring that attacks are detected at early stages in MSAs. Besides, for IR, these insights help to understand the attack behavioural patterns and lead to reduced time in recovery following an incident. The proposed approach is evaluated on a publicly available MSAs dataset. The performance results are promising as evidenced by over 99% accuracy in identified malicious traffic clusters.
  • Failure analysis of IoT-based smart agriculture system: towards sustainable food security

    Rahman, Md M.; Abdulhamid, Alhassan; Kabir, Sohag; Gope, P. (IEEE, 2023-12)
    Internet of Things (IoT)-based smart agriculture systems are increasingly being used to improve agricultural yield. IoT devices used for agricultural monitoring are often deployed in outdoor environments in remote areas. Due to the exposure to harsh environments and the nature of deployment, sensors and other devices are susceptible to an increased rate of failure, which can take a system to unsafe and dangerous states. Failure of a smart agriculture system can cause significant harm to nature and people and reduce agricultural production. To address the concerns associated with the failure of the system, it is necessary to understand how the failures of the components of a system can contribute to causing the overall system failure. This paper adopts Fault Tree Analysis, a widely used framework for failure behaviour analysis in other safety-critical domains, to demonstrate the qualitative failure analysis of smart irrigation systems based on the components’ failure.
  • Qualitative Failure Analysis of IoT-enabled Industrial Fire Detection and Prevention System

    Rahman, Md M.; Abdulhamid, A.; Kabir, Sohag (IEEE, 2023-12)
    The Internet of Things (IoT) has improved our lives through various applications such as home automation, smart city monitoring, environmental monitoring, intelligent farming, and a host of others. IoT is increasingly being used for environmental monitoring to prevent fire incidents and other environmental hazards. However, for IoT systems to function effectively in preventing fire incidents, they must operate in a safe, reliable, and dependable manner. The intelligent sensors and devices that constitute the system are prone to different types of failures, which can lead to unsafe or dangerous conditions. Failure of a fire prevention system can pose significant risks to Health, Safety, and the Environment (HSE). To address these concerns, it is essential to understand how component failures can contribute to the overall system failure. This paper adopts Fault Tree Analysis, a widely used framework for failure behaviour analysis in other safety-critical domains, to qualitatively analyse an intelligent fire detection system in an industrial setting. The analysis outlines the ways in which the system can fail and the necessary prevention mechanism to guard against undesired system failure.
  • A comprehensive review on carbon dioxide sequestration methods

    Mwenketishi, G.; Benkreira, Hadj; Rahmanian, Nejat (2023-12)
    Capturing and storing CO2 (CCS) was once regarded as a significant, urgent, and necessary option for reducing the emissions of CO2 from coal and oil and gas industries and mitigating the serious impacts of CO2 on the atmosphere and the environment. This recognition came about as a result of extensive research conducted in the past. The CCS cycle comes to a close with the last phase of CO2 storage, which is accomplished primarily by the adsorption of CO2 in the ocean and injection of CO2 subsurface reservoir formation, in addition to the formation of limestone via the process of CO2 reactivity with reservoir formation minerals through injectivities. CCS is the last stage in the carbon capture and storage (CCS) cycle and is accomplished chiefly via oceanic and subterranean geological sequestration, as well as mineral carbonation. The injection of supercritical CO2 into geological formations disrupts the sub-surface’s existing physical and chemical conditions; changes can occur in the pore fluid pressure, temperature state, chemical reactivity, and stress distribution of the reservoir rock. This paper aims at advancing our current knowledge in CO2 injection and storage systems, particularly CO2 storage methods and the challenges encountered during the implementation of each method and analyses on how key uncertainties in CCS can be reduced. CCS sites are essentially unified systems; yet, given the scientific context, these storage systems are typically split during scientific investigations based on the physics and spatial scales involved. Separating the physics by using the chosen system as a boundary condition is a strategy that works effectively for a wide variety of physical applications. Unfortunately, the separation technique does not accurately capture the behaviour of the larger important system in the case of water and gas flow in porous media. This is due to the complexity of geological subsurface systems, which prevents the approach from being able to effectively capture the behaviour of the larger relevant system. This consequently gives rise to different CCS technology with different applications, costs and social and environmental impacts. The findings of this study can help improve the ability to select a suitable CCS application method and can further improve the efficiency of greenhouse gas emissions and their environmental impact, promoting the process sustainability and helping to tackle some of the most important issues that human being is currently accounting global climate change. Though this technology has already had large-scale development for the last decade, some issues and uncertainties are identified. Special attention was focused on the basic findings achieved in CO2 storage operational projects to date. The study has demonstrated that though a number of CCS technologies have been researched and implemented to date, choosing a suitable and acceptable CCS technology is still daunting in terms of its technological application, cost effectiveness and socio-environmental acceptance.
  • Exploring Radio Frequency Techniques for Bone Fracture Detection: A Comprehensive Review of Low Frequency and Microwave Approaches

    Ahmad, Aldelemy; Ebenezer, Adjei; Prince, Siaw; Buckley, John; Hardy, Maryann; Qahwaji, Rami S.R.; Abd-Alhameed, Raed; Bastos, J.; Barbosa, C.; Elfergani, I.; et al. (2023-09-13)
    This comprehensive review paper examines bone fracture detection techniques based on time-domain low-frequency and microwave radiofrequency (RF). Early and accurate diagnosis of bone fractures remains critical in healthcare, as it can significantly improve patient outcomes. This review focuses on the potential of low-frequency and microwave RF methods, particularly their combination and application of time-domain analysis for enhanced fracture detection. We begin by providing an overview of the fundamental concepts of RF techniques and then by examining biological tissues' dielectric properties. We then compare the advantages and limitations of various bone fracture detection techniques, such as low-frequency RF methods, microwave RF methods, ultrasonography, X-ray, and CT scans. The discussion then shifts to hybrid approaches that combine low-frequency and microwave techniques, emphasising the advantages of such combinations in fracture detection. Machine learning techniques, their applications in bone fracture detection, and the role of time-domain analysis in hybrid approaches are also investigated. Finally, we examine the accuracy and reliability of simulated models for bone fracture detection. We discuss recent advancements and future directions, such as novel sensor technologies, improved signal processing techniques, integration with medical imaging modalities, and personalised fracture detection approaches. This review aims to comprehensively understand the landscape and future potential of time-domain analysis in low-frequency and microwave RF techniques for bone fracture detection.
  • Monitoring damage of concrete beams via self-sensing cement mortar coating with carbon nanotube-nano carbon black composite fillers

    Qiu, L.; Li, L.; Ashour, Ashraf; Ding, S.; Zhang, L.; Han, B. (2024)
    Self-sensing concrete used in coating form for structural health monitoring of concrete structures has the merits of cost-effectiveness, offering protective effect on structural components, enabling electrical measurements unaffected by steel reinforcement and is also convenient to maintain and replace. This paper investigates the feasibility of using self-sensing cement mortar coating containing carbon nanotube-nano carbon black (CNT-NCB) composite fillers (CNCFs) for damage monitoring of concrete beams. The self-sensing cement mortar coated to concrete beams demonstrated outstanding electrical conductivity (resistivity ranging from 18 to 85 Ω·cm). Under monotonic flexural loadings, self-sensing cement mortar coating with 1.8 vol.% CNCFs featured sensitive self-sensing performance in terms of capturing the initiation of vertical cracks at pure bending span of concrete beams, with fractional change in resistivity (FCR) reaching up to 60.6%. Moreover, FCR variations of self-sensing cement mortar coating exhibited good synchronization and stability with the variation of mid-span deflections of concrete beams during cyclic flexural loadings irrespective of the contents of CNCFs and cyclic amplitudes. Remarkably, it was found that FCR of cement mortar coating basically showed a progressive upward tendency, representing irreversible increase in the resistance during cyclic loading. The irreversible residual FCR indicated the crack occurrence and damage accumulation of concrete beams.
  • A curved single-layer FSS design for gain improvement of a compact size CPW-fed UWB monopole antenna

    Daira, S.E.I.; Lashab, M.; Berkani, H.A.; Belattar, M.; Gharbia, Ibrahim; Abd-Alhameed, Raed (2024-01)
    A Novel design of a curved single-layered frequency selective surface with an 11 × 11 array of a 13 × 13 mm-sized unit cell has been merged with a miniaturized, CPW-fed ultra-wideband monopole of dimensions (20 × 25 mm2) for gain enhancement. The suggested prototype, crafted on an FR-4 dielectric substrate and demonstrates a very broad bandwidth starting from 2.66 to 17.98 GHz (148%), which covers the entire UWB frequency band. The combined antenna-curved FSS reflector shows a very important gain improvement from 0.2–5.4 dB to 8.8–14.9 dB, having a peak gain increase of 10 dB at 10.6 GHz. Basic design features were studied and discussed through simulations, yielding promising results The proposed structure can be used in UWB and GPR applications.
  • Carbon dioxide sequestration methodothologies - A review

    Mwenketishi, G.; Benkreira, Hadj; Rahmanian, Nejat (Scientific Research Publishing, 2023-12)
    The process of capturing and storing carbon dioxide (CCS) was previously considered a crucial and time-sensitive approach for diminishing CO2 emissions originating from coal, oil, and gas sectors. Its implementation was seen necessary to address the detrimental effects of CO2 on the atmosphere and the ecosystem. This recognition was achieved by previous substantial study efforts. The carbon capture and storage (CCS) cycle concludes with the final stage of CO2 storage. This stage involves primarily the adsorption of CO2 in the ocean and the injection of CO2 into subsurface reservoir formations. Additionally, the process of CO2 reactivity with minerals in the reservoir formations leads to the formation of limestone through injectivities. Carbon capture and storage (CCS) is the final phase in the CCS cycle, mostly achieved by the use of marine and underground geological sequestration methods, along with mineral carbonation techniques. The introduction of supercritical CO2 into geological formations has the potential to alter the prevailing physical and chemical characteristics of the subsurface environment. This process can lead to modifications in the pore fluid pressure, temperature conditions, chemical reactivity, and stress distribution within the reservoir rock. The objective of this study is to enhance our existing understanding of CO2 injection and storage systems, with a specific focus on CO2 storage techniques and the associated issues faced during their implementation. Additionally, this research examines strategies for mitigating important uncertainties in carbon capture and storage (CCS) practises. Carbon capture and storage (CCS) facilities can be considered as integrated systems. However, in scientific research, these storage systems are often divided based on the physical and spatial scales relevant to the investigations. Utilising the chosen system as a boundary condition is a highly effective method for segregating the physics in a diverse range of physical applications. Regrettably, the used separation technique fails to effectively depict the behaviour of the broader significant system in the context of water and gas movement within porous media. The limited efficacy of the technique in capturing the behaviour of the broader relevant system can be attributed to the intricate nature of geological subsurface systems. As a result, various carbon capture and storage (CCS) technologies have emerged, each with distinct applications, associated prices, and social and environmental implications. The results of this study have the potential to enhance comprehension regarding the selection of an appropriate carbon capture and storage (CCS) application method. Moreover, these findings can contribute to the optimisation of greenhouse gas emissions and their associated environmental consequences. By promoting process sustainability, this research can address critical challenges related to global climate change, which are currently of utmost importance to humanity. Despite the significant advancements in this technology over the past decade, various concerns and ambiguities have been highlighted. Considerable emphasis was placed on the fundamental discoveries made in practical programmes related to the storage of CO2 thus far. The study has provided evidence that despite the extensive research and implementation of several CCS technologies thus far, the process of selecting an appropriate and widely accepted CCS technology remains challenging due to considerations related to its technological feasibility, economic viability, and societal and environmental acceptance.

View more