Now showing items 1-20 of 2028

    • Estimation of Dulling Rate and Bit Tooth Wear Using Drilling Parameters and Rock Abrasiveness

      Mazen, Ahmed Z.; Rahmanian, Nejat; Mujtaba, Iqbal M.; Hassanpour, A. (2019)
      Optimisation of the drilling operations is becoming increasingly important as it can significantly reduce the oil well development cost. One of the major objectives in oil well drilling is to increase the penetration rate by selecting the optimum drilling bit based on offset wells data, and adjust the drilling factors to keep the bit in good condition during the operation. At the same time, it is important to predict the bit wear and the time to pull out the bit out of hole to prevent fishing jobs. Numerous models have been suggested in the literature for predicting the time to pull the bit out to surface rather than predict or estimate the bit wear rate. Majority of the available models are largely empirical and can be applied for limited conditions, and do not include all the drilling parameters such as the formation abrasiveness and bit hydraulic. In this paper, a new approach is presented to improve the drill bit wear estimation that consists of a combination of both Bourgoyne and Young (BY) drilling rate model and theory of empirical relation for the effects of rotary speed (RPM), and weight on bit (WOB) on drilling arte (ROP) and rate of tooth wear. In addition to the drilling parameters, the formation abrasiveness and the effect of the jet impact force of the mud have also been accounted to estimate the bit wear. The proposed model enables estimation of the rock abrasiveness, and that lead to calculate the dynamic dulling rate of the bit while drilling that used in more accurate to assess the bit tooth wear compared with the mechanical specific energy (MSE). Then the estimated dulling rate at the depth of pulling out is used to determine the dull grade of the bit. The technique is validated in five wells located in two different oil fields in Libya. All studied wells in this showed a good agreement between the actual bit tooth wear and the estimated bit tooth wear.
    • Development of sensing concrete: principles, properties and its applications

      Siqi Ding, Sufen Dong, Ashraf Ashour, Baoguo Han; Ding, S.; Dong, S.; Ashour, Ashraf F.; Han, B. (AIP publishing, 2020)
      Sensing concrete has the capability to sense its condition and environmental changes, including stress (or force), strain (or deformation), crack, damage, temperature and humidity through incorporating functional fillers. Sensing concrete has recently attracted major research interests, aiming to produce smart infrastructures with elegantly integrated health monitoring abilities. In addition to having highly improved mechanical properties, sensing concrete has multifunctional properties, such as improved ductility, durability, resistance to impact, and most importantly self-health monitoring due to its electrical conductivity capability, allowing damage detection without the need of an external grid of sensors. This tutorial will provide an overview of sensing concrete, with attentions to its principles, properties, and applications. It concludes with an outline of some future opportunities and challenges in the application of sensing concrete in construction industry.
    • Correlating nano-scale surface replication accuracy and cavity temperature in micro-injection moulding using in-line process control and high-speed thermal imaging

      Baruffi, F.; Gülçür, Mert; Calaon, M.; Romano, J.-M.; Penchev, P.; Dimov, S.; Whiteside, Benjamin R.; Tosello, G. (2019-11)
      Micro-injection moulding (μIM) stands out as preferable technology to enable the mass production of polymeric components with micro- and nano-structured surfaces. One of the major challenges of these processes is related to the quality assurance of the manufactured surfaces: the time needed to perform accurate 3D surface acquisitions is typically much longer than a single moulding cycle, thus making impossible to integrate in-line measurements in the process chain. In this work, the authors proposed a novel solution to this problem by defining a process monitoring strategy aiming at linking sensitive in-line monitored process variables with the replication quality. A nano-structured surface for antibacterial applications was manufactured on a metal insert by laser structuring and replicated using two different polymers, polyoxymethylene (POM) and polycarbonate (PC). The replication accuracy was determined using a laser scanning confocal microscope and its dependence on the variation of the main μIM parameters was studied using a Design of Experiments (DoE) experimental approach. During each process cycle, the temperature distribution of the polymer inside the cavity was measured using a high-speed infrared camera by means of a sapphire window mounted in the movable plate of the mould. The temperature measurements showed a high level of correlation with the replication performance of the μIM process, thus providing a fast and effective way to control the quality of the moulded surfaces in-line.
    • Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks

      Kabir, Sohag; Taleb-Berrouane, M.; Papadopoulos, Y. (2019)
      Flaring is a combustion process commonly used in the oil and gas industry to dispose flammable waste gases. Flare flameout occurs when these gases escape unburnt from the flare tip causing the discharge of flammable and/or toxic vapor clouds. The toxic gases released during this process have the potential to initiate safety hazards and cause serious harm to the ecosystem and human health. Flare flameout could be caused by environmental conditions, equipment failure, and human error. However, to better understand the causes of flare flameout, a rigorous analysis of the behavior of flare systems under failure conditions is required. In this article, we used fault tree analysis (FTA) and the dynamic Bayesian network (DBN) to assess the reliability of flare systems. In this study, we analyzed 40 different combinations of basic events that can cause flare flameout to determine the event with the highest impact on system failure. In the quantitative analysis, we use both constant and time-dependent failure rates of system components. The results show that combining these two approaches allows for robust probabilistic reasoning on flare system reliability, which can help improving the safety and asset integrity of process facilities. The proposed DBN model constitutes a significant step to improve the safety and reliability of flare systems in the oil and gas industry.
    • A Conceptual Framework to Incorporate Complex Basic Events in HiP-HOPS

      Kabir, Sohag; Aslansefat, K.; Sorokos, I.; Papadopoulos, Y.; Gheraibia, Y. (2019-10-11)
      Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) have made the reliability analysis process less expensive in terms of effort and time required. HiP-HOPS uses an analytical modelling approach for Fault tree analysis to automate the reliability analysis process, where each system component is associated with its failure rate or failure probability. However, such non-state-space analysis models are not capable of modelling more complex failure behaviour of component like failure/repair dependencies, e.g., spares, shared repair, imperfect coverage, etc. State-space based paradigms like Markov chain can model complex failure behaviour, but their use can lead to state-space explosion, thus undermining the overall analysis capacity. Therefore, to maintain the benefits of MBSA while not compromising on modelling capability, in this paper, we propose a conceptual framework to incorporate complex basic events in HiP-HOPS. The idea is demonstrated via an illustrative example.
    • Safety + AI: A novel approach to update safety models using artificial intelligence

      Gheraibia, Y.; Kabir, Sohag; Aslansefat, K.; Sorokos, I.; Papadopoulos, Y. (2019-09-16)
      Safety-critical systems are becoming larger and more complex to obtain a higher level of functionality. Hence, modeling and evaluation of these systems can be a difficult and error-prone task. Among existing safety models, Fault Tree Analysis (FTA) is one of the well-known methods in terms of easily understandable graphical structure. This study proposes a novel approach by using Machine Learning (ML) and real-time operational data to learn about the normal behavior of the system. Afterwards, if any abnormal situation arises with reference to the normal behavior model, the approach tries to find the explanation of the abnormality on the fault tree and then share the knowledge with the operator. If the fault tree fails to explain the situation, a number of different recommendations, including the potential repair of the fault tree, are provided based on the nature of the situation. A decision tree is utilized for this purpose. The effectiveness of the proposed approach is shown through a hypothetical example of an Aircraft Fuel Distribution System (AFDS).
    • A Runtime Safety Analysis Concept for Open Adaptive Systems

      Kabir, Sohag; Sorokos, I.; Aslansefat, K.; Papadopoulos, Y.; Gheraibia, Y.; Reich, J.; Saimler, M.; Wei, R. (2019)
      In the automotive industry, modern cyber-physical systems feature cooperation and autonomy. Such systems share information to enable collaborative functions, allowing dynamic component integration and architecture reconfiguration. Given the safety-critical nature of the applications involved, an approach for addressing safety in the context of reconfiguration impacting functional and non-functional properties at runtime is needed. In this paper, we introduce a concept for runtime safety analysis and decision input for open adaptive systems. We combine static safety analysis and evidence collected during operation to analyse, reason and provide online recommendations to minimize deviation from a system’s safe states. We illustrate our concept via an abstract vehicle platooning system use case.
    • Bond strength between corroded steel and recycled aggregate concrete incorporating nano silica

      Alhawat, Musab; Ashour, Ashraf F. (2019)
      Limited information related to the application of nano silica in recycled aggregate concretes has been available in the literature. However, investigations on the effect of nano silica on the bond performance of reinforcement embedment length in recycled aggregate concrete have not been conducted yet. Therefore, the present study aimed at investigating the bond strength for recycled aggregate concretes incorporating nano silica under different levels of corrosive environments. The experimental work consisted of testing 180 pull-out specimens prepared from different mixtures. The main parameters studied were the amount of recycled aggregate (i.e. 0%, 25%, 50% and 100%), nano silica (1.5% and 3%), embedment length (5 and 13Ø) as well as reinforcement diameter (12 and 20mm). Different levels of corrosion were electrochemically induced by applying impressed voltage technique for 2, 5, 10 and 15 days. Finally, the experimental results were compared with the existing models. Experimental results showed that the bond performance between un-corroded steel and RCA concrete slightly reduced, while a significant degradation was observed after being exposed to corrosive conditions, in comparison to normal concrete. On the other hand, the use of a small quantity of NS (1.5%) showed between 8 and 21% bond enhancement with both normal and RCA concretes under normal conditions. However, much better influence was observed with the increase of corrosion periods, reflecting the improvement in corrosion resistance. NS particles showed a more effective role with RCA concretes rather than conventional concretes in terms of enhancing bond and corrosion resistance. Therefore, it was superbly effective in recovering the poor performance in bond for RCA concretes. By doubling the content of NS (3%), the bond resistance slightly enhanced for non-corroded samples, while its influence becomes more pronounced with increasing RCA content as well as exposure time to corrosion.
    • Dynamic mechanical properties of cementitious composites with carbon nanotubes

      Wang, J.; Dong, S.; Ashour, Ashraf F.; Wang, X.; Han, B. (Elsevier, 2019)
      This paper studied the effect of different types of multi-walled carbon nanotubes (MWCNTs) on the dynamic mechanical properties of cementitious composites. Impact compression test was conducted on various specimens to obtain the dynamic stress-strain curves and dynamic compressive strength as well as deformation of cementitious composites. The dynamic impact toughness and impact dissipation energy were, then, estimated. Furthermore, the microscopic morphology of cementitious composites was identified by using the scanning electron microscope to show the reinforcing mechanisms of MWCNTs on cementitious composites. Experimental results show that all types of MWCNTs can increase the dynamic compressive strength and ultimate strain of the composite, but the dynamic peak strain of the composite presents deviations with the MWCNT incorporation. The composite with thick-short MWCNTs has a 100.8% increase in the impact toughness, and the composite with thin-long MWCNTs presents an increased dissipation energy up to 93.8%. MWCNTs with special structure or coating treatment have higher reinforcing effect to strength of the composite against untreated MWCNTs. The modifying mechanisms of MWCNTs on cementitious composite are mainly attributed to their nucleation and bridging effects, which prevent the micro-crack generation and delay the macro-crack propagation through increasing the energy consumption.
    • Random projectors with continuous resolutions of the identity in a finite-dimensional Hilbert space

      Vourdas, Apostolos (2019-10)
      Random sets are used to get a continuous partition of the cardinality of the union of many overlapping sets. The formalism uses Möbius transforms and adapts Shapley's methodology in cooperative game theory, into the context of set theory. These ideas are subsequently generalized into the context of finite-dimensional Hilbert spaces. Using random projectors into the subspaces spanned by states from a total set, we construct an infinite number of continuous resolutions of the identity, that involve Hermitian positive semi-definite operators. The simplest one is the diagonal continuous resolution of the identity, and it is used to expand an arbitrary vector in terms of a continuum of components. It is also used to define the function on the 'probabilistic quadrant' , which is analogous to the Wigner function for the harmonic oscillator, on the phase-space plane. Systems with finite-dimensional Hilbert space (which are naturally described with discrete variables) are described here with continuous probabilistic variables.
    • A synthesis of logic and bio-inspired techniques in the design of dependable systems

      Papadopoulos, Y.; Walker, M.; Parker, D.; Sharvia, S.; Bottaci, L.; Kabir, Sohag; Azevedo, L.; Sorokos, I. (2016-01)
      Much of the development of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, from the early stages of, and throughout, the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems, presented in the scope of the HiP-HOPS tool and technique, that brings these technologies together to realise their combined potential benefits. The paper begins by identifying current challenges in model-based safety assessment and then overviews the use of meta-heuristics at various stages of the design lifecycle covering topics that span from allocation of dependability requirements, through dependability analysis, to multi-objective optimisation of system architectures and maintenance schedules.
    • Fuzzy evidence theory and Bayesian networks for process systems risk analysis

      Yazdi, M.; Kabir, Sohag (2018)
      Quantitative risk assessment (QRA) approaches systematically evaluate the likelihood, impacts, and risk of adverse events. QRA using fault tree analysis (FTA) is based on the assumptions that failure events have crisp probabilities and they are statistically independent. The crisp probabilities of the events are often absent, which leads to data uncertainty. However, the independence assumption leads to model uncertainty. Experts’ knowledge can be utilized to obtain unknown failure data; however, this process itself is subject to different issues such as imprecision, incompleteness, and lack of consensus. For this reason, to minimize the overall uncertainty in QRA, in addition to addressing the uncertainties in the knowledge, it is equally important to combine the opinions of multiple experts and update prior beliefs based on new evidence. In this article, a novel methodology is proposed for QRA by combining fuzzy set theory and evidence theory with Bayesian networks to describe the uncertainties, aggregate experts’ opinions, and update prior probabilities when new evidences become available. Additionally, sensitivity analysis is performed to identify the most critical events in the FTA. The effectiveness of the proposed approach has been demonstrated via application to a practical system.
    • An overview of the approaches for automotive safety integrity levels allocation

      Gheraibia, Y.; Kabir, Sohag; Djafri, K.; Krimou, H. (2018-06)
      ISO 26262, titled Road Vehicles–Functional Safety, is the new automotive functional safety standard for passenger vehicle industry. In order to accomplish the goal of designing and developing dependable automotive systems, ISO 26262 uses the concept of Automotive Safety Integrity Levels (ASILs), the adaptation of Safety Integrity Levels. ASILs are allocated to the components and subsystems that can cause system failure and malfunctions that lead to hazards. ASILs allocation is a hard problem consists of finding the optimal allocation of safety levels to the system architecture which must guarantee that the highest safety requirements are met while development cost of the automotive system is kept minimum. There were many successful attempts to solve this problem using different techniques. However, it is worth pointing out that there is an absence of a review that provides an in-depth study of all the existing methods and highlights their merits and demerits. This paper presents an overview of different approaches that were used to solve ASILs allocation problem. The review provides an overview of safety requirements including the related standards followed by a study of the resolution methods of the existing approaches. The study of each approach provides a detailed explanation of the used methodology and a discussion of its strength and weaknesses including the main open challenges.
    • Performance evaluation and design for variable threshold alarm systems through semi-Markov process

      Aslansefat, K.; Gogani, M.B.; Kabir, Sohag; Shoorehdeli, M.A.; Yari, M. (2019)
      In large industrial systems, alarm management is one of the most important issues to improve the safety and efficiency of systems in practice. Operators of such systems often have to deal with a numerous number of simultaneous alarms. Different kinds of thresholding or filtration are applied to decrease alarm nuisance and improve performance indices, such as Averaged Alarm Delay (ADD), Missed Alarm and False Alarm Rates (MAR and FAR). Among threshold-based approaches, variable thresholding methods are well-known for reducing the alarm nuisance and improving the performance of the alarm system. However, the literature suffers from the lack of an appropriate method to assess performance parameters of Variable Threshold Alarm Systems (VTASs). This study introduces two types of variable thresholding and proposes a novel approach for performance assessment of VTASs using Priority-AND gate and semi-Markov process. Application of semi-Markov process allows the proposed approach to consider industrial measurements with non-Gaussian distributions. In addition, the paper provides a genetic algorithm based optimized design process for optimal parameter setting to improve performance indices. The effectiveness of the proposed approach is illustrated via three numerical examples and through a comparison with previous studies.
    • Model-based dependability analysis: State-of-the-art, challenges, and future outlook

      Sharvia, S.; Kabir, Sohag; Walker, M.; Papadopoulos, Y. (2015-01)
    • A Conceptual Framework to Incorporate Complex Basic Events in HiP-HOPS

      Kabir, Sohag; Aslansefat, K.; Sorokos, I.; Papadopoulos, Y.; Gheraibia, Y. (Springer, 2019-10-16)
      Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) have made the reliability analysis process less expensive in terms of effort and time required. HiP-HOPS uses an analytical modelling approach for Fault tree analysis to automate the reliability analysis process, where each system component is associated with its failure rate or failure probability. However, such non-state-space analysis models are not capable of modelling more complex failure behaviour of component like failure/repair dependencies, e.g., spares, shared repair, imperfect coverage, etc. State-space based paradigms like Markov chain can model complex failure behaviour, but their use can lead to state-space explosion, thus undermining the overall analysis capacity. Therefore, to maintain the benefits of MBSA while not compromising on modelling capability, in this paper, we propose a conceptual framework to incorporate complex basic events in HiP-HOPS. The idea is demonstrated via an illustrative example.
    • Uncertainty handling in fault tree based risk assessment: State of the art and future perspectives

      Mohammad, Yazdi; Kabir, Sohag; Martin, Walker (2019-11)
      Risk assessment methods have been widely used in various industries, and they play a significant role in improving the safety performance of systems. However, the outcomes of risk assessment approaches are subject to uncertainty and ambiguity due to the complexity and variability of system behaviour, scarcity of quantitative data about different system parameters, and human involvement in the analysis, operation, and decision-making processes. The implications for improving system safety are slowly being recognised; however, research on uncertainty handling during both qualitative and quantitative risk assessment procedures is a growing field. This paper presents a review of the state of the art in this field, focusing on uncertainty handling in fault tree analysis (FTA) based risk assessment. Theoretical contributions, aleatory uncertainty, epistemic uncertainty, and integration of both epistemic and aleatory uncertainty handling in the scientific and technical literature are carefully reviewed. The emphasis is on highlighting how assessors can handle uncertainty based on the available evidence as an input to FTA.
    • Uncertainty handling in fault tree based risk assessment: State of the art and future perspectives

      Yazdi, M.; Kabir, Sohag; Walker, M. (2019-11)
      Risk assessment methods have been widely used in various industries, and they play a significant role in improving the safety performance of systems. However, the outcomes of risk assessment approaches are subject to uncertainty and ambiguity due to the complexity and variability of system behaviour, scarcity of quantitative data about different system parameters, and human involvement in the analysis, operation, and decision-making processes. The implications for improving system safety are slowly being recognised; however, research on uncertainty handling during both qualitative and quantitative risk assessment procedures is a growing field. This paper presents a review of the state of the art in this field, focusing on uncertainty handling in fault tree analysis (FTA) based risk assessment. Theoretical contributions, aleatory uncertainty, epistemic uncertainty, and integration of both epistemic and aleatory uncertainty handling in the scientific and technical literature are carefully reviewed. The emphasis is on highlighting how assessors can handle uncertainty based on the available evidence as an input to FTA.
    • A Runtime Safety Analysis Concept for Open Adaptive Systems

      Kabir, Sohag; Sorokos, I.; Aslansefat, K.; Papadopoulos, Y.; Gheraibia, Y.; Reich, J.; Saimler, M.; Wei, R. (Springer, 2019-10-16)
      In the automotive industry, modern cyber-physical systems feature cooperation and autonomy. Such systems share information to enable collaborative functions, allowing dynamic component integration and architecture reconfiguration. Given the safety-critical nature of the applications involved, an approach for addressing safety in the context of reconfiguration impacting functional and non-functional properties at runtime is needed. In this paper, we introduce a concept for runtime safety analysis and decision input for open adaptive systems. We combine static safety analysis and evidence collected during operation to analyse, reason and provide online recommendations to minimize deviation from a system’s safe states. We illustrate our concept via an abstract vehicle platooning system use case.
    • Fuzzy temporal fault tree analysis of dynamic systems

      Kabir, Sohag; Walker, M.; Papadopoulos, Y.; Rüde, E.; Securius, P. (2016-10)
      Fault tree analysis (FTA) is a powerful technique that is widely used for evaluating system safety and reliability. It can be used to assess the effects of combinations of failures on system behaviour but is unable to capture sequence dependent dynamic behaviour. A number of extensions to fault trees have been proposed to overcome this limitation. Pandora, one such extension, introduces temporal gates and temporal laws to allow dynamic analysis of temporal fault trees (TFTs). It can be easily integrated in model-based design and analysis techniques. The quantitative evaluation of failure probability in Pandora TFTs is performed using exact probabilistic data about component failures. However, exact data can often be difficult to obtain. In this paper, we propose a method that combines expert elicitation and fuzzy set theory with Pandora TFTs to enable dynamic analysis of complex systems with limited or absent exact quantitative data. This gives Pandora the ability to perform quantitative analysis under uncertainty, which increases further its potential utility in the emerging field of model-based design and dependability analysis. The method has been demonstrated by applying it to a fault tolerant fuel distribution system of a ship, and the results are compared with the results obtained by other existing techniques.