Development of air-breathing polymer electrolyte membrane (PEM) fuel cell for small UAV application

Tezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir.Polymer exchange membrane fuel cells (PEMFC) are the devices that directly convert Chemical energy into Electrical energy and are potential candidates for portable and stationary power supply applications due to their several advantages over combustion engines. This study has been carried out to develop Air breathing and air cooling PEM Fuel cell stack for small Unmanned Aerial Vehicle (UAV) application with a power re- quirement of 200 W. Keeping in view the available space and weight constraints of UAV, I have optimally designed the shape of active area (10 cm x 2 cm) and ow channels. Fluid ow analysis using ANSYS Fluent software was performed on dierent channel shapes and an optimal design (double serpentine), with least pressure drop and optimal velocity proles, was selected. Electro-chemical simulations were also done to predict the fuel cell performance (IV and Power curves) using MATLAB software prior manufacturing the prototype. Moreover, for the sake of DOE targets, initial tests were performed on single cell. Bipolar plates were more focused in terms of alternate material, novel design and fabrication process. An alternate fabrication technique was studied to manufacture Ex- panded Graphite (EG) polymer composite bipolar plates. Cutting molds were designed to cut channels on thin (0.6 mm) commercially acquired EG sheets. Three separate sheets, with ow channel textures removed, were glued to each other by a commercial conductive epoxy to build a single bipolar plate. The nal product was characterized in terms of electro-mechanical properties as well as density, weight and cost. Fabrica- tion process devised can be good alternate for small scale as well as mass production. Moreover, a PEM fuel cell stack is provided with an appropriate clamping torque to prevent leakage of reactant gases and to minimize the contact resistance between gas diusion media (GDL) and bipolar plates. GDL porous structure and gas permeability is directly aected by the compaction pressure which consequently drastically change the fuel cell performance. Single cell performance tests were performed at ve dier- ent clamping torque values for achieving optimal cell performance. Experimental and theoretical results were compared for making inferences about optimal cell performance. Keywords: PEM Fuel Cell, Simulations, Bipolar Plate, Graphite polymer composite, manufacturing technique, Clamping torque, Optimal cell performanceDeclaration of Authorship ii Abstract iv Öz v Acknowledgments vii List of Figures xi Abbreviations xiii Physical Constants xiv Symbols xv 1 Introduction to Fuel Cells 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 PEM Fuel Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2.1 PEM Fuel Cell Components . . . . . . . . . . . . . . . . . . . . . . 4 1.2.2 Technical Targets for PEM Fuel cells . . . . . . . . . . . . . . . . . 6 1.2.3 Applications of PEM fuel cell technology . . . . . . . . . . . . . . . 6 1.3 Research Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 Organization of dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 PEM Fuel Cell Design and Prototype Fabrication 9 2.1 Fuel Cell Stack Design / size calculations . . . . . . . . . . . . . . . . . . 9 2.2 Mechanical Model of PEM Fuel cell components . . . . . . . . . . . . . . . 11 2.2.1 Bipolar Plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2.1.1 Main Functions of Bipolar Plate . . . . . . . . . . . . . . 11 2.2.1.2 Essential Requirements . . . . . . . . . . . . . . . . . . . 12 2.2.1.3 Gas Flow Channel cross-section and layout design . . . . 12 2.2.2 Membrane Electrode Assembly . . . . . . . . . . . . . . . . . . . . 13 2.2.3 Gas Diusion Layer . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2.4 Seal / Gasket . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.5 End Plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.2.6 Single Cell Assembly . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.3 Prototype Fabrication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.1 Bipolar Plates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.2 Membrane Electrode Assembly (MEA) . . . . . . . . . . . . . . . . 20 2.3.3 Single cell assembly . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3 Development of PEM Fuel Cell using simulated results of bipolar ow eld design and electrochemical models 23 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Performance Prediction . . . . . . 31 3.3 Experimental . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.3.1 Materials, Method and Assembly . . . . . . . . . . . . . . . . . . . 36 3.3.2 Fuel Cell Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.4 Crux of the study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4 An alternate low cost fabrication technique for PEM Fuel cell bipolar plates using graphite polymer composite material 39 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.2 Experimental . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2.2 Bipolar plate and reactants ow led design . . . . . . . . . . . . . 41 4.2.3 Design of cutting Molds . . . . . . . . . . . . . . . . . . . . . . . . 42 4.2.4 Preparation of Bipolar Plates . . . . . . . . . . . . . . . . . . . . . 44 4.2.5 Characterization of the bipolar plate . . . . . . . . . . . . . . . . . 45 4.2.6 Mechanical Strength Measurements . . . . . . . . . . . . . . . . . . 45 4.2.7 Contact Resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.2.8 Electrical Conductivity Measurements . . . . . . . . . . . . . . . . 46 4.2.9 Weight Measurements . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 4.3.1 Physical and Mechanical Properties . . . . . . . . . . . . . . . . . . 47 4.3.2 Electrical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.3.3 Cost and Weight Analysis . . . . . . . . . . . . . . . . . . . . . . . 48 4.3.4 Fuel Cell performance . . . . . . . . . . . . . . . . . . . . . . . . . 49 4.4 Main Crux / Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 5 Experimental determination of optimal clamping torque for AB-PEM Fuel cell 51 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 5.1.1 Clamping Torque calculation Theory . . . . . . . . . . . . . . . . . 53 5.1.2 Contact Resistance and clamping Pressure . . . . . . . . . . . . . . 54 5.2 Experimental . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.2.1 Materials, Method and Assembly . . . . . . . . . . . . . . . . . . . 55 5.2.2 Contact Resistance Measurement . . . . . . . . . . . . . . . . . . . 56 5.2.3 Pressure Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.1 Pressure distribution results . . . . . . . . . . . . . . . . . . . . . . 57 5.3.2 Single Cell Performance . . . . . . . . . . . . . . . . . . . . . . . . 57 5.4 Summary of the study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 6 Conclusion and Future Work 60 6.1 Summary and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography. . . . . . . . . 6

Anomaly detection for resilience in cloud computing infrastructures

Cloud computing is a relatively recent model where scalable and elastic resources are provided as optimized, cost-effective and on-demand utility-like services to customers. As one of the major trends in the IT industry in recent years, cloud computing has gained momentum and started to revolutionise the way enterprises create and deliver IT solutions. Motivated primarily due to cost reduction, these cloud environments are also being used by Information and Communication Technologies (ICT) operating Critical Infrastructures (CI). However, due to the complex nature of underlying infrastructures, these environments are subject to a large number of challenges, including mis-configurations, cyber attacks and malware instances, which manifest themselves as anomalies. These challenges clearly reduce the overall reliability and availability of the cloud, i.e., it is less resilient to challenges. Resilience is intended to be a fundamental property of cloud service provisioning platforms. However, a number of significant challenges in the past demonstrated that cloud environments are not as resilient as one would hope. There is also limited understanding about how to provide resilience in the cloud that can address such challenges. This implies that it is of utmost importance to clearly understand and define what constitutes the correct, normal behaviour so that deviation from it can be detected as anomalies and consequently higher resilience can be achieved. Also, for characterising and identifying challenges, anomaly detection techniques can be used and this is due to the fact that the statistical models embodied in these techniques allow the robust characterisation of normal behaviour, taking into account various monitoring metrics to detect known and unknown patterns. These anomaly detection techniques can also be applied within a resilience framework in order to promptly provide indications and warnings about adverse events or conditions that may occur. However, due to the scale and complexity of cloud, detection based on continuous real time infrastructure monitoring becomes challenging. Because monitoring leads to an overwhelming volume of data, this adversely affects the ability of the underlying detection mechanisms to analyse the data. The increasing volume of metrics, compounded with complexity of infrastructure, may also cause low detection accuracy. In this thesis, a comprehensive evaluation of anomaly detection techniques in cloud infrastructures is presented under typical elastic behaviour. More specifically, an investigation of the impact of live virtual machine migration on state of the art anomaly detection techniques is carried out, by evaluating live migration under various attack types and intensities. An initial comparison concludes that, whilst many detection techniques have been proposed, none of them is suited to work within a cloud operational context. The results suggest that in some configurations anomalies are missed and some configuration anomalies are wrongly classified. Moreover, some of these approaches have been shown to be sensitive to parameters of the datasets such as the level of traffic aggregation, and they suffer from other robustness problems. In general, anomaly detection techniques are founded on specific assumptions about the data, for example the statistical distributions of events. If these assumptions do not hold, an outcome can be high false positive rates. Based on this initial study, the objective of this work is to establish a light-weight real time anomaly detection technique which is more suited to a cloud operational context by keeping low false positive rates without the need for prior knowledge and thus enabling the administrator to respond to threats effectively. Furthermore, a technique is needed which is robust to the properties of cloud infrastructures, such as elasticity and limited knowledge of the services, and such that it can support other resilience supporting mechanisms. From this formulation, a cloud resilience management framework is proposed which incorporates the anomaly detection and other supporting mechanisms that collectively address challenges that manifest themselves as anomalies. The framework is a holistic endto-end framework for resilience that considers both networking and system issues, and spans the various stages of an existing resilience strategy, called (D2R 2+DR). In regards to the operational applicability of detection mechanisms, a novel Anomaly Detection-as-a-Service (ADaaS) architecture has been modelled as the means to implement the detection technique. A series of experiments was conducted to assess the effectiveness of the proposed technique for ADaaS. These aimed to improve the viability of implementing the system in an operational context. Finally, the proposed model is deployed in a European Critical Infrastructure provider’s network running various critical services, and validated the results in real time scenarios with the use of various test cases, and finally demonstrating the advantages of such a model in an operational context. The obtained results show that anomalies are detectable with high accuracy with no prior-knowledge, and it can be concluded that ADaaS is applicable to cloud scenarios for a flexible multi-tenant detection systems, clearly establishing its effectiveness for cloud infrastructure resilience

Towards policy refinement for resilience management in cloud

Cloud computing is becoming increasingly important for provision of critical services because of potential cost saving, scalability and elasticity. Therefore, it is particularly important for clouds and cloud-based services to be resilient, i.e., they are able to operate correctly and continuously even in the presence of challenges. To do this, a number of resilience supporting mechanisms are needed at various levels in cloud infrastructure. It is non-trivial to manage these mechanisms and there is a need for flexible instruments which assist cloud providers in this complex task. Policy based management is an established instrument to manage resilience supporting mechanisms and they are useful if it allows not only high level description of abstract policy (e.g high level security and resilience requirements), but also enables such policy to be refined and eventually mapped into an appropriate low levels in cloud settings. This paper sheds light on basic concepts behind policy based management in cloud, more specifically it emphasises the use of policy refinement which is the process of translating higher level requirements (such as security and resilience requirements) into the sequence of actions at lower levels that can implement them, in order to generate more refined policies that govern the behaviour of an overall cloud system when under challenge. We finally present two example scenarios on how policy refinement can work for the cloud to establish its relevance for the overall resilience management

Experimental determination of optimal clamping torque for AB-PEM fuel cell

Polymer electrolyte Membrane (PEM) fuel cell is an electrochemical device producing electricity by the reaction of hydrogen and oxygen without combustion. PEM fuel cell stack is provided with an appropriate clamping torque to prevent leakage of reactant gases and to minimize the contact resistance between gas diffusion media (GDL) and bipolar plates. GDL porous structure and gas permeability is directly affected by the compaction pressure which, consequently, drastically change the fuel cell performance. Various efforts were made to determine the optimal compaction pressure and pressure distributions through simulations and experimentation. Lower compaction pressure results in increase of contact resistance and also chances of leakage. On the other hand, higher compaction pressure decreases the contact resistance but also narrows down the diffusion path for mass transfer from gas channels to the catalyst layers, consequently, lowering cell performance. The optimal cell performance is related to the gasket thickness and compression pressure on GDL. Every stack has a unique assembly pressure due to differences in fuel cell components material and stack design. Therefore, there is still need to determine the optimal torque value for getting the optimal cell performance. This study has been carried out in continuation of development of Air breathing PEM fuel cell for small Unmanned Aerial Vehicle (UAV) application. Compaction pressure at minimum contact resistance was determined and clamping torque value was calculated accordingly. Single cell performance tests were performed at five different clamping torque values i.e 0.5, 1.0, 1.5, 2.0 and 2.5 N m, for achieving optimal cell performance. Clamping pressure distribution tests were also performed at these torque values to verify uniform pressure distribution at optimal torque value. Experimental and theoretical results were compared for making inferences about optimal cell performance. A clamping torque value of 1.5 N m was determined experimentally to be the best for getting optimal performance as well as uniform pressure distribution for this specific fuel cell

Nexus of Block Chain Alignment, Supply Chain Agility, Supply Chain Performance and their Impact on Firm’s Environmental Performance: A Developing Country Perspective

Blockchain technology has significant potential for improving the environmental performance of businesses and supply chains. One of the key benefits of blockchain is its ability to provide greater transparency and traceability in supply chains. This can enable companies to better monitor and manage their environmental impacts, such as carbon emissions and waste production, throughout their supply chain. Therefore, the purpose of this study was to investigate the use of blockchain technology in improving supply chain alignment (SCA), supply chain agility (SCAG), and supply chain performance (SCP), and their influence on the environmental performance (EP) of firms. Additionally, the study aimed to identify the moderating effect of innovative climate (IC) on the relationship between SCA, SCAG, SCP, and EP. The researchers employed a quantitative research paradigm and collected data through a survey questionnaire. The sample was collected using the probability cluster sampling method and consisted of 350 personnel in executive and middle management positions. The results indicated that SCA, SCAG, and SCP positively impact the EP of businesses, and this relationship is moderated by IC. The study's findings have several theoretical and practical implications, including the potential for blockchain technology to improve supply chain sustainability and the importance of fostering an innovative climate to enhance the positive effects of SCA, SCAG, and SCP on EP

Anomaly detection in the cloud using data density

Cloud computing is now extremely popular because of its use of elastic resources to provide optimized, cost-effective and on-demand services. However, clouds may be subject to challenges arising from cyber attacks including DoS and malware, as well as from sheer complexity problems that manifest themselves as anomalies. Anomaly detection techniques are used increasingly to improve the resilience of cloud environments and indirectly reduce the cost of recovery from outages. Most anomaly detection techniques are computation ally expensive in a cloud context, and often require problem-specific parameters to be predefined in advance, impairing their use in real-time detection. Aiming to overcome these problems, we propose a technique for anomaly detection based on data density. The density is computed recursively, so the technique is memory-less and unsupervised, and therefore suitable for real-time cloud environments. We demonstrate the efficacy of the proposed technique using an emulated dataset from a testbed, under various attack types and intensities, and in the face of VM migration. The obtained results, which include precision, recall, accuracy, F-score and G-score, show that network level attacks are detectable with high accuracy

Mining scientific trends based on topics in conference call for papers

Ever since analyzing scientific topics and evolution of technology have become vital for researchers, academics, funding institutes and research administration departments, there is a crucial need to mine scientific trends to fill this appetite more rigorously. In this paper, we procured a novel Call for Papers (CFPs) dataset in order to analyze scientific evolution and prestige of conferences that set scientific trends using scientific publications indexed in DBLP. Using ACM CSS, 1.3 million publications that appear in 146 data mining conferences are mapped into different thematic areas by matching the terms that appear in publication titles with ACM CSS. In recent years, an attempt termed as Topic Detection and Tracking (TDT) [1] is made to find the solution for the problem of "well-awareness" on this dynamic data. As conference ranking has been made by different forums on the basis of mixed indicators1. ERA2 ranks Australia's higher education research institutions. The major contributions of this paper are as follows: (i) compilation of CFPs dataset, (ii) identification of topics and keywords from CFP corpus, and (iii) measure the impact of these extracted hot topics from CFPs

Demographic Characteristics of COVID-19 Patients in District Gujrat

Objective: To determine the prevalence of Covid-19 in the district of Gujrat, its association with gender, age, its correlation with respiratory and cardiac symptoms and to find the link of this disease with travel history of patients to affected areas. Methodology: A total of 222 COVID-19 -Positive patients (Male and Female) out of 514 clinically suspected cases (fever, cough, dyspnoea, lethargy & anosmia) as per WHO guidelines were selected. The use of the data for research purposes was explained to patients, and informed consent was taken. The study was approved by the ethical committee of Aziz Bhatti Shaheed Hospital. Samples were extracted from nasopharyngeal swabs using standard extraction protocol. Statistical tools used was SPSS Version 24. Chi-square test and correlation of age with respiratory and cardiac symptoms was calculated. Results: Male gender was significantly affected by this disease (P=0.001) as compared to the female gender. Regarding the prevalence of respiratory symptoms, 31(14%) were asymptomatic. 37(16.7%) had Dyspnea, 45 (65.3%) cough (P= 0.001). Nine (4.1%) developed pneumonia. Fever and Cough was the most common symptom in the age group 21-40 yrs(P=0.001). While pneumonia developed in the older age group. The cardiac symptoms appeared in young age group (p=0.000) in the age group 21-40 yrs (70.9% n=78).38 patients (17.2%) had the symptom of chest pain, 24(10.9%) tachycardia and 1(0.5%) developed arrhythmia. Out of 222 COVID positive patients, 67.1% (149) gave a history of direct contact with positive patients, 19.8% (n=44) gave travel history,4.5% (n=10) had a history of going to Raiwind Ijtamah and 8.6% (n=19) were zaireen/pilgrims from Taftan. Conclusion: The COVID -19 is comparatively more common in male patients. 50% of the patients were of age group 21-40 years showing the symptoms of fever and cough along with mild cardiac symptoms. Acute pneumonia developed in older age groups while cardiac symptoms were significant in young age. In Gujrat District, the majority of the patients (67.1%) developed Covid-19 due to travelling

Evaluation of Anomaly Detection Techniques for SCADA Communication Resilience

Attacks on critical infrastructures’ Supervisory Control and Data Acquisition (SCADA) systems are beginning to increase. They are often initiated by highly skilled attackers, who are capable of deploying sophisticated attacks to exfiltrate data or even to cause physical damage. In this paper, we rehearse the rationale for protecting against cyber attacks and evaluate a set of Anomaly Detection (AD) techniques in detecting attacks by analysing traffic captured in a SCADA network. For this purpose, we have implemented a tool chain with a reference implementation of various state-of-the-art AD techniques to detect attacks, which manifest themselves as anomalies. Specifically, in order to evaluate the AD techniques, we apply our tool chain on a dataset created from a gas pipeline SCADA system in Mississippi State University’s lab, which include artefacts of both normal operations and cyber attack scenarios. Our evaluation elaborate on several performance metrics of the examined AD techniques such as precision; recall; accuracy; F-score and G-score. The results indicate that detection rate may change significantly when considering various attack types and different detections modes (i.e., supervised and unsupervised), and also provide indications that there is a need for a robust, and preferably real-time AD technique to introduce resilience in critical infrastructures