Search results for: solar photovoltaic systems

Authors: Shahzad Yousaf, Imran Shafi

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This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

Procedia PDF Downloads 386

Authors: Chetna Tyagi, Ambuj Tripathi, Devesh Avasthi

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Graphene oxide consists of sp³ hybridization along with sp² hybridization due to the presence of different oxygen-containing functional groups on its edges and basal planes. However, its sp³ / sp² hybridization can be tuned by various methods to utilize it in different applications, like transistors, solar cells and biosensors. Ion beam irradiation can also be one of the methods to optimize sp² and sp³ hybridization ratio for its desirable properties. In this work, graphene oxide films were irradiated with 100 keV Argon ions at different fluences varying from 10¹³ to 10¹⁶ ions/cm². Synchrotron X-ray diffraction measurements showed an increase in crystallinity at the low fluence of 10¹³ ions/cm². Raman spectroscopy performed on irradiated samples determined the defects induced by the ion beam qualitatively. Also, identification of different groups and their removal with different fluences was done using Fourier infrared spectroscopy technique.

Keywords: graphene oxide, ion beam irradiation, spectroscopy, X-ray diffraction

Procedia PDF Downloads 131

Authors: Sijuade A. A., Oguntoye J. P., Awodoye O. O., Adedapo O. A., Wahab W. B., Okediran O. O., Omidiora E. O., Olabiyisi S. O.

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Electronic voting systems have been introduced to improve the efficiency, accuracy, and transparency of the election process in many countries around the world, including Nigeria. However, concerns have been raised about the security and integrity of these systems. One way to address these concerns is through the implementation of electronic forensic election audit systems. This study aims to evaluate voters' intention to the adoption of electronic forensic election audit systems using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. In the study, the UTAUT model which is a widely used model in the field of information systems to explain the factors that influence individuals' intention to use a technology by integrating performance expectancy, effort expectancy, social influence, facilitating conditions, cost factor and privacy factor to voters’ behavioural intention was proposed. A total of 294 sample data were collected from a selected population of electorates who had at one time or the other participated in at least an electioneering process in Nigeria. The data was then analyzed statistically using Partial Least Square Structural Equation Modeling (PLS-SEM). The results obtained show that all variables have a significant effect on the electorates’ behavioral intention to adopt the development and implementation of an electronic forensic election audit system in Nigeria.

Keywords: election Audi, voters, UTAUT, performance expectancy, effort expectancy, social influence, facilitating condition social influence, facilitating conditions, cost factor, privacy factor, behavioural intention

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: H. Falsafi Falsafizadeh, R. Zeinali Zeinali

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This paper focuses on determination of total Operating Reserve (OR) level, consisting of spinning and non-spinning reserves, in two small real power systems, in such a way that the system reliability indicator would comply with typical industry standards. For this purpose, the standard used by the North American Electric Reliability Corporation (NERC) – i.e., 1 day outage in 10 years or 0.1 days/year is relied. The simulation of system operation for these systems that was used for the determination of total operating reserve level was performed by industry standard production simulation software in this field, named PLEXOS. In this paper, the operating reserve which meets an annual Loss of Load Expectation (LOLE) of approximately 0.1 days per year is determined in the study year. This reserve is the minimum amount of reserve required in a power system and generally defined as a percentage of the annual peak.

Keywords: frequency control, LOLE, operating reserve, system reliability

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Authors: L. Freeborn

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This paper discusses the application of complex dynamic system theory (DST) to the study of individual differences in second language development. This transdisciplinary framework allows researchers to view the trajectory of language development as a dynamic, non-linear process. A DST approach views language as multi-componential, consisting of multiple complex systems and nested layers. These multiple components and systems continuously interact and influence each other at both the macro- and micro-level. Dynamic systems theory aims to explain and describe the development of the language system, rather than make predictions about its trajectory. Such a holistic and ecological approach to second language development allows researchers to include various research methods from neurological, cognitive, and social perspectives. A DST perspective would involve in-depth analyses as well as mixed methods research. To illustrate, a neurobiological approach to second language development could include non-invasive neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate areas of brain activation during language-related tasks. A cognitive framework would further include behavioural research methods to assess the influence of intelligence and personality traits, as well as individual differences in foreign language aptitude, such as phonetic coding ability and working memory capacity. Exploring second language development from a DST approach would also benefit from including perspectives from the field of applied linguistics, regarding the teaching context, second language input, and the role of affective factors such as motivation. In this way, applying mixed research methods from neurobiological, cognitive, and social approaches would enable researchers to have a more holistic view of the dynamic and complex processes of second language development.

Keywords: dynamic systems theory, mixed methods, research design, second language development

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Authors: Sandhya Armoogum

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In distributed systems and in open systems such as the Internet, often mobile code has to run on unknown and potentially hostile hosts. Mobile code such as a mobile agent is vulnerable when executing on remote hosts. The mobile agent may be subjected to various attacks such as tampering, inspection, and replay attack by a malicious host. Much research has been done to provide solutions for various security problems, such as authentication of mobile agent and hosts, integrity and confidentiality of the data carried by the mobile agent. Many of such proposed solutions in literature are not suitable for open systems whereby the mobile code arrives and executes on a host which is not known and trusted by the mobile agent owner. In this paper, we propose the adoption of the reference monitor by hosts in an open system for providing trust and security for mobile code execution. A secure protocol for the distribution of the reference monitor entity is described. This reference monitor entity on the remote host may also provide several security services such as authentication and integrity to the mobile code.

Keywords: security, mobile agents, reference monitor, trust

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Authors: Makenzy Lee Gilbert

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This literature review explores the role of attractor neural networks (ANNs) in modeling psychological processes in artificial and biological systems. By synthesizing research from dynamical systems theory, psychology, and computational neuroscience, the review provides an overview of the current understanding of ANN function in memory formation, reinforcement, retrieval, and forgetting. Key mathematical foundations, including dynamical systems theory and energy functions, are discussed to explain the behavior and stability of these networks. The review also examines empirical applications of ANNs in cognitive processes such as semantic memory and episodic recall, as well as highlighting the hippocampus's role in pattern separation and completion. The review addresses challenges like catastrophic forgetting and noise effects on memory retrieval. By identifying gaps between theoretical models and empirical findings, it highlights the interdisciplinary nature of ANN research and suggests future exploration areas.

Keywords: attractor neural networks, connectionism, computational modeling, cognitive neuroscience

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Authors: Resul Fikir

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Unmanned Aircraft Systems (UAS) become indispensable parts of modern airpower as force multiplier .One of the main advantages of UAS is long endurance. UAS have to take extra payloads to accomplish different missions but these payloads decrease endurance of aircraft because of increasing drug. There are continuing researches to increase the capability of UAS. There are some vertical thermal air currents, which can cause climb and increase endurance, in nature. Birds and gliders use thermals to gain altitude with no effort. UAS have wide wing which can use of thermals like birds and gliders. Thermal regions, which is area of 2-3 NM, exist all around the world. It is free and clean source. This study analyses if thermal regions can be adopted and implemented as an assistant tool for UAS route planning. First and second part of study will contain information about the thermal regions and current applications about UAS in aviation and climbing performance with a real example. Continuing parts will analyze the contribution of thermal regions to UAS endurance. Contribution is important because planning declaration of UAS navigation rules will be in 2015.

Keywords: unmanned aircraft systems, Air4All, thermals, gliders

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Authors: T. Gayen

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Although, there are several software reliability models existing today there does not exist any versatile model even today which can be used for the reliability assessment of software. Complex software has a large number of states (unlike the hardware) so it becomes practically difficult to completely test the software. Irrespective of the amount of testing one does, sometimes it becomes extremely difficult to assure that the final software product is fault free. The Black Box Software Reliability models are found be quite uncertain for the reliability assessment of various systems. As mission critical applications need to be highly reliable and since it is not always possible to ensure the development of highly reliable system. Hence, in order to achieve fault-free operation of software one develops some mechanism to handle faults remaining in the system even after the development. Although, several such techniques are currently in use to achieve fault tolerance, yet these mechanisms may not always be very suitable for various systems. Hence, this discussion is focused on analyzing the issues and challenges faced with the existing techniques for reliability assessment and fault tolerance of various software systems.

Keywords: black box, fault tolerance, failure, software reliability

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Authors: Nicolas Haber

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The study addresses the conceptual design of Product-Service Systems (PSSs) as a means of innovating solutions with the aim of reducing the environmental load of conventional product based solutions. Functional approaches targeting PSS solutions are developed in instinctive methods within the constraints of the setting in which they are conceived. Adopting morphological matrices in designing PSS concepts allows a thorough understanding of the settings, stakeholders, and functional requirements. Additionally, such a methodology is robust and adaptable to product-oriented, use-oriented and result-oriented systems. The research is based on a functional decomposition of the task in a similar way as in product design; while extended to include service components, providers, and receivers, while assessing the adaptability and homogeneity of the selected components and actors. A use-oriented concept is presented via a practical case study at an agricultural boom-sprayer manufacturer to demonstrate the effectiveness of the morphological approach to justify its viability. Additionally, a life cycle analysis is carried out in order to evaluate the environmental advantages inherited in a PSS solution versus a conventional solution. In light of the applications presented, the morphological approach appears to be a valid and generic tactic to conceiving integrated solutions whilst capturing the interrelations between the actors and elements of an integrated product-service system.

Keywords: conceptual design, design for sustainability, functional decomposition, product-service systems

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Authors: Majid Alsubaie, Hamed Sarbazhosseini

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Many working environments have experienced increased uncertainty due to the fast-moving and unpredictable world. IT systems development projects, in particular, face several challenges because of their rapidly changing environments and emerging technologies. Information technology organizations within these contexts adapt systems development methodology and new software approaches to address this issue. One of these methodologies is the Agile method, which has gained huge attention in recent years. However, due to failure rates in IT projects, there is an increasing demand for the use of hybrid Agile methods among organizations. The scarce research in the area means that organizations do not have solid evidence-based knowledge for the use of hybrid Agile. This research was designed to provide further insights into the development of hybrid Agile methods within systems development projects, including how frameworks and processes are used and what benefits and challenges are gained and faced as a result of hybrid Agile methods. This paper presents how three organizations (two government and one private) use hybrid Agile methods in their Agile environments. The data was collected through interviews and a review of relevant documents. The results indicate that these organizations do not predominantly use pure Agile. Instead, they are waterfall organizations by virtue of systems nature and complexity, and Agile is used underneath as the delivery model. Prince2 Agile framework, SAFe, Scrum, and Kanban were the identified models and frameworks followed. This study also found that customer satisfaction and the ability to build quickly are the most frequently perceived benefits of using hybrid Agile methods. In addition, team resistance and scope changes are the common challenges identified by research participants in their working environments. The findings can help to understand Agile environmental conditions and projects that can help get better success rates and customer satisfaction.

Keywords: agile, hybrid, IT systems, management, success rate, technology

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Zahra Kouzehgari

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Since the early emergence of chaos theory in the 1970s in mathematics and physical science, it has increasingly been developed and adapted in social sciences as well. The non-linear and dynamic characteristics of the theory make it a useful conceptual framework to interpret the complex social systems behavior. Regarding chaotic approach principals, sensitivity to initial conditions, dynamic adoption, strange attractors and unpredictability this paper aims to examine whether chaos approach could interpret the ancient social changes. To do this, at first, a brief history of the chaos theory, its development and application in social science as well as the principals making the theory, then its application in archaeological since has been reviewed. The study demonstrates that although based on existing archaeological records reconstruct the whole social system of the human past, the non-linear approaches in studying social complex systems would be of a great help in finding general order of the ancient societies and would enable us to shed light on some of the social phenomena in the human history or to make sense of them.

Keywords: archaeology, non-linear approach, chaos theory, ancient social systems

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Authors: Gulmira Umarova

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The data on the assessment of the influence of environmental risk to the health of the population of Uralsk in the West region of Kazakhstan were presented. Calculation of non-carcinogenic risks was performed for such air pollutants as sulfur dioxide, nitrogen oxides, hydrogen sulfide, carbon monoxide. Here with the critical organs and systems, which are affected by the above-mentioned substances were taken into account. As well as indicators of primary and general morbidity by classes of diseases among the population were considered. The quantitative risk of the influence of substances on organs and systems is established by results of the calculation.

Keywords: environment, health, morbidity, non-carcinogenic risk

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Authors: Ryan Messina, Mehedi Hasan

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This research is to examine the impacts of using data to generate performance requirements for automation in visual inspections using machine vision. These situations are intended for design and how projects can smooth the transfer of tacit knowledge to using an algorithm. We have proposed a framework when specifying machine vision systems. This framework utilizes varying levels of automation as contingency planning to reduce data processing complexity. Using data assists in extracting tacit knowledge from those who can perform the manual tasks to assist design the system; this means that real data from the system is always referenced and minimizes errors between participating parties. We propose using three indicators to know if the project has a high risk of failing to meet requirements related to accuracy and reliability. All systems tested achieved a better integration into operations after applying the framework.

Keywords: automation, contingency planning, continuous engineering, control theory, machine vision, system requirements, system thinking

Procedia PDF Downloads 201

Authors: Eman Hegazy, Stefan Anderberg, Joakim Krook

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Urban water infrastructure systems are central to functioning cities. For securing a continuous and efficient supply of the systems services, continuous investment, maintenance, and renewal are needed. Neglecting maintenance and renewal can lead to recurrent breakdown problems as systems age, which makes it more and more difficult to secure efficient long-term supply. Globally, many cities struggle with aging water infrastructure, often due to competing funding priorities. Investment in maintenance and renewal is not prioritized. The problem primarily stems from the challenge of reaping the benefits of investments promptly. The long-term benefits gained from investing in the renewal of water infrastructure may be achievable in the long run, resulting in the oversight of such investments. This leads to a build-up of "renewal debt" for future generations to inherit. Addressing this issue is difficult due to various contributing factors and the complex nature of the systems. The study aims to contribute to an increased understanding of the long-term management challenges of urban water infrastructure, the development of improved maintenance and renewal strategies through the examination of water infrastructure management, and the assessment of the adequacy of the maintenance and renewal in a case study, the city of Linköping, Sweden. Employing a multi-methods approach, this study utilized both qualitative and quantitative methods, including interviews, workshops, and data analysis. The findings of the study provided insights into the current status of the water and sewerage networks in Linkoping, highlighting the risks to ensuring reliable and sustainable water supply and discussing strategies for improving maintenance and renewal.

Keywords: case study, infrastructure management, renewal needs, Sweden, urban water infrastructure

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

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Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows to form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Jianguo Huang, Hong Cai, Bin Dong, Jifang Tao, Aiqun Liu, Dim-Lee Kwong, Yuandong Gu

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We developed a miniaturized tunable optomechanical oscillator based on the nanoelectromechanical systems (NEMS) technology, and its frequencies can be electrostatically tuned by as much as 10%. By taking both advantages of optical and electrical spring, the oscillator achieves a high tuning sensitivity without resorting to mechanical tension. In particular, the proposed high-Q optical cavity design greatly enhances the system sensitivity, making it extremely sensitive to the small motional signal.

Keywords: nanoelectromechanical systems (NEMS), nanotechnology, optical force, oscillator

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Authors: Sadia H. Syeda, Zain H. Malik

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As systems continue to become more complex and the interdependencies of processes and sub-systems continue to grow and transform, the need for a comprehensive method of tracking and linking the lifecycle of the systems in a digital form becomes ever more critical. Digital Engineering (DE) provides an approach to managing an authoritative data source that links, tracks, and updates system data as it evolves and grows throughout the system development lifecycle. DE enables the developing, tracking, and sharing system data, models, and other related artifacts in a digital environment accessible to all necessary stakeholders. The DE environment provides an integrated electronic repository that enables traceability between design, engineering, and sustainment artifacts. The DE activities' primary objective is to develop a set of integrated, coherent, and consistent system models for the program. It is envisioned to provide a collaborative information-sharing environment for various stakeholders, including operational users, acquisition personnel, engineering personnel, and logistics and sustainment personnel. Examining the processes that DE can support in the systems engineering life cycle (SELC) is a primary step in the DE adoption and implementation journey. Through an analysis of the U.S Department of Defense’s (DoD) Office of the Secretary of Defense (OSD’s) Digital Engineering Strategy and their implementation, examples of DE implementation by the industry and technical organizations, this paper will provide descriptions of the current DE processes and best practices of implementing DE across an enterprise. This will help identify the capabilities, environment, and infrastructure needed to develop a potential roadmap for implementing DE practices consistent with its business strategy. A capability maturity matrix will be provided to assess the organization’s DE maturity emphasizing how all the SELC elements interlink to form a cohesive ecosystem. If implemented, DE can increase efficiency and improve the systems engineering processes' quality and outcomes.

Keywords: digital engineering, digital environment, digital maturity model, single source of truth, systems engineering life-cycle

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Authors: I. Mentziou, C. Delezos, D. Krikidis, A. Nestoridou, G. Boskou

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Introduction: The systems of production and distribution of meals can have a significant impact on the food intake of hospital patients who are likely to develop malnutrition. In hospitals, the consequences of food borne infections can range from annoying to life-threatening for a patient, since they can lead up to death in vulnerable groups Aim: The aim of the present study was the evaluation of food safety management systems implementation, as well as the general evaluation of the total quality management systems in Greek hospitals. Methods: This is a multifocal study on the implementation and evaluation of the food safety management systems in the Greek hospitals of Attica region. Eleven hospitals from the city of Athens were chosen for this purpose. The sample was derived from the high rank personnel of the nutritional department (dietician, head-chef, food technologist, public health inspector). Tailor made questionnaires on hygiene regulations were used as tools for the interviews. Results: Overall, 30 employees in the field of hospital nutrition participated. Most of the replies implied that almost always the hygiene regulations are implemented. Nevertheless, only 30% stated that there is a Hazard Analysis Critical Control Points HACCP system (HACCP) in the hospital. In a small number of questionnaires there were proposals for changes by the staff. Conclusion: Measurement of the opinion of the personnel about the provided food services within a hospital can further lead to continuous improvement of the hospital nutrition.

Keywords: evaluation, food service, HACCP, hospital, personnel

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Authors: N. Soli, B. Chaouachi, M. Bourouis

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We propose in this work the thermodynamic feasibility study of the operation of a refrigerating machine with absorption-diffusion with mixtures of hydrocarbons. It is for a refrigerating machine of low power (300 W) functioning on a level of temperature of the generator lower than 150 °C (fossil energy or solar energy) and operative with non-harmful fluids for the environment. According to this study, we determined to start from the digraphs of Oldham of the different binary of hydrocarbons, the minimal and maximum temperature of operation of the generator, as well as possible enrichment. The cooling medium in the condenser and absorber is done by the ambient air with a temperature at 35 °C. Helium is used as inert gas. The total pressure in the cycle is about 17.5 bars. We used suitable software to modulate for the two binary following the system propylene /butane and propylene/pentane. Our model is validated by comparison with the literature’s resultants.

Keywords: absorption, DAR cycle, diffusion, propyléne

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Authors: Nivedha Rajaram

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Hybrid Quantum solvers have been given prime focus in recent days by computation problem-solving domain industrial applications. D’Wave Quantum Computers are one such paragon of systems built using quantum annealing mechanism. Discrete Quadratic Models is a hybrid quantum computing model class supplied by D’Wave Ocean SDK - a real-time software platform for hybrid quantum solvers. These hybrid quantum computing modellers can be employed to solve classic problems. One such problem that we consider in this paper is finding a network connectivity knowledge hub in a huge network of systems. Using this quantum solver, we try to find out the prime system hub, which acts as a supreme connection point for the set of connected computers in a large network. This paper establishes an innovative problem approach to generate a connectivity system hub plot for a set of systems using DWave ocean SDK hybrid quantum solvers.

Keywords: quantum computing, hybrid quantum solver, DWave annealing, network knowledge graph

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Authors: Abdulatif Abdulsalam Mohamed Shaban

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This paper states that the art of Procedure Entry Array (PEA) plan with a focus on control system applications. This paper begins with an impression of PEA technology development, followed by an arrangement of design technologies, and the use of programmable description languages and system-level design tools. They allow a practical approach based on a unique model for complete engineering electronics systems. There are three main design rules are implemented in the system. These are algorithm based fine-tuning, modularity, and the control act and the architectural constraints. An overview of contributions and limits of PEAs is also given, followed by a short survey of PEA-based gifted controllers for recent engineering systems. Finally, two complete and timely case studies are presented to illustrate the benefits of a PEA implementation when using the proposed system modelling and devise attitude. These consist of the direct control for training motor drives and the control of a diesel-driven stand-alone generator with the help of logical design.

Keywords: control (DC), engineering electronics systems, training motor drives, procedure entry array

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Authors: Stefania Fortino, Petr Hradil, Timo Avikainen

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Timber bridges have an excellent environmental performance, are economical, relatively easy to build and can have a long service life. However, the durability of these bridges is the main problem because of their exposure to outdoor climate conditions. The moisture content accumulated in wood for long periods, in combination with certain temperatures, may cause conditions suitable for timber decay. In addition, moisture content variations affect the structural integrity, serviceability and loading capacity of timber bridges. Therefore, the monitoring of the moisture content in wood is important for the durability of the material but also for the whole superstructure. The measurements obtained by the usual sensor-based techniques provide hygro-thermal data only in specific locations of the wood components. In this context, the monitoring can be assisted by numerical modelling to get more information on the hygro-thermal response of the bridges. This work presents a hygro-thermal model based on a multi-phase moisture transport theory to predict the distribution of moisture content, relative humidity and temperature in wood. Below the fibre saturation point, the multi-phase theory simulates three phenomena in cellular wood during moisture transfer, i.e., the diffusion of water vapour in the pores, the sorption of bound water and the diffusion of bound water in the cell walls. In the multi-phase model, the two water phases are separated, and the coupling between them is defined through a sorption rate. Furthermore, an average between the temperature-dependent adsorption and desorption isotherms is used. In previous works by some of the authors, this approach was found very suitable to study the moisture transport in uncoated and coated stress-laminated timber decks. Compared to previous works, the hygro-thermal fluxes on the external surfaces include the influence of the absorbed solar radiation during the time and consequently, the temperatures on the surfaces exposed to the sun are higher. This affects the whole hygro-thermal response of the timber component. The multi-phase model, implemented in a user subroutine of Abaqus FEM code, provides the distribution of the moisture content, the temperature and the relative humidity in a volume of the timber deck. As a case study, the hygro-thermal data in wood are collected from the ongoing monitoring of the stress-laminated timber deck of Tapiola Bridge in Finland, based on integrated humidity-temperature sensors and the numerical results are found in good agreement with the measurements. The proposed model, used to assist the monitoring, can contribute to reducing the maintenance costs of bridges, as well as the cost of instrumentation, and increase safety.

Keywords: moisture content, multi-phase models, solar radiation, timber decks, FEM

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Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

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In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

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Authors: Shwadhin Sharma

Abstract:

As there has been increasing focus on the shorter attention span of the millennials students, there is a relative absence of instructional tools on behavioral assessments in learning information technology skills within the information systems field and textbooks. This study uses project-based learning in which students gain knowledge and skills related to information technology by working on an extended project that allows students to find a real business problem design information systems based on information collected from the company and develop an information system that solves the problem of the company. Eighty students from two sections of the same course engage in the project from the first week of the class till the sixteenth week of the class to deliver a small business information system that allows them to employ all the skills and knowledge that they learned in the class into the systems they are creating. Computer Information Systems related courses are often difficult to understand and process especially for the Under Representative Minorities students who have limited computer or information systems related (academic) experiences. Project-based learning demands constant attention of the students and forces them to apply knowledge learned in the class to a project that helps retaining knowledge. To make sure our assumption is correct, we started with a pre-test and post-test to test the students learning (of skills) based on the project. Our test showed that almost 90% of the students from the two sections scored higher in post-test as compared to pre-test. Based on this premise, we conducted a further survey that measured student’s job-search preparation, knowledge of data analysis, involved with the course, satisfaction with the course, student’s overall reaction the course and students' ability to meet the traditional learning goals related to the course.

Keywords: project-based learning, job-search preparation, satisfaction with course, traditional learning goals

Procedia PDF Downloads 204

Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

Abstract:

Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

Procedia PDF Downloads 147

Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy

Abstract:

The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.

Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems

Procedia PDF Downloads 72

Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

Abstract:

The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

Procedia PDF Downloads 430