Search results for: discrete time systems

Authors: Nico Fuchs, Fabian Wüllhorst, Laura Maier, Dirk Müller

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The decarbonization of building stocks necessitates the modernization of existing buildings. Key measures for this include reducing energy demands through insulation of the building envelope, replacing heat generators, and installing solar systems. Given limited financial resources, it is impractical to modernize all buildings in a portfolio simultaneously; instead, prioritization of buildings and modernization measures for a given planning horizon is essential. Optimization models for modernization pathways can assist portfolio managers in this prioritization. However, modeling and solving these large-scale optimization problems, often represented as mixed-integer problems (MIP), necessitates simplifying the operation of building energy systems particularly with respect to system dynamics and transient behavior. This raises the question of which level of simplification remains sufficient to accurately account for realistic costs and emissions of building energy systems, ensuring a fair comparison of different modernization measures. This study addresses this issue by comparing a two-stage simulation-based optimization approach with a single-stage mathematical optimization in a mixed-integer linear programming (MILP) formulation. The simulation-based approach serves as a benchmark for realistic energy system operation but requires a restriction of the solution space to discrete choices of modernization measures, such as the sizing of heating systems. After calculating the operation of different energy systems in terms of the resulting final energy demands in simulation models on a first stage, the results serve as input for a second stage MILP optimization, where the design of each building in the portfolio is optimized. In contrast to the simulation-based approach, the MILP-based approach can capture a broader variety of modernization measures due to the efficiency of MILP solvers but necessitates simplifying the building energy system operation. Both approaches are employed to determine the cost-optimal design and dimensioning of several buildings in a portfolio to meet climate targets within limited yearly budgets, resulting in a modernization pathway for the entire portfolio. The comparison reveals that the MILP formulation successfully captures design decisions of building energy systems, such as the selection of heating systems and the modernization of building envelopes. However, the results regarding the optimal dimensioning of heating technologies differ from the results of the two-stage simulation-based approach, as the MILP model tends to overestimate operational efficiency, highlighting the limitations of the MILP approach.

Keywords: building energy system optimization, model accuracy in optimization, modernization pathways, building stock decarbonization

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Authors: Mingyu Xie, Mietek Brdys

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The paper develops a non-linear model predictive control (NMPC) of water quality in drinking water distribution systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.

Keywords: model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives

Procedia PDF Downloads 308

Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

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Authors: Mohamed Amhal, Jose Sayritupac

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Photovoltaic (PV) systems have risen as one of the modern renewable energy sources that are used in wide ranges to produce electricity and deliver it to the electrical grid. In parallel, monitoring systems have been deployed as a key element to track the energy production and to forecast the total production for the next days. The reliability of the PV energy production has become a crucial point in the analysis of PV systems. A deeper understanding of each phenomenon that causes a gain or a loss of energy is needed to better design, operate and maintain the PV systems. This work analyzes the current losses distribution in PV systems starting from the available solar energy, going through the DC side and AC side, to the delivery point. Most of the phenomena linked to energy losses and gains are considered and modeled, based on real time monitoring data and datasheets of the PV system components. An analysis of the order of magnitude of each loss is compared to the current literature and commercial software. To date, the analysis of PV systems performance based on a breakdown structure of energy losses and gains is not covered enough in the literature, except in some software where the concept is very common. The cutting-edge of the current analysis is the implementation of software tools for energy losses estimation in PV systems based on several energy losses definitions and estimation technics. The developed tools have been validated and tested on some PV plants in France, which are operating for years. Among the major findings of the current study: First, PV plants in France show very low rates of soiling and aging. Second, the distribution of other losses is comparable to the literature. Third, all losses reported are correlated to operational and environmental conditions. For future work, an extended analysis on further PV plants in France and abroad will be performed.

Keywords: energy gains, energy losses, losses distribution, monitoring, photovoltaic, photovoltaic systems

Procedia PDF Downloads 159

Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

Procedia PDF Downloads 128

Authors: Yan Yu, Wang Yu, Chen Xintong, Liu Yi, Zhang Yanzhong, Wang Yanji, Chen Xingyu, Zhang Miaocheng, Tong Yi

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Neuromorphic computing based on spiking neural networks (SNNs) has emerged as a promising avenue for building the next generation of intelligent computing systems. Owing to its high-density integration, low power, and outstanding nonlinearity, memristors have attracted emerging attention on achieving SNNs. However, fabricating a low-power and robust memristor-based spiking neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a TiO₂-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, used to realize single layer fully connected (FC) SNNs. Moreover, our TiO₂-based resistive switching (RS) memristors realize spiking-time-dependent-plasticity (STDP), originating from the Ag diffusion-based filamentary mechanism. This work demonstrates that TiO2-based memristors may provide an efficient method to construct hardware neuromorphic computing systems.

Keywords: leaky integrate-and-fire, memristor, spiking neural networks, spiking-time-dependent-plasticity

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Authors: Juneseok You, Kuewhan Jang, Chanho Park, Jaeyeong Choi, Hyunjun Park, Sehyun Shin, Changsoo Han, Sungsoo Na

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Nanomaterials occur toxic effects to human being or ecological systems. Some sensors have been developed to detect toxic materials and the standard for toxic materials has been established. Zinc oxide nanowire (ZnO NW) is known for toxic material. By ionizing in cell body, ionized Zn ions are overexposed to cell components, which cause critical damage or death. In this paper, we detected ZnO NW in water using QCM (Quartz Crystal Microbalance) and ssDNA (single strand DNA). We achieved 30 minutes of response time for real time detection and 100 pg/mL of limit of detection (LOD).

Keywords: zinc oxide nanowire, QCM, ssDNA, toxic material, biosensor

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Authors: Louis N. Y. Wong

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En-echelon fractures are commonly found in rocks, which appear as a special set of regularly oriented and spaced fractures. By using both experimental and numerical approaches, this study investigates the interaction among them, and how this interaction finally contributes to the development of a shear rupture (fault), especially in brittle natural rocks. Firstly, uniaxial compression tests are conducted on marble specimens containing en-echelon flaws. The latter is cut by using the water abrasive jet into the rock specimens. The fracturing processes of these specimens leading to the formation of a fault are observed in detail by the use of a high speed camera. The influences of the flaw geometry on the production of tensile cracks and shear cracks, which in turn dictate the coalescence patterns of the entire set of en-echelon flaws are comprehensively studied. Secondly, a numerical study based on a recently developed contact model, flat-joint contact model using the discrete element method (DEM) is carried out to model the present laboratory experiments. The numerical results provide a quantitative assessment of the interaction of en-echelon flaws. Particularly, the evolution of the stress field, as well as the characteristics of new crack initiation, propagation and coalescence associated with the generation of an eventual shear rupture are studied in detail. The numerical results are found to agree well with the experimental results obtained in both microscopic and macroscopic observations.

Keywords: discrete element method, en-echelon flaws, fault, marble

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Authors: Hafiz Md. Hasan Babu, Khandaker Mohammad Mohi Uddin, Nitish Biswas, Sarreha Tasmin Rikta, Nuzmul Hossain Nahid

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Nanomedicine and bioengineering use biological systems that can perform computing operations. In a biocomputational circuit, different types of biomolecules and DNA (Deoxyribose Nucleic Acid) are used as active components. DNA computing has the capability of performing parallel processing and a large storage capacity that makes it diverse from other computing systems. In most processors, the multiplier is treated as a core hardware block, and multiplication is one of the time-consuming and lengthy tasks. In this paper, cost-effective DNA multipliers are designed using algorithms of molecular DNA operations with respect to conventional ones. The speed and storage capacity of a DNA multiplier are also much higher than a traditional silicon-based multiplier.

Keywords: biological systems, DNA multiplier, large storage, parallel processing

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Authors: Edwin Calderon-Mendoza, Patrick Schweitzer, Serge Weber

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Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Keywords: indoor power line, fault location, fault map trace, series arc fault

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Authors: Hamide Özyürek, Metin Yılmaz

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Standard processes, similar and limited production lines, the production of high direct costs will be more accurate than the use of parts of the traditional cost systems in the literature. However, direct costs, overhead expenses, in turn, decreases the burden of increasingly sophisticated production facilities, a situation that led the researchers to look for the cost of traditional systems of alternative techniques. Variety cost management approaches for example Total quality management (TQM), just-in-time (JIT), benchmarking, kaizen costing, targeting cost, life cycle costs (LLC), activity-based costing (ABC) value engineering have been introduced. Management and cost applications have changed over the past decade and will continue to change. Modern cost systems can provide relevant and accurate cost information. These methods provide the decisions about customer, product and process improvement. The aim of study is to describe and explain the adoption and application of costing systems in SME. This purpose reports on a survey conducted during 2014 small and medium sized enterprises (SME) in Ankara. The survey results were evaluated using SPSS package program.

Keywords: modern costing systems, managerial accounting, cost accounting, costing

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Adekunle O. Afolabi, Pekka Toivanen

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The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.

Keywords: recommendation systems, Internet of Things, healthcare, homecare, real-time

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Authors: Kodo Sektani, Apostolos Tsouvalas, Andrei Metrikine

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The reassessment of existing movable bridges in The Netherlands has created the need for acceptance/rejection criteria to assess whether the machineries are meet certain design demands. However, the existing design code defines a different limit state design, meant for new machineries which is based on a simple linear spring-mass model. Observations show that existing bridges do not confirm the model predictions. In fact, movable bridges are nonlinear systems consisting of mechanical components, such as, gears, electric motors and brakes. Next to that, each movable bridge is characterized by a unique set of parameters. However, in the existing code various variables that describe the physical characteristics of the bridge are neglected or replaced by partial factors. For instance, the damping ratio ζ, which is different for drawbridges compared to bascule bridges, is taken as a constant for all bridge types. In this paper, a model is developed that overcomes some of the limitations of existing modelling approaches to capture the dynamics of the powertrain of a class of bridge machineries First, a semidefinite dynamic model is proposed, which accounts for stiffness, damping, and some additional variables of the physical system, which are neglected by the code, such as nonlinear braking torques. The model gives an upper bound of the peak forces/torques occurring in the powertrain during emergency braking. Second, a discrete nonlinear dynamic model is discussed, with realistic motor torque characteristics during normal operation. This model succeeds to accurately predict the full time history of the occurred stress state of the opening and closing cycle for fatigue purposes.

Keywords: Dynamics of movable bridges, Bridge machinery, Powertrains, Torque measurements

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Authors: Muhammad Zikril Hakim Md. Azizi, Norhafizan Ahmad, Raja Ariffin Raja Ghazilla

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Postural stability, attention level of the archer and particularly the vibrations of the bow itself plays a prominent role in determining the athletes performance. Many techniques and systems had been developing to monitor the parameters of the archers during training. In Malaysia, archery coaches tend to use non-scientific ways that they are familiar with, to evaluate archer performance. An approach that provides more affordable yet accurate systems to the masses and relatively easy system deployment procedure need to be proposed. Hence, this project will address to fulfil the needs. Three area of the archer parameter were included for data monitoring sensors. Attention level can be measured using EEG sensor, centre of mass linked to the postural stability can be measured by foot pressure sensor, and the bow vibrations in three axis will be relayed by the vibrations sensors placed directly on the bow using wireless sensors. Arduino based microcontroller used to relay all the data back to the interfacing systems. Interface systems will be using Python language and C++ framework for user interface and hardware interfacing systems. All sensor data can be observed in real time using the in-house applications, and each sessions can be saved to common files so that coach and the team can have a further discussion and comparisons.

Keywords: archery, graphical user interface, microcontroller, wireless sensor, monitoring system

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Authors: Rauf R. Hussein, Devon M. Ramey

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Integrating Ground Penetrating Radar (GPR) with Geographic Information Systems (GIS) can provide valuable insights for various applications, such as archaeology, transportation, and utility locating. Although there has been progress toward automating the integration of GPR data with GIS, fully automatic integration has not been achieved yet. Additionally, manually integrating GPR data with GIS can be a time-consuming and error-prone process. In this study, actual, real-world GPR applications are presented, and a software named GPR-GIS 10 is created to interactively extract subsurface targets from GPR radargrams and automatically integrate them into GIS. With this software, it is possible to quickly and reliably integrate the two techniques to create informative subsurface maps. The results indicated that automatic integration of GPR with GIS can be an efficient tool to map and view any subsurface targets in their appropriate location in a 3D space with the needed precision. The findings of this study could help GPR-GIS integrators save time and reduce errors in many GPR-GIS applications.

Keywords: GPR, GIS, GPR-GIS 10, drone technology, automation

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Authors: Ting-Yu Hsu, Shyu-Yu Wu, Shieh-Kung Huang, Hung-Wei Chiang, Kung-Chun Lu, Pei-Yang Lin, Kuo-Liang Wen

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Regional earthquake early warning (EEW) systems are not suitable for Taiwan, as most destructive seismic hazards arise due to in-land earthquakes. These likely cause the lead-time provided by regional EEW systems before a destructive earthquake wave arrives to become null. On the other hand, an on-site EEW system can provide more lead-time at a region closer to an epicenter, since only seismic information of the target site is required. Instead of leveraging the information of several stations, the on-site system extracts some P-wave features from the first few seconds of vertical ground acceleration of a single station and performs a prediction of the oncoming earthquake intensity at the same station according to these features. Since seismometers could be triggered by non-earthquake events such as a passing of a truck or other human activities, to reduce the likelihood of false alarms, a seismometer was installed at three different locations on the same site and the performance of the EEW system for these three sensor locations were discussed. The results show that the location on the ground of the first floor of a school building maybe a good choice, since the false alarms could be reduced and the cost for installation and maintenance is the lowest.

Keywords: earthquake early warning, on-site, seismometer location, support vector machine

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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Authors: Haijie Li, Xuping Zhang

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This paper presents a computationally efficient method for the modeling of robot manipulators with flexible links and joints. This approach combines the Discrete Time Transfer Matrix Method with the Finite Segment Method, in which the flexible links are discretized by a number of rigid segments connected by torsion springs; and the flexibility of joints are modeled by torsion springs. The proposed method avoids the global dynamics and has the advantage of modeling non-uniform manipulators. Experiments and simulations of a single-link flexible manipulator are conducted for verifying the proposed methodologies. The simulations of a three-link robot arm with links and joints flexibility are also performed.

Keywords: flexible manipulator, transfer matrix method, linearization, finite segment method

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Aysegul Sener, Gonca Tuncel Memis, Mirac Kamislioglu

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Chaos theory is one of the new paradigms of science since the last century. After determining chaos in the weather systems by Edward Lorenz the popularity of the theory was increased. Chaos is observed in many natural systems and studies continue to defect chaos to other natural systems. Acid rain is one of the environmental problems that have negative effects on environment and acid rains values are monitored continuously. In this study, we aim that analyze the chaotic behavior of acid rains in Turkey with the chaotic defecting approaches. The data of pH degree of rain waters, concentration of sulfate and nitrate data of wet rain water samples in the rain collecting stations which are located in different regions of Turkey are provided by Turkish State Meteorology Service. Lyapunov exponents, reconstruction of the phase space, power spectrums are used in this study to determine and predict the chaotic behaviors of acid rains. As a result of the analysis it is found that acid rain time series have positive Lyapunov exponents and wide power spectrums and chaotic behavior is observed in the acid rain time series.

Keywords: acid rains, chaos, chaotic analysis, Lypapunov exponents

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Authors: Olga I. Moskalenko, Vladislav A. Khanadeev, Anastasya D. Koloskova, Alexey A. Koronovskii, Anatoly A. Pivovarov

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Generalized synchronization is one of the most intricate phenomena in nonlinear science. It can be observed both in systems with a unidirectional and mutual type of coupling including the complex networks. Such a phenomenon has a number of practical applications, for example, for the secure information transmission through the communication channel with a high level of noise. Known methods for the secure information transmission needs in the increase of the privacy of data transmission that arises a question about the observation of such phenomenon in systems with a complex topology of chaotic attractor possessing two or more positive Lyapunov exponents. The present report is devoted to the study of such phenomenon in two unidirectionally and mutually coupled dynamical systems being in chaotic (with one positive Lyapunov exponent) and hyperchaotic (with two or more positive Lyapunov exponents) regimes, respectively. As the systems under study, we have used two mutually coupled modified Lorenz oscillators and two unidirectionally coupled time-delayed generators. We have shown that in both cases the generalized synchronization regime can be detected by means of the calculation of Lyapunov exponents and phase tube approach whereas due to the complex topology of attractor the nearest neighbor method is misleading. Moreover, the auxiliary system approaches being the standard method for the synchronous regime observation, for the mutual type of coupling results in incorrect results. To calculate the Lyapunov exponents in time-delayed systems we have proposed an approach based on the modification of Gram-Schmidt orthogonalization procedure in the context of the time-delayed system. We have studied in detail the mechanisms resulting in the generalized synchronization regime onset paying a great attention to the field where one positive Lyapunov exponent has already been become negative whereas the second one is a positive yet. We have found the intermittency here and studied its characteristics. To detect the laminar phase lengths the method based on a calculation of local Lyapunov exponents has been proposed. The efficiency of the method has been verified using the example of two unidirectionally coupled Rössler systems being in the band chaos regime. We have revealed the main characteristics of intermittency, i.e. the distribution of the laminar phase lengths and dependence of the mean length of the laminar phases on the criticality parameter, for all systems studied in the report. This work has been supported by the Russian President's Council grant for the state support of young Russian scientists (project MK-531.2018.2).

Keywords: complex topology of attractor, generalized synchronization, hyperchaos, Lyapunov exponents

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Authors: Zhi Liu, Hui Jiang, Jin Li, Kunhao Chen, Langfang Zhang

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Fast acquisition of the seismic information and accurate assessment of the earthquake disaster is the key problem for emergency rescue after a destructive earthquake. In order to meet the requirements of the earthquake emergency response and rescue for the cities and counties, a quasi real-time comprehensive evaluation system for earthquake disaster is developed. Based on monitoring data of Micro-Electro-Mechanical Systems (MEMS) strong motion network, structure database of a county area and the real-time disaster information by the mobile terminal after an earthquake, fragility analysis method and dynamic correction algorithm are synthetically obtained in the developed system. Real-time evaluation of the seismic disaster in the county region is finally realized to provide scientific basis for seismic emergency command, rescue and assistant decision.

Keywords: quasi real-time, earthquake disaster data collection, MEMS accelerometer, dynamic correction, comprehensive evaluation

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Authors: Pedro Esteban

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Today’s electrical networks, including microgrids, are evolving into smart grids. The smart grid concept brings the idea that the power comes from various sources (continuous or intermittent), in various forms (AC or DC, high, medium or low voltage, etc.), and it must be integrated into the electric power system in a smart way to guarantee a continuous and reliable supply that complies with power quality and energy efficiency standards and grid code requirements. This idea brings questions for the different players like how the required power will be generated, what kind of power will be more suitable, how to store exceeding levels for short or long-term usage, and how to combine and distribute all the different generation power sources in an efficient way. To address these issues, there has been lots of development in recent years on the field of on-grid and off-grid hybrid power systems (HPS). These systems usually combine one or more modes of electricity generation together with energy storage to ensure optimal supply reliability and high level of energy security. Hybrid power systems combine power generation and energy storage technologies together with real-time energy management and innovative power quality and energy efficiency improvement functionalities. These systems help customers achieve targets for clean energy generation, they add flexibility to the electrical grid, and they optimize the installation by improving its power quality and energy efficiency.

Keywords: microgrids, hybrid power systems, energy storage, power quality improvement

Procedia PDF Downloads 128

Authors: Qianqian He, Naian Liu, Xiaodong Xie, Linhe Zhang, Yang Zhang, Weidong Yan

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In the wild, the vegetation layer with exceptionally complex fuel composition and heterogeneous spatial distribution strongly affects the rate of fire spread (ROS) and fire intensity. Clarifying the influence of fuel bed structure on fire spread behavior is of great significance to wildland fire management and prediction. The packing ratio is one of the key physical parameters describing the property of the fuel bed. There is a threshold value of the packing ratio for ROS, but little is known about the controlling mechanism. In this study, to address this deficiency, a series of fire spread experiments were performed across a discrete fuel bed composed of some regularly arranged laser-cut cardboards, with constant wind speed and different packing ratios (0.0125-0.0375). The experiment aims to explore the relative importance of the internal and surface heat transfer with packing ratio. The dependence of the measured ROS on the packing ratio was almost consistent with the previous researches. The data of the radiative and total heat fluxes show that the internal heat transfer and surface heat transfer are both enhanced with increasing packing ratio (referred to as ‘Stage 1’). The trend agrees well with the variation of the flame length. The results extracted from the video show that the flame length markedly increases with increasing packing ratio in Stage 1. Combustion intensity is suggested to be increased, which, in turn, enhances the heat radiation. The heat flux data shows that the surface heat transfer appears to be more important than the internal heat transfer (fuel preheating inside the fuel bed) in Stage 1. On the contrary, the internal heat transfer dominates the fuel preheating mechanism when the packing ratio further increases (referred to as ‘Stage 2’) because the surface heat flux keeps almost stable with the packing ratio in Stage 2. As for the heat convection, the flow velocity was measured using Pitot tubes both inside and on the upper surface of the fuel bed during the fire spread. Based on the gas velocity distribution ahead of the flame front, it is found that the airflow inside the fuel bed is restricted in Stage 2, which can reduce the internal heat convection in theory. However, the analysis indicates not the influence of inside flow on convection and combustion, but the decreased internal radiation of per unit fuel is responsible for the decrease of ROS.

Keywords: discrete fuel bed, fire spread, packing ratio, wildfire

Procedia PDF Downloads 129

Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

Abstract:

Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

Procedia PDF Downloads 514

Authors: Joanna Nieżurawska, Hanna Karaszewska, Anna Dziadkiewicz

Abstract:

Contemporary conditions force companies to constantly implement changes and improvements, which is connected with plasticization of their activity in all spheres. Cafeteria systems are a good example of flexible remuneration systems. Cafeteria systems are well-known and often used in the United States, Great Britain and in Western Europe. In Poland, they are hardly ever used and greater flexibility in remuneration packages refers mainly to senior managers and executives. The main aim of this article is to research the attractiveness of the cafeteria system as viewed by generation Z. The additional aim of the article is to prioritize using the importance index of particular types of cafeteria systems from the generation Z’s perspective, as well as to identify the factors which determine the development of cafeteria systems in Poland. The research was conducted in June 2015 among 185 young employees (generation Z). The paper presents some of the results.

Keywords: cafeteria, generation X, generation Y, generation Z, flexible remuneration systems, plasticization of remuneration

Procedia PDF Downloads 399

Authors: Ahmad Aridah, Maria Fay Rola-Rubzen, Zora Singh

Abstract:

This study investigated the effectiveness of various types of irrigation systems in regards to the impact that these have on the productivity of date palms in the semi-arid and arid region of Sebha, Southwest Libya. The date palm is an economically important crop in Libya and contributes to the agriculture industry, foreign exchange earnings, farmers’ income, and employment in the country. The date palm industry relies on large amounts of water for growing the crop. Farmers in Southwest Libya use a variety of irrigation systems, but the quality and quantity of water varies between systems and this affects the productivity and income of farmers. Using survey data from 210 farmers, this study estimated and assessed the pros and cons of different types of irrigation systems for date palm production under various irrigation systems currently used in Sebha, Libya. The number of years farmers have used irrigation, the area, irrigation water consumption, time of irrigation, number of farm workers (including family labour) and inputs used were measured for surface, sprinkler and drip irrigation methods. Findings from this research provide new insights into the advantages and disadvantages of the various irrigation systems, problems encountered by farmers and the factors that affect the quality and quantity of the irrigation system. The paper discussed proposed solutions to deal with the problems including timing of irrigation, canal maintenance, repair of wells and water control.

Keywords: Libya, factors, irrigation method, date palm

Procedia PDF Downloads 329

Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

Abstract:

Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

Procedia PDF Downloads 142

Authors: Jan Busch, Maurice Schmidt, Peter Nyhuis

Abstract:

The change of conditions for production companies in high-wage countries is characterized by the globalization of competition and the transition of a supplier´s to a buyer´s market. The companies need to face the challenges of reacting flexibly to these changes. Due to the significant and increasing degree of automation, assembly has become the most expensive production process. Regarding the reduction of production cost, assembly consequently offers a considerable rationalizing potential. Therefore, an aerodynamic feeding system has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. In former research activities, this system has been enabled to adjust itself using genetic algorithm. The longer the genetic algorithm is executed the better is the feeding quality. In this paper, the relation between the system´s setting time and the feeding quality is observed and a function which enables the user to achieve the minimum of the total feeding time is presented.

Keywords: aerodynamic feeding system, batch size, optimisation, setting time

Procedia PDF Downloads 247