Search results for: wind turbine systems

Authors: J. R. Wang, S. W. Chen, Y. Chiang, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT analysis methodology was established for Maanshan nuclear power plant (NPP). The Final Safety Analysis Report (FSAR), reports, and other data were used in this study. To evaluate the control room habitability under the CO₂ storage burst, the HABIT methodology was used to perform this analysis. The HABIT result was below the R.G. 1.78 failure criteria. This indicates that Maanshan NPP habitability can be maintained. Additionally, the sensitivity study of the parameters (wind speed, atmospheric stability classification, air temperature, and control room intake flow rate) was also performed in this research.

Keywords: PWR, HABIT, Habitability, Maanshan

Procedia PDF Downloads 446

Authors: Y. Chiang, W. Y. Li, J. R. Wang, S. W. Chen, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT code was used to estimate the concentration under the CO₂ and H₂SO₄ storage burst conditions for Kuosheng nuclear power plant (NPP). The Final Safety Analysis Report (FSAR) and reports were used in this research. In addition, to evaluate the control room habitability for these cases, the HABIT analysis results were compared with the R.G. 1.78 failure criteria. The comparison results show that the HABIT results are below the criteria. Additionally, some sensitivity studies (stability classification, wind speed and control room intake rate) were performed in this study.

Keywords: BWR, HABIT, habitability, Kuosheng

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Authors: Ondrej Lufinka, Jan Kaderabek, Juraj Prstek, Jiri Skala, Kamil Kosturik

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This paper deals with the problem of using Autonomous Robotic Platforms (ARP) for the ADAS (Advanced Driver Assistance Systems) testing in automotive. There are different possibilities of the testing already in development, and lately, the autonomous robotic platforms are beginning to be used more and more widely. Autonomous Robotic Platform discussed in this paper explores the hardware and software design possibilities related to the field of embedded systems. The paper focuses on its chapters on the introduction of the problem in general; then, it describes the proposed prototype concept and its principles from the embedded HW and SW point of view. It talks about the key features that can be used for the innovation of these platforms (e.g., modularity, omnidirectional movement, common and non-traditional sensors used for localization, synchronization of more platforms and cars together, or safety mechanisms). In the end, the future possible development of the project is discussed as well.

Keywords: advanced driver assistance systems, ADAS, autonomous robotic platform, embedded systems, hardware, localization, modularity, multiple robots synchronization, omnidirectional movement, safety mechanisms, software

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Authors: Michel Soto Chalhoub

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Building designers in the Mediterranean region and other parts of the world utilize natural stone panels on the exterior façades as skin cover. This type of finishing is not only intended for aesthetic reasons but also environmental. The stone, since the earliest ages of civilization, has been used in construction and to-date some of the most appealing buildings owe their beauty to stone finishing. The stone also provides warmth in winter and freshness in summer as it moderates heat transfer and absorbs radiation. However, as structural codes became increasingly stringent about the dynamic performance of buildings, it became essential to study the performance of stone panels under cyclic loading – a condition that arises under the building is subjected to wind or earthquakes. The present paper studies the performance of stone panels using mechanical connectors when subjected to load reversal. In this paper, we present a theoretical model that addresses modes of failure in the steel connectors, by yield, and modes of failure in the stone, by fracture. Then we provide an experimental set-up and test results for rectangular stone panels of varying thickness. When the building is subjected to an earthquake, its rectangular panels within the structural system are subjected to shear deformations, which in turn impart stress into the stone cover. Rectangular stone panels, which typically range from 40cmx80cm to 60cmx120cm, need to be designed to withstand transverse loading from the direct application of lateral loads, and to withstand simultaneously in-plane loading (membrane stress) caused by inter-story drift and overall building lateral deflection. Results show correlation between the theoretical model which we derive from solid mechanics fundamentals and the experimental results, and lead to practical design recommendations. We find that for panel thickness below a certain threshold, it is more advantageous to utilize structural adhesive materials to connect stone panels to the main structural system of the building. For larger panel thicknesses, it is recommended to utilize mechanical connectors with special detailing to ensure a minimum level of ductility and energy dissipation.

Keywords: solid mechanics, cyclic loading, mechanical connectors, natural stone, seismic, wind, building skin

Procedia PDF Downloads 257

Authors: Mehmet Savsar

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Complex Life Support Systems (LSS) are used in all large commercial and public aquariums in order to keep the fish alive. Reliabilities of individual equipment, as well as the complete system, are extremely important and critical since the life and safety of important fish depend on these life support systems. Failure of some critical device or equipment, which do not have redundancy, results in negative consequences and affects life support as a whole. In this paper, we have considered a life support system in a large public aquarium in Kuwait Scientific Center and presented a procedure and analysis to show how the reliability of such systems can be estimated by using appropriate tools and collected data. We have also proposed possible improvements for systems reliability. In particular, addition of parallel components and spare parts are considered and the numbers of spare parts needed for each component to achieve a required reliability during specified lead time are calculated. The results show that significant improvements in system reliability can be achieved by operating some LSS components in parallel and having certain numbers of spares available in the spare parts inventories. The procedures and the results presented in this paper are expected to be useful for aquarium engineers and maintenance managers dealing with LSS.

Keywords: life support systems, aquariums, reliability, failures, availability, spare parts

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Authors: Siddeeq Y. Ameen, Mohammed K. Yousif

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Cooperative communication systems are considered to be a promising technology to improve the system capacity, reliability and performances over fading wireless channels. Cooperative relaying system with a single antenna will be able to reach the advantages of multiple antenna communication systems. It is ideally suitable for the distributed communication systems; the relays can cooperate and form virtual MIMO systems. Thus the paper will aim to investigate the possible enhancement of cooperated system using decode and forward protocol. On decode and forward an attempt to cancel or at least reduce the interference instead of increasing the SNR values is achieved. The latter can be achieved via the use group of relays depending on the channel status from source to relay and relay to destination respectively. In the proposed system, the transmission time has been divided into two phases to be used by decode and forward protocol. The first phase has been allocated for the source to transmit its data whereas the relays and destination nodes are in receiving mode. On the other hand, the second phase is allocated for the first and second groups of relay nodes to relay the data to the destination node. Simulations results have shown an improvement in performance is achieved compared to the conventional decode and forward in terms of BER and transmission rate.

Keywords: cooperative systems, decode and forward, interference cancellation, virtual MIMO

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Authors: Amarnath M., Ramachandra C. G., H. Chelladurai, P..Sateesh Kumar, K. Santhosh Kumar

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Journal bearings are extensively used sliding contact machine elements to support radial/axial loaded rotors used in various applications viz. automobile crankshaft, turbine propeller shaft, rope conveyer, heavy duty electric motors. The primary reasons for the failures of these bearings include unstable lubricant film, oil degradation, misalignment, etc. This paper describes the results of experimental investigations carried out to detect surface fatigue wear developed on load bearing the contact surfaces of journal bearing. The test bearing was subjected to fatigue load cycles over a period of 600 hours. The vibration signals were acquired from the journal bearing at regular intervals of 100 hrs. These signals were post-processed by using the vibration analysis technique to obtain diagnostic information of wear propagated in the journal-bearing system.

Keywords: fatigue, journal bearing, sound signals, vibration signals, wear

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

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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

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Authors: Rhaed Khiati, Muhammad Hanif

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In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. In this work, we proposed a smart hospital bed, which mixes the complexity and big data usage of traditional healthcare systems with the comfort found in soft beds while taking certain concerns like data confidentiality, security, and maintaining SLA agreements, etc. into account. This research work potentially provides users, namely patients and doctors, with a seamless interaction with to their respective nurses, as well as faster access to up-to-date personal data, including prescriptions and severity of the condition in contrast to the previous research in the area where there is lack of consideration of such provisions.

Keywords: big data, smart healthcare, distributed systems, bioinformatics

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Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

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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

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Authors: G. L. Rithika, Arvind B. S., Akash R., Ananda Vinayak, Hema M. S.

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Cryptocurrencies were first launched in the year 2009 and have been a great asset to own. Cryptocurrencies are a representation of a completely distinct decentralization model for money. They also contribute to the elimination of currency monopolies and the liberation of money from control. The fact that no government agency can determine a coin's value or flow is what cryptocurrency advocates believe makes them safe and secure. The aim of this paper is to analyze the economic implications of cryptocurrency and how it would disrupt traditional financial systems. This paper analyses the growth of Cryptocurrency over the years and the potential threats of cryptocurrency to financial systems. Our analysis shows that although the DeFi design, like the traditional financial system, may have the ability to lower transaction costs, there are multiple layers where rents might build up because of endogenous competition limitations. The permissionless and anonymous design of DeFi poses issues for ensuring tax compliance, anti-money laundering laws and regulations, and preventing financial misconduct.

Keywords: cryptocurrencies, bitcoin, blockchain technology, traditional financial systems, decentralisation, regulatory framework

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Authors: Samar Raffoul, Martin Heywood, Dimitrios Moutaftsis, Michael Rowell

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This paper comprises an experimental investigation into the structural performance of cold formed steel (CFS) and timber board composite floor systems. The tests include a series of small-scale pushout tests and full-scale bending tests carried out using a refined loading system to simulate uniformly distributed constant load. The influence of connection details (screw spacing and adhesives) on floor performance was investigated. The results are then compared to predictions from relevant existing models for composite floor systems. The results of this research demonstrate the significant benefits of considering the composite action of the boards in floor design. Depending on connection detail, an increase in flexural stiffness of up to 40% was observed in the floor system, when compared to designing joists individually.

Keywords: cold formed steel joists, composite action, flooring systems, shear connection

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Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

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The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Monica Hoeldtke Pietruchinski, Andrey Ricardo Pimentel

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The teaching of computer programming for beginners has been presented to the community as a not simple or trivial task. Several methodologies and research tools have been developed; however, the problem still remains. This paper aims to present multi-agent system architecture to be incorporated to the educational collaborative game software for teaching programming that monitors, evaluates and encourages collaboration by the participants. A literature review has been made on the concepts of Collaborative Learning, Multi-agents systems, collaborative games and techniques to teach programming using these concepts simultaneously.

Keywords: architecture of multi-agent systems, collaborative evaluation, collaboration assessment, gamifying educational software

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Authors: Touil Djamal, Fergani Zineb

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In this study, an Organic Rankine Cycle (ORC) with Cyclohexane working fluid is proposed for cogeneration in the cement industry. In this regard: first, a parametric study is conducted to evaluate the effects of some key parameters on the system performances. Next, single and multi-objective optimizations are performed to achieve the system optimal design. The optimization considers the exergy efficiency, the cost per exergy unit and the environmental impact of the net produced power as objective functions. Finally, exergy, exergoeconomic and exergoenvironmental analysis of the cycle is carried out at the optimum operating conditions. The results show that the turbine inlet pressure, the pinch point temperature difference and the heat transfer fluid temperature have significant effects on the performances of the ORC system.

Keywords: organic rankine cycle, multi-objective optimization, exergy, exergoeconomic, exergoenvironmental, multi-objective optimisation, organic rankine cycle, cement plant

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Authors: Gizem Kodak, Alper Unal, Birsen Koldemir, Tayfun Acarer

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Turkish Straits System which consists of Istanbul Strait (Bosphorus), Canakkale Strait (Dardanelles) and the Marmara Sea has a strategical location on international maritime as it is a unique waterway between the Mediterranean Sea, Black Sea and the Aegean Sea. Thus, this area has great importance since it is the only waterway between Black Sea countries and the rest of the World. Turkish Straits System has dangerous environmental factors hosts more vessel every day through developing World trade and this situation results in expanding accident risks day by day. Today, a lot of precautions have been taken to ensure safe navigation and to prevent maritime accidents, and international standards are followed to avoid maritime accidents. Despite this, the environmental factors that affect this area, trigger the maritime accidents and threaten the vessels with new accidents risks in different months with different hazards. This descriptive study consists of temporal and spatial analyses of environmental factors causing maritime accidents. This study also aims at contributing to safety navigation including monthly and regionally characteristics of variables. In this context, two different data sets are created consisting of environmental factors and accidents. This descriptive study on the accidents between 2001 and 2017 the mentioned region also studies the months and places of the accidents with environmental factor variables. Environmental factor variables are categorized as dynamic and static factors. Dynamic factors are appointed as meteorological and oceanographical while static factors are appointed as geological factors that threaten safety navigation with geometrical restricts. The variables that form dynamic factors are approached meteorological as wind direction, wind speed, wave altitude and visibility. The circulations and properties of the water mass on the system are studied as oceanographical properties. At the end of the study, the efficient meteorological and oceanographical parameters on the region are presented monthly and regionally. By this way, we acquired the monthly, seasonal and regional distributions of the accidents. Upon the analyses that are done; The Turkish Straits System that connects the Black Sea countries with the other countries and which is one of the most important parts of the world trade; is analyzed on temporal and spatial dimensions on the reasons of the accidents and have been presented as environmental factor dynamics causing maritime accidents.

Keywords: descriptive study, environmental factors, maritime accidents, statistics

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Authors: James Kaweesa

Abstract:

The Internet of Things (IoT) has become a critical component of modern technology, enabling the connection of numerous devices to the internet. The interconnected nature of IoT devices, along with their heterogeneous and resource-constrained nature, makes them vulnerable to various types of attacks, such as malware, denial-of-service attacks, and network scanning. Intrusion Detection Systems (IDSs) are a key mechanism for protecting IoT networks and from attacks by identifying and alerting administrators to suspicious activities. In this review, the paper will discuss the different types of IDSs available for IoT systems and evaluate their effectiveness in detecting and preventing attacks. Also, examine the various evaluation methods used to assess the performance of IDSs and the challenges associated with evaluating them in IoT environments. The review will highlight the need for effective and efficient IDSs that can cope with the unique characteristics of IoT networks, including their heterogeneity, dynamic topology, and resource constraints. The paper will conclude by indicating where further research is needed to develop IDSs that can address these challenges and effectively protect IoT systems from cyber threats.

Keywords: cyber-threats, iot, intrusion detection system, networks

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: Vahid Rashtchi, Ashkan Pirooz

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This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

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Authors: Adetunji A. Adeyanju., Mathew O. Omeike, Johnson O. Adeniran, Biodun S. Badmus

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In this paper, we discuss certain conditions for uniform asymptotic stability and uniform ultimate boundedness of solutions to some systems of Aizermann-type of differential equations by means of second method of Lyapunov. In achieving our goal, some Lyapunov functions are constructed to serve as basic tools. The stability results in this paper, extend some stability results for some Aizermann-type of differential equations found in literature. Also, we prove some results on uniform boundedness and uniform ultimate boundedness of solutions of systems of equations study.

Keywords: Aizermann, boundedness, first order, Lyapunov function, stability

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Mahdi Alsagour, Sam Ramrattan

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This paper was developed to investigate two types of sands from the Kingdom of Saudi Arabia (KSA) for potential use in the global metal casting industry. Four types of sands were selected for study, two of the sand systems investigated are natural sands from the KSA. The third sand sample is a heat processed synthetic sand and the last sample is commercially available US silica sand that is used as a control in the study. The purpose of this study is to define the durability of the four sand systems selected for foundry usage. Additionally, chemical analysis of the sand systems is presented before and after elevated temperature exposure. Results show that Saudi silica sands are durable and can be used in foundry processing.

Keywords: alternative molding media, foundry sand, reclamation, silica sand, specialty sand

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Authors: Imme Petersen, Wiebke Sick, Regine Kollek

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In systems medicine, high-throughput technologies produce large amounts of data on different biological and pathological processes, including (disturbed) gene expressions, metabolic pathways and signaling. The large volume of data of different types, stored in separate databases and often located at different geographical sites have posed new challenges regarding data handling and processing. Tools based on bioinformatics have been developed to resolve the upcoming problems of systematizing, standardizing and integrating the various data. However, the heterogeneity of data gathered at different levels of biological complexity is still a major challenge in data analysis. To build multilayer disease modules, large and heterogeneous data of disease-related information (e.g., genotype, phenotype, environmental factors) are correlated. Therefore, a great deal of attention in systems medicine has been put on data standardization, primarily to retrieve and combine large, heterogeneous datasets into standardized and incorporated forms and structures. However, this data-centred concept of standardization in systems medicine is contrary to the debate in science and technology studies (STS) on standardization that rather emphasizes the dynamics, contexts and negotiations of standard operating procedures. Based on empirical work on research consortia that explore the molecular profile of diseases to establish systems medical approaches in the clinic in Germany, we trace how standardized data are processed and shaped by bioinformatics tools, how scientists using such data in research perceive such standard operating procedures and which consequences for knowledge production (e.g. modeling) arise from it. Hence, different concepts and meanings of standardization are explored to get a deeper insight into standard operating procedures not only in systems medicine, but also beyond.

Keywords: data, science and technology studies (STS), standardization, systems medicine

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper presents development results of usage of C-OTDR monitoring systems for rail traffic management. The C-OTDR method is based on vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes which take place due to microscopic seismoacoustic impacts on the optical fiber allows to determine seismoacoustic emission source positions and to identify their types. This approach proved successful for rail traffic management (moving block system, weigh- in-motion system etc).

Keywords: C-OTDR systems, moving block-sections, rail traffic management, Rayleigh backscattering, weigh-in-motion

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Authors: Sitarrine Thongpussawal, Dasarath Jayasuriya, Thanaroj Woraratprasert, Sakawtree Prajamwong

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Thailand grapples with recurrent floods causing substantial repercussions on its economy, society, and environment. In 2021, the economic toll of these floods amounted to an estimated 53,282 million baht, primarily impacting the agricultural sector. The existing flood monitoring system in Thailand suffers from inaccuracies and insufficient information, resulting in delayed warnings and ineffective communication to the public. The Office of the National Water Resources (OWNR) is tasked with developing and integrating data and information systems for efficient water resources management, yet faces challenges in monitoring accuracy, forecasting, and timely warnings. This study endeavors to evaluate the viability of enhancing Thailand's Flood Forecasting and Warning (FFW) systems. Additionally, it aims to formulate a comprehensive work package grounded in international best practices to enhance the country's FFW systems. Employing qualitative research methodologies, the study conducted in-depth interviews and focus groups with pertinent agencies. Data analysis involved techniques like note-taking and document analysis. The study substantiates the feasibility of developing and enhancing FFW systems in Thailand. Implementation of international best practices can augment the precision of flood forecasting and warning systems, empowering local agencies and residents in high-risk areas to prepare proactively, thereby minimizing the adverse impact of floods on lives and property. This research underscores that Thailand can feasibly advance its FFW systems by adopting international best practices, enhancing accuracy, and improving preparedness. Consequently, the study enriches the theoretical understanding of flood forecasting and warning systems and furnishes valuable recommendations for their enhancement in Thailand.

Keywords: flooding, forecasting, warning, monitoring, communication, Thailand

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Authors: Mohamed El-Sayed Mosaad

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An analytic approach is obtained for the steady heat transfer problem of two fluid systems, in thermal communication via heat conduction across a solid wall separating them. The two free convection layers created on wall sides are assumed to be in parallel flow. Fluid-solid interface temperature on wall sides is not prescribed in analysis in advance; rather, determined from conjugate solution among other unknown parameters. The analysis highlights the main conjugation parameters controlling thermal interaction process of involved heat transfer modes. Heat transfer results of engineering importance are obtained.

Keywords: conjugate heat transfer, boundary layer, convection, thermal systems

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Authors: Emine Laarouchi, Daniela Cancila, Laurent Soulier, Hakima Chaouchi

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Cyber-Physical Systems as drones proved their efficiency for supporting emergency applications. For these particular applications, travel time and autonomous navigation algorithms are of paramount importance, especially when missions are performed in urban environments with high obstacle density. In this context, however, safety properties are not properly addressed. Our ambition is to optimize the system safety level under autonomous navigation systems, by preserving performance of the CPS. At this aim, we introduce genetic algorithms in the autonomous navigation process of the drone to better infer its trajectory considering the possible obstacles. We first model the wished safety requirements through a cost function and then seek to optimize it though genetics algorithms (GA). The main advantage in the use of GA is to consider different parameters together, for example, the level of battery for navigation system selection. Our tests show that the GA introduction in the autonomous navigation systems minimize the risk of safety lossless. Finally, although our simulation has been tested for autonomous drones, our approach and results could be extended for other autonomous navigation systems such as autonomous cars, robots, etc.

Keywords: safety, unmanned aerial vehicles , CPS, ACPS, drones, path planning, genetic algorithms

Procedia PDF Downloads 181