Search results for: steam turbine machines

Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Pranab Kumar Goswami, Elena Gurung

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Small and medium enterprises (SME) are considered as the driving force for the economic growth of a developing country like India. Most of the SMEs are located in residential/non-industrial areas to avoid legal obligations of occupational safety and health (OSH) provisions. This study was conducted in Delhiwith a view to analyze the accidents that occurredduringthe year 2019 & 2020. The objective of the study was to find out the accident prone SMEs in Delhi and major causes of such accidents. Methods: Survey and comprehensive data analysis methods, followed by applying simple statistical techniques, were used for this study. The accident reports for the study period collected from the labour department and police stations were analyzed for the study. The injured workers were interviewed to ascertain safety compliances, training and awareness programs, etc. The study was completed in March2021. Results: It was found that most of the accidents took place in SMEs located in residential/non- industrial areas in Delhi. The accident-prone machines were found to be power presses (42%) and injection moulding machines (37%). Predominantly unsafe machinery or unsafe working conditions and lack of training of worker were observed to be the major causes of accidents in such industries. Conclusions: It was concluded from the study that unsafe machinery/equipment and lack of proper training to the workers were two main reasons for increase in accidents.It was also concluded that the industries located in industrial areas were better placed in terms of workplace compliances. The managements who were running their operations from residential/non-industrial areaswere found to be less aware on health and safety issues. Lack of enforcement by government agencies in such areas has escalated this problem. Adequate training to workers, managing safe & healthy workplace, and sustained enforcement can reduce accidents in such industries.

Keywords: SME, accident prevention, cause of accident, unorganised

Procedia PDF Downloads 83

Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

Procedia PDF Downloads 232

Authors: Loice K. Gudukeya, Charles Mbohwa

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The research investigates hydropower plant efficiency with a view to improving the power output while keeping the overall project cost per kilowatt produced within an acceptable range. It reviews the commonly used Pelton and Cross-flow turbines which are employed in the region for micro-hydro power plants. Turbine parameters such as surface texture, material used and fabrication processes are dealt with the intention of increasing the efficiency by 20 to 25 percent for the micro hydro-power plants.

Keywords: hydro, power plant, efficiency, manufacture

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Authors: David Serero, Loic Couton, Jean-Denis Parisse, Robert Leroy

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This paper presents an analysis method of airflow at the periphery of several typologies of architectural volumes. To understand the complexity of the urban environment on the airflows in the city, we compared three sites at different architectural scale. The research sets a method to identify the optimal location for the installation of wind turbines on the edges of a building and to achieve an improvement in the performance of energy extracted by precise localization of an accelerating wing called “aero foil”. The objective is to define principles for the installation of wind turbines and natural ventilation design of buildings. Instead of theoretical winds analysis, we combined numerical aeraulic simulations using STAR CCM + software with wind data, over long periods of time (greater than 1 year). If airflows computer fluid analysis (CFD) simulation of buildings are current, we have calibrated a virtual wind tunnel with wind data using in situ anemometers (to establish localized cartography of urban winds). We can then develop a complete volumetric model of the behavior of the wind on a roof area, or an entire urban island. With this method, we can categorize: - the different types of wind in urban areas and identify the minimum and maximum wind spectrum, - select the type of harvesting devices - fixing to the roof of a building, - the altimetry of the device in relation to the levels of the roofs - The potential nuisances around. This study is carried out from the recovery of a geolocated data flow, and the connection of this information with the technical specifications of wind turbines, their energy performance and their speed of engagement. Thanks to this method, we can thus define the characteristics of wind turbines to maximize their performance in urban sites and in a turbulent airflow regime. We also study the installation of a wind accelerator associated with buildings. The “aerofoils which are integrated are improvement to control the speed of the air, to orientate it on the wind turbine, to accelerate it and to hide, thanks to its profile, the device on the roof of the building.

Keywords: wind energy harvesting, wind turbine selection, urban wind potential analysis, CFD simulation for architectural design

Procedia PDF Downloads 131

Authors: Ticiane Rossi, Maurício C. Araújo, José O. Brito, Harold S. Freeman

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Natural dyes are gaining interest due their expected low risk to human health and to the environment. In this study, the wash fastness of a natural coloring matter from the liquid waste produced in the steam treatment of eucalyptus wood in textile fabrics was investigated. Specifically, eucalyptus wood extract was used to dye cotton, nylon and wool in an exhaust dyeing process without the addition of the traditional mordanting agents and then submitted to wash fastness analysis. The resulting dyed fabrics were evaluated for color fastness. It was found that wash fastness of dyed fabrics was very good to cotton and excellent to nylon and wool.

Keywords: eucalyptus, natural dye, textile fibers, wash fastness

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Authors: B. Atli-Veltin, A. Vosteen, D. Megan, A. Jedynska, L. K. Cheng

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Composite materials combine the advantages of being lightweight and possessing high strength. This is in particular of interest for the development of large constructions, e.g., aircraft, space applications, wind turbines, etc. One of the shortcomings of using composite materials is the complex nature of the failure mechanisms which makes it difficult to predict the remaining lifetime. Therefore, condition and health monitoring are essential for using composite material for critical parts of a construction. Different types of sensors are used/developed to monitor composite structures. These include ultrasonic, thermography, shearography and fiber optic. The first 3 technologies are complex and mostly used for measurement in laboratory or during maintenance of the construction. Optical fiber sensor can be surface mounted or embedded in the composite construction to provide the unique advantage of in-operation measurement of mechanical strain and other parameters of interest. This is identified to be a promising technology for Structural Health Monitoring (SHM) or Prognostic Health Monitoring (PHM) of composite constructions. Among the different fiber optic sensing technologies, Fiber Bragg Grating (FBG) sensor is the most mature and widely used. FBG sensors can be realized in an array configuration with many FBGs in a single optical fiber. In the current project, different aspects of using embedded FBG for composite wind turbine monitoring are investigated. The activities are divided into two parts. Firstly, FBG embedded carbon composite laminate is subjected to tensile and bending loading to investigate the response of FBG which are placed in different orientations with respect to the fiber. Secondly, the demonstration of using FBG sensor array for temperature and strain sensing and monitoring of a 5 m long scale model of a glass fiber mono-pile is investigated. Two different FBG types are used; special in-house fibers and off-the-shelf ones. The results from the first part of the study are showing that the FBG sensors survive the conditions during the production of the laminate. The test results from the tensile and the bending experiments are indicating that the sensors successfully response to the change of strain. The measurements from the sensors will be correlated with the strain gauges that are placed on the surface of the laminates.

Keywords: Fiber Bragg Gratings, embedded sensors, health monitoring, wind turbine towers

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Authors: Asfaw Gezae Daful, Mohsen Alimandagari, Kathleen Haigh, Somayeh Farzad, Eugene Van Rensburg, Johann F. Görgens

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The sugar industry has to 're-invent' itself to ensure long-term economic survival and opportunities for job creation and enhanced community-level impacts, given increasing pressure from fluctuating and low global sugar prices, increasing energy prices and sustainability demands. We propose biorefineries for re-vitalisation of the sugar industry using low value lignocellulosic biomass (sugarcane bagasse, leaves, and tops) annexed to existing sugar mills, producing a spectrum of high value platform chemicals along with biofuel, bioenergy, and electricity. Opportunity is presented for greener products, to mitigate climate change and overcome economic challenges. Xylose from labile hemicellulose remains largely underutilized and the conversion to value-add products a major challenge. Insight is required on pretreatment and/or extraction to optimize production of cellulosic ethanol together with lactic acid, furfural or biopolymers from sugarcane bagasse, leaves, and tops. Experimental conditions for alkaline and pressurized hot water extraction dilute acid and steam explosion pretreatment of sugarcane bagasse and harvest residues were investigated to serve as a basis for developing various process scenarios under a sugarcane biorefinery scheme. Dilute acid and steam explosion pretreatment were optimized for maximum hemicellulose recovery, combined sugar yield and solids digestibility. An optimal range of conditions for alkaline and liquid hot water extraction of hemicellulosic biopolymers, as well as conditions for acceptable enzymatic digestibility of the solid residue, after such extraction was established. Using data from the above, a series of energy efficient biorefinery scenarios are under development and modeled using Aspen Plus® software, to simulate potential factories to better understand the biorefinery processes and estimate the CAPEX and OPEX, environmental impacts, and overall viability. Rigorous and detailed sustainability assessment methodology was formulated to address all pillars of sustainability. This work is ongoing and to date, models have been developed for some of the processes which can ultimately be combined into biorefinery scenarios. This will allow systematic comparison of a series of biorefinery scenarios to assess the potential to reduce negative impacts on and maximize the benefits of social, economic, and environmental factors on a lifecycle basis.

Keywords: biomass, biorefinery, green economy, sustainability

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: M. A. Ferhat, M. N. Boukhatem, F. Chemat

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Lycopene extraction with petroleum derivatives as solvents has caused safety, health, and environmental concerns everywhere. Thus, finding a safe alternative solvent will have a strong and positive impact on environments and general health of the world population. d-limonene from the orange peel was extracted through a steam distillation procedure followed by a deterpenation process and combining this achievement by using it as a solvent for extracting lycopene from tomato fruit as a substitute of dichloromethane. Lycopene content of fresh tomatoes was determined by high-performance liquid chromatography after extraction. Yields obtained for both extractions showed that yields of d-limonene’s extracts were almost equivalent to those obtained using dichloromethane. The proposed approach using a green solvent to perform extraction is useful and can be considered as a nice alternative to conventional petroleum solvent where toxicity for both operator and environment is reduced.

Keywords: alternative solvent, d-limonene, extraction, lycopene

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Authors: Saule Mussabekova

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Recent advances in genetics have allowed increasing acutely the capacities of the formation of reliable evidence in conducting forensic examinations. Thus, traces of biological origin are important sources of information about a crime. Currently, around the world, sexual offenses have increased, and among them are those in which the criminals use various detergents to remove traces of their crime. A feature of modern synthetic detergents is the presence of biological additives - enzymes. Enzymes purposefully destroy stains of biological origin. To study the nature and extent of the impact of modern washing powders on saliva stains on the physical evidence, specially prepared test specimens of different types of tissues to which saliva was applied have been examined. Materials and Methods: Washing machines of famous manufacturers of household appliances have been used with different production characteristics and advertised brands of washing powder for test washing. Over 3,500 experimental samples were tested. After washing, the traces of saliva were identified using modern research methods of forensic medicine. Results: The influence was tested and the dependence of the use of different washing programs, types of washing machines and washing powders in the process of establishing saliva trace and identify of the stains on the physical evidence while washing was revealed. The results of experimental and practical expert studies have shown that in most cases it is not possible to draw the conclusions in the identification of saliva traces on physical evidence after washing. This is a consequence of the effect of biological additives and other additional factors on traces of saliva during washing. Conclusions: On the basis of the results of the study, the feasibility of saliva traces of the stains on physical evidence after washing is established. The use of modern molecular genetic methods makes it possible to partially solve the problems arising in the study of unlaundered evidence. Additional study of physical evidence after washing facilitates detection and investigation of sexual offenses against women and children.

Keywords: saliva research, modern synthetic detergents, laundry detergents, forensic medicine

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Authors: E. Ramprasath, P. Manojkumar, P. Veena

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DC motors have been widely used in the past centuries which are proudly known as the workhorse of industrial systems until the invention of the AC induction motors which makes a huge revolution in industries. Since then, the use of DC machines have been decreased due to enormous factors such as reliability, robustness and complexity but it lost its fame due to the losses. A new methodology is proposed to construct a DC motor through the simulation in LabVIEW to get an idea about its real time performances, if a change in parameter might have bigger improvement in losses and reliability.

Keywords: analysis, characteristics, direct current motor, LabVIEW software, simulation

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB/Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind energy, PWM inverter, modeling

Procedia PDF Downloads 300

Authors: Gabriela-Andreea Despescu, Mădălina-Elena Mavrodin, Gheorghe Lăzăroiu, Florin Adrian Grădinaru

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The purpose of this paper is to contribute to the enhancement of a hydroelectric plant protection by coordinating protection measures and existing security and introducing new measures under a risk management process. Also, the plan identifies key critical elements of a hydroelectric plant, from its level vulnerabilities and threats it is subjected to in order to achieve the necessary protection measures to reduce the level of risk.

Keywords: critical infrastructure, risk analysis, critical infrastructure protection, vulnerability, risk management, turbine, impact analysis

Procedia PDF Downloads 529

Authors: Fikremariam Beyene, Getachew Bekele

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Ethiopia is currently on the move with various projects to raise the amount of power generated in the country. The progress observed in recent years indicates this fact clearly and indisputably. The rural electrification program, the modernization of the power transmission system, the development of wind farm is some of the main accomplishments worth mentioning. As it is well known, currently, wind power is globally embraced as one of the most important sources of energy mainly for its environmentally friendly characteristics, and also that once it is installed, it is a source available free of charge. However, integration of wind power plant with an existing network has many challenges that need to be given serious attention. In Ethiopia, a number of wind farms are either installed or are under construction. A series of wind farm is planned to be installed in the near future. Ashegoda Wind farm (13.2°, 39.6°), which is the subject of this study, is the first large scale wind farm under construction with the capacity of 120 MW. The first phase of 120 MW (30 MW) has been completed and is expected to be connected to the grid soon. This paper is concerned with the investigation of the wind farm interaction with the national grid under transient operating condition. The main concern is the fault ride through (FRT) capability of the system when the grid voltage drops to exceedingly low values because of short circuit fault and also the active and reactive power behavior of wind turbines after the fault is cleared. On the wind turbine side, a detailed dynamic modelling of variable speed wind turbine of a 1 MW capacity running with a squirrel cage induction generator and full-scale power electronics converters is done and analyzed using simulation software DIgSILENT PowerFactory. On the Ethiopian electric power corporation side, after having collected sufficient data for the analysis, the grid network is modeled. In the model, a fault ride-through (FRT) capability of the plant is studied by applying 3-phase short circuit on the grid terminal near the wind farm. The results show that the Ashegoda wind farm can ride from voltage deep within a short time and the active and reactive power performance of the wind farm is also promising.

Keywords: squirrel cage induction generator, active and reactive power, DIgSILENT PowerFactory, fault ride-through capability, 3-phase short circuit

Procedia PDF Downloads 148

Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

Procedia PDF Downloads 97

Authors: Haroon Jan Khan, Xian-Feng Xu, Syed Nasir Shah, Anooshay Niazi

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CNC machines are not only used on a large scale but also now become a prominent necessity among households and smaller businesses. Printed Circuit Boards manufactured by the chemical process are not only risky and unsafe but also expensive and time-consuming. A 3-axis precise CNC machine has been developed, which not only fabricates PCB but has also been used for multi-tasks just by changing the materials used and tools, making it versatile. The advanced CNC machine takes data from CAM software. The TB-6560 controller is used in the CNC machine to adjust variation in the X, Y, and Z axes. The advanced machine is efficient in automatic drilling, engraving, and cutting.

Keywords: CNC, G-code, CAD, CAM, Proteus, FLATCAM, Easel

Procedia PDF Downloads 141

Authors: Matheus Nunes, Rafael Mendes, Taygoara Felamingo Oliveira, Antonio Brasil Junior

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Wind tunnel experiments of horizontal axis propeller hydrokinetic turbines model were carried out, in order to determine the performance behavior for different configurations and operational range. The present experiments introduce the use of two different geometries of rear diffusers to enhance the performance of the free flow machine. The present paper reports an increase of the power coefficient about 50%-80%. It represents an important feature that has to be taken into account in the design of this kind of machine.

Keywords: diffuser-enhanced turbines, hydrokinetic turbine, wind tunnel experiments, micro hydro

Procedia PDF Downloads 253

Authors: C. Fúnez Guerra, B. Nieto Calderón, M. Jaén Caparrós, L. Reyes-Bozo, A. Godoy-Faúndez, E. Vyhmeister

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The global energy system is experiencing a change of scenery. Unstable energy markets, an increasing focus on climate change and its sustainable development is forcing businesses to pursue new solutions in order to ensure future economic growth. This has led to the interest in using hydrogen as an energy carrier in transportation and industrial applications. As an energy carrier, hydrogen is accessible and holds a high gravimetric energy density. Abundant in hydrocarbons, hydrogen can play an important role in the shift towards low-emission fossil value chains. By combining hydrogen production by natural gas reforming with carbon capture and storage, the overall CO2 emissions are significantly reduced. In addition, the flexibility of hydrogen as an energy storage makes it applicable as a stabilizer in the renewable energy mix. The recent development in hydrogen fuel cells is also raising the expectations for a hydrogen powered transportation sector. Hydrogen value chains exist to a large extent in the industry today. The global hydrogen consumption was approximately 50 million tonnes (7.2 EJ) in 2013, where refineries, ammonia, methanol production and metal processing were main consumers. Natural gas reforming produced 48% of this hydrogen, but without carbon capture and storage (CCS). The total emissions from the production reached 500 million tonnes of CO2, hence alternative production methods with lower emissions will be necessary in future value chains. Hydrogen from electrolysis is used for a wide range of industrial chemical reactions for many years. Possibly, the earliest use was for the production of ammonia-based fertilisers by Norsk Hydro, with a test reactor set up in Notodden, Norway, in 1927. This application also claims one of the world’s largest electrolyser installations, at Sable Chemicals in Zimbabwe. Its array of 28 electrolysers consumes 80 MW per hour, producing around 21,000 Nm3/h of hydrogen. These electrolysers can compete if cheap sources of electricity are available and natural gas for steam reforming is relatively expensive. Because electrolysis of water produces oxygen as a by-product, a system of Autothermal Reforming (ATR) utilizing this oxygen has been analyzed. Replacing the air separation unit with electrolysers produces the required amount of oxygen to the ATR as well as additional hydrogen. The aim of this paper is to evaluate the technical and economic potential of large-scale production of hydrogen for oil refining industry. Sensitivity analysis of parameters such as investment costs, plant operating hours, electricity price and sale price of hydrogen and oxygen are performed.

Keywords: autothermal reforming, electrolyser, hydrogen, natural gas, steam methane reforming

Procedia PDF Downloads 194

Authors: Nebras Gharbi, Itebeddine Ghorbel

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In the latest years and with the advancements of the multicore computing world, the constraint programming community tried to benefit from the capacity of new machines and make the best use of them through several parallel schemes for constraint solving. In this paper, we propose a survey of the different proposed approaches to solve Constraint Satisfaction Problems using parallel architectures. These approaches use in a different way a parallel architecture: the problem itself could be solved differently by several solvers or could be split over solvers.

Keywords: constraint programming, parallel programming, constraint satisfaction problem, speed-up

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Authors: Alan C. Lin, Tzu-Kuan Lin, Tsong Der Lin

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This paper proposes a new method to find the equations of transformation matrix for the rotation angles of the two rotational axes and the coordinates of the three linear axes of an orthogonal multi-axis milling machine. This approach provides intuitive physical meanings for rotation angles of multi-axis machines, which can be used to evaluate the accuracy of the conversion from CL data to NC data.

Keywords: CAM, multi-axis milling machining, transformation matrix, rotation angles

Procedia PDF Downloads 462

Authors: Emilio A. Berny-Brandt, Sonia E. Ruiz

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Steel tubular towers serving as support structures for large wind turbines are subject to several hundred million stress cycles arising from the turbulent nature of the wind. This causes high-cycle fatigue which can govern tower design. The practice of maintaining the support structure after wind turbines reach its typical 20-year design life have become common, but without quantifying the changes in the reliability on the tower. There are several studies on this topic, but most of them are based on the S-N curve approach using the Miner’s rule damage summation method, the de-facto standard in the wind industry. However, the qualitative nature of Miner’s method makes desirable the use of fracture mechanics to measure the effects of fatigue in the capacity curve of the structure, which is important in order to evaluate the integrity and reliability of these towers. Temporal and spatially varying wind speed time histories are simulated based on power spectral density and coherence functions. Simulations are then applied to a SAP2000 finite element model and step-by-step analysis is used to obtain the stress time histories for a range of representative wind speeds expected during service conditions of the wind turbine. Rainflow method is then used to obtain cycle and stress range information of each of these time histories and a statistical analysis is performed to obtain the distribution parameters of each variable. Monte Carlo simulation is used here to evaluate crack growth over time in the tower base using the Paris-Erdogan equation. A nonlinear static pushover analysis to assess the capacity curve of the structure after a number of years is performed. The capacity curves are then used to evaluate the changes in reliability of a steel tower located in Oaxaca, Mexico, where wind energy facilities are expected to grow in the near future. Results show that fatigue on the tower base can have significant effects on the structural capacity of the wind turbine, especially after the 20-year design life when the crack growth curve starts behaving exponentially.

Keywords: crack growth, fatigue, Monte Carlo simulation, structural reliability, wind turbines

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Authors: R. N. Pateriya, T. K. Bhattacharya

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In India, rice-wheat cropping system occupies the major area and contributes about 40% of the country’s total food grain production. It is necessary that production of rice and wheat must keep pace with growing population. However, various factors such as degradation in natural resources, shift in cropping pattern, energy constraints etc. are causing reduction in the productivity of these crops. Seedbed for rice after wheat is difficult to prepare due to presence of straw and stubbles, and require excessive tillage operations to bring optimum tilth. In addition, delayed sowing and transplanting of rice is mainly due to poor crop residue management, multiplicity of tillage operations and non-availability of the power source. With increasing concern for fuel conservation and energy management, farmers might wish to estimate the best cultivation system for more productivity. The widest spread method of tilling land is ploughing with mould board plough. However, with the mould board plough upper layer of soil is neither always loosened at the desired extent nor proper mixing of different layers are achieved. Therefore, additional operations carried out to improve tilth. The farmers are becoming increasingly aware of the need for minimum tillage by minimizing the use of machines. Soil management can be achieved by using the combined active-passive tillage machines. A study was therefore, undertaken in wheat-harvested field to study the impact of conventional and modified tillage practices on paddy crop cultivation. Tillage treatments with tractor as a power source were selected during the experiment. The selected level of tillage treatments of tractor machinery management were (T1:- Direct Sowing of Rice), (T2:- 2 to 3 harrowing and no Puddling with manual transplanting), (T3:- 2 to 3 harrowing and Puddling with paddy harrow with manual transplanting), (T4:- 2 to 3 harrowing and Puddling with Rotavator with manual transplanting). The maximum output was obtained with treatment T1 (7.85 t/ha)) followed by T4 (6.4 t/ha), T3 (6.25 t/ha) and T2 (6.0 t/ha)) respectively.

Keywords: crop residues, cropping system, minimum tillage, yield

Procedia PDF Downloads 196

Authors: Iyad Al-Attar

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Air filters installed in HVAC equipment and gas turbine for power generation confront several atmospheric contaminants with various concentrations while operating in different environments (tropical, coastal, hot). This leads to engine performance degradation, as contaminants are capable of deteriorating components and fouling compressor assembly. Compressor fouling is responsible for 70 to 85% of gas turbine performance degradation leading to reduction in power output and availability and an increase in the heat rate and fuel consumption. Therefore, filter design must take into account face velocities, pleat count and its corresponding surface area; to verify filter performance characteristics (Efficiency and Pressure Drop). The experimental work undertaken in the current study examined two groups of four filters with different pleating densities were investigated for the initial pressure drop response and fractional efficiencies. The pleating densities used for this study is 28, 30, 32 and 34 pleats per 100mm for each pleated panel and measured for ten different flow rates ranging from 500 to 5000 m3/h with increment of 500m3/h. This experimental work of the current work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase in face velocity and pleat density. The reasons that led to surface area losses of filtration media are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. It is evident from entire array of experiments that as the particle size increases, the efficiency decreases until the MPPS is reached. Beyond the MPPS, the efficiency increases with increase in particle size. The MPPS shifts to a smaller particle size as the face velocity increases, while the pleating density and orientation did not have a pronounced effect on the MPPS. Throughout the study, an optimal pleat count which satisfies initial pressure drop and efficiency requirements may not have necessarily existed. The work has also suggested that a valid comparison of the pleat densities should be based on the effective surface area that participates in the filtration action and not the total surface area the pleat density provides.

Keywords: air filters, fractional efficiency, gas cleaning, glass fibre, HEPA filter, permeability, pressure drop

Procedia PDF Downloads 126

Authors: Till Gramberg, Erwin Gross, Christoph Birenbaum

Abstract:

This paper presents the approach of the Easy2IoT research project. Easy2IoT aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. It focuses on the development of physical hardware and software to easily capture machine activities from on a sawing machine, benefiting various stakeholders in the SME value chain, including machine operators, tool manufacturers and service providers. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements and potential solutions for smart services are derived. The focus is on providing actionable recommendations, competencies and easy integration through no-/low-code applications to facilitate implementation and connectivity within production networks. At the core of the project is a novel, non-invasive measurement and analysis system that can be easily deployed and made IIoT-ready. This system collects machine data without interfering with the machines themselves. It does this by non-invasively measuring the tension on a sawing machine. The collected data is then connected and analyzed using artificial intelligence (AI) to provide smart services through a platform-based application. Three Smart Services are being developed within Easy2IoT to provide immediate benefits to users: Wear part and product material condition monitoring and predictive maintenance for sawing processes. The non-invasive measurement system enables the monitoring of tool wear, such as saw blades, and the quality of consumables and materials. Service providers and machine operators can use this data to optimize maintenance and reduce downtime and material waste. Optimize Overall Equipment Effectiveness (OEE) by monitoring machine activity. The non-invasive system tracks machining times, setup times and downtime to identify opportunities for OEE improvement and reduce unplanned machine downtime. Estimate CO2 emissions for connected machines. CO2 emissions are calculated for the entire life of the machine and for individual production steps based on captured power consumption data. This information supports energy management and product development decisions. The key to Easy2IoT is its modular and easy-to-use design. The non-invasive measurement system is universally applicable and does not require specialized knowledge to install. The platform application allows easy integration of various smart services and provides a self-service portal for activation and management. Innovative business models will also be developed to promote the sustainable use of the collected machine activity data. The project addresses the digitalization gap between large enterprises and SME. Easy2IoT provides SME with a concrete toolkit for IIoT adoption, facilitating the digital transformation of smaller companies, e.g. through retrofitting of existing machines.

Keywords: smart services, IIoT, IIoT-platform, industrie 4.0, big data

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Authors: Zeinab Syed Abdel Rehim

Abstract:

Water shortage is considered as one of the huge problems the world encounter now. Water desalination is considered as one of the more suitable methods governments can use to substitute the increased need for potable water. The humidification-dehumidification process for water desalination is viewed as a promising technique for small capacity production plants. The process has several attraction features which include the use of sustainable energy sources, low technology, and low-temperature dehumidification. A pilot experimental set-up plant was constructed with the conventional HVAC components such as air blower that supplies air to an air duct inside which air preheater, steam injector and cooling coil of a small refrigeration unit are placed. The present work evaluates the characteristics of humidification-dehumidification process for water desalination as a function of air flow rate, total power input and air inlet temperature in order to study the optimum conditions required to produce distilled water.

Keywords: condensation, dehumidification, evaporation, humidification, water desalination

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Authors: T. A. Faria, C. C. Toniolo, L. F. Ribeiro

Abstract:

In order to satisfy the costumer’s needs, many sectors of industry and services has been spending major effort to make its processes more efficient. Facing a situation, when its production cannot cover the demand, the traditional way to achieve the production required involves, mostly, adding shifts, workforce, or even more machines. This paper narrates how lean manufacturing supported a dramatic increase of productivity at a rail welding plant in Brazil in order to meet the demand for the next years.

Keywords: productivity, lean manufacturing, rail welding, value stream mapping

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Authors: Francis C. Emejeamara, Alison S. Tomlin, James Gooding

Abstract:

Due to the highly turbulent nature of urban air flows, and by virtue of the fact that turbines are likely to be located within the roughness sublayer of the urban boundary layer, proposed urban wind installations are faced with major challenges compared to rural installations. The challenge of operating within turbulent winds can however, be counteracted by the development of suitable gust tracking solutions. In order to assess the cost effectiveness of such controls, a detailed understanding of the urban wind resource, including its turbulent characteristics, is required. Estimating the ambient turbulence and total kinetic energy available at different control response times is essential in evaluating the potential performance of wind systems within the urban environment should effective control solutions be employed. However, high resolution wind measurements within the urban roughness sub-layer are uncommon, and detailed CFD modelling approaches are too computationally expensive to apply routinely on a city wide scale. This paper therefore presents an alternative semi-empirical methodology for estimating the excess energy content (EEC) present in the complex and gusty urban wind. An analytical methodology for predicting the total wind energy available at a potential turbine site is proposed by assessing the relationship between turbulence intensities and EEC, for different control response times. The semi-empirical model is then incorporated with an analytical methodology that was initially developed to predict mean wind speeds at various heights within the built environment based on detailed mapping of its aerodynamic characteristics. Based on the current methodology, additional estimates of turbulence intensities and EEC allow a more complete assessment of the available wind resource. The methodology is applied to 4 UK cities with results showing the potential of mapping turbulence intensities and the total wind energy available at different heights within each city. Considering the effect of ambient turbulence and choice of wind system, the wind resource over neighbourhood regions (of 250 m uniform resolution) and building rooftops within the 4 cities were assessed with results highlighting the promise of mapping potential turbine sites within each city.

Keywords: excess energy content, small-scale wind, turbulence intensity, urban wind energy, wind resource assessment

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Authors: Irfan Anjum Manarvi, Zahid Ali kaimkhani

Abstract:

Predicting location of the fracture in human bones has been a keen area of research for the past few decades. A variety of tests for hardness, deformation, and strain field measurement have been conducted in the past; but considered insufficient due to various limitations. Researchers, therefore, have proposed further studies due to inaccuracies in measurement methods, testing machines, and experimental errors. Advancement and availability of hardware, measuring instrumentation, and testing machines can now provide remedies to these limitations. The human foot is a critical part of the body exposed to various forces throughout its life. A number of products are developed for using it for protection and care, which many times do not provide sufficient protection and may itself become a source of stress due to non-consideration of the delicacy of bones in the feet. A continuous strain or overloading on feet may occur resulting to discomfort and even fracture. Mechanical properties of Tarsals, Metatarsals, and phalanges are, therefore, the primary area of consideration for all such design applications. Hardness is one of the mechanical properties which are considered very important to establish the mechanical resistance behavior of a material against applied loads. Past researchers have worked in the areas of investigating mechanical properties of these bones. However, their results were based on a limited number of experiments and taking average values of hardness due to either limitation of samples or testing instruments. Therefore, they proposed further studies in this area. The present research has been carried out to develop a hardness map of the human foot by measuring micro hardness at various locations of these bones. Results are compiled in the form of distance from a reference point on a bone and the hardness values for each surface. The number of test results is far more than previous studies and are spread over a typical bone to give a complete hardness map of these bones. These results could also be used to establish other properties such as stress and strain distribution in the bones. Also, industrial engineers could use it for design and development of various accessories for human feet health care and comfort and further research in the same areas.

Keywords: tarsals, metatarsals, phalanges, hardness testing, biomechanics of human foot

Procedia PDF Downloads 410

Authors: Alex Atanaw Alebachew

Abstract:

The outcomes of a numerical research study conducted using the PLAXIS software to analyze surface settlements and moments generated in tunnel linings. The investigation focuses on both circular and rectangular twin tunnels. The study suggests that rectangular tunnels, although considered unconventional in modern tunneling practices, may be a viable option for shallow-depth tunneling in weak ground. The recommendation for engineers in the tunneling industry is to consider the use of rectangular tunnel boring machines (TBMs) based on the findings of this analysis. The research emphasizes the importance of evaluating various tunneling methods to optimize performance and address specific challenges in different ground conditions. These findings provide valuable insights into the behavior of rectangular tunnels compared to circular tunnels, emphasizing factors such as burial depth, relative positioning, tunnel size, and critical distance that influence surface settlements and bending moments. This research explores the feasibility of utilizing rectangular Tunnel Boring Machines (TBMs) as an alternative to conventional circular TBMs. The research findings indicate that rectangular tunnels exhibit slightly lower settlement than circular tunnels at shallow depths, especially in a narrower range directly above the twin tunnels. This difference could be attributed to maintaining a consistent tunnel-lining thickness across all depths. In deeper tunnel scenarios, circular tunnels experience less settlement compared to rectangular tunnels. Additionally, parallel rectangular tunnels settle more gradually than piggyback configurations, while piggyback tunnels show increased moments in the tunnel built second at the same level. Both settlement and moment coefficients increase with the diameter of twin tunnels, irrespective of their shape. The critical distance for both circular and rectangular tunnels is around 2.5 times the tunnel diameter, and distances closer than this result in a notable increase in moments. Rectangular tunnels spaced closer than 5 times the diameter led to higher settlement, and circular tunnels spaced closer than 2.5 to 3 times the diameter experience increased settlement as well.

Keywords: alternative, rectangular, tunnel, twin bored circular, weak ground

Procedia PDF Downloads 41