Search results for: steam turbine machines
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1488

Search results for: steam turbine machines

408 Hydroinformatics of Smart Cities: Real-Time Water Quality Prediction Model Using a Hybrid Approach

Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

Abstract:

Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 163
407 Epileptic Seizure Onset Detection via Energy and Neural Synchronization Decision Fusion

Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

Abstract:

This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

Procedia PDF Downloads 458
406 Instrumentation for Engine Start Cycle Characterization at Cold Weather High Altitude Condition

Authors: Amit Kumar Gupta, Rohit Vashistha, G. P. Ravishankar, Mahesh P. Padwale

Abstract:

A cold soaked gas turbine engine have known starting problems in high altitude and low temperature conditions. The high altitude results in lower ambient temperature, pressure, and density. Soaking at low temperature leads to higher oil viscosity, increasing the engine starter system torque requirement. Also, low temperature soaks results in a cold compressor rotor and casing. Since the thermal mass of rotor is higher than casing, casing expands faster, thereby, increasing the blade-casing tip clearance. The low pressure flow over the compressor blade coupled with the secondary flow through the compressor tip clearance during start result in stall inception. The present study discusses engine instrumentation required for capturing the stall inception event. The engine fan exit and combustion chamber were instrumented with dynamic pressure probes to capture the pressure characteristic and clamp-on current meter on primary igniter cable to capture ignition event during start cycle. The experiment was carried out at 10500 Ft. pressure altitude and -15°C ambient temperature. The high pressure compressor stall events were recorded during the starts.

Keywords: compressor inlet, dynamic pressure probe, engine start cycle, flight test instrumentation

Procedia PDF Downloads 303
405 Mage Fusion Based Eye Tumor Detection

Authors: Ahmed Ashit

Abstract:

Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

Procedia PDF Downloads 341
404 Feasibility of BioMass Power Generation in Punjab Province of Pakistan

Authors: Muhammad Ghaffar Doggar, Farah

Abstract:

The primary objective of this feasibility study is to conduct a techno-financial assessment for installation of biomass based power plant in Faisalabad division. The study involves identification of best site for power plant followed by an assessment of biomass resource potential in the area and propose power plant of suitable size. The study also entailed comprehensive supply chain analysis to determine biomass fuel pricing, transportation and storage. Further technical and financial analyses have been done for selection of appropriate technology for the power plant and its financial viability, respectively. The assessment of biomass resources and the subsequent technical analysis revealed that 20 MW biomass power plant could be implemented at one of the locations near Faisalabad city i.e. AARI Site, Near Chak Jhumra district Faisalabad, Punjab province. Three options for steam pressure; namely, 70 bar, 90 bar and 100 bar boilers have been considered. Using international experience and prices on power plant technology and local prices on locally available equipment, the study concludes biomass fuel price of around 50 US dollars (USD) per ton when delivered to power plant site. The electricity prices used for feasibility calculations were 0.13 USD per KWh for electricity from a locally financed project and 0.11 USD per KWh for internationally financed power plant. For local financing the most viable choice is the 70 bar solution and with international financing, the most feasible solution is using a 90 bar boiler. Between the two options, the internationally financed 90 bar boiler setup gives better financial results than the locally financed 70 bar boiler project. It has been concluded that 20 MW with 90 bar power plant and internationally financed would have an equity IRR of 23% and a payback period of 7 years. This will be a cheap option for installation of power plants.

Keywords: AARI, Ayub agriculture research institute, biomass - crops residue, KWh - electricity Units, MG - Muhammad Ghaffar

Procedia PDF Downloads 322
403 Analysis and Modeling of Vibratory Signals Based on LMD for Rolling Bearing Fault Diagnosis

Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

Abstract:

The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally non-stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. the results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, local mean decomposition, rolling element bearing, vibration analysis

Procedia PDF Downloads 392
402 Application of Chemical Tests for the Inhibition of Scaling From Hamma Hard Waters

Authors: Samira Ghizellaoui, Manel Boumagoura

Abstract:

Calcium carbonate precipitation is a widespread problem, especially in hard water systems. The main water supply that supplies the city of Constantine with drinking water is underground water called Hamma water. This water has a very high hardness of around 590 mg/L CaCO₃. This leads to the formation of scale, consisting mainly of calcium carbonate, which can be responsible for the clogging of valves and the deterioration of equipment (water heaters, washing machines and encrustations in the pipes). Plant extracts used as scale inhibitors have attracted the attention of several researchers. In recent years, green inhibitors have attracted great interest because they are biodegradable, non-toxic and do not affect the environment. The aim of our work is to evaluate the effectiveness of a chemical antiscale treatment in the presence of three green inhibitors: gallicacid; quercetin; alginate, and three mixtures: (gallic acid-quercetin); (quercetin-alginate); (gallic acid-alginate). The results show that the inhibitory effect is manifested from an addition of 1mg/L of gallic acid, 10 mg/L of quercetin, 0.2 mg/L of alginate, 0.4mg/L of (gallic acid-quercetin), 2mg/L of (quercetin-alginate) and 0.4 mg/L of (gallic acid-alginate). On the other hand, 100 mg/L (Drinking water standard) of Ca2+is reached for partial softening at 4 mg/L of gallic acid, 40 mg/L of quercetin, 0.6mg/L of alginate, 4mg/L of (gallic acid-quercetin), 10mg/L of (quercetin-alginate) and 1.6 mg/L of (gallic acid-alginate).

Keywords: water, scaling, calcium carbonate, green inhibitor

Procedia PDF Downloads 52
401 Sustainable Use of Agricultural Waste to Enhance Food Security and Conserve the Environment

Authors: M. M. Tawfik, Ezzat M. Abd El Lateef, B. B. Mekki, Amany A. Bahr, Magda H. Mohamed, Gehan S. Bakhoom

Abstract:

The rapid increase in the world’s population coupled by decrease the arable land per capita has resulted into an increased demand for food which has in turn led to the production of large amounts of agricultural wastes, both at the farmer, municipality and city levels. Agricultural wastes can be a valuable resource for improving food security. Unfortunately, agricultural wastes are likely to cause pollution to the environment or even harm to human health. This calls for increased public awareness on the benefits and potential hazards of agricultural wastes, especially in developing countries. Agricultural wastes (residual stalks, straw, leaves, roots, husks, shells etcetera) and animal waste (manures) are widely available, renewable and virtually free, hence they can be an important resource. They can be converted into heat, steam, charcoal, methanol, ethanol, bio diesel as well as raw materials (animal feed, composting, energy and biogas construction etcetera). agricultural wastes are likely to cause pollution to the environment or even harm to human health, if it is not used in a sustainable manner. Organic wastes could be considered an important source of biofertilizer for enhancing food security in the small holder farming communities that would not afford use of expensive inorganic fertilizers. Moreover, these organic wastes contain high levels of nitrogen, phosphorus, potassium, and organic matter important for improving nutrient status of soils in urban agriculture. Organic compost leading to improved crop yields and its nutritional values as compared with inorganic fertilization. This paper briefly reviews how agricultural wastes can be used to enhance food security and conserve the environment.

Keywords: agricultural waste, organic compost, environment, valuable resources

Procedia PDF Downloads 502
400 Auto-Tuning of CNC Parameters According to the Machining Mode Selection

Authors: Jenq-Shyong Chen, Ben-Fong Yu

Abstract:

CNC(computer numerical control) machining centers have been widely used for machining different metal components for various industries. For a specific CNC machine, its everyday job is assigned to cut different products with quite different attributes such as material type, workpiece weight, geometry, tooling, and cutting conditions. Theoretically, the dynamic characteristics of the CNC machine should be properly tuned match each machining job in order to get the optimal machining performance. However, most of the CNC machines are set with only a standard set of CNC parameters. In this study, we have developed an auto-tuning system which can automatically change the CNC parameters and in hence change the machine dynamic characteristics according to the selection of machining modes which are set by the mixed combination of three machine performance indexes: the HO (high surface quality) index, HP (high precision) index and HS (high speed) index. The acceleration, jerk, corner error tolerance, oscillation and dynamic bandwidth of machine’s feed axes have been changed according to the selection of the machine performance indexes. The proposed auto-tuning system of the CNC parameters has been implemented on a PC-based CNC controller and a three-axis machining center. The measured experimental result have shown the promising of our proposed auto-tuning system.

Keywords: auto-tuning, CNC parameters, machining mode, high speed, high accuracy, high surface quality

Procedia PDF Downloads 366
399 Optimization Techniques of Doubly-Fed Induction Generator Controller Design for Reliability Enhancement of Wind Energy Conversion Systems

Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

Abstract:

The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

Procedia PDF Downloads 80
398 A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

Abstract:

All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

Procedia PDF Downloads 220
397 Theoretical Performance of a Sustainable Clean Energy On-Site Generation Device to Convert Consumers into Producers and Its Possible Impact on Electrical National Grids

Authors: Eudes Vera

Abstract:

In this paper, a theoretical evaluation is carried out of the performance of a forthcoming fuel-less clean energy generation device, the Air Motor. The underlying physical principles that support this technology are succinctly described. Examples of the machine and theoretical values of input and output powers are also given. In addition, its main features like portability, on-site energy generation and delivery, miniaturization of generation plants, efficiency, and scaling down of the whole electric infrastructure are discussed. The main component of the Air Motor, the Thermal Air Turbine, generates useful power by converting in mechanical energy part of the thermal energy contained in a fan-produced airflow while leaving intact its kinetic energy. Due to this fact an air motor can contain a long succession of identical air turbines and the total power generated out of a single airflow can be very large, as well as its mechanical efficiency. It is found using the corresponding formulae that the mechanical efficiency of this device can be much greater than 100%, while its thermal efficiency is always less than 100%. On account of its multiple advantages, the Air Motor seems to be the perfect device to convert energy consumers into energy producers worldwide. If so, it would appear that current national electrical grids would no longer be necessary, because it does not seem practical or economical to bring the energy from far-away distances while it can be generated and consumed locally at the consumer’s premises using just the thermal energy contained in the ambient air.

Keywords: electrical grid, clean energy, renewable energy, in situ generation and delivery, generation efficiency

Procedia PDF Downloads 165
396 Effect of Variety and Fibre Type on Functional and organoleptic Properties of Plantain Flour Intended for Food "Fufu"

Authors: C. C. Okafor

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The effect of different varieties of plantain (Horn, false horn and French) and fibre types (soy bean residue, cassava sievette and rice bran) on functional and organoleptic properties of plantain-based flour was assessed. Horn, false horn french were processed by washing, peeling with knife, slicing into 3mm thickness and steam blanched at 80℃ for 5minutes, oven dried at 65℃ for 48 hours and milled into flours with attrition mill, sieved with 60 mesh sieve, separately. Fibre sources were processed, milled and fractionated into 60, 40 & 20 mesh sizes. Both flours were blended as 80:20, 70:30 and 60:40. Results obtained indicated that water absorption capacity is highest (2.68) in French plantain variety irrespective of the fibre type used. And in all variety tested the swelling capacity is highest (2.93) when the plantain flour is blended with soy residue (SR) and lowest (1.25) when blended with rice brain (RB). The results show that there is significant variety and fibre type interaction effect at (P < : 0.05). Again the results showed that texture mold ability and overall acceptability were best (7.00) when soy residue was used where as addition of rice bran into plantain flour resulted in fufu with poor texture. This trend was observed in all the verities of plantain tested and in all of the particle size of flour. Using cassava serviette also yield fufu similar to that produced with soy residue in all the parameter tested (mold ability, texture and overall acceptability. Generally, plantain flours from french and false horn yielded better quality fufu in terms of texture mold ability, overall acceptability, irrespective of the fibre type used.

Keywords: functional, organoleptic, particle size, sieve mesh, variety

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395 Optimal Energy Management and Environmental Index Optimization of a Microgrid Operating by Renewable and Sustainable Generation Systems

Authors: Nabil Mezhoud

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The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently.

Keywords: renewable energy sources, energy management, distributed generator, micro-grids, firefly algorithm

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394 Strategies and Difficulties to Integrate Renewable Energy into Recreational Open Spaces

Authors: A. Tereci, M. Atmaca

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Recreational spaces designed or build for refreshment of the users through natural riches and/or activities. Those places contribute to the quality of city life by providing relaxation point for citizens and maintaining the environmental equilibrium. The elements which constitute the recreational areas also promote long-term environmental and social sustainability of cities. Preservation and creation of the recreation open spaces are important for water and air quality, natural habitat and also social communication. On this point, it is also a good area for promoting the renewable energy sources through comprehension of the sustainable development which is possible only with using nature and technic together. Energy production is mainly technical issue, and architectural design of these elements to the site always ignores or avoid. The main problems for integration of renewable energy sources are the system suitability, security, durability, and resiliency. In this paper, one of the city recreational open spaces in Konya, Turkey was evaluated for integration of possible renewable energy sources. It shows that the solar energy potential is high and PV integration is the best option. On the other hand wind, energy power and area is not suitable for wind turbine, so wind belts were decided to integrate on the design. According to recreational activities, the chosen elements was designed for site application, and their performance was calculated. According to possible installation on the furniture, there is 50 MWh/a electricity production capacity.

Keywords: energy, integrated design, recreational space, renewables

Procedia PDF Downloads 142
393 Resource-Constrained Assembly Line Balancing Problems with Multi-Manned Workstations

Authors: Yin-Yann Chen, Jia-Ying Li

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Assembly line balancing problems can be categorized into one-sided, two-sided, and multi-manned ones by using the number of operators deployed at workstations. This study explores the balancing problem of a resource-constrained assembly line with multi-manned workstations. Resources include machines or tools in assembly lines such as jigs, fixtures, and hand tools. A mathematical programming model was developed to carry out decision-making and planning in order to minimize the numbers of workstations, resources, and operators for achieving optimal production efficiency. To improve the solution-finding efficiency, a genetic algorithm (GA) and a simulated annealing algorithm (SA) were designed and developed in this study to be combined with a practical case in car making. Results of the GA/SA and mathematics programming were compared to verify their validity. Finally, analysis and comparison were conducted in terms of the target values, production efficiency, and deployment combinations provided by the algorithms in order for the results of this study to provide references for decision-making on production deployment.

Keywords: heuristic algorithms, line balancing, multi-manned workstation, resource-constrained

Procedia PDF Downloads 189
392 3D Steady and Transient Centrifugal Pump Flow within Ansys CFX and OpenFOAM

Authors: Clement Leroy, Guillaume Boitel

Abstract:

This paper presents a comparative benchmarking review of a steady and transient three-dimensional (3D) flow computations in centrifugal pump using commercial (AnsysCFX) and open source (OpenFOAM) computational fluid dynamics (CFD) software. In centrifugal rotor-dynamic pump, the fluid enters in the impeller along to the rotating axis to be accelerated in order to increase the pressure, flowing radially outward into another stage, vaned diffuser or volute casing, from where it finally exits into a downstream pipe. Simulations are carried out at the best efficiency point (BEP) and part load, for single-phase flow with several turbulence models. The results are compared with overall performance report from experimental data. The use of CFD technology in industry is still limited by the high computational costs, and even more by the high cost of commercial CFD software and high-performance computing (HPC) licenses. The main objectives of the present study are to define OpenFOAM methodology for high-quality 3D steady and transient turbomachinery CFD simulation to conduct a thorough time-accurate performance analysis. On the other hand a detailed comparisons between computational methods, features on latest Ansys release 18 and OpenFOAM is investigated to assess the accuracy and industrial applications of those solvers. Finally an automated connected workflow (IoT) for turbine blade applications is presented.

Keywords: benchmarking, CFX, internet of things, openFOAM, time-accurate, turbomachinery

Procedia PDF Downloads 189
391 Analysis of Noodle Production Process at Yan Hu Food Manufacturing: Basis for Production Improvement

Authors: Rhadinia Tayag-Relanes, Felina C. Young

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This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: production, continuous improvement, process, operations, PDCA

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390 Non-Reacting Numerical Simulation of Axisymmetric Trapped Vortex Combustor

Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

Abstract:

This paper will focus on the suitability of a trapped vortex combustor as a candidate for gas turbine combustor objectives to minimize pressure drop across the combustor and investigate aerodynamic performance. Non-reacting simulation of axisymmetric cavity trapped vortex combustors were simulated to investigate the pressure drop for various cavity aspect ratios of 0.3, 0.6, and 1 and for air mass flow rates of 14 m/s, 28 m/s, and 42 m/s. A numerical study of an axisymmetric trapped vortex combustor was carried out by using two-dimensional and three-dimensional computational domains. A comparison study was conducted between Reynolds Averaged Navier Stokes (RANS) k-ε Realizable with enhanced wall treatment and RANS k-ω Shear Stress Transport (SST) models to find the most suitable turbulence model. It was found that the k-ω SST model gives relatively close results to experimental outcomes. The numerical results were validated and showed good agreement with the experimental data. Pressure drop rises with increasing air mass flow rate, and the lowest pressure drop was observed at 0.6 cavity aspect ratio for all air mass flow rates tested, which agrees with the experimental outcome. A mixing enhancement study showed that 30-degree angle air injectors provide improved fuel-air mixing.

Keywords: aerodynamic, computational fluid dynamics, propulsion, trapped vortex combustor

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389 Comparative Studies of Distributed and Aggregated Energy Storage Configurations in Direct Current Microgrids

Authors: Frimpong Kyeremeh, Albert Y. Appiah, Ben B. K. Ayawli

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Energy storage system (ESS) is an essential part of a microgrid (MG) because of its immense benefits to the economics and the stability of MG. For a direct current (DC) MG (DCMG) in which the generating units are mostly variable renewable energy generators, DC bus voltage fluctuation is inevitable; hence ESS is vital in managing the mismatch between load demand and generation. Besides, to accrue the maximum benefits of ESS in the microgrid, there is the need for proper sizing and location of the ESSs. In this paper, a performance comparison is made between two configurations of ESS; distributed battery energy storage system (D-BESS) and an aggregated (centralized) battery energy storage system (A-BESS), on the basis of stability and operational cost for a DCMG. The configuration consists of four households with rooftop PV panels and a wind turbine. The objective is to evaluate and analyze the technical efficiencies, cost effectiveness as well as controllability of each configuration. The MG is first modelled with MATLAB Simulink then, a mathematical model is used to determine the optimal size of the BESS that minimizes the total operational cost of the MG. The performance of the two configurations would be tested with simulations. The two configurations are expected to reduce DC bus voltage fluctuations, but in the cases of voltage stability and optimal cost, the best configuration performance will be determined at the end of the research. The work is in progress, and the result would help MG designers and operators to make the best decision on the use of BESS for DCMG configurations.

Keywords: aggregated energy storage system, DC bus voltage, DC microgrid, distributed battery energy storage, stability

Procedia PDF Downloads 142
388 Efficiency of Google Translate and Bing Translator in Translating Persian-to-English Texts

Authors: Samad Sajjadi

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Machine translation is a new subject increasingly being used by academic writers, especially students and researchers whose native language is not English. There are numerous studies conducted on machine translation, but few investigations have assessed the accuracy of machine translation from Persian to English at lexical, semantic, and syntactic levels. Using Groves and Mundt’s (2015) Model of error taxonomy, the current study evaluated Persian-to-English translations produced by two famous online translators, Google Translate and Bing Translator. A total of 240 texts were randomly selected from different academic fields (law, literature, medicine, and mass media), and 60 texts were considered for each domain. All texts were rendered by the two translation systems and then by four human translators. All statistical analyses were applied using SPSS. The results indicated that Google translations were more accurate than the translations produced by the Bing Translator, especially in the domains of medicine (lexis: 186 vs. 225; semantic: 44 vs. 48; syntactic: 148 vs. 264 errors) and mass media (lexis: 118 vs. 149; semantic: 25 vs. 32; syntactic: 110 vs. 220 errors), respectively. Nonetheless, both machines are reasonably accurate in Persian-to-English translation of lexicons and syntactic structures, particularly from mass media and medical texts.

Keywords: machine translations, accuracy, human translation, efficiency

Procedia PDF Downloads 59
387 Small Scale Waste to Energy Systems: Optimization of Feedstock Composition for Improved Control of Ash Sintering and Quality of Generated Syngas

Authors: Mateusz Szul, Tomasz Iluk, Aleksander Sobolewski

Abstract:

Small-scale, distributed energy systems enabling cogeneration of heat and power based on gasification of sewage sludge, are considered as the most efficient and environmentally friendly ways of their treatment. However, economic aspects of such an investment are very demanding; therefore, for such a small scale sewage sludge gasification installation to be profitable, it needs to be efficient and simple at the same time. The article presents results of research on air gasification of sewage sludge in fixed bed GazEla reactor. Two of the most important aspects of the research considered the influence of the composition of sewage sludge blends with other feedstocks on properties of generated syngas and ash sintering problems occurring at the fixed bed. Different means of the fuel pretreatment and blending were proposed as a way of dealing with the above mentioned undesired characteristics. Influence of RDF (Refuse Derived Fuel) and biomasses in the fuel blends were evaluated. Ash properties were assessed based on proximate, ultimate, and ash composition analysis of the feedstock. The blends were specified based on complementary characteristics of such criteria as C content, moisture, volatile matter, Si, Al, Mg, and content of basic metals in the ash were analyzed, Obtained results were assessed with use of experimental gasification tests and laboratory ISO-procedure for analysis of ash characteristic melting temperatures. Optimal gasification process conditions were determined by energetic parameters of the generated syngas, its content of tars and lack of ash sinters within the reactor bed. Optimal results were obtained for co-gasification of herbaceous biomasses with sewage sludge where LHV (Lower Heating Value) of the obtained syngas reached a stable value of 4.0 MJ/Nm3 for air/steam gasification.

Keywords: ash fusibility, gasification, piston engine, sewage sludge

Procedia PDF Downloads 180
386 Healthcare Big Data Analytics Using Hadoop

Authors: Chellammal Surianarayanan

Abstract:

Healthcare industry is generating large amounts of data driven by various needs such as record keeping, physician’s prescription, medical imaging, sensor data, Electronic Patient Record(EPR), laboratory, pharmacy, etc. Healthcare data is so big and complex that they cannot be managed by conventional hardware and software. The complexity of healthcare big data arises from large volume of data, the velocity with which the data is accumulated and different varieties such as structured, semi-structured and unstructured nature of data. Despite the complexity of big data, if the trends and patterns that exist within the big data are uncovered and analyzed, higher quality healthcare at lower cost can be provided. Hadoop is an open source software framework for distributed processing of large data sets across clusters of commodity hardware using a simple programming model. The core components of Hadoop include Hadoop Distributed File System which offers way to store large amount of data across multiple machines and MapReduce which offers way to process large data sets with a parallel, distributed algorithm on a cluster. Hadoop ecosystem also includes various other tools such as Hive (a SQL-like query language), Pig (a higher level query language for MapReduce), Hbase(a columnar data store), etc. In this paper an analysis has been done as how healthcare big data can be processed and analyzed using Hadoop ecosystem.

Keywords: big data analytics, Hadoop, healthcare data, towards quality healthcare

Procedia PDF Downloads 389
385 Design-Analysis and Optimization of 10 MW Permanent Magnet Surface Mounted Off-Shore Wind Generator

Authors: Mamidi Ramakrishna Rao, Jagdish Mamidi

Abstract:

With advancing technology, the market environment for wind power generation systems has become highly competitive. The industry has been moving towards higher wind generator power ratings, in particular, off-shore generator ratings. Current off-shore wind turbine generators are in the power range of 10 to 12 MW. Unlike traditional induction motors, slow-speed permanent magnet surface mounted (PMSM) high-power generators are relatively challenging and designed differently. In this paper, PMSM generator design features have been discussed and analysed. The focus attention is on armature windings, harmonics, and permanent magnet. For the power ratings under consideration, the generator air-gap diameters are in the range of 8 to 10 meters, and active material weigh ~60 tons and above. Therefore, material weight becomes one of the critical parameters. Particle Swarm Optimization (PSO) technique is used for weight reduction and performance improvement. Four independent variables have been considered, which are air gap diameter, stack length, magnet thickness, and winding current density. To account for core and teeth saturation, preventing demagnetization effects due to short circuit armature currents, and maintaining minimum efficiency, suitable penalty functions have been applied. To check for performance satisfaction, a detailed analysis and 2D flux plotting are done for the optimized design.

Keywords: offshore wind generator, PMSM, PSO optimization, design optimization

Procedia PDF Downloads 135
384 Experimental Study of the Fiber Dispersion of Pulp Liquid Flow in Channels with Application to Papermaking

Authors: Masaru Sumida

Abstract:

This study explored the feasibility of improving the hydraulic headbox of papermaking machines by studying the flow of wood-pulp suspensions behind a flat plate inserted in parallel and convergent channels. Pulp fiber concentrations of the wake downstream of the plate were investigated by flow visualization and optical measurements. Changes in the time-averaged and fluctuation of the fiber concentration along the flow direction were examined. In addition, the control of the flow characteristics in the two channels was investigated. The behaviors of the pulp fibers and the wake flow were found to be strongly related to the flow states in the upstream passages partitioned by the plate. The distribution of the fiber concentration was complex because of the formation of a thin water layer on the plate and the generation of Karman’s vortices at the trailing edge of the plate. Compared with the flow in the parallel channel, fluctuations in the fiber concentration decreased in the convergent channel. However, at low flow velocities, the convergent channel has a weak effect on equilibrating the time-averaged fiber concentration. This shows that a rectangular trailing edge cannot adequately disperse pulp suspensions; thus, at low flow velocities, a convergent channel is ineffective in ensuring uniform fiber concentration.

Keywords: fiber dispersion, headbox, pulp liquid, wake flow

Procedia PDF Downloads 369
383 Finite Elemental Simulation of the Combined Process of Asymmetric Rolling and Plastic Bending

Authors: A. Pesin, D. Pustovoytov, M. Sverdlik

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Traditionally, the need in items represents a large body of rotation (e.g. shrouds of various process units: a converter, a mixer, a scrubber, a steel ladle and etc.) is satisfied by using them at engineering enterprises. At these enterprises large parts of bodies of rotation are made on stamping units or bending and forming machines. In Nosov Magnitogorsk State Technical University in alliance with JSC "Magnitogorsk Metal and Steel Works" there was suggested and implemented the technology for producing such items based on a combination of asymmetric rolling processes and plastic bending under conditions of the plate mill. In this paper, based on finite elemental mathematical simulation in technology of a combined process of asymmetric rolling and bending plastic has been improved. It is shown that for the same curvature along the entire length of the metal sheet it is necessary to introduce additional asymmetry speed when rolling front end and tape trailer. Production of large bodies of rotation at mill 4500 JSC "Magnitogorsk Metal and Steel Works" showed good convergence of theoretical and experimental values of the curvature of the metal. Economic effect obtained more than 1.0 million dollars.

Keywords: asymmetric rolling, plastic bending, combined process, FEM

Procedia PDF Downloads 302
382 Analysis of Vibratory Signals Based on Local Mean Decomposition (LMD) for Rolling Bearing Fault Diagnosis

Authors: Toufik Bensana, Medkour Mihoub, Slimane Mekhilef

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally nonstationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA), and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, rolling element bearing, local mean decomposition, condition monitoring

Procedia PDF Downloads 374
381 Advances in Artificial intelligence Using Speech Recognition

Authors: Khaled M. Alhawiti

Abstract:

This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

Procedia PDF Downloads 460
380 Modelling and Investigation of Phase Change Phenomena of Multiple Water Droplets

Authors: K. R. Sultana, K. Pope, Y. S. Muzychka

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In recent years, the research of heat transfer or phase change phenomena of liquid water droplets experiences a growing interest in aircraft icing, power transmission line icing, marine icing and wind turbine icing applications. This growing interest speeding up the research from single to multiple droplet phenomena. Impingements of multiple droplets and the resulting solidification phenomena after impact on a very cold surface is computationally studied in this paper. The model used in the current study solves the flow equation, composed of energy balance and the volume fraction equations. The main aim of the study is to investigate the effects of several thermo-physical properties (density, thermal conductivity and specific heat) on droplets freezing. The outcome is examined by various important factors, for instance, liquid fraction, total freezing time, droplet temperature and total heat transfer rate in the interface region. The liquid fraction helps to understand the complete phase change phenomena during solidification. Temperature distribution and heat transfer rate help to demonstrate the overall thermal exchange behaviors between the droplets and substrate surface. Findings of this research provide an important technical achievement for ice modeling and prediction studies.

Keywords: droplets, CFD, thermos-physical properties, solidification

Procedia PDF Downloads 228
379 Computational Neurosciences: An Inspiration from Biological Neurosciences

Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

Procedia PDF Downloads 95