scholarly journals Autonomous Underwater Vehicle Powered by Direct Methanol Fuel Cell-Based Power Plants: A Quick Preliminary Design Model

2020 ◽  
Vol 10 (21) ◽  
pp. 7687
Author(s):  
Antonio Villalba-Herreros ◽  
Ó. Santiago ◽  
Loredana Magistri ◽  
Teresa J. Leo
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Direct Methanol Fuel Cells ◽  
Autonomous Underwater Vehicle ◽  
Energy Content ◽  
Autonomous Underwater Vehicles ◽  
Preliminary Design ◽  
Underwater Communications ◽  
Direct Methanol ◽  
Remote Sites

Investigation, conservation, and exploitation of seas require platforms capable of accomplishing a wide variety of missions in harsh environments with restricted human intervention for long periods of time. Autonomous Underwater Vehicles (AUVs) are excellent tools for carrying out these missions due to their versatility and ability to access remote sites. However, despite the improvement of their capabilities, their development is not devoid of challenges. Endurance, among others, such as underwater communications or autonomy, is still a pending subject. Current battery-based solutions do not offer sufficient endurance and innovative power plants with higher energy content are needed. This work studies the advantages, in terms of endurance, of using a power plant based on Direct Methanol Fuel Cells (DMFCs) to power AUVs. In order to accomplish this, a multi-objective optimization tool that makes use of a genetic algorithm was developed. This tool allows quick preliminary design of AUVs with a DMFC-based power plant, complying with a user-defined payload, operation profile, and restrictions. Six designs based on a real AUV model were studied, and endurance values up to 2 times longer than the corresponding reference AUV were obtained. These results support the benefits of using DMFCs to power AUVs to increase their endurance.

Conceptual Design of an Autonomous Underwater Vehicle Powered by a Direct Methanol Fuel Cell to Enlarge Endurance

2018 ◽  
Author(s):  
Antonio Villalba-Herreros ◽  
Teresa J. Leo ◽  
Ricardo Abad
Keyword(s):  
Fuel Cell ◽  
Conceptual Design ◽  
Direct Methanol Fuel Cell ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
High Energy ◽  
High Energy Density ◽  
Direct Methanol ◽  
Offshore Industry ◽  
Methanol Fuel Cell

Autonomous underwater vehicles (AUVs) are versatile machines capable of more and more complex missions including the offshore industry. The ability to carry out some missions relies on the endurance the vehicle is provided with. In this sense, fuel cells are found to be very adequate devices to enlarge AUVs endurance because of the high energy density and specific energy they can achieve, but the application of fuel cell technology to AUVs faces specific challenges that need to be overcome. The present work describes the conceptual design process of a typical AUV powered by a direct methanol fuel cell. Methanol is a high available fuel and its handling system is simple. The obtained results indicate that the manufacturing of such a vehicle is possible within several constrains, being the carbon dioxide treatment system the most critical component of the energy plant. The projected vehicle is compared to current vehicles on the market showing the improved endurance.

Modeling and Control of Subcritical Coal-Fired Power Plant Components for Fault Detection

2020 ◽  
Author(s):  
Selorme Agbleze ◽  
Fernando V. Lima ◽  
Natarianto Indrawan ◽  
Rupendranath Panday ◽  
Paolo Pezzini ◽  
...  
Keyword(s):  
Power Plant ◽  
Fault Detection ◽  
Power Plants ◽  
Energy Content ◽  
Leak Detection ◽  
Primary Component ◽  
Plant Performance ◽  
Saturated Steam ◽  
Power Sources

Abstract Due to the increased penetration of renewable power sources into the electric grid, the current number of existing coal-fired power plants shifting from baseload to load-following operations has also increased. This shift creates challenges especially for the power industry as coal-fired power plants were not designed for ramping situations, leading to added stress on major components of these plants. This stress causes the system to degrade over time and eventually develop faults. As boilers are still the primary component that fails and causes forced outages, accurate characterization of faults and fractures of boilers is now becoming increasingly critical to reduce plant downtime and extend the plant life during cycling operations. This work focuses on modeling sections of a subcritical coal-fired power plant and proposes algorithms for fault detection in MATLAB/Simulink. The developed model simulates the process dynamics including steam and feedwater flow regulating valves, drum-boiler, and heat rate on the regulation of pressure, drum level and production of saturated steam. The model also simulates the dynamics of superheaters for increasing the energy content of steam, and a spray section for regulating the temperature of steam upstream of the high-pressure turbine to allow for power output adjustment within a given valve operating range. Furthermore, an extension to a leak detection framework proposed by co-authors in previous work is explored. The new framework includes a modification to the threshold analysis portion of the previous work. The extended framework is then applied to a subcritical coal-fired power plant model for leak detection. In particular, this framework analyzes mismatches or deviations in expected plant dynamics with an identified transfer function model. The mismatch is flagged after it exceeds a threshold. The developed algorithm thus aids in rapid detection of faults to reduce impeded plant performance. The results of this work will support real plant operations by providing an accurate characterization of faults in the operation of coal-fired power plants.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Human Factors ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Cooling System ◽  
Human Reliability ◽  
Non Destructive ◽  
Plant Components

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.

Nonlinear Trend Analysis of Mill Fan System Vibrations for Predictive Maintenance and Diagnostics

2012 ◽  
Vol 58 (4) ◽  
pp. 351-356
Author(s):  
Mincho B. Hadjiski ◽  
Lyubka A. Doukovska ◽  
Stefan L. Kojnov
Keyword(s):  
Power Plant ◽  
Trend Analysis ◽  
Thermal Power Plant ◽  
Power Plants ◽  
Thermal Power ◽  
Balkan Peninsula ◽  
Predictive Maintenance ◽  
Nonlinear Trend ◽  
The Subject ◽  
The Given

Abstract Present paper considers nonlinear trend analysis for diagnostics and predictive maintenance. The subject is a device from Maritsa East 2 thermal power plant a mill fan. The choice of the given power plant is not occasional. This is the largest thermal power plant on the Balkan Peninsula. Mill fans are main part of the fuel preparation in the coal fired power plants. The possibility to predict eventual damages or wear out without switching off the device is significant for providing faultless and reliable work avoiding the losses caused by planned maintenance. This paper addresses the needs of the Maritsa East 2 Complex aiming to improve the ecological parameters of the electro energy production process.

Progress and Perspectives in Passive Direct Methanol Fuel Cells Operating with Concentrated Methanol

2012 ◽  
Vol 7 (3) ◽  
pp. 1-7
Author(s):  
Naveen K. Shrivastavaa ◽  
◽  
Shashikant B. Thombreb ◽  
Kailas L. Wasewar ◽  
◽  
...  
Keyword(s):  
Fuel Cells ◽  
Direct Methanol Fuel Cells ◽  
Direct Methanol ◽  
Methanol Fuel Cells

Features of antibodies against benzo[a]pyrene formation in workers of coal mines and thermal power plants

2019 ◽  
pp. 9-14
Author(s):  
Ye. G. Polenok ◽  
S. A. Mun ◽  
L. A. Gordeeva ◽  
A. A. Glushkov ◽  
M. V. Kostyanko ◽  
...  
Keyword(s):  
Power Plant ◽  
Thermal Power Plant ◽  
Power Plants ◽  
Reference Group ◽  
Coal Dust ◽  
Thermal Power ◽  
Coal Mines ◽  
Serum Levels ◽  
Thermal Power Plants ◽  
Immune Reactions

Introduction.Coal dust and coal fi ring products contain large amounts of carcinogenic chemicals (specifically benz[a]pyrene) that are different in influence on workers of coal mines and thermal power plants. Specific immune reactions to benz[a]pyrene therefore in these categories of workers can have specific features.Objective.To reveal features of antibodies specifi c to benz[a]pyrene formation in workers of coal mines and thermal power plants.Materials and methods.The study covered A and G class antibodies against benz[a]pyrene (IgA-Bp and IgG-Bp) in serum of 705 males: 213 donors of Kemerovo blood transfusion center (group 1, reference); 293 miners(group 2) and 199 thermal power plant workers (group 3). Benz[a]pyrene conjugate with bovine serum albumin as an adsorbed antigen was subjected to immune-enzyme assay.Results.IgA-Bp levels in the miners (Me = 2.7) did not differ from those in the reference group (Me = 2.9), but in the thermal power plant workers (Me = 3.7) were reliably higher than those in healthy men and in the miners (p<0.0001). Levels of IgG-Bp in the miners (Me = 5.0) appeared to be lower than those in the reference group (Me = 6.4; (p = 0.05). IgG-Bb level in the thermal power plantworkers (Me = 7.4) exceeded the parameters in the healthy donors and the miners (p<0.0001). Non-industrial factors (age and smoking) appeared tohave no influence on specific immune reactions against benz[a]pyrene in the miners and the thermal power plant workers.Conclusions.Specific immune reactions against benz[a]pyrene in the miners and the thermal power plant workers are characterized by peculiarities: the miners demonstrate lower levels of class A serum antibodies to benz[a]pyrene; the thermal power plant workers present increased serum levels of class G antibodies to benz[a]pyrene. These peculiarities result from only the occupational features, but do not depend on such factors as age, smoking and length of service at hazardous production. It is expedient to study specific immune reactions to benz[a]pyrene in workers of coal mines and thermal power plants, to evaluate individual oncologic risk and if malignancies occur.

Reliability Index of Wind-Solar Hybrid Power Plants using the Expected Energy Not Supplied Method

2019 ◽  
Vol 8 (4) ◽  
pp. 9449-9456
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Electricity Market ◽  
Reliability Index ◽  
Power Plants ◽  
Initial Conditions ◽  
Hybrid Plant ◽  
Total Power ◽  
Hybrid Power ◽  
Hybrid Power Plant

This paper proposes the reliability index of wind-solar hybrid power plants using the expected energy not supplied method. The location of this research is wind-solar hybrid power plants Pantai Baru, Bantul, Special Region of Yogyakarta, Indonesia. The method to determine the reliability of the power plant is the expected energy not supplied (EENS) method. This analysis used hybrid plant operational data in 2018. The results of the analysis have been done on the Pantai Baru hybrid power plant about reliability for electric power systems with EENS. The results of this study can be concluded that based on the load duration curve, loads have a load more than the operating kW of the system that is 99 kW. In contrast, the total power contained in the Pantai Baru hybrid power plant is 90 kW. This fact makes the system forced to release the load. The reliability index of the power system in the initial conditions, it produces an EENS value in 2018, resulting in a total value of 2,512% or 449 kW. The EENS value still does not meet the standards set by the National Electricity Market (NEM), which is <0.002% per year. Based on this data, it can be said that the reliability of the New Coast hybrid power generation system in 2018 is in the unreliable category.

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