Prediction of gaseous emissions from industrial stacks using an artificial intelligence method

2006 ◽  
Vol 60 (6) ◽  
Author(s):  
C. Anghel ◽  
A. Ozunu
Keyword(s):  
Artificial Intelligence ◽  
Predictive Power ◽  
Thermal Power ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Gaseous Emissions ◽  
Classification Problems ◽  
Power Station ◽  
The Core ◽  
Minimax Probability Machine Regression

AbstractA novel technique based on artificial intelligence methods able to predict pollutant emission concentrations from industrial stacks is presented. This procedure combines regression and classification problems into a unified technique, named minimax decision procedure. The core of this procedure is based on the minimax probability machine regression model. Using experimental databases, the trend of pollutant emissions and the level of pollution for one industrial thermal power station stack were presented. Based on this unified technique, numerical experiments provided the estimates of concentrations of CO, NOx, NO, and SO2 confirming the predictive power of this procedure.

Environmental Economic Power Dispatch Using Bat Algorithm with Generalized Fly and Evolutionary Boundary Constraint Handling Scheme

2020 ◽  
Vol 11 (2) ◽  
pp. 171-191
Author(s):  
Latifa Dekhici ◽  
Khaled Guerraiche ◽  
Khaled Belkadi
Keyword(s):  
Environmental Economic ◽  
Thermal Power ◽  
Bat Algorithm ◽  
Pollutant Emissions ◽  
Constraint Handling ◽  
Pollutant Emission ◽  
Economic Power ◽  
Power Dispatch ◽  
Boundary Constraint ◽  
Economic Power Dispatch

This article intends to resolve the evolving environmental economic power dispatching problem (EED) using an enhanced version of the bat algorithm (BA) which is the Bat Algorithm with Generalized Fly (BAG). A good solution based on the Evolutionary Boundary Constraint Handling Scheme rather than the well-known absorbing technique and a good choice of the bi-objective function are provided to maintain the advantages of such algorithms on this problem. In the first stage, an individual economic power dispatch problem is considered by minimizing the fuel cost and taking into account the maximum pollutant emission. In the second stage and after weighting soft constraints satisfaction maximization and hard constraints abuse penalties, the proposed approach of the bi-objective environmental and economic load dispatch was built on a pareto function. The approach was tested on a thermal power plant with 10 generators and an IEEE30 power system of 6 generators. The results on the two datasets compared to those of other methods show that the proposed technique yields better cost and pollutant emissions.

scholarly journals Artificial Intelligence Integration with Nanotechnology

2020 ◽  
Vol 2 (4) ◽  
pp. 1-6
Author(s):  
Farahnaz Behgounia
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Predictive Power ◽  
Short Communication ◽  
Business Value ◽  
Autonomous Learning ◽  
The Core ◽  
Technological Developments ◽  
Data Analytic

Artificial intelligence is a new phenomenon that has occupied a prominent place in our present lives. Its presence in almost any industry that deals with any huge sheer volume of data are taking advantage of AI by integrating it into its day-to-day operation. AI has predictive power based on its data analytic functionality and some levels of autonomous learning, which its raw ingredient is just the massive sheer volume of data. Artificial intelligence is about extracting value from data, which has become the core business value when insight can be extracted. AI has various fundamental applications. This technology can be applied to many different sectors and industries. There has been a tremendous use of artificial intelligence in Nanotechnology research during the last decades. Convergence between artificial intelligence and Nanotechnology can shape the path for various technological developments and a large variety of disciplines. In this short communication, we present such innovative and dynamic sites utilizing artificial intelligence and its sub-sets of machine learning driven by deep learning in Nanotechnology

Backward-Inclined Diffusion Jet Flames in Crossflow at Low Jet-to-Crossflow Momentum Flux Ratios

2018 ◽  
Vol 141 (5) ◽  
Author(s):  
Dickson Bwana Mosiria ◽  
Rong Fung Huang ◽  
Ching Min Hsu
Keyword(s):  
Inclination Angle ◽  
Momentum Flux ◽  
Diffusion Flames ◽  
Thermal Power ◽  
Flux Ratio ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Jet Flames ◽  
Air Mixing ◽  
Flame Flashback

In the design of gas turbine combustors, efforts are engineered toward reducing the combustion pollutant emission levels. The pollutant emissions can be reduced by premixing the fuel and the air prior to ignition. However, the main challenges encountered with premixing are flame flashback and blowout, thus, the preference of diffusion flames. In this study, flame behavior, flow patterns, and thermochemical fields of backward-inclined diffusion jet flames in crossflow at low jet-to-crossflow momentum flux ratio of smaller than 0.04 were studied in a wind tunnel. The backward-inclination angle was varied within 0–50 deg. The flames presented three characteristic modes: crossflow dominated flame (low backward inclination angle) denoted by a large down-washed recirculation flame, transitional flame (mediate backward inclination angle) identified by a recirculation flame and a tail flame, and jet dominated flame (high backward inclination angle) characterized by a blue flame base, a yellow tail flame, and the absence of a recirculation flame. Short flames are detected in the regime of the crossflow dominated flames—an indication of improved fuel–air mixing. The findings suggest that for low exhaust emissions which are vigorously pursued in the aviation and thermal power plant industries, especially during low-load operations, the jet dominated flames are the preferable flames as they generate low unburned hydrocarbon, carbon monoxide, and nitric oxide emissions compared to the other flames.

EZEE®: A High Power Density Modulating FLOX® Combustor

2012 ◽  
Author(s):  
H. Schütz ◽  
O. Lammel ◽  
G. Schmitz ◽  
T. Rödiger ◽  
M. Aigner
Keyword(s):  
Gas Turbine ◽  
Power Density ◽  
Power Level ◽  
Thermal Power ◽  
Fine Tuning ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
First Results ◽  
Combustion Technology ◽  
Operational Range

Presented in this paper is a novel gas turbine combustor: EZEE® based upon the FLOX® combustion technology. The specific feature of this combustor is the ability to modulate the power density PA for natural gas (NG) combustion on a high thermal power level between PA = 13.3 MW/m2/bar in the main load and PA = 7.9 MW/m2/bar in the part load operation. The operational range for the global air to fuel excess ratio λ is between λ = 1.6 and λ = 2.7 corresponding to adiabatic flame temperatures between Tad ≈ 2000 K and 1500 K, respectively. The air preheating temperature is 673 K and the pressure level is 8 bar. The inspected operational range satisfies the demands of modern gas turbine combustors. The idea of EZEE® is to manipulate the flame position by radial staging of two independent fuel supplies in order to prevent flame extinction with increasing λ. The combustor is developed with the aid of computational tools and accordingly manufactured and experimentally investigated at the DLR test facilities. It is demonstrated that the combustion is complete and stable and that the pollutant emission is low. Presented are first results of our investigations that show the usefulness and the potential of the concept. However, it is also shown that additional fine-tuning is still necessary to further reduce the pollutant emissions.

scholarly journals Environmental Impact and External Costs Associated with Hub-and-Spoke Network in Air Transport

2021 ◽  
Vol 13 (2) ◽  
pp. 465
Author(s):  
Mengyuan Sun ◽  
Yong Tian ◽  
Yao Zhang ◽  
Muhammad Nadeem ◽  
Can Xu
Keyword(s):  
Environmental Impact ◽  
Living Environment ◽  
Strategic Decision ◽  
Air Transport ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Civil Aviation ◽  
External Costs ◽  
Hub And Spoke ◽  
City Network

Under the background of economic globalization, the air transport industry developed rapidly. It turns out that the city-to-city network has not been able to adapt well to the development of the society, and the hub-and-spoke network came into being. The hub-and-spoke network demonstrates the advantages of reducing the operating costs of airlines to keep a competitive advantage, and by maintaining the interests of airlines in the rapidly developing context. However, during the operation of aircrafts, they consume fuel and spew a great deal of harmful pollutants into the air, which has an adverse impact on the living environment. This paper explores the impact and external costs associated with hub-and-spoke network in air transport from an environmental perspective. With some mathematical models, we construct a hub-and-spoke network and take a quantitative study on the environmental impact of air transport. For calculating pollutant emissions, meteorological conditions were considered to revise the pollutant emission factors of the Engine Emissions Data Base (EEDB) published by International Civil Aviation Organization (ICAO). The environmental external costs measurement model is employed to calculate the externality of toxic gas and greenhouse gas (GHG). In order to make the study more convincing, two alternative networks are computed: hub-and-spoke network and city-to-city network. It is found that the hub-and-spoke network is associated with poorer environmental impact and environmental external costs because of the different network characteristics and the scale of the fleets. Therefore, under the general trend of green aviation, the environmental impact and environmental external costs associated with hub-and-spoke network in air transport provides a certain reference for airlines’ strategic decision-making.

A Case Study of ESP Electrical Characteristics from a Thermal Power Station

2009 ◽  
Author(s):  
Gabriel Nicolae Popa ◽  
Cristian Abrudean ◽  
Sorin Ioan Deaconu ◽  
Iosif Popa ◽  
Victor Vaida
Keyword(s):  
Thermal Power Station ◽  
Thermal Power ◽  
Electrical Characteristics ◽  
Power Station
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