A Statistical Investigation on Particle to Particle Variation of Fly Ash Using SEM-AIA-EDAX Technique.

1989 ◽  
Vol 178 ◽  
Author(s):  
L. E. Barta ◽  
G. VÁmos ◽  
M. A. Toqan ◽  
J. D. Teare ◽  
J. M. BeÉr ◽  
...  
Keyword(s):  
Fly Ash ◽  
Chemical Composition ◽  
Random Variables ◽  
Statistical Investigation ◽  
Distribution Functions ◽  
Mineral Matter ◽  
Size Distributions ◽  
Bulk Analysis ◽  
Mean Values ◽  
Particle Properties

AbstractDue to the particle to particle variation of coal mineral properties and random coalescence of mineral particles during coal burnout, fly ash particle properties change from particle to particle. The variations of particle properties (e.g. SiO2 content, viscosity) can be mathematically described by random variables. Since bulk analysis of fly ash gives only the mean values of chosen random variables, it is considered insufficient to describe the fly ash behavior either in boiler slagging/fouling or in different concrete structures. SEM-AIA-EDAX technique was used to supply raw data for estimating the distribution functions of particle size and chemical compounds in Texas lignite minerals and fly ash and Eagle Butte fly ash. To determine the volume based size distributions of these samples from their area-based size distributions, Abelian transformation was used. To estimate the distribution functions of CaO and SiO2 contents of the samples, particle area fractions were used. The confidence limits were also calculated for the estimated parameters. By determining the distribution functions of particle viscosity and chemical composition, it was shown that in the case of Texas lignite the coal burnout does not cause significant changes in the mineral matter properties. It was observed that the properties of fly ash depended solely on the mineral matter properties. However, in the Eagle Butte case the coal burnout has a major effect on the fly ash size distribution and its chemical composition.

scholarly journals Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Julia Schmale ◽  
Silvia Henning ◽  
Bas Henzing ◽  
Helmi Keskinen ◽  
Karine Sellegri ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Radiative Forcing ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Size Distributions ◽  
Atmospheric Conditions ◽  
Condensation Nuclei ◽  
Retrieval Method ◽  
Particle Properties ◽  
Aerosol Cloud Interactions

Abstract Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.

scholarly journals Prediction of metabolizable energy values in poultry offal meal for broiler chickens

2010 ◽  
Vol 39 (10) ◽  
pp. 2237-2245 ◽  
Author(s):  
Edney Pereira da Silva ◽  
Carlos Bôa-Viagem Rabello ◽  
Luiz Fernando Teixeira Albino ◽  
Jorge Victor Ludke ◽  
Michele Bernardino de Lima ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Broiler Chickens ◽  
Crude Protein ◽  
Matter Content ◽  
Metabolizable Energy ◽  
Mineral Matter ◽  
Ether Extract ◽  
High Fat ◽  
Collection Method ◽  
Gross Energy

This research aimed at generating and evaluating prediction equations to estimate metabolizable energy values in poultry offal meal. The used information refers to values of apparent and true metabolizable energy corrected for nitrogen balance (AMEn and TMEn) and for chemical composition of poultry offal meal. The literature review only included published papers on poultry offal meal developed in Brazil, and that had AMEn and TMEn values obtained by the total excreta collection method from growing broiler chickens and the chemical composition in crude protein (CP), ether extract (EE), mineral matter (MM), gross energy (GE), calcium (Ca) and phosphorus (P). The general equation obtained to estimate AMEn values of poultry offal meal was: AMEn = -2315.69 + 31.4439(CP) + 29.7697(MM) + 0.7689(GE) - 49.3611(Ca), R² = 72%. For meals with high fat contents (higher than 15%) and low mineral matter contents (lower than 10%), it is suggest the use of the equation AMEn = + 3245.07 + 46.8428(EE), R² = 76%, and for meals with high mineral matter content (higher than 10%), it is suggest the equations AMEn = 4059.15 - 440.397(P), R² = 82%. To estimate values of TMEn, it is suggested for meals with high mineral matter content the equation: TMEn = 5092.57 - 115.647(MM), R² = 78%, and for those with low contents of this component, the option is the equation: TMEn = 3617.83 - 15.7988(CP) - 18.2323(EE) - 96.3884(MM) + 0.4874(GE), R² = 76%.

scholarly journals Stochastic Comparisons of Some Distances between Random Variables

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 981
Author(s):  
Patricia Ortega-Jiménez ◽  
Miguel A. Sordo ◽  
Alfonso Suárez-Llorens
Keyword(s):  
Financial Risk ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Stochastic Ordering ◽  
Random Variable ◽  
Distribution Functions ◽  
Stochastic Comparisons ◽  
Stochastic Orderings ◽  
Absolute Value ◽  
The Difference

The aim of this paper is twofold. First, we show that the expectation of the absolute value of the difference between two copies, not necessarily independent, of a random variable is a measure of its variability in the sense of Bickel and Lehmann (1979). Moreover, if the two copies are negatively dependent through stochastic ordering, this measure is subadditive. The second purpose of this paper is to provide sufficient conditions for comparing several distances between pairs of random variables (with possibly different distribution functions) in terms of various stochastic orderings. Applications in actuarial and financial risk management are given.

scholarly journals Finding Maximum Clique in Stochastic Graphs Using Distributed Learning Automata

2015 ◽  
Vol 23 (01) ◽  
pp. 1-31 ◽  
Author(s):  
Alireza Rezvanian ◽  
Mohammad Reza Meybodi
Keyword(s):  
Community Structure ◽  
Dominating Set ◽  
Learning Automata ◽  
Random Variables ◽  
Graph Model ◽  
Maximum Clique ◽  
Distribution Functions ◽  
Maximum Clique Problem ◽  
Stochastic Graphs ◽  
Stochastic Graph

Because of unpredictable, uncertain and time-varying nature of real networks it seems that stochastic graphs, in which weights associated to the edges are random variables, may be a better candidate as a graph model for real world networks. Once the graph model is chosen to be a stochastic graph, every feature of the graph such as path, clique, spanning tree and dominating set, to mention a few, should be treated as a stochastic feature. For example, choosing stochastic graph as the graph model of an online social network and defining community structure in terms of clique, and the associations among the individuals within the community as random variables, the concept of stochastic clique may be used to study community structure properties. In this paper maximum clique in stochastic graph is first defined and then several learning automata-based algorithms are proposed for solving maximum clique problem in stochastic graph where the probability distribution functions of the weights associated with the edges of the graph are unknown. It is shown that by a proper choice of the parameters of the proposed algorithms, one can make the probability of finding maximum clique in stochastic graph as close to unity as possible. Experimental results show that the proposed algorithms significantly reduce the number of samples needed to be taken from the edges of the stochastic graph as compared to the number of samples needed by standard sampling method at a given confidence level.

scholarly journals Mass size distributions and size resolved chemical composition of fine particulate matter at the Pittsburgh supersite

2004 ◽  
Vol 38 (20) ◽  
pp. 3127-3141 ◽  
Author(s):  
Juan C. Cabada ◽  
Sarah Rees ◽  
Satoshi Takahama ◽  
Andrey Khlystov ◽  
Spyros N. Pandis ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Chemical Composition ◽  
Fine Particulate Matter ◽  
Size Distributions ◽  
Fine Particulate ◽  
Mass Size

Influence of Different Mineral Precursors on the Properties of Fly Ash Based Alkali-Activated Mortars

2018 ◽  
Vol 761 ◽  
pp. 73-78 ◽  
Author(s):  
Matej Špak ◽  
Pavel Raschman
Keyword(s):  
Mechanical Properties ◽  
Fly Ash ◽  
Chemical Composition ◽  
Coal Combustion ◽  
Pure Aluminum ◽  
Partial Replacement ◽  
Black Coal ◽  
Fly Ashes ◽  
Final Composition ◽  
Alkali Activated

Alkali-activated materials based on fly ash are widely developed and also produced on the present. Some of fly ashes are not suitable for production of alkali-activated materials because of their inconvenient chemical composition. Alumina-silicates are the most important components that are needed to accomplish the successful reaction. The proper content of amorphous phase of alumina-silicates and its proportion as well should be provided for the final composition of alkali-activated materials. The influence of pure aluminum oxide powder as well as raw milled natural perlite on mechanical properties and durability of alkali-activated mortars was investigated. These minerals were used as partial replacement of fly ash coming from black coal combustion. In addition, the mortars were prepared by using different alkali activators.

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