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  • Liquid Slag Viscosity Calculation in Microsoft Excel | Algoness
    MgO Na2O K2O CaF2 FeO MnO TiO2 ZrO2 Al2O3 Fe2O3 The model is programmed in an Excel add in that can be downloaded here 5 00 Algoness Slag Viscosity Calculator Excel Add in Checkout Added to cart Worksheet functions definitions The following worksheet function is available to calculate liquid slag viscosity Viscosity ComponentNames Masses Temperature C The names in the function above are defined as follows Viscosity Function name returning the calculated viscosity with units of poise ComponentName The input range of cells containing the slag component names e g SiO2 CaO Al2O3 Masses The input range of cells containing the masses in kg of the components Temperature C The input range of a single cell containing the temperature in C at which the viscosity should be calculated The following worksheet function is available to estimate the temperature that would result in specified viscosity TemperatureForViscosity ComponentNames Masses Viscosity P The names in the function above are defined as follows TemperatureForViscosity Function name returning the estimated temperature with units of C ComponentName The input range of cells containing the slag component names e g SiO2 CaO Al2O3 Masses The input range of cells containing the masses in kg of the components Viscosity P The input range of a single cell containing the viscosity in poise for which the temperature in C should be estimated Example spreadsheet application The use of the above two worksheet functions is illustrated using the demonstration spreadsheet Algoness Slag Viscosity Calculator Demo The slag viscosity model has been programmed in VBA behind this workbook with no add in required to use the worksheet functions The light blue coloured cells indicate user input cells The figure below shows how the components SiO2 CaO and Al2O3 and associated masses are entered in columns A temperature of 1500 C is

    Original URL path: http://www.algoness.co.za/liquid-slag-viscosity-calculation-in-microsoft-excel/ (2016-04-26)
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  • Jacques Muller | Algoness
    Muller This article discusses the application of a liquid slag viscosity model as worksheet functions in Microsoft Excel This follows on a previous post that discusses the model and background in greater detail together with the implementation thereof in a Microsoft Silverlight application This application of the viscosity model in Excel is specifically useful as it be more easily integrated with existing mass and energy balance calculations and used to calculate viscosities for multiple slag chemical compositions and temperatures The remainder of this article discusses the worksheet functions and the use thereof as per a demonstration spreadsheet that can be download following instructions below Continue reading Slag Ternary Diagramming Tool Posted on 6 February 2011 9 October 2015 by Jacques Muller In this post I introduce and demonstrate a ternary diagramming tool to calculate and analyse metallurgical slag properties such as viscosity liquidus temperature etc In short this could be used to calculate slag liquid viscosity and then to calculate and plot contours on a ternary diagram It is also possible to import property values from a csv file as a function of the varied components plotted on the diagram and then to calculate and plot the contour values The ternary diagramming tool can be found here This software was again based on the Microsoft Silverlight technology which make it possible to have rich internet application inside your browser or to easily install the software on your computer More on this can be found in a previous post The ternary diagram software component was developed in a way to easily be used in other applications as well Continue reading Smelting furnace refractory and freeze lining heat transfer model Posted on 11 December 2010 9 October 2015 by Jacques Muller In this post I would like to illustrate how to model heat transfer through the refractory of a smelting furnace and how to estimate the thickness of a freeze lining on the hot face This is targeted at readers familiar with smelting furnaces and would like to utilize measured data to evaluate the heat transfer performance or alternatively to investigate refractory options Although complex phenomena exists in the furnace influencing heat transfer and the formation of freeze lining which are in some cases largely unknown a simple approach is demonstrated to model the most important effects observed Continue reading A tool to calculate slag liquid viscosity using Silverlight Posted on 8 November 2010 27 November 2015 by Jacques Muller In this blog I present and discuss a tool to calculate metallurgical slag liquid viscosity This tool has been developed using the Microsoft Silverlight technology which will also be discussed in a bit more detail than was done in the previous post 2015 11 27 Update The slag liquid viscosity calculation was programmed in an updated Microsoft Excel add in and is discussed and available for download here Continue reading Kohonen Self Organizing Maps for Process Applications using Silverlight Posted on 6 November 2010 9 October 2015 by Jacques Muller In this

    Original URL path: http://www.algoness.co.za/author/jacques-muller/ (2016-04-26)
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  • A tool to calculate slag liquid viscosity using Silverlight | Algoness
    B2O3 Parameters were derived and tuned for these groups from experimental data to model the viscosity from the mole fraction of each component and the temperature The software presented here provides a tool to estimate the slag viscosity using this Urbain model as published by dr KC Mills This tool allows for the following two calculations Liquid viscosity Calculates the liquid viscosity for the input chemical composition mass s and temperature C using the Urbain model publish by dr K C Mills in the Slag Atlas 2nd Ed It is called the liquid viscosity based on the assumption that the slag specified is fully liquid at the temperature at which viscosity is calculated temperature is higher than liquidus Temperature for viscosity The viscosity model above is used to solve the temperature C at which a slag will have the target viscosity specified This is useful in operation to calculate the temperature that a slag need to be knowing the typical viscosity value predicted by this specific model for slag classified as easy to tap Microsoft Silverlight The application platform chosen for presenting the calculation tool is Microsoft Silverlight This is a relatively new technology allowing for rich internet applications that is available in runtime environment as a plug in to most browsers Another useful feature is that the applications do not have to run in the browser alone but could very easily be installed onto a computer without directly having to download any software and available off line The viscosity calculation tool has been embedded as a component at the end of this blog or can be opened in new window by following this link This means that if the Silverlight plug in is installed you should see the fully functional application If this is not visible but an icon

    Original URL path: http://www.algoness.co.za/tool-calculate-slag-liquid-viscosity-silverlight/ (2016-04-26)
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  • Slag Ternary Diagramming Tool | Algoness
    MgO and CaO to the list of corner B species How to Configure diagram scale This section illustrates how to change the axes scales in order to zoom in or out of the diagram The scale window could be accessed similarly to the setup window by a right click anywhere on the diagram selecting Configure Diagram and then selecting the Scale tab partly shown in the following screenshot In this window it is possible to enter the weight percentage intervals for the gridlines of each of the axes and also the minimum and maximum weight percentages of the axes to plot The lower limit is zero while the upper limit is 100 minus the sum of the constant species Again it should be noted that only the numerical value need to be entered In the above screenshot then the intervals of the gridlines were all 10 while the axes were plotted between 0 and 81 with the sum of the constant species being 19 For illustration the following blank diagram shows how the diagram was configure to display values between 10 and 50 on all the axes with all gridline intervals of 5 Not the corners of the triangle being cut off due to the axes maximum values being less than the maximums allowable How to Calculate property data This section shows the first step of adding data to the diagram through the calculation of the slag liquid viscosity The data calculation window could be obtained by a right click on the diagram and selecting Add Data Layer and then the Property Raw Data as in the following screenshot In the left section the Property Source is selected and in this case the Generate Data option should be selected Firstly the property to be calculated must be selected currently the only option built in is the slag liquid viscosity Then the temperature at which the property must be calculated need to be entered and the interval with which it should vary the variable components when calculating the property In general 1 works well The next step is to select the variable species and enter values for constant species in the Component Values list Only 3 species can be selected as variable species and constant values can be entered for the non selected species Pressing calculate will generate a range of compositions with the constant specie values specified and the values of the other 3 species varied between 0 and 100 minus constant specie total to cover the entire ternary diagram This data will be used to derive contours that will be plotted For example to coincide with the configuration the variable species selected were SiO2 MnO and CaO The constant species and values specified were Al2O3 13 and MgO 6 Pressing Calculate generated the results in the right hand side of the screen as shown in the screenshot below How to Import property data Should you wish to plot other slag properties than the liquid viscosity calculated here then the

    Original URL path: http://www.algoness.co.za/slag-ternary-diagramming-tool/ (2016-04-26)
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  • algoNess.TernaryDiagramming
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    Original URL path: http://www.algoness.co.za/Blog/ternary_diagramming_tool/algoNess.TernaryDiagrammingMainPage.html (2016-04-26)
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  • Kohonen Self Organizing Maps for Process Applications, using Silverlight | Algoness
    the typical layout of a SOM in two dimensions Firstly the grid of the entire map 5 x 5 here shows the row and column index of each node then the vectors with values are shown for each node For training the map is initialized with vectors of random but typical values and then iteratively trained using one training vector at a time In the training process the vector closest to the training point is found and adjusted together with the surrounding nodes to be closer to the training value This means that each value in the vector is manipulated while the neighborhood radius of surrounding nodes decreases as training progresses as well as the training rate After training then the map would have been organized into region of vectors with related values If for example the SOM is trained to model plant operating conditions certain regions in the SOM would represent vectors where the values of one or more elements is significantly different and indicating specific operating conditions Basic example One of the most basic examples of SOM s is that of a grid of vectors each of length 2 representing an X and Y coordinate plotted on a chart Each point plotted is connected with a line to the points of all 4 of its neighbours in the grid The SOM is initialized with random values and when first plotted it s a mess with points and lines As the SOM is trained also with random values the points move around and also their neighbours get moved closer After training a neat grid has been obtained and all the nodes have been de tangled The example is shown in the frame below and requires of your browser to have Microsoft Silverlight installed which can be done by following the plug in information displayed in its place below This application can also be installed by right clicking on it and selecting the installation option You can start stop and reset the training of the example SOM Starting it would begin execution of 5000 steps and resetting it would randomize the vector values Each node is plotted as a circle on a canvas with the coordinates of X and Y values in the vector and the color changed from white to blue depending on the euclidean distance to the neighbor vectors white the lowest distance field name iframe2 Below is a static image of what the example above could look like after training Higher dimension example Another typical example is that of defining vectors of length 3 and translating it to colors For example let s consider a smelting process where the three points represent the mass percentages of three slag species say SiO2 CaO and MgO Historical operational data is available like that shown in the following table representing typical slag compositions that has been obtained Our vector might also be longer containing values of say metal tonnage produced and energy consumption If we create a SOM and train

    Original URL path: http://www.algoness.co.za/kohonen-organizing-maps-process-applications-silverlight/ (2016-04-26)
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  • Finite difference heat transfer analyses in Excel | Algoness
    In one dimensional form heat flux through a node is where q is the heat flux W m2 T is the temperature Kelvin at a node through which heat is flowing and k is the conductivity W mK of the material through which heat is flowing 1D Heat Transfer The body for the temperature distribution which needs to be solved is broken up into a number of finite elements or nodes as illustrated below Consider the node numbered x somewhere inside the body The node to the left is numbered x 1 and to the right is x 1 Heat is flowing through it in the x direction and because we are only considering the steady state at the moment the heat flux over the left boundary should be equal to the heat flux over the right boundary Or in general the heat flux into the node should be the heat flux out of the node The heat balance for the node x can be written as follows discretized and reduced to a single equation for the temperature of node x as function of the temperatures to the left and right Boundary conditions The above sections covered nodes inside the body but the nodes on the boundaries need different equations to be solved For illustration the problem was defined to have convective heat transfer cooling on the left side with a heat transfer coefficient of 5 W m2K and have a fixed temperature of 1600 C on the right side The temperature equation for first node can be derived defining the heat flux into the first node as a function of the heat transfer coefficient Application in Excel The next step is to program these equations into Excel and model the temperature profile in one dimension The following two pictures show how to setup the solution and then firstly how to enter the equations for node 0 and then the equations for nodes 1 to 8 Node 9 is simply given the value of 1600 The above is then all that s required to have Excel solve the heat transfer for our body Ensure just that iterative calculations are enabled in the Excel options and press F9 until the values in cells does not change anymore To enhance the display of the results the colors of the cells can be conditionally formatted to the value in the cells 2D Example The principles illustrated above in one dimension can now simply be applied for two dimensions The following illustrates our example domain It is a square body with a fixed temperature at the bottom convective heat transfer at the top no heat transfer in the x direction on the right and a heat loss value in the x direction on the left General internal node The domain is now divided into nodes in both the x and y directions and the first step is to derive the temperature equation of a general internal node taking into account the heat fluxes in

    Original URL path: http://www.algoness.co.za/finite-difference-analyses-excel/ (2016-04-26)
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  • algoNess.LiquidViscosity
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    Original URL path: http://www.algoness.co.za/Blog/prop_liqVisc/algoNess.LiquidViscosityTestPage.html (2016-04-26)
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