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This is because you can do it all with free GIS software. The best part is: These free GIS software give you the firepower to get the job done as if you’re working with. We’ve, but these 13 (out of 30) reign supreme for free mapping software. 1 QGIS – Formerly Quantum GIS Highlights: Community All-in-one Cartography Plugins GISGeography Favorite After the, we illustrated with 27 differences why QGIS is undoubtedly the #1 free GIS software package. Is jam-packed with hidden gems at your fingertips.
For example, you can automate map production, process geospatial data, and generate drool-worthy cartographic figures. There’s no other free mapping software on this list that lets you map like a rock star than QGIS. Boost this mapping software into a state of epicness. If the tool doesn’t exist, search for a plugin developed by the QGIS community. Volunteer effort is key to its success. The support is impressively great. If you’re still searching for free GIS software, you’d be insane not to download the free GIS software QGIS.
Here’s your to get your feet wet. In February 2018, QGIS 3 brings a whole new set of cartography, 3D and analysis tools. We’ve got you covered on how to find all of its newest features and plugins: READ MORE: 2 gVSIG Highlights: 3D Tools Compatibility CAD Tools Data Management In 2004, the emerged as a free, open source GIS software option in Spain. We illustrate in this why we like it SO much: gvSIG really outperforms QGIS 2 for 3D.
It really is the best 3D visualization available in open source GIS. The NavTable is agile in that it allows you to see records one-by-one vertically. The CAD tools are impressive on gvSIG. Thanks to the OpenCAD Tools, you can trace geometries, edit vertices, snap and split lines and polygons.
If you need GIS on your mobile phone, gvSIG Mobile is perfect for field work because of its interface and GPS tools. 3 Whitebox GAT Highlights: LiDAR Tools Hydrology GISGeography Favorite Yes, (Geospatial Analysis Toolbox) is #3 on the list of open source, free GIS software.
Unbelievably, Whitebox GAT has only been around since 2009 because it feels so fine-tuned when you see it in action. There’s a hydrology theme around Whitebox GAT. It actually replaced – a tool for hydro-geomorphic applications. Whitebox GAT is really a full-blown open-access GIS and remote sensing software package. Where it shines is LIDAR! With no barriers, Whitebox GAT is the swiss-army knife of.
The LiDAR toolbox is a life-saver. For example, LAS to shapefile is an insanely useful tool. But you may need a Java update to go in full throttle though. The cartographic mapping software tools are primitive compared to QGIS. But overall Whitebox GAT is solid with over 410 tools to clip, convert, analyze, manage, buffer and extract geospatial information. I find it amazing this free GIS software almost goes unheard of in the GIS industry. Get more useful knowledge from the.
4 SAGA GIS Highlights: Geoscientific Tools Ease of Use GISGeography Favorite (System for Automated Geoscientific Analyses) is one of the classics in the world of free GIS software. It started out primarily for terrain analysis such as hillshading, watershed extraction and visibility analysis. Now, SAGA GIS is a powerhouse because it delivers a fast growing set of geoscientific methods to the geoscientific community. Enable multiple windows to lay out all your analysis (map, histograms, scatter plots, attributes, etc). It provides both a user-friendly GUI and API. It’s not particularly useful in cartography but it’s a lifesaver in terrain analysis. The morphometry tools are unique including the SAGA topographic wetness index and topographic position classification.
If you have a DEM, and don’t know what to do with it – you NEED to look at SAGA GIS. Overall, it’s quick, reliable and accurate. Consider SAGA GIS a prime choice for environmental modeling and other applications. READ MORE: 5 GRASS GIS Highlights: Research Community Analysis Tools (Geographic Resources Analysis Support System) was developed by the US Army Corps of Engineers as a tool for land management and environmental planning. It has evolved into a free GIS software option for different areas of study.
Academia, environment consultants and government agencies (NASA, NOAA, USDA and USGS) use GRASS GIS because of its intuitive GUI and its reliability. It has over 350 rock-solid vector and raster manipulation tools. Not awfully useful in cartographic design, GRASS GIS excels primarily as a free GIS software option for analysis, image processing, digital terrain manipulation and statistics. 6 MapWindow Highlights: Hydrology Plugins Programmer Tools In 2000, was proprietary GIS software. However, it has been made open through a contract with the.
At this point, The source code was released to the public. Now that MapWindow 5 has been released, it surprisingly has some serious punch. For example, MapWindow does about 90% of what GIS users need – map viewer, identify features, processing tools and print layout. It has some higher level tools such as TauDEM for automatic watershed delineation.
While HydroDesktop for data discovery, download, visualization and editing, DotSpatial for GIS programmers. In addition, it has an extensible plugin architecture for customization. 7 ILWIS Highlights: Open Source Ease of Use Free GIS software users rejoice. Once commercial GIS software, now turned into open source GIS. (Integrated Land and Water Information Management) is an oldie but a goodie.
The extinction-proof ILWIS is free GIS software for planners, biologists, water managers and geospatial users. ILWIS is good at the basics – digitizing, editing, displaying geographic data. Further to this, it’s also used for remote sensing with tools for image classification, enhancements and spectral band manipulation. Over time, it has improved support for time series, 3 analysis and animation. Overall, I found it difficult to do some of the basics like adding layers. However, the documentation is thorough with a pretty decent following for usage.
READ MORE: 8 GeoDa Highlights: Open Source Geostatistics GeoDa Software is a free GIS software program primarily used to introduce new users into spatial data analysis. It’s main functionality is data exploration in statistics. One of the nicest things about it is how it comes with sample data for you to give a test-drive. From simple box-plots all the way to regression statistics, GeoDa has to do nearly anything spatially. It’s user base is strong.
For example, Harvard, MIT and Cornell universities have embraced this free GIS software to serve as a gentle introduction to spatial analysis for non-GIS users. From economic development to health and real estate, it’s been used as an exciting analytical in labs as well. READ MORE: 9 uDig Highlights: Open Source Ease of Use Basic Mapping is an acronym to help get a better understanding what this Free GIS software is all about. u stands for user-friendly interface. D stands for desktop (Windows, Mac or Linux). You can run uDIG on a Mac.
I stand for internet oriented consuming standard (WMS, WFS or WPS). G stands for GIS-ready for complex analytical capabilities. When you start digging into uDig, it’s a nice open source GIS software option for basic mapping. UDig’s Mapnik lets you import basemaps with the same tune as ArcGIS Specifically, it’s easy-to-use, the catalog, symbology and Mac OS functionality are some of the strong points.
But it has limited tools and the bugs bog it down to really utilize it as a truly complete free GIS software package. 10 OpenJump Highlights: Open Source Conflation Formerly JUMP GIS, (JAVA Unified Mapping Platform) started as a first class conflation project. It succeeded.
But eventually grew into something much bigger. Because of how its large community effort grew, OpenJUMP into a more complete free GIS software package.
One of its strengths is how it handles large data sets well. Rendering is above-grade with a whole slew of mapping options. For example, you can generate pie charts, plotting and choropleth maps. Enhance its capabilities. There are plugins for editing, raster, printing, web-processing, spatial analysis, GPS and databases. Conflating data is another option with a whole lot more from its plugins.
11 Diva GIS Highlights: Open Source Biology Data Biologists using GIS unite! This one specializes in mapping biological richness and diversity distribution including DNA data. Is another free GIS software package for mapping and analyzing data. Diva GIS also delivers useful, every day for your mapping needs. It’s possible to extract climate data for all locations on the land. From here, there are statistical analysis and modeling techniques to work with.
For the biologist in you, it’s worth a long look for biologists around the world. Otherwise, you should be looking at one of the top options above. 12 FalconView Highlights: Open Source Fly-throughs The initial purpose of FalconView is to be a free and open source GIS software. Georgia Tech built this open software for displaying various types of maps and geographically referenced overlays. Now, most of FalconView’s users are from the US Department of Defense and other National Geospatial Intelligence Agencies. This is because it can be used for combat flight planning.
In SkyView mode, you can fly-through even using MXD files. It supports various types of display like elevation, satellite, LiDAR, KMZ and MrSID.
13 OrbisGIS Highlights: Open Source is a work-in-progress. Its goal is to be a cross-platform open source GIS software package designed by and for research. It provides some GIS techniques to manage and share spatial data. OrbisGIS is able to process vector and raster data models. It can execute processes like noise maps or hydrology process without any add-ons. Are available but are very limited for the time-being. The developers are still working on the documentation.
You may want to look elsewhere until this project gets sturdy up on its feet. Another option is R. Because it does not rely on a GUI, some people find it tricky to get started. But once you figure out the syntax and command-line workflow, it is undoubtedly one of the most powerful GIS systems going. Regarding gestatistics, it simply trounces competitors due to the vast array of contributed packages provided by statisticians: A great introductory resource on R for spatial data is provided by James Cheshire and myself and is free to download here: Note the opening quote by Gary Sherman who created QGIS: “With the advent of ‘modern’ GIS software, most people want to point and click their way through life. That’s good, but there is a tremendous amount of flexibility and power waiting for you with the command line. Many times you can do something on the command line in a fraction of the time you can do it with a GUI.”.
Nice article. A few comments about FalconView. FalconView was originally part of a flight planning software suite developed by Georgia Tech for the National Imagery and Mapping Agency (NIMA, the predecessor to NGA). It allowed military pilots to use digital versions of NIMA flight planning charts, including taking their flight plans and overlaying the plans on the charts. Pilots could also overlay multiple point symbols on the charts. Others soon discovered it was useful for making and printing basic maps quickly.
I haven’t used it in years. It looks like GT continues to add functionality to the software. I am a single individual looking to map a woodland which I have just purchased. Using GIS I would like to create maps of the woodland including the locations of individual tree species,their health,ground type,animal holes etc, so that I can make informed decisions on sustainable forest management. I currently have an iPad with gps capabilities to use on the site to collect the data, and will be buying a new computer soon, but am having difficulty finding the right program to use.
Could you please help me with any suggestions about software and if it is Apple compatible many thanks John. Could you perhaps help me with some advice?
Download Excel Heat Transport Software Fds-smv For Mac
I’ve been typesetting an annual South Africa wine guide for 17 years and, more or less by default, have been drawing the maps that show the locations of the wineries. I’ve been doing these in CorelDraw, usually tracing an image of a map imported into a layer reserved for that. There are 20-odd maps showing the locations of several hundreds of wineries. I would love to be able to do this properly, using real-world co-ordinates, and showing the topography. I would like to add all the wineries, and output windows showing specific regions at different scales (some maps cover large areas; other cover much smaller areas densely populated with wineries). Where should I start? I’d like at least to begin with free software, to see whether I get the hang of it.
Can you suggest what would be the best to start with? Many thanks Gawie du Toit. I should probably write a whole article how to do this, but I’ll go ahead and list the steps below. Step 1) You’ll need to download GIS software and data. My suggestion is to use QGIS and Natural Earth data. The reason why you’ll want to use Natural Earth is because it’s completely public use and they give permission to modify, disseminate and use the data in any manner. Here’s how to download – Step 2) The next thing you’ll have to do is go into the ‘Quick Start’ folder in Natural Earth and open up the.QGS file in QGIS by double clicking it.
Step 3) I don’t know if you have coordinates for each winery or not. Either way, you’ll have to create a shape file with each winery.
This might take some time, but once it’s created you will always have that data to work with as a layer. There’s a button on the left panel ‘New Shapefile Layer’. Make sure you choose ‘Point’. Give the shape file a name.
You can add fields to your shapefile, which are like columns in a spreadsheet. For example, you can add the field ‘NAME’ as TEXT 100 length, which will be each winery name. Click ‘ADD FIELD TO LIST’ and save your shape file somewhere.
STEP 4) Now, it’s time to add point locations on the map. You’ll need some imagery to see where each winery point should go. Go to Plugins Manage and Install Plugins Search for the Open Layers plugin and Install it. Under Web OpenLayersPlugin, you can add Google, Bing or OpenStreetMaps imagery to QGIS. STEP 5) Finally, you can add points to your shape file.
In the Digitizing Toolbar (usually at the top), click the pencil icon to toggle on editing. Click the ‘Add Feature’ button to add points to the map. Keep on adding points until you have all the wineries.
To create a professional looking map, you can use the Natural Earth data as you’re basemap. Using QGIS Composer, you can add cartographic elements like a scalebar, north arrow, title, etc Export as an image file or PDF. For purposes of my thesis, I plan to use qgis to map a spatial data layer of average agricultural yield of different crops in Colombia (such as coffee, sugarcane, oilseed, etc.) over a shapefile of Colombia divided in all its 1105 municipios and 33 departments (states). At the end, I would like to obtain a complete picture of the agro-climatical suitability of different crops per municipio in Colombia.
However I have some problems. Firstly, I have some problems finding the needed data in the right format. Does somebody knows a database where I can find such shapefiles as I need from Colombia? For the data on average agro-climatical yield, I was told to look at United Nations FAO’s website for GAEZ maps , however I only seem to obtain.jpeg images from this site, not really useful Does somebody has some experience in this field and knows where I can find the data? Lastly, I am a beginner with qgis, or gis software, so a short tutorial on how to map different spatial data layers on each other would be very welcomed! Thanks in advance!
Hi Sophie The first link is just an image. You are going to need the GIS dataset found at the FAO GeoNetwork. You’ll find it in the search by typing “crop suitability”. Each crop (maize, cereals, vegetables, etc) has its own data set. Values in it range from 0 as very marginal to 100 as very high. For the Colombia municipalities, go to the Esri Open Data Hub and search for Colombia sub regions or municipalities. It should turn up there, or directly contact Esri Colombia.
These links are found here: As for the analysis, it depends on what you want to do with it. A common analysis is measuring suitability per municipality by creating a pivot table report. Here are the steps to do this: 1. Add the two data sets by dragging the.SHP and GRID files in. From here you can work with the crop suitability raster data as is, or convert to vector. If you have a vector, the GroupStats plugin will help you summarize by municipality.
If you are working with crop suitability as a raster, then you can use the “Grid Splitter” plugin with the municipalities as the cut layer. Calculate the area in hectares for each municipality.
In Excel, take the average ‘suitability value’ per municipality. Now, you might have to do this for a lot of different crop types and their suitability. In this case, you might want to create a ‘Processor Model’ to automate the workflow for each crop suitability.
Since you are going to be out in the field I would recommend two applications. The first I’d suggest is QGIS. The reason is because it has a good field app for Android called QField for QGIS Experimental.
Basically, the app helps you get data from the field to the office efficiently in a minimalist way. I’ve heard good things but haven’t tried it myself.
It has 4.2 stars out of 5 so it can’t be too bad. Another option is using Collector for ArcGIS in combination with ArcGIS Online. It has an app for Android and Apple. It does give you a certain amount of credits where you can use it for free, or a free trial for a period of time. Collector is solid, but Esri is a commercial software company that eventually wants to make you a customer. It’s a good way to test out the product, but you have to realize that you don’t get the full-blown thing with a limit. Hope this helps.
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As a field ecologist most of my mapping requirements can be achieved using Google Earth or similar. However I have a local government client who requires shape files to import into ArcGIS. These will need to match ortho-photos. The cost of ArcGIS isn’t warranted and QGIS looks possible but it looks like QGIS doesn’t output files in an.shp format, is that easy to remedy? I also would like to work with the LENZ data set, This has 15 raster layers covering the whole of NZ on a 100m grid with numerically defined environmental parameters. I looked at your list and shortened it to QGIS, Grass, ILWIS, GEOda and OpenJump.
If possible I only want one gis system, preferably one that is reasonably intuitive as my level might be described as 1 day introductory with ArcGIS.
68 separable. This term is sometimes referred to as the baroclinic torque, and it is responsible for generating vorticity due to the non-alignment of pressure and density gradients. In versions of FDS prior to 6, the inclusion of the baroclinic torque term was found to sometimes cause numerical instabilities. If it is suspected that the term is responsible for numerical problems, it can be removed by setting BAROCLINIC=.FALSE. On the MISC line. For example, in the simple helium plume test case below, neglecting the baroclinic torque changes the puffing behavior noticeably. In other applications, however, its effect is less significant.
For further discussion of its effect, see Ref. Example Case: Flowfields/helium2disothermal This case demonstrates the use of baroclinic correction for an axially-symmetric helium plume. Note that the governing equations solved in FDS are written in terms of a three dimensional Cartesian coordinate system.
However, a two dimensional Cartesian or two dimensional cylindrical (axially-symmetric) calculation can be performed by setting the number of cells in the y direction to 1. An example of an axially-symmetric helium plume is shown in Fig &HEAD CHID='helium2disothermal',TITLE='Axisymmetric Helium Plume' / &MESH IJK=72,1,144 XB=0.00,0.08,-0.001,0.001,0.00,0.16, CYLINDRICAL=.TRUE. / &TIME TEND=5.0 / &MISC DNS=.TRUE., ISOTHERMAL=.TRUE. / &RADI RADIATION=.FALSE.
/ &SPEC ID='HELIUM' / &SURF ID='HELIUM', VEL=-0.673, MASSFRACTION(1)=1.0, TAUMF(1)=0.3 / &VENT MB='XMAX',SURFID='OPEN' / &VENT MB='ZMAX',SURFID='OPEN' / &OBST XB= 0.0,0.036,-0.001,0.001,0.00,0.02, SURFIDS='HELIUM','INERT','INERT' / &DUMP PLOT3DQUANTITY(1)='PRESSURE',PLOT3DQUANTITY(5)='HELIUM' / &SLCF PBY=0.000,QUANTITY='DENSITY', VECTOR=.TRUE. / &SLCF PBY=0.000,QUANTITY='HELIUM' / &TAIL / Figure 6.5: Simulation of a helium plume Special Topic: Large Eddy Simulation Parameters By default FDS uses the Deardorff 10, 11 turbulent viscosity, (µ LES /ρ) = C ν k sgs (6.4) where C ν = 0.1 and the subgrid scale (sgs) kinetic energy is taken from an algebraic relationship based on scale similarity (see the FDS Technical Reference Guide 1). The LES filter width is taken as the maximum cell dimension, = max(δx,δy,δz). This selection is intended to promote the use of cubic grid cells, which are optimal for isotropic turbulent flows typical of thermally-driven fire plumes. Alternatively, you may invoke the geometric mean definition of the filter width, = (δxδyδz) (1/3), by setting LESFILTERWIDTH= MEAN on MISC. Options for the TURBULENCEMODEL on the MISC line are listed in Table 6.1. Note that the model used in FDS versions 1-5 is CONSTANT SMAGORINSKY.
The thermal conductivity and material diffusivity are related to the turbulent viscosity by: k LES = µ LES c p Pr t; (ρd) LES = µ LES Sc t (6.5) 42 69 The turbulent Prandtl number Pr t and the turbulent Schmidt number Sc t are assumed to be constant for a given scenario. Although it is not recommended for most calculations, you can modify Pr t = 0.5, and Sc t = 0.5 via the parameters PR, and SC on the MISC line. A more detailed discussion of these parameters is given in the FDS Technical Reference Guide 1.
Table 6.1: Turbulence model options. TURBULENCEMODEL Description Coefficient CONSTANT SMAGORINSKY Constant coefficient Smagorinsky model 12 CSMAGORINSKY DYNAMIC SMAGORINSKY Dynamic Smagorinsky model 13, 14 None DEARDORFF Deardorff model 10, 11 CDEARDORFF VREMAN Vreman s eddy viscosity model 15 CVREMAN Special Topic: Numerical Stability Parameters FDS uses an explicit time advancement scheme; thus, the time step plays an important role in maintaining numerical stability and accuracy. Below we examine the constraints on the time step necessary for stability in the presence of advection, diffusion, and expansion of the velocity and scalar fields. In addition, there are additional constraints that ensure accuracy of various algorithms. The Courant-Friedrichs-Lewy (CFL) Constraint The well-known CFL constraint given by CFL = δt u δx 0 therefore leads to the following restriction on the time step: δt.
86 Figure 7.1: An example of the multiplier function. This has the effect of making an array of obstructions according to the following formulae: x1 = x1 + DX0 + i DX; ILOWER i IUPPER x2 = x2 + DX0 + i DX; ILOWER i IUPPER y1 = y1 + DY0 + j DY; JLOWER j JUPPER y2 = y2 + DY0 + j DY; JLOWER j JUPPER z1 = z1 + DZ0 + k DZ; KLOWER k KUPPER z2 = z2 + DZ0 + k DZ; KLOWER k KUPPER In situations where the position of the obstruction needs shifting prior to the multiplication, use the parameters DX0, DY0, and DZ0. A variation of this idea is to replace the parameters, DX, DY, and DZ, with a sextuplet called DXB. The six entries in DXB increment the respective values of the obstruction coordinates given by XB. For example, the x coordinates are transformed as follows: x1 = x1 + DX0 + n DXB(1); NLOWER n NUPPER x2 = x2 + DX0 + n DXB(2); NLOWER n NUPPER Notice that we use NLOWER and NUPPER to denote the range of N.
This more flexible input scheme allows you to create, for example, a slanted roof in which the individual roof segments shorten as they ascend to the top. This feature is demonstrated by the following short input file that creates a hollowed out pyramid using the four perimeter obstructions that form the outline of its base: &HEAD CHID='pyramid', TITLE='Simple demo of multiplier function' / &MESH IJK=100,100,100, XB=0.0,1.0,0.0,1.0,0.0,1.0 / &TIME TEND=0. 103 the thermal properties of each, along with estimates of the reference temperatures as described above. The foam might be described as follows: &MATL ID = 'FOAM' SPECIFICHEAT = 1.0 CONDUCTIVITY = 0.05 DENSITY = 40.0 NREACTIONS = 1 SPECID = 'FUEL' NUSPEC = 1. REFERENCETEMPERATURE = 350. HEATOFREACTION = HEATOFCOMBUSTION = / Note that these properties are completely made up.
Both the fabric and the foam decompose into fuel gases via single-step reactions. The fuel gases from each have different composition and heats of combustion.
FDS automatically adjusts the mass loss rate of each so that the effective fuel gas is that which is specified on the REAC line. The same couch model is included in a room-scale fire simulation, known as the roomfire test case. Figure 8.2 shows the fire after 5 min. Only the reaction zone of the fire is shown; the smoke is hidden so that you can see the fire progressing along the couch.
![Heat Heat](https://www.exceldemy.com/wp-content/uploads/2018/02/formatting-pic-1.png)
Figure 8.2: Output of roomfire test case showing fire on the couch at 5 min Shrinking and swelling materials Many practical materials change in thickness during the thermal reactions. For example: Non-charring materials will shrink as material is removed from the condensed phase to the gas phase. Porous materials like foams would shrink when the material melts and forms a non-porous layer. 77 104 Some charring materials swell, i.e., get thicker, when a porous char layer is formed. Intumescent fire protection materials would swell significantly, creating an insulating layer. In FDS, the layer thickness is updated according to the ratio of the instantaneous material density and the density of the material in its pure form, i.e., the DENSITY on the MATL line. In cases involving several material components, the amount of swelling and shrinking is determined by the maximum and sum of these ratios, respectively.
In mathematical terms, this means that in each time step the size of each condensed phase cell is changed according to the ratio δ ( ρs,i max i δ = ( ρs,i i ) ) ρ i ρ i if max i ( ρs,i ρ i ) 1 if max i ( ρs,i ρ i ) 0) or t 2 ramp (TAUVF0) or t 2 ramp (TAUVF 0) or t 2 ramp (TAUFAN. 123 Jet Fans Fans do not have to be mounted on a solid wall, like a supply or an exhaust fan. If you just want to blow gases in a particular direction, create an obstruction OBST and apply to it VENT lines that are associated with a simple HVAC system. This allows hot, smokey gases to pass through the obstruction, much like a free-standing fan. See the example case jetfan.fds which places a louvered fan (blowing diagonally down) near a fire (see Fig.
You may also want to construct a shroud around the fan using four flat plates arranged to form a short passageway that draws gases in one side and expels them out the other. The obstruction representing the fan can be positioned about halfway along the passage (if a louvered fan is being used, place the fan at the end of the passage). Figure 9.4: Jet fan with a louvered output UVW=-1,0, HVAC Filter Parameters A sample input for a filter is given by: &HVAC TYPE ID='FILTER', ID='filter 1', LOADING=0., SPECID='SOOT', EFFICIENCY=0.99, LOADINGMULTIPLIER=1, CLEANLOSS=2., LOSS=100./ where: CLEANLOSS is the flow loss through the filter when it is new (zero loading). EFFICIENCY is an array of the species removal efficiency from 0 to 1 where 0 is no removal of that species and 1 is complete filtration of the species. The species are identified using SPECID.
LOADING is an array of the initial loading (kg) of the filter for each species being filtered. LOADINGMULTIPLIER is an array of the species multiplier, M i, used in computing the total filter loading when computing loss. LOSS invokes a linear flow loss model where the flow loss, K, is given as a linear function of the total loading, K f ilter = K CLEANLOSS + K LOSS (L i M i ), where L i is the species loading and M i is a multiplier. Only one of LOSS or RAMPID should be specified. 97 124 RAMPID identifies the RAMP that contains a table of pressure drop across the filter as a function of total loading (the summation term given in the defintion of LOSS above).
Only one of LOSS or RAMPID should be specified. SPECID identifies the tracked species for the inputs of LOADINGMULTIPLIER and LOADING. A sample set of filter inputs is shown below. These lines define a filter that removes the species PARTICULATE with 100% efficiency. The filter has an initial flow loss of 1 and that loss increases by a factor of 7332 for each kg of PARTICULATE captured by the filter.
For further details see the sample case HVACfilter, which is documented in the Verification Guide. &SPEC ID='PARTICULATE',MW=28.,MASSFRACTION0=0.001,SPECIFICHEAT=1./ &HVAC TYPEID='NODE',ID='FILTER',DUCTID='DUCT1','DUCT2',XYZ(3)=0.55,FILTERID='FILTER'/ &HVAC TYPEID='FILTER',ID='FILTER',CLEANLOSS=1.,SPECID='PARTICULATE',EFFICIENCY=1., LOSS=,LOADINGMULTIPLIER=1./ Note that a filter input refers to a class of filters and that multiple ducts can reference the same filter definition HVAC Aircoil Parameters An aircoil refers to a device that either adds or removes heat from air flowing through a duct.
In a typical HVAC system this is done by blowing the air over a heat exchanger (hence the term aircoil) containing a working fluid such as chilled water or a refrigerant. A sample input line is as follows: &HVAC TYPEID='AIRCOIL', ID='aircoil 1', DEVCID='device 1', EFFICIENCY=0.5, COOLANTSPECIFICHEAT=4.186, COOLANTTEMPERATURE=10., COOLANTMASSFLOW=1./ where: COOLANTMASSFLOW is the flow rate of the working fluid (kg/s). COOLANTSPECIFICHEAT is the specific heat (kj/(kg K)) of the working fluid. COOLANTTEMPERATURE is the inlet temperature of the working fluid ( C). DEVCID is the name of a device controlling the operation of the aircoil. A CTRLID can be used as an alternative. EFFICIENCY is the heat exchanger efficiency, η, from 0 to 1.
A value of 1 indicates the exit temperatures on both sides of the heat exchanger will be equal. FIXEDQ is the constant heat exchange rate. A negative value indicates heat removal from the duct. The heat exchange rate can be controlled by either RAMPID or by TAUAC. TAUAC defines a tanh (TAUAC0) or t 2 ramp (TAUAC.