The software framework called **Rts** builds upon the precursor, **Rt**, which is posted elsewhere on this website. To understand **Rts** it is helpful to keep in mind that our objective is NOT to develop yet another computer program. Various companies, research centres, and private citizens often offer their own tools and programs, developed in various programming languages. Our proposal, an echo from OpenSees and many books on object-oriented programming, is to develop contributions to a distributed **library** of models and methods. Then we can pick & choose the models and methods we want, when we need them. Rts was created with the C++ programming language using the cross-platform development tool **Qt**. Soon you will find below examples, tutorials, open-source code, and executables for Windows and Mac.

- INSTALLATION FILES
- For Windows: Rts.exe
- For Mac: Rts.dmg

**EXAMPLES**

- To run a reliability analysis with the “CalREL limit-state function” start by storing the files Algebraic_Limit_State_Function.txt and Load_Last_These_Reliability_Analysis_Tools.txt on your computer. Then open Rts or do a Clear All if it is already running. Drag & drop the file with the limit-state function into Rts, followed by the file that contains the reliability tools. Careful with that order! To run FORM, right-click on the FORM model and select Run; notice in the input file that you can play around with different line search algorithms. The sampling model is run the same way and you can stop the analysis anytime by changing the Max Samples property.
- To run a reliability analysis with a limit-state function defined in a Java script, start by downloading the file JavaScript.txt and renaming it to JavaScript.js. In the same folder, store the file JavaScript_Limit_State_Function.txt. Following the same procedure as the first example, drag & drop the file with the limit-state function (never the .js file) into a clean Rts followed by the analysis tools, then run FORM or sampling.
- To find the root of a one-variable function, i.e., to find the variable value that gives zero function value, store the file Root_Finding.txt on your computer. Then drag & drop it into a clean Rts and run the Root Finding model. Notice that this function can be tricky; some of the line search algorithms get into trouble if the input parameters are off.
- To run a single-variable optimization analysis, i.e., to minimize a function with only one design variable, store the file Single_Variable_Optimization.txt on your computer, then drag and drop it into a clean Rts. Right-click on the optimization model and select run. Notice the delay parameter that slows down the analysis to make it easier to follow the on-screen plotting of each trial point. Also notice the collection of different line search algorithms in the input file.
- To carry out a non-gradient-based optimization with the downhill simplex algorithm, store the file Downhill_Simplex_Optimization.txt on your computer, then drag and drop it into a clan Rts. Right-click on the optimization model and select run. Notice the delay parameter that slows down the analysis to make it easier to follow the on-screen plotting of each simplex. They may be hard to see in the beginning but each simplex is a triangle for this two-variable problem.
- To carry out a gradient-based multi-variable optimization analysis with line searches along selected search directions, then store the file Directional_Line_Search_Optimization.txt on your computer, then drag and drop it into a clan Rts. Right-click on the optimization model and select run. Notice the default line search algorithm, used along each search direction, is the golden section algorithm.
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