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Contributed by: [[Dipak Chirmade]]
Contributed by: [[Dipak Chirmade]]


== Real-time solver ==
== Real-time solver ==
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If we calculate dCoffee/dt we can get a graph as shown in following diagram  
If we calculate dCoffee/dt we can get a graph as shown in following diagram  


<div class="thumb tnone"><div class="thumbinner" style="width:602px;">[[Image:DTCoffee.png]] <div class="thumbcaption"><div class="magnify">[[File:DTCoffee.png|<img src="/skins/common/images/magnify-clip.png" width="15" height="11" alt="" />]]</div>Rate of change of coffee temperature with reference to environment temperature.</div></div></div>
<div class="thumb tnone"><div class="thumbinner" style="width:602px;">[[Image:DTCoffee.png]] <div class="thumbcaption"><div class="magnify">[[File:DTCoffee.png|<img src="/skins/common/images/magnify-clip.png" width="15" height="11" alt="" />]]</div>Rate of change of coffee temperature with reference to environment temperature.</div></div></div>
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As you can see, prediction after 1st step starts differing than actual measured reading meaning we needed to tune the step to get accurate simulated results.
As you can see, prediction after 1st step starts differing than actual measured reading meaning we needed to tune the step to get accurate simulated results.
[[Category:Development]]

Latest revision as of 13:18, 2 August 2010

←back to Real-time ASCEND.

Contributed by: Dipak Chirmade

Real-time solver

Runge Kutta based single step solver

Work in progress!

Real-time solver using Runge Kutta method is currently implemented as an extern method for initial testing purpose. Building a stand alone real-time solver is already in progress.

Using real-time data reader, one can calculate dCoffee/dt for cooling of coffee example. From initial test, I have collected following logs Source:dipak:models/dipak/Workspace_Broken/sensorreadings.logs

If we calculate dCoffee/dt we can get a graph as shown in following diagram

File:DTCoffee.png
Rate of change of coffee temperature with reference to environment temperature.

Todo: Application: Once we have dCoffee/dt, we can solve model like following

Qdot = h A (T_coffee - T_amb)

Qdot = - m_coffee * cp_coffee * dT_coffee / dt

where Qdot is the heat transfer rate
  h is the convection coefficient
  A is the heat transfer surface area
  T_coffee and T_amb are the coffee (+ cup) and ambient air temperatures, respectively.

  m_coffee is the mass of the coffee + cup
  cp_coffee is the average specific heat capacity of the cup + coffee etc


Following graph shows simulated results from real-time solver Vs real-reading over 10 mins of time slot.

Source can be found at: Source:dipak:models/dipak/RealtimeSolver

As you can see, prediction after 1st step starts differing than actual measured reading meaning we needed to tune the step to get accurate simulated results.