Hone

Hone is an optimisation tool that allows you to find the optimal building design whilst saving time and cost

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Overview

  • Independent tool to optimise VE models
  • Use Hone to converge on your final and optimal design quickly and accurately
  • Fully customisable Optimisation Worksheets can be created and shared to create optimisation approaches for quality and repeatability for all users
  • Worksheets feature allows non-expert users to use the tool readily

> Technical Details

Images


Hone - Pre Simulation

Hone with Worksheet Configured

Hone - Post Simulation

Hone with Model Image - Post Simulation

Pareto Progress Charts

Hone Results Output

Technical Details

An outcome of the R&D project UMBRELLA, Hone is a standalone tool that references a VE model with the advantage being that the VE can still be used whilst any optimisation is being performed. It is completely customisable even down to the graphics rendered, making it an ideal tool for expert users. The tool can be found in the Programs menu under IES >> Virtual Environment 2017 alongside the VE shortcut.

Input

First time users can use the Elements tool to create inputs for the Hone tool. The tool helps select variables and outputs, which are then converted into Scripts.

Input variables can be referenced from any VE model:

  • Use ‘tags’ to vary most input variables
  • Linked via APR
  • Use Elements tool or scripts to define approach

Worksheets

Optimisation worksheets provides a link between the problem domain and the optimisation algorithm. With the aid of prepared worksheets, the user will gain the opportunity to undertake a several optimisation studies. The readily available studies accessible to the user are as follow:

  1. Minimising Conditioning Energy and Maximising Comfort
  2. Optimising Humidity Levels for Comfort and System’s Energy

Pareto

The Pareto front represents the trade-off curve that highlights the balance between the two or more potentially conflicting objectives. The Pareto curves are updated after every evaluation of the cost function to represents the set of optimal solutions.

  • The Pareto curve helps in making the informed decision about the cost of the implementation of different variable setting of the model under study
  • The Pareto Summary chart plots the objective values for the first and last two generations to illustrate the progression of the optimisation study
  • The Pareto Progress chart plots a set of optimal solutions and is the result of the Hone study

The results of the Hone study are outputted into an excel worksheet and can be appropriately reformatted at wish to emphasise the trade-off between the objectives of the study.
 

Hone User Guide