Author Topic: Can the height of adjustable barriers be different in each scenario?  (Read 1459 times)


  • Administrator
  • Full Member
  • *****
  • Posts: 156
NoiseMap allows you to define 10 level adjustment layers which you can then apply to any or all barriers.
For example, you could set Level 1 to be 0.5 m, Level 2 could be 1.0 m, Level 3 could be 2.0 m and Level 4 could be 3.0 m.
You can then apply any or all of these levels to any noise barrier. The selected levels are then added to the height already assigned to that barrier.

Thus, suppose a barrier is defined as having a height of 40 m above datum.  If you assign adjustment level 1 to that barrier, a height of 40.5 m will be used in the calculation.
If you assign both adjustment level 1 and adjustment level 2 to that barrier, a height of 41.5 m will be used in the calculation.
If you assign adjustment levels 2 and 4 to that barrier, then a height of 44.0 m will be used in the calculation.

The adjustment levels of a barrier can be different in each scenario.

However, there is only one set of adjustment levels in a model and these apply to every scenario. So if you change the levels of the adjustments, for instance in the above example you change level 3 from 2.0 m to 1.5 m, this will affect the height of every barrier which uses adjustment level 3.  But this will not automatically invalidate any calculation that depends on adjustment level 3.

We therefore strongly recommend that when using adjustment layers, that you decide on their heights and do not then change them once you have started calculations.
If you change the adjustment levels assigned to a barrier, this does invalidate the affected results, thus warning you of potential inconsistencies.

Whilst it might seem a quick solution to change the adjustment level value rather than going through the barriers and clicking on the check boxes, you still need to create a different scenario if you want to save a calculated contour, and unless you are careful to name the scenario carefully, you will not have any record of changes in assumptions so QA will be more difficult.