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Dynamo visual programming – BIM and LEED

AUTORI: Edoardo Maroder & Damiano Di Ciaccio

Dynamo visual programming – BIM and LEED: implementing design data to streamline the process


The need to manage the complexity and the whole aspects of sustainability of buildings, requires from designers (and owners as well) to manage tools able to support them in decision-making process. Indeed, the more the facility is complex, the higher is the complexity that steers the resource-assignment.

In this context, LEED® (Leadership in Energy and Environmental Design) is one of the most used and proved protocol of sustainability, which aims to implement an iterative design process, in which stakeholders and professionals are involved in: in the following lines, is showed how is possible to optimize the water-use of a building facility, allowing a sensitive saving of this important natural element, always rarer.


LEED protocol focuses on indoor and outdoor water consumption in order to increase efficiency and to reduce the redundant usage of water resources due to the development and the operation within the built environment.

The intent of Indoor Water Reduction prerequisite and credit is to reduce the indoor water consumption. LEED rating system requires a minimum 20% reduction and rewards designers who achieve better performance (5% more is worth 1 point, up to 6 points plus 1 point in the exemplary performance section). So the first step is to install performing fixtures and fittings able to use 20% up 60% less water than the established baseline. To achieve this goal, it’s possible to install WaterSense labelled products or to follow the Alternative Compliance Path which aims to demonstrate the indoor water use reduction analysing a group of parameters available on the Reference Guide and on fixtures cut sheet.

To demonstrate these savings it’s needed to apply the following formula (explained in the reference guide) to each fixture type.

Let’s go through each parameter:

  • Fixture Flush: it’s a fixture’s data which should lead us during the “efficiency first”strategy. It can be expressed in liter per minute or liter per flush. In the second case, it is not needed the duration of use.
  • Duration of use: it’s the assessment of the fixture-usage-time by a user in a single session use.
  • Uses per person per day: times people usually use each fixture per day.
  • Users: this number could be implemented as a design result or can be obtained from index (gross square meters per occupant) defined in Appendix 2 in the Reference Guide.

The Equation 1 must be performed to calculate both the baseline of water consumption and the design case water consumption. Then it is possible to obtain the rate of reduction. The result will provide us if the minimum requirement is met (W.E. – prereq.1) and, eventually, the points achieved (W.E.- credit.2)


It’s evident that water efficiency data depends on fixture types and specifications, and building in which they are installed and its occupation rate as well.

All these information can be (or, better, should be) implemented within the BIM model of the building which should reproduce and provide all data, regarding its components related to each disciplines.

Therefore, it’s quite credible the hypothesis to have plumbing fixture information and a valuation of how many people will affect the use of indoor water.

Starting from these basic data we aim to create an automatic workflow which collects this data from the BIM model and treats them in order to verify the achievement of thresholds shown in table 1.

The result is an user-friendly application able to perform LEED’s formulas, requiring few easy inputs (reachable in the Reference Guide) and a geo-localized BIM model, which is the prerequisite to explore the computational design method.

We are now going to analyse an applying example to understand deeply the work method and the potentiality of this kinds of process.


One of the most important things to do is to “prepare” data within the BIM model in order to be easily found and treated once we start computational design. This fundamental step requires a pre-design phase in which it’s needed a rigorous organization (workflow strategy, parameters, steps, …) to avoid biggest obstacles may occur and, sometimes, force us to go back and restart again with a new strategy.

Therefore, starting with generic plumbing fixture Revit families, we are going to follow this strategy to make BIM model coordinated with computational design workflow:

  • Insert within “comments” parameter the type of the fixture (WC, Faucet, Shower, Kitchen sink), in order to avoid difficulties related to different family-names which fixtures may have, causing obstacles in collecting similar appliances.(e.g. Different shower fixtures may have different names depending on the producers who provides us the <.rfa> file, while analytic plumbing data are the same).
  • Consider a common parameter, between each kind of fixtures, where to insert flow data so to streamline the collecting phase in dynamo, with a recurring strategy. [lpf: liter per flush (l) ; lpm: liter per minute (l/m)].
  • Make a valuation of building users by analysing apartments composition.


Once strategy is thought, the dynamo script can be started. The result we expect is similar groups of nodes, one each type of fixture, from which it’s possible to calculate the actual performance (Revit parameter) and the baseline performance (LEED’s table inputs); to complete the formula we have also to implement users (given data), uses per day and, if needed, duration of use (Table 8 and Table 9).

The base script is as follow:

To streamline this phase it’s possible to edit a custom node which allow to complete just the fundamental inputs, so to have a faster and smarter workflow which is also easier to control and to use.

After applying this workflow to each plumbing fixture within Revit model, results have to be added and compared to have the percentage of improvement, required by LEED process. Supporting with a simple script, it’s possible to have calculated point earned directly here.


The increasing need of data management, due to the actual complexity of the design strategy, is creating a strong relationship between AEC world and digital technologies. Consequently, to improve their performance in terms of product-quality, designers should develop new strategies, taking advantage of big IT potentiality which allow them to create customized way to overview or even imagine projects.

The application shown has been perceived in this way: once we implement information within BIM model (the only pressing condition) why shouldn’t we go further? The possibility now we have is to transform the design into a real integrative process in order to handle the complexity and to aim towards harder challenges in terms of sustainability and human health.