performancereports_adjacentbuildingsFigure: Example of performance analysis reports.

Task 1 – Identification of requirements

In this first task, requirements for building renovation, ES, design drafting, and tool operability standpoints are identified. The result of this task will be a list of prerequisites to be satisfied in the subsequent tasks.

Task 2 – Formulation of the mathematical models

The development of the renovation optimization procedure to improve the building’s EE and IEQ requires the identification of appropriate decision variables and constraints, and the definition of suitable design actions as their cost. The optimization objectives will be then formulated. As these may be conflicting, the chosen methodology must compute non-dominated solutions to find a compromise one, where the preferences of the decision maker are essential in the evaluation procedure.

Task 3 – Development of the generative and optimization algorithms

According to the mathematical models formulated in previous Task 2, three core algorithms will be developed in this task. The first algorithm consists in a design generation space allocation algorithm and it will be adapted to incorporate a larger set of design elements and requirements. It is a hybrid evolutionary strategy enhanced with a local search method. It is able to incorporate geometric and topological requirements and preferences. The second algorithm is a sequential variable optimization procedure. According to the user design strategy, a set of design variables are transformed aiming to explore the improvement potential of the floor plans generated by the previous algorithm, thus reducing the degree-hours of thermal discomfort. It will be adapted to incorporate detailed construction specifications for each building element. The third and last algorithm is an Evolutionary Algorithm (EA) and its purpose is to optimize the CS and the ES according to the chosen building renovation design actions. This algorithm aims to improve the building’s EE and IEQ in a CC effective manner.

Task 4 – Development of ANN and cloud point algorithms

In this task, complementary algorithms will be developed to reduce the computation time of the optimization algorithms developed in Task 3 and to reduce the manual work in creating surfaces from point clouds. So, two subtasks will be carried out. The first will develop and train an ANN as a fast estimation mechanism of the buildings performance, thus avoiding the use of dynamic simulation, and reduces the computation time required by the optimization process. The second algorithm will be developed to identify surfaces from immense number of points that result from 3D scanning of the existing building.

Task 5 – Implementation of the tool graphical interface

In this task, the tool graphical interface will be implemented and the tool backoffice system to manage the different ES and CS, as also the algorithms’ specifications. The developed algorithms in the previous tasks are integrated in the BIM add-on tool workflow. This task will develop the tool prototype and will have the usability and accessibility tests feedback from Task 6.

Task 6 – Validation and usability tests

Task 6 involves a set of tests to feedback the implementation task on usability and accessibility of the graphical interface from ergonomic human-interface criteria. It also comprehends the validation and verification of the prototype tool features and functions.

Task 7 – Case studies

In this task it is intended to apply the renovation tool to different scenarios of interventions. In the first set of case studies it is considered the residential typology, with smaller scale. In the second set of case studies large-scale typologies such as service buildings renovations or industrial buildings adaptation to new uses will be addressed. The results of these cases will be used as showcases in the tool dissemination material.