Solar Energy | Genesis Lab

Generating Building Envelopes Using Multi-Objective Optimization Techniques

Wed, 27 Apr 2016 00:00:00 +0000

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Opto-Geometric Modelling of Complex Urban Landscapes

Wed, 27 Apr 2016 00:00:00 +0000

Generative Solar-Climatic Configuration

Mon, 01 Jan 0001 00:00:00 +0000

The complete thesis is under a temporary embargo until we publish the results of the research in a peer-reviewed journal article that is in preparation. Team: Ir. A. Kassiani Florou, Dr.ir. P. Nourian, Ir. S.Azadi

The typical solar energy potential simulation workflows used in the AEC industry require an abundance of information regarding the detailed geometry and materialization of the design. These requisites render them incompatible with early-stage design decision-making pertaining to form-finding. By performing solar energy potential simulations at the pre-conceptual design phase, the necessary time for later-stage environmental assessments and design improvements is reduced considerably, while building designs with high performance but low environmental footprint are attained. This research proposes a computational framework to navigate voxel-based morphologies of building envelopes in a performative design space. It investigates a generative workflow through an embedded multi-criteria optimization of solar-related indicators, which are mapped in a solar energy potential field. The formulation of this field consists of an a priori assessment of the solar energy potential in every discrete volumetric unit (voxel) and a vectorized description of the interdependency of them. The astronomical size of this solution space renders the use of metaheuristic methods more appropriate. More specifically, a subtractive strategy that incorporates an MCDA approach is being applied in order to reach user-defined optimization targets. The novelty and potential of the proposed methodology lies in streamlining the early decision making process for designers and architects and expanding the morphological possibilities. Through this framework, the performative design space is effectively navigated and nearly optimal solutions are generated, to act as suggestive mechanisms for informed architectural decisions.

A Computational Method to Generate One-story Floor Plans

Wed, 27 Apr 2016 00:00:00 +0000

Generative Design for Smart Regulations

Sat, 06 Feb 2021 16:49:47 +0000

Generative Solar-Climatic Configuration

Sat, 06 Feb 2021 16:49:47 +0000

Background and aim:

Early design decisions have great influence on final energy performance and comfort of buildings. Proper consideration of such influences requires using simulation engines. The existing simulation methods can be too data demanding and slow for early stage computational design explorations (e.g. in optimization loops or form-finding). The aim of this project is to devise and prototype fast and design-friendly simulation methods for generative design of optimal envelopes.

Research question:

How to adapt and develop direct sunlight and view-shed simulation methods for generation of optimal envelopes?

Design objective:

To design and prototype a suite of generative methods for fair and optimal provision of solar irradiation, radiative cooling potential and view shed.

Methods:

Spatial Computing (Computational Geometry & Linear Algebra)
Physical Analysis of Light and Principles of Naturally Lit Design
Computer Programming (Python or C#)

Maximizing Solar Electricity Yield

Sat, 06 Feb 2021 16:49:47 +0000

Background and aim:

Early design decisions have great influence on final energy performance and comfort of buildings. The costs of installation, maintenance, and the eventual replacement of solar panels cannot be ignored in the financial outlook of a building. This project aims to develop procedures for including such financial considerations in addition to architectural factors in optimal configuration of solar panels.

Research question:

How to configure an optimal array of photovoltaic cells on a building envelope so as to maximize solar electricity yield subject to architectural and economic constraints?

Design objective:

To computationally configure an optimal array of photovoltaics on a building envelope.

Methods:

Spatial Computing (Computational Geometry & Linear Algebra)
Ladybug Recipes (environmental simulation workflows)
Computer Programming (Python)