A hierarchical decomposition approach for multi-level building design optimization

2021 ◽  
Vol 44 ◽  
pp. 103272
Author(s):  
Yin Li ◽  
Nima Bonyadi ◽  
Ashleigh Papakyriakou ◽  
Bruno Lee
Keyword(s):  
Design Optimization ◽  
Building Design ◽  
Hierarchical Decomposition ◽  
Decomposition Approach ◽  
Multi Level ◽  
Level Building

scholarly journals Automatic Reconstruction of Multi-Level Indoor Spaces from Point Cloud and Trajectory

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3493
Author(s):  
Gahyeon Lim ◽  
Nakju Doh
Keyword(s):  
Point Cloud ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Complex Environments ◽  
Indoor Space ◽  
Multi Level ◽  
Level Building ◽  
Indoor Spaces ◽  
Data Term

Remarkable progress in the development of modeling methods for indoor spaces has been made in recent years with a focus on the reconstruction of complex environments, such as multi-room and multi-level buildings. Existing methods represent indoor structure models as a combination of several sub-spaces, which are constructed by room segmentation or horizontal slicing approach that divide the multi-room or multi-level building environments into several segments. In this study, we propose an automatic reconstruction method of multi-level indoor spaces with unique models, including inter-room and inter-floor connections from point cloud and trajectory. We construct structural points from registered point cloud and extract piece-wise planar segments from the structural points. Then, a three-dimensional space decomposition is conducted and water-tight meshes are generated with energy minimization using graph cut algorithm. The data term of the energy function is expressed as a difference in visibility between each decomposed space and trajectory. The proposed method allows modeling of indoor spaces in complex environments, such as multi-room, room-less, and multi-level buildings. The performance of the proposed approach is evaluated for seven indoor space datasets.

scholarly journals Automated Storey Separation and Door and Window Extraction for Building Models from Complete Laser Scans

2021 ◽  
Vol 13 (17) ◽  
pp. 3384
Author(s):  
Kate Pexman ◽  
Derek D. Lichti ◽  
Peter Dawson
Keyword(s):  
Building Design ◽  
Point Clouds ◽  
Heritage Sites ◽  
Building Models ◽  
Significant Research ◽  
Heritage Buildings ◽  
Floor Plans ◽  
Multi Level ◽  
Dimensional Errors ◽  
Work Done

Heritage buildings are often lost without being adequately documented. Significant research has gone into automated building modelling from point clouds, challenged by irregularities in building design and the presence of occlusion-causing clutter and non-Manhattan World features. Previous work has been largely focused on the extraction and representation of walls, floors, and ceilings from either interior or exterior single storey scans. Significantly less effort has been concentrated on the automated extraction of smaller features such as windows and doors from complete (interior and exterior) scans. In addition, the majority of the work done on automated building reconstruction pertains to the new-build and construction industries, rather than for heritage buildings. This work presents a novel multi-level storey separation technique as well as a novel door and window detection strategy within an end-to-end modelling software for the automated creation of 2D floor plans and 3D building models from complete terrestrial laser scans of heritage buildings. The methods are demonstrated on three heritage sites of varying size and complexity, achieving overall accuracies of 94.74% for multi-level storey separation and 92.75% for the building model creation. Additionally, the automated door and window detection methodology achieved absolute mean dimensional errors of 6.3 cm.

scholarly journals On the performance of meta-models in building design optimization

2018 ◽  
Vol 225 ◽  
pp. 814-826 ◽  
Author(s):  
A. Prada ◽  
A. Gasparella ◽  
P. Baggio
Keyword(s):  
Design Optimization ◽  
Building Design

scholarly journals Multi-Level Modeling Methodology for Optimal Design of Electric Machines Based on Multi-Disciplinary Design Optimization

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4173
Author(s):  
Zehua Dai ◽  
Li Wang ◽  
Lexuan Meng ◽  
Shanshui Yang ◽  
Ling Mao
Keyword(s):  
Power Systems ◽  
Design Optimization ◽  
Synchronous Generator ◽  
Electric Machines ◽  
Modeling Method ◽  
System Level ◽  
Superior Performance ◽  
Efficient Design ◽  
Modeling Methodology ◽  
Multi Level

The transportation sector is undergoing electrification to gain advantages such as lighter weight, improved reliability, and enhanced efficiency. As contributors to the safety of embedded critical functions in electrified systems, better sizing of electric machines in vehicles is required to reduce the cost, volume, and weight. Although the designs of machines are widely investigated, existing studies are mostly complicated and application-specific. To satisfy the multi-level design requirements of power systems, this study aims to develop an efficient modeling method of electric machines with a background of aircraft applications. A variable-speed variable-frequency (VSVF) electrically excited synchronous generator is selected as a case study to illustrate the modular multi-physics modeling process, in which weight and power loss are the major optimization goals. In addition, multi-disciplinary design optimization (MDO) methods are introduced to facilitate the optimal variable selection and simplified model establishment, which can be used for the system-level overall design. Several cases with industrial data are analyzed to demonstrate the effectiveness and superior performance of the modeling method. The results show that the proposed practices provide designers with accurate, fast, and systematic means to develop models for the efficient design of aircraft power systems.

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