scholarly journals Self-Organising Floor Plans in Care Homes

2020 ◽  
Vol 12 (11) ◽  
pp. 4393
Author(s):  
Silvio Carta ◽  
Stephanie St. Loe ◽  
Tommaso Turchi ◽  
Joel Simon
Keyword(s):  
Genetic Algorithm ◽  
Spatial Configuration ◽  
Care Home ◽  
Building Design ◽  
Design Solution ◽  
Floor Plan ◽  
Home Building ◽  
Spatial Layouts ◽  
Floor Plans ◽  
Behaviour Models

This paper presents and discusses an optimisation approach applied to spatial layouts in care home building design. With this study, we introduce a method for increasing the floor plan efficiency using a self-organising genetic algorithm, thus reducing energy consumption, improving the wellbeing of residents and having an implicit impact on the costs of energy and health care. In order to find an optimal spatial configuration, we elaborated and tested a number of design criteria based on existing literature reviews and interpreted through initial considerations of care home layouts. These are used as objectives in a Genetic Algorithm (GA) to evaluate the best design solution. The self-organised floor plan is then used to run a final simulation to observe how residents could use the optimised spaces and to measure the improved efficiency of the new plans. The paper concludes with the discussion of the results and some considerations for future studies and experiments using emergence behaviour models to improve sustainable development in design.

scholarly journals Impact of Window to Wall Ratio on Energy Loads in Hot Regions: A Study of Building Energy Performance

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1080
Author(s):  
Mamdooh Alwetaishi ◽  
Omrane Benjeddou
Keyword(s):  
Saudi Arabia ◽  
Building Materials ◽  
Building Design ◽  
Building Energy ◽  
Energy Performance ◽  
Design Stage ◽  
Design Solution ◽  
Building Energy Efficiency ◽  
Climatic Regions ◽  
Heating And Cooling

The concern regarding local responsive building design has gained more attention globally as of late. This is due to the issue of the rapid increase in energy consumption in buildings for the purpose of heating and cooling. This has become a crucial issue in educational buildings and especially in schools. The major issue in school buildings in Saudi Arabia is that they are a form of prototype school building design (PSBD). As a result, if there is any concern in the design stage and in relation to the selection of building materials, this will spread throughout the region. In addition to that, the design is repeated regardless of the climate variation within the kingdom of Saudi Arabia. This research will focus on the influence of the window to wall ratio on the energy load in various orientations and different climatic regions. The research will use the energy computer tool TAS Environmental Design Solution Limited (EDSL) to calculate the energy load as well as solar gain. During the visit to the sample schools, a globe thermometer will be used to monitor the globe temperature in the classrooms. This research introduces a framework to assist architects and engineers in selecting the proper window to wall ratio (WWR) in each direction within the same building based on adequate natural light with a minimum reliance on energy load. For ultimate WWR for energy performance and daylight, the WWR should range from 20% to 30%, depending on orientation, in order to provide the optimal daylight factor combined with building energy efficiency. This ratio can be slightly greater in higher altitude locations.

A Performance Study of Real Coded Genetic Algorithm on Gear Design Optimization

2012 ◽  
Vol 622-623 ◽  
pp. 64-68 ◽  
Author(s):  
S. Padmanabhan ◽  
M. Chandrasekaran ◽  
P. Asokan ◽  
V. Srinivasa Raman
Keyword(s):  
Genetic Algorithm ◽  
Power Efficiency ◽  
Mechanical Design ◽  
Design Solution ◽  
Functional Requirements ◽  
Performance Study ◽  
Gear Design ◽  
Adverse Result ◽  
Real Coded Genetic Algorithm ◽  
Comparative Results

he major problem that deals with practical engineers is the mechanical design and creativeness. Mechanical design can be defined as the choice of materials and geometry, which satisfies, specified functional requirements of that design. A good design has to minimize the most significant adverse result and to maximize the most significant desirable result. An evolutionary algorithm offers efficient ways of creating and comparing a new design solution in order to complete an optimal design. In this paper a type of Genetic Algorithm, Real Coded Genetic Algorithm (RCGA) is used to optimize the design of helical gear pair and a combined objective function with maximizes the Power, Efficiency and minimizes the overall Weight, Centre distance. The performance of the proposed algorithms is validated through LINGO Software and the comparative results are analyzed.

Closed-Form Correlation of Buildings Energy Use With Key Design Parameters Calibrated Using a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Algorithm ◽  
Closed Form ◽  
Energy Use ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Wide Range ◽  
Variable Function ◽  
Real Coded Genetic Algorithm ◽  
The Difference

This work aims at developing a closed-form correlation between key building design variables and its energy use. The results can be utilized during the initial design stages to assess the different building shapes and designs according to their expected energy use. Prototypical, 20-floor office buildings were used. The relative compactness, footprint area, projection factor, and window-to-wall ratio were changed and the resulting buildings performances were simulated. In total, 729 different office buildings were developed and simulated in order to provide the training cases for optimizing the correlation’s coefficients. Simulations were done using the VisualDOE TM software with a Typical Meteorological Year data file, Kuwait City, Kuwait. A real-coded genetic algorithm (GA) was used to optimize the coefficients of a proposed function that relates the energy use of a building to its four key parameters. The figure of merit was the difference in the ratio of the annual energy use of a building normalized by that of a reference building. The objective was to minimize the difference between the simulated results and the four-variable function trying to predict them. Results show that the real-coded GA was able to come up with a function that estimates the thermal performance of a proposed design with an accuracy of around 96%, based on the number of buildings tested. The goodness of fit, roughly represented by R2, ranged from 0.950 to 0.994. In terms of the effects of the various parameters, the area was found to have the smallest role among the design parameters. It was also found that the accuracy of the function suffers the most when high window-to-wall ratios are combined with low projection factors. In such cases, the energy use develops a potential optimum compactness. The proposed function (and methodology) will be a great tool for designers to inexpensively explore a wide range of alternatives and assess them in terms of their energy use efficiency. It will also be of great use to municipality officials and building codes authors.

Solving Vibration Control Problems Using Reduced Order Models for Flexible Structures: A Genetic Algorithm Approach

1997 ◽  
Author(s):  
Sourav Kundu ◽  
Kentaro Kamagata ◽  
Shigeru Sugino ◽  
Takeshi Minowa ◽  
Kazuto Seto
Keyword(s):  
Genetic Algorithm ◽  
Vibration Control ◽  
Controller Design ◽  
Fitness Function ◽  
Flexible Structures ◽  
Design Solution ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Fitness Value ◽  
Genetic Algorithm Approach

Abstract A Genetic Algorithm (GA) based approach for solution of optimal control design of flexible structures is presented in this paper. The method for modeling flexible structures with distributed parameters as reduced-order models with lumped parameters, which has been developed previously, is employed. Due to some restrictions on controller design it is necessary to make a reduced-order model of the structure. Once the model is established the design of flexible structures is considered as a feedback search procedure where a new solution is assigned some fitness value for the GA and the algorithm iterates till some satisfactory design solution is achieved. We propose a pole assignment method to determine the evaluation (fitness) function to be used by the GA to find optimal damping ratios in passive elements. This paper demonstrates the first results of a genetic algorithm approach to solution of the vibration control problem for practical control applications to flexible tower-like structures.

scholarly journals Daylighting Evaluation and Optimisation of Window to Wall Ratio for Lecture Theatre in the Tropical Climate

2021 ◽  
Vol 8 (1) ◽  
pp. 20-35
Author(s):  
Moses Iorakaa Ayoosu ◽  
◽  
Yaik-Wah Lim ◽  
Pau Chung Leng ◽  
Olusegun Moses Idowu ◽  
...  
Keyword(s):  
Architectural Design ◽  
Spatial Configuration ◽  
Tropical Climate ◽  
Base Case ◽  
Floor Plan ◽  
Humid Climate ◽  
Design For Sustainability ◽  
Ceiling Height ◽  
Lecture Theatre ◽  
Hot Humid Climate

A base case model is a more potent dose for applied research; the passive architectural design for sustainability requires optimised experiments. However, experimenting with physical developments require construction and deconstruction until they achieved the optimal scenario. These wastes resources and time; hence, base models' development as useful instruments in the optimisation design process is desirable. Lecture theatres in universities have no specific design model whereby optimising one may not apply to the other. Therefore, this research evaluated a base model for lecture theatre regarding spatial configuration, daylighting potentials, and optimised window-to-wall ratio (WWR) for tropical daylighting. A study of ten existing lecture theatres in eight universities within eight states in Nigeria's hot-humid climate was analysed descriptively for the base model. The study employed Simulations with IES-VE software. The daylighting performance analysis adopted the daylighting rule of thumb, daylight factor, work plane illuminance (WPI), and WPI ratio. The results show that a typical lecture theatre in the study area has a dimensional configuration of 12×20 m floor plan, 6 m ceiling height, and a window wall ratio (WWR) of 13%. In the deduced base model, 4H was required for adequate daylighting against the thumb's 2.5 H daylighting rule. The research concludes a low window-wall ratio with poor daylighting quality and quantities in the base model; therefore, it implies that the daylighting was not a criterion in the designs. However, the experiment revealed a progression in daylighting performance with an increase in WWR from the base case until 30% WWR. Beyond that, there was a decline in the daylighting performance. Therefore, 30% WWR was optimal for daylighting performance in lecture theatre retrofitting within the tropical climate.

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.

Comparison of Two Multiobjective Optimization Techniques With and Within Genetic Algorithms

1999 ◽  
Author(s):  
Shapour Azar ◽  
Brian J. Reynolds ◽  
Sanjay Narayanan
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Pareto Set ◽  
Design Solution ◽  
Multiple Objective ◽  
Multiple Objective Optimization ◽  
Continuous Variables ◽  
Optimal Set

Abstract Engineering decision making involving multiple competing objectives relies on choosing a design solution from an optimal set of solutions. This optimal set of solutions, referred to as the Pareto set, represents the tradeoffs that exist between the competing objectives for different design solutions. Generation of this Pareto set is the main focus of multiple objective optimization. There are many methods to solve this type of problem. Some of these methods generate solutions that cannot be applied to problems with a combination of discrete and continuous variables. Often such solutions are obtained by an optimization technique that can only guarantee local Pareto solutions or is applied to convex problems. The main focus of this paper is to demonstrate two methods of using genetic algorithms to overcome these problems. The first method uses a genetic algorithm with some external modifications to handle multiple objective optimization, while the second method operates within the genetic algorithm with some significant internal modifications. The fact that the first method operates with the genetic algorithm and the second method within the genetic algorithm is the main difference between these two techniques. Each method has its strengths and weaknesses, and it is the objective of this paper to compare and contrast the two methods quantitatively as well as qualitatively. Two multiobjective design optimization examples are used for the purpose of this comparison.

An areal openness model (AOM) for quantifying the “openness” of floor plans

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zoraya Roldán Rockow ◽  
Brandon E. Ross
Keyword(s):  
Real World ◽  
Design Methodology ◽  
Floor Plan ◽  
Existing Buildings ◽  
Content Type ◽  
Alternative Plan ◽  
Proposed Model ◽  
Reasonable Approach ◽  
Floor Plans

PurposeThis paper aims to describe and demonstrate a quantitative areal openness model (AOM) for measuring the openness of floor plans. Creation of the model was motivated by the widely reported but rarely quantified link between openness and adaptability.Design/methodology/approachThe model calculates values for three indicators: openness score (OS), weighted OS (WOS) and openness potential (OP). OS measures the absence of obstructions (walls, chases, columns) that separate areas in a floor plan. WOS measures the number of obstructions while also accounting for the difficulty of removing them. OP measures the potential of a floor plan to become more open. Indicators were calculated for three demolished case study buildings and for three adapted buildings. The case study buildings were selected because openness – or lack thereof – contributed to the owners' decisions to demolish or adapt.FindingsOpenness indicators were consistent with the real-world outcomes (adaptation or demolition) of the case study buildings. This encouraging result suggests that the proposed model is a reasonable approach for comparing the openness of floor plans and evaluating them for possible adaptation or demolition.Originality/valueThe AOM is presented as a tool for facility managers to evaluate inventories of existing buildings, designers to compare alternative plan layouts and researchers to measure openness of case studies. It is intended to be sufficiently complex as to produce meaningful results, relatively simple to apply and readily modifiable to suit different situations. The model is the first to calculate floor plan openness within the context of adaptability.

Introduction to generic rectangular floor plans

2018 ◽  
Vol 32 (3) ◽  
pp. 331-350
Author(s):  
Krishnendra Shekhawat ◽  
José P. Duarte
Keyword(s):  
Theoretical Approach ◽  
Mathematical Theory ◽  
Architectural Design ◽  
Important Task ◽  
Floor Plan ◽  
Design Processes ◽  
Topological Constraints ◽  
Graph Theoretical Approach ◽  
Floor Plans

AbstractAn important task in the initial stages of most architectural design processes is the design of planar floor plans, that are composed of non-overlapping rooms divided from each other by walls while satisfying given topological and dimensional constraints. The work described in this paper is part of a larger research aimed at developing the mathematical theory for examining the feasibility of given topological constraints and providing a generic floor plan solution for all possible design briefs.In this paper, we mathematically describe universal (or generic) rectangular floor plans with n rooms, that is, the floor plans that topologically contain all possible rectangular floor plans with n rooms. Then, we present a graph-theoretical approach for enumerating generic rectangular floor plans upto nine rooms. At the end, we demonstrate the transformation of generic floor plans into a floor plan corresponding to a given graph.

Sign in / Sign up

Export Citation Format

Share Document