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.

VIBRATION OPTIMIZATION OF A PASSIVE SUSPENSION SYSTEM VIA GENETIC ALGORITHM

2012 ◽  
Vol 04 (01) ◽  
pp. 1250022 ◽  
Author(s):  
S. D. JABEEN
Keyword(s):  
Genetic Algorithm ◽  
Center Of Mass ◽  
Suspension System ◽  
Design Parameters ◽  
Suspension Spring ◽  
Real Coded Genetic Algorithm ◽  
Cubic Polynomial ◽  
Passive Suspension System ◽  
Technological Constraints ◽  
Iso 2631

In this paper, we have formulated mathematical models to optimize the bouncing transmissibility of the sprung mass of the half car system with passengers' seat suspensions considering different road conditions. The corresponding problem has been solved with the help of advanced real coded Genetic Algorithm (GA). The nonlinearity of suspension spring and damper, which are the most important characteristics of the suspension, has been taken into account in order to validate the model to real applications. The nonlinear cubic polynomial has been used to describe the spring characteristic and a quadratic polynomial has been used to describe the damper characteristic. The coefficients of each polynomial represent the design parameters of the suspension system and are to be determined. To find these parameters we have formulated a nonlinear optimization problem in which the bouncing transmissibility of the sprung mass at the center of mass has been minimized with respect to technological constraints and the constraints which satisfy the performance as per ISO 2631 standards. The advanced real coded GA has been used to solve this problem in time domain and the results obtained have been compared to those obtained using the existing design parameters. The objective function and the constraints have been evaluated by simulating the vehicle model over two roads with multiple bumps at uniform velocity.

General Correlation of Building Energy Use Via Hybrid Genetic Programming/Genetic Algorithm

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Mohammed A. Altarakma ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Programming ◽  
Closed Form ◽  
Hybrid Algorithm ◽  
Energy Use ◽  
Building Energy ◽  
Simulation Engine ◽  
Building Energy Use ◽  
The Difference ◽  
Predicted Values ◽  
Specific Number

A hybrid algorithm that combines genetic programming (GP) and genetic algorithms (GAs) that deduce a closed-form correlation of building energy use is presented. Throughout the evolution, the terms, functions, and form of the correlation are evolved via the genetic program. Whenever the fitness of the best correlation stagnates for a specific number of GP generations, the GA optimizes the real-valued coefficients of each correlation in the population. When the GA, in turn, stagnates, correlations with optimized coefficients and powers are passed back to the GP for further search. The hybrid algorithm is applied to the problem of predicting energy use of a U-shape building. More than 800 buildings with various foot-print areas, relative compactness (RC), window-to-wall ratio (WWR), and projection factor (PF) values were simulated using the VisualDOETM energy simulation engine. The algorithm tries to minimize the difference between simulated and predicted values by maximizing the R2 value. The algorithm was able to arrive at a closed-form correlation that combines the four building parameters, accurate to within 4%. The methodology can be easily used to model any type of data behavior in any engineering or nonengineering application.

scholarly journals Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics

Facilities ◽  
2019 ◽  
Vol 37 (11/12) ◽  
pp. 860-878
Author(s):  
Pan Lee ◽  
Edwin H.W. Chan ◽  
Queena K. Qian ◽  
Patrick T.I. Lam
Keyword(s):  
Regression Model ◽  
Carbon Emissions ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Design Teams ◽  
Content Type ◽  
High Rise ◽  
User Friendly ◽  
Influential Parameters

Purpose Design teams have difficulties in assessing building carbon emissions at an early stage, as most building energy simulation tools require a detailed input of building design for estimation. The purpose of this paper is to develop a user-friendly regression model to estimate carbon emissions of the preliminary design of office buildings in the subtropics by way of example. Five sets of building design parameters, including building configuration, building envelope, design space conditions, building system configuration and occupant behaviour, are considered in this study. Design/methodology/approach Both EnergyPlus and Monte Carlo simulation were used to predict carbon emissions for different combinations of the design parameters. A total of 100,000 simulations were conducted to ensure a full range of simulation results. Based on the simulation results, a regression model was developed to estimate carbon emissions of office buildings based on preliminary design information. Findings The results show that occupant density, annual mean occupancy rate, equipment load, lighting load and chiller coefficient of performance are the top five influential parameters affecting building carbon emissions under the subtropics. Besides, the design parameters of ten office buildings were input into this user-friendly regression model for validation. The results show that the ranking of its simulated carbon emissions for these ten buildings is consistent with the original carbon emissions ranking. Practical implications With the use of this developed regression model, design teams can not only have a simple and quick estimation of carbon emissions based on the building design information at the conceptual stage but also explore design options by understanding the level of reduction in carbon emissions if a certain building design parameter is changed. The study also provides recommendations on building design to reduce carbon emissions of office buildings. Originality/value Limited research has been conducted to date to investigate how the change of building design affects carbon emissions in the subtropics where four distinct seasons lead to significant variations of outdoor temperature and relative humidity. Previous research also did not emphasise on the impact of high-rise office building designs (e.g. small building footprint, high window-to-wall ratio) on carbon emissions. This paper adds value by identifying the influential parameters affecting carbon emissions for a high-rise office building design and allows a handy estimate of building carbon emissions under the subtropical conditions. The same approach may be used for other meteorological conditions.

scholarly journals AN ITERATIVE ASSESSMENT CONCEPT FOR BUILDING DESIGN BASED ON THE ECO‐FACTOR

2006 ◽  
Vol 12 (1) ◽  
pp. 51-56
Author(s):  
Henrik Brohus ◽  
Erik Bjørn
Keyword(s):  
Energy Use ◽  
Building Design ◽  
Energy System ◽  
Design Guidelines ◽  
Office Buildings ◽  
Indoor Climate ◽  
Energy Efficient Buildings ◽  
Energy Optimisation ◽  
And Control ◽  
Indoor Comfort

Problems in office buildings are often related to the design and control of the indoor environment and of the building as an energy system. The often interconnected nature of the above two issues is important to take into account, since, for instance, internal and external heat loads, temperatures, and air change rates affect both energy use and indoor comfort. Thus, to avoid the indoor climate problems, it is essential that energy optimisation is integrated with assessment of indoor climate. An assessment concept based on the so‐called Eco‐factor has been developed; it can assist building designers in creating solutions of these problems. The assessment concept is meant to be an integral part of new design guidelines for office buildings, which aim to achieve energy efficient buildings with a good indoor comfort and low environmental impact. The building designers have different needs at different stages of the design process. For this reason, the assessment concept makes use of the Eco‐factor tool, which is defined so input can be based on both simple and advanced calculations in early and later phases of design, respectively, while still delivering the same output.

scholarly journals Nonlinear System Identification with a Real–Coded Genetic Algorithm (RCGA)

2015 ◽  
Vol 25 (4) ◽  
pp. 863-875 ◽  
Author(s):  
Imen Cherif ◽  
Farhat Fnaiech
Keyword(s):  
Genetic Algorithm ◽  
Volterra Series ◽  
Fitness Function ◽  
Nonlinear System Identification ◽  
Identification Problem ◽  
Stationary Gaussian Sequence ◽  
Volterra Models ◽  
Real Coded Genetic Algorithm ◽  
Precision Time ◽  
The Difference

Abstract This paper is devoted to the blind identification problem of a special class of nonlinear systems, namely, Volterra models, using a real-coded genetic algorithm (RCGA). The model input is assumed to be a stationary Gaussian sequence or an independent identically distributed (i.i.d.) process. The order of the Volterra series is assumed to be known. The fitness function is defined as the difference between the calculated cumulant values and analytical equations in which the kernels and the input variances are considered. Simulation results and a comparative study for the proposed method and some existing techniques are given. They clearly show that the RCGA identification method performs better in terms of precision, time of convergence and simplicity of programming.

A Conceptual Design Study of an Open Rotor Powered Regional Aircraft

2014 ◽  
Author(s):  
Linda Larsson ◽  
Anders Lundbladh ◽  
Tomas Grönstedt
Keyword(s):  
Mach Number ◽  
Aircraft Design ◽  
Design Parameters ◽  
Propulsive Efficiency ◽  
Turbofan Engine ◽  
Turbofan Engines ◽  
Wide Range ◽  
Open Rotor ◽  
The Difference ◽  
Engine Power

Today many of the routes between small to medium sized airports and large hubs are operated by regional aircraft, powered by turboprop or turbofan engines. In the future the open rotor engine might provide an alternative option. The open rotor would combine the possibility of high cruise speed with high propulsive efficiency. Also, since the open rotor essentially is a turboprop with the possibility to fly fast, there is a benefit of high specific range at low cruising speeds, thus giving it a wide range cruise operation. In this paper a regional aircraft for 70 passengers and 3000 km range is studied. The aircraft is evaluated with both a counter rotating open rotor and a turbofan engine. Aircraft design parameters such as wing area and sweep are varied together with engine parameters such as engine power and propeller disc loading. Results show that the open rotor aircraft has a 17.0 % higher specific range at the optimal cruise Mach number compared to the turbofan aircraft. For higher speeds, at Mach 0.78, the difference is reduced to 15.0 %. The long range cruise Mach number is around Mach 0.7 for the open rotor aircraft while for the turbofan aircraft it is slightly higher, around Mach 0.72.

scholarly journals Identification of Optimal Parameters for a Small-Scale Compressed-Air Energy Storage System Using Real Coded Genetic Algorithm

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 377 ◽  
Author(s):  
Thomas Guewouo ◽  
Lingai Luo ◽  
Dominique Tarlet ◽  
Mohand Tazerout
Keyword(s):  
Genetic Algorithm ◽  
Energy Storage ◽  
Electric Energy ◽  
Exergy Efficiency ◽  
Compressed Air ◽  
Optimum Operating ◽  
Design Parameters ◽  
Small Scale ◽  
Real Coded Genetic Algorithm ◽  
Optimum Operating Point

Compressed-Air energy storage (CAES) is a well-established technology for storing the excess of electricity produced by and available on the power grid during off-peak hours. A drawback of the existing technique relates to the need to burn some fuel in the discharge phase. Sometimes, the design parameters used for the simulation of the new technique are randomly chosen, making their actual construction difficult or impossible. That is why, in this paper, a small-scale CAES without fossil fuel is proposed, analyzed, and optimized to identify the set of its optimal design parameters maximizing its performances. The performance of the system is investigated by global exergy efficiency obtained from energy and exergy analyses methods and used as an objective function for the optimization process. A modified Real Coded Genetic Algorithm (RCGA) is used to maximize the global exergy efficiency depending on thirteen design parameters. The results of the optimization indicate that corresponding to the optimum operating point, the consumed compressor electric energy is 103 . 83 k W h and the electric energy output is 25 . 82 k W h for the system charging and discharging times of about 8.7 and 2 h, respectively. To this same optimum operating point, a global exergy efficiency of 24.87% is achieved. Moreover, if the heat removed during the compression phase is accounted for in system efficiency evaluation based on the First Law of Thermodynamics, an optimal round-trip efficiency of 79.07% can be achieved. By systematically analyzing the variation of all design parameters during evolution in the optimization process, we conclude that the pneumatic motor mass flow rate can be set as constant and equal to its smallest possible value. Finally, a sensitivity analysis performed with the remaining parameters for the change in the global exergy efficiency shows the impact of each of these parameters.

scholarly journals Exploring Climate-Change Impacts on Energy Efficiency and Overheating Vulnerability of Bioclimatic Residential Buildings under Central European Climate

2021 ◽  
Vol 13 (12) ◽  
pp. 6791
Author(s):  
Luka Pajek ◽  
Mitja Košir
Keyword(s):  
Climate Change ◽  
Energy Efficiency ◽  
Energy Efficient ◽  
Energy Demand ◽  
Energy Use ◽  
Residential Buildings ◽  
Building Design ◽  
Temperate Climate ◽  
Design Parameters ◽  
Central European

Climate change is expected to expose the locked-in overheating risk concerning bioclimatic buildings adapted to a specific past climate state. The study aims to find energy-efficient building designs which are most resilient to overheating and increased cooling energy demands that will result from ongoing climate change. Therefore, a comprehensive parametric study of various passive building design measures was implemented, simulating the energy use of each combination for a temperate climate of Ljubljana, Slovenia. The approach to overheating vulnerability assessment was devised and applied using the increase in cooling energy demand as a performance indicator. The results showed that a B1 heating energy efficiency class according to the Slovenian Energy Performance Certificate classification was the highest attainable using the selected passive design parameters, while the energy demand for heating is projected to decrease over time. In contrast, the energy use for cooling is in general projected to increase. Furthermore, it was found that, in building models with higher heating energy use, low overheating vulnerability is easier to achieve. However, in models with high heating energy efficiency, very high overheating vulnerability is not expected. Accordingly, buildings should be designed for current heating energy efficiency and low vulnerability to future overheating. The paper shows a novel approach to bioclimatic building design with global warming adaptation integrated into the design process. It delivers recommendations for the energy-efficient, robust bioclimatic design of residential buildings in the Central European context, which are intended to guide designers and policymakers towards a resilient and sustainable built environment.

Building Sector & Climate Change: The Case of Hungary

2014 ◽  
Vol 899 ◽  
pp. 99-104
Author(s):  
Attila Talamon
Keyword(s):  
Climate Change ◽  
Energy Use ◽  
Ghg Emissions ◽  
Building Design ◽  
Building Energy ◽  
Climate Impacts ◽  
Design Parameters ◽  
Building Sector ◽  
Energy And Environment ◽  
Low Energy Buildings

Building sector plays an important role in climate impacts mitigation, as it is responsible for 40% of global energy use and global GHG emissions. Climate change has a dual implication on the built environment: on one hand human settlements and buildings are vulnerable to the effects of changing climate and on the other hand the building sector has a significant climate change mitigation potential. Although nowadays the trends are positive, the share of newly built low-energy buildings is very low, the near-zero-energy building market is in its early phase. Simultaneously the optimizing technologies in the building design are strongly highlighted. The presence of the energy and environment efficient buildings and the stringent building energy regulations of the EU need more accurate building design. The constant design parameters will come to foreground and their role will be appreciated. The relevant sustainable development and building policies, as well as the building design, construction and maintenance should jointly respond both to adaptation to and mitigation of climate change. This paper focuses the relevance of the main constant design parameter: How to take into account the increasing outdoor temperature in the building energy design.

scholarly journals Optimization Of Thermo-Electric Coolers Using Hybrid Genetic Algorithm And Simulated Annealing

2014 ◽  
Vol 24 (2) ◽  
pp. 155-176 ◽  
Author(s):  
Doan V.K. Khanh ◽  
Pandian Vasant ◽  
Irraivan Elamvazuthi ◽  
Vo N. Dieu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Problems ◽  
Hybrid Genetic Algorithm ◽  
Coefficient Of Performance ◽  
Design Parameters ◽  
Leg Length ◽  
Thermo Electric ◽  
Material Parameters ◽  
Wide Range

Abstract Thermo-electric Coolers (TECs) nowadays are applied in a wide range of thermal energy systems. This is due to their superior features where no refrigerant and dynamic parts are needed. TECs generate no electrical or acoustical noise and are environmentally friendly. Over the past decades, many researches were employed to improve the efficiency of TECs by enhancing the material parameters and design parameters. The material parameters are restricted by currently available materials and module fabricating technologies. Therefore, the main objective of TECs design is to determine a set of design parameters such as leg area, leg length and the number of legs. Two elements that play an important role when considering the suitability of TECs in applications are rated of refrigeration (ROR) and coefficient of performance (COP). In this paper, the review of some previous researches will be conducted to see the diversity of optimization in the design of TECs in enhancing the performance and efficiency. After that, single-objective optimization problems (SOP) will be tested first by using Genetic Algorithm (GA) and Simulated Annealing (SA) to optimize geometry properties so that TECs will operate at near optimal conditions. Equality constraint and inequality constraint were taken into consideration.

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