Honeycomb core sandwich panels for origami-inspired deployable shelters: Multi-objective optimization for minimum weight and maximum energy efficiency

2014 ◽  
Vol 69 ◽  
pp. 158-167 ◽  
Author(s):  
F.J. Martínez-Martín ◽  
A.P. Thrall
Keyword(s):  
Energy Efficiency ◽  
Minimum Weight ◽  
Sandwich Panels ◽  
Maximum Energy ◽  
Multi Objective Optimization ◽  
Honeycomb Core ◽  
Multi Objective

scholarly journals Application of Urban Scale Energy Modelling and Multi-Objective Optimization Techniques for Building Energy Renovation at District Scale

2021 ◽  
Vol 13 (20) ◽  
pp. 11554
Author(s):  
Fahad Haneef ◽  
Giovanni Pernigotto ◽  
Andrea Gasparella ◽  
Jérôme Henri Kämpf
Keyword(s):  
Energy Efficiency ◽  
Building Energy ◽  
Energy Performance ◽  
Building Envelope ◽  
Optimization Techniques ◽  
Multi Objective Optimization ◽  
Building Stock ◽  
Energy Efficiency Measures ◽  
Multi Objective ◽  
Efficiency Measures

Nearly-zero energy buildings are now a standard for new constructions. However, the real challenge for a decarbonized society relies in the renovation of the existing building stock, selecting energy efficiency measures considering not only the energy performance but also the economic and sustainability ones. Even if the literature is full of examples coupling building energy simulation with multi-objective optimization for the identification of the best measures, the adoption of such approaches is still limited for district and urban scale simulation, often because of lack of complete data inputs and high computational requirements. In this research, a new methodology is proposed, combining the detailed geometric characterization of urban simulation tools with the simplification provided by “building archetype” modeling, in order to ensure the development of robust models for the multi-objective optimization of retrofit interventions at district scale. Using CitySim as an urban scale energy modeling tool, a residential district built in the 1990s in Bolzano, Italy, was studied. Different sets of renovation measures for the building envelope and three objectives —i.e., energy, economic and sustainability performances, were compared. Despite energy savings from 29 to 46%, energy efficiency measures applied just to the building envelope were found insufficient to meet the carbon neutrality goals without interventions to the system, in particular considering mechanical ventilation with heat recovery. Furthermore, public subsidization has been revealed to be necessary, since none of the proposed measures is able to pay back the initial investment for this case study.

Multi-Objective Optimization Approach for Improving Performance of Building

2009 ◽  
Vol 3 (3) ◽  
pp. 70-73
Author(s):  
A. Kamenders ◽  
A. Blumberga
Keyword(s):  
Energy Efficiency ◽  
Target Function ◽  
Complex Problem ◽  
Optimization Approach ◽  
Efficiency Measure ◽  
Multi Objective Optimization ◽  
Energy Efficiency Measures ◽  
Multi Objective ◽  
Energy Efficiency Measure ◽  
Efficiency Measures

Multi-Objective Optimization Approach for Improving Performance of Building Energy efficiency measures are different from energy efficiency and cost effectiveness perspective. For decision maker it is hard to make right decision about different energy efficiency measure combinations in building. It is a complex problem to choose the best energy efficiency measure combination as decision involves many different factors that should be taken in account. Decision on implementation of energy efficiency measure implementation usually depends on investment costs and pay back time. Standards like Latvian Building Code LBN 002-01 can't be used to achieve reasonable expenses in renovation of buildings. Therefore, in order to find the optimal energy-efficiency measures, it is necessary to carry out optimization taking all the variable parameters into account. In the paper target function was presented that gives ability of the multi-objective optimization approach to handle the problem of improving energy efficiency in buildings. Case study is used to demonstrate the feasibility of the approach. 104. series soviet type dwellings was analysed to optimized insulation thickness for external walls. Even if accord with the LBN 002-01 it is enough to use 7 cm thick isolation (λ-0,039 W/(m2K)) layers optimal insulation layer is 12 cm (λ-0,039 W/(m2K)).

The Application of an Immune Clonal Selection Algorithm Based on the Information Entropy in Truss Structure Multi-Objective Optimization

2012 ◽  
Vol 249-250 ◽  
pp. 1119-1125
Author(s):  
Chang Yuan Hu ◽  
He Sheng Tang ◽  
Li Xin Deng ◽  
Song Tao Xue
Keyword(s):  
Information Entropy ◽  
Optimization Design ◽  
Clonal Selection ◽  
Minimum Weight ◽  
Truss Structures ◽  
Penalty Function Method ◽  
Clonal Selection Algorithm ◽  
Multi Objective Optimization ◽  
Selection Algorithm ◽  
Multi Objective

In order to solve the conflict multi-objective optimization of truss structures between the structure minimum weight and safety redundancy, the immune clonal selection algorithm based on information entropy was adopted in this paper. Based on the immunology theory, the non-dominated neighbor-based selection, proportional cloning and elitism strategy were introduced in the multi-objective immune clonal selection algorithm (MOICSA) to enhance the diversity, the uniformity and the convergence of the obtained solution. Mathematical models for truss multi-objective optimization design are constructed, in which the information entropy value of bar stress is taken as one of objective functions, and penalty function method was used to deal with violated constraints. Several classical problems are solved using the MOICSA algorithm, and the results compared with other optimization methods. The simulation results show that the method can achieve the effect of multiple-objective optimization successfully.

Towards a multi-objective optimization approach for improving energy efficiency in buildings

2008 ◽  
Vol 40 (9) ◽  
pp. 1747-1754 ◽  
Author(s):  
Christina Diakaki ◽  
Evangelos Grigoroudis ◽  
Dionyssia Kolokotsa
Keyword(s):  
Energy Efficiency ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective
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