scholarly journals A MULTI-CRITERIA DECISION-MAKING SYNTHESIS METHOD TO DETERMINE THE MOST EFFECTIVE OPTION FOR MODERNISING A PUBLIC BUILDING

2020 ◽  
Vol 26 (6) ◽  
pp. 1237-1262
Author(s):  
Jovita Starynina ◽  
Leonas Ustinovichius

The study presents a sustainable building modernisation model that uses knowledgebased decision-making methods to general reconstruct old public buildings, intending to achieve the best level of energy use on the design scene. The rapid development and dissemination of standards cause multiple research opportunities in the fields of process automation and adaptation of BIM technologies to the prerequisites of existing buildings. Decision-making was widely supported by imitating structures used in the late stages of design. However, its application is not sufficient at the beginning, which affects design solutions with a significant impact on the performance of the completed building. Construction design is a multifaceted discipline where architects, engineers, contractors, and builders influence design decisions. This modernisation way uses digital systems and simulations to estimate the expected energy consumption of construction faster and economically. BIM and critical characteristics are the basis of the model, where design and general processing needs to follow to pre-built instructions. This solution allows estimating energy demand in reconstructed buildings and correlation of parameters.

Author(s):  
Jovita Starynina ◽  
Leonas Ustinovičius ◽  
Mantas Vaišnoras

This research represents sustainable building modernization model, which creates knowledge-based decision-making method for old public buildings refurbishment seeking to reach the best energy performance during the design stage. Despite the fast development and spreading standards, challenging research opportunities arise from process automation and BIM adaptation for existing buildings’ requirements. To aid decision-making, building simulation is widely used in the late design stages, but its application is still limited in the early stages in which design decisions have a major impact on final building performance. Building design is a multi-collaborator discipline, where architects influence design decisions, engineers, contractors, and building owners. Using digital systems and simulations this modernization method performs already expected building energy consumption in a quickest and economic way. This model is BIM-based where design and refurbishment are based on pre-built indicators, which allows assessing the building energy demand and eco-building parameters.


2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.


2021 ◽  
Vol 13 (2) ◽  
pp. 737
Author(s):  
Indre Siksnelyte-Butkiene ◽  
Dalia Streimikiene ◽  
Tomas Balezentis ◽  
Virgilijus Skulskis

The European Commission has recently adopted the Renovation Wave Strategy, aiming at the improvement of the energy performance of buildings. The strategy aims to at least double renovation rates in the next ten years and make sure that renovations lead to higher energy and resource efficiency. The choice of appropriate thermal insulation materials is one of the simplest and, at the same time, the most popular strategies that effectively reduce the energy demand of buildings. Today, the spectrum of insulation materials is quite wide, and each material has its own specific characteristics. It is recognized that the selection of materials is one of the most challenging and difficult steps of a building project. This paper aims to give an in-depth view of existing multi-criteria decision-making (MCDM) applications for the selection of insulation materials and to provide major insights in order to simplify the process of methods and criteria selection for future research. A systematic literature review is performed based on the Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In order to determine which MCDM method is the most appropriate for different questions, the main advantages and disadvantages of different methods are provided.


2021 ◽  
Vol 9 (6) ◽  
pp. 596
Author(s):  
Murugan Ramasamy ◽  
Mohammed Abdul Hannan ◽  
Yaseen Adnan Ahmed ◽  
Arun Kr Dev

Offshore vessels (OVs) often require precise station-keeping and some vessels, for example, vessels involved in geotechnical drilling, generally use Spread Mooring (SM) or Dynamic Positioning (DP) systems. Most of these vessels are equipped with both systems to cover all ranges of water depths. However, determining which system to use for a particular operational scenario depends on many factors and requires significant balancing in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors for both the SM and DP station-keeping systems. Operational information and cost data are collected for several field operations, and Artificial Neural Networks (ANN) are trained using those data samples. After that, the trained ANN is used to predict the components of cost for any given environmental situation, fieldwork duration and water depth. Later, the total cost is investigated against water depth for both DP and SM systems to determine the most cost-effective option. The results are validated using two operational scenarios for a specific geotechnical vessel. This decision-making algorithm can be further developed by adding up more operational data for various vessels and can be applied in the development of sustainable decision-making business models for OVs operators.


2016 ◽  
Vol 128 ◽  
pp. 132-142 ◽  
Author(s):  
Paz Arroyo ◽  
Camila Fuenzalida ◽  
Alex Albert ◽  
Matthew R. Hallowell

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 898
Author(s):  
Michaela Bobková ◽  
Lukáš Pospíšil

We are interested in a contact problem for a thin fixed beam with an internal point obstacle with possible rotation and shift depending on a given swivel and sliding friction. This problem belongs to the most basic practical problems in, for instance, the contact mechanics in the sustainable building construction design. The analysis and the practical solution plays a crucial role in the process and cannot be ignored. In this paper, we consider the classical Euler–Bernoulli beam model, which we formulate, analyze, and numerically solve. The objective function of the corresponding optimization problem for finding the coefficients in the finite element basis combines a quadratic function and an additional non-differentiable part with absolute values representing the influence of considered friction. We present two basic algorithms for the solution: the regularized primal solution, where the non-differentiable part is approximated, and the dual formulation. We discuss the disadvantages of the methods on the solution of the academic benchmarks.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stuti Haldar ◽  
Gautam Sharma

Purpose The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India. Design/methodology/approach The present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use. Findings Energy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India. Research limitations/implications The study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces. Originality/value There are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).


Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1869 ◽  
Author(s):  
Alexandre Lucas ◽  
Giuseppe Prettico ◽  
Marco Flammini ◽  
Evangelos Kotsakis ◽  
Gianluca Fulli ◽  
...  

Electric vehicle (EV) charging infrastructure rollout is well under way in several power systems, namely North America, Japan, Europe, and China. In order to support EV charging infrastructures design and operation, little attempt has been made to develop indicator-based methods characterising such networks across different regions. This study defines an assessment methodology, composed by eight indicators, allowing a comparison among EV public charging infrastructures. The proposed indicators capture the following: energy demand from EVs, energy use intensity, charger’s intensity distribution, the use time ratios, energy use ratios, the nearest neighbour distance between chargers and availability, the total service ratio, and the carbon intensity as an environmental impact indicator. We apply the methodology to a dataset from ElaadNL, a reference smart charging provider in The Netherlands, using open source geographic information system (GIS) and R software. The dataset reveals higher energy intensity in six urban areas and that 50% of energy supplied comes from 19.6% of chargers. Correlations of spatial density are strong and nearest neighbouring distances range from 1101 to 9462 m. Use time and energy use ratios are 11.21% and 3.56%. The average carbon intensity is 4.44 gCO2eq/MJ. Finally, the indicators are used to assess the impact of relevant public policies on the EV charging infrastructure use and roll-out.


Environments ◽  
2018 ◽  
Vol 5 (11) ◽  
pp. 119 ◽  
Author(s):  
Alessia Arteconi ◽  
Luca Del Zotto ◽  
Roberto Tascioni ◽  
Khamid Mahkamov ◽  
Chris Underwood ◽  
...  

In this paper, the smart management of buildings energy use by means of an innovative renewable micro-cogeneration system is investigated. The system consists of a concentrated linear Fresnel reflectors solar field coupled with a phase change material thermal energy storage tank and a 2 kWe/18 kWth organic Rankine cycle (ORC) system. The microsolar ORC was designed to supply both electricity and thermal energy demand to residential dwellings to reduce their primary energy use. In this analysis, the achievable energy and operational cost savings through the proposed plant with respect to traditional technologies (i.e., condensing boilers and electricity grid) were assessed by means of simulations. The influence of the climate and latitude of the installation was taken into account to assess the performance and the potential of such system across Europe and specifically in Spain, Italy, France, Germany, U.K., and Sweden. Results show that the proposed plant can satisfy about 80% of the overall energy demand of a 100 m2 dwelling in southern Europe, while the energy demand coverage drops to 34% in the worst scenario in northern Europe. The corresponding operational cost savings amount to 87% for a dwelling in the south and at 33% for one in the north.


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