A hybrid Decision Support System for Generation of Holistic Renovation Scenarios—Cases of Energy Consumption, Investment Cost, and Thermal Indoor Comfort

Assessing the Transformability of Public Housing through BIM

Public residential buildings make a large portion of the European existing stock and they quite often require deep renovation interventions. A methodology for setting priorities and targeting regeneration investments should be defined relying on the increasing use of building information modelling (BIM) tools even for managing existing buildings. The aim of this paper is to integrate the evaluation process into BIM Revit software developing a specific plug-in, a Decision support system (DSS) that will help to identify the most appropriate flats to be transformed. It is based on measuring three indicators: Usability, Fragmentation, and Constructive Modifiability. Through their weighted average it is possible to obtain a final transformability score. The proposed approach has been tested on a case study chosen within the 1st P.E.E.P. (1st public plan for council and affordable housing) that has been approved in Rome in 1964. The results demonstrate that the transformability of apartments is related mainly to the Constructive Modifiability indicator and buildings with reinforced concrete frames show higher scores. A widespread application of such a methodology on large real estate portfolio may lead stakeholders involved in housing management investments in clear choices related to maintenance of buildings.

BIM-Enabled Virtual Reality (VR) for Sustainability Life Cycle and Cost Assessment

Virtual Reality (VR) is receiving ever-increasing attention and is utilized by many construction companies in their current practices. This paper aims at a critical investigation of the impact of VR technology on how sustainability and cost are understood and perceived by the users in building design projects, which could lead to improving and supporting the actual building design processes. The research study focused on evaluating design alternatives using Building Information Modeling (BIM)-enabled VR technology integrated with cost and sustainability life cycle assessment (LCA) software. In doing so, the paper begins with reviewing the relevant literature in the mentioned areas. Thereafter, it adopts an experimental-qualitative-quantitative method to test the research hypothesis and analyze the effects of 360-degree VR on the users (66 participants), while distinguishing between users who have a relevant background in building/construction engineering (i.e., architect engineers and civil engineers), and those who have not (i.e., owners and clients). It is observed that despite their background, the user participants positively embrace the ideas and aspirations of sustainability, and that there is some evidence of respondents preferring the economy over sustainability. Likewise, the participants are not making an effort to measure the emissions of their design options rather than focus on the building’s economic aspects.

Renovation Construction Process Scheduling for Long-Term Performance of Buildings: An Application Case of University Campus

Renovation construction is employed for maintaining the long-term performance of buildings. For the occupants, the building users, renovation contributes to the acceptable levels of convenience and quality of the buildings. However, if the operation continues during the renovation for an area containing several buildings, such as a university campus, the impacts on the occupants are unavoidable. The complicated schedule plan is needed due to the various types of buildings and types of renovation under limited resources. The goal of this study is to build a model that can help the planners to make the renovation schedule plan. Taking a university campus as an example, the occupants’ convenience rate and the long-term quality of the building are analyzed in this paper. Based on the key attributes of building renovation, this study proposes a model integrating the genetic algorithm and simulation to provide the optimal schedule plan to the planners. The model is demonstrated by an application case of a university campus of 11 buildings remaining in operation. It helps the university maintain a good level of long-term performance of buildings.

A HOLISTIC MULTI-METHODOLOGY FOR SUSTAINABLE RENOVATION

A review of the barriers for building renovation has revealed a lack of methodologies, which can promote sustainability objectives and assist various stakeholders during the design stage of building renovation/retrofitting projects. The purpose of this paper is to develop a Holistic Multi-methodology for Sustainable Renovation, which aims to deal with complexity of renovation projects. It provides a framework through which to involve the different stakeholders in the design process to improve group learning and group decision-making, and hence make the building renovation design process more robust and efficient. Therefore, the paper discusses the essence of multifaceted barriers in building renovation regarding cultural changes and technological/physical changes. The outcome is a proposal for a multi-methodology framework, which is developed by introducing, evaluating and mixing methods from Soft Systems Methodologies (SSM) with Multiple Criteria Decision Making (MCDM). The potential of applying the proposed methodology in renovation projects is demonstrated through a case study.

Artificial Neural Network-Based Decision Support System for Development of an Energy-Efficient Built Environment

Implementing energy-efficient solutions in a built environment is important for reaching international energy reduction targets. For advanced energy efficiency-related solutions, computer-based decision support systems are proposed and rapidly used in a variety of spheres relevant to a built environment. Present research proposes a novel artificial neural network-based decision support system for development of an energy-efficient built environment. The system was developed by integrating methods of the multiple criteria evaluation and multivariant design, determination of project utility and market value, and visual data mining by artificial neural networks. It enables a user to compose up to 100,000,000 combinations of the energy-efficient solutions, analyze strengths and weaknesses of a built environment projects, provide advice for stakeholders, and calculate market value and utility degree of the projects. For visual data mining, self-organizing maps (type neural networks) are used, which may influence the choosing of the final set of alternatives and criteria in the decision-making problem, taking into account the discovered similarities of alternatives or criteria. A system was validated by the real case study on the design of an energy-efficient individual house.