Roberta Di Bari defended her doctoral dissertation

On 26.02.2025, Roberta Di Bari defended her doctoral research titled "Predictive Risk-Integrated Dynamic Life Cycle Analyses and Integration in Building Design" in front of the doctoral committee. The doctoral committee consisted of Prof. H. C. Jünger (IBL) as chair, Prof. P. Leistner (IABP) as supervisor and first examiner, and Prof.K. Sedlbauer (Chair of Building Physics, TUM) as second examiner

Congratulations to Roberta Di Bari on her great achievement

Abstract of Doctoral Research

Decarbonizing the construction sector is crucially important for mitigating climate change on a global scale.

Climate change is already affecting the scheduling and financial planning of construction projects. It is therefore in the interests of the entire construction industry to take urgent measures to decarbonize new, existing, and planned buildings. Increasing energy efficiency and reducing the environmental impact and resource consumption of building materials can be identified as key measures that contribute to achieving this goal. In several European countries, so-called environmental or climate budgets have also been established as a supplementary measure. The current limits define the permissible environmental impact of construction projects and will be subject to even stricter requirements in the future.

The Integrative Computational Design and Construction (IntCDC) Cluster of Excellence is developing innovative building systems with the aim of reducing resource consumption and environmental impact. Such building systems make use of computer-aided design and robot-assisted manufacturing methods. Since these are building systems developed in the research project, knowledge about their performance, for example, their service life, is still insufficient. These uncertainties can lead to a reduced service life and an increased frequency of renovation work during the operation of the building. They can also result in a higher environmental impact. In this context, there is a need for new approaches in life cycle assessment to enable a sound evaluation of the environmental profiles of new building systems and to allow a comparison with conventional systems.

This dissertation presents a new methodology for future-oriented life cycle assessments, called PRINTED (Predictive Risk-INTEgrated Dynamic environmental life cycle analysis). It is used to evaluate the environmental profiles of novel IntCDC building systems, to optimize them, and ensure values of environmental impact below predefined budgets. One of the novelties of the methodology is the implementation of a predictive modelling routine, i.e., an algorithm that predicts the need for renovation work based on a building's life cycle.

Furthermore, the algorithm is designed to automatically generate life cycle inventories for life cycle assessments. This contrasts with current routines, which require manual data entry. Additionally, PRINTED advances the state of the art in probabilistic and dynamic life cycle assessment approaches. The algorithm considers dynamic and uncertain parameters and automates the analysis of their interdependencies. One example is the replacement of insulation, which changes the building energy demand.

As part of the methodological development, the matrices used to calculate the life cycle assessment results are being adapted to the PRINTED analyses. The Holistic Quality Model (HQM), a method for holistic quality assurance developed in the IntCDC cluster, enables the collection of environmental budgets (also referred to in this work as environmental requirements and targets) as well as information on relevant uncertainties, variability, and interactions between parameters. The algorithm for predictive modeling is then developed and characterized so that it can be used for dynamic and probabilistic analyses.

To operationalize and evaluate the methodology, a tool known as the PRINTED tool is being developed. It can be used throughout the entire design process, beginning with the early decision-making stages. The PRINTED tool facilitates the transfer of information with Sustainability Building Assessment (SBA) tools and digital building models. This enables planners to receive faster feedback on the environmental profiles of building systems.

In this work, the PRINTED tool is used for two different applications: it is used in the early design stages to develop a novel IntCDC wood system, and in the later stages to predict the renovation work required for an existing building. The present analysis takes into account the fact that the components (e.g., structural support systems, insulation, facade cladding) have an uncertain service life, which might lead to a more frequent replacement of the components. The installation of PV modules is considered a potential renovation measure. This results in a change in the overall energy efficiency of the building over the duration of the analysis. In the early design phases, PRINTED identifies planning options with higher environmental quality. In the later design phases, optimal points in time for renovation measures are determined in order to achieve maximum reduction of environmental impacts.

The use of PRINTED enables the evaluation from a longer-term perspective of the environmental quality of emerging technologies, such as those being researched within IntCDC. It also contributes to reducing the risk of exceeding climate budgets. In the future, the methodology will be expanded through the implementation of more advanced prediction models, such as machine learning and artificial intelligence. The goal of this development is to speed up the delivery of results and increase their accuracy. Finally, the methodology can be applied to different use cases. One potential area of application, for example, is the identification of strategies to reduce the risk of unexpected environmental impacts and economic losses caused by natural hazards such as climate change.

The dissertation is a monograph

Papers produced during the doctoral research

• R. Di Bari, N. Alaux, M. Saade, S.H. Hong, R. Horn, A. Passer, Systematising the LCA approaches’ soup: a framework based on text mining, Int J LCA 29 (2024) 1621-1638. https://doi.org/10.1007/s11367-024-02332-8. 
• R. Di Bari, A. Belleri, A. Marini, R. Horn, J. Gantner, Probabilistic Life-Cycle Assessment of Service Life Extension on Renovated Buildings under Seismic Hazard, Buildings 10 (2020) 48. https://doi.org/10.3390/buildings10030048. 
• R. Di Bari, R. Horn, S. Bruhn, N. Alaux, M. Ruschi Mendes Saade, B. Soust-Verdaguer, T. Potrč Obrecht, A. Hollberg, H. Birgisdottír, A. Passer, R. Frischknecht, Buildings LCA and digitalization: Designers toolbox based on a survey, IOP Conf. Ser.: Earth Environ. Sci. 1078 (2022) 12092. https://doi.org/10.1088/1755-1315/1078/1/012092. 
• R. Di Bari, O. Jorgji, R. Horn, J. Gantner, S. Ebertshäuser, Step-by-step implementation of BIM-LCA: A case study analysis associating defined construction phases with their respective environmental impacts, IOP Conf. Ser.: Earth Environ. Sci. 323 (2019) 12105. https://doi.org/10.1088/1755-1315/323/1/012105. 
• R. Di Bari, O. Jorgji, F. Turrin, R. Pinotti, C. Pozza, Environmental lifecycle impact assessment for CULTURAL-E climate and cultural based solution sets, IOP Conf. Ser.: Earth Environ. Sci. 1085 (2022) 12061. https://doi.org/10.1088/1755-1315/1085/1/012061.
• D. Frost, O. Gericke, R. Di Bari, L. Balangé, L. Zhang, B. Blagojevic, D. Nigl, P. Haag, L. Blandini, H.C. Jünger, C. Kropp, P. Leistner, O. Sawodny, V. Schwieger, W. Sobek, Holistic Quality Model and Assessment—Supporting Decision-Making towards Sustainable Construction Using the Design and Production of Graded Concrete Components as an Example, Sustainability 14 (2022) 11269. https://doi.org/10.3390/su141811269.
• P. Haag, L. Balangé, R. Di Bari, K. Braun, J. Weißert, L. Zhang, V. Schwieger, P. Leistner, C. Kropp, H.C. Jünger, Development of the holistic quality model and assessment – Integrating the economic quality aspect and establishing an extended interrelation analysis, Developments in the Built Environment 19 (2024) 100511. https://doi.org/10.1016/j.dibe.2024.100511.