CH001B - RENOVATION, MAINTENANCE AND CONSERVATION OF HISTORICAL BUILDINGS

Course learning objectives
By the end of the course, students should be able to interpret historic built heritage as a complex system, recognizing its values, constraints, and vulnerabilities, and to structure a knowledge pathway aimed at conservation, maintenance, and risk mitigation. Students should understand the concept of a “digital identity” for historic buildings, the principles for organizing and managing multi-source data (geometric surveys, critical-historical analysis, construction techniques, materials, deterioration/damage), and the ways in which such information can be structured and made interoperable through technical/graphic outputs and heritage-oriented information systems (introductory notes on H-BIM and information models).
Students should also understand the main multi-scale and multi-risk analysis methods, with particular attention to seismic vulnerability and risk (multi-level approaches, the Masonry Quality Index—MQI, interpretation of cracking patterns) and to climate-change impacts (at both territorial and single-building scales). Based on these evaluations, they should be able to identify strategies consistent with conservation principles, including monitoring, preventive maintenance, and consolidation/strengthening interventions, while being aware of the potential and limitations of digital platforms and automation processes for replicable workflows in analysis and management.
Expected learning outcomes
Autonomy of judgement: ability to formulate well-grounded assessments of conservation conditions and risk, integrating interdisciplinary evidence, knowledge/uncertainty levels, and comparison among alternative intervention and management options.
Communication skills: ability to communicate results, assessments, and decisions clearly and with technical accuracy, through oral presentations and essential documentation.
Learning skills: ability to independently update knowledge on methods, standards, and digital tools, recognizing when interdisciplinary expertise is required and setting up replicable approaches for different case studies.