Designing out waste is the core principle of the CE. Design for disassembly or design for deconstruction (DfD) is the practice of planning the future deconstruction of a building and the reuse of its materials. Concepts like DfD, CE, and product-service systems (PSS) can work together to promote CLC in the built environment. PSS are business models based on stewardship instead of ownership. CE combines DfD, PSS, materials’ durability, and materials’ reuse in multiple life cycles to promote a low-carbon, regenerative economy. CE prioritizes reuse over recycling. Dealing with resource scarcity demands us to think beyond the incremental changes from recycling waste; it demands an urgent, systemic, and radical change in the way we design, build, and procure construction materials.
This dissertation aims to answer three research questions: 1) How can researchers estimate the environmental benefits of reusing building components, 2) What variables are susceptible to affect the environmental impact assessment of reuse, and 3) What are the barriers and opportunities for DfD and materials’ reuse in the current design practice in the United States.
The first part of this study investigated how different life cycle assessment (LCA) methods (i.e., hybrid LCA and process-based LCA), assumptions (e.g., reuse rates, transportation distances, number of reuses), and LCA timelines can affect the results of a closed-loop LCA. The second part of this study built on interviews with architects in the United States to understand why DfD is not part of the current design practice in the country.
Briefly explains how lack of monetary savings serves as a barrier to accessing to finance capital for women of color seeking to launch their own tech startup.
This article assesses the combined influence of information integration and automated data analytics on project performance. To this end, retrospective data on 78 completed projects, with a total installed value of $8 billion, was collected. The data collection effort characterized, for each project, the level of internal and external information integration. Information integration was assessed as the seamlessly interoperable sharing of data produced from a work function with other functions/stakeholders so that no manual data transfer was required. Also, the level of automated data analytics, understood as the full automation of the data analysis function after input data are entered, was also characterized on a project basis. Then, non-parametric statistical techniques were used to assess the impact of such functions on cost and schedule performance. The statistical analysis was also stratified by project type, e.g. greenfield and brownfield, additions, and modifications or shutdowns. Overall, projects with a sophisticated degree of information integration and automated data analytics can control their projects with more reliable information and in a proactive manner so that informed decisions can be timely made on behalf of the project and the organization.