This section focuses on the methodology for simulating the C&D waste management process outlined in the proposed conceptual framework. To evaluate its effectiveness, the framework is applied to an existing townhouse in the Washington, D.C., area. The study assesses the financial benefits of implementing BIM and Digital Twin technologies in demolition waste management by comprehensively analysing cost savings and resource optimisation. For this simulation, architectural and structural data of existing townhouses were obtained from the study by Kaewunruen et al.32. This data is the foundation for accurately modelling the demolition and waste management process, ensuring that the simulation reflects real-world scenarios. By integrating BIM and Digital Twin technologies, the study aims to enhance demolition planning, optimise waste classification and transportation, and quantify the economic and environmental benefits of improved C&D waste management practices.
Demolition waste management and BIM-integrated planning
Effective demolition waste management necessitates the development of a comprehensive demolition plan, including a three-dimensional (3D) model of the existing building. In this study, the 3D model of a townhouse in the Washington, D.C. area is first constructed and then imported into BIM-Navisworks to facilitate precise planning and execution. The process begins with classifying BIM object categories and identifying relevant attributes, such as the dismantling method and the corresponding recycling approach. This classification ensures that each building component is appropriately managed during demolition, optimising waste separation and material reuse. The next step involves establishing a systematic demolition sequence. In alignment with standard demolition practices, the deconstruction process follows a top-down approach, reversing the original construction order to maintain structural stability and ensure safety. Particular attention is given to the disassembly of prefabricated components, where beams and slabs are removed as integrated units, while walls and columns are dismantled collectively. Figure 5 presents the fundamental demolition sequence, illustrating the phased deconstruction process in conjunction with the demolition schedule developed in Navisworks. The demolition plan for the case study commences with removing the building’s windows, followed sequentially by the doors and roof walls. Upon completion of roof removal at Stage 4, the subsequent phases involve systematically dismantling the beams, staircases, and interior and exterior walls, proceeding progressively from the third floor down to the ground floor. The demolition workflow is monitored and updated in real time, utilising an imported demolition plan from a spreadsheet to guide and track progress.
To highlight, the 3D model of the existing townhouse located in Washington, D.C., including static structural elements such as beams, columns, and walls, is developed using Autodesk Revit. This BIM model was subsequently imported into Navisworks to support detailed demolition planning. Within the Navisworks environment, the BIM model was integrated with a predefined demolition schedule to quantify the building components designated for removal at each stage of the demolition process. Upon finalisation of the demolition plan, the model was further integrated with three distinct waste management strategies. These strategies encompass alternative treatments for materials resulting from demolition, including reuse, recycling, and landfilling. This integration enabled a comparative analysis of the financial implications associated with each waste management approach. The automation of this workflow was achieved through the use of Dynamo scripts, which allowed for real-time parametric linking between the demolition schedule, component classification, and corresponding waste management strategy. This facilitated dynamic visualisation and monitoring of component removal and material allocation throughout the demolition timeline, thereby supporting informed decision-making within a C&D waste management framework.
While the outcomes presented are specific to the case study, the workflow architecture is inherently modular and adaptable. Its application to other demolition projects is feasible with appropriate customisation to reflect project-specific parameters, data formats, and model structures. A key limitation, however, lies in its reliance on structured and consistently formatted data, which may require additional preprocessing for broader implementation. A detailed discussion of the financial benefits and implementation outcomes is provided in the subsequent sections.
The Demolition Process of Existing Townhouse in Washington, D.C.
In this study, the primary categories of C&D waste include concrete, metal, wood, and glass. According to existing research, a significant proportion, ranging from approximately 50–95% of construction and C&D waste can be effectively recycled or reused. This potential is primarily determined by the material properties, with both inert materials (e.g., concrete, sand) and non-inert materials (e.g., glass, wood, plastic) offering opportunities for recovery and diversion from landfill42. Based on these findings, the present study proposes three distinct waste treatment strategies aimed at optimising the management of C&D waste. Each strategy differs in terms of recycling efficiency and reliance on landfill disposal. Importantly, the proposed waste management plans are designed to satisfy the constraints outlined in Eq. (3), ensuring both environmental and economic feasibility within the demolition framework.
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Plan A: 50% of C&D waste is recycled, with 10% on-site recycling & sale (Xp) and 40% transported to recycling facilities (XR). The remaining 50% is disposed of in landfills (XL).
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Plan B: 80% of C&D waste is recycled, including 10% for on-site recycling & sale and 70% processed at recycling facilities. The remaining 20% is landfilled.
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Plan C: 95% of C&D waste is recycled, with 10% on-site recycling & sale and 85% transported to recycling facilities. Only 5% is sent to landfills.
These waste management plans provide a structured approach to balancing economic and environmental sustainability, offering varying levels of material recovery while minimising landfill disposal. The selection of an optimal strategy depends on project-specific constraints, financial considerations, and regulatory requirements.
Waste dismantling and transportation strategy
The quantity of dismantled waste is presented in Table 2. Utilising BIM-Navisworks for pre-demolition planning, this study assumes that 10% of dismantled components can be directly reused and sold on-site. In practice, the recycling of reinforced concrete structures is primarily achieved through crushing and separation into aggregate and steel. Since wood is a natural material, it can be repurposed into engineered wood products43. Current research indicates that the predominant treatment method for dismantled glass involves reprocessing, with some materials being converted into concrete aggregates44. A study found that the average transport distance of C&D waste by truck ranges from 10 to 30 kilometres45. This study references these existing waste management solutions and assumes that the transportation distance from the demolition site to the treatment facility is approximately 10 km. The transportation plan is managed through a real-time data platform integrated with a DT system. When the accumulated waste reaches a predefined transportation threshold, an automated “Transport Order” is generated. The total mass of material was calculated using Eq. 9, with the material density referenced from Ansys Granta EduPack 202146.
$$:{Mass:(Q}_{t})={Volume:(V}_{F})times:Density:left({uprho:}right)$$
(9)
Within the “Transportation Task Allocation” framework, the data platform assigns tasks to specific drivers via smartphone-based communication. Simultaneously, drivers provide real-time feedback regarding waste transportation and recycling status through mobile terminals, ensuring an efficient, closed-loop system for waste transportation management. This dynamic approach enhances logistical efficiency while reducing environmental and operational costs.
Analysis of financial benefits
Table 3 provides a comprehensive breakdown of unit costs associated with the treatment of various categories of C&D waste in the Washington, D.C., area. These costs encompass multiple components, including waste collection fees, transportation expenditures, material recovery processing costs, and landfill disposal charges. The data reflects region-specific economic factors and operational practices, offering valuable insight into the financial implications of C&D waste management strategies and supporting cost-benefit analyses for sustainable demolition planning. The data is sourced from the Metropolitan Washington Council of Governments and supplemented with information from local organizations, including American Recycler, the Institute for Local Self-Reliance, and Zero Waste DC. Furthermore, by utilising BIM-Dynamo software enables precise quantification of the total demolition volume of the existing building model, facilitating an in-depth analysis of the financial benefits associated with different waste management strategies. Figure 6 illustrates the sequential process, beginning with the initial static calculation and progressing to the real-time, automated demolition workflow executed using Dynamo, based on the parameters defined in this study. The system architecture is designed to be adaptable to varying demolition plans, allowing for immediate updates and dynamic reconfiguration within the model. In this case study, the system processes input data derived from the three proposed demolition scenarios, Plans A, B, and C, as described in previous sections, allowing for a comparative analysis of material flows and resource recovery potential under each approach. Tables 3 and 4, and 5 present the detailed cost analyses corresponding to the three proposed C&D waste treatment plans. Each table outlines the breakdown of waste treatment fees for various material categories, including concrete, steel, wood, and glass. These calculations encompass associated costs such as collection, transportation, material recovery, and landfill disposal. In addition to the treatment expenses, the tables also account for the potential financial returns generated through the reclamation and resale of reusable materials. The resulting net financial benefits are computed for each plan, thereby enabling a comparative assessment of the economic efficiency and resource recovery potential across the different demolition strategies.
As illustrated in Table 6, increasing the recycling rate of C&D waste from 50 to 80% and 95% yields a substantial improvement in financial returns. The analysis demonstrates that, at a 50% recycling rate, the process results in a financial deficit, with a negative net benefit of -£10,627.62. This indicates that under low recycling conditions, the costs associated with collection, transportation, and treatment outweigh the economic value of recovered materials. However, when the recycling and reuse rate is increased to 80%, the financial outlook shifts positively, resulting in a net benefit of £70,418.51. Further improvement is observed at a 95% recycling rate, where the net monetary benefit reaches £110,941.57, as presented in Table 7. These findings underscore the strong correlation between higher recycling efficiency and economic viability, highlighting the importance of maximizing material recovery rates in sustainable demolition practices. Therefore, based on the simulation calculations conducted through the BIM-Dynamo integration, the results indicate that the intelligent waste management approach proposed in this study’s conceptual framework has the potential to generate positive economic returns in the context of building demolition and C&D waste management. The analysis reveals a strong positive correlation between the material recycling rate and the overall financial benefits, suggesting that higher levels of material recovery significantly enhance the cost-effectiveness of demolition activities. This correlation highlights the economic viability of adopting a BIM-driven decision-support system, which enables dynamic modelling, real-time scenario analysis, and optimisation of resource recovery strategies. As such, the proposed approach not only supports environmentally sustainable practices but also offers measurable financial advantages, reinforcing the value of digital technologies in circular economy applications within the construction sector.
