Abstract
Introduction:
The technical research of this portfolio explores how civil engineering (CE) projects can provide long-lasting solutions for community solid waste management. These specific projects require innovative designs that are supported by diverse teams. The STS research of this portfolio investigates the interactions between civil engineering software (CES) and neurodiverse individuals, addressing a gap in how CES incorporates neurodiverse needs in its design process. Essentially, this study introduces how major CE applications accommodate neurodiverse users. CE projects require major decision-making by project teams to provide innovative, long-lasting solutions. Therefore, it is critical to evaluate the systems and environments in which teams work to support their best performance.
Technical Research: Municipal Solid Waste (MSW) Transfer Station
Rationale and Methods: Casella Waste Systems plans to design a long-term solid waste management solution for the City of Pittsfield by converting an aging incineration facility site into a transfer station. The transfer station will better manage the increasing MSW volume, address constraints of space, regulatory, economic, and resource limitations, and provide a practical solution for efficient transport and accessible waste management. The project followed four phases: (1) regulation research and facility sizing, (2) key site decisions, (3) community drop-off design, and (4) final deliverables. The team held bi-weekly meetings with an industry advisor and weekly meetings with a faculty advisor to refine the design.
Results and Conclusions: The project addresses common transfer station challenges including fires, limited space, operational efficiency, and community engagement. Proposed solutions include a Fire Rover system, a dedicated safety storage building, nuisance mitigation strategies, and separate vehicle entrance points. The design consists of three buildings: a community drop off area, an MSW transfer station, and a recycling facility. Deliverables include site plans, a construction cost estimate, a bid-build narrative, and a community flyer and brochure. Key lessons learned emphasized that simple designs are most effective when supported by innovative technology, efficient site operations, and community considerations.
STS Research: Civil Engineering Software (CES) Design and Neurodiversity
Research Topic, Significance, and Methodology: This research investigates how neurodiversity relates to CES, focusing on how design choices affect inclusion, usability, and cognitive load for neurodivergent engineers. Neurodivergent individuals make up about 15–20% of the global population but face high unemployment, while the civil engineering workforce anticipates about 17 million infrastructure workers. This highlights a workforce gap and an opportunity to redesign systems for greater inclusion. The study’s methodology incorporates website analysis, VPAT review, and literature on neurodiversity and UI/UX design. Findings are analyzed using Interactive Sociotechnical Analysis (ISTA), considering how technical systems, social structures, and user adaptations interact to shape CES use.
Evidence, Results, and Conclusions: Evidence shows CES platforms generally lack explicit consideration of neurodivergent users, despite partial accessibility compliance (about 42%–71%) across major applications. Website and document analysis indicate neurodivergent perspectives are rarely represented, and tools like Civil 3D and MicroStation are often criticized for steep learning curves, outdated interfaces, and performance issues, with compliance often reflecting legal requirements rather than usability. ISTA shows CES use is shaped by technical limits (hardware, performance, interfaces) and social systems (training, workflows, feedback), while neurodivergent needs remain largely absent. Users rely on workarounds like scripts and external tools, reinforcing a “workaround culture,” but this does not lead to meaningful redesign. Overall, CES improves incrementally but does not integrate cognitive diversity into core CES design.
