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RISExamining Low-Carbon Material Initiatives: Existing Policies, Impacts on the Procurement of Projects, Current Challenges, and Potential Solutions to Reduce Embodied Carbon in the Construction Industry
Publisher: ASCE
Abstract: Given the reinforced expectations of a carbon-constrained future and to address carbon dioxide (CO2) emissions from construction materials, the construction industry has been seeking solutions for proactive climate change ...
Key Decision-Making Factors Influencing Bundling Strategies: Analysis of Bundled Infrastructure Projects
Publisher: American Society of Civil Engineers
Abstract: Project bundling is the process of awarding a single contract to several infrastructure projects to address construction, rehabilitation, replacement, or maintenance needs. This novel approach has presented several benefits ...
Improving the Predictive Analytics of Machine-Learning Pipelines for Bridge Infrastructure Asset Management Applications: An Upstream Data Workflow to Address Data Quality Issues in the National Bridge Inventory Database
Publisher: ASCE
Abstract: The increasing availability of bridge data from the National Bridge Inventory (NBI) offers a great opportunity to perform predictive analytics (such as bridge deterioration prediction) using machine learning (ML) pipelines ...
Development and Validation of a Heat Resilience Index: Measuring Communities Resilience to Extreme Heat Events
Publisher: American Society of Civil Engineers
Abstract: The level of preparedness of communities to heat-related consequences varies. While several studies have developed heat vulnerability indices, little-to-no research efforts were directed to assess the heat resilience of ...
Analyzing the Critical Success Factors Affecting Project Bundling Performance of Infrastructure Projects
Publisher: American Society of Civil Engineers
Abstract: Project bundling is an innovative project-delivery approach that bundles and groups different infrastructure projects into a single contract. Project bundling provides numerous opportunities and benefits for agencies and ...
Modeling the Impact of Low-Carbon Procurement on Bidding Dynamics
Publisher: American Society of Civil Engineers
Abstract: Low-carbon procurement policies are growing rapidly at the local, state, and federal levels within the US and globally. Despite the prevailing recognition of the importance of low-carbon procurement, the research effort ...
A Data-Driven Decision-Support Tool for Selecting the Optimal Project Delivery Method for Bundled Projects: Integrating Machine Learning and Expert Domain Knowledge
Publisher: American Society of Civil Engineers
Abstract: Project bundling is an innovative project delivery approach that combines several projects under a single contract. While previous studies have provided important information about different project bundling-related aspects, ...
Developing a Scoring Framework to Assess the Feasibility of the Design–Build Project Delivery Method for Bundled Projects
Publisher: American Society of Civil Engineers
Abstract: Project bundling has been introduced as an innovative approach that groups several infrastructure projects into a single contract. Project bundling has numerous benefits such as expediting project delivery, capitalizing ...
A Real-Time Intelligent Acoustic IoT-Enabled Embedded Construction Site Monitoring and Alert System: Integrating Deep Learning–Based Machine-Listening Algorithms, Edge Computing, and Cloud Computing
Publisher: American Society of Civil Engineers
Abstract: Acoustic-based construction site monitoring approaches have attracted recent interest due to their advantages compared to other methods. Previous relevant studies have many limitations, including narrowly focusing on sounds ...
Expert Knowledge–Guided Bayesian Belief Networks for Predicting Bridge Pile Capacity
Publisher: ASCE
Abstract: Bridge pile capacity is a vital criterion used to assure the durability and stability of a bridge pile foundation. In fact, reliably predicting the pile capacity plays a significant role in supporting data-driven decisions ...