Ali Mostafavi

Selecting Appropriate Project Delivery System: Fuzzy Approach with Risk Analysis

The selection of an appropriate project delivery system that suits all project and owner needs is one of the key decisions to a successful project. Therefore, this decision should be made based on thorough analysis. In this paper, a fuzzy multiattribute decision-making (FMADM) model is developed. The model accounts for uncertainties and imprecision in the decision space as well as fuzziness in the nature of the decision attributes. The model utilizes fuzzy decision-making approach in order to evaluate the membership function corresponding to the utility of each project delivery alternative. Project delivery system alternatives are ranked using fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method based on their utility membership functions and by evaluating the distance of each project delivery alternative from fuzzy ideal solutions. In the TOPSIS method, alternatives are ranked based on their closeness coefficient (CC). In addition, the risk attitude of the decision maker is considered in the model by using derived utility membership functions corresponding to the risk attitude of the decision maker. The model is applied to a petrochemical project as a case study. In the case study, the model outcome that ranked Turnkey system as the best system conforms to the lessons learned by the decision maker from several past projects. Moreover, sensitivity analysis is done in the case study. The results show the significant value of the FMADM model for selecting appropriate project delivery system for projects.

Assessment of network-level environmental sustainability in infrastructure systems using service and performance adjusted life cycle analysis

Managing environmental impacts of civil infrastructure systems is critical for fostering sustainable development. However, despite the growing body of literature, an integrated methodology that captures the specific traits of infrastructure systems for a network-level environmental impact assessment is still missing. The objective of this paper is to propose a novel methodology [called Service and Performance Adjusted Life Cycle Assessment (SPA-LCA)] for addressing the limitations of the traditional LCA in environmental assessment of infrastructure networks. The SPA-LCA methodology adopts a service-based accounting approach to enable aggregation of the impacts pertaining to assets with different functions and service life expectancies at the network level. In the proposed SPA-LCA methodology, first, through conducting traditional asset-level LCA, life cycle inventories for the assets are determined. Second, the life cycle inventories are disaggregated to performance-sensitive and nonesensitive impacts. Then, using a hybrid mathematical/agent-based simulation model, the levels of service and performance are simulated for different assets in the network across the analysis horizon. Finally, the environmental impacts are determined for each year based on the levels of service and performance. The application of the proposed SPA-LCA method is demonstrated in environmental assessment of a road network. The results highlight the capabilities of SPA-LCA in providing better insight regarding environmental performance of infrastructure networks.

Service and performance adjusted life cycle assessment: a methodology for dynamic assessment of environmental impacts in infrastructure systems

Abstract Infrastructure systems are at the core of the sustainability challenge. Currently life cycle assessment (LCA) is widely used for assessing environmental sustainability of infrastructure systems. However, infrastructure systems have specific traits that are incompatible with the requirements of LCA. In particular, infrastructure systems do not have definite ‘life cycle’ as a basis of LCA. In addition, environmental performance of infrastructure systems depends on the dynamic changes in the level of service and performance of infrastructure normally not captured in existing LCA approaches. The objective of the research presented in this paper attempts to address the limitations of existing LCA approaches by creating a service and performance adjusted LCA (SPA-LCA) methodology, one which is specifically tailored for the requirements of environmental assessment of infrastructure systems. Among other improvements, the created methodology introduces a dynamic conception of life cycle inventory analysis and a service-based environmental accounting for the impact assessment phase of LCA. A simulation-based computational model is created to enable implementation of the SPA-LCA methodology. The SPA-LCA method and the created computational model are tested in a case study related to assessing the environmental impacts of a pavement network. Results include assessing impacts of different budget and demand scenarios on the environmental performance of the case study network. The results indicate capabilities of SPA-LCA methodology in addressing the limitations of existing LCA approaches for assessing environmental impacts of infrastructure systems.

Adaptive Capacity under Chronic Stressors: Assessment of Water Infrastructure Resilience in 2015 Nepalese Earthquake Using a System Approach

AbstractThe objective of the study presented in this paper is to investigate determinants of resilience in water infrastructure systems in developing countries using the case study of the 2015 Nepa...

Performance Assessment in Complex Engineering Projects Using a System-of-Systems Framework

In this paper, a system-of-systems (SoS) framework is proposed for bottom-up assessment of complex engineering projects. Two principles of SoS analysis (i.e., base-level abstraction and multilevel aggregation) are used to develop the proposed framework. At the base level, complex engineering projects are abstracted as various entities (i.e., human agents, resources, and information) whose attributes and interactions influence the dynamic behaviors of project systems. The performance of project systems at higher levels (i.e., activity level, process level, and project level) is then determined by aggregating entities at the levels below. Through the use of the proposed SoS framework, new dimensions of analysis for better understanding of the performance of engineering projects were explored. One application example of the proposed framework was demonstrated in a case study of a complex construction project. The findings highlight the capability of the proposed framework in providing a novel approach for bottom-up assessment of performance in engineering projects.

A System Analytics Framework for Detecting Infrastructure-Related Topics in Disasters Using Social Sensing.

The objective of this paper is to propose and test a system analytics framework based on social sensing and text mining to detect topic evolution associated with the performance of infrastructure systems in disasters. Social media, like Twitter, as active channels of communication and information dissemination, provide insights into real-time information and first-hand experience from affected areas in mass emergencies. While the existing studies show the importance of social sensing in improving situational awareness and emergency response in disasters, the use of social sensing for detection and analysis of infrastructure systems and their resilience performance has been rather limited. This limitation is due to the lack of frameworks to model the events and topics (e.g., grid interruption and road closure) evolution associated with infrastructure systems (e.g., power, highway, airport, and oil) in times of disasters. The proposed framework detects infrastructure-related topics of the tweets posted in disasters and their evolutions by integrating searching relevant keywords, text lemmatization, Part-of-Speech (POS) tagging, TF-IDF vectorization, topic modeling by using Latent Dirichlet Allocation (LDA), and K-Means clustering. The application of the proposed framework was demonstrated in a study of infrastructure systems in Houston during Hurricane Harvey. In this case study, more than sixty thousand tweets were retrieved from 150-mile radius in Houston over 39 days. The analysis of topic detection and evolution from user-generated data were conducted, and the clusters of tweets pertaining to certain topics were mapped in networks over time. The results show that the proposed framework enables to summarize topics and track the movement of situations in different disaster phases. The analytics elements of the proposed framework can improve the recognition of infrastructure performance through text-based representation and provide evidence for decision-makers to take actionable measurements.

Teaching Building Sciences in Immersive Environments: A Prototype Design, Implementation, and Assessment

ABSTRACT Immersive technologies are transforming all aspects of daily life. In educational context, augmented reality (AR) and virtual reality (VR) offer the promise of experiential learning, where the real world is enhanced with information and graphics or is completely simulated. The project described in this paper, builds on advances of these technologies to develop, implement, and test “Skope,” a prototype immersive learning environment. Skope is designed to facilitate interdisciplinary education of architecture, engineering, and construction (AEC) students for design and construction of environmentally sustainable buildings. The Skope learning environment is comprised of an AR and a VR visualization tool as well as learning modules that contain interdisciplinary content. Skope is implemented and tested in three interdisciplinary AEC classes. Quantitative and qualitative analyses of student performance in these classes suggest that Skope has a positive impact and increased students’ motivation and understanding of building science principles, ultimately leading to an improvement of learning across domains. In addition, findings of this research indicate that using Skope improves students’ attitude toward collaborative learning.

An Automated Methodology for Worker Path Generation and Safety Assessment in Construction Projects

Collisions between automated moving equipment and human workers in job sites are one of the main sources of fatalities and accidents during the execution of construction projects. In this paper, we present a methodology to identify and assess project plans in terms of hazards before their execution. Our methodology has the following steps: 1) several potential plans are extracted from an initial activity graph; 2) plans are translated from a high-level activity graph to a discrete-event simulation model; 3) trajectories and safety policies are generated that avoid static and moving obstacles using existing motion planning algorithms; 4) safety scores and risk-based heatmaps are calculated based on the trajectories of moving equipment; and 5) managerial implications are provided to select an acceptable plan with the aid of a sensitivity analysis of different factors (cost, resources, and deadlines) that affect the safety of a plan. Finally, we present illustrative case study examples to demonstrate the usefulness of our model.Note to Practitioners—Currently, construction project planning does not explicitly consider safety due to a lack of automated tools that can identify a plan’s safety level before its execution. This paper proposes an automated construction safety assessment tool which is able to evaluate the alternate construction plans and help to choose considering safety, cost, and deadlines. Our methodology uses discrete-event modeling along with motion planning to simulate the motions of workers and equipment, which account for most of the hazards in construction sites. Our method is capable of generating safe motion trajectories and coordination policies for both humans and machines to minimize the number of collisions. We also provide safety heatmaps as a spatiotemporal visual display of construction site to identify risky zones inside the environment throughout the entire timeline of the project. Additionally, a detailed sensitivity analysis helps to choose among plans in terms of safety, cost, and deadlines.

A simulation framework for ex-ante analysis of safety and productivity in construction projects

Safety hazards are one of the major challenges facing construction industry across the globe. Despite a growing literature on assessment of construction safety, the majority of the existing studies are descriptive in nature, do not capture the specific conditions of construction operations and provide onesize-fits-all strategies for enhancing the safety of construction projects. On the other hand, productivity improvement is also a main concern in construction projects. However, the research effort addressing both safety and productivity improvement concerns is still missed in the construction industry. Among different tools used for construction project planning and productivity improvement, discrete event simulation is a well-known tool which has been widely used for analyzing and improving complex construction operations. In this research, for the first time, we are proposing a simulation based framework which concurrently follows safety and productivity improvement in construction projects.

Hybrid Technologies for Interdisciplinary Education

Integrated applications using Augmented Reality (AR) and Building Information Modeling (BIM), enhanced by the capacity of handheld devices, are becoming prevalent in the building industry; however their use in learning environments has not been fully explored. Recent research shows that interaction with computer-based tools can enhance learning and collaboration skills. Augmented Reality–the ability to enhance real world observations with computer-generated information– is bringing new dimensions to learning. Combining AR with computer modeling applications and other simulation technologies promises to guide the next generation of computer-based learning environments. This paper describes a learning environment, Ecocon, designed by the integration of AR, BIM, visual simulations, and interactive lessons to support collaborative and interdisciplinary learning for the Architecture, Engineering and Construction (AEC) fields. Building on theoretical perspectives and advances in the understanding of learning processes, cognition, and development, we describe the pedagogical principles for the design of a prototype tool to enhance AEC interdisciplinary education. The main features of the tool include: 1) using real-world or field contexts for delivering context-aware information and lessons, 2) enriching AR visualization with “intelligence,” so augmented information is responsive to a user’s location, and 3) providing data visualization to support learning.