Sharif Digital Repository

Construction managers regularly monitor projects to ensure that the project performance is under control. The earned value method (EVM) is a widely used tool to forecast project cost and time at completion. However, the effectiveness of the EVM in forecasting schedule performance has been questioned particularly because of its inability to address the associated uncertainties and poor performance in predicting project duration. The objective of this study is to present an activity-based model to conduct a probabilistic assessment and estimation of schedule performance in repetitive construction projects. This model, called the Weibull evaluation and forecasting model (WEFM), emphasizes the... 

In the aftermath of earthquakes, hospitals serve the critical role of treating casualties. In many cases, the key components of a hospital (i.e., the building, staff, medicine inventory, technical systems, and medical equipment) are affected by an earthquake. To handle the demand surge, affected hospitals should recover in an effective manner. Hospital recovery is a complex and dynamic process because each component requires specific types and amount of resources to recover. Furthermore, the recovery of each component not only affects its performance but also plays a role in the overall hospital recovery. Hospital administrators need to model the complex recovery process after a future... 

Interventions such as seismic retrofits and reconstruction of vulnerable buildings can minimize the social and economic consequences of future earthquakes. Various policies can reduce the vulnerability of communities in the face of future earthquakes by enhancing the public risk perception and reducing the costs of interventions for the landlords. There is a need for appropriate tools that can characterize the dynamics of the housing market in response to these policies. The simulation model presented in this manuscript addresses this need. In this model, the decision of the tenants and landlords is characterized by utilizing prospect theory. The impact of candidate policy interventions on... 

This manuscript presents a framework to develop vector error correction (VEC) models applicable to forecasting the short- and long-run movements of the average hourly earnings of construction labor, which is an essential predictor of the construction labor costs. These models characterize the relationship between average hourly earnings and a set of explanatory variables. The framework is applied to develop VEC forecasting models for the average hourly earnings of construction labor in the USA based on the identified variables that govern its movements, such as Global Energy Price Index, Gross Domestic Product, and Personal Consumption Expenditures. More than 150 candidate VEC models were... 

Due to the unavailability of accurate data and the limitations of the existing methods, reliable input–output tables (IOTs) may not be available for all the regions in a country. This study proposes a novel approach to estimate the regional input coefficients. It harnesses the capabilities of machine-learning (ML) algorithms to estimate the regional input coefficients of one region based on the IOTs of multiple other regions for which reliable data are available. The application of three ML algorithms is investigated using data from Japan. The results highlight the superior performance of the ML models compared with location quotient models. © 2021 Regional Studies Association  

Natural Gas Distribution Networks (NGDNs) are complex infrastructure systems that play an essential role in ensuring the welfare and prosperity of many communities by serving their residential, commercial, industrial, and transportation sectors. Earthquakes can damage the critical components of NGDNs and disrupt their services. The disruption of NGDN services can lead to significant economic and social losses. These losses can be mitigated by adopting appropriate resilience enhancement measures. This study puts forward a probabilistic framework to quantify the seismic resilience of NGDNs. This framework comprises multiple interconnected probabilistic models that work in harmony to... 

Earthquakes can cause significant damage to vulnerable residential buildings and cause irreversible adverse economic, social, and socioeconomic consequences. Implementing hazard mitigation policies can enhance homeowners' willingness to adopt hazard mitigation measures such as seismic retrofits or insurance. Several past studies have proposed models that aimed to explain individuals' hazard mitigation behavior. Despite their advantages, these decision-making models are subject to limitations. This manuscript proposes a new decision-making model that addresses the shortcomings of previous models. The proposed decision-making model is then incorporated at the core of an agent-based model to... 

Due to the unavailability of accurate data and the limitations of the existing methods, reliable input–output tables (IOTs) may not be available for all the regions in a country. This study proposes a novel approach to estimate the regional input coefficients. It harnesses the capabilities of machine-learning (ML) algorithms to estimate the regional input coefficients of one region based on the IOTs of multiple other regions for which reliable data are available. The application of three ML algorithms is investigated using data from Japan. The results highlight the superior performance of the ML models compared with location quotient models. © 2021 Regional Studies Association  

Engineering, procurement and construction (EPC) contracts are commonly used for the construction of oil and gas production facilities. These projects are subjected to many uncertainties. EPC contractors often assume most of the project risks. Several studies have focused on the identification and analysis of EPC project risks. However, they generally fail to define appropriate and effective risk management strategies. The objective of this study is to define efficient risk mitigation strategies that can be utilized in EPC oil and gas projects. A comprehensive review of literature was conducted to identify the risks in EPC projects. Experts' opinion were used to analyze and categorize these... 

This study presents a framework that utilizes Bayesian regression to create probabilistic cost models for retrofit actions. Performance improvement is the key parameter introduced in the proposed framework. The incorporation of this novel feature facilitates the characterization of retrofit cost as a continuous function of the desired performance improvement. Accounting for the performance gained from retrofit enables the use of the models in determining the optimal level of retrofit. Furthermore, accounting for the model uncertainty facilitates the use of the models in risk and reliability analyses. The proposed framework is applied to create seismic retrofit cost models for masonry school... 

Recently, development of advanced materials of metal-organic frameworks (MOFs) has attracted attention for the fabrication of supercapacitors (SCs) because of their high surface area and high level of porosity. However, poor electrical conductivity and weak mechanical properties of the MOFs have restricted their applications in the field. In this study, a one-step, in-situ synthesis of Cobalt-based MOF with graphene (CoMG nanocomposite) was employed to overcome the poor properties of MOFs. Accordingly, when the nanocomposite (CoMG5) was use as a supercapacitor electrode material, a specific capacitance (CS) of 549.96 F g−1 was observed in a three-electrode system with 6 M KOH electrolyte... 

Purpose: Motivated by the high cost of material movements in road construction projects, past studies have used analytical methods to optimize materials logistics plans. A key shortcoming of these methods is their inability to capture the uncertain, dynamic and complex characteristics of the road construction material logistics. Failure to incorporate these characteristics can lead to sub-optimal results. The purpose of this study is to propose the use of discrete event simulation (DES) to address the existing shortfall. Design/methodology/approach: Despite the powerful capabilities of DES models in capturing the operational complexities of construction projects, they have not been... 

Recently, development of advanced materials of metal-organic frameworks (MOFs) has attracted attention for the fabrication of supercapacitors (SCs) because of their high surface area and high level of porosity. However, poor electrical conductivity and weak mechanical properties of the MOFs have restricted their applications in the field. In this study, a one-step, in-situ synthesis of Cobalt-based MOF with graphene (CoMG nanocomposite) was employed to overcome the poor properties of MOFs. Accordingly, when the nanocomposite (CoMG5) was use as a supercapacitor electrode material, a specific capacitance (CS) of 549.96 F g−1 was observed in a three-electrode system with 6 M KOH electrolyte... 

In the absence of effective and adequate vaccines, healthcare decision-makers must rely on non-pharmaceutical interventions (NPIs), such as lockdown, testing, hospital capacity building, and increasing the number of medical staff to control the outbreak of an infectious disease like COVID-19. This manuscript presents a System Dynamics (SD) model to analyze the healthcare system performance under various NPIs during a pandemic. The proposed model, which extends the commonly-used Susceptible-Exposed-Infectious-Recovered (SEIR) model, comprises four sub-models: outbreak, hospital performance, medicine supply, and staff functionality. These sub-models work in harmony to stimulate the impact of... 

Systemic inflammation biomarkers have been associated with risk of cardiovascular morbidity and mortality. We aimed to clarify associations of acute exposure to particulate matter (PM10(PM < 10 μm), PM2.5-10(PM 2.5–10 μm), PM2.5(PM < 2.5 μm), PM1-2.5(PM 1–2.5 μm), and PM1 (PM < 1 μm)) with systemic inflammation using panels of elderly subjects and healthy young adults. We followed a panel of 44 nonsmoking elderly subjects living in a retirement home and a panel of 40 healthy young adults living in a school dormitory in Tehran city, Iran from May 2012 to May 2013. Blood biomarkers were measured one every 7–8 weeks and included white blood cells (WBC), high sensitive C-reactive protein... 

In the present work, we investigated the characteristics of polycyclic aromatic hydrocarbons (PAHs) and metal(loid)s in indoor/outdoor PM10, PM2.5, and PM1 in a retirement home and a school dormitory in Tehran from May 2012 to May 2013. The results indicated that the annual levels of indoor and outdoor PM10 and PM2.5 were much higher than the guidelines issued by the World Health Organization (WHO). The most abundant detected metal(loid)s in PM were Si, Fe, Zn, Al, and Pb. We found higher percentages of metal(loid)s in smaller size fractions of PM. Additionally, the results showed that the total PAHs (ΣPAHs) bound to PM were... 

This paper proposes a model for a financial assessment of construction companies. This model is derived from the combination of data envelopment analysis (DEA), entropy method (EM), and TOPSIS. In the first step of the model, the financial ratios are calculated based on balance sheets and income statements. In the next step, the 15 ratios are categorized and classified utilizing a combination of TOPSIS and EM methods. Finally, they are aggregated in six indicators. Then, the BCC model of DEA with the type of output-oriented is used for these six indicators to calculate companies' relative efficiency. In the paper's conclusion, the model is examined in 20 construction companies that obtained...