Risk-based Framework for Management of Construction Projects

Well-developed risk management tools provide critical support for successful delivery of construction projects. Considerable research has been conducted towards integration of risk management in front-end planning and in execution phases of this class of projects. The accuracy of these tools relies heavily on their respective assumptions and on the data used in their application. Consideration of risk in these tools utilizes two types of data: actual past records and estimated future data related to completion of projects under consideration. The literature reveals that most published work in this area utilized these data either in bidding phase or in one of individual project execution phases to minimize the negative impact of risk on project cost and duration at completion. However, there is a lack of a comprehensive framework that employs both types of data in different phases of construction projects. This prevents construction practitioners from implementing an efficient risk management program. In this research, a new risk-based framework is developed, addressing limitations of existing models for different management functions over project lifecycle. The developed framework employs past performance data of construction organizations and projects in the bidding phase for risk maturity evaluation, contingency estimation, markup estimation, planning and scheduling, and progress reporting. The framework has five developed models. The first introduces a decision support model for risk maturity evaluation of construction organizations to identify their strengths and weaknesses in risk management processes, employing the Analytic Network Process (ANP) and fuzzy set theory. It enables construction organizations to assess and continuously improve their risk management capabilities. The second model introduces a new cost contingency estimation model considering correlations among project cost items, subjectively and objectively. It is also capable of modeling project cost contingency with and without the use of Monte Carlo simulation, which is deemed particularly useful when using subjective correlations. The third model introduces new pattern recognition techniques for estimating project markup. It utilizes Multiple Regression (MR), Artificial Neural Network (ANN) and Adaptive Nero-Fuzzy Inference System (ANFIS) techniques for that purpose, considering five factors: need for work, job uncertainty, job complexity, market condition, and owner capability. The fourth model introduces a newly developed multi-objective optimization model for scheduling of repetitive projects under uncertainty. The model considers the estimated cost contingency and the project markup in the total project cost and conducts, simultaneously, trade-offs between project duration, project cost, crew work interruptions, and interruption costs. It safeguards against assignment of unnecessary costly resources and provides a reliable project baseline. The fifth model presents a newly developed risk-based earned duration management model (RBEDM) that utilizes the generated project baseline in forecasting project duration at completion, considering critical activities only and their associated risk factors. It introduces a new risk adjustment factor (RAFcr) that quantifies the impact of future uncertainties associated with critical activities in estimating project duration at completion. This unique aspect of the developed model addresses the main drawback of earned duration management (EDM) its reliance on past performance data only. It also assists project managers in estimating more accurate and realistic required time to project completion

Collapsibility Prediction of Stabilized Soil with Styrene-Butadiene Rubber Polymer Using ANFIS

Collapsible soils are among the problematic soils in nature that, due to moisture content increasing and under the same stress, show a high rate of decrease in volume. This volume reduction leads to loss of soil structure and ultimately to significant subsidence. Such soils in many parts of the world, including the Kerman province of Iran, necessitate researches regarding the collapsible soils\u27 behavior and characteristics. This study aims to investigate the effect of butadiene rubber on the stabilization of collapsible soils. The tested fine-grained soils that have been sampled from two different sites were stabilized through injecting different percentages of butadiene (the number of experiments was 84). The ASTM D5333 Double-Consolidation Method was applied to examine the stabilized soils on intact soil samples. The results show that the penetrations of butadiene rubber and the formation of butadiene rubber columns have led to a reduction in soil collapse. Considering the development of intelligent systems using the prediction behavior of stabilized collapsible soils, the adaptive neural-fuzzy inference system (ANFIS) model was used to predict the degree of collapsibility of soil samples stabilized by injection of Styrene Butadiene Rubber

Organic–Inorganic Halide Perovskite Formation: In Situ Dissociation of Cation Halide and Metal Halide Complexes during Crystal Formation

Organic–inorganic halide perovskites have shown great promise as photovoltaic materials that bridge the gap between facile and low-cost fabrication and exceptional solar cell performance. Manipulation of the stoichiometry and chemistry of the precursors is among the main techniques for controlling the structural properties of perovskite layer. Herein we report that when a precursor solution containing excess cation halides (CH₃NH₃I) is utilized for perovskite formation, in situ dissociation of cations (CH₃NH₃⁺) occurs. The excess iodide ions­(I^–) mostly participate in the formation of iodoplumbate complexes such as PbI₃^– and PbI₄^2–. It is shown that the released energy from the crystal formation reaction can dissociate the free CH₃NH₃I molecules and iodoplumbate complexes into smaller molecules such as CH₃I and NH₃. When the I^– concentration in the precursor is increased, more complexes are formed and subsequently more dissociations occur. The produced components are mostly trapped in the perovskite crystals and can act as defects

Stability improvement of MAPbI3-based perovskite solar cells using a photoactive solid-solid phase change material

Funding Information: The authors would like to acknowledge the financial support from the research department of Tarbiat Modares University (Research group of phase change materials, Grant No. IG-39710 and research group of nano plasma photonic, IG-39704 ). Maryam Mousavi would acknowledge the financial support from Fortum and Nestse Foundation (Grant No. 20210045 ), Espoo, Finland. Publisher Copyright: © 2021In this work, to increase the optical and thermal stability of perovskite solar cells, the composition of the perovskite layer is engineered by adding azobenzene (AZO) as a photoswitchable organic molecule. In this regard, solar cells with the FTO/b-TiO2/m-TiO2/CH3NH3PbI3/HTM/Au structure are fabricated using spiro-OMETAD hole transporting layer. Remarkably, an improvement of the optical, thermal, and structural stability of the devices comprising 5%, 10%, and 20% AZO is observed. Through the solid-solid phase-change mechanism of AZO, harmful UV radiation is absorbed and leads to photoisomerization between the trans and cis isomers, thus aiding in the management of thermal stresses on the device. Devices with pure perovskite absorber layer and perovskite absorber layer containing 10 wt% AZO retained 43% and 70% of their initial performances, respectively, after 70 min of exposure to sunlight. Furthermore, after 1440 h of storage in ambient conditions (25 ℃ and 42% relative humidity), the reference device maintains 35% of its initial performance while the device containing 10 wt% AZO retains 89% of its initial performance. In the case of thermal stability, the device containing 10% AZO shows superior thermal stability by keeping about 55% of its initial efficiency after exposure to a temperature of 85 ℃ and one sun illumination, simultaneously, for 60 min, compared to the reference device which retains only 35% of its performance under the same condition.Peer reviewe