Concrete waste (CW) recycling stands as a promising strategy to promote sustainable construction practices. This research aims to assess the feasibility of using recycled concrete aggregates (RCA) as a surrogate for natural aggregates (NA) in concrete applications and reduce the environmental impact associated with the depletion of natural resources and landfill space. To achieve these objectives, CW was segregated from debris mixes of construction and demolition waste (CDW), collected, crushed, and graded to generate RCA. Thirty-two concrete samples were prepared and categorized into four distinct groups with 0% (reference), 50%, 75%, and 100% substitution levels for both coarse RCA (CRCA) and fine RCA (FRCA), all utilized simultaneously. Concurrently, the environmental impacts of producing 1 m³ of concrete were evaluated using a life cycle assessment (LCA) approach, (cradle-to-gate) covering three phases, the raw material supply (A1), transportation (A2) and concrete production (A3). At the 50% replacement level, the mechanical properties of recycled aggregate concrete (RAC) demonstrated a 20.0% increase in splitting tensile strength, accompanied by marginal decrease in workability (15.0%) and compressive strength (6.0%). In addition, at that percentage, the average environmental effects were reduced by 31.3%, with specific reductions of 34.7% for A1, 40.3% for A2, and no change in A3.

This paper introduces and further applies an approach to support the decision makers in construction projects differentiating among a variety of deep excavation supporting systems (DESSs). These kinds of problems include dealing with uncertainty in data, multi-criteria affecting the decision, and multi-alternatives to select one from them. The proposed approach combines the analytic hierarchy process (AHP) with the fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS) in a multicriteria decision-making (MCDM) model. The MCDM model emphasize the ability to combine expert knowledge, cost calculations, and laboratory test results for soil properties to achieve the scope. The model proved it had a superior ability to deal with the complexity and vague data that are related to construction projects. Furthermore, it was applied to a real case study for a governmental housing project in Egypt. Secant pile walls, sheet pile walls, and soldier piles and lagging are selected and studied as being the most common DESSs and as they satisfy the project requirements. The model utilized four criteria and fourteen comparing factors, including site characteristics, safety, cost, and environmental impacts. Based on the results of the model application on the investigated case study, a decision was reached that using secant piles as a supporting system in this project is mostly preferred. Furthermore, sheet pile wall, and soldier piles and lagging, come next in the ranking order. A sensitivity analysis is carried out to investigate how sensitive the results are to the criteria weights. In addition, the paper discusses in detail the reasons and factors which affect and control the decision-making process.

Multi-Criteria Decision-Making (MCDM) techniques are found to be useful tools in project managersâ hands to overcome decision-making (DM) problems in Civil Engineering Projects (CEPs). The main contribution of this paper includes selecting and studying the popular MCDM techniques that uses different and wide ranges of data types in CEPs. A detailed study including advantages and pitfalls of using the Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) is introduced. Those two techniques are selected for the purpose of forming a package that covers most available data types in CEPs. The results indicated that AHP has a structure which simplifies complicated problems, while Fuzzy TOPSIS uses the advantages of linguistic variables to solve the issue of undocumented data and ill-defined problems. Furthermore, AHP is a simple technique that depends on pairwise comparisons of factors and natural attributes, beside it is preferable for widely spread hierarchies. On the other hand, Fuzzy TOPSIS needs more information but works well for the one-tier decision tree as well as it shows more flexibility to work in fuzzy environments. The two techniques have the facility to be integrated and combined in a new module to support most of the decisions required in CEPs. Keywords: Decision-making, AHP, Fuzzy TOPSIS, CBA, Civil Engineering Project

This paper develops a model, introduced in software, namely Multi-Criteria Decision-Making Model (MCDMM). The model helps decision makers selecting the most suitable alternative based on the customer requirements and preferences. Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) form a package that covers most available data types in construction projects. In MCDMM, AHP produces criteria relative weights according to their influence on the discussed problem, while Fuzzy TOPSIS is applied to rank the available alternatives. The model consists of two modules, first one uses AHP only to deal with precise, qualitative alongside quantitative data, while the other module combines AHP with Fuzzy TOPSIS due to the importance of linguistic variables to cover undocumented data. MCDMM is verified using two real case studies. The model is applied to a real case project for constructing solar power plants at Saudi Arabia. A decision required to select the most suitable surveying technique for producing Digital Terrain Model (DTM) among four alternatives (Total Station, Remote Sensing, Photogrammetry, and Global Positioning Systems). This issue is studied and key points are identified for prioritizing among them. Total Station is selected based on the model results.