The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision-making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are among the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision-making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. The geographical criteria are geology, land use, sediment, erosion, slope, groundwater, and discharge. The water quality criteria include Soluble Sodium Percentage, Total Dissolved Solid, Potential of Hydrogen, and Electrical Conductivity of water. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this study area. Actual locations of dams constructed in the area were used to verify the results of both methods.

Traditional energy analysis in Building Information Modeling (BIM) only accounts for the energy requirements of building operations during a portion of the occupancy phase of the building’s life cycle and as such is unable to quantify the true impact of buildings on the environment. Specifically, the typical energy analysis in BIM does not account for the energy associated with resource formation, recycling, and demolition. Therefore, a comprehensive method is required to analyze the true environmental impact of buildings. Emergy analysis can offer a holistic approach to account for the environmental cost of activities involved in building construction and operation in all its life cycle phases from resource formation to demolition. As such, the integration of emergy analysis with BIM can result in the development of a holistic sustainability performance tool. Therefore, this study aimed at developing a comprehensive framework for the integration of emergy analysis with existing Building Information Modeling tools. The proposed framework was validated using a case study involving a test building element of 8’ × 8’ composite wall. The case study demonstrated the successful integration of emergy analysis with Revit^®2021 using the inbuilt features of Revit and external tools such as MS Excel. The framework developed in this study will help in accurately determining the environmental cost of the buildings, which will help in selecting environment-friendly building materials and systems. In addition, the integration of emergy into BIM will allow a comparison of various built environment alternatives enabling designers to make sustainable decisions during the design phase.

Objective: To address prolonged lengths of stay (LOS) in a Level 1 trauma center, we examined the impact of implementing two data-driven strategies with a focus on the physical environment. Background: Crowding in emergency departments (EDs) is a widely reported problem leading to increased service times and patients leaving without being seen. Methods: Using ED historical data and expert estimates, we created a discrete-event simulation model. We analyzed the likely impact of initiating care and boarding patients in the hallway (hallway care) instead of the exam rooms and adding a dedicated triage space for patients who arrive by emergency medical services (EMS triage) to decrease hallway congestion. The scenarios were compared in terms of LOS, time spent in exam rooms and hallway spaces, service time, blocked time, and utilization rate. Results: The hallway care scenario resulted in significantly lower LOS and exam room time only for EMS patients but when implemented along with the EMS triage scenario, a significantly lower LOS and exam room time was observed for all patients (EMS and walk-in). The combination of two simulated scenarios resulted in significant improvements in other flow metrics as well. Conclusions: Our findings discourage boarding of admitted patients in ED exam rooms. If space limitations require that admitted patients be placed in ED hallways, designers and planners should consider enabling hallway spaces with features recommended in this article. Alternative locations for boarding should be prioritized in or out of the ED. Our findings also encourage establishing a triage area dedicated to EMS patients in the ED.

Diameters and wall thicknesses of flexible pipes are usually designed as per hydraulic requirements, such as flow capacity, internal fluid pressure, and pipe material properties. Proper embedment is then designed to protect the pipe integrity against external loads. This paper considered engineering properties of embedment soils in analysis of flexible pipe–soil system for external load conditions and a new model was developed for the prediction of deflection of flexible steel pipe. Full-scale laboratory tests were performed to develop the new model and finite-element models were analyzed to validate the test results. In this research, the finite-element method was effectively used to model the soil–pipe interaction for five full-scale laboratory tests conducted on a steel pipe. Such models can be used for analysis of flexible pipe embedment design for layered embedment conditions. The results of finite-element analysis showed that the squaring of the pipe occurs when the haunch soil is weak compared to the side column. Another critical observation made during the tests was that the stresses at the bottom of the pipe and the bedding angle are highly dependent on haunch soil strength. It is desirable that the stress due to surcharge load on top of the pipe, weight of the pipe, and water inside the pipe be distributed uniformly across the width of the bedding.

The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are amongst the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this case study. Actual locations of dams constructed in the area were used to verify the results of both methods.

This article is focused on developing an Energy Service Company (ESCO) risk assessment model for use by energy savings certificates (ESC) market regulators. This model enables market regulators to determine the appropriate point in time for ESCOs to sell their certificates with the aim of minimizing risk as well as maximizing economic gain yet remain motivated for reducing the cost of energy efficiency technologies. To this end, the interactions between an ESCO and other parties (such as suppliers) in the market in addition to the principles of the energy efficiency performance contract are taken into consideration. Then, appropriate probability distributions have been fitted to the stochastic variables to be applied in the Net Present Value (NPV) function, based on sampled company data. A case study considers a one MW Organic Rankine Cycle (ORC) implementation in Iran’s petrochemical industry. The finding of this study shows if the ESCO is allowed to sell the certificates during the first seven years as well reduce 30% of the investment cost, the expected Net Present Value over Investment Cost (NPV/I) savings will cover more than one cycle.