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• A novel approach for regional modeling and forecasting of PWV using LS-SVR is suggested. • The results of the new model are analyzed at control and radiosonde stations. • A comparative analysis between the results of new model, GPS and VBT is made. We propose a new model for spatio-temporal modeling and forecasting of precipitable water vapor (PWV) using least square support vector regression (LS-SVR) method. The LS-SVR uses simple linear equations. As a result, the complexity of the computational algorithm is reduced. In addition, the convergence speed and accuracy of the results increase. The evaluation of the new method has been done with the observations of the GPS networks at north-west and central Alborz in Iran. In the north-west GPS network, observations of 23 GPS stations in the period of 27 October to 10 November 2011 are used. However, in central Alborz network, the observations of 11 GPS stations in the period of 10 to 24 June 2016 have been used. The north-west GPS network is in the mountainous region and its observations are for the winter season. But, the second network is near the coastal area and summer season measurements are used. The latitude, longitude and height of GPS stations, DOY, time, relative humidity, temperature and pressure are considered as an input of the LS-SVR model. The output of the new model is the PWV (LS-SVR PWV). After the training step, the new model is used to estimate the spatio-temporal variation of PWV. The results of the LS-SVR model are compared and evaluated with the standard neural network (SNN), adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), Saastamoinen, global pressure and temperature 3 (GPT3), voxel-based tomography (VBT) models, as well as with radiosonde measurements. Error evaluation of models has been done in control stations as well as by precise point positioning (PPP) method. For LS-SVR model, the averaged RMSE in the control stations of the north-west GPS network is 1.69 mm, while for the central Alborz GPS network, 1.88 mm is calculated. Also, the averaged relative error of LS-SVR model calculated in the Tabriz and Tehran radiosonde stations are 4.66 % and 6.12 %, respectively. The results of this paper show that the LS-SVR model has a very high capability in forecasting the spatio-temporal variation of PWV at the GPS network territory. The new model can be used for accurate estimation of PWV, meteorological applications and flood forecasting. [ABSTRACT FROM AUTHOR]

• Determining the urban critical infrastructures in the event of an earthquake. • Designing Location-Routing-Inventory decisions in humanitarian relief chain. • Simulation of interaction of urban infrastructure in earthquake conditions. • Using a cooperative game to examine the manner of cooperation of disaster relief supply chain players. • Application of the model to a real-world disaster relief logistic case study. This paper describes a new simulation based mathematical model for locating distribution centres, vehicle routing, and inventory problems under earthquake conditions. In this paper, the proposed network includes affected areas, suppliers, distribution centres, and hospitals. Additionally, the basic infrastructures of the city, which are very fragile at the time of the earthquake, are identified. Then, the demand of each relief commodity is calculated depending on the different earthquake scenarios using simulation. The estimated demand is incorporated into the mathematical model as an uncertain parameter. The proposed methodology is designed as a two-stage model so that in the first stage the location and inventory of distribution centres are addressed. Thereafter, in the second stage the routing decisions are taken for the distribution of relief commodities from the distribution centres and suppliers to the affected areas. Due to the NP-hardness of the second stage model, this model is solved using multi-objective stochastic fractal search. This algorithm is one of the population-based and stochastic optimization techniques and inspired by the natural phenomenon of fractal growth. It should be noted that in the second stage, a cooperative game theory of coalition type is considered, which resulted in synergies that minimize the relief golden time. The kind of cooperation is the use of potential of co-operators' vehicle. In this stage, the possibility for the players to cooperate by sharing people and commodities transportation requests is considered. Also, to validate the model, a real case study is provided for a possible earthquake in Tehran. Finally, the comparison between the simulation results and the values obtained from the real system evaluates the performance of the implemented model. Considering normality and a 95% confidence interval, it can be concluded that the proposed model provides a precise representation of the real system's performance. [ABSTRACT FROM AUTHOR]

In this paper, a new method of temporal extrapolation of the ionosphere total electron content (TEC) is proposed. Using 3-layer wavelet neural networks (WNNs) and particle swarm optimization (PSO) training algorithm, TEC time series are modeled. The TEC temporal variations for next times are extrapolated with the help of training model. To evaluate the proposed model, observations of Tehran GNSS station (35.69°N, 51.33°E) from 2007 to 2018 are used. The efficiency of the proposed model has been evaluated in both low and high solar activity periods. All observations of the 2015 and 2018 have been removed from the training step to test the proposed model. On the other hand, observations of these 2 years are not used in network training. According to the F10.7, the 2015 has high solar activity and the 2018 has quiet conditions. The results of the proposed model are compared with the global ionosphere maps (GIMs) as a traditional ionosphere model, international reference ionosphere 2016 (IRI2016), Kriging and artificial neural network (ANN) models. The root mean square error (RMSE), bias, dVTEC = |VTEC GPS − VTEC Model | and correlation coefficient are used to assess the accuracy of the proposed method. Also, for more accurate evaluation, a single-frequency precise point positioning (PPP) approach is used. According to the results of 2015, the maximum values of the RMSE for the WNN, ANN, Kriging, GIM and IRI2016 models are 5.49, 6.02, 6.34, 6.19 and 13.60 TECU, respectively. Also, the maximum values of the RMSE at 2018 for the WNN, ANN, Kriging, GIM and IRI2016 models are 2.47, 2.49, 2.50, 4.36 and 6.01 TECU, respectively. Comparing the results of the bias and correlation coefficient shows the higher accuracy of the proposed model in quiet and severe solar activity periods. The PPP analysis with the WNN model also shows an improvement of 1 to 12 mm in coordinate components. The results of the analyzes of this paper show that the WNN is a reliable, accurate and fast model for predicting the behavior of the ionosphere in different solar conditions. [ABSTRACT FROM AUTHOR]

A multi-mode resource-constrained project scheduling problem (MRCPSP) with multiple skills is investigated in this paper. Unlike the traditional form of this problem, and considering the real-world project circumstances, project activities can be preempted. In this paper, a new multi-objective mixed-integer linear programming (MILP) model with three objective functions is extended. These objectives are: (1) minimizing the project makespan, (2) minimizing the total resource costs, and (3) minimizing the total project risk. Based on real-life projects, non-renewable resources are represented as an uncertain stochastic parameter. To cope with the uncertain environment, chance-constrained programming with a confidence level is considered. A real-world construction project of a sports center in Tehran is utilized to demonstrate the applicability of the presented formulation. A well-known lexicographic optimization method, namely AUGMECON2, is applied to solve the proposed formulation with three objectives. Ultimately, for the case study and two datasets J30 and MM50, the proposed lexicographic optimization algorithm is compared with an efficient multi-objective mathematical programming technique known as the AUGMECON method. The comparison is based on performance metrics (i.e., IGD and HV) commonly used in multi-objective optimization. The results show the relative dominance of the proposed lexicographic optimization algorithm over the AUGMECON method in all sizes of the problem instances. [Display omitted] • Considering a multi-skill multi-mode resource-constrained project scheduling problem with preemption. • Presenting a new multi-objective mixed-integer linear programming model for problem with a time lag between activities. • Minimizing three objectives: the total project risk, project makespan, and total project cost simultaneously. • Investigating the real project of building a sports center in a prominent engineering company to validate the model. • Proposing chance-constrained programming with the stochastic parameter and AUGMECON2 method for the first time. [ABSTRACT FROM AUTHOR]

This paper investigates the possibility of high resolution mapping of PM2.5 concentration over Tehran city using high resolution satellite AOD (MAIAC) retrievals. For this purpose, a framework including three main stages, data preprocessing; regression modeling; and model deployment was proposed. The output of the framework was a machine learning model trained to predict PM2.5 from MAIAC AOD retrievals and meteorological data. The results of model testing revealed the efficiency and capability of the developed framework for high resolution mapping of PM2.5, which was not realized in former investigations performed over the city. Thus, this study, for the first time, realized daily, 1 km resolution mapping of PM2.5 in Tehran with R 2 around 0.74 and RMSE better than 9.0 μ g m 3 . [ABSTRACT FROM AUTHOR]

This paper focuses on a comprehensive solution for dry municipal solid waste (MSW) management with describes the scenario of the gasification process. For this purpose, the potential of implementing the MSW gasification process in Southeast Asia (Iran) with three agents of air, steam, and air-steam is investigated. In order to manage the MSW gasification process as accurately as possible in the study area, a thermodynamic, exergy, economic, environmental, carbon footprint, water footprint, ecological emergy, and risk assessment for the three mentioned gasification agents were carried out in the most populated cities of Iran. In the capital of Iran (Tehran) with the largest population and as a result of largest MSW production, the potential of the gasification process has been investigated at different times (10 consecutive years and 12 months of a year). Finally, by combining artificial neural networks and genetic programming, comprehensive relationships have been established to predict the thermodynamic conditions of gasification with an air-steam agent. The general results of the survey indicate that gasification with air agents has good potential for most regions. The use of the steam agent has created worse economic, environmental, and risk conditions than the other two agents. Investigating the potential of the gasification process in Tehran shows that this city has a good potential to implement this process compared to other cities in Iran, and the most suitable location for establishing the gasification process is the 4th region of this city. [Display omitted] • Potential of municipal solid waste (MSW) gasification for all Iranian cities. • Comparison of using air, steam, and air-steam agents for MSW gasification. • The payback period of air agent MSW gasification is lower than other agents. • Machine Learning used for prediction of the behavior of MSW gasification. [ABSTRACT FROM AUTHOR]

The Integrated Solid Waste Management (ISWM) is a recent effective tool to manage with the growing challenge of Municipal Solid Waste (MSW). The ISWM integrates all the system components (i.e. transfer, treatment, recycling and disposal of wastes) to enhance the sustainable waste management whilst reducing operational costs. In this paper, we investigate an integrated framework of the Fleet Size and Mix Vehicle Routing Problem (VRP) to optimize the cost-effective ISWM system. A novel bi-objective Mixed-Integer Linear Programming (MILP) model is developed to concurrently minimize the transportation cost in the entire waste management system and total deviation from the fair load allocation to transfer stations. A complete ISWM system with all interdependent facilities and multiple technologies, is developed to address a tri-echelon Fleet Size and Mix VRP with a heterogeneous fleet of vehicles under multiple technologies and waste compatibility constraints. The model was solved for both the Preemptive and Non-Preemptive conditions using Lexicographic and Goal Programming optimization approaches. The model was tested on a case of ISWM in the Southern part of Tehran, Iran. [ABSTRACT FROM AUTHOR]

• The paper develops a new closed-loop hybrid system dynamics-optimization approach. • The system dynamics model and hybrid model are compared. • Energy production from waste is considered in the paper. • Social, environmental, and economic aspects are studied in the models. System dynamics approach is a tool to study socio-economic systems and make strategic decisions. However, it is not an appropriate planning method. For this purpose, optimization models are more powerful options. This paper represents a new combination of a system dynamics simulation with an optimization model to consider both aspects. For this purpose, a system dynamics model is developed to simulate the system in a feed-forward path. Then, it is connected to an already developed multi-objective optimization model on the feedback path in a real-time manner to constitute a hybrid closed-loop model. The hybrid model is applied to study the waste management system in Tehran. The focus of the hybrid model is on waste-to-energy technologies and how the system decides to install them. Comparing the hybrid model's results with those of the system dynamics model proves that the optimized policies considerably improve the system financially and environmentally. As far as technologies are concerned, the hybrid model suggests more capacities and diversity of technologies rather than the open-loop system dynamics model. Overall, the framework can be applied to all decision-making models that can add an advantage to system dynamics models. Moreover, the system dynamics model obtained through several scenarios shows that raising awareness, increasing Feed-in-Tariff, and investment in waste-to-energy technologies positively affect the waste management system. [ABSTRACT FROM AUTHOR]

This paper proposes a new Vehicle Routing Problem (VRP) with fair Carrier Collaboration (CC) which split multi-pickup and delivery services are considered for serving customers. This study has focused on VRP and serving customers with several commodity requirements from different geographically scattered suppliers subject to constraints on the vehicle capacity. A Mixed Integer Programming (MIP) model to maximize the total profit and the fair sharing of profit among the carriers by considering the travel time minimization is developed. Each carrier with its limited capacity can have reserved requests which must be served by itself and selective requests which can be served by itself or other vehicles or not served at all. There are various applications of the proposed model in the environment which can help reducing number of vehicles serving to the customers and eliminating empty back hauls. A Genetic Algorithm (GA) is proposed to solve this problem due to its Non-deterministic Polynomial-time hard (NP-hard) nature. In addition, Variable Neighbourhood Search (VNS) method is developed for improving the quality of initial solutions. Some instances are generated at different scales to evaluate the algorithm's performance by comparing the results of an exact optimal solution with that of the proposed algorithm. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time. The algorithm is also tested for an online shopping website in Tehran, Iran. The test outcome shows that the proposed model returns a better benefit compared to the manual methods. The results of sensitivity analysis suggest that increasing the fairness coefficient among carries can led to a decrease in the total obtained profit. • Develop a novel carrier collaboration routing problem model with multi-commodity service and sharing fair profit. • Extend the carrier collaboration to general problems with in many-to-one problem pickup and delivery category. • Solve the problem with genetic algorithm with a new specific chromosome representation. • Result of implementation of the model in the real-world and sample instances. • Sensitivity analysis of the model based on fair distribution between participants is conducted. [ABSTRACT FROM AUTHOR]

This paper aims to improve the spatial accuracy of urban growth simulation models and clarify any associated uncertainties. Artificial Neural Networks (ANNs), Random Forest (RF), and Logistic Regression (LR) were implemented to simulate urban growth in the megacity of Tehran, Iran, as a case study. Model calibration was performed using data between 1985 and 1999 whereas the data between 1999 and 2014 was used for model validation. First of all, Transition Index Maps (TIMs) were computed by means of each model to assess the potential of urban growth for each cell. Using the standard deviation, consensus between the TIMs was evaluated. Because the TIMs of the individual models manifested discrepancies, they were combined using a number of ensemble forecasting approaches including median, mathematical average, principle component analysis, and weighted area under the total operating characteristic. The individual and combined TIMs were then put into Cellular Automata (CA) to simulate the future pattern of urban growth in Tehran. The results were evaluated in two stages. At first, the TIMs were evaluated by means of Total Operating Characteristics (TOC), and then a set of statistical indices was used to evaluate the spatial accuracy of the simulated urban growth maps. The best result was obtained by median ensemble forecasting, whereas the LR model showed the lowest level of accuracy. In similar studies, it is recommended to implement and compare different ensemble methods when integrating individual models. • We compared the effectiveness of ANNs, RF and LR for urban growth modelling. • Standard error map indicated discrepancy among the results of individual models. • Various ensemble forecasting approaches were proposed to combine individual models. • Mean ensemble forecasting created more accurate simulated maps. [ABSTRACT FROM AUTHOR]

• A multi-criteria framework is proposed for bioethanol facility location. • The best worst method is used to calculate the weights of the criteria. • The provinces of Iran are evaluated as alternatives in this study. • A questionnaire answered by 41 experts from Iran is used for the BWM. • Province of Khuzestan (followed by Tehran) is selected for bioethanol production. One of the major factors in the success of renewable energy is finding a proper location for production facilities. At a national level, different parts of a country (e.g. provinces) can be seen as alternatives that can be assessed based on a set of criteria, and ranking them to identify the best location. The focus in this paper is on identifying the best location for the production of bioethanol. After a comprehensive literature review, an evaluation framework is proposed based on the three dimensions of sustainability (economic, environmental and social). Using data provided by a sample of experts in a developing country – Iran – and applying the best-worst method (BWM), a number of decision-making criteria are evaluated. Performance data involving the various provinces of Iran are collected from different sources. The performance data and the weights identified through BWM are used to calculate an overall score for each province, which is then used to rank the provinces, with the province of Khuzestan (closely followed by Tehran) being identified as the most suitable province for bioethanol production in Iran. [ABSTRACT FROM AUTHOR]

This paper presents a novel study on the multi-objective energy audit and management of a proposed plus-ZEB covered by a green roof in Tehran's climate. The planning impact of changing a proposed plus-ZEB to an intensive plus-ZEB is also evaluated. The planning is performed for one year based on Tehran's accurate urban climate data. The plus-ZEB consists of renewable and non-renewable resources like CHP, boiler, furnace, photovoltaic, solar water heater, wind turbine, air to the water heat pump, electric heat pump, and chiller boiler units in addition to energy storage to supply diverse electrical, thermal, and cooling demands of the presented building. The planning's functions are included in the total cost and emission of the plus-ZEB. The objective function prioritization is also participated to show the planner's decision on the function. Also, diverse solvers are implemented to evaluate and compare and validate results. The problem is simulated in energy plus to assess the amount of demands, construction materials, and energy audit issues; then, the results transfer to the GAMS software for energy management of the proposed plus-ZEB by utilizing a green roof. The problem in GAMS is modeled as a real mixed-integer programming (RMIP) and solved using the augmented epsilon constraint method (AEC). The final results show the significant effect of the proposed planning on reducing the cost and emission of the plus-ZEB, in which the total cost and pollution are decreased by about 7.4 % and 10.6 %, respectively. [ABSTRACT FROM AUTHOR]

In this paper, a new approach is proposed for the system identification of the stock returns. Allocating an accurate model to the nonlinear and stochastic financial system, which can accurately manifest the system, is considered one of the critical issues in control and system engineering. We employ an autoregressive with exogenous variable (ARX) process and propose a new model that accurately exhibits the stock returns system dynamics. The proposed model can identify the system with more than 96% accuracy. Furthermore, one of the indispensable approaches in the financial market, which presents a significant investment role, is forecasting the trends accurately. Therefore, we propose and implement a new algorithm, multiple adaptive forecast (MAF), based on adaptive control systems, estimation, and stochastic processes to detect the future trends of prices. In addition, we study some companies' stocks from Tehran Stock Exchange in this paper. Simulation results indicate that the proposed model obtains more accurate outcomes than the two other models. Ultimately, as inferred from the simulation results, employing the proposed model combined with the MAF algorithm would yield more competent outcomes for creating the portfolio for short-term investment. [ABSTRACT FROM AUTHOR]

This paper introduces a multi-objective robust optimization model for a municipal solid waste (MSW) management system consisting of customers, transfer stations, landfills, recycle plants, and waste transport vehicles. The proposed model addresses the economic, environmental, and social perspectives of this system simultaneously by minimizing the total cost, the greenhouse gas emission, and the resulting visual pollution, respectively. This model can aid decision makers to locate the optimal sites of MSW recycling and disposal facilities, optimize the capacity allocation of landfills to transfer stations and population centers, optimize the capacity allocation of transfers stations and recycle plants to population centers, determine the most suitable technology for each operation, and find the right number and type of transport vehicles based on aforementioned objectives. Comparing to prior studies, considering all three dimensions of sustainability (i.e. economic, environmental and social) simultaneously, attempting to locate all three major MSW processing and disposal facilities (namely, transfer stations, recycling plants, and landfills) at the same time, and Considering uncertainties involved in this group of facility location problems are the innovations of this study. The proposed model, which is also fully compatible with the waste segregation at source approach, was validated by the use of real data for long-term planning of Tehran's MSW management system by examining five candidate sites for the construction of new facilities. The results show the efficiency of proposed model. [ABSTRACT FROM AUTHOR]

• Designing a two-echelon blood bank network based on ABO/Rh substitution priority. • Considering the RBC inventory level in the HBB and BC simultaneously as a CTMC. • Modeling the (r , Q) inventory policy for all RBC types as eight dependent 2D-CTMCs. • Creating an imperfect queueing-inventory system in HBB integrating with eight CTMCs. • Developing a screening system in SL with false positive and false negative errors. The uncertain nature of blood supply and demand in a blood supply chain network (BSCN) makes it impossible completely meet the blood demands on time. That's why there is a vital need to develop a comprehensive model for optimally managing blood networks considering all challenges they face with. Although many researches have studied blood inventory management (BIM) in BSCNs, there is still a lack of models simultaneously considering blood inventory levels in hospital blood banks (HBBs) and blood centers (BCs) as a stochastic process. Also, most models have not evaluated the impact of false positive (FP) and false negative (FN) errors in the screening laboratories (SLs) of BCs. Moreover, no study has modeled the HBB demands as a queueing-inventory model with multiple blood types according to ABO/Rh substitution priority. To fill these gaps, this paper develops a two-echelon blood bank network considering ABO/Rh factors and substitution priority in which inventory levels of all red blood cell (RBC) types in an HBB and BC are simultaneously modeled as eight dependent continuous-time Markov chains (CTMCs). An unobservable M/M/m queueing-inventory system with infected RBCs and (r , Q) policy in the HBB is proposed. The blood requests arrive at the requests queueing system in the HBB, and after processing and departing from the queue, they leave the HBB with exactly-one RBC unit with the same ABO and Rh (Rhesus) groups or compatible with other types of RBC. Lost sales occur if all possible types of RBC for transfusion are unavailable. HBB continuously checks each RBC type's inventory level and places an order to the BC once the inventory level of each one of them reaches a predetermined reorder point. Due to transfusion-transmissible infections (TTIs), an SL conducts a 100 % quality-assured screening in the BC modeled as an M / M / m queueing system. Due to unreliable inspectors, FP and FN errors are considered in the SL. The stationary distribution of the number of requests at the HBB, the number of RBCs in the SL, and joint stationary distributions of inventory level of all RBC types in the HBB and BC are derived. Afterward, each RBC type's waiting-time distribution in the HBB is obtained. Some performance measures and the long-run total cost are extended, and a mixed integer nonlinear programming model (MINLP) is presented. Then, we propose the grasshopper optimization algorithm (GOA) to solve the complicated model. Also, this model is implemented in a case study in Tehran. Results show RBCs types O + and A + have the most lost sales, and the management should absorb more donors with these blood groups. Afterward, an approximation method to deal with multiple HBBs is suggested. Finally, several remarkable managerial and practical implications are presented. [ABSTRACT FROM AUTHOR]

The seismic hazard assessment of Tehran, the capital of Iran with a population of over 10 million, is necessary in the decision-making process for risk reduction. The main objective of this paper is to present a procedure for obtaining maximum hazard maps in seismically active regions such as Tehran with a history of destructive earthquakes, but where the number of the instrumentally recorded large magnitude events is small. The deterministic and probabilistic seismic hazard methods are two quantitative approaches with some practical limitations. To overcome their limitations, the Bayesian statistics are used to estimate maximum earthquake magnitude by combining prior seismological information with the available limited data. The Bayesian approach is used to estimate maximum earthquakes corresponding to different individual ground-motion scenarios at a specific hazard level. The maximum hazard maps are obtained by merging different individual worst-case ground-motion scenarios at a specific hazard level. The hazard analyses under different scenarios are conducted by the finite-fault procedure which uses geological and seismological parameters for each seismic source. The obtained results are in agreement with the observed intensities of historical earthquakes. Moreover, the conventional approach of probabilistic seismic hazard analysis is presented to show the difference between the two procedures. The findings provide information about the seismic design or retrofit of structures and infrastructures. [ABSTRACT FROM AUTHOR]

Because the building sector has become a huge energy consumer, providing useful approaches can help tackle this important issue. Windows are an important component of a building since most of the natural light inside the building is provided by passing this component. Improper design of windows and their associated components, such as shadings, overheats the space and increases energy consumption, and on the other hand, disturbs the visual and thermal comfort of the building's occupants. The present paper aims to present a new approach for multi-objective optimization of the architectural specifications and control parameters of a smart shadow curtain. The use of this proposed approach leads to a significant reduction in building energy consumption and improved thermal and visual comfort. Energy-related simulations are performed through EnergyPlus software. Afterward, 21 design variables including control strategies and setpoints, location and orientation of shading, slat dimensions and material specifications, as well as hourly slat angle are considered in JEPLUS software. These simulations are conducted in four geographical directions over seasonal and annual periods for the city of Tehran, Iran. JEPLUS + EA software is employed to perform sensitivity analysis on the outputs of JEPLUS software and data optimization. Morris sensitivity analysis is implemented to investigate the effects of input variables on the objective functions. The NSGA-II algorithm is then applied to optimize the data to extract the optimal points on a Pareto front. The optimization results indicate that the external blind performs better than the internal blind and also the smaller the angle of the blind slat is, the better the visual comfort is but increases the electricity consumption for lighting. A comparison of the results of multi-objective optimization of controlled blind characteristics with initial values demonstrates that based on geographical directions, the total energy consumption of the entire building decreases by a range of 40–50 % per year, while visual comfort and thermal comfort are improved by ranges of 70–100 % and 10–40 %, respectively. [ABSTRACT FROM AUTHOR]

Abstract: Train timetabling with minimum delays is the most important operating problem in any railway industry. This problem is considered to be one of the most interesting research topics in railway optimization problems. This paper deals with scheduling different types of trains in a single railway track. The primary focus of this paper is on the periodic aspects of produced timetables and the proposed modeling is based on the periodic event scheduling problem (PESP). To solve large-scale problems, a hybrid meta-heuristic algorithm based on simulated annealing (SA) and particle swarm optimization (PSO) is proposed and validated using some numerical examples and an Iranian case study that covers the railway line between two cities of Isfahan and Tehran. [Copyright &y& Elsevier]

Abstract: The availability of reliable and ubiquitous urban services data is a key component of successful city management. The inability of traditional bureaucratic public administration to meet citizens’ needs effectively has led to a search for new methods that grant more efficient, effective and reliable provision of services to citizens. Because there are many users with distinct computing platforms and preferences, urban services data must be accessible using interoperable solutions. Numerous solutions for providing interoperability are proposed by the Geospatial Information (GI) community, as well as the Information Technology (IT) community. The most widely used technologies for providing interoperability in the GI community are OGC services framework. In the IT community, Web services technologies provide full potential interoperability among heterogeneous computing platforms. However, these two kinds of services are not directly compatible. To provide an interoperable solution, OGC services and Web services should be integrated efficiently. The underlying issue in integrating OGC services and Web services is the gap between the predefined functionality inherent in the OGC services, and the lack of any predefined functionality in the Web services technologies. This paper identifies the implementation issues in integrating OGC services and Web services and then proposes standards-based approaches to overcome these integration issues. Afterwards, the paper explains the design and development of Standards-based Interoperable Services for Accessing Urban Services Data (SISAUSD). [Copyright &y& Elsevier]

• Reveals the role of alternative optimal solutions for portfolio selection using DEA cross-evaluation. • Improves the result of the mean-variance portfolio selection method. • Identifies superior stocks in the Tehran stock market. This paper deals with the role of alternative optimal solutions existing in the data envelopment analysis (DEA) models for cross-efficiency evaluation in portfolio selection. The paper shows that incorporating alternative optimal solutions for constructing cross-efficiency matrix improves the result of the mean-variance portfolio selection method. This improvement means that building portfolios with lower risk and higher expected return is possible when alternative optimal solutions are considered. The proposed method in this paper is applied to stock portfolio selection in the Tehran stock market. [ABSTRACT FROM AUTHOR]

In this study, the efficiency of air cleaners in removal of chemical components of PM 2.5 (PAHs, heavy metals, and ions) in the indoor air of dormitories of Tehran University of Medical Sciences, Iran were assessed. 12 rooms were selected and randomly divided into two groups: sham air purifier system deployed room (SR) vs. true air purifier system deployed room (TR). 24-h PM 2.5 samples were simultaneously collected in both TR and SR on PTFE filter papers at a flow rate of 5 L/min. The results showed overall removal efficiency of 76.5 ± 15.5%, 63.1 ± 22.5%, and 66.2 ± 24.8% for PAHs, heavy metals and ions, respectively. Moreover, the fraction of positive ions decreased when air purifiers were used in the rooms. The results showed that the smoking is an important influencing factor on the indoor air quality; smoking can leads to reduction in removal efficiency of PAHs, heavy metals and ions by 26%, 40%, and 51%, respectively. An air purifier could decreased the PM 2.5 even lower than the WHO annual guideline level in non-smoker rooms. The present study revealed that use of indoor air purifiers can significantly reduce the risk of carcinogenicity and non-carcinogenicity attributed to heavy metals and PAHs, especially in places without a smoker. [Display omitted] • Efficiency of air purifiers (AP) in removal of components of PM 2.5 was investigated. • The results showed removal of 76.5%, 63.1%, and 66.2% for PAHs, metals and ions, respectively. • Smoking leads to efficiency reduction of PAHs, metals and ions by 26%, 40%, and 51%, respectively. • AP could decline the PM 2.5 even lower than the WHO guideline in non-smoker rooms. • AP can significantly reduce the health risks attributed to metals and PAHs. [ABSTRACT FROM AUTHOR]

To reduce the negative impact of the conventional vehicles, governments and authorities try to provide facilities in order to encourage people to use electric vehicles. For this purpose, determining the location and the number of charging stations is of paramount importance. It becomes more challenging when some charging stations cannot provide service due to the disruption or breakdown. In this paper, a bi-objective mixed-integer linear mathematical model for a charging station location problem is developed and solved by Lagrangian relaxation method. Two different chargers that could be installed in the charging stations and budget constraint is considered in the model. To evaluate the applicability of the proposed model on real-world problems, a case study on Tehran is conducted. Based on computational experiments and numerical results, sensitivity analysis on key parameters of the problem is carried out and some helpful suggestions are presented for decision-makers. • A bi-objective region-based model for optimizing CSLP is presented. • Disruption in charging stations is taken into account. • Two different types of chargers and tolerable distance for the users are considered. • The proposed model is implemented in a real-world case study to evaluate the applicability of the model. • Lagrangian relaxation algorithm is used to solve the model and some useful managerial insights are also presented. [ABSTRACT FROM AUTHOR]

Abstract: The essential requirements of a successful TBM tunneling operation are the complete characterization of the ground and the thorough identification of geological and geotechnical risks. These besides other information are needed for selecting the right TBM and determining its technical specifications for proper soil conditioning and for achieving the optimum TBM performance. This paper concentrates on a methodology for engineering geological investigations and geotechnical ground characterization, which is important for successful application of mechanized tunneling methods in soft alluvial sediments along the East–West section of line 7 of the Tehran Metro. Geotechnical considerations related to tunneling with a soft ground TBM are described in detail, including the site investigation program, project-specific soil grouping system, distribution of soil types, geological–geotechnical risks (oversize grains, clogging, soil abrasiveness, fine grain content, permeability and groundwater fluctuation) and the engineering geological subsurface model. The encountered soil materials have been divided into four categories according to physical characteristics and engineering properties. In this study, the characteristics of the ground and the hydrogeological regime indicate that an EPB-TBM is rather a slurry-TBM. Although the engineering geological conditions of the ground along the tunnel are favorable for EPB-TBM, stickiness of fine-grained soils, abrasiveness of soils, existence of coarse-grained soils with low fine content and groundwater fluctuations are the most important risks for applying mechanized tunneling method in this specific project. [Copyright &y& Elsevier]

• Presenting an optimization model to design and operate based on maximum profit NPV. • Planning the development of integrated waste management system for long-time horizon. • Evaluating the possibility of energy supply by WtE processes using superstructure. In this paper, a model of integrated waste management system was presented that evaluates the possibility of energy supply by the system and offers sustainable plans for expansion and development of the system in the long-time horizon. Initially, the system superstructure was represented, which includes waste-to-energy (WtE) processes with electricity product and waste-to-material (WtM) processes with products of recycled material and compost, and does not include the transportation sector. The mixed and source-segregated municipal solid waste, which is collected from city area, can be considered as feedstock in superstructure. Then, an optimization model of mixed integer nonlinear programming was formulated based on the superstructure. In addition to optimally determining the strategic process and feedstock allocation, this model plans product production and capacity expansion. The ability of model was tested through a case study of future Tehran metropolis. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: This paper treats with K-shortest viable path problem in a transportation network including multiple modes. The considered modes are metro, rapid-bus, private and walking. In this network, a viable path is one that the number of mode changes is limited and the traverse time and also the walking, metro and private usage are restricted subjected to some constraints. The traverse time is defined dependent on congestion level. Because constrained shortest path is NP-hard, we extend two metaheuristic algorithms namely GASA and BACS for the given problem. GASA is a Greedy Algorithm Simulated Annealing and BACS is a bi-direction searching Ant Colony System made by two colonies of ants. We evaluate the validation of these algorithms applying several multimodal random networks. In addition, their results are compared with CPLEX 12.1. We find that GASA is appropriate for small networks and BACS has better performance in median and large-scale networks. Our results on Tehran network also demonstrate that BACS provides better objective values than BACS ones because Tehran public transportation is sparse. [Copyright &y& Elsevier]

Abstract: This paper presents the seismic vulnerability and rehabilitation of a steel building with semi-rigid connections in Tehran. This 19-storey building with an asymmetric plan was constructed 30 years ago in three blocks. The qualitative vulnerability of the building was evaluated in the first step of the study, indicating its high seismic vulnerability. In the next step of the study, the quantitative vulnerability of the structure was investigated. The results show that the building was strong enough to resist gravity loads but the strength was not adequate for seismic loads. Finally, three seismic retrofitting methods consisting of concrete shear wall, steel shear wall, and steel bracing were proposed. The comparison of the three retrofitting alternatives in terms of architecture, implementation, and seismic performance showed the superiority of using the concrete shear walls over the two other alternatives. [Copyright &y& Elsevier]

Abstract: In this paper, a hybrid model which combines Extended Kalman Filter (EKF) and Genetic Programming (GP) for forecasting of water demand in Tehran is developed. The initial goal of the current work is forecasting monthly water demand using GP for achieving an explicit optimum formula. In the proposed model, the EKF is applied to infer latent variables in order to make a forecasting based on GP results of water demand. The available dataset includes monthly water consumption of Tehran, the capital of Iran, from 1992 to 2002. Five best formulas based on GP results on this dataset are presented. In these models, the first five to three lags of observed water demand are used as probable and independent inputs. For each model, sensitivity of the results for each input is measured mathematically. A model with the most compatibility of the computed versus the observed water demand is used for filtering based on EKF method. Results of GP and hybrid models of EKFGP demonstrate the visible effect of observation precision on water demand prediction. These results can help decision makers of water resources to reduce their risks of online water demand forecasting and optimal operation of urban water systems. [Copyright &y& Elsevier]

Abstract: In this paper, the results of an investigation on a two-stage cooling system have been studied. This system consists of a nocturnal radiative unit, a cooling coil, and an indirect evaporative cooler. During the night in summer, requisite chilled water for a cooling coil unit is provided by nocturnal radiative cooling and is stored in a storage tank. During the next day, the water in the tank provides chilled water for the cooling coil unit and hot outdoor air passes through two-stages: the cooling coil unit and an indirect evaporative cooler. Three sources provide secondary air for the indirect evaporative cooler. The sources are outdoor air, the air leaving from the cooling coil, and the air leaving from the indirect stage (regenerative). The investigation has been conducted in weather conditions in the city Tehran. The results obtained demonstrate that the first stage of the system increases the effectiveness of the indirect evaporative cooler. Also, the regenerative model provides the best comfort conditions. Therefore, this environmentally friendly and energy-efficient system can be considered as an alternative to the mechanical vapor compression systems. [ABSTRACT FROM AUTHOR]

Abstract: Energy consumption in buildings is heavily affected by climate change. It causes significant variations of the outdoor design conditions, cooling and heating loads. In this paper, a total of 40 years (1967–2006) of hourly temperature data were considered in four decades and outdoor design conditions for each decade were calculated. It was found that wet-bulb temperature (WBT) has increased by 3.28°C during the mentioned period, which impacts on design and selection of the cooling equipment. The results show that cooling hours is projected to increase around 15% over the whole 1967–2006 period. The most important result found in this study is the inability of direct evaporative cooling (DEC) systems in preparing comfort condition after 1997, whereas these systems provided thermal comfort in Tehran''s buildings from 1967 to 1996. The prediction of climate change impacts on the outdoor design conditions and cooling systems performance until 2020 demonstrates dry bulb temperature (DBT) and WBT increase 1.05°C and 2.42°C respectively. Hence, indirect–direct evaporative cooling systems (IDEC) may not be responsible for the years after 2016. Besides, the additional energy for absorption and vapor compression (VC) cooling systems will grow quickly in the future. [Copyright &y& Elsevier]

Abstract: The key issue for decision making in stock trading is selection of the right stock at the right time. In order to select the superior stocks (alternatives) for investment, a finite number of alternatives have to be ranked considering several and sometimes conflicting criteria that often are vague and have uncertainty conditions. Therefore, we are faced with a special Multiple Criteria Decision Making (MCDM) problem. The purpose of this paper is to develop a fuzzy expert system for selecting superior stocks in order to encounter the uncertainty of stock portfolio recommendation and model the recommendation rules which experts at Tehran Stock Exchange (TSE) use for portfolio recommendation. The results of implementing the designed fuzzy expert system at TSE were affirmative. [Copyright &y& Elsevier]

Abstract: This paper studies the energy balance between the input and the output per unit area for greenhouse cucumber production. For this purpose, the data on 43 cucumber production greenhouses in the Tehran province, Iran, were collected and analyzed. The results indicated that a total energy input of 148836.76MJha−1 was consumed for cucumber production. Diesel fuel (with 41.94%) and chemical fertilizers (with 19.69%) were amongst the highest energy inputs for cucumber production. The energy productivity was estimated as 0.80kgMJ−1. The ratio of energy output to energy input was approximately 0.64. Results indicate 10.93% and 89.07% of total energy input was in renewable and non-renewable forms, respectively. The regression results revealed that the contribution of energy inputs on crop yield (except for fertilizers and seeds energies) was significant. The human labour energy had the highest impact (0.35) among the other inputs in greenhouse cucumber production. Econometric analysis indicated that the total cost of production for one hectare of cucumber production was around 33425.70$. Accordingly, the benefit–cost ratio was estimated as 2.58. [Copyright &y& Elsevier]

Abstract: The well-known fuzzy rule-based Takagi–Sugeno–Kang (TSK) model is combined with a set of fuzzy regressions (FR) to investigate the impact of the climate change on the electricity consumption duration. The electricity demand forecasts in the short-terms have a vital application in electricity markets. Knowing that the energy is a product of the relation between the climate change and the average consumption duration of the peak load. The paper introduces a type III TSK fuzzy inference machine combined with a set of linear and nonlinear fuzzy regressors in the consequent part to model effects of the climate change on the electricity demand. However, a simplified version of the model is applied to daily data of the average temperature in Tehran, 2004. First, based on an initially fitted nonlinear curve, an optimization model is employed to cluster data into three groups of cold, temperate and hot. The fuzzy data have been expanded to reduce the temperature volatile property. Then the relation is estimated by the fuzzy regressions in company with the TSK model. Numerical results show high efficiency of the proposed combined fuzzy model, as well as a minor decrease in the average absolute error. [Copyright &y& Elsevier]

Industry 4.0 Predictive Maintenance (PdM 4.0) architecture in the broadcasting chain is one of the taxonomy challenges for deploying Industry 4.0 frameworks. This paper proposes a novel PdM framework based on advanced Reference Architecture Model Industry 4.0 (RAMI 4.0) to reduce operation and maintenance costs. This framework includes real-time production monitoring, business processes, and integration based on Design Science Research (DSR) to generate an innovative Business Process Model and Notation (BPMN) meta -model. The addressed model visualizes sub-processes based on experts' and stakeholders' knowledge to reduce the cost of maintenance of audiovisual services including satellite TV, cable TV, and live audio and video broadcast services. Based on the recommendation and the concept of Industry 4.0, the proposed framework tolerates the predictable failures and further concerns in similar related industries. Some empirical experiments have been conducted by using the Islamic Republic of Iran Broadcasting's (IRIB) high-power station (located near the capital city of Iran, Tehran) to evaluate the functionality and efficiency of the proposed predictive maintenance framework. Practical outcomes demonstrate that interval times between data collection should be increased in audio and video broadcasting predictive maintenance because of the limitation of the internal processing performance of equipment. The framework also indicates the role of the Frequency Modulation (FM) transmitters' data clearance to reduce the instability and untrustworthy data during data mining. The proposed DSR method endorses using a customized RAMI 4.0 meta -model framework to adapt distributed broadcasting and communication with PdM 4.0, which increases the stability as well as decreasing maintenance costs of the broadcasting chain in comparison to state-of-the-art methodologies. Furthermore, it is shown that the proposed framework outperforms the best-evaluated methods in terms of acceptance. [ABSTRACT FROM AUTHOR]

This paper couples a Forward Feature Selection algorithm with Random Forest (FFS-RF) to create a transition index map, which then guides the spatial allocation for the extrapolation of urban growth using a Cellular Automata model. We used Landsat imagery to generate land cover maps at the years 1998, 2008, and 2018 for the Tehran-Karaj Region (TKR) in Iran. The FFS-RF considered the independent variables of slope, altitude, and distances from urban, crop, greenery, barren, and roads. The FFS-RF revealed temporal non-stationary of drivers from 1998–2008 to 2008–2018. The FFS-RF detected that altitude and distance from greenery were the most important drivers of urban growth during 1998–2008, then distances from crop and barren were the most important drivers during 2008–2018. We used the Total Operating Characteristic to evaluate the transition index maps. Validation during 2008–2018 showed that FFS-RF produced a transition index map that had predictive power no better than an allocation of urban growth near existing urban. Simulation to 2060 extrapolated that Tehran, Karaj, and their adjacent cities will interconnect spatially to form a gigantic city-region. [Display omitted] • A Forward Feature Selection - Random Forest (FFS-RF) model describes urban growth. • FFS-RF found temporal non-stationarity of drivers in Iran's Tehran-Karaj region. • The Total Operating Characteristic evaluated the transition index map (TIM). • FFS-RF produced a TIM that has predictive power no better than a baseline TIM. • FFS-RF and Cellular Automata extrapolated urban growth to the year 2060. [ABSTRACT FROM AUTHOR]

Despite the fundamental role of the social aspect in the implementation of sustainability in the bio-based industries, most of the sustainability assessments research have addressed the environmental and economic dimensions. However, the social dimension has been neglected and it can cause an irreparable outcome in the biotechnology industries. Following this issue, this study propounds a modified systemic approach for a social sustainability impact assessment of the treatment technologies for converting waste into bioenergy, based on a review on the common social assessment methods. As it is known, the guideline presented by the United Nations Environment Program (UNEP) and the Society of Environmental Toxicology and Chemistry (2009) due to considering social life cycle assessment has a comprehensive look at the stakeholders. Therefore, in this paper, UNEP method was selected. However, it needs to be modified based on the bio-energy supply chain derived from municipal solid waste. For this purpose, the bioenergy value chain derived from municipal solid waste was designed and combined with UNEP guideline, to complete the level of stakeholder subgroups and the levels of the indicators. The final method of the social assessment system was presented to the board of experts and finalized. In order to design the measurement part of the social assessment system, because of a multi criteria decision making nature of the social sustainability evaluation of the conversion technologies of municipal solid waste to bio-energies, a recent developed multi-criteria decision making method so-called Best Worst Method (BWM) was used in two stages. The criteria are ranked according to their average weight obtained through Best Worst method. One of the major novelties in this research is the way of application of the best worst technique in the second stage. The model was implemented in the case of Tehran as one of the pioneering Iranian municipalities with high potential to produce bioenergy. The results of this study help decision makers to decide where to concentrate their attention during the implementation stage, and to increase social sustainability in their bioenergy supply chains derived waste. [ABSTRACT FROM AUTHOR]

In this paper, the energy, exergy, and economic analysis of a novel integrated power plant is investigated. The novel power plant is integrated by using the heliostat solar receiver, the heliostat solr reciever is integrated with many types of traditional power plants such as the gas turbine cycle, air-bottoming cycle, and absorption refrigeration system. Also, the integration of the heliostat solar receiver to heat the exhaust air from the compressor to reduce the natural gas consumption within the gas cycle has been investigated. For the proposed configurations, energy, exergy, and economic analysis for Tehran, Iran (35.689°N, 51.5°E) has been conducted. The model has been validated using previously published results of other authors. Since the investigated configurations are innovative and to the best of our knowledge a similar whole system does not exist in the literature, each cycle has been validated separately. Results and comparisons are given for six different combinations: gas cycle, gas cycle with air bottoming cycle, and gas cycle with air bottoming cycle and absorption refrigeration system. The previously mentioned cycles are analyzed again but this time with integrating them with heliostat solr reciever. The comparisons study is conducted in terms of monthly average energy efficiency, monthly average exergy efficiency, annual average energy efficiency, annual average exergy efficiency, net present value, simple payback period, payback period, and internal rate of return. Results show that adding the heliostat solr reciever to the different cycles minimizes the fossil fuel consumption and enhance energy performance very significantly, for example the energy and exergy efficiencies are increased from 44% up to 69%. Regarding some economic indicators such as the internal rate of return parameter, the results show that the highest internal rate of return belongs to the combination of the gas cycle with air bottoming cycle and absorption refrigeration system with the value of 0.48 and the combination of the gas cycle combined with heliostat solar receiver has the lowest value of internal rate of return of 0.16. As a result of the reduction in fuel consumption savings and other economic indicators are achieved in addition to better environment impact. Finally, the integration of heliostat solar receiver in power cycles shows many advantages mainly in hot areas where solar radiation is high. [ABSTRACT FROM AUTHOR]

Air pollution in metropolises is one of the serious problems of human life. Tehran is one of the cities facing air pollution problem. Urban managers concern about choosing different management methods to control air pollution. In this study, a combination of fuzzy systems and neural networks has been used to select the most suitable scenario for controlling SO 2 pollution. According to the method presented in this paper, 8 input data categories such as wind speed, precipitation, temperature, pressure, humidity, gas oil consumption, gasoline consumption and urban green space levels have been used as independent parameters and SO 2 pollutant concentration has been considered as the dependent parameter. The contribution of each meteorological station to the meteorological data was determined by Thiessen Polygon Method. Then, using adaptive neural fuzzy inference systems, modeling was done in Sugeno Method and the least root mean square error (3.19) was determined for the model. Then, by changing each of the independent parameters, the effect of each of these independent parameters on SO 2 pollutant was measured. The results showed that the parameters of pressure, urban green space, gasoline consumption, gas oil consumption, temperature, wind speed and humidity, respectively, had the greatest effect on reducing the SO 2 concentration. Since the parameters of gasoline and gas oil consumption as well as the area of green space are changeable by different policies and by human decisions, the concentration of SO 2 pollutant can be controlled by reducing the consumption of gasoline and gas oil and increasing the green space in Tehran. • Finding the lowest error rate in any of the models predicting sulfur dioxide concentration. • Determine the effect of each of the independent parameters on the concentration of SO 2. • Determination of the best predictive model for sulfur dioxide emissions based on ANFIS model. • Providing solutions to improve air pollution. [ABSTRACT FROM AUTHOR]

In recent years, the vulnerability and protection of subsurface structures under blast loads became a fundamental issue in terms of security (loss of lives and structural damage). A tunnel can be considered as an underground shelter and is a crucial structure owing to its conservative nature against explosions. This study is performed to obtain a further understanding of surface explosion influence on segmental tunnels. In this paper, a tunnel lining and its segmentation with planar and curved joints under dynamic loads were investigated. In this regard, a 2D finite-deference simulation of the Tehran metro segmental lining was conducted. Subsequently, an explosion wave stress of 500 kg of TNT explosive was considered as the reference loading case. The results indicated that the segmental lining with curved joints is efficient and succeeds in neutralizing the surface explosion. The maximum bending moments and axial forces in the curved segmental lining are lower than in the planar segmental and continuous lining. In terms of vertical and horizontal displacements of the tunnel lining, the segmental structure with curved joints induces the minimum deformation amount. The continuous lining and planar segmental lining show instability under the reference blast load. Finally, it can be concluded that the segmental lining with curved joints is highly efficient and stable in case of a surface explosion. [ABSTRACT FROM AUTHOR]

In spite of numerous valuable researches for evaluating the effect of different parameters for analyzing exergy/environmental/economic/energy-matrices/heat transfer of solar stills; the effect of high altitude (highlands) on these parameters and comparing two active/passive systems was not performed. This paper conducted a meticulous analysis of two active and passive solar stills at different altitudes (Tochal: 3964 m and Tehran: 1171 m) during seven consecutive days between 24.07.2018 and 30.07.2018. The geometry of solar stills in both experiments is similar and for active type, the system utilized with thermoelectric (Peltier) modules and powered by a photovoltaic panel. Results revealed that altitude has a direct effect on the exergy of solar stills where the summit-located solar stills (passive and active) have higher exergy efficiency. Furthermore, higher evaporative exergy is obtained by both active solar stills at the Peak of Tochal Mountain and the center of Tehran. Likewise, heat transfer analysis showed that the highest and lowest heat transfer coefficients are obtained by active solar still at the Peak of Tochal Mountain and passive solar still in Tehran respectively. However, due to the higher glass temperature, the highest radiative heat transfer coefficients are obtained by Tehran-located systems. Economic results showed that the highest and lowest cost of water with 0.0079 and 0.0372 $/L are assessed by passive solar still in Tehran and active solar still at the Peak of Tochal Mountain respectively. Energy-matrices indicated that the lowest and highest energy payback time based on energy and exergy with 1.57 and 52.75 years attained by passive solar still in Tehran. Also, Environmental analysis showed that higher CO 2 mitigation obtained by active solar stills rather than passive types in both locations. Also, enviroeconomic as well as exergoeconomic (based on energy) parameters showed that both passive and active SSs at the city of Tehran have higher values rather than that of solar stills at the summit because of higher days of operation during the year. • Exergy efficiency at high-altitude for active/passive solar stills (SSs) is greater than Tehran-located systems. • Higher daily energy/exergy output and evaporation exergy obtained by active SSs. • Highest and lowest EPBT based on energy and exergy with 1.57 and 52.75 years obtained by passive SS in Tehran respectively. • Maximum overall and evaporative heat transfer coefficients (HTCs) are obtained by active SS at the summit of Tochal. • Operation days of the systems has huge impact on Environmental, economic, environeconomic, and exergoeconomic parameters. [ABSTRACT FROM AUTHOR]

• Evaluating the polarimetric capabilities of dual polarized S1A and TSX data. • Improving the PS-InSAR technique using the polarimetric optimization of ADI. • PolInSAR technique for estimation of ground deformation in Tehran, Iran. • Investigating the physical interpretation of optimum scattering mechanisms. • Investigating the PSC and PS pixels density of optimum and conventional channels. Polarimetric data is an additional source of information in PSI technique to improve its performance in land subsidence estimation. The combination of polarimetric data and radar interferometry can lead to an increase in coherence and the number of PS pixels. In this paper, we evaluated and compared the dual polarized Sentinel-1A (S1A) and TerraSAR-X (TSX) data to improve the PSInSAR algorithm. The improvement of this research is based on minimizing Amplitude Dispersion Index (ADI) by finding the optimum scattering mechanism to increase the number of PSC and PS pixels. The proposed method was tested using a dataset of 40 dual-pol SAR data (VV/VH) acquired by S1A and 20 dual-pol SAR data (HH/VV) acquired by TSX. The results revealed that using the TSX data, the number of PS pixels increased about 3 times in ESPO method than using the conventional channels, e.g., HH, and VV. This increase in S1A data was about 1.7 times in ESPO method. In addition, we investigated the efficiency of the three polarimetric optimization methods i.e. ESPO, BGSM, and Best for the dual polarized S1A and TSX data. Results showed that the PS density increased about 1.9 times in BGSM and about 1.5 times in Best method in TSX data. However, in S1A data, PS density increased about 1.1 times in BGSM. The Best method was not successful in increasing the PS density using the S1A data. Also, the effectiveness of the method was evaluated in urban and non-urban regions. The experimental results showed that the method was successful in significantly increasing the number of final PS pixels in both regions. [ABSTRACT FROM AUTHOR]

The idea of Adaptive Solar Façade (ASF), as a modular, dynamic, and flexible types of smart façades could be a promising approach in a comfort-centric design through the proper integration with the parametric design. Therefore, this paper is to investigate the development process of ASF grounded on parametric design tools with a focus towards its visual comfort indices through a controllable shading system. To that end, first, a comprehensive literature review was carried out to develop an origami-based dynamic system, and three numerical timing patterns were then applied using Grasshopper plug-in for Rhino. In addition, the environmental plug-ins of Honeybee and Ladybug were employed to determine indoor daylight quality via different geometrical and physical properties. Thus, 1800 design models were prepared, based on several variables including rotation motions, indoor view angles, time hours and transmittance properties in order to investigate the daylighting performance and glare probability in a single office space located in the hot-arid climate representative; Tehran, Iran. Furthermore, interactive correlations between the geometrical pattern and visual performance were investigated, leading to this fact that the proposed prototype can significantly improve the flexibility of the shading system to control visual comfort. As the conclusion, all datasets were integrated into an algorithmic workflow while converting its advantages and limitations into an optimization process. Finally, a full potential hexagonal adaptive system was presented to achieve the maximum visual comfort level based on the users' preferences that can be the basis for future investment on smart building envelopes. • Investigating a pioneer parametric approach towards daylight performance and glare discomfort • A new kinetic hexagonal shading system was developed. • Three timing patterns were successfully implemented in full-scale facade and compared. • 1800 point-in-time simulations were used for overall evaluation of the pattern. • The system provided the possibility to control indoor visual performance based on the user demand in an office unit. [ABSTRACT FROM AUTHOR]