Flood zoning and developing strategies to increase resilience against floods with a crisis management approach

Assessment and planning of crisis management with the approach to natural flood disasters include many factors. In this regard, one of the basic principles of crisis management is based on the resilience of urban infrastructure against floods. This study developed strategies to increase resilience by flood zoning and crisis management. The investigation of the current situation shows that despite the efforts being made, the climatic and environmental conditions of the rivers, the settlements of the infiltration basin, the constructions, and the location inaccuracy of the following structures indicate many challenges in managing the current situation in various components of crisis management. In this regard, the main direction of this article is to evaluate the urban resilience of the Khuzestan region against floods based on a crisis management approach and technique for order preference by similarity to ideal solution (TOPSIS) and Fuzzy weighting methods using geographic information system (GIS)

Analysis and Evaluation of Thermal-cooling Loads of Office Buildings Using Carrier Software in Iran

The importance and necessity of energy saving in the world have been discussed for many years, but achieving a logical and transparent solution isstill one of the main challenges and problems of the world’s economy. Therapid growth of energy consumption in the last two decades has caused thesecurity of the domestic energy supply of buildings to face serious problems. In this research, first by entering parameters such as the type of materials, doors and windows, and the type of soil on the floor connected to theground, etc. in the heat and cold load calculation software (HAP Carrier) asthe design calculations and then in the second step entering the specifications inferred from the Iran’s national building code as a reference for energy saving calculations, calculations are performed and compared as the firstcriterion, and finally these two outputs are compared. The actual energyconsumption and determination of the building energy consumption indexare determined as another criterion, as well as the degree of deviation fromthe actual consumption. The results showed that the theoretical method andthe thermal and refrigeration load calculations of the Zanjan Gas Companybuilding have 6% difference in cooling load but the heating load is about34% different, which means for cooling loads, the theoretical model can beused with high accuracy but for heating loads, the national building codeneeds fundamental changes

Herbicide Residues in Water Resources: A Scoping Review

Several recent studies have focused on leaching pesticides from agricultural soils into surface and groundwater resources during irrigation. As a result, information about herbicide residues in water was necessary for conserving related resources. This study provided an overview of monitoring herbicides in water resources worldwide. In this scoping review, five databases were searched for publications (1990 to April 2021), including Scopus, PubMed/Medline, Cochrane library, Embase, and Web of Science. Among the 394 identified articles, 17 papers were selected for inclusion. Most of these studies have been conducted in regions with low herbicide concentrations, including Spain, Greece, Canada, Brazil, Hungary, Malawi, Portugal, Lesotho, Germany, Serbia, and the USA. The high-level alachlor, metolachlor, atrazine, metribuzin, and simazine herbicides in groundwater were detected in Portugal (0.4-13μg/L). An overview of studies demonstrated that herbicides are widely used in water resources, and surface waters are more contaminated than groundwaters

Pulmonary metastases: Results of surgical resection in 60 cases: Treatment modalities other than surgery are needed

Pulmonary metastases occur in 30 of all oncology patients. Surgical resection of lung metastases is a widely accepted procedure but long-term results are disappointing with a 5-year survival rate of 20-40 and the results vary with the histologic type of the primary tumor. Due to unavailability of any study regarding pulmonary metastasectomy in Iran and emergence of new treatment modalities, reassessment of our current practices is essential. We performed a retrospective study of 60 cases of pulmonary metastasectomy during a 5-year period in one of the major thoracic surgery centers in Tehran (Imam Khomeini Hospital). Bilateral metastases were present in 23 of cases, number of metastases in each patient ranged from 1-12. Average disease-free interval was 12 months, pneumonectomy rate was 21.7 mostly as a second or third attempt and finally, recurrence or death following initial metastasectomy occurred in 12-18 months in most patients. These results confirm that surgery remains unsuccessful in obtaining long-term survival or cure in most patients with pulmonary metastases and treatment strategies other than surgery, such as radiofrequency ablation are needed to avoid performing multiple operations in these patients and improving their quality of life. © 2007 Tehran University of Medical Sciences. All rights reserved

Artificial intelligence and machine learning in energy systems: A bibliographic perspective

Economic development and the comfort-loving nature of human beings in recent years have resulted in increased energy demand. Since energy resources are scarce and should be preserved for future generations, optimizing energy systems is ideal. Still, due to the complexity of integrated energy systems, such a feat is by no means easy. Here is where computer-aided decision-making can be very game-changing in determining the optimum point for supply and demand. The concept of artificial intelligence (AI) and machine learning (ML) was born in the twentieth century to enable computers to simulate humans' learning and decision-making capabilities. Since then, data mining and artificial intelligence have become increasingly essential areas in many different research fields. Naturally, the energy section is one area where artificial intelligence and machine learning can be very beneficial. This paper uses the VOSviewer software to investigate and review the usage of artificial intelligence and machine learning in the energy field and proposes promising yet neglected or unexplored areas in which these concepts can be used. To achieve this, the 2000 most recent papers in addition to the 2000 most cited ones in different energy-related keywords were studied and their relationship to AI- and ML-related keywords was visualized. The results revealed different research trends in recent years from the basic to more cutting-edge topics and revealed many promising areas that are yet to be explored. Results also showed that from the commercial aspect, patents submitted for artificial intelligence and machine learning in energy-related areas had a sharp increase

Lab-Scale Investigation of the Integrated Backup/Storage System for Wind Turbines Using Alkaline Electrolyzer

The depletion of fossil fuel sources has encouraged the authorities to use renewable resources such as wind energy to generate electricity. A backup/storage system can improve the performance of wind turbines, due to fluctuations in power demand. The novelty of this study is to utilize a hybrid system for a wind farm, using the excess electricity generated by the wind turbines to produce hydrogen in an alkaline electrolyzer (AEL). The hydrogen storage tank stores the produced hydrogen and provides hydrogen to the proton-exchange membrane fuel cell (PEMFC) to generate electricity once the power demand is higher than the electricity generated by the wind turbines. The goal of this study is to use the wind profile of a region in Iran, namely the Cohen region, to analyze the performance of the suggested integrated system on a micro scale. The output results of this study can be used as a case study for construction in the future, based on the exact specification of NTK300 wind turbines. The results indicate that, with the minimum power supply of 30 kW from the wind turbines on a lab scale, the generated power by the PEMFC will be 1008 W, while the maximum generated hydrogen will be 304 mL/h

Machine Learning and Deep Learning in Energy Systems: A Review

With population increases and a vital need for energy, energy systems play an important and decisive role in all of the sectors of society. To accelerate the process and improve the methods of responding to this increase in energy demand, the use of models and algorithms based on artificial intelligence has become common and mandatory. In the present study, a comprehensive and detailed study has been conducted on the methods and applications of Machine Learning (ML) and Deep Learning (DL), which are the newest and most practical models based on Artificial Intelligence (AI) for use in energy systems. It should be noted that due to the development of DL algorithms, which are usually more accurate and less error, the use of these algorithms increases the ability of the model to solve complex problems in this field. In this article, we have tried to examine DL algorithms that are very powerful in problem solving but have received less attention in other studies, such as RNN, ANFIS, RBN, DBN, WNN, and so on. This research uses knowledge discovery in research databases to understand ML and DL applications in energy systems’ current status and future. Subsequently, the critical areas and research gaps are identified. In addition, this study covers the most common and efficient applications used in this field; optimization, forecasting, fault detection, and other applications of energy systems are investigated. Attempts have also been made to cover most of the algorithms and their evaluation metrics, including not only algorithms that are more important, but also newer ones that have received less attention

Thermal analysis model of a building equipped with green roof and its energy optimization

In this research, the simulation and modeling of the energy use for a two-story theoretical building which is equipped with the green roof in three various climates of Iran (Tabriz: cold and dry; Tehran: mild and dry; and Bandar Abbas: tropical and dry) has been done. The purpose of this simulation is to show the impacts of the green roof on reducing thermal loads of a building and also its role in reducing the heat flux passing through the roof of the building. The procedure is that first this building takes its model in one software and then this 3D model is delivered to the Energy Plus simulation engine, then simulation is done in different period of times. For each city, a normal building with an asphalt roof was simulated along with a completely similar building which has the vegetation cover rather than asphalt in the last layer of its roof and the output results are compared with each other. The simulation results show that by applying the green roof, the basic state of annual electricity consumption in the cities of Tehran, Tabriz and Bandar Abbas decrease 16.3%, 12.5% and 23%, respectively. According to the values obtained, using the green roof is more efficient in tropical areas (Bandar Abbas) than cold areas (Tabriz). Bandar Abbas with tropical and dry climate needs much energy to cool the environment in the summer, but due to the balanced temperature in the cold months and no need of energy for heating, the amount of energy consumption in Bandar Abbas is much lower than other cities during the year. Also, the sensitization analysis tests have shown that the energy consumption of building is strongly dependent on the thickness of the soil parameters changes and plant density of the green roof structure, therefore more thickness of the applied soil has better thermal insulation. The economic savings per year based on the use of a green roof for the building, located in Tehran, Tabriz and Bandar Abbas are 562, 660 and 381 $ respectively

Exergy-economic assessment of a hybrid power, cooling and heating generation system based on SOFC

In this research, a combined cycle using a solid oxide fuel cell system, a single-stage H2O–NH3 absorption chiller and a residential hot water HX, is developed for the electricity production, hot water and cooling all at the same time, and it is studied from an exergy, energy, and exergoeconomic standpoint. Performance of system under the design condition is analyzed and the mathematical model is simulated. After analyzing the results in the initial input mode, changing the fuel cell current density effect and fuel utilization factor on the system efficiency is evaluated. The result indicates that total energy is 4.418 kW, the total exergy efficiency is 37.8%. And the overall irreversibility is 1.650 kW. On the other hand, the air HX, fuel cell and water HX are designed as elements that must be given more attention than others from the exergoeconomic perspective, because they have nearly the most amount of price compared to other parts

Simulating the performance of HOV lanes for optimal urban traffic management

Traffic congestion is a significant problem in crowded cities, resulting in increased travel times, air pollution, and reduced productivity. High-occupancy vehicle (HOV) lanes have emerged as a promising solution to tackle these issues. HOV lanes are reserved for vehicles carrying multiple passengers, incentivizing shared travel and reducing the number of low-occupancy vehicles on the road like school buses. By reducing the overall number of cars on the road, HOV lanes can significantly alleviate traffic congestion, improve travel times, and reduce air pollution. The effectiveness of HOV lanes depends on the degree of demand for shared travel and the availability of incentives, such as employer-provided benefits or toll exemptions. Additionally, the design and implementation of HOV lanes must be carefully planned to ensure that they do not negatively impact other road users. Tehran, as one of the largest and most populous cities in Asia, is a major destination for daily travel by workers. The Tehran-Karaj freeway serves as the primary and busiest entrance to Tehran city, experiencing heavy traffic every day in the morning towards Tehran and in the evening towards Karaj. In this study, the traffic conditions of this freeway were simulated in the existing state and with the presence of HOV lanes, and the resulting traffic parameters were compared and analyzed under different traffic scenarios. The findings of this research can offer valuable insights for decision-makers and traffic policy makers