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Due to the increase in energy demand and the effects of global warming, energy-efficient buildings have gained significant importance in the modern construction industry. To create a suitable framework with the aim of reducing energy consumption in the building sector, the external walls of a residential building were considered with two criteria of global warming potential and energy consumption.

In the first stage, to achieve a nearly zero-energy building, energy analysis was performed for 37 different states of thermal insulation. Then, the insulation materials’ life cycle assessment was performed. These results were used to find a set of optimal modes in the Pareto front by using non-dominated sorting genetic algorithm II multi-objective genetic algorithm. Thus, based on the data obtained from this method, it was possible to compare and choose different thermal insulation materials based on the distance from the Pareto front, reducing the environmental effects.

The results showed that replacing the windows was possible to save 3.24% in energy consumption. Also, selecting the proper insulation reduced energy consumption value by 63.13%. Finally, this building can save 69.31% of energy consumption compared to the base building by following the zero-energy building standard. As a result, the Pareto curve was introduced as a guide for the optimal design of the building’s wall insulation.

The proposed method provides designers with a framework for latent carbon analysis to access quickly and select optimal scenarios. It can also be used without restrictions for other decisions with different goals and criteria.

This paper aims to outlines a model for water main rehabilitation in Kitchener, Ontario, using a machine-learning approach. Water main networks are vital infrastructure, requiring regular condition assessments to ensure consistent service. Budgets are often allocated for nondestructive testing methods, but using machine learning to predict network conditions offers cost benefits.

The study focuses on a prediction approach that includes the rehabilitation requirement model. The Decision Tree machine learning method was applied to predict water main pipe breaks in 2024. Based on the predictions, 24 pipes were identified for rehabilitation, and the appropriate Trenchless Rehabilitation Method was selected accordingly.

The model, applied to data from Kitchener, successfully predicted 24 water main pipe breaks for 2024. The largest pipe diameter was 1200 mm, and the longest length was 6977 m. A cost comparison, factoring in Environmental and Social (E&S) costs, showed that open-cut methods were 25% more expensive than Cured-in-Place Pipe (CIPP). When E&S costs were included, the total cost of the open-cut method increased by approximately 300% compared to sliplining.

Based on the pipe characteristics, CIPP lining and sliplining are recommended for rehabilitation by the City of Kitchener. This study presents a novel approach using Decision Tree machine learning techniques to predict pipe breaks, with a 97% prediction accuracy, making it a promising alternative to traditional models.

This study aims to optimize the energy consumption of residential buildings in mild and humid climates. It investigates the use of thermal insulation to reduce thermal load through energy simulation analysis.

A residential building located in Rasht city, Iran (a mild and humid climate zone), is simulated using DesignBuilder software. Subsequently, the minimum thermal resistance for external walls and roof is analyzed along with its impact on building energy consumption and carbon emissions.

The simulation results indicated a 26.5% reduction in heat loss through the walls and a 14.2% reduction through the roof due to optimal thermal insulation. Furthermore, optimal insulation led to a 19.2% reduction in cooling system energy use, a 12% reduction in heating system energy use and a combined 15.3% reduction in total energy consumption for cooling and heating.

This optimization process leads to several benefits: reduced costs associated with thermal and cooling energy losses in buildings, improved building performance against atmospheric factors and, ultimately, a reduction in energy consumption across the building industry. This research can be valuable to various stakeholders, including the construction industry and building sector, municipalities and engineering systems, building owners and contractors and environmental organizations. By implementing these findings, they can improve the state of modern building insulation and achieve greater energy efficiency.

The purpose of this research is to design a residential green building using a sustainable approach from an ecosystem-technology perspective in the Darakeh area in the north of Tehran.

First step: based on climatic and geographical data, the study area is defined and a preliminary building design is developed. Second step: sustainable architecture principles and comfort zone requirements are analyzed to inform the design process. Third step: Building modeling and energy simulation are conducted using DesignBuilder software, incorporating green technologies. Final step: the building’s energy performance and environmental impact are assessed.

The results show that the amount of annual production of electricity due to the installation of solar collectors on the roof of the building is 12,236 kWh. Considering the building’s total area of 463 m² and its annual energy consumption of 17,676 kWh, the energy consumption per square meter of building surface per year is 38 kWh.

The obtained findings showed that the designed building complies with the criteria of sustainable development and green building. A Giovanni-based EchoTech (ecosystem-technology) approach was used in this research, which greatly increases the reliability of the results.

This paper aims to investigate the optimum energy consumption of building atriums in hot, cold and dry climate zones in Iran.

This paper uses simulation software to analyze atrium design for energy saving in buildings and the effects of the energy saving process on the use of atrium in hot summer and cold winter zones in Iran. The buildings exhibit brick cavity concrete block plaster for wall, double-glazed alum frame for glaze, concrete slab on ground for flour and plaster insulation suspend for ceiling. This process is analyzed by choosing a suitable atrium for building energy efficiency in warmest session for warm weather conditions and the coldest session for cold weather conditions in Iran.

According to the analysis done using simulation software, with respect to the hot need prevention of direct and indirect solar energy and cold need absorption of direct and indirect solar energy, four-side atrium with total radiation incident of 2,506,027 and 69,613 W, radiation absorption of 902,795 and 29,057 W and radiation transmission of 297,118 and 4,201 W in hot summer and in cold winter are the best optimum selections.

The results of this research are useful for both building energy efficiency and producing a comfortable living environment in the future and will support new observations of how residential building developers can accept sustainable strategies to grow their overtaking in the Iranian construction market.

This paper aims to report on the findings from a research project, incorporated by Iran’s Ministry of Petroleum, investigating the integration of inspection management with analysis of document information.

A combination of group and individual interviews were undertaken with qualitative methods of analysis to develop an integrated process model. The model developed uses integrity management factors, which allows flexibility and the early integration of inspection management systems at a strategic level, although detailed planning is still required through the use of integrated management tools. The model combines information on responsibilities, tasks and policies, of personnel in the inspection management of the piping system with the oil and gas industry.

The six inspection activities recognized for the main practical model are, namely, identify pipeline situation; inspect and measure defects; inspection assessment; design inspection; implement inspection activities and measure and report inspection.

This research presented not only a process but also the framework and techniques to manage and improve management effectiveness and inspection efficiency in pipelines of the oil and gas industry. This study will be useful to researchers maintenance professionals and others concerned with inspection and maintenance management of facilities and equipment in the oil and gas industry.

The purpose of this paper is to examine the feasibility and design of zero-energy buildings (ZEBs) in cold and semi-arid climates. In this study, to maximize the use of renewable energy, energy consumption is diminished using passive solar architecture systems and techniques.

The case study is a residential building with a floor area of 100 m² and four inhabitants in the cold and semi-arid climate, northeast of Iran. For thermal simulation, the climate data such as air temperature, sunshine hours, wind, precipitation and hourly sunlight, are provided from the meteorological station and weather databases of the region. DesignBuilder software is applied for simulation and dynamic analysis of the building, as well as PVsyst software to design and evaluate renewable energy performance.

The simulation results show a 30% decrease in annual energy consumption of the building by complying with the principles of passive design (optimal selection of direction, Trombe wall, shade, proper insulation selection) from 25,443 kWh to 17,767 kWh. Then, the solar energy photovoltaic (PV) system is designed using PVsyst software, taking into account the annual energy requirement and the system’s annual energy yield is estimated to be 26,291 kWh.

The adaptive comparison of the values obtained from the energy analysis indicated that constructing a ZEB is feasible in cold and semi-arid conditions and is considered an effective step to achieve sustainable and environmentally friendly construction.

This paper introduces a novel multi-setup merging method and assesses its performance using simulated response data from a Finite Element (FE) model of a five-storey frame and experimental data from a cantilever beam tested in a laboratory setting.

In the research conducted at the Central Building Research Institute (CBRI) in Roorkee, India, a cantilever beam was examined in a laboratory setting. The study successfully extracted the modal properties of the multi-storey building using the merging technique. Identified frequencies and mode shapes provide valuable insights into the building's dynamic behavior, which is essential for structural analysis and assessment. The sensor layout and data merging approach allowed for the capture of relevant vibration modes despite the limited number of sensors, demonstrating the effectiveness of the methodology.

The results show that reducing the number of sensors can impact the accuracy of the mode shapes. It is recommended to use a minimum of 8 sensor locations (every two floors) for the building under study to obtain reliable benchmark results for further evaluation, periodic monitoring, and damage identification.

The results demonstrate that the developed algorithm can improve the system identification process and streamline data handling. Furthermore, the proposed method is successfully applied to analyze the modal properties of a multi-storey building.

Divorce has negative effects on children, although emotions that children experience after parental divorce are open to different interpretations. Accordingly, this study was conducted to explore loneliness in children of divorce.

A constructivist grounded theory study was carried out through the lens of definitive guidelines provided by Charmaz (2006). The participants were 15 female children aged 11–12 years, who were purposively selected. Data were collected using semi-structured interviews and memos. To analyze data, the authors used four coding techniques, including initial, focused, axial, and theoretical coding. Also, to examine the links between the identified themes, the authors focused on three factors: conditions, actions/interactions, and consequences.

The analysis of the obtained data through the above-mentioned stages led to the identification of three main themes, including parental unavailability, rejection, and mistrust, which shaped children's experience of loneliness through lack of physical access, lack of emotional access, low levels of parental expectations, lack of supervision, absence of belongingness, being ignored, pessimistic views, and insecure relationships.

As was suggested by attachment theory, children of divorce lost their attachment bonds with their parents that intensified their perception of loneliness and negatively affected their social and academic performance. It was revealed that, effects of divorce went beyond the loss of the attachment bonds in families because our participants talked about their relationships with peers and their position in a society, where divorce carries the social stigma and children of divorced mother are marginalized.