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Residential buildings in Greece constitute an important portion of the existing building stock. Furthermore, most of these buildings were built prior to the first Thermal Insulation Code of 1981. The article focuses on existing, typical residences built after 1920, which are found mostly in suburban areas and settlements all around Greece. The purpose of the research is to evaluate the effect of simple bioclimatic interventions focused on the improvement of their diurnal, inter-seasonal and annual thermal performance.

The applied strategies include application of thermal insulation in the building shell and openings, passive solar systems for the heating period and shading and natural ventilation for the summer period. The effect of the strategies is analysed with the use of building energy analysis. The simulation method was selected because it provides the possibility of parametric analysis and comparisons for different proposals in different orientations.

The results show that the increased thermal mass of the construction is the most decisive parameter of the thermal behaviour throughout the year.

The typical residences under investigation are often found in urban and/or suburban surroundings. These mostly refer to free-standing buildings situated, which, in many cases, do not have the disadvantages and limitations that the geometrical characteristics of densely built urban locations impose on incident solar radiation (e.g. overshadowing during the winter) and air circulation (e.g. reduce natural ventilation during the summer). Nevertheless, even in these cases, the surrounding built environment may also have relevant negative effects, which were not taken under consideration and could be included in further, future research that will include the effect of various orientations, as well as of neighbouring buildings.

Existing residences built prior to the first Thermal Insulation Code (1981) form an important part of the building stock. Consequently their energy upgrade could contribute to significant conventional energy savings for heating and cooling, along with the inter-seasonal improvement of interior thermal comfort conditions.

The proposed interventions can improve thermal comfort conditions and lead to a reduction of energy consumption for heating and cooling, which is an important step against energy poverty and the on-going energy crisis.

The proposed interventions only involve the building envelope and are simple with relatively low cost.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

Climate change reports from New Zealand claim that climate change will impact some cities such as Auckland from a heating-dominated to a cooling-dominated climate. The benefits and risks of climate change on buildings' thermal performance are still unknown. This paper examines the impacts of climate change on the energy performance of residential buildings in New Zealand and provides insight into changes in trends in energy consumption by quantifying the impacts of climate change.

The present paper used a downscaling method to generate weather data for three locations in New Zealand: Auckland, Wellington and Christchurch. The weather data sets were applied to the energy simulation of a residential case study as a reference building using a validated building energy analysis tool (EnergyPlus).

The result indicated that in Wellington and Christchurch, heating would be the major thermal load of residential buildings, while in Auckland, the main thermal load will change from heating to cooling in future years. The revised R-values for the building code will affect the pattern of dominant heating and cooling demands in buildings in Auckland in the future, while in Wellington and Christchurch, the heating load will be higher than the cooling load.

The findings of this study gave a broader insight into the risks and opportunities of climate change for the thermal performance of buildings. The results established the significance of considering climate change in energy performance analysis to inform the appropriate building codes for the design of residential buildings to avoid future costly changes to buildings.

This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings.

This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics.

Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting.

While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK.

This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system.

This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

Effective safety supervision plays a crucial role in ensuring safe production within coal mines. Conventional coal mine safety supervision (CMSS) in China has suffered from the problems of power-seeking, excessive resource consumption and poor timeliness. This paper aims to explore the Internet+ CMSS mode being emerged in China.

The evolution of CMSS systems underwent comprehensive scrutiny through a blend of qualitative and quantitative approaches. First, evolutionary game theory was used to analyze the necessity of incorporating Internet+ technology. Second, a system dynamics model of Internet+ CMSS was crafted, encompassing a system flow diagram and equations for various variables. The model was subsequently simulated by taking the W coal mine in Shanxi Province as a representative case study.

It was revealed that the expected safety profit from the Internet+ mode is 296.03% more than that from the conventional mode. The precise dissemination of law enforcement information was identified as a pivotal approach through which the Internet+ platform served as a conduit to foster synergistic collaboration among diverse elements within the system.

The outcomes of this study not only raise awareness about the potential of Internet+ technology in safety supervision but also establish a vital theoretical foundation for enhancing the efficacy of the Internet+ CMSS mode. The significance of these findings extends to fostering the wholesome and sustainable progress of the coal mining industry.

This research stands out as one of the limited studies that delve into the influence of Internet+ technology on CMSS. Building upon the pivotal approach identified, to the best of authors’ knowledge, a novel “multi-blind” working mechanism for Internet+ CMSS is introduced for the first time.

Temperature anomalies in the upper troposphere have become a reality as a result of global warming, which has a noticeable impact on aircraft performance. The purpose of this study is to investigate the total air temperature (TAT) anomaly observed during the cruise level and its impact on engine parameter variations.

Empirical methodology is used in this study, and it is based on measurements and observations of anomalous phenomena on the tropopause. The primary data were taken from the Boeing 747-8F's enhanced flight data recorder, which refers to the quantitative method, while the qualitative method is based on a literature review and interviews. The GEnx Integrated Vehicle Health Management system was used for the study's evaluation of engine performance to support the complete range of operational priorities throughout the entire engine lifecycle.

The study's findings indicate that TAT and SAT anomalies, which occur between 270- and 320-feet flight level, have a substantial impact on aircraft performance at cruise altitude and, as a result, on engine parameters, specifically an increase in fuel consumption and engine exhaust gas temperature values. The TAT and Ram Rise anomalies were the focus of the atmospheric deviations, which were assessed as major departures from the International Civil Aviation Organizations–defined International Standard Atmosphere, which is obvious on a positive tendency and so goes against the norms.

Necessary fixed flight parameters gathered from the aircraft's enhanced airborne flight recorder (EAFR) via Aeronautical Radio Incorporated (ARINC) 664 Part 7 at a certain velocity and altitude interfacing with the diagnostic program direct parameter display (DPD), allow for analysis of aircraft performance in a real-time frame. Thus, processed data transmits to the ground maintenance infrastructure for future evaluation and for proper maintenance solutions.

A real-time analysis of aircraft performance is possible using the diagnostic program DPD in conjunction with necessary fixed flight parameters obtained from the aircraft's EAFR via ARINC 664 Part 7 at a specific speed and altitude. Thus, processed data is transmitted to the ground infrastructure for maintenance to be evaluated in the future and to find the best maintenance fixes.

This article explores the impacts of the changing land-use on urban heat island (UHI) in an urban transformation zone in Ankara (Türkiye). Identifying a characteristic rural landscape until the 1950s, the study area experienced a drastic land-use change by razing the fertile landscape of the city and replacing it with a sealed surface. Development of the squatter houses after the 1960s and, subsequently, the implementation of a new housing morphology have introduced new sceneries, scales and surface conditions that make the study area a noteworthy case to analyze.

Regarding the drastic spatio-temporal change of the study area, this research assesses the impacts of the changing land-use on UHI based on three periods. Using 1957, 1991 and 2021 aerial imaginaries and maps, it analyzes the temperature alteration caused by the changing land-use. To do so, different surface types, green patterns and built-up areas have been modeled using Ankara climatic data and transferred to ENVI-Met to calculate the Universal Thermal Climate Index (UTCI) values.

The calculation has been developed over a transect covering an area of 40 m × 170 m, which includes diversity in terms of architecture, landscape and open space elements. To encourage future design strategies, the research findings deliberate into three extents that discuss the lacking climate knowledge in the ongoing urban transformation projects: impervious surface ratio and regional albedo variation, changing aspect ratio and temperature variation at the pedestrian level.

Urban transformation projects, being countrywide operations in Türkiye, need to cover climate-informed design strategies. Herein, the article underlines the critical position of design decisions in forming a climate-informed urban environment. Dwelling on a typical model of housing transformation in Türkiye, the research could trigger climate-informed urban development strategies in the country.

To investigate the mechanical properties of geopolymer concrete at elevated temperatures.

The investigation involved studying the influence of partially replacing fly ash with ground granulated blast furnace slag (GGBS) at different proportions (5%, 10%, 15%, 20% and 25%) on the composition of the geopolymer. This approach aimed to examine how the addition of GGBS impacts the properties of the geopolymer material. The chemical NaOH was purchased from the local supplier of Jamshedpur. The alkali solution was prepared with a concentration of 12 M NaOH to produce the concrete. After several trials, the alkaline-to-binder ratio was determined to be 0.43.

The compressive strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 35.42 MPa, 41.26 MPa, 44.79 MPa, 50.51 MPa and 46.33 MPa, respectively. The flexural strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 5.31 MPa, 5.64 MPa, 6.12 MPa, 7.15 MPa and 6.48 MPa, respectively. The split tensile strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 2.82 MPa, 2.95 MPa, 3.14 MPa, 3.52 MPa and 3.31 MPa, respectively.

This approach allows for the examination of how the addition of GGBS affects the properties of the geopolymer material. Four different temperature levels were chosen for analysis: 100 °C, 300 °C, 500 °C and 700 °C. By subjecting the geopolymer samples to these elevated temperatures, the study aimed to observe any changes in their mechanical.